text:
@inproceedings{DBLP:conf/sac/AmadiniGM14,
  author    = {Roberto Amadini and
               Maurizio Gabbrielli and
               Jacopo Mauro},
  title     = {An enhanced features extractor for a portfolio of constraint solvers},
  booktitle = {Symposium on Applied Computing, {SAC} 2014, Gyeongju, Republic of
               Korea - March 24 - 28, 2014},
  pages     = {1357--1359},
  year      = {2014},
  url       = {http://doi.acm.org/10.1145/2554850.2555114},
  doi       = {10.1145/2554850.2555114},
  timestamp = {Sun, 20 Jul 2014 11:32:29 +0200},
  biburl    = {http://dblp.uni-trier.de/rec/bib/conf/sac/AmadiniGM14},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}

@article{DBLP:journals/tplp/AmadiniGM14,
  author    = {Roberto Amadini and
               Maurizio Gabbrielli and
               Jacopo Mauro},
  title     = {{SUNNY:} a Lazy Portfolio Approach for Constraint Solving},
  journal   = {{TPLP}},
  volume    = {14},
  number    = {4-5},
  pages     = {509--524},
  year      = {2014},
  url       = {http://dx.doi.org/10.1017/S1471068414000179},
  doi       = {10.1017/S1471068414000179},
  timestamp = {Mon, 11 Aug 2014 11:04:57 +0200},
  biburl    = {http://dblp.uni-trier.de/rec/bib/journals/tplp/AmadiniGM14},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}


text:
@article{kendall-mrav-420-11-2016,
 abstract = {Continental rifting has a fundamental role in the tectonic
behaviour of the Earth, shaping the surface we live on. Although
there is not yet a consensus about the dominant mechanism for
rifting, there is a general agreement that the stresses required
to rift the continental lithosphere are not readily available.
Here we use a global finite element model of the lithosphere to
calculate the stresses acting on Africa. We consider the stresses
induced by mantle flow, crustal structure and topography in two
types of models: one in which flow is exclusively driven by the
subducting slabs and one in which it is derived from a shear wave
tomographic model. The latter predicts much larger stresses and a
more realistic dynamic topography. It is therefore clear that the
mantle structure beneath Africa plays a key part in providing the
radial and horizontal tractions, dynamic topography and
gravitational potential energy necessary for rifting.
Nevertheless, the total available stress (c. 100 MPa) is much less
than that needed to break thick, cold continental lithosphere.
Instead, we appeal to a model of magma-assisted rifting along
pre-existing weaknesses, where the strain is localized in a narrow
axial region and the strength of the plate is reduced
significantly. Mounting geological and geophysical observations
support such a model.},
 author = {John-Michael Kendall and Carolina Lithgow-Bertelloni},
 entrydate = {2020/07/13},
 journal = {Magmatic Rifting Active Volcanism},
 pages = {11--30},
 title = {Why is Africa rifting?},
 volume = {420},
 year = {2016}
}

license: MIT

repository: xiyuanbao/kgb

license_type: permissive

repo_name: xiyuanbao/kgb

branch_name: refs/heads/master

extension: bib


text:
file(REMOVE_RECURSE
  "CMakeFiles/string_libcxx_capacity_resize_size_char.dir/libcxx/basic_string/string.capacity/resize_size_char.pass.cpp.o"
  "string_libcxx_capacity_resize_size_char.pdb"
  "string_libcxx_capacity_resize_size_char"
)

# Per-language clean rules from dependency scanning.
foreach(lang CXX)
  include(CMakeFiles/string_libcxx_capacity_resize_size_char.dir/cmake_clean_${lang}.cmake OPTIONAL)
endforeach()

repository: urcs-sync/Montage

repo_name: urcs-sync/Montage

gha_license_id: NOASSERTION

extension: cmake


text:
SUMMARY = "Memory Efficient Serialization Library - Python3 Modules"
HOMEPAGE = "https://github.com/google/flatbuffers"
SECTION = "console/tools"
LICENSE = "Apache-2.0"
LIC_FILES_CHKSUM = "file://../LICENSE;md5=3b83ef96387f14655fc854ddc3c6bd57"

require flatbuffers.inc

S = "${WORKDIR}/git/python"

RDEPENDS:${PN} = "flatbuffers"

inherit setuptools3

BBCLASSEXTEND = "native"

repository: openembedded/meta-openembedded

repo_name: openembedded/meta-openembedded

gha_license_id: MIT

gha_language: BitBake

extension: bb


text:
@article{leydesdorff_routine_2012,
	title = {A Routine for Measuring Synergy in University-Industry-Government Relations: Mutual Information as a Triple-Helix and Quadruple-Helix Indicator},
	shorttitle = {A Routine for Measuring Synergy in University-Industry-Government Relations},
	url = {http://arxiv.org/abs/1211.7230},
	abstract = {Mutual information in three (or more) dimensions can be considered as a Triple-Helix indicator of synergy in university-industry-government relations. An open-source routine th4.exe makes the computation of this indicator interactively available at the Internet, and thus applicable to large sets of data. Th4.exe computes all probabilistic entropies and mutual information in two, three, and, if available in the data, four dimensions among, for example, classes such as geographical addresses (cities, regions), technological codes (e.g., {OECD}'s {NACE} codes), and size categories; or, alternatively, among institutional addresses (academic, industrial, public sector) in document sets. The relations between the Triple-Helix indicator -- as an indicator of synergy -- and the Triple-Helix model that specifies the possibility of feedback by an overlay of communications, are also discussed.},
	urldate = {2014-02-27},
	journal = {Scientometrics},
        pages = {27-35},
        volume = {99},
        number = {1},
	author = {Leydesdorff, Loet and Park, Han Woo and Lengyel, Balazs},
	year = {2014},
	keywords = {Computer Science - Computers and Society},
	annote = {Comment: submitted to a special issue of Scientometrics entitled "Mapping Triple Helix Innovation for Developing and Transitional Economies: Webometrics, Scientometrics, and Informetrics"},
	file = {1211.7230 PDF:/Users/matthijsdenbesten/Library/Application Support/Firefox/Profiles/6cp3m47y.default/zotero/storage/ZWCFFG3X/Leydesdorff et al. - 2012 - A Routine for Measuring Synergy in University-Indu.pdf:application/pdf;arXiv.org Snapshot:/Users/matthijsdenbesten/Library/Application Support/Firefox/Profiles/6cp3m47y.default/zotero/storage/BWXWJDFR/1211.html:text/html}
}

@Manual{Rcore,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2012},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org/},
  }

@Manual{entropy,
    title = {entropy: Entropy and Mutual Information Estimation},
    author = {Jean Hausser and Korbinian Strimmer},
    year = {2013},
    note = {R package version 1.1.8},
    url = {http://CRAN.R-project.org/package=entropy},
  }


text:
competition|dog|nn
events|national|mod
national|and|punc
national|international|conj
competition|events|in
is|entertainment|pred
competitions|business|mod
attract|competitions|subj
contestants|numerous|mod
attract|contestants|obj
contestants|and|punc
contestants|visitors|conj
visitors|israel|in
israel|dog|appo
outshone|briefly|mod-before
outshone|contest|subj
election|general|nn
outshone|election|obj
known|uprising|subj
dog|one|nn
owners|dog|of
embroiled|owners|obj
suit|law|nn
embroiled|suit|in
over|whether|c
retired|dog|obj
artist|manhattan|nn
weimaraners|artist|gen
served as|weimaraners|subj
served as|models|obj
work|his|gen
models|work|for
be|sesame street dog|on
be|lucrative|pred
is|high|pred
are|long|pred
are|bill mcfadden|according to
handler|professional|mod
handler|dog|nn

branch_name: refs/heads/main

gha_language: Jupyter Notebook

extension: be


text:
@article{OderskyBLBMS18popl,
  author =       {Odersky, Martin and
                  Blanvillain, Olivier and
                  Liu, Fengyun and
                  Biboudis, Aggelos and
                  Miller, Heather and
                  Stucki, Sandro},
  title =        {Simplicitly: Foundations and Applications of
                  Implicit Function Types},
  journal =      {Proceedings of the ACM on Programming Languages},
  volume =       {2},
  number =       {{POPL}},
  pages =        {42:1--42:29},
  month =        jan,
  year =         {2018},
  articleno =    {42},
  numpages =     {29},
  url =          {http://doi.acm.org/10.1145/3158130},
  doi =          {10.1145/3158130},
  issn =         {2475-1421},
  publisher =    {ACM},
  address =      {New York, NY, USA},
}


text:
@article{Bae:2017tqn,
 archiveprefix = {arXiv},
 author = {Bae, Kyu Jung and Kamada, Ayuki and Liew, Seng Pei and
Yanagi, Keisuke},
 doi = {10.1103/PhysRevD.97.055019},
 eprint = {1707.02077},
 journal = {Phys. Rev.},
 number = {5},
 pages = {055019},
 primaryclass = {hep-ph},
 reportnumber = {CTPU-17-24, UT-17-24},
 slaccitation = {%%CITATION = ARXIV:1707.02077;%%},
 title = {{Colder Freeze-in Axinos Decaying into Photons}},
 volume = {D97},
 year = {2018}
}


text:
@article{name,
  year = 2016,
  title = {SessionBasedBlah}
}

@inproceedings{ng2014,
  title = "Blah",
  author = "Me",
  booktitle = "ABCD2014"
}

repository: FlamingTempura/bibtex-tidy

repo_name: FlamingTempura/bibtex-tidy

gha_language: TeX


text:
/*
  Flot Line Chart With Facet Panel
*/

.flot-facet-container {
    overflow: hidden;
}

.flot-facet-container .flot-chart-facet-container {
    display: block;
    height: 500px;
}

.flot-facet-container .flot-side-panel {
    height: 500px;
    box-shadow: -5px 0px 12px #ccc;
    border: 1px solid #ddd;
}

.flot-facet-container .flot-side-panel .date-range-label {
    padding: 0;
    margin: 6px 0;
}

.flot-facet-container .flot-side-panel .warning-text {
    color: #ff454f;
    text-align: center;
    margin-top: 10px;
}

.flot-facet-container .flot-side-panel .no-indent {
    padding-left: 0;
}

repository: cmjio/UXAspects

repo_name: cmjio/UXAspects

extension: css


text:
@article{Feng_2010,
  doi = {10.1016/j.bcp.2009.11.016},
  url = {https://doi.org/10.1016\%2Fj.bcp.2009.11.016},
  year = 2010,
  month = {apr},
  publisher = {Elsevier {BV}},
  volume = {79},
  number = {7},
  pages = {1053--1061},
  author = {Qiping Feng and Suda Vannaprasaht and Yi Peng and Susothorn Angsuthum and Yingyos Avihingsanon and Vivien C. Yee and Wichittra Tassaneeyakul and Richard M. Weinshilboum},
  title = {Thiopurine S-methyltransferase pharmacogenetics: Functional characterization of a novel rapidly degraded variant allozyme},
  journal = {Biochemical Pharmacology}
}

repository: larmcr/px

repo_name: larmcr/px


text:
/* TODO: collapse to icon */
pre {
  max-height: 10em;
  min-width: 10em;
  max-width: 30em;
  overflow-y: auto;
  overflow-x: auto;
  font-size: 80%;
  border: none;
  padding: 0;
  margin: 0;
  background-color: transparent;
  box-shadow: none;
  white-space: pre;
}

:host > div {
  max-height: 6em;
  overflow-y: auto;
}

:host > div.leaf-content-type-object {
  max-height: 15em;
}

:host > div.leaf-content-type-image {
  max-height: 10em;
  max-width: 10em;
}

.leaf-content-type-image img {
  max-width: 100%;
  max-height: 100%;
}

object {
  max-width: 20em;
  min-height: 10px;
}

.list-group-item {
  padding: 5px;
  background: #F3F3F3;
  clear: both;
}

.show-object {
  border: none;
  background: transparent;
  padding: 0;
}

.leaf-seed-link a {
  display: inline-block;
}

.leaf-seed-name {
  min-width: 10em;
}

.leaf-content-type-list > div {
  white-space: pre;
}

.leaf-content-type-counts {
  max-height: 10em;
}

/** .list-group, from Bootstrap */

.list-group {
  padding-left: 0;
  margin-bottom: 20px;
  margin-top: 0;
  max-height: 12em;
  overflow-y: auto;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 5px 10px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-left-radius: 4px;
  border-top-right-radius: 4px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 4px;
  border-bottom-left-radius: 4px;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
a.list-group-item {
  color: #555;
}
a.list-group-item:hover,
a.list-group-item:focus {
  color: #555;
  text-decoration: none;
  background-color: #f5f5f5;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #428bca;
  border-color: #428bca;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #e1edf7;
}

.badge {
  background-color: #ccc;
  border-radius: 10px;
  padding: 0px 10px;
}

repository: hubgit/vege-table

repo_name: hubgit/vege-table


text:
@article{Alvares2016,
 abstract = {Background: Autonomic nervous system (ANS) dysfunction is a putative underlying mechanism for increased cardiovascular disease risk in individuals with psychiatric disorders. Previous studies suggest that this risk may be related to psychotropic medication use. In the present study we systematically reviewed and analyzed published studies of heart rate variability (HRV), measuring ANS output, to determine the effect of psychiatric illness and medication use.

Methods: We searched for studies comparing HRV in physically healthy adults with a diagnosed psychiatric disorder to controls and comparing HRV pre- and post-treatment with a psychotropic medication.

Results: In total, 140 case-control (mood, anxiety, psychosis, dependent disorders, k = 151) and 30 treatment (antidepressants, antipsychotics; k = 43) studies were included. We found that HRV was reduced in all patient groups compared to controls (Hedges g = -0.583) with a large effect for psychotic disorders (Hedges g = -0.948). Effect sizes remained highly significant for medication-free patients compared to controls across all disorders. Smaller and significant reductions in HRV were observed for specific antidepressants and antipsychotics.

Limitations: Study quality significantly moderated effect sizes in case-control analyses, underscoring the importance of assessing methodological quality when interpreting HRV findings.

Conclusion: Combined findings confirm substantial reductions in HRV across psychiatric disorders, and these effects remained significant even in medication-free individuals. Reductions in HRV may therefore represent a significant mechanism contributing to elevated cardiovascular risk in individuals with psychiatric disorders. The negative impact of specific medications on HRV suggest increased risk for cardiovascular disease in these groups, highlighting a need for treatment providers to consider modifiable cardiovascular risk factors to attenuate this risk.},
 author = {Alvares, G. A. and Quintana, D. S. and Hickie, I. B. and Guastella, A. J.},
 copyright = {All rights reserved},
 doi = {10.1503/jpn.140217},
 journal = {Journal of Psychiatry and Neuroscience},
 number = {2},
 pages = {89--104},
 title = {Autonomic Nervous System Dysfunction in Psychiatric Disorders and the Impact of Psychotropic Medications: A Systematic Review and Meta-Analysis},
 url = {https://doi.org/10.1503/jpn.140217},
 volume = {41},
 year = {2016}
}


text:
Automatically generated by Mendeley Desktop 1.19.4
Any changes to this file will be lost if it is regenerated by Mendeley.

BibTeX export options can be customized via Preferences -> BibTeX in Mendeley Desktop

@article{Weston2015,
abstract = {One long-term goal of machine learning research is to produce methods that are applicable to reasoning and natural language, in particular building an intelligent dialogue agent. To measure progress towards that goal, we argue for the usefulness of a set of proxy tasks that evaluate reading comprehension via question answering. Our tasks measure understanding in several ways: whether a system is able to answer questions via chaining facts, simple induction, deduction and many more. The tasks are designed to be prerequisites for any system that aims to be capable of conversing with a human. We believe many existing learning systems can currently not solve them, and hence our aim is to classify these tasks into skill sets, so that researchers can identify (and then rectify) the failings of their systems. We also extend and improve the recently introduced Memory Networks model, and show it is able to solve some, but not all, of the tasks.},
archivePrefix = {arXiv},
arxivId = {1502.05698},
author = {Weston, Jason and Bordes, Antoine and Chopra, Sumit and Rush, Alexander M. and van Merri{\"{e}}nboer, Bart and Joulin, Armand and Mikolov, Tomas},
doi = {10.1016/j.jpowsour.2014.09.131},
eprint = {1502.05698},
file = {:Users/sepmein/Qsync/Papers/Weston et al.{\_}2015{\_}Towards AI-Complete Question Answering A Set of Prerequisite Toy Tasks.pdf:pdf},
isbn = {1502.05698},
issn = {03787753},
title = {{Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks}},
url = {http://arxiv.org/abs/1502.05698},
year = {2015}
}

license: Unlicense

repository: sepmein/references

repo_name: sepmein/references


text:
@article{balduzzi_how_2019,
 abstract = {Objective Meta-analysis is of fundamental importance to obtain an unbiased assessment of the available evidence. In general, the use of meta-analysis has been increasing over the last three decades with mental health as a major research topic. It is then essential to well understand its methodology and interpret its results. In this publication, we describe how to perform a meta-analysis with the freely available statistical software environment R, using a working example taken from the field of mental health.
Methods R package meta is used to conduct standard meta-analysis. Sensitivity analyses for missing binary outcome data and potential selection bias are conducted with R package metasens. All essential R commands are provided and clearly described to conduct and report analyses.
Results The working example considers a binary outcome: we show how to conduct a fixed effect and random effects meta-analysis and subgroup analysis, produce a forest and funnel plot and to test and adjust for funnel plot asymmetry. All these steps work similar for other outcome types.
Conclusions R represents a powerful and flexible tool to conduct meta-analyses. This publication gives a brief glimpse into the topic and provides directions to more advanced meta-analysis methods available in R.},
 author = {Balduzzi, Sara and Rücker, Gerta and Schwarzer, Guido},
 date = {2019-11-01},
 doi = {10.1136/ebmental-2019-300117},
 issn = {1362-0347, 1468-960X},
 journaltitle = {Evidence-Based Mental Health},
 langid = {english},
 note = {Publisher: Royal College of Psychiatrists
Section: Statistics in practice},
 number = {4},
 pages = {153--160},
 pmid = {31563865},
 rights = {© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.},
 shorttitle = {How to perform a meta-analysis with R},
 title = {How to perform a meta-analysis with R: a practical tutorial},
 url = {https://ebmh.bmj.com/content/22/4/153},
 urldate = {2021-03-11},
 volume = {22}
}


text:
@inproceedings {type-your-key-here,
  author = "Mário Torres and Uirá Kulesza and Rosana Braga and Paulo Masiero and Paulo Pires and Élder Cirilo and Thaís Batista and Paulo Borba and Carlos Lucena",
  booktitle = "1st Brazilian Workshop on Model-Driven Development (BW-MDD 2010), associado ao Primeiro Congresso Brasileiro de Software: Teoria e Prática (CBSoft 2010)",
  title = "Estudo Comparativo de Ferramentas de Derivação Dirigidas por Modelos: Resultados Preliminares",
  year = "2010",
  pages = "1-8"
}

repository: pauloborba/academic-kickstart

repo_name: pauloborba/academic-kickstart


text:
*{
    box-sizing: border-box;
}

html, body{
    font-family: 'Source Sans Pro', sans-serif;
    margin: 0;
    padding: 0;
}
.sec::before{
    content: "";
    height: 50px;
    display: block;
}
.container{
    padding: 5px;
    min-height: 100px;
    position: relative;
    margin: 0 auto;
}
.container img{
    max-width: 100%;
}
.container h2{
    text-align: center;
    text-transform: uppercase;
   background-color: black;
    color: white;
    font-size: 3em;
}
.col {
    float: left;
   position: relative;
   padding: 5px;
}
.card{
    border: 1px solid #222;
    border-radius: 20px;
    padding: 10px;
    background-color: white;
    text-align: center;
}
.col-4{
    width: 25%;
}
.col-3{
    width: 33.3%;
}
.col-2{
    width: 50%;
}
.col-1{
    width: 100%;
    margin: auto;
    text-align: center;
}
.box{
    background-color: white;
    border-radius: 15px;
    margin: 10px;
    border: 1px solid #ddd;
    padding: 10px;
}
.box .content{
    padding: 10px;
    font-size: 1.4em;
}
.box .content::first-letter{
    font-size: 2em;
}

.box header{
    background-color: #333;
    text-transform: uppercase;
    text-align: center;
    color: white;
    line-height: 45px;
    font-size: 2em;
}

.box footer{
    background-color: #ddd;
    text-align: center;
    color: white;
    line-height: 45px;
    font-size: 1.2em;
}
input[type=text], input[type=email], textarea{
    width: 100%;
    padding: 10px;
    border: 1px solid #ccc;
    border-radius: 5px;
    margin-bottom: 10px;
}
.mainForm{
    padding: 25px;
    background: #333;
    color: white;
    width: 50%;
    margin: auto;
    border: 1px solid #333;
    border-radius: 10px;
}
.btn {
    background-color:#ddd;
    color:#222;
    font-size: 2em;
    padding:10px;
    border-radius: 10px;
    cursor: pointer;
}
.btn:hover{
    background-color:#ededed;
}
label{
    text-align: left;
    margin: 10px 0;
    display: block;
}

#message{
    height: 150px;
}
#footer{
    background-color: black;
    color:white;
    min-height: 200px;
    padding: 20px;
    display: block;
    overflow: hidden;
}
.bottom h3{
    text-align: center;
    text-transform: uppercase;
    font-size: 1.8em;
    border-bottom: 1px solid #ddd;
    padding: 20px;
}
.bottom p{
    text-align: center;
    font-size: 1em;
}
.hero{
    color:white;
    font-size: 1.5em;
    background-color: #222;
    text-align: center;
    padding:20px;
}
.hero h1{
    font-size: 3em;
}
.hero h2{
    font-size: 2em;
}
.header{
    height: 100px;
}
.section{
    clear: both;
    border: 1px solid#ddd;
    padding: 20px 0;
    background-color: #eee;
    height: auto;
    overflow: hidden;
}
.logo{
    float: left;
    background-color: blue;
    color: white;
    width: 200px;
    height: 50px;
    margin-left: 10px;
    text-align: center;
    line-height: 50px;
}

nav ul{
    float: right;
    list-style: none;
    margin: 0;
    padding: 0;

}

nav ul li{
    float: left;
    position: relative;
}
 nav ul li a{
     padding: 15px;
     text-decoration: none;
     color: white;
     font-size: 1.5em;
 }

 nav ul li:hover a{
     background-color: white;
     color: black;
 }

 .mainHeader{
     position: fixed;
     left: 0;
     top: 0;
     height: 100px;
     background-color: #000;
     width: 100%;
     z-index: 10;
     padding: 5px;
 }

 @media all and (max-width:760px){
    .mainHeader{
        height: auto;
    }
    .logo{
        float: none;
        margin: 10px auto 20px;
        display: block;
    }

    nav ul{
        float: none;
        display: block;
        margin: 0 auto;
        text-align: center;
    }
    nav ul li{
        float: initial;
        display: inline-block;
    }
    nav ul li a{
        padding: 0 15px;
    }
    .col-4{
        width: 100%;
    }
 }

 @media all and (max-width:600px){
     .col-3, .col-2{
        width: 100%;
        margin: auto;
        text-align: center;

     }
     .mainForm{
        width: 100%;
     }
 }


text:
@inproceedings{eusipco22,
 address = {Belgrade},
 author = {M. van den Ende and A. Ferrari and  A. Sladen and C. Richard},
 booktitle = {European Signal Processing Conference (EUSIPCO)},
 month = {August},
 title = {Deep Deconvolution Applied to Distributed Acoustic Sensing for Traffic Analysis},
 year = {2022}
}

repository: andferrari/academic-kickstart

repo_name: andferrari/academic-kickstart


text:
include(RunCMake)

run_cmake(CMP0078-WARN)
run_cmake(CMP0078-OLD)
run_cmake(CMP0078-NEW)

repository: crouchingtigre/turicreate

repo_name: crouchingtigre/turicreate


text:
@inproceedings{Chen2009,
 abstract = {Biomedical images and captions are one of the major sources of information in online biomedical publications. They often contain the most important results to be reported, and provide rich information about the main themes in published papers. In the data mining and information retrieval community, there has been much effort on using text mining and language modeling algorithms to extract knowledge from the text content of online biomedical publications; however, the problem of knowledge extraction from biomedical images and captions has not been fully studied yet. In this paper, a hierarchical probabilistic topic model with background distribution (HPB) is introduced to uncover the latent semantic topics from the co-occurrence patterns of caption words, visual words and biomedical concepts. With downloaded biomedical figures, restricted captions are extracted with regard to each individual image panel. During the indexing stage, the 'bag-of-words' representation of captions is supplemented by an ontology-based concept indexing to alleviate the synonym and polysemy problems. As the visual counterpart of text words, the visual words are extracted and indexed from corresponding image panels. The model is estimated via collapsed Gibbs sampling algorithm. We compare the performance of our model with the extension of the Correspondence LDA (Corr-LDA) model under the same biomedical image annotation scenario using cross-validation. Experimental results demonstrate that our model is able to accurately extract latent patterns from complicated biomedical image-caption pairs and facilitate knowledge organization and understanding in online biomedical literatures. Copyright 2009 ACM.},
 author = {Chen, Xin and Lu, Caimei and An, Yuan and Achananuparp, Palakorn},
 booktitle = {Proceedings of the 18th ACM international conference on Information and knowledge management - CIKM '09},
 doi = {10.1145/1645953.1646017},
 isbn = {9781605585123},
 keywords = {Automatic image annotation,Bioinformatics,Gibbs sampling,Probabilistic models,Topic learning,Visual words},
 title = {Probabilistic models for topic learning from images and captions in online biomedical literatures},
 year = {2009}
}

repository: aekpalakorn/academic-kickstart

repo_name: aekpalakorn/academic-kickstart


text:
@Article{,
  author                = {Clerx, Michael and Cooling, Michael T and Cooper, Jonathan and Garny, Alan and Moyle, Keri and Nickerson, David P and Nielsen, Poul M F and Sorby, Hugh},
  journal               = {Journal of integrative bioinformatics},
  journal-abbreviation  = {J Integr Bioinform},
  title                 = {CellML 2.0.},
  year                  = {2020},
  issn                  = {1613-4516},
  month                 = jul,
  volume                = {17},
  abstract              = {Following are examples of MathML elements:  ${\eta }_{p}^{2}$  $\infty $  $\begin{pmatrix}0 & 1 & 0\\ 0 & 0 & 1\\ 1 & 0 & 0\end{pmatrix}$  $17+29i\in \mathbb{C}$  $\left(a,b,c\right)\left(abc\right)\left|a,b,c\right>$  $\sum _{i=1}^{n}\left({a}_{i}\right)$  $\underset{a}{\overset{b}{\int }}\left(5x+2\mathrm{sin}\left(x\right)\right)\mathrm{dx}$  $\frac{a+1}{b}$  $y=\sqrt[3]{{x}^{2}}$  $\mathrm{det A}=\left|\begin{array}{cccc}{a}_{11}& {a}_{12}& \dots & {a}_{1n}\\ & ⋮\\ {a}_{j1}& {a}_{j2}& \dots & {a}_{jn}\\ & ⋮\\ {a}_{k1}& {a}_{k2}& \dots & {a}_{kn}\\ & ⋮\\ {a}_{n1}& {a}_{n2}& \dots & {a}_{nn}\end{array}\right|$  $\stackrel{\to }{v}=\left({v}_{1},{v}_{2},{v}_{3}\right)$},
  citation-subset       = {IM},
  completed             = {2021-04-27},
  country               = {Germany},
  doi                   = {10.1515/jib-2020-0021},
  issn-linking          = {1613-4516},
  issue                 = {2-3},
  keywords              = {Computer Simulation; Models, Biological; Models, Theoretical; Software; computational physiology; modularity; physiome project; reproducibility; reusability},
  nlm-id                = {101503361},
  status                = {MEDLINE},
  owner                 = {NLM},
  pii                   = {20200021},
  pmc                   = {PMC7756617},
  pmid                  = {32759406},
  pubmodel              = {Electronic},
  pubstate              = {epublish},
  revised               = {2021-05-06},
}

repository: JabRef/jabref

repo_name: JabRef/jabref

gha_language: Java


text:
DESCRIPTION = "etk SHR theme"
LICENSE = "MIT BSD"
PV = "1.1.1-${EFL_SRCREV}+gitr${SRCREV}"
PR = "r2"

SRC_URI = "git://git.shr-project.org/repo/shr-themes.git;protocol=http;branch=master"

require etk-theme.inc

repository: demsey/openembedded

repo_name: demsey/openembedded

branch_name: HEAD


text:
body {
  font-family:  'Open Sans Condensed', sans-serif;;
  /* padding: 20px 60px; from clothing scss*/
  padding: .5em;
}

a {
  text-decoration: none;
  color: black;
}

* {
  box-sizing: border-box;
}

/* .App {
  text-align: center;
  font-family: 'Open Sans', sans-serif;
} */

/* .center {
  display: flex;
  justify-content: center;
} */

repository: kcrites/trainingtracker

repo_name: kcrites/trainingtracker

gha_language: JavaScript


text:
@inproceedings{Briat:10a,
 address = {Atlanta, GA, USA},
 author = {C. Briat and H. Hjalmarsson and G. Karlsson and K. H. Johansson and U. T. Jönsson and H. Sandberg},
 booktitle = {Proceedings 49th IEEE Conference on Decision and Control},
 title = {Nonlinear State-Dependent Delay Modeling and Stability Analysis of Internet Congestion Control},
 year = {2010}
}

repository: hhjalmars/academic-kickstart

repo_name: hhjalmars/academic-kickstart


text:
@book{khalil2002nonlinear,
  title={Nonlinear systems},
  author={Khalil, Hassan K and Grizzle, Jessy W},
  volume={3},
  year={2002},
  publisher={Prentice hall Upper Saddle River, NJ}
}
@article{bernat2015multi,
  title={Multi-modelling as new estimation schema for high-gain observers},
  author={Bernat, Jakub and Stepien, Slawomir},
  journal={International Journal of Control},
  volume={88},
  number={6},
  pages={1209--1222},
  year={2015},
  publisher={Taylor \& Francis}
}
@article{pasand2019luenberger,
  title={Luenberger-Type Cubic Observers for State Estimation of Linear Systems},
  author={Pasand, Mohammad Mahdi Share},
  journal={arXiv preprint arXiv:1909.11978},
  year={2019}
}
@article{gautheir1992simple,
  title={A simple observer for nonlinear systems application to bioreactors},
  author={Gautheir, JP and Hammouri, H and Othman, S},
  journal={IEEE Transactions on Automatic Control},
  volume={37},
  number={6},
  pages={875--880},
  year={1992}
}
@article{ciccarella199310,
  title={10.1080/00207179308934406},
  author={Ciccarella, G and Mora, M Dalla and Germani, A},
  journal={Internat. J. Control},
  volume={57},
  number={3},
  pages={537--556},
  year={1993}
}
@article{hadj2001estimation,
  title={Estimation of uncertain models of activated sludge processes with interval observers},
  author={Hadj-Sadok, MZ and Gouz{\'e}, JL},
  journal={Journal of Process Control},
  volume={11},
  number={3},
  pages={299--310},
  year={2001},
  publisher={Elsevier}
}
@article{vinodh2013comparison,
  title={Comparison of four state observer design algorithms for MIMO system},
  author={Vinodh, Kumar E and Jovitha, Jerome and Ayyappan, S},
  journal={Archives of Control Sciences},
  volume={23},
  year={2013}
}

path: /student_lecture_notes/state observer (Fadi Younes)/ref_observer.bib


text:
@THESIS{Skvortsov:2008,
  title        = {Флуктуационные и интерференционные эффекты в мезоскопических системах},
  author       = {Скворцов, Михаил Андреевич},
  type         = {docthesis},
  _year         = {2008},
  institution  = {ИТФ им. Л.\,Д.~Ландау},
  langid       = {russian},
  language     = {russian},
  location     = {Черноголовка},
  speciality     = {физ.-мат. наук},
  specialitycode = {01.04.02},
  media        = {text},
  pagetotal    = {224},
}


text:
@InProceedings{cotter16,
  author = {Cotter, Andrew and Gupta, Maya and Pfeifer, Jan},
  title = {A Light Touch for Heavily Constrained SGD},
  pages = {729-771},
  abstract = {Minimizing empirical risk subject to a set of constraints can be a
useful strategy for learning restricted classes of functions, such as monotonic
functions, submodular functions, classifiers that guarantee a certain class
label for some subset of examples, etc. However, these restrictions may result
in a very large number of constraints. Projected stochastic gradient descent
(SGD) is often the default choice for large-scale optimization in machine
learning, but requires a projection after each update. For heavily-constrained
objectives, we propose an efficient extension of SGD that stays close to the
feasible region while only applying constraints probabilistically at each
iteration. Theoretical analysis shows a compelling trade-off between
per-iteration work and the number of iterations needed on problems with a large
number of constraints.},
}

repository: mreid/papersite

repo_name: mreid/papersite


text:
@article{melymcb-0113,
 author = {Scalise, O.H.},
 document_type = {Article},
 doi = {10.1016/j.fluid.2005.08.007},
 journal = {Fluid Phase Equilibria},
 note = {cited By 1},
 number = {1-2},
 pages = {31-39},
 source = {Scopus},
 title = {On the phase equilibrium of atomic and molecular pure fluids from thermodynamic perturbation theory},
 url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-26444433205&doi=10.1016%2fj.fluid.2005.08.007&partnerID=40&md5=8ff49880b51d660c8c3b797410381a53},
 volume = {237},
 year = {2005}
}


text:
/* ==UserStyle==
@name           Youla FullBlack
@namespace      USO Archive
@author         Justonsant ³
@description    `Полностью чёрный стиль для Youla FullBlack style for YoulaО багах сообщите мне:https://vk.com/justonsant`
@version        2020727.14.20
@license        CC0-1.0
@preprocessor   uso
==/UserStyle== */
@-moz-document url-prefix("https://youla.ru"), url-prefix("https://auto.youla.ru"), url-prefix("https://realty.youla.ru/"), url-prefix("https://youla.ru/im"), domain("youla.ru"), domain("auto.youla.ru"), domain("realty.youla.ru") {
/*27.7.20*/
html {filter:invert(100%); background-color:#0f0f0f;}
    body {background-color:#fff;}
.sc-psrQp {filter:invert(100%);} /*ава*/
.sc-qPlga {filter:invert(100%);} /*ава п*/
.sc-pkDYi.dPCKcD {filter:invert(100%);}
.sc-pBolk.fTkEkl {filter:invert(100%);}
.sc-qPkqk.gwrbDt {filter:invert(100%);}

/*24/06/2020
.top_banner, .mrg-banner-container, .banners_rotator_container--desktop, .social_block, .sc-jRYpxy.eDMYZv, .sc-jSglzX.kYupqH{display:none;}
.logo, .HeaderYOULA_logoYoula__3aE8K{background: url("https://cdn.rawgit.com/xob0t/226be68d6ce368c25c8fd575d0334af7/raw/47c0a23088aaf678a331415cc32c21f1633ffea0/youla.logo.white.svg") no-repeat;}
input, textarea, .gkfaWj .Select div, .page_title .Select--single .suggest_list, .suggest_list__item, .form_control--select>.Select-control, .Select span, .modal_map__content, .list--data .list__wrapper, .c_subject_dropdown__list li button, .c_subject_dropdown__list li a, .order__QeK1j0d_, .product__2oLb4nXl, .summary__1jd0id8q, .modal_tel .modal__inner, .fkuSKM:hover{background-color:#222!important;color:white!important;}
::-webkit-scrollbar,::-webkit-scrollbar-corner {background: #000;width: 14px;height: 14px;}
.sc-qYtkq {background: #000 !important;color:#FFF !important}
.sc-qQKBW {background: #000 !important;color:#FFF !important}
.sc-pZcYF {background: #000 !important;color:#FFF !important}
.sc-fzolEj {background: #000 !important;color:#FFF !important}
.sc-fzpkqZ {background: #000 !important;color:#FFF !important}
.sc-pciEQ {background: #000 !important;color:#FFF !important}
.sc-AxjAm {color:#FFF !important}
.sc-qancl {background: #000 !important;color:#FFF !important}
.gLiaon {background: #000 !important; max-width: 1920px;padding-left:none}
.sc-AxjAm {background: #000 !important;color:#FFF !important}
.sc-qPIWj.lkZjPW {background: #000 !important;color:#FFF !important}
.sc-pBAKv.hqhBQb {background: #000 !important;color:#FFF !important}
.mapboxgl-canvas {filter: invert(100%)!important;}
.sc-pbXLt.fxQuKH {background: #000 !important;color:#FFF !important}
.sc-plVjM {background: #000 !important;color:#FFF !important}
.sc-pRpgy {background: #000 !important;color:#FFF !important}
.sc-fzqAbL {background: #000 !important;color:#FFF !important;}
.frlvqA {background: #000 !important;color:#FFF !important;width: 0%;}
.sc-kjahIM.hsrQvv {background: #000 !important;color:#FFF !important;}
.breadcrumbs.visible-md.visible-lg {background: #000 !important;color:#FFF !important;}
.breadcrumbs_list__item.breadcrumbs_list__item--current {background: #000 !important;color:#FFF !important;}
.sc-oUMOe.sc-pdkfH.cVXNWO {background: #000 !important;color:#FFF !important;}
.sc-qXFOy.sc-pQrUA.sc-pYPmd.fqlqii {background: #000 !important;color:#FFF !important;}
.sc-oUMOe.sc-pdkfH.sc-pDboM.cvLlFX {background: #000 !important;color:#FFF !important;}
.sc-kNYdoZ.iehGOv {background: #000 !important;color:#FFF !important;}
.sc-pAyMl.jtvfva {background: #000 !important;color:#FFF !important;}
.sc-pkURi.dQlsQw {background: #000 !important;color:#FFF !important;}
.sc-oUqyN {background: #000 !important;color:#FFF !important;}
.sc-qYSYK.ifvsRv {background: #000 !important;color:#FFF !important;}
.sc-jCDCQp.jBSeRm {background: #000 !important;color:#FFF !important;}
.sc-jxtrTG {background: #000 !important;color:#FFF !important;}
.sc-psTpt {background: #000 !important;color:#FFF !important;}
.sc-jDcoUE {background: #000 !important;color:#FFF !important;}
.sc-jCKJyL {background: #000 !important;color:#FFF !important;}
.footer {background: #000 !important;color:#FFF !important;}
.body.route__catalog.body--animations {background: #000 !important;color:#FFF !important;}
.sc-jCKJyL {background: #000 !important;color:#FFF !important;}
.sc-pYbQl {background: #000 !important;color:#FFF !important;}
.sc-jHnSRx.iBAvdS {background: #000 !important;color:#FFF !important;}
.sc-jNfkTq {background: #000 !important;color:#FFF !important;}
.sc-jTnOeS {background: #000 !important;color:#FFF !important;}
.sc-jNFcNp {background: #000 !important;color:#FFF !important;}
.sc-kbKqNe {background: #000 !important;color:#FFF !important;}
.sc-pBAKv.sc-kIyqIZ.ixdkvk {background: #000 !important;color:#FFF !important;}
.sc-kNQTFb.sc-jSglzX.jwpAPL {background: #000 !important;color:#FFF !important;}
.sc-pBAKv {background: #000 !important;color:#FFF !important;}
.sc-jTwuPi {background: #000 !important;color:#FFF !important;}
.sc-jCcXib {background: #000 !important;color:#FFF !important;}
.sc-kHzxZO {background: #000 !important;color:#FFF !important;}
.sc-jMNFxx {background: #000 !important;color:#FFF !important;}
.sc-khlcQO {background: #000 !important;color:#FFF !important;}
.sc-pJTpM {background: #000 !important;color:#FFF !important;}
.sc-jSphag {background: #000 !important;color:#FFF !important;}
.sc-pscky.kBPJSk {fill: #000 !important;}
.product_item__title {background: #000 !important;color:#FFF !important;}
.product_item__date {background: #000 !important;color:#FFF !important;}
.product_figure {border-top-color:#000 !important;background: #000 !important;color:#FFF !important;}
.product_item__description {background: #000 !important;color:#FFF !important;}
.sc-jwLFCW.iPQRlV {background: #000 !important;color:#FFF !important;}
.sc-jHwnSs.dPqiJA {background: #000 !important;color:#FFF !important;}
.sc-kbSmKH.iGxCoX {background: #000 !important;color:#FFF !important;}
.gbNsCT::before {background: #000 !important;color:#FFF !important;}
.ktKuHY::before {background: #000 !important;color:#FFF !important;}
.sc-ptHdI.dtEDoZ {background: #000 !important;color:#FFF !important;}
.sc-pAayJ {background: #000 !important;color:#FFF !important;}
.sc-pbXLt {background: #000 !important;color:#FFF !important;}
.sc-pQQAz {background: #000 !important;color:#FFF !important;}
.sc-pcmTJ {background: #000 !important;color:#FFF !important;}
.sc-pDboM {background: #000 !important;color:#FFF !important;}
.sc-oUmZK {background: #000 !important;color:#FFF !important;}
.sc-jwLvut {background: #000 !important;color:#FFF !important;}
.sc-kcIxiK {background: #000 !important;color:#FFF !important;}
.sc-fzomuh {background: #000 !important;color:#FFF !important;}
.sc-pAkMi {background: #000 !important;color:#FFF !important;}
.sc-jCLxrW {background: #000 !important;color:#FFF !important;}
.sc-qPzgd {background: #000 !important;color:#FFF !important;}
.sc-pZlBu {background: #000 !important;color:#FFF !important;}
.sc-qOvoE {background: #000 !important;color:#FFF !important;}
.Select-multi-value-wrapper {background: #000 !important;color:#FFF !important;}
.Select-menu-outer {background: #000 !important;color:#FFF !important;}
.sc-jxcAmc.kHuFUl {background: #000 !important;color:#FFF !important;}
.sc-jBEKhe {background: #000 !important;color:#FFF !important;}
.sc-pQtXH {background: #000 !important;color:#FFF !important;}
.sc-jTvKhr {background: #000 !important;color:#FFF !important;}
.sc-pIVsU {background: #000 !important;color:#FFF !important;}
.sc-oTaAA {background: #000 !important;color:#FFF !important;}
.sc-fzomME {background: #000 !important;color:#FFF !important;}
.sc-qcpaC {background: #000 !important;color:#FFF !important;}
.sc-ptBBy {background: #000 !important;color:#FFF !important;}
.sc-pAzCb {background: #000 !important;color:#FFF !important;}
.sc-qPJtC {background: #000 !important;color:#FFF !important;}
.sc-qQlyE {background: #000 !important;color:#FFF !important;}
.sc-pAali {background: #000 !important;color:#FFF !important;}
.sc-pQsrT {background: #000 !important;color:#FFF !important;}
.sc-pcYTN {background: #000 !important;color:#FFF !important;}
.sc-kbSNoR {background: #000 !important;color:#FFF !important;}
.sc-jMNSMy {background: #000 !important;color:#FFF !important;}
.sc-jTooJc {background: #000 !important;color:#FFF !important;}
.sc-jXhGnS {background: #000 !important;color:#FFF !important;}
.sc-pQgNC {background: #000 !important;color:#FFF !important;}
.sc-pYcLf {background: #000 !important;color:#FFF !important;}
.sc-pkfPC {background: #000 !important;color:#FFF !important;}
.sc-pdkDa {background: #000 !important;color:#FFF !important;}
.sc-jROQhL {background: #000 !important;color:#FFF !important;}
.sc-qPKZq {background: #000 !important;color:#FFF !important;}
.sc-qXEwl {background: #000 !important;color:#FFF !important;}
.sc-jSgLZl {background: #000 !important;color:#FFF !important;}
.sc-jBFwuJ {background: #000 !important;color:#FFF !important;}
.base {background: #000 !important;color:#FFF !important;}
.sc-pkHCh.yWA-DK {background: #000 !important;color:#FFF !important;}
.payments_container {background: #000 !important;color:#FFF !important;}
.body {background: #000 !important;color:#FFF !important;}
.sc-ptcDc.sc-jWRcat.jCzKSE {background: #000 !important;color:#FFF !important;}
.sc-kjahIM.sc-jxSJjv.fyvDCE {background: #000 !important;color:#FFF !important;}
.sc-pbKro.jgNmvb {background: #000 !important;color:#FFF !important;}
.sc-ptcDc.wjUEF {background: #000 !important;color:#FFF !important;}
.sc-qPYjv.cimeKJ {background: #000 !important;color:#FFF !important;}
.sc-pReKu.dTsFgq {background: #000 !important;color:#FFF !important;}
.sc-pkfsj.bKskNz {background: #000 !important;color:#FFF !important;}
.sc-jxtSxQ.jQbTeE {background: #000 !important;color:#FFF !important;}

*{border-top-color:#000 !important;border-right-color:#000 !important;border-left-color:#000 !important;border-bottom-color:#000 !important;}
.c_message_stack__bubble {background: #000 !important;color:#FFF !important}
.c_message_list__scrollable {background: #000 !important;color:#FFF !important}
.c_subject_product__name {background: #000 !important;color:#FFF !important}
.c_chat_item__wrap {background: #000 !important;color:#FFF !important}
.c_subject__product {background: #000 !important;color:#FFF !important}
.c_create_message__form {background: #000 !important;color:#FFF !important}
.c_create_message__textarea {background: #000 !important;color:#FFF !important}
.gpt_advertisement__inner {background: #000 !important;color:#FFF !important}
.c_notice {background: #000 !important;color:#FFF !important}
._yjs_link-list {background: #000 !important;color:#FFF !important}
.bundle {background: #000 !important;color:#FFF !important;}
.sc-qYGzz.fIlQVX {background: #000 !important;color:#FFF !important;}
.body.body--overflow_hidden.body--im.route__im.body--animations {background: #000 !important;color:#FFF !important;}
.c_message_stack__messages {background: #000 !important;color:#FFF !important;}
.c_message_item__text {background: #000 !important;color:#FFF !important;}
.sc-jybekq {background: #000 !important;color:#FFF !important;}
.sc-kjyuJJ {background: #000 !important;color:#FFF !important;}
.sc-qZqrs {background: #000 !important;color:#FFF !important;}
.sc-qQVqx {background: #000 !important;color:#FFF !important;}
.sc-oTmHo {background: #000 !important;color:#FFF !important;}
.sc-jwUflh {background: #000 !important;color:#FFF !important;}
.sc-jwLFCW {background: #000 !important;color:#FFF !important;}
.sc-jNeAlz {background: #000 !important;color:#FFF !important;}
.sc-kIpRaO {background: #000 !important;color:#FFF !important;}
.sc-kIGLJU {background: #000 !important;color:#FFF !important;}
.sc-jXPivZ {background: #000 !important;color:#FFF !important;}
.sc-jCUVcd {background: #000 !important;color:#FFF !important;}
.sc {background: #000 !important;color:#FFF !important;}*/
}

branch_name: refs/heads/flomaster


text:
.app{
  display: flex;
  flex-direction: column;
  justify-content: space-between;
  background-color: #FAFAFA;
}

#root {
  height: 100%;
  width: 100%;
    background-color: #FAFAFA;
}

a {
  text-decoration: none !important;
  color:none !important;
}
a:visited{
  color: 'white' !important;
}

.router{
  height: auto;
}


text:
@article{MR2806686,
 author = {Fernandez, Isabel and Lopez, Francisco J.},
 doi = {10.1090/S0002-9947-2011-05133-0},
 fjournal = {Transactions of the American Mathematical Society},
 issn = {0002-9947},
 journal = {Trans. Amer. Math. Soc.},
 mrclass = {53A10 (53A35)},
 mrnumber = {2806686},
 mrreviewer = {Fei-Tsen Liang},
 number = {9},
 pages = {4603--4650},
 title = {On the uniqueness of the helicoid and Enneper's surface in
the Lorentz-Minkowski space $\Bbb R^3_1$},
 url = {https://doi.org/10.1090/S0002-9947-2011-05133-0},
 volume = {363},
 year = {2011}
}

repository: torralbofco/geometric-analysis-fork

repo_name: torralbofco/geometric-analysis-fork


text:
@article{Kim-2022-Climate,
    title = "Climate change impact on water supply and hydropower generation potential in Northern Manitoba",
    author = "Kim, Su Jin  and
      Asadzadeh, Masoud  and
      Stadnyk, Tricia A.",
    journal = "Journal of Hydrology: Regional Studies, Volume 41",
    volume = "41",
    year = "2022",
    publisher = "Elsevier BV",
    url = "https://aclanthology.org/G22-82001",
    doi = "10.1016/j.ejrh.2022.101077",
    pages = "101077",
    abstract = "Lower Nelson River Basin, Manitoba, Canada Hydroelectricity makes up almost 97{\%} of electricity generated in Manitoba, of which over 70{\%} of its generation capacity is installed along the Lower Nelson River (LNR). In this study, 19 climate projections representing {\textasciitilde} 87{\%} of climatic variability over Hudson Bay Drainage Basin are applied to coupled hydrologic-operations models to estimate water supply and hydropower generation potential changes under future climates. Future inflow to the forebay of the main hydropower generating stations along LNR is expected to increase in spring and summer but decrease in winter and fall. Consequently, hydropower generation potential is projected to increase for spring, the historical flood season, which may lead to reduced reservoir inflow retention efficiency. In extremely dry climatic simulations, winter seasons see a reduction in reservoir inflow and hydropower generation potential, up to 35{\%} and 37{\%} in 2021{--}2050 and 2041{--}2070, respectively. Projected changes in reservoir inflow and hydropower generation potential continue to diverge over time, with dry scenarios becoming drier and wet becoming wetter, yielding high basin climate sensitivity and uncertainty with system supply and generation potential. Despite the presence of statistically significant individual trends and changes, there is a low agreement within the climate ensemble. Analysis of system robustness shows adjustment of the operations along LNR should be considered over time to better leverage changing seasonal water supply. {\mbox{$\bullet$}} Unique dynamic coupling of climate-hydrologic-operations models. {\mbox{$\bullet$}} Projected reservoir inflow and hydropower generation potential for LNRB. {\mbox{$\bullet$}} No significant change or trend in mean or median values due to uncertainty. {\mbox{$\bullet$}} Wet seasons are getting wetter, dry seasons are getting drier. {\mbox{$\bullet$}} Increase in uncertainty and extremes under future climates poses operational challenge.",
}

repository: gwf-uwaterloo/gwf-publications

repo_name: gwf-uwaterloo/gwf-publications

gha_language: Python


text:
@article{DYNA43195,
author="Zoido, C.
and Maroto, J.
and Romero, G.
and Felez, J.",
title = {MÉTODO DE CORRECCIÓN AUTOMÁTICA DE SISTEMAS DE PROYECCIÓN PANORÁMICOS MULTI-PROYECTOR},
journal = {DYNA Ingenieria e Industria},
volume = {88},
number = {5},
year = {2013},
keywords = {sistemas multi-proyector, edge blending, simulación, gráficos por computador, proyección panorámica, multi-projector displays, edge blending, simulation, computer graphics, panoramic projection},
abstract = {RESUMEN: En el presente artículo se describe un método sencillo y novedoso para calibrar sistemas de proyección panorámicos formados por la composición de las imágenes de varios proyectores. Este tipo de sistemas de proyección tienen multitud de aplicaciones en campos  como la simulación, el entretenimiento, el marketing y la visualización de datos. El método de corrección hace uso de una cámara convencional que puede girar en torno a su eje vertical para captar la totalidad de la superficie de proyección. Sobre esta superficie de proyección cada proyector emite patrones de luz estructurada que permiten relacionar las imágenes emitidas por el proyector con las captadas por la cámara. Gracias a que la cámara experimenta solo una transformación de rotación pura entre vistas se pueden relacionar unas vistas con otras mediante el uso de técnicas de composición de fotografía panorámica. Estás técnicas de composición permiten el establecer un sistema de referencia común para todos los proyectores donde realizar la corrección de manera sencilla. Una vez se han establecido relaciones de transformación entre los elementos del sistema se pueden corregir las imágenes parciales para que la imagen final parezca emitida por un único proyector. Además, la aplicación de modelos de Bezier para definir las zonas de proyección de cada proyector permiten que se pueda emplear una cámara sin calibración previa. La principal aportación de este estudio es la aplicación de técnicas de composición fotográfica a sistemas multi-proyector lo que permite una corrección más sencilla que con métodos anteriores. La validación del método de corrección descrito se validará aplicando la metodología a un sistema de proyección panorámico formado por cinco proyectores. },
issn = {1989-1490},
url = {http://dx.doi.org/10.6036/5713},
doi = {10.6036/5713},
pages = {536--542}
}

@Article{Zoido2013,
author="Zoido, C.
and Maroto, J.
and Romero, G.
and Felez, J.",
title="Optimized methods for multi-projector display correction",
journal="International Journal on Interactive Design and Manufacturing (IJIDeM)",
year="2013",
month="Feb",
day="01",
volume="7",
number="1",
pages="13--25",
abstract="Multi-projector displays are commonly used for a wide range of applications such as virtual reality systems, simulators or data visualization where a high resolution image over a large projection surface is required. Such systems are cheap for the resolutions they can provide, can be configured to project images on almost any kind of screen shapes and are easily scalable, but in order to provide a seamless image with no photometric discontinuities they require a precise geometric and colour correction. In this paper, we propose a series of optimization techniques for large projection displays which make the adjustment procedure simpler and faster. Calibration method uses commercial off-the-shelf equipment such as a webcam and an intermediate performance graphics card. Multiple views are used if one camera image can't cover the entire display with enough resolution. The effect of these optimizations in the calibration of a simulated display formed by 48 projectors are shown.",
issn="1955-2505",
doi="10.1007/s12008-012-0161-0",
url="https://doi.org/10.1007/s12008-012-0161-0"
}

@INPROCEEDINGS{6131254,
author={C. Zoido and J. Maroto and G. Romero and J. Felez},
booktitle={2011 UKSim 5th European Symposium on Computer Modeling and Simulation},
title={Tiled Projector Displays Correction for Dark Scenes in Railway Simulators},
year={2011},
volume={},
number={},
pages={317-322},
abstract={Tiled projector displays are a common choice for training simulators, where a high resolution output image is required. They are cheap for the resolution that they can reach and can be configured in many different ways. Nevertheless, such kinds of displays require geometric and color correction so that the composite image looks seamless. Display correction is an even bigger challenge when the projected images include dark scenes combined with brighter scenes. This is usually a problem for railway simulators when the train is positioned inside a tunnel and the black offset effect becomes noticeable. In this paper, a method for fast photometric and geometric correction of tiled display systems where dark and bright scenes are combined is presented. The image correction is carried out in two steps. First, geometric alignment and overlapping areas attenuation for brighter scenes is applied. Second, in the event of being inside a tunnel, the brightness of the scene is increased in certain areas using light sources in order to create the impression of darkness but minimizing the effect of the black offset.},
keywords={data visualisation;image colour analysis;natural scenes;railway engineering;tiled projector displays correction;dark scenes;railway simulators;geometric correction;color correction;photometric correction;tiled display systems;bright scenes;geometric alignment;overlapping areas attenuation;Image color analysis;Brightness;Lighting;Rail transportation;Cameras;Attenuation;Three dimensional displays;projection;simulator;black offset;blending},
doi={10.1109/EMS.2011.69},
ISSN={},
month={Nov},}

repository: czoido/my-awesome-cv

repo_name: czoido/my-awesome-cv


text:
@INPROCEEDINGS{Turo1992,
  author = {David Turo and Brian Johnson},
  title = {Improving the visualization of hierarchies with treemaps: Design Issues and Experimentation},
  pages = {124--131},
  abstract = {Controlled experiments with novice treemap users and real data highlight the strengths of treemaps and provide direction for improvement. Issues discussed include experimental results, layout algorithms, nesting offsets, labeling, animation, and small multiple displays. Treemaps prove to be a potent tool for hierarchy display. The principles discussed are applicable to many information visualization situations.},
  doi = {10.1109/VISUAL.1992.235217},
  year = {1992},
  booktitle = {Visualization'92: Proceedings of the IEEE Conference on Visualization},
  editor = {Arie Kaufman and Gregory M. Nielson},
  publisher = {IEEE Computer Society},
  isbn = {0818628979}
}

repository: vis-au/treevisnet

repo_name: vis-au/treevisnet


text:
SUMMARY = "foxconn OEM IPMI commands"
DESCRIPTION = "foxconn OEM IPMI commands"

LICENSE = "Apache-2.0"
LIC_FILES_CHKSUM = "file://${COMMON_LICENSE_DIR}/Apache-2.0;md5=89aea4e17d99a7cacdbeed46a0096b10"

S = "${WORKDIR}/git"

DEPENDS = "boost phosphor-ipmi-host phosphor-logging systemd libgpiod"

inherit cmake obmc-phosphor-ipmiprovider-symlink

EXTRA_OECMAKE="-DENABLE_TEST=0 -DYOCTO=1"

LIBRARY_NAMES = "libfiioemcmds.so"

SRC_URI = "git://github.com/openbmc/foxconn-ipmi-oem.git"
SRCREV = "da2cf0d2b0f4cd56bc93575a435a5ee1c848f7b0"

HOSTIPMI_PROVIDER_LIBRARY += "${LIBRARY_NAMES}"
NETIPMI_PROVIDER_LIBRARY += "${LIBRARY_NAMES}"

FILES:${PN}:append = " ${libdir}/ipmid-providers/lib*${SOLIBS}"
FILES:${PN}:append = " ${libdir}/host-ipmid/lib*${SOLIBS}"
FILES:${PN}:append = " ${libdir}/net-ipmid/lib*${SOLIBS}"
FILES:${PN}-dev:append = " ${libdir}/ipmid-providers/lib*${SOLIBSDEV}"

repository: Intel-BMC/openbmc

repo_name: Intel-BMC/openbmc