text:
# CMake generated Testfile for
# Source directory: /home/jonatan/Documents/Dev/foo-bar-fighters/test
# Build directory: /home/jonatan/Documents/Dev/foo-bar-fighters/test
#
# This file includes the relevant testing commands required for
# testing this directory and lists subdirectories to be tested as well.
include("/home/jonatan/Documents/Dev/foo-bar-fighters/test/tests_include-4c0d252.cmake")
include("/home/jonatan/Documents/Dev/foo-bar-fighters/test/constexpr_tests_include-c8884dd.cmake")
include("/home/jonatan/Documents/Dev/foo-bar-fighters/test/relaxed_constexpr_tests_include-ff2b5b0.cmake")

license: Unlicense

repository: jmidt/foo-bar-fighters

repo_name: jmidt/foo-bar-fighters


text:
% Encoding: UTF-8

@Article{JenkinsRambautPybusEtAl2002,
  author =      {Jenkins, Gareth M. and Rambaut, Andrew and Pybus, Oliver G. and Holmes, Edward C.},
  title =       {Rates of molecular evolution in RNA viruses: a quantitative phylogenetic analysis.},
  journal =     {J Mol Evol},
  year =        {2002},
  volume =      {54},
  number =      {2},
  pages =       {156--165},
  month =       {Feb},
  abstract =    {The study of rates of nucleotide substitution in RNA viruses is central to our understanding of their evolution. Herein we report a comprehensive analysis of substitution rates in 50 RNA viruses using a recently developed maximum likelihood phylogenetic method. This analysis revealed a significant relationship between genetic divergence and isolation time for an extensive array of RNA viruses, although more rate variation was usually present among lineages than would be expected under the constraints of a molecular clock. Despite the lack of a molecular clock, the range of statistically significant variation in overall substitution rates was surprisingly narrow for those viruses where a significant relationship between genetic divergence and time was found, as was the case when synonymous sites were considered alone, where the molecular clock was rejected less frequently. An analysis of the ecological and genetic factors that might explain this rate variation revealed some evidence of significantly lower substitution rates in vector-borne viruses, as well as a weak correlation between rate and genome length. Finally, a simulation study revealed that our maximum likelihood estimates of substitution rates are valid, even if the molecular clock is rejected, provided that sufficiently large data sets are analyzed.},
  doi =         {10.1007/s00239-001-0064-3},
  institution = {Department of Zoology, University of Oxford, UK.},
  keywords =    {Amino Acid Substitution; Computer Simulation; Databases, Nucleic Acid; Evolution, Molecular; Genome, Viral, genetics; Likelihood Functions; Models, Genetic; Phylogeny; RNA Viruses, genetics; Sequence Alignment},
  language =    {eng},
  medline-pst = {ppublish},
  pmid =        {11821909},
  url =         {http://dx.doi.org/10.1007/s00239-001-0064-3}
}

@Article{KosakovskyPondFrost2005,
  author =      {{Kosakovsky Pond}, Sergei L. and Frost, Simon D W.},
  title =       {Not so different after all: a comparison of methods for detecting amino acid sites under selection.},
  journal =     {Mol Biol Evol},
  year =        {2005},
  volume =      {22},
  number =      {5},
  pages =       {1208--1222},
  month =       {May},
  abstract =    {We consider three approaches for estimating the rates of nonsynonymous and synonymous changes at each site in a sequence alignment in order to identify sites under positive or negative selection: (1) a suite of fast likelihood-based "counting methods" that employ either a single most likely ancestral reconstruction, weighting across all possible ancestral reconstructions, or sampling from ancestral reconstructions; (2) a random effects likelihood (REL) approach, which models variation in nonsynonymous and synonymous rates across sites according to a predefined distribution, with the selection pressure at an individual site inferred using an empirical Bayes approach; and (3) a fixed effects likelihood (FEL) method that directly estimates nonsynonymous and synonymous substitution rates at each site. All three methods incorporate flexible models of nucleotide substitution bias and variation in both nonsynonymous and synonymous substitution rates across sites, facilitating the comparison between the methods. We demonstrate that the results obtained using these approaches show broad agreement in levels of Type I and Type II error and in estimates of substitution rates. Counting methods are well suited for large alignments, for which there is high power to detect positive and negative selection, but appear to underestimate the substitution rate. A REL approach, which is more computationally intensive than counting methods, has higher power than counting methods to detect selection in data sets of intermediate size but may suffer from higher rates of false positives for small data sets. A FEL approach appears to capture the pattern of rate variation better than counting methods or random effects models, does not suffer from as many false positives as random effects models for data sets comprising few sequences, and can be efficiently parallelized. Our results suggest that previously reported differences between results obtained by counting methods and random effects models arise due to a combination of the conservative nature of counting-based methods, the failure of current random effects models to allow for variation in synonymous substitution rates, and the naive application of random effects models to extremely sparse data sets. We demonstrate our methods on sequence data from the human immunodeficiency virus type 1 env and pol genes and simulated alignments.},
  doi =         {10.1093/molbev/msi105},
  institution = {Antiviral Research Center, University of California San Diego, USA.},
  keywords =    {Amino Acids, genetics; Codon, genetics; Evolution, Molecular; Genes, pol, genetics; Genetic Variation; HIV Envelope Protein gp120, genetics; Humans; Likelihood Functions; Models, Genetic; Mutation; Phylogeny; Selection, Genetic},
  language =    {eng},
  medline-pst = {ppublish},
  pii =         {msi105},
  pmid =        {15703242},
  url =         {http://dx.doi.org/10.1093/molbev/msi105}
}

@Article{LeitnerAlbert1999,
  author =      {Leitner, T. and Albert, J.},
  title =       {The molecular clock of HIV-1 unveiled through analysis of a known transmission history.},
  journal =     {Proc Natl Acad Sci U S A},
  year =        {1999},
  volume =      {96},
  number =      {19},
  pages =       {10752--10757},
  month =       {Sep},
  abstract =    {Detailed knowledge about the rate and mode of the genetic variation is vital for understanding how HIV-1 induces disease and develops resistance as well as for studies on the molecular epidemiology and origin of the virus. To unveil the molecular clock of HIV-1 we analyzed a unique set of viruses from a known transmission history with separation times between samples of up to 25 years. The env V3 and p17gag regions of the genome were sequenced, and genetic distances were estimated by using the true tree and a nucleotide substitution model based on a general reversible Markov process with a gamma distribution to account for differences in substitution rates among sites. Linear regression analysis showed that separation times were significantly correlated with synonymous as well as nonsynonymous nucleotide distances in both V3 and p17, giving strong support for the existence of a molecular clock. The estimated rate of nucleotide substitution was 6.7 +/- 2.1 x 10(-3) substitutions/site per year in V3 and 2.7 +/- 0.5 x 10(-3) in p17. Importantly, the regression analyses showed that there was a significant genetic distance at zero divergence times. This pretransmission interval exists because the ramifications in the phylogenetic trees do not correspond to time of transmission, but rather to the coalescence time of the most recent common ancestor of the viruses carried by the transmitter and the recipient. Simulation experiments showed that neither the V3 nor the p17 clocks were overdispersed, which indicates that the introduction of nucleotide substitutions can be described adequately by a simple stochastic Poisson process.},
  institution = {Theoretical Biology and Biophysics, Group T-10, MS K710, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. tkl@biochem.kth.se},
  keywords =    {Disease Transmission, Infectious; Evolution, Molecular; Gene Products, env, genetics; Gene Products, gag, genetics; Genetic Variation; HIV-1, genetics; Humans; Infectious Disease Transmission, Vertical; Models, Genetic; Molecular Sequence Data; Time Factors},
  language =    {eng},
  medline-pst = {ppublish},
  pmc =         {PMC17955},
  pmid =        {10485898}
}

@Article{LeitnerEscanillaFranzenEtAl1996,
  author =      {Leitner, T. and Escanilla, D. and Franz{\'{e}}n, C. and Uhl{\'{e}}n, M. and Albert, J.},
  title =       {Accurate reconstruction of a known HIV-1 transmission history by phylogenetic tree analysis.},
  journal =     {Proc Natl Acad Sci U S A},
  year =        {1996},
  volume =      {93},
  number =      {20},
  pages =       {10864--10869},
  month =       {Oct},
  abstract =    {Phylogenetic analyses are increasingly used in attempts to clarify transmission patterns of human immunodeficiency virus type 1 (HIV-1), but there is a continuing discussion about their validity because convergent evolution and transmission of minor HIV variants may obscure epidemiological patterns. Here we have studied a unique HIV-1 transmission cluster consisting of nine infected individuals, for whom the time and direction of each virus transmission was exactly known. Most of the transmissions occurred between 1981 and 1983, and a total of 13 blood samples were obtained approximately 2-12 years later. The p17 gag and env V3 regions of the HIV-1 genome were directly sequenced from uncultured lymphocytes. A true phylogenetic tree was constructed based on the knowledge about when the transmissions had occurred and when the samples were obtained. This complex, known HIV-1 transmission history was compared with reconstructed molecular trees, which were calculated from the DNA sequences by several commonly used phylogenetic inference methods [Fitch-Margoliash, neighbor-joining, minimum-evolution, maximum-likelihood, maximum-parsimony, unweighted pair group method using arithmetic averages (UPGMA), and a Fitch-Margoliash method assuming a molecular clock (KITSCH)]. A majority of the reconstructed trees were good estimates of the true phylogeny; 12 of 13 taxa were correctly positioned in the most accurate trees. The choice of gene fragment was found to be more important than the choice of phylogenetic method and substitution model. However, methods that are sensitive to unequal rates of change performed more poorly (such as UPGMA and KITSCH, which assume a constant molecular clock). The rapidly evolving V3 fragment gave better reconstructions than p17, but a combined data set of both p17 and V3 performed best. The accuracy of the phylogenetic methods justifies their use in HIV-1 research and argues against convergent evolution and selective transmission of certain virus variants.},
  institution = {Department of Clinical Virology, Swedish Institute for Infectious Disease Control, Karolinska Institute, Stockholm, Sweden.},
  keywords =    {Amino Acid Sequence; Base Sequence; Female; Genes, env; Genes, gag; HIV Infections, transmission; HIV-1, genetics; Humans; Male; Methods; Molecular Sequence Data; Phylogeny; RNA, Viral, genetics},
  language =    {eng},
  medline-pst = {ppublish},
  pmc =         {PMC38248},
  pmid =        {8855273}
}

@Article{LeitnerFitch1999,
  author =        {Leitner, T and Fitch, WM},
  title =         {The phylogenetics of known transmission histories},
  journal =       {The evolution of HIV. Johns Hopkins University Press, Baltimore, Md},
  year =          {1999},
  pages =         {315--345},
  __markedentry = {[simon:6]}
}

@Article{LeitnerKumarAlbert1997,
  author =      {Leitner, T. and Kumar, S. and Albert, J.},
  title =       {Tempo and mode of nucleotide substitutions in gag and env gene fragments in human immunodeficiency virus type 1 populations with a known transmission history.},
  journal =     {J Virol},
  year =        {1997},
  volume =      {71},
  number =      {6},
  pages =       {4761--4770},
  month =       {Jun},
  abstract =    {The complex evolutionary process of human immunodeficiency virus type 1 (HIV-1) is marked by a high level of genetic variation. It has been shown that the HIV-1 genome is characterized by variable and more constant regions, unequal nucleotide frequencies, and preference for G-to-A substitutions. However, this knowledge has largely been neglected in phylogenetic analyses of HIV-1 nucleotide sequences, even though these analyses are applied to a number of important biological questions. The purpose of this study was to identify a realistic model of HIV-1 evolution and to statistically test if the application of such a model significantly improves the accuracy of phylogenetic analyses. A unique and recently reported HIV-1 transmission cluster consisting of nine infected individuals, for whom the direction and time for each transmission were exactly known, formed the basis for the analyses which were performed under a general model of nucleotide substitution using population sequences from the env V3 and p17gag regions of the HIV-1 genome. Examination of seven different substitution models by maximum-likelihood methods revealed that the fit of the general reversible (REV) model was significantly better than that of simpler models, indicating that it is important to account for the asymmetric substitution pattern of HIV-1 and that the nucleotide substitution rate varied significantly across sites. The shape parameter alpha, which describes the variation across sites by a gamma distribution, was estimated to be 0.38 and 0.25 for env V3 and p17gag, respectively. In env V3, the estimated average transition/transversion rate ratio was 1.42. Thus, the REV model with variable rates across sites (described by a gamma distribution) provides the best description of HIV-1 evolution, whereas simple models are unrealistic and inaccurate. It is likely that the accuracy of phylogenetic studies of HIV-1 and many other viruses would improve substantially by the use of more realistic nucleotide substitution models. This is especially true when attempts are made to estimate the age of distant viral ancestors from contemporary viral sequences.},
  institution = {Theoretical Biology and Biophysics, Group T-10, Los Alamos National Laboratory, New Mexico 87545, USA. tkl@t10.lanl.gov},
  keywords =    {Base Sequence; Biological Evolution; Codon; Genes, env; Genes, gag; Genetics, Population; HIV Infections, transmission; HIV-1, genetics; Humans; Phylogeny; Sequence Alignment; Sequence Homology, Nucleic Acid},
  language =    {eng},
  medline-pst = {ppublish},
  pmc =         {PMC191698},
  pmid =        {9151870}
}

@Article{NickleHeathJensenEtAl2007,
  author =        {Nickle, David C. and Heath, Laura and Jensen, Mark A. and Gilbert, Peter B. and Mullins, James I. and {Kosakovsky Pond}, Sergei L.},
  title =         {HIV-specific probabilistic models of protein evolution.},
  journal =       {PLoS One},
  year =          {2007},
  volume =        {2},
  number =        {6},
  pages =         {e503},
  __markedentry = {[simon:]},
  abstract =      {Comparative sequence analyses, including such fundamental bioinformatics techniques as similarity searching, sequence alignment and phylogenetic inference, have become a mainstay for researchers studying type 1 Human Immunodeficiency Virus (HIV-1) genome structure and evolution. Implicit in comparative analyses is an underlying model of evolution, and the chosen model can significantly affect the results. In general, evolutionary models describe the probabilities of replacing one amino acid character with another over a period of time. Most widely used evolutionary models for protein sequences have been derived from curated alignments of hundreds of proteins, usually based on mammalian genomes. It is unclear to what extent these empirical models are generalizable to a very different organism, such as HIV-1-the most extensively sequenced organism in existence. We developed a maximum likelihood model fitting procedure to a collection of HIV-1 alignments sampled from different viral genes, and inferred two empirical substitution models, suitable for describing between-and within-host evolution. Our procedure pools the information from multiple sequence alignments, and provided software implementation can be run efficiently in parallel on a computer cluster. We describe how the inferred substitution models can be used to generate scoring matrices suitable for alignment and similarity searches. Our models had a consistently superior fit relative to the best existing models and to parameter-rich data-driven models when benchmarked on independent HIV-1 alignments, demonstrating evolutionary biases in amino-acid substitution that are unique to HIV, and that are not captured by the existing models. The scoring matrices derived from the models showed a marked difference from common amino-acid scoring matrices. The use of an appropriate evolutionary model recovered a known viral transmission history, whereas a poorly chosen model introduced phylogenetic error. We argue that our model derivation procedure is immediately applicable to other organisms with extensive sequence data available, such as Hepatitis C and Influenza A viruses.},
  doi =           {10.1371/journal.pone.0000503},
  institution =   {Department of Microbiology, University of Washington School of Medicine, Seattle, Washington, United States of America.},
  keywords =      {Amino Acid Substitution; Evolution, Molecular; Human Immunodeficiency Virus Proteins, chemistry/genetics/metabolism; Humans; Models, Statistical; Phylogeny; Sequence Analysis, Protein},
  language =      {eng},
  medline-pst =   {epublish},
  pmc =           {PMC1876811},
  pmid =          {17551583},
  url =           {http://dx.doi.org/10.1371/journal.pone.0000503}
}

@Article{SeoThorneHasegawaEtAl2002,
  author =      {Seo, Tae-Kun and Thorne, Jeffrey L. and Hasegawa, Masami and Kishino, Hirohisa},
  title =       {A viral sampling design for testing the molecular clock and for estimating evolutionary rates and divergence times.},
  journal =     {Bioinformatics},
  year =        {2002},
  volume =      {18},
  number =      {1},
  pages =       {115--123},
  month =       {Jan},
  abstract =    {The high pace of viral sequence change means that variation in the times at which sequences are sampled can have a profound effect both on the ability to detect trends over time in evolutionary rates and on the power to reject the Molecular Clock Hypothesis (MCH). Trends in viral evolutionary rates are of particular interest because their detection may allow connections to be established between a patient's treatment or condition and the process of evolution. Variation in sequence isolation times also impacts the uncertainty associated with estimates of divergence times and evolutionary rates. Variation in isolation times can be intentionally adjusted to increase the power of hypothesis tests and to reduce the uncertainty of evolutionary parameter estimates, but this fact has received little previous attention.We provide approximations for the power to reject the MCH when the alternative is that rates change in a linear fashion over time and when the alternative is that rates differ randomly among branches. In addition, we approximate the standard deviation of estimated evolutionary rates and divergence times. We illustrate how these approximations can be exploited to determine which viral sample to sequence when samples representing different dates are available.},
  institution = {Department of Biosystems Science, The Graduate University for Advanced Studies, Hayama, Kanagawa, 240-0193, Japan. seo@ism.ac.jp},
  keywords =    {Computational Biology; Evolution, Molecular; HIV-1, genetics/isolation /&/ purification; Humans; Models, Genetic; Models, Statistical; Time Factors; Viruses, genetics/isolation /&/ purification},
  language =    {eng},
  medline-pst = {ppublish},
  pmid =        {11836219}
}

@Article{YangNielsenGoldmanEtAl2000,
  author =      {Yang, Z. and Nielsen, R. and Goldman, N. and Pedersen, A. M.},
  title =       {Codon-substitution models for heterogeneous selection pressure at amino acid sites.},
  journal =     {Genetics},
  year =        {2000},
  volume =      {155},
  number =      {1},
  pages =       {431--449},
  month =       {May},
  abstract =    {Comparison of relative fixation rates of synonymous (silent) and nonsynonymous (amino acid-altering) mutations provides a means for understanding the mechanisms of molecular sequence evolution. The nonsynonymous/synonymous rate ratio (omega = d(N)d(S)) is an important indicator of selective pressure at the protein level, with omega = 1 meaning neutral mutations, omega < 1 purifying selection, and omega > 1 diversifying positive selection. Amino acid sites in a protein are expected to be under different selective pressures and have different underlying omega ratios. We develop models that account for heterogeneous omega ratios among amino acid sites and apply them to phylogenetic analyses of protein-coding DNA sequences. These models are useful for testing for adaptive molecular evolution and identifying amino acid sites under diversifying selection. Ten data sets of genes from nuclear, mitochondrial, and viral genomes are analyzed to estimate the distributions of omega among sites. In all data sets analyzed, the selective pressure indicated by the omega ratio is found to be highly heterogeneous among sites. Previously unsuspected Darwinian selection is detected in several genes in which the average omega ratio across sites is <1, but in which some sites are clearly under diversifying selection with omega > 1. Genes undergoing positive selection include the beta-globin gene from vertebrates, mitochondrial protein-coding genes from hominoids, the hemagglutinin (HA) gene from human influenza virus A, and HIV-1 env, vif, and pol genes. Tests for the presence of positively selected sites and their subsequent identification appear quite robust to the specific distributional form assumed for omega and can be achieved using any of several models we implement. However, we encountered difficulties in estimating the precise distribution of omega among sites from real data sets.},
  institution = {Department of Biology, University College London, London NW1 2HE, United Kingdom. z.yang@ucl.ac.uk},
  keywords =    {Amino Acid Substitution; Amino Acids; Animals; Codon; Drosophila, genetics; Gene Products, vif, genetics; Genes, pol; Globins, genetics; HIV Envelope Protein gp120, genetics; Hemagglutinin Glycoproteins, Influenza Virus, genetics; Humans; Membrane Glycoproteins, genetics; Mitochondria; Models, Genetic; Peptide Fragments, genetics; Selection, Genetic; Vertebrates, genetics; Viral Envelope Proteins, genetics; Viral Nonstructural Proteins, genetics},
  language =    {eng},
  medline-pst = {ppublish},
  pmc =         {PMC1461088},
  pmid =        {10790415}
}

repository: molecular-epidemiology/molepi-data

license_type: permissive

repo_name: molecular-epidemiology/molepi-data

branch_name: refs/heads/master

extension: bib


text:
SUMMARY = "A behavior-driven development framework, Python style"
HOMEPAGE = "https://github.com/behave/behave"
LICENSE = "BSD-2-Clause"
LIC_FILES_CHKSUM = "file://LICENSE;md5=d950439e8ea6ed233e4288f5e1a49c06"

PV .= "+git${SRCREV}"
SRCREV = "9520119376046aeff73804b5f1ea05d87a63f370"
SRC_URI += "git://github.com/behave/behave;branch=master;protocol=https"

S = "${WORKDIR}/git"

inherit setuptools3

RDEPENDS:${PN} += " \
    ${PYTHON_PN}-parse-type \
    ${PYTHON_PN}-setuptools \
    ${PYTHON_PN}-six \
    "

repository: openembedded/meta-openembedded

repo_name: openembedded/meta-openembedded

gha_license_id: MIT

gha_language: BitBake

extension: bb


text:
SUMMARY = "A fast implementation of the Cassowary constraint solver"
HOMEPAGE = "https://github.com/nucleic/kiwi"
LICENSE = "BSD"
LIC_FILES_CHKSUM = "file://setup.py;endline=7;md5=1c177d169db050341d3b890c69fb80e3"

SRC_URI[md5sum] = "fc8a614367f7ba0d34a02fd08c535afc"
SRC_URI[sha256sum] = "53eaed412477c836e1b9522c19858a8557d6e595077830146182225613b11a75"

inherit pypi setuptools3

RDEPENDS_${PN} += "\
    python3-core \
    python3-setuptools \
"

BBCLASSEXTEND = "native nativesdk"


text:
function ShowDivNoteDoneAjax(){
    var SettingInputLogin = $('.SettingInputLogin').val();

    $.ajax({
        url: "http://d0008482.atservers.net/ShowDivNoteDone.php",
        type: "POST",
        data:{
            "SettingInputLogin":SettingInputLogin
        },
        dataType: "html",
        success: SuccesAjaxShowDivNoteDone
    });

}
function SuccesAjaxShowDivNoteDone(data){

    $(".ContainerNote").html(data);
//    console.log(data);
    ShowFirstTextNoteAjax();
    $('.InfoTextNote').text("Выполненные");
    $('.ContainerNote').css('background-color','#d9d9d9');
};

license: MIT

extension: js


text:
@article{Harper:2017aa,
 author = {Harper, Sam and Kaufman, Jay S and Cooper, Richard S},
 bdsk-url-1 = {https://doi.org/10.1097/EDE.0000000000000677},
 date-added = {2020-09-24 17:39:55 -0400},
 date-modified = {2020-09-24 17:39:55 -0400},
 doi = {10.1097/EDE.0000000000000677},
 journal = {Epidemiology},
 journal-full = {Epidemiology (Cambridge, Mass.)},
 mesh = {Humans; Life Expectancy; United States},
 month = {11},
 number = {6},
 pages = {e54-e56},
 pmid = {28445248},
 pst = {ppublish},
 title = {Declining US Life Expectancy: A First Look},
 volume = {28},
 year = {2017}
}


text:
DESCRIPTION = "Lua bindings to zeromq2."
HOMEPAGE = "http://github.com/iamaleksey/lua-zmq"
LICENSE = "MIT"
LIC_FILES_CHKSUM = "file://zmq.c;beginline=1;endline=21;md5=e1bbb5e9ca8c6fb7215f886d9d0d5cd3"

DEPENDS += "lua5.1 zeromq"

PR = "r0"
PV = "0.10+gitr${SRCREV}"
S = "${WORKDIR}/git/"
SRCREV = "5578612efe296faa36203c7b80507e38fa7714e0"

SRC_URI = "git://github.com/iamaleksey/lua-zmq.git;protocol=git \
           file://makefile.patch \
          "

LUA_LIB_DIR = "${libdir}/lua/5.1"

PACKAGES = "${PN} ${PN}-dbg"
FILES_${PN}-dbg = "${LUA_LIB_DIR}/.debug/zmq.so"
FILES_${PN} = "${LUA_LIB_DIR}/zmq.so"

EXTRA_OEMAKE = "MYFLAGS='${CFLAGS} ${LDFLAGS} -shared'"

do_install() {
        oe_runmake install PREFIX=${D}${LUA_LIB_DIR}
}

repository: balister/openembedded

repo_name: balister/openembedded


text:
@article{pfoertner2022linpde,
  author  = {Pförtner, Marvin and Steinwart, Ingo and Hennig, Philipp and Wenger, Jonathan},
  journal = {arXiv preprint},
  title   = {Physics-Informed {G}aussian Process Regression Generalizes Linear {PDE} Solvers},
  url     = {https://arxiv.org/abs/2212.12474},
  year    = {2022}
}


text:
@import "//netdna.bootstrapcdn.com/font-awesome/3.0/css/font-awesome.css";

@import url(http://fonts.googleapis.com/css?family=Open+Sans);

*, html, body {
    font-family: Open Sans;
}

ul, li {
    margin: 0;
    padding: 0;
    list-style-type: none;
}

.profile-container {
   # position: relative;
    width: 143px;
    float: left;
}

.profile {
    background: #f6f6f6;
    float: left;
    padding: 4px;
    border-radius: 3px;
    -o-border-radius: 3px;
    -ms-border-radius: 3px;
    -moz-border-radius: 3px;
    -webkit-border-radius: 3px;
    -webkit-transition: all 0.2s ease-in-out;
    -moz-transition: all 0.2s ease-in-out;
    -ms-transition: all 0.2s ease-in-out;
    -o-transition: all 0.2s ease-in-out;
    transition: all 0.2s ease-in-out;
}

.profile-list {
    overflow: hidden;
    width: 100%;
    box-sizing: border-box;
    color: #767b7e;
    font-size: 13px;
}

.profile-list li {
    cursor: pointer;
    background: #ffffff;
    border-top: 1px solid #e5e6e6;
    padding: 15px 10px;
}

.profile-list li:last-child {
    border-radius: 0 0 3px 3px;;
    -o-border-radius: 0 0 3px 3px;
    -ms-border-radius: 0 0 3px 3px;
    -moz-border-radius: 0 0 3px 3px;
    -webkit-border-radius: 0 0 3px 3px;
}

.profile-list li [class^="icon-"] {
    margin: 0 3px 0 0;
}

.profile-list .profile {
    border-radius: 3px 3px 0 0;
   # position: relative;
}

.profile-list li {
    -webkit-transform-origin: 50% 0%;
    -o-transform-origin: 50% 0%;
    transform-origin: 50% 0%;
    -webkit-transform: perspective(250px) rotateX(-90deg);
    -o-transform: perspective(250px) rotateX(-90deg);
    transform: perspective(250px) rotateX(-90deg);
    -moz-box-shadow: 0px 2px 10px rgba(0,0,0,0.05);
}

.profile-list .first {
    -webkit-transition: 0.2s linear 0.8s;
    -o-transition: 0.2s linear 0.8s;
    transition: 0.2s linear 0.8s;
}

.profile-list .second {
    -webkit-transition: 0.2s linear 0.6s;
    -o-transition: 0.2s linear 0.6s;
    transition: 0.2s linear 0.6s;
}

.profile-list .third {
    -webkit-transition: 0.2s linear 0.4s;
    -o-transition: 0.2s linear 0.4s;
    transition: 0.2s linear 0.4s;
}

.profile-list .fourth {
    -webkit-transition: 0.2s linear 0.2s;
    -o-transition: 0.2s linear 0.2s;
    transition: 0.2s linear 0.2s;
}

.profile-container:hover .profile {
    border-radius: 3px 3px 0 0;
    -o-border-radius: 3px 3px 0 0;
    -ms-border-radius: 3px 3px 0 0;
    -moz-border-radius: 3px 3px 0 0;
    -webkit-border-radius: 3px 3px 0 0;
}

.profile-container:hover .profile-list li {
    -webkit-transform: perspective(350px) rotateX(0deg);
    -o-transform: perspective(350px) rotateX(0deg);
    transform: perspective(350px) rotateX(0deg);
    -webkit-transition: 0.2s linear 0s;
    -o-transition: 0.2s linear 0s;
    transition: 0.2s linear 0s;
}

.profile-container:hover .profile-list .second {
    -webkit-transition-delay: 0.2s;
    -o-transition-delay: 0.2s;
    transition-delay: 0.2s;
}

.profile-container:hover .profile-list .third {
    -webkit-transition-delay: 0.4s;
    -o-transition-delay: 0.4s;
    transition-delay: 0.4s;
}

.profile-container:hover .profile-list .fourth {
    transition-delay: 0.6s;
    -o-transition-delay: 0.6s;
    transition-delay: 0.6s;
}

 Profile

 Activity

 Timeline

 Favorites

repository: jatin-ch/Project-manager-google

repo_name: jatin-ch/Project-manager-google

extension: css


text:
SUMMARY = "OpenBMC fan control"
DESCRIPTION = "OpenBMC fan control."
PR = "r1"

inherit skeleton-python
inherit obmc-phosphor-dbus-service

RDEPENDS_${PN} += "\
        python-dbus \
        python-pygobject \
        pyphosphor-dbus \
        "
SKELETON_DIR = "pyfanctl"
DBUS_SERVICE_${PN} += "org.openbmc.control.Fans.service"
SYSTEMD_SERVICE_${PN} += "obmc-max-fans.service"


text:
SUMMARY     = "AGL Data Harvester Service/API"
DESCRIPTION = "V2C interface that collect data to TimeSeries database"
HOMEPAGE    = "https://git.automotivelinux.org/apps/agl-service-harvester/"
SECTION     = "apps"

LICENSE = "Apache-2.0"
LIC_FILES_CHKSUM = "file://LICENSE;md5=86d3f3a95c324c9479bd8986968f4327"

SRC_URI = "git://gerrit.automotivelinux.org/gerrit/apps/agl-service-harvester;protocol=http;branch=sandbox/SebD/wip"
SRCREV = "${AUTOREV}"

PV = "0.1+git${SRCPV}"
S  = "${WORKDIR}/git"

inherit cmake aglwgt pkgconfig

DEPENDS += "json-c systemd libafb-helpers libappcontroller curl"

repository: iotbzh/meta-iot-bzh

repo_name: iotbzh/meta-iot-bzh

gha_language: Shell


text:
import React, { Component } from 'react';
import {
  Nav,
  BDiv,
  BA
} from 'bootstrap-4-react';

export default class Components extends Component {
  renderItem(name, label) {
    const path = this.props.path || '';
    const subPath = path.replace(/^components\/?/, '') || 'alert';
    const subMatch = new RegExp(name + '\\/?$');
    const isActive = subPath.match(subMatch);

    return (
      <Nav.Item active={isActive}>
        <Nav.Link href={'#documentation/components/' + name}>{label}</Nav.Link>
      </Nav.Item>
    )
  }

  render() {
    const path = this.props.path || '';
    const isActive = path && path.startsWith('components');

    return (
      <React.Fragment>
        <BDiv className="bd-toc-item" active={isActive}>
          <BA className="bd-toc-link" href="#documentation/components">Components</BA>
        </BDiv>
        { isActive &&
          <Nav display="block">
            {this.renderItem('alert', 'Alert')}
            {this.renderItem('badge', 'Badge')}
            {this.renderItem('blockquote', 'Blockquote')}
            {this.renderItem('breadcrumb', 'Breadcrumb')}
            {this.renderItem('button', 'Button')}
            {this.renderItem('button-group', 'ButtonGroup')}
            {this.renderItem('card', 'Card')}
            {this.renderItem('carousel', 'Carousel')}
            {this.renderItem('collapse', 'Collapse')}
            {this.renderItem('display', 'Display')}
            {this.renderItem('dropdown', 'Dropdown')}
            {this.renderItem('figure', 'Figure')}
            {this.renderItem('form', 'Form')}
            {this.renderItem('input-group', 'InputGroup')}
            {this.renderItem('jumbotron', 'Jumbotron')}
            {this.renderItem('lead', 'Lead')}
            {this.renderItem('list', 'List')}
            {this.renderItem('list-group', 'ListGroup')}
            {this.renderItem('modal', 'Modal')}
            {this.renderItem('nav', 'Nav')}
            {this.renderItem('navbar', 'Navbar')}
            {this.renderItem('pagination', 'Pagination')}
            {this.renderItem('progress', 'Progress')}
            {this.renderItem('popover', 'Popover')}
            {this.renderItem('tooltip', 'Tooltip')}
          </Nav>
        }
      </React.Fragment>
    )
  }
}

gha_language: JavaScript

extension: jsx


text:
@online{ rbe,
author = {The Vinus Project},
title = {Resource Based Economy},
note = {\url{http://www.thevenusproject.com/the-venus-project/resource-based-economy}},
}

@online{ tzfs,
author = {Peter Joseph},
title = {The Zeitgeist Film Series Gateway},
note = {\url{http://www.zeitgeistmovie.com/}},
}

@online{ 4hourday,
author = {Carlos Tovar Samanez},
title = {Global Campaign for the 4-hour Work Day},
note = {\url{http://4hourworkdaycampaign.wordpress.com/}},
}

@book{ plenitude,
author = {Juliet Schor},
title = {Visualizing a Plenitude Economy},
year = {2011},
publisher = {YouTube},
}


text:
const slugify = require('slugify');

const states = {
  AL: 'Alabama',
  AK: 'Alaska',
  AZ: 'Arizona',
  AR: 'Arkansas',
  CA: 'California',
  CO: 'Colorado',
  CT: 'Connecticut',
  DE: 'Delaware',
  FL: 'Florida',
  GA: 'Georgia',
  HI: 'Hawaii',
  ID: 'Idaho',
  IL: 'Illinois',
  IN: 'Indiana',
  IA: 'Iowa',
  KS: 'Kansas',
  KY: 'Kentucky',
  LA: 'Louisiana',
  ME: 'Maine',
  MD: 'Maryland',
  MA: 'Massachusetts',
  MI: 'Michigan',
  MN: 'Minnesota',
  MS: 'Mississippi',
  MO: 'Missouri',
  MT: 'Montana',
  NE: 'Nebraska',
  NV: 'Nevada',
  NH: 'New Hampshire',
  NJ: 'New Jersey',
  NM: 'New Mexico',
  NY: 'New York',
  NC: 'North Carolina',
  ND: 'North Dakota',
  OH: 'Ohio',
  OK: 'Oklahoma',
  OR: 'Oregon',
  PA: 'Pennsylvania',
  RI: 'Rhode Island',
  SC: 'South Carolina',
  SD: 'South Dakota',
  TN: 'Tennessee',
  TX: 'Texas',
  UT: 'Utah',
  VT: 'Vermont',
  VA: 'Virginia',
  WA: 'Washington',
  WV: 'West Virginia',
  WI: 'Wisconsin',
  WY: 'Wyoming',
};

const stateNames = Object.values(states);
const stateKeys = Object.keys(states);
const stateEntries = Object.entries(states);

const slugifyOptions = { lower: true };

const stateKeySlugs = stateKeys.map(state => slugify(state, slugifyOptions));
const stateNameSlugs = stateNames.map(state => slugify(state, slugifyOptions));
const stateEntrySlugs = stateEntries.map(([code, name]) => [
  slugify(code, slugifyOptions),
  slugify(name, slugifyOptions),
]);

function findStateByName(input) {
  const state = stateEntries.find(([code, name]) => {
    const inputSlug = slugify(input, slugifyOptions);
    if (
      inputSlug === slugify(code, slugifyOptions) ||
      inputSlug === slugify(name, slugifyOptions)
    ) {
      return true;
    }
    return false;
  });

  return state || [undefined, undefined];
}

module.exports = {
  states,
  stateNames,
  stateKeys,
  stateEntries,
  stateKeySlugs,
  stateNameSlugs,
  stateEntrySlugs,
  findStateByName,
};

repository: mcansh/nps-gallery

repo_name: mcansh/nps-gallery

gha_language: TypeScript


text:
@inproceedings{HEARTBEAT_18,
 author={Acar, Umut A and Charguéraud, Arthur and Guatto, Adrien and Rainey, Mike and Sieczkowski, Filip},
 title = {Heartbeat Scheduling: Provable Efficiency for Nested Parallelism},
 booktitle = {PLDI'18},
 year = {2018},
 url = {http://deepsea.inria.fr/heartbeat/heartbeat.pdf},
 publisher = {ACM},
}

@Article{LAZY_SCHEDULING_14,
  author	= {Tzannes, Alexandros and Caragea, George C. and Vishkin,
		  Uzi and Barua, Rajeev},
  title		= {Lazy Scheduling: A Runtime Adaptive Scheduler for
		  Declarative Parallelism},
  journal	= {TOPLAS},
  issue_date	= {September 2014},
  volume	= {36},
  number	= {3},
  month		= sep,
  year		= {2014},
  optissn	= {0164-0925},
  pages		= {10:1--10:51},
  articleno	= {10},
  numpages	= {51},
  url		= {http://doi.acm.org/10.1145/2629643},
  doi		= {10.1145/2629643},
  acmid		= {2629643},
  publisher	= {ACM},
  address	= {New York, NY, USA},
  keywords	= {Work stealing, adaptive scheduling, declarative,
		  fine-grained, load balancing, nested parallelism,
		  performance portability, task-parallel}
}

repository: deepsea-inria/deepsea-web

repo_name: deepsea-inria/deepsea-web


text:
#!/usr/bin/env node

'use strict';

var path = require('path');
var _ = require('lodash');

/*
 * Constructor.
 */
function Drush(kbox, app, image, plugin) {

  // We might want to use a different image to run drush commands
  // a la terminus but set drush as the default is no arg
  if (image === undefined) {
    image = 'drush';
  }
  if (plugin === undefined) {
    plugin = 'kalabox-plugin-drush';
  }

  /// Set our things
  // The plugin calling the client
  this.plugin = plugin;
  this.image = image;
  this.app = app;
  this.kbox = kbox;

}

/**
 * Gets plugin conf from the appconfig or from CLI arg
 **/
Drush.prototype.getOpts = function(options) {
  // Override kalabox.json options with command line args
  var defaults = this.app.config.pluginConf[this.plugin];
  _.each(Object.keys(defaults), function(key) {
    if (_.has(options, key) && options[key]) {
      defaults[key] = options[key];
    }
  });
  return defaults;
};

/**
 * Runs a git command on the app data container
 **/
Drush.prototype.cmd = function(payload, options, done) {

  var engine = this.kbox.engine;
  var Promise = this.kbox.Promise;
  var globalConfig = this.kbox.core.deps.lookup('globalConfig');

  // Run the drush command in the correct directory in the container if the
  // user is somewhere inside the code directory on the host side.
  // @todo: consider if this is better in the actual engine.run command
  // vs here.

  // Get current working directory.
  var cwd = process.cwd();

  // Get code root.
  var codeRoot = this.app.config.codeRoot;

  // Get the branch of current working directory.
  // Run the drush command in the correct directory in the container if the
  // user is somewhere inside the code directory on the host side.
  // @todo: consider if this is better in the actual engine.run command
  // vs here.
  var workingDirExtra = '';
  if (_.startsWith(cwd, codeRoot)) {
    workingDirExtra = cwd.replace(codeRoot, '');
  }
  var codeDir = globalConfig.codeDir;
  var workingDir = '/' + codeDir + workingDirExtra;

  // Get drush version.
  var opts = this.getOpts(options);
  var drushVersion = (opts['drush-version'] === 'backdrush') ?
    'backdrush' :
    'drush' + opts['drush-version'];

  // Image name.
  var image = this.image;

  // Build create options.
  var idObj = this.kbox.util.docker.containerName.createTemp();
  var id = this.kbox.util.docker.containerName.format(idObj);
  var createOpts = this.kbox.util.docker.CreateOpts(id)
    .workingDir(workingDir)
    .env('DRUSH_VERSION', drushVersion)
    .volumeFrom(this.app.dataContainerName)
    .json();

  // force drush entrypoint; needed if we use a different image then
  // then core drush image
  /* jshint ignore:start */
  //jscs:disable
  createOpts.Entrypoint = ["/usr/local/bin/kdrush"];
  /* jshint ignore:end */

  // Build start options.
  var startOpts = this.kbox.util.docker.StartOpts()
    .bind(this.app.config.homeBind, '/ssh')
    .bind(this.app.rootBind, '/src')
    .json();

  // Perform a container run.
  return engine.run(image, payload, createOpts, startOpts)
  // Return.
  .nodeify(done);

};

// Return constructor as the module object.
module.exports = Drush;

repository: pirog/kalabox-plugin-drush

repo_name: pirog/kalabox-plugin-drush


text:
@article{2020:JSS:RENAME,
 abstract = {Identifier names are the atoms of program comprehension. Weak identifier names decrease developer productivity and degrade the performance of automated approaches that leverage identifier names in source code analysis; threatening many of the advantages which stand to be gained from advances in artificial intelligence and machine learning. Therefore, it is vital to support developers in naming and renaming identifiers. In this paper, we extend our prior work, which studies the primary method through which names evolve: rename refactorings. In our prior work, we contextualize rename changes by examining commit messages and other refactorings. In this extension, we further consider data type changes which co-occur with these renames, with a goal of understanding how data type changes influence the structure and semantics of renames. In the long term, the outcomes of this study will be used to support research into: (1) recommending when a rename should be applied, (2) recommending how to rename an identifier, and (3) developing a model that describes how developers mentally synergize names using domain and project knowledge. We provide insights into how our data can support rename recommendation and analysis in the future, and reflect on the significant challenges, highlighted by our study, for future research in recommending renames.},
 author = {Anthony Peruma and Mohamed Wiem Mkaouer and Michael J. Decker and Christian D. Newman},
 doi = {https://doi.org/10.1016/j.jss.2020.110704},
 issn = {0164-1212},
 journal = {Journal of Systems and Software},
 keywords = {Program comprehension, Identifier names, Refactoring, Rename refactoring, Data types},
 pages = {110704},
 title = {Contextualizing rename decisions using refactorings, commit messages, and data types},
 url = {https://www.sciencedirect.com/science/article/pii/S0164121220301503},
 volume = {169},
 year = {2020}
}

repository: SCANL/scanl-web-redesign

repo_name: SCANL/scanl-web-redesign

branch_name: refs/heads/main


text:
@misc{compliant, title={About Compliant Mechanisms}, url={https://www.compliantmechanisms.byu.edu/about-compliant-mechanisms}, journal={Compliant Mechanisms}, publisher={BYU Compliant Mechanisms Research Group}}
@article{invention,
 ISSN = {21678472, 21678480},
 URL = {http://www.jstor.org/stable/43957291},
 author = {Larry L. Howell},
 journal = {BYU Studies Quarterly},
 number = {3},
 pages = {83--99},
 publisher = {Brigham Young University},
 title = {Anatomy of Invention},
 volume = {55},
 year = {2016},
 doi={10.2307/43957291}
}
@misc{wrench, url={http://3dfilaprint.com/project-update-9-compliant-mechanisms-printed-with-polyflex/}, journal={Project Update #9: Compliant mechanisms printed with PolyFlex!}, publisher={3D FilaPrint}, author={billyboyclyde}, year={2014}, month={May}}
@article{functionallygradedmaterials, title={Optimal design of compliant mechanisms using functionally graded materials}, volume={57}, url={https://link.springer.com/article/10.1007/s00158-017-1744-y}, DOI={10.1007/s00158-017-1744-y}, number={1}, journal={Structural and Multidisciplinary Optimization}, author={Conlan-Smith, Cian and Bhattacharyya, Anurag and James, Kai A.}, year={2018}, pages={197–212}}
 @article{hingedesign, title={Modeling and Design of Flexure Hinge-Based Compliant Mechanisms}, DOI={10.5772/intechopen.85224}, journal={Kinematics - Analysis and Applications}, author={Linß, Sebastian and Henning, Stefan and Zentner, Lena}, year={2019}, month={Apr}}
@article{rotationalhinges,
author = {Kern, Dominik and Rösner, Malte and Bauma, Elisabeth and Seemann, Wolfgang and Lammering, Rolf and Schuster, Thomas},
url={https://www.researchgate.net/publication/263225114_Key_features_of_flexure_hinges_used_as_rotational_joints_Transition_from_concentrated_to_distributed_compliances},
year = {2013},
month = {12},
pages = {},
title = {Key features of flexure hinges used as rotational joints: Transition from concentrated to distributed compliances},
volume = {77},
journal = {Forschung im Ingenieurwesen},
doi = {10.1007/s10010-013-0169-z}
}
@article{CHANDRAN2016222,
title = {Mechanical fatigue of polymers: A new approach to characterize the SN behavior on the basis of macroscopic crack growth mechanism},
journal = {Polymer},
volume = {91},
pages = {222-238},
year = {2016},
issn = {0032-3861},
doi = {https://doi.org/10.1016/j.polymer.2016.03.058},
url = {https://www.sciencedirect.com/science/article/pii/S003238611630204X},
author = {K.S. Ravi Chandran}
}
@misc{elastomer, title={Elastomer}, url={https://en.wikipedia.org/wiki/Elastomer}, journal={Wikipedia}, publisher={Wikimedia Foundation}, year={2021}, month={Mar}}
@Inbook{Bogdanovich2013,
author="Bogdanovich, Pavel N.
and Tkachuk, Denis V.",
editor="Wang, Q. Jane
and Chung, Yip-Wah",
title="Polymer Fatigue",
bookTitle="Encyclopedia of Tribology",
year="2013",
publisher="Springer US",
address="Boston, MA",
pages="2578--2585",
isbn="978-0-387-92897-5",
doi="10.1007/978-0-387-92897-5_818",
url="https://doi.org/10.1007/978-0-387-92897-5_818"
}
@misc{wiki, title={Compliant mechanism}, url={https://en.wikipedia.org/wiki/Compliant_mechanism}, journal={Wikipedia}, publisher={Wikimedia Foundation}, year={2021}, month={Mar}}
@misc{fatigue, title={Fatigue (material)}, url={https://en.wikipedia.org/wiki/Fatigue_(material)}, journal={Wikipedia}, publisher={Wikimedia Foundation}, year={2021}, month={Mar}}


text:
@article{reilly_exacerbation_2019,
 abstract = {Psychotic disorders can be exacerbated by the hormonal changes associated with childbirth, but the extent to which exacerbations occur with the menstrual cycle is unclear. We addressed this issue by conducting a systematic review. Embase, Medline, and PsychINFO databases were searched for studies that measured exacerbations of psychotic disorders in relation to the menstrual cycle. We extracted exacerbation measure, definition of menstrual cycle phase, and measurement of menstrual cycle phase. Standard incidence ratios were calculated for the perimenstrual phase based on the observed admissions during this phase divided by the expected number of admissions if the menstrual cycle had no effect. Random effects models were used to examine pooled rates of psychiatric admission in the perimenstrual phase. Nineteen studies, comprising 1193 participants were eligible for inclusion. Eleven studies examined psychiatric admission rates, 5 examined symptoms scores, 2 examined self-reported exacerbation, and 1 examined both admission rates and symptom scores. A random effects model demonstrated the rate of admissions during the perimenstrual phase was 1.48 times higher than expected (95% CI: 1.31–1.67), with no significant heterogeneity detected. Four of six symptom score studies reported perimenstrual worsening, but lack of consistency in timepoints precluded meta-analysis. Two studies examining self-reported menstrual exacerbations reported prevalences ranging from 20% to 32.4%. Psychiatric admission rates are significantly higher than expected during the perimenstrual phase. There is some evidence that a worsening of psychotic symptoms also occurs during this phase, but further research with more precise measurement of the menstrual cycle and symptomatology is required.},
 author = {Reilly, Thomas J and Sagnay de la Bastida, Vanessa C and Joyce, Dan W and Cullen, Alexis E and McGuire, Philip},
 doi = {10.1093/schbul/sbz030},
 issn = {0586-7614},
 journal = {Schizophrenia Bulletin},
 month = {May},
 number = {1},
 pages = {78--90},
 title = {Exacerbation of Psychosis During the Perimenstrual Phase of the Menstrual Cycle: Systematic Review and Meta-analysis},
 url = {https://doi.org/10.1093/schbul/sbz030},
 urldate = {2020-05-04},
 volume = {46},
 year = {2019}
}

repository: danwjoyce/technical-blog

repo_name: danwjoyce/technical-blog


text:
% Encoding: UTF-8

@article{邢永康2003统计语言模型综述,
  title={统计语言模型综述},
  author={邢永康 and 马少平},
  journal={计算机科学},
  volume={30},
  number={9},
  pages={22--26},
  year={2003}
}

@incollection{fink2014n,
  title={n-Gram Models},
  author={Fink, Gernot A},
  booktitle={Markov Models for Pattern Recognition},
  pages={107--127},
  year={2014},
  publisher={Springer}
}

@article{bengio2003neural,
  title={A neural probabilistic language model},
  author={Bengio, Yoshua and Ducharme, R{\'e}jean and Vincent, Pascal and Jauvin, Christian},
  journal={Journal of machine learning research},
  volume={3},
  number={Feb},
  pages={1137--1155},
  year={2003}
}

@inproceedings{gutmann2010noise,
  title={Noise-contrastive estimation: A new estimation principle for unnormalized statistical models.},
  author={Gutmann, Michael and Hyv{\"a}rinen, Aapo},
  booktitle={AISTATS},
  volume={1},
  number={2},
  pages={6},
  year={2010}
}

@article{kumar2007rough,
  title={Rough clustering of sequential data},
  author={Kumar, Pradeep and Krishna, P Radha and Bapi, Raju S and De, Supriya Kumar},
  journal={Data \& Knowledge Engineering},
  volume={63},
  number={2},
  pages={183--199},
  year={2007},
  publisher={Elsevier}
}
@comment{jabref-meta: selector_publisher:}

@comment{jabref-meta: selector_author:}

@comment{jabref-meta: selector_journal:}

@comment{jabref-meta: selector_keywords:}


text:
@article{Kairov2017,
author = {Kairov, Ulykbek and Cantini, Laura and Greco, Alessandro and Molkenov, Askhat and Czerwinska, Urszula and Barillot, Emmanuel and Zinovyev, Andrei},
doi = {10.1186/s12864-017-4112-9},
issn = {1471-2164},
journal = {BMC Genomics},
keywords = {Animal Genetics and Genomics,Life Sciences,Microarrays,Microbial Genetics and Genomics,Plant Genetics and Genomics,Proteomics,general},
number = {1},
pages = {712},
publisher = {BioMed Central},
title = {{Determining the optimal number of independent components for reproducible transcriptomic data analysis}},
url = {http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-4112-9},
volume = {18},
year = {2017}
}
@incollection{Czerwinska2018b,
author = {Czerwinska, Urszula and Cantini, Laura and Kairov, Ulykbek and Barillot, Emmanuel and Zinovyev, Andrei},
doi = {10.1007/978-3-319-93764-9_46},
pages = {501--513},
publisher = {Springer, Cham},
title = {{Application of Independent Component Analysis to Tumor Transcriptomes Reveals Specific and Reproducible Immune-Related Signals}},
url = {http://link.springer.com/10.1007/978-3-319-93764-9{\_}46},
year = {2018}
}

repository: UrszulaCzerwinska/UCzPhDThesis

repo_name: UrszulaCzerwinska/UCzPhDThesis


text:
require recipes-core/images/core-image-minimal.bb

DEPENDS = "linux-yocto-linkit7688 padjffs2-native"

IMAGE_FSTYPES = "squashfs-xz jffs2"
# IMAGE_FEATURES += "read-only-rootfs"

# EXTRA_IMAGECMD_jffs2_remove = "--pad"
EXTRA_IMAGECMD_jffs2 += "-x lzo -x zlib"

IMAGE_INSTALL += "mtd-utils"
IMAGE_INSTALL += "mtd-utils-ubifs"
IMAGE_INSTALL += "iw"
IMAGE_INSTALL += "alsa-utils-amixer"
IMAGE_INSTALL += "alsa-utils-aplay"
IMAGE_INSTALL += "alsa-utils-speakertest"
IMAGE_INSTALL += "swconfig"
IMAGE_INSTALL += "mt7688-utils"
IMAGE_INSTALL += "earlysetup"
IMAGE_INSTALL += "wpa-supplicant"
IMAGE_INSTALL += "packagegroup-core-ssh-dropbear"

do_prepare_sysupgrade() {
    cd ${DEPLOY_DIR_IMAGE}
    ubinize -o base-image-ubi.img -m 1 -p 0x10000 -O 4096 lks7688_ubinize.cfg
    dd if=${DEPLOY_DIR_IMAGE}/uImage >  ${DEPLOY_DIR_IMAGE}/lks7688.img
    dd if=${DEPLOY_DIR_IMAGE}/base-image-ubi.img >>  ${DEPLOY_DIR_IMAGE}/lks7688.img
}

# Call function prepare_sysupgrade to generate images
addtask prepare_sysupgrade after do_image_complete before do_populate_lic_deploy

repository: fagius/micro-iot

repo_name: fagius/micro-iot


text:
SUMMARY = "libtar, tar manipulating library"
DESCRIPTION = "libtar is a library for manipulating POSIX tar files"
HOMEPAGE = "http://www.feep.net/libtar"
SECTION = "libs"
LICENSE = "MIT"
LIC_FILES_CHKSUM = "file://COPYRIGHT;md5=61cbac6719ae682ce6cd45b5c11e21af"

SRC_URI = "${DEBIAN_MIRROR}/main/libt/${BPN}/${BPN}_${PV}.orig.tar.gz \
           file://fix_libtool_sysroot.patch \
           file://0002-Do-not-strip-libtar.patch \
           "

S = "${WORKDIR}/${BPN}"

SRC_URI[md5sum] = "6ced95ab3a4b33fbfe2dfb231d156cdb"
SRC_URI[sha256sum] = "50f24c857a7ef1cb092e6508758b86d06f1188508f897f3e6b40c573e8879109"

inherit autotools-brokensep

PACKAGECONFIG ??= "zlib"
PACKAGECONFIG[zlib] = "--with-zlib,--without-zlib,zlib"

BBCLASSEXTEND += "native"


text:
# Base this image on rpi-basic-image
include recipes-core/images/core-image-minimal.bb

LICENSE = "Apache-2.0"

MACHINE = "raspberrypi3"

# Include modules in rootfs
IMAGE_INSTALL += " \
        ldd \
        u-boot-fw-utils \
        logrotate \
        util-linux-agetty \
        util-linux \
        rng-tools \
        e2fsprogs \
        kernel-modules"

create_mnt_dirs() {
   mkdir -p ${IMAGE_ROOTFS}/mnt/flags
   mkdir -p ${IMAGE_ROOTFS}/mnt/config
   mkdir -p ${IMAGE_ROOTFS}/mnt/cache
   mkdir -p ${IMAGE_ROOTFS}/mnt/root
}

ROOTFS_POSTPROCESS_COMMAND += "create_mnt_dirs;"

#Required for libglib read-only filesystem support
DEPENDS += " qemuwrapper-cross "

IMAGE_FEATURES += " read-only-rootfs "

repository: PelionIoT/meta-mbed-raspberrypi

repo_name: PelionIoT/meta-mbed-raspberrypi


text:
@misc{phd_thesis_template,
  author       = {Tom Pollard and
                  Marvin Reimer and
                  David San and
                  Arco Mul and
                  Matthew Gwynfryn Thomas and
                  Jakub Nowosad and
                  Dennis Weissmann and
                  W. Caleb McDaniel},
  title        = {Template for writing a PhD thesis in Markdown},
  month        = jul,
  year         = 2016,
  doi          = {10.5281/zenodo.58490},
  url          = {https://doi.org/10.5281/zenodo.58490}
}

@article{scikit-learn,
 title={Scikit-learn: Machine Learning in {P}ython},
 author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
         and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
         and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
         Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
 journal={Journal of Machine Learning Research},
 volume={12},
 pages={2825--2830},
 year={2011}
}

@misc{chollet2015keras,
  title={Keras},
  author={Chollet, Fran\c{c}ois and others},
  year={2015},
  howpublished={\url{https://keras.io}},
}

@misc{tensorflow2015-whitepaper,
title={ {TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems},
url={https://www.tensorflow.org/},
note={Software available from tensorflow.org},
author={
    Mart\'{\i}n~Abadi and
    Ashish~Agarwal and
    Paul~Barham and
    Eugene~Brevdo and
    Zhifeng~Chen and
    Craig~Citro and
    Greg~S.~Corrado and
    Andy~Davis and
    Jeffrey~Dean and
    Matthieu~Devin and
    Sanjay~Ghemawat and
    Ian~Goodfellow and
    Andrew~Harp and
    Geoffrey~Irving and
    Michael~Isard and
    Yangqing Jia and
    Rafal~Jozefowicz and
    Lukasz~Kaiser and
    Manjunath~Kudlur and
    Josh~Levenberg and
    Dandelion~Man\'{e} and
    Rajat~Monga and
    Sherry~Moore and
    Derek~Murray and
    Chris~Olah and
    Mike~Schuster and
    Jonathon~Shlens and
    Benoit~Steiner and
    Ilya~Sutskever and
    Kunal~Talwar and
    Paul~Tucker and
    Vincent~Vanhoucke and
    Vijay~Vasudevan and
    Fernanda~Vi\'{e}gas and
    Oriol~Vinyals and
    Pete~Warden and
    Martin~Wattenberg and
    Martin~Wicke and
    Yuan~Yu and
    Xiaoqiang~Zheng},
  year={2015},
}

@ARTICLE{nilearn,
AUTHOR={Abraham, Alexandre and Pedregosa, Fabian and Eickenberg, Michael and Gervais, Philippe and Mueller, Andreas and Kossaifi, Jean and Gramfort, Alexandre and Thirion, Bertrand and Varoquaux, Gael},
TITLE={Machine learning for neuroimaging with scikit-learn},
JOURNAL={Frontiers in Neuroinformatics},
VOLUME={8},
PAGES={14},
YEAR={2014},
URL={https://www.frontiersin.org/article/10.3389/fninf.2014.00014},
DOI={10.3389/fninf.2014.00014},
ISSN={1662-5196},
ABSTRACT={Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g. resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.}
}

@article{KONONENKO200189,
title = "Machine learning for medical diagnosis: history, state of the art and perspective",
journal = "Artificial Intelligence in Medicine",
volume = "23",
number = "1",
pages = "89 - 109",
year = "2001",
issn = "0933-3657",
doi = "https://doi.org/10.1016/S0933-3657(01)00077-X",
url = "http://www.sciencedirect.com/science/article/pii/S093336570100077X",
author = "Igor Kononenko",
keywords = "Machine learning, Medical diagnosis, Reliability of prediction, Kirlian camera"
}

@book{Mitchell:1997:ML:541177,
 author = {Mitchell, Thomas M.},
 title = {Machine Learning},
 year = {1997},
 isbn = {0070428077, 9780070428072},
 edition = {1},
 publisher = {McGraw-Hill, Inc.},
 address = {New York, NY, USA},
}

@article{Turing1950,
author = {Turing, A. M.},
title = {I.—Computing Machinery and Intelligence},
journal = {Mind},
volume = {LIX},
number = {236},
pages = {433-460},
year = {1950},
doi = {10.1093/mind/LIX.236.433},
URL = { + http://dx.doi.org/10.1093/mind/LIX.236.433},
eprint = {/oup/backfile/content_public/journal/mind/lix/236/10.1093_mind_lix.236.433/1/433.pdf}
}

@article{DBLP:journals/corr/SamekBMBM15,
  author    = {Wojciech Samek and
               Alexander Binder and
               Gr{\'{e}}goire Montavon and
               Sebastian Bach and
               Klaus{-}Robert M{\"{u}}ller},
  title     = {Evaluating the visualization of what a Deep Neural Network has learned},
  journal   = {CoRR},
  volume    = {abs/1509.06321},
  year      = {2015},
  url       = {http://arxiv.org/abs/1509.06321},
  archivePrefix = {arXiv},
  eprint    = {1509.06321},
  timestamp = {Wed, 07 Jun 2017 14:42:56 +0200},
  biburl    = {http://dblp.org/rec/bib/journals/corr/SamekBMBM15},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}

@book{Bishop:2006:PRM:1162264,
 author = {Bishop, Christopher M.},
 title = {Pattern Recognition and Machine Learning (Information Science and Statistics)},
 year = {2006},
 isbn = {0387310738},
 publisher = {Springer-Verlag New York, Inc.},
 address = {Secaucus, NJ, USA},
}

@book{KuhnBook2013,
    address = {New York, Heidelberg, Dordrecht, London},
    author = {Kuhn, Max and Johnson, Kjell},
    keywords = {modelling, prediction, r},
    publisher = {Springer},
    title = {Applied Predictive Modeling},
    year = {2013}
}

@INPROCEEDINGS{Vellido12makingmachine,
    author = {Alfredo Vellido and José D. Martín-Guerrero and Paulo J. G. Lisboa},
    title = {Making machine learning models interpretable},
    booktitle = {IN PROC. EUROPEAN SYMPOSIUM ON ARTIFICIAL NEURAL NETWORKS, COMPUTATIONAL INTELLIGENCE AND MACHINE LEARNING},
    year = {2012},
    publisher = {}
}

@inproceedings{Boser:1992:TAO:130385.130401,
 author = {Boser, Bernhard E. and Guyon, Isabelle M. and Vapnik, Vladimir N.},
 title = {A Training Algorithm for Optimal Margin Classifiers},
 booktitle = {Proceedings of the Fifth Annual Workshop on Computational Learning Theory},
 series = {COLT '92},
 year = {1992},
 isbn = {0-89791-497-X},
 location = {Pittsburgh, Pennsylvania, USA},
 pages = {144--152},
 numpages = {9},
 url = {http://doi.acm.org/10.1145/130385.130401},
 doi = {10.1145/130385.130401},
 acmid = {130401},
 publisher = {ACM},
 address = {New York, NY, USA},
}

@article{abide_dataset,
  author = {Di Martino, A. and Yan, C-G G. and Li, Q. and Denio, E. and Castellanos, F. X. and Alaerts, K. and Anderson, J. S. and Assaf, M. and Bookheimer, S. Y. and Dapretto, M. and Deen, B. and Delmonte, S. and Dinstein, I. and Ertl-Wagner, B. and Fair, D. A. and Gallagher, L. and Kennedy, D. P. and Keown, C. L. and Keysers, C. and Lainhart, J. E. and Lord, C. and Luna, B. and Menon, V. and Minshew, N. J. and Monk, C. S. and Mueller, S. and M\"{u}ller, R-A A. and Nebel, M. B. and Nigg, J. T. and O'Hearn, K. and Pelphrey, K. A. and Peltier, S. J. and Rudie, J. D. and Sunaert, S. and Thioux, M. and Tyszka, J. M. and Uddin, L. Q. and Verhoeven, J. S. and Wenderoth, N. and Wiggins, J. L. and Mostofsky, S. H. and Milham, M. P.},
  day = {18},
  doi = {10.1038/mp.2013.78},
  issn = {1476-5578},
  journal = {Molecular psychiatry},
  keywords = {abide, autism, resting-state},
  month = jun,
  number = {6},
  pages = {659--667},
  pmid = {23774715},
  posted-at = {2013-09-19 22:24:23},
  priority = {0},
  publisher = {Nature Publishing Group},
  title = {{The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.}},
  url = {http://dx.doi.org/10.1038/mp.2013.78},
  volume = {19},
  year = {2014}
}

@online{abide_preprocessed_qa_site,
url={http://preprocessed-connectomes-project.org/abide/quality_assessment.html},
title={{ABIDE Preprocessed - QA}},
urldate = {2018-04-28}
}

@online{abide_preprocessed_pipelines_site,
url={http://preprocessed-connectomes-project.org/abide/Pipelines.html},
title={{ABIDE Preprocessed - Pipelines}},
urldate = {2018-04-28}
}

@online{abide_preprocessed_download_site,
url={http://preprocessed-connectomes-project.org/abide/download.html},
title={{ABIDE Preprocessed - Download}},
urldate = {2018-04-28}
}

@online{nilearn_conn_comparison,
url={https://nilearn.github.io/auto_examples/03_connectivity/plot_group_level_connectivity.html#sphx-glr-auto-examples-03-connectivity-plot-group-level-connectivity-py},
title={{Functional connectivity matrices for group analysis of connectomes}},
urldate = {2018-04-28}
}

@ARTICLE{neuro_preprocessing,
 author={Craddock, Cameron  and  Benhajali, Yassine  and  Chu, Carlton  and  Chouinard, Francois  and  Evans, Alan  and  Jakab, Andr?s  and  Khundrakpam, Budhachandra Singh  and  Lewis, John David  and  Li, Qingyang  and  Milham, Michael  and  Yan, Chaogan  and  Bellec, Pierre},
 title={The Neuro Bureau Preprocessing Initiative: open sharing of preprocessed neuroimaging data and derivatives},
 journal={Frontiers in Neuroinformatics},
 volume={},
 year={2013},
 number={41},
 url={http://www.frontiersin.org/neuroinformatics/10.3389/conf.fninf.2013.09.00041/full},
 doi={10.3389/conf.fninf.2013.09.00041},
 issn={1662-5196},
 abstract={}
}

@article{SMITH2011875,
title = "Network modelling methods for FMRI",
journal = "NeuroImage",
volume = "54",
number = "2",
pages = "875 - 891",
year = "2011",
issn = "1053-8119",
doi = "https://doi.org/10.1016/j.neuroimage.2010.08.063",
url = "http://www.sciencedirect.com/science/article/pii/S1053811910011602",
author = "Stephen M. Smith and Karla L. Miller and Gholamreza Salimi-Khorshidi and Matthew Webster and Christian F. Beckmann and Thomas E. Nichols and Joseph D. Ramsey and Mark W. Woolrich",
keywords = "Network modelling, FMRI, Causality"
}

@article{VAROQUAUX2013405,
title = "Learning and comparing functional connectomes across subjects",
journal = "NeuroImage",
volume = "80",
pages = "405 - 415",
year = "2013",
note = "Mapping the Connectome",
issn = "1053-8119",
doi = "https://doi.org/10.1016/j.neuroimage.2013.04.007",
url = "http://www.sciencedirect.com/science/article/pii/S1053811913003340",
author = "Gaël Varoquaux and R. Cameron Craddock",
keywords = "Functional connectivity, Connectome, Group study, Effective connectivity, fMRI, Resting-state"
}

@InProceedings{tangent_connectivity,
author="Varoquaux, Ga{\"e}l
and Baronnet, Flore
and Kleinschmidt, Andreas
and Fillard, Pierre
and Thirion, Bertrand",
editor="Jiang, Tianzi
and Navab, Nassir
and Pluim, Josien P. W.
and Viergever, Max A.",
title="Detection of Brain Functional-Connectivity Difference in Post-stroke Patients Using Group-Level Covariance Modeling",
booktitle="Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2010",
year="2010",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="200--208",
abstract="Functional brain connectivity, as revealed through distant correlations in the signals measured by functional Magnetic Resonance Imaging (fMRI), is a promising source of biomarkers of brain pathologies. However, establishing and using diagnostic markers requires probabilistic inter-subject comparisons. Principled comparison of functional-connectivity structures is still a challenging issue. We give a new matrix-variate probabilistic model suitable for inter-subject comparison of functional connectivity matrices on the manifold of Symmetric Positive Definite (SPD) matrices. We show that this model leads to a new algorithm for principled comparison of connectivity coefficients between pairs of regions. We apply this model to comparing separately post-stroke patients to a group of healthy controls. We find neurologically-relevant connection differences and show that our model is more sensitive that the standard procedure. To the best of our knowledge, these results are the first report of functional connectivity differences between a single-patient and a group and thus establish an important step toward using functional connectivity as a diagnostic tool.",
isbn="978-3-642-15705-9"
}

@article{what_is_autism_like,
author = {Uta Frith and Francesca Happé},
title = {Theory of Mind and Self‐Consciousness: What Is It Like to Be Autistic?},
year="2002",
journal = {Mind \& Language},
volume = {14},
number = {1},
pages = {82-89},
doi = {10.1111/1468-0017.00100},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1468-0017.00100},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/1468-0017.00100},
abstract = {Autism provides a model for exploring the nature of self‐consciousness: self‐consciousness requires the ability to reflect on mental states, and autism is a disorder with a specific impairment in the neurocognitive mechanism underlying this ability. Experimental studies of normal and abnormal development suggest that the abilities to attribute mental states to self and to others are closely related. Thus inability to pass standard ‘theory of mind’ tests, which refer to others’ false beliefs, may imply lack of self‐consciousness. Individuals who persistently fail these tests may, in the extreme, be unable to reflect on their intentions or to anticipate their own actions. In contrast, individuals with high‐functioning autism or Asperger syndrome often possess a late‐acquired, explicit theory of mind, which appears to be the result of effortful learning. An experimental study with three people with Asperger syndrome suggested that level of performance on standard theory of mind tasks was strongly related to the ability to engage in introspection. Qualitative differences in the introspections of high‐functioning people with autism are also reflected in autobiographical accounts which may give a glimpse of what it is like to be autistic.}
}

@Inbook{Dietterich2000,
author="Dietterich, Thomas G.",
title="Ensemble Methods in Machine Learning",
bookTitle="Multiple Classifier Systems: First International Workshop, MCS 2000 Cagliari, Italy, June 21--23, 2000 Proceedings",
year="2000",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="1--15",
abstract="Ensemble methods are learning algorithms that construct a set of classifiers and then classify new data points by taking a (weighted) vote of their predictions. The original ensemble method is Bayesian averaging, but more recent algorithms include error-correcting output coding, Bagging, and boosting. This paper reviews these methods and explains why ensembles can often perform better than any single classifier. Some previous studies comparing ensemble methods are reviewed, and some new experiments are presented to uncover the reasons that Adaboost does not overfit rapidly.",
isbn="978-3-540-45014-6",
doi="10.1007/3-540-45014-9_1",
url="https://doi.org/10.1007/3-540-45014-9_1"
}

@book{american2013diagnostic,
  title={Diagnostic and Statistical Manual of Mental Disorders: Dsm-5},
  author={{American Psychiatric Association}},
  isbn={9780890425541},
  lccn={2013011061},
  series={Diagnostic and Statistical Manual of Mental Disorders},
  url={https://books.google.co.uk/books?id=EIbMlwEACAAJ},
  year={2013},
  publisher={Amer Psychiatric Pub Incorporated}
}

@article{doi:10.1056/NEJMp1306380,
  author = {Jeffrey P. Baker},
  title = {Autism at 70 — Redrawing the Boundaries},
  journal = {New England Journal of Medicine},
  volume = {369},
  number = {12},
  pages = {1089-1091},
  year = {2013},
  doi = {10.1056/NEJMp1306380},
  note ={PMID: 24047057},
  URL = {https://doi.org/10.1056/NEJMp1306380},
  eprint = {https://doi.org/10.1056/NEJMp1306380}
}

@book{abnormalPsychology,
  author ={Ronald J. Comer},
  title={Fundamentals of Abnormal Psychology},
  year={2016},
  pages={457},
  isbn={9781464176975},
  publisher={Macmillan Learning}
}

@article{TAGERFLUSBERG20101072,
title = "The origins of social impairments in autism spectrum disorder: Studies of infants at risk",
journal = "Neural Networks",
volume = "23",
number = "8",
pages = "1072 - 1076",
year = "2010",
note = "Social Cognition: From Babies to Robots",
issn = "0893-6080",
doi = "https://doi.org/10.1016/j.neunet.2010.07.008",
url = "http://www.sciencedirect.com/science/article/pii/S0893608010001474",
author = "Helen Tager-Flusberg",
keywords = "Autism spectrum disorder, Social impairment, Infants at risk, Endophenotype"
}

@article{premack_woodruff_1978,
  title={Does the chimpanzee have a theory of mind?},
  volume={1},
  DOI={10.1017/S0140525X00076512},
  number={4},
  journal={Behavioral and Brain Sciences},
  publisher={Cambridge University Press},
  author={Premack, David and Woodruff, Guy},
  year={1978},
  pages={515–526}
}

@article{mirrorneuronsystem,
  author = {Giacomo Rizzolatti and Laila Craighero},
  title = {The Mirror-Neuron System},
  journal = {Annual Review of Neuroscience},
  volume = {27},
  number = {1},
  pages = {169-192},
  year = {2004},
  doi = {10.1146/annurev.neuro.27.070203.144230},
  note ={PMID: 15217330},
  URL = {https://doi.org/10.1146/annurev.neuro.27.070203.144230},
  eprint = {https://doi.org/10.1146/annurev.neuro.27.070203.144230},
  abstract = {A category of stimuli of great importance for primates, humans in particular, is that formed by actions done by other individuals. If we want to survive, we must understand the actions of others. Furthermore, without action understanding, social organization is impossible. In the case of humans, there is another faculty that depends on the observation of others' actions: imitation learning. Unlike most species, we are able to learn by imitation, and this faculty is at the basis of human culture. In this review we present data on a neurophysiological mechanism—the mirror-neuron mechanism—that appears to play a fundamental role in both action understanding and imitation. We describe first the functional properties of mirror neurons in monkeys. We review next the characteristics of the mirror-neuron system in humans. We stress, in particular, those properties specific to the human mirror-neuron system that might explain the human capacity to learn by imitation. We conclude by discussing the relationship between the mirror-neuron system and language.}
}

@book{cognitive_neuroscience_ward,
  author ={Jamie Ward},
  title={The Student's Guide to Cognitive Neuroscience},
  year={2006},
  isbn={9781848722729},
  publisher={Psychology Press}
}

@article{ASSAF2010247,
title = "Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients",
journal = "NeuroImage",
volume = "53",
number = "1",
pages = "247 - 256",
year = "2010",
issn = "1053-8119",
doi = "https://doi.org/10.1016/j.neuroimage.2010.05.067",
url = "http://www.sciencedirect.com/science/article/pii/S1053811910008013",
author = "Michal Assaf and Kanchana Jagannathan and Vince D. Calhoun and Laura Miller and Michael C. Stevens and Robert Sahl and Jacqueline G. O'Boyle and Robert T. Schultz and Godfrey D. Pearlson",
keywords = "Independent component analysis, Functional MRI, Resting state, Default mode network, High-functioning autism"
}

@article{baron-cohen_ring_moriarty_schmitz_costa_ell_1994,
  title={Recognition of Mental State Terms: Clinical Findings in Children with Autism and a Functional Neuroimaging Study of Normal Adults},
  volume={165},
  DOI={10.1192/bjp.165.5.640},
  number={5},
  journal={British Journal of Psychiatry},
  publisher={Cambridge University Press},
  author={Baron-Cohen, Simon and Ring, Howard and Moriarty, John and Schmitz, Bettina and Costa, Durval and Ell, Peter},
  year={1994},
  pages={640–649}
}

@article{doi:10.1111/j.1469-7610.1991.tb00351.x,
author = {Sally Ozonoff and Bruce F. Pennington and Sally J. Rogers},
title = {Executive Function Deficits in High‐Functioning Autistic Individuals: Relationship to Theory of Mind},
journal = {Journal of Child Psychology and Psychiatry},
year={1991},
volume = {32},
number = {7},
pages = {1081-1105},
keywords = {Autism, executive function, theory of mind},
doi = {10.1111/j.1469-7610.1991.tb00351.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1469-7610.1991.tb00351.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1469-7610.1991.tb00351.x},
abstract = {Abstract A group of high‐functioning autistic individuals was compared to a clinical control group matched on VTQ, age, sex and SES. Significant group differences were found on executive function, theory of mind, emotion perception and verbal memory tests, but not on spatial or other control measures. Second‐order theory of mind and executive function deficits were widespread among the autistic group, while first‐order theory of mind deficits were found in only a subset of the sample. The relationship of executive function and theory of mind deficits to each other, and their primacy to autism, are discussed.}
}

@article{joseph_tager-flusberg_2004,
  title={The relationship of theory of mind and executive functions to symptom type and severity in children with autism},
  volume={16},
  DOI={10.1017/S095457940404444X},
  number={1},
  journal={Development and Psychopathology},
  publisher={Cambridge University Press},
  author={Joseph, Robert M. and Tager–Flusberg, Helen},
  year={2004},
  pages={137–155}
}

@article{FRITH1994115,
title = {Autism: beyond "theory of mind"},
journal = "Cognition",
volume = "50",
number = "1",
pages = "115 - 132",
year = "1994",
issn = "0010-0277",
doi = "https://doi.org/10.1016/0010-0277(94)90024-8",
url = "http://www.sciencedirect.com/science/article/pii/0010027794900248",
author = "Uta Frith and Francesca Happé"
}

@article {Yahata2016,
	title = {A small number of abnormal brain connections predicts adult autism spectrum disorder},
	author = {Yahata, Noriaki and Morimoto, Jun and Hashimoto, Ryuichiro and Lisi, Giuseppe and Shibata, Kazuhisa and Kawakubo, Yuki and Kuwabara, Hitoshi and Kuroda, Miho and Yamada, Takashi and Megumi, Fukuda and Imamizu, Hiroshi and Náñez, José E and Takahashi, Hidehiko and Okamoto, Yasumasa and Kasai, Kiyoto and Kato, Nobumasa and Sasaki, Yuka and Watanabe, Takeo and Kawato, Mitsuo},
	doi = {10.1038/ncomms11254},
	volume = {7},
	month = {April},
	year = {2016},
	journal = {Nature Communications},
	issn = {2041-1723},
	pages = {11254},
	url = {https://www.nature.com/articles/ncomms11254#supplementary-information},
}

@article{Nylander2013,
  author = {Lena Nylander and Maria Holmqvist and Lars Gustafson and Christopher Gillberg},
  title = {Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) in adult psychiatry. A 20-year register study},
  journal = {Nordic Journal of Psychiatry},
  volume = {67},
  number = {5},
  pages = {344-350},
  year  = {2013},
  publisher = {Taylor & Francis},
  doi = {10.3109/08039488.2012.748824},
  url = {https://doi.org/10.3109/08039488.2012.748824},
  eprint = {https://doi.org/10.3109/08039488.2012.748824}
}

@article{Mandell2007,
  author="Mandell, David S.
  and Ittenbach, Richard F.
  and Levy, Susan E.
  and Pinto-Martin, Jennifer A.",
  title="Disparities in Diagnoses Received Prior to a Diagnosis of Autism Spectrum Disorder",
  journal="Journal of Autism and Developmental Disorders",
  year="2007",
  month="Oct",
  day="01",
  volume="37",
  number="9",
  pages="1795--1802",
  abstract="This study estimated differences by ethnicity in the diagnoses assigned prior to the diagnosis of autism. In this sample of 406 Medicaid-eligible children, African-Americans were 2.6 times less likely than white children to receive an autism diagnosis on their first specialty care visit. Among children who did not receive an autism diagnosis on their first visit, ADHD was the most common diagnosis. African-American children were 5.1 times more likely than white children to receive a diagnosis of adjustment disorder than of ADHD, and 2.4 times more likely to receive a diagnosis of conduct disorder than of ADHD. Differences in diagnostic patterns by ethnicity suggest possible variations in parents' descriptions of symptoms, clinician interpretations and expectations, or symptom presentation.",
  issn="1573-3432",
  doi="10.1007/s10803-006-0314-8",
  url="https://doi.org/10.1007/s10803-006-0314-8"
}

@article{Lord2000,
author="Lord, Catherine
and Risi, Susan
and Lambrecht, Linda
and Cook, Edwin H.
and Leventhal, Bennett L.
and DiLavore, Pamela C.
and Pickles, Andrew
and Rutter, Michael",
title="The Autism Diagnostic Observation Schedule---Generic: A Standard Measure of Social and Communication Deficits Associated with the Spectrum of Autism",
journal="Journal of Autism and Developmental Disorders",
year="2000",
month="Jun",
day="01",
volume="30",
number="3",
pages="205--223",
abstract="The Autism Diagnostic Observation Schedule---Generic (ADOS-G) is a semistructured, standardized assessment of social interaction, communication, play, and imaginative use of materials for individuals suspected of having autism spectrum disorders. The observational schedule consists of four 30-minute modules, each designed to be administered to different individuals according to their level of expressive language. Psychometric data are presented for 223 children and adults with Autistic Disorder (autism), Pervasive Developmental Disorder Not Otherwise Specified (PDDNOS) or nonspectrum diagnoses. Within each module, diagnostic groups were equivalent on expressive language level. Results indicate substantial interrater and test---retest reliability for individual items, excellent interrater reliability within domains and excellent internal consistency. Comparisons of means indicated consistent differentiation of autism and PDDNOS from nonspectrum individuals, with some, but less consistent, differentiation of autism from PDDNOS. A priori operationalization of DSM-IV/ICD-10 criteria, factor analyses, and ROC curves were used to generate diagnostic algorithms with thresholds set for autism and broader autism spectrum/PDD. Algorithm sensitivities and specificities for autism and PDDNOS relative to nonspectrum disorders were excellent, with moderate differentiation of autism from PDDNOS.",
issn="1573-3432",
doi="10.1023/A:1005592401947",
url="https://doi.org/10.1023/A:1005592401947"
}

@Article{Lord1994,
author="Lord, Catherine
and Rutter, Michael
and Le Couteur, Ann",
title="Autism Diagnostic Interview-Revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders",
journal="Journal of Autism and Developmental Disorders",
year="1994",
month="Oct",
day="01",
volume="24",
number="5",
pages="659--685",
abstract="Describes the Autism Diagnostic Interview-Revised (ADI-R), a revision of the Autism Diagnostic Interview, a semistructured, investigator-based interview for caregivers of children and adults for whom autism or pervasive developmental disorders is a possible diagnosis. The revised interview has been reorganized, shortened, modified to be appropriate for children with mental ages from about 18 months into adulthood and linked to ICD-10 and DSM-IV criteria. Psychometric data are presented for a sample of preschool children.",
issn="1573-3432",
doi="10.1007/BF02172145",
url="https://doi.org/10.1007/BF02172145"
}

@article {Ogawa9868,
	author = {Ogawa, S and Lee, T M and Kay, A R and Tank, D W},
	title = {Brain magnetic resonance imaging with contrast dependent on blood oxygenation},
	volume = {87},
	number = {24},
	pages = {9868--9872},
	year = {1990},
	doi = {10.1073/pnas.87.24.9868},
	publisher = {National Academy of Sciences},
	abstract = {Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradient-echo techniques in high fields, we demonstrate in vivo images of brain microvasculature with image contrast reflecting the blood oxygen level. This blood oxygenation level-dependent (BOLD) contrast follows blood oxygen changes induced by anesthetics, by insulin-induced hypoglycemia, and by inhaled gas mixtures that alter metabolic demand or blood flow. The results suggest that BOLD contrast can be used to provide in vivo real-time maps of blood oxygenation in the brain under normal physiological conditions. BOLD contrast adds an additional feature to magnetic resonance imaging and complements other techniques that are attempting to provide positron emission tomography-like measurements related to regional neural activity.},
	issn = {0027-8424},
	URL = {http://www.pnas.org/content/87/24/9868},
	eprint = {http://www.pnas.org/content/87/24/9868.full.pdf},
	journal = {Proceedings of the National Academy of Sciences}
}

@article {Raichle676,
	author = {Raichle, Marcus E. and MacLeod, Ann Mary and Snyder, Abraham Z. and Powers, William J. and Gusnard, Debra A. and Shulman, Gordon L.},
	title = {A default mode of brain function},
	volume = {98},
	number = {2},
	pages = {676--682},
	year = {2001},
	doi = {10.1073/pnas.98.2.676},
	publisher = {National Academy of Sciences},
	abstract = {A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors. OEF,oxygen extraction fraction;fMRI,functional MRI;PET,positron-emission tomography;CBF,cerebral blood flow;CMRO2,cerebral metabolic rate for oxygen;MPFC,medial prefrontal cortex},
	issn = {0027-8424},
	URL = {http://www.pnas.org/content/98/2/676},
	eprint = {http://www.pnas.org/content/98/2/676.full.pdf},
	journal = {Proceedings of the National Academy of Sciences}
}

@article {Matthews2006,
	Title = {Applications of fMRI in translational medicine and clinical practice},
	Author = {Matthews, Paul M and Honey, Garry D and Bullmore, Edward T},
	DOI = {10.1038/nrn1929},
	Number = {9},
	Volume = {7},
	Month = {September},
	Year = {2006},
	Journal = {Nature reviews. Neuroscience},
	ISSN = {1471-003X},
	Pages = {732—744},
	URL = {https://doi.org/10.1038/nrn1929},
}

@ARTICLE{10.3389/fnsys.2010.00019,
AUTHOR={Fox, Michael and Greicius, Michael},
TITLE={Clinical applications of resting state functional connectivity},
JOURNAL={Frontiers in Systems Neuroscience},
VOLUME={4},
PAGES={19},
YEAR={2010},
URL={https://www.frontiersin.org/article/10.3389/fnsys.2010.00019},
DOI={10.3389/fnsys.2010.00019},
ISSN={1662-5137},
ABSTRACT={During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of fMRI.  The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI) and has the potential to greatly increase the translation of fMRI into clinical care.  In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations.  We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm.}
}

@article{SMITH2004S208,
title = "Advances in functional and structural MR image analysis and implementation as FSL",
journal = "NeuroImage",
volume = "23",
pages = "S208 - S219",
year = "2004",
note = "Mathematics in Brain Imaging",
issn = "1053-8119",
doi = "https://doi.org/10.1016/j.neuroimage.2004.07.051",
url = "http://www.sciencedirect.com/science/article/pii/S1053811904003933",
author = "Stephen M. Smith and Mark Jenkinson and Mark W. Woolrich and Christian F. Beckmann and Timothy E.J. Behrens and Heidi Johansen-Berg and Peter R. Bannister and Marilena De Luca and Ivana Drobnjak and David E. Flitney and Rami K. Niazy and James Saunders and John Vickers and Yongyue Zhang and Nicola De Stefano and J. Michael Brady and Paul M. Matthews",
keywords = "FMRI, Structural MR image analysis, FSL"
}

@article{POWER20122142,
title = "Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion",
journal = "NeuroImage",
volume = "59",
number = "3",
pages = "2142 - 2154",
year = "2012",
issn = "1053-8119",
doi = "https://doi.org/10.1016/j.neuroimage.2011.10.018",
url = "http://www.sciencedirect.com/science/article/pii/S1053811911011815",
author = "Jonathan D. Power and Kelly A. Barnes and Abraham Z. Snyder and Bradley L. Schlaggar and Steven E. Petersen",
keywords = "fMRI, fcMRI, Resting state, Network, Motion, Movement, Artifact, Noise"
}

@article{JENKINSON2002825,
title = "Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images",
journal = "NeuroImage",
volume = "17",
number = "2",
pages = "825 - 841",
year = "2002",
issn = "1053-8119",
doi = "https://doi.org/10.1006/nimg.2002.1132",
url = "http://www.sciencedirect.com/science/article/pii/S1053811902911328",
author = "Mark Jenkinson and Peter Bannister and Michael Brady and Stephen Smith",
keywords = "accuracy, affine transformation, global optimization, motion correction, multimodal registration, multiresolution search, robustness"
}

@article{HEINSFELD201816,
title = "Identification of autism spectrum disorder using deep learning and the ABIDE dataset",
journal = "NeuroImage: Clinical",
volume = "17",
pages = "16 - 23",
year = "2018",
issn = "2213-1582",
doi = "https://doi.org/10.1016/j.nicl.2017.08.017",
url = "http://www.sciencedirect.com/science/article/pii/S2213158217302073",
author = "Anibal Sólon Heinsfeld and Alexandre Rosa Franco and R. Cameron Craddock and Augusto Buchweitz and Felipe Meneguzzi",
keywords = "Autism, fMRI, ABIDE, Resting state, Deep learning"
}

@article{LEDOIT2004365,
title = "A well-conditioned estimator for large-dimensional covariance matrices",
journal = "Journal of Multivariate Analysis",
volume = "88",
number = "2",
pages = "365 - 411",
year = "2004",
issn = "0047-259X",
doi = "https://doi.org/10.1016/S0047-259X(03)00096-4",
url = "http://www.sciencedirect.com/science/article/pii/S0047259X03000964",
author = "Olivier Ledoit and Michael Wolf",
keywords = "Condition number, Covariance matrix estimation, Empirical Bayes, General asymptotics, Shrinkage"
}

@article{Cawley:2010:OMS:1756006.1859921,
 author = {Cawley, Gavin C. and Talbot, Nicola L.C.},
 title = {On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation},
 journal = {J. Mach. Learn. Res.},
 issue_date = {3/1/2010},
 volume = {11},
 month = aug,
 year = {2010},
 issn = {1532-4435},
 pages = {2079--2107},
 numpages = {29},
 url = {http://dl.acm.org/citation.cfm?id=1756006.1859921},
 acmid = {1859921},
 publisher = {JMLR.org},
}

repository: davejm/dissertation-report

repo_name: davejm/dissertation-report


text:
SUMMARY = "Documentation generator for glib-based software"
DESCRIPTION = "Gtk-doc is a set of scripts that extract specially formatted comments \
               from glib-based software and produce a set of html documentation files from them"
HOMEPAGE = "http://www.gtk.org/gtk-doc/"
LICENSE = "GPLv2"
LIC_FILES_CHKSUM = "file://COPYING;md5=94d55d512a9ba36caa9b7df079bae19f"

inherit gnomebase

inherit debian-package
require recipes-debian/sources/gtk-doc.inc
FILESEXTRAPATHS =. "${FILE_DIRNAME}/gtk-doc:${COREBASE}/meta/recipes-gnome/gtk-doc/files/:"

# Configure the scripts correctly (and build their dependencies) only if they are actually
# going to be used; otheriwse we need only the m4/makefile includes from the gtk-doc tarball.
PACKAGECONFIG ??= "${@bb.utils.contains("DISTRO_FEATURES", "api-documentation", "working-scripts", "", d)}"

# This will cause target gtk-doc to hardcode paths of native dependencies
# into its scripts. This means that target gtk-doc package is broken;
# hopefully no one minds because its scripts are not used for anything during build
# and shouldn't be used on targets.
PACKAGECONFIG[working-scripts] = "--with-highlight=source-highlight,--with-highlight=no,libxslt-native xmlto-native source-highlight-native python3-six"
PACKAGECONFIG[tests] = "--enable-tests,--disable-tests,glib-2.0"

SRC_URI += "file://0001-Do-not-hardocode-paths-to-perl-python-in-scripts.patch \
           file://0001-Do-not-error-out-if-xsltproc-is-not-found.patch \
           file://conditionaltests.patch \
           file://no-clobber.patch \
           "
SRC_URI_append_class-native = " file://pkg-config-native.patch"

BBCLASSEXTEND = "native nativesdk"

# Do not check for XML catalogs when building because that
# information is not used for anything during build. Recipe
# dependencies make sure we have all the right bits.
do_configure_prepend() {
        sed -i -e 's,^JH_CHECK_XML_CATALOG.*,,' ${S}/configure.ac
}

FILES_${PN} += "${datadir}/sgml"
FILES_${PN}-dev += "${libdir}/cmake"
FILES_${PN}-doc = ""

SYSROOT_PREPROCESS_FUNCS_append_class-native = " gtkdoc_makefiles_sysroot_preprocess"
gtkdoc_makefiles_sysroot_preprocess() {
        # Patch the gtk-doc makefiles so that the qemu wrapper is used to run transient binaries
        # instead of libtool wrapper or running them directly
        sed -i \
           -e "s|GTKDOC_RUN =.*|GTKDOC_RUN = \$(top_builddir)/gtkdoc-qemuwrapper|" \
           ${SYSROOT_DESTDIR}${datadir}/gtk-doc/data/gtk-doc*make
}

repository: meta-debian/meta-debian

repo_name: meta-debian/meta-debian

branch_name: refs/heads/warrior