cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr38635.v1
title: Federal Justice Statistics Program: Charges Filed Against Defendants in Criminal Cases in District Court, 2021
title: Version 1

description: The data contain records of charges filed against defendants whose cases were filed by United States attorneys in United States district court during fiscal year 2021. The data are charge-level records, and more than one charge may be filed against a single defendant. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central Charge file. The charge-level data may be linked to defendant-level data (extracted from the EOUSA Central System file) through the CS_SEQ variable, and it should be noted that some defendants may not have any charges other than the lead charge appearing on the defendant-level record. The Central Charge and Central System data contain variables from the original EOUSA files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Charges Filed Against Defendants in Criminal Cases in District Court, 2021
description: Charges filed against defendants in United States district court during fiscal year 2021.
DOI: 10.5281/zenodo.7407195
title: VIGET: A web portal for study of vaccine-induced host responses based on Reactome pathways and ImmPort data

description: Host responses to vaccines are complex but important to investigate. To facilitate the study, we have developed a tool called Vaccine Induced Gene Expression Analysis Tool (VIGET), with the aim to provide an interactive online tool for users to efficiently and robustly analyze the host immune response gene expression data collected in the ImmPort database. VIGET allows users to select vaccines, choose ImmPort studies, set up analysis models by choosing confounding variables and two groups of samples having different vaccination times, and then perform differential expression analysis to select genes for pathway enrichment analysis and functional interaction network construction using the Reactome’s web services. VIGET provides features for users to compare results from two analyses, facilitating comparative response analysis across different demographic groups. VIGET uses the Vaccine Ontology (VO) to classify various types of vaccines such as live or inactivated flu vaccines, yellow fever vaccines, etc. Different variables are classified using our Vaccine Investigation Ontology (VIO). To showcase the utilities of VIGET, we conducted a longitudinal analysis of immune responses to yellow fever vaccines and found an intriguing complex activity response pattern of pathways in the immune system annotated in Reactome, demonstrating that VIGET is a valuable web portal that supports effective vaccine response studies using Reactome pathways and ImmPort data. The portal has been deployed at https://viget.violinet.org/.
DOI: 10.5281/zenodo.7407194
title: VIGET: A web portal for study of vaccine-induced host responses based on Reactome pathways and ImmPort data

description: Host responses to vaccines are complex but important to investigate. To facilitate the study, we have developed a tool called Vaccine Induced Gene Expression Analysis Tool (VIGET), with the aim to provide an interactive online tool for users to efficiently and robustly analyze the host immune response gene expression data collected in the ImmPort database. VIGET allows users to select vaccines, choose ImmPort studies, set up analysis models by choosing confounding variables and two groups of samples having different vaccination times, and then perform differential expression analysis to select genes for pathway enrichment analysis and functional interaction network construction using the Reactome’s web services. VIGET provides features for users to compare results from two analyses, facilitating comparative response analysis across different demographic groups. VIGET uses the Vaccine Ontology (VO) to classify various types of vaccines such as live or inactivated flu vaccines, yellow fever vaccines, etc. Different variables are classified using our Vaccine Investigation Ontology (VIO). To showcase the utilities of VIGET, we conducted a longitudinal analysis of immune responses to yellow fever vaccines and found an intriguing complex activity response pattern of pathways in the immune system annotated in Reactome, demonstrating that VIGET is a valuable web portal that supports effective vaccine response studies using Reactome pathways and ImmPort data. The portal has been deployed at https://viget.violinet.org/.
DOI: 10.6084/m9.figshare.22337880
title: Data model 3 from Innovation across 13 ungulate species: problem solvers are less integrated in the social group and less neophobic

description: Data for model 3
DOI: 10.6084/m9.figshare.22337880.v1
title: Data model 3 from Innovation across 13 ungulate species: problem solvers are less integrated in the social group and less neophobic

description: Data for model 3
DOI: 10.6084/m9.figshare.22337883
title: Data model 1 from Innovation across 13 ungulate species: problem solvers are less integrated in the social group and less neophobic

description: Data for model 1
DOI: 10.6084/m9.figshare.22337883.v1
title: Data model 1 from Innovation across 13 ungulate species: problem solvers are less integrated in the social group and less neophobic

description: Data for model 1
DOI: 10.6084/m9.figshare.22337889
title: Script from Innovation across 13 ungulate species: problem solvers are less integrated in the social group and less neophobic

description: Script to make the models of the statistical analysis
DOI: 10.6084/m9.figshare.22337889.v2
title: Script from Innovation across 13 ungulate species: problem solvers are less integrated in the social group and less neophobic

description: Script to make the models of the statistical analysis
DOI: 10.6084/m9.figshare.22337892.v1
title: Data model 2 from Innovation across 13 ungulate species: problem solvers are less integrated in the social group and less neophobic

description: Data for model 2
DOI: 10.6084/m9.figshare.22337892
title: Data model 2 from Innovation across 13 ungulate species: problem solvers are less integrated in the social group and less neophobic

description: Data for model 2
DOI: 10.6084/m9.figshare.22337889.v1
title: Script from Innovation across 13 ungulate species: problem solvers are less integrated in the social group and less neophobic

description: Script to make the models of the statistical analysis
DOI: 10.3886/icpsr38628.v1
title: Federal Justice Statistics Program: Criminal Appeals Cases in Courts of Appeals - Terminated, 2021
title: Version 1

description: The data contain records of criminal appeals cases terminated in United States Courts of Appeals during fiscal year 2021. The data were constructed from the Administrative Office of the United States Courts' (AOUSC) Court of Appeals file. These contain variables on the nature of the criminal appeal, the underlying offense, and the disposition of the appeal. An appeal can be filed by the government or the offender, and the appellant can appeal the sentence, the verdict, or both sentence and verdict. Appeals may be terminated on the merits or on procedural grounds. Of those that are terminated on the merits, the district court ruling may be affirmed, reversed, remanded to criminal court, or dismissed. The data file contains variables from the original AOUSC files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Criminal Appeals Cases in Courts of Appeals - Terminated, 2021
description: Criminal appeals cases terminated in United States Courts of Appeals during fiscal year 2021.
DOI: 10.3886/icpsr38628
title: Federal Justice Statistics Program: Criminal Appeals Cases in Courts of Appeals - Terminated, 2021
title: Archival Version

description: The data contain records of criminal appeals cases terminated in United States Courts of Appeals during fiscal year 2021. The data were constructed from the Administrative Office of the United States Courts' (AOUSC) Court of Appeals file. These contain variables on the nature of the criminal appeal, the underlying offense, and the disposition of the appeal. An appeal can be filed by the government or the offender, and the appellant can appeal the sentence, the verdict, or both sentence and verdict. Appeals may be terminated on the merits or on procedural grounds. Of those that are terminated on the merits, the district court ruling may be affirmed, reversed, remanded to criminal court, or dismissed. The data file contains variables from the original AOUSC files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Criminal Appeals Cases in Courts of Appeals - Terminated, 2021
description: Criminal appeals cases terminated in United States Courts of Appeals during fiscal year 2021.
DOI: 10.5281/zenodo.7775772
title: Cold Solar Flares I. Microwave Domain Appendix

description: We present the appendix of the statistical analysis of ~100 solar flares with prominent electron acceleration, ``cold'' flares, in the microwave range.<br> These cold flares are characterized by a weak thermal response relative to nonthermal emission.<br> This work is a follow up of a previous statistical study of cold flares, which focused on hard X-ray emission to quantify the flare nonthermal component. Here we focus on the microwave emission.<br> Thermal response is evaluated by soft X-ray emission observed by GOES X-ray sensors.<br> We obtain spectral parameters of the flare gyrosynchrotron emission and reveal patterns of their temporal evolution.<br> Main results of the previous statistical study are confirmed: as compared to a ``mean'' flare, the cold flares have shorter durations, higher spectral peak frequencies, and harder spectral indices after the spectral peak.<br> Though, there are cold flares with moderate and low peak frequencies.<br> In a majority of cold flares, we find evidence in favor of Razin effect in the microwave spectra indicative of rather dense flaring loops.<br> We discuss obtained results in the context of electron acceleration efficiency. Appendix contains figures and tables with temporal and spectral characteristics of all cold flares analyzed in this work.<br> Figures present microwave dynamic spectra, time profiles in soft X-ray range and temporal evolution of gyrosynchrotron spectral parameters.<br> Tables contain quantifications of the flare microwave and soft X-ray emission, the beginning and the end of the flare impulsive phase, flare helioprojective coordinates, obtained patterns of parameter temporal evolution.
DOI: 10.5281/zenodo.7775771
title: Cold Solar Flares I. Microwave Domain Appendix

description: We present the appendix of the statistical analysis of ~100 solar flares with prominent electron acceleration, ``cold'' flares, in the microwave range.<br> These cold flares are characterized by a weak thermal response relative to nonthermal emission.<br> This work is a follow up of a previous statistical study of cold flares, which focused on hard X-ray emission to quantify the flare nonthermal component. Here we focus on the microwave emission.<br> Thermal response is evaluated by soft X-ray emission observed by GOES X-ray sensors.<br> We obtain spectral parameters of the flare gyrosynchrotron emission and reveal patterns of their temporal evolution.<br> Main results of the previous statistical study are confirmed: as compared to a ``mean'' flare, the cold flares have shorter durations, higher spectral peak frequencies, and harder spectral indices after the spectral peak.<br> Though, there are cold flares with moderate and low peak frequencies.<br> In a majority of cold flares, we find evidence in favor of Razin effect in the microwave spectra indicative of rather dense flaring loops.<br> We discuss obtained results in the context of electron acceleration efficiency. Appendix contains figures and tables with temporal and spectral characteristics of all cold flares analyzed in this work.<br> Figures present microwave dynamic spectra, time profiles in soft X-ray range and temporal evolution of gyrosynchrotron spectral parameters.<br> Tables contain quantifications of the flare microwave and soft X-ray emission, the beginning and the end of the flare impulsive phase, flare helioprojective coordinates, obtained patterns of parameter temporal evolution.
DOI: 10.20363/zfmk-coll.herpetology-2023-02
title: ZFMK Herpetology collection

description: The herpetological collection houses more than 100,000 catalogued specimens. Amphibians and reptiles are traditionally combined in the collection, with the latter making up nearly two thirds of the total specimens. The collection includes type specimens of around 650 taxa, among them more than 300 primary types (i.e. holotypes, lectotypes, and neotypes) and 100 syntypes that objectively define a scientific name and are literally irreplaceable. The majority of specimens is wet material preserved in ethanol, but the collection also includes osteological specimens and (sub-)fossils. These figures make the herpetological collection at the Leibniz Institut for the Analysis of Biodiversity Change - Museum Koenig Bonn one of the largest of its kind in Germany and also one of international importance.  Correspondingly to their high species diversity, frogs and squamates (lizards and snakes) represent the majority of species. However, members of all major groups of amphibians (salamanders and caecilians) and reptiles (crocodiles, turtles, and tuataras) are found in the collection.  There is no explicit geographic focus and specimens are originating not only from Europe, but from more than 200 countries worldwide. Due to the research focus of past curators and students, the ZFMK holds remarkable collections from the Mediterranean, the Middle East, Africa, Madagascar, and Brazil. Recent geographical focuses are Southeast Asia, Peru, and the western Palearctic.
DOI: 10.6084/m9.figshare.22372222
title: ggcaller_output.tar.gz

description: Output from running ggcaller on the sparc dataset. (github repository with full details forthcoming).
DOI: 10.6084/m9.figshare.22372222.v1
title: ggcaller_output.tar.gz

description: Output from running ggcaller on the sparc dataset. (github repository with full details forthcoming).
DOI: 10.5281/zenodo.7782114
title: Model weights and predictions for reproducible benchmarking experiments in MedMNIST v2

description: This data repository is associated with our GitHub code <code>weights_*.zip</code>: PyTorch, AutoKeras and Google AutoML Vision are provided for MedMNIST2D. PyTorch and AutoKeras are provided for MedMNIST3D. If you are using PyTorch model weights, please note that the ResNet18_224 / ResNet50_224 models are trained with images resized to 224 x 224 by <code>PIL.Image.NEAREST</code>. Snapshots for <code>auto-sklearn</code> are not uploaded due to the embarrassingly large model sizes (lots of model ensemble). <code>predictions.zip</code>: We also provide all standard prediction files by PyTorch, auto-sklearn, AutoKeras and Google AutoML Vision, which works with <code>medmnist.Evaluator</code>. Each file is named as <code>{flag}_{split}_[AUC]{auc:.3f}_[ACC]{acc:.3f}@{run}.csv</code>, e.g., <code>bloodmnist_test_[AUC]0.997_[ACC]0.957@autokeras_3.csv</code>.
DOI: 10.5281/zenodo.7782113
title: Model weights and predictions for reproducible benchmarking experiments in MedMNIST v2

description: This data repository is associated with our GitHub code <code>weights_*.zip</code>: PyTorch, AutoKeras and Google AutoML Vision are provided for MedMNIST2D. PyTorch and AutoKeras are provided for MedMNIST3D. If you are using PyTorch model weights, please note that the ResNet18_224 / ResNet50_224 models are trained with images resized to 224 x 224 by <code>PIL.Image.NEAREST</code>. Snapshots for <code>auto-sklearn</code> are not uploaded due to the embarrassingly large model sizes (lots of model ensemble). <code>predictions.zip</code>: We also provide all standard prediction files by PyTorch, auto-sklearn, AutoKeras and Google AutoML Vision, which works with <code>medmnist.Evaluator</code>. Each file is named as <code>{flag}_{split}_[AUC]{auc:.3f}_[ACC]{acc:.3f}@{run}.csv</code>, e.g., <code>bloodmnist_test_[AUC]0.997_[ACC]0.957@autokeras_3.csv</code>.
DOI: 10.3886/icpsr38638.v1
title: Federal Justice Statistics Program: Defendants Charged in Criminal Cases Filed in District Court, 2021
title: Version 1

description: The data contain records of defendants in federal criminal cases filed in United States District Court during fiscal year 2021. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central System file. According to the EOUSA, the United States attorneys conduct approximately 95 percent of the prosecutions handled by the Department of Justice. The Central Charge and Central System data contain variables from the original EOUSA files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Defendants Charged in Criminal Cases Filed in District Court, 2021
description: Defendants in federal criminal cases filed in United States District Court during fiscal year 2021.
DOI: 10.3886/icpsr38638
title: Federal Justice Statistics Program: Defendants Charged in Criminal Cases Filed in District Court, 2021
title: Archival Version

description: The data contain records of defendants in federal criminal cases filed in United States District Court during fiscal year 2021. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central System file. According to the EOUSA, the United States attorneys conduct approximately 95 percent of the prosecutions handled by the Department of Justice. The Central Charge and Central System data contain variables from the original EOUSA files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security Number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Defendants Charged in Criminal Cases Filed in District Court, 2021
description: Defendants in federal criminal cases filed in United States District Court during fiscal year 2021.
DOI: 10.6084/m9.figshare.20332890
title: Phylogenomic and phylogenetic datasets and trees

description: Phylogenomic and phylogenetic datasets and trees
DOI: 10.6084/m9.figshare.20332890.v8
title: Phylogenomic and phylogenetic datasets and trees

description: Phylogenomic and phylogenetic datasets and trees
DOI: 10.6084/m9.figshare.20332890.v7
title: Phylogenomic and phylogenetic datasets and trees

description: Phylogenomic and phylogenetic datasets and trees
DOI: 10.6084/m9.figshare.20332842
title: Genomes, transcriptomes, proteomes and introns for Agogonia voluta and Ophirina chinija

description: Genomes, transcriptomes and proteomes for Agogonia and O. chinija
DOI: 10.6084/m9.figshare.20332842.v2
title: Genomes, transcriptomes and proteomes for Agogonia voluta and Ophirina chinija

description: Genomes, transcriptomes and proteomes for Agogonia and O. chinija
DOI: 10.25345/c5kd1qw14
title: MassIVE MSV000091593 - Effect of salinity stress on the exoproteome profile of Bacillus amyloliquefaciens EB2003A
title: The study investigated the effect of 200 mM NaCl on the exoproteome profile of Bacillus amyloliquefaciens. 0 mM NaCl was the control.
DOI: 10.3886/icpsr38629.v1
title: Federal Justice Statistics Program: Defendants in Federal Criminal Cases Filed in District Court, 2021
title: Version 1

description: The data contain records of defendants in criminal cases filed in United States District Court during fiscal year 2021. The data were constructed from the Administrative Office of the United States District Courts' (AOUSC) criminal file. Defendants in criminal cases may be either individuals or corporations. There is one record for each defendant in each case filed. Included in the records are data from court proceedings and offense codes for up to five offenses charged at the time the case was filed. (The most serious charge at termination may differ from the most serious charge at case filing, due to plea bargaining or action of the judge or jury.) In a case with multiple charges against the defendant, a "most serious" offense charge is determined by a hierarchy of offenses based on statutory maximum penalties associated with the charges. The data file contains variables from the original AOUSC files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt Associates and the Bureau of Justice Statistics. Data and documentation were prepared by Abt Associates.
description: Datasets: DS1: Federal Justice Statistics Program: Defendants in Federal Criminal Cases Filed in District Court, 2021
description: Criminal cases filed in United States District Court during fiscal year 2021. Smallest Geographic Unit: United States