cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr36713
title: Federal Justice Statistics Program: Defendants in Federal Criminal Cases Filed in District Court, 2014
title: Archival Version

description: The data contain records of defendants in criminal cases filed in United States District Court during fiscal year 2014. 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, or "SAF" variables, that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 4.1-4.5 and 5.1-5.6. Variables containing information (e.g., name, Social Security number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by Abt and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.
description: Datasets: DS1: Federal Justice Statistics Program: Defendants in Federal Criminal Cases Filed in District Court, 2014
description: Criminal cases filed in United States District Court during fiscal year 2014. Smallest Geographic Unit: United States
DOI: 10.3886/icpsr38220.v1
title: Federal Justice Statistics Program: Defendants Charged in Criminal Cases Filed in District Court, 2017
title: Version 1

description: The data contain records of defendants in federal criminal cases filed in United States District Court during fiscal year 2017. 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 and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.
description: Datasets: DS1: Federal Justice Statistics Program: Defendants Charged in Criminal Cases Filed in District Court, 2017
description: Defendants in federal criminal cases filed in United States District Court during fiscal year 2017.
DOI: 10.3886/icpsr38220
title: Federal Justice Statistics Program: Defendants Charged in Criminal Cases Filed in District Court, 2017
title: Archival Version

description: The data contain records of defendants in federal criminal cases filed in United States District Court during fiscal year 2017. 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 and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.
description: Datasets: DS1: Federal Justice Statistics Program: Defendants Charged in Criminal Cases Filed in District Court, 2017
description: Defendants in federal criminal cases filed in United States District Court during fiscal year 2017.
DOI: 10.18119/n9g606
title: STRING network - Upregulated DE Genes From Mutation Clusters
DOI: 10.18119/n9bg7c
title: STRING network - Upregulated DE Genes from Gene Expression Clusters
DOI: 10.18119/n96p5f
title: STRING network - Downregulated DE Genes from Gene Expression Clusters
DOI: 10.18119/n9303v
title: STRING network - Downregulated DE Genes from Mutation Clustering
DOI: 10.4121/21220784.v1
title: Implementation of campus innovation: Atlas.ti codebook and innovations list

description: Interviews were held with Campus Real Estate management units about implementation of innovation on campus. This dataset was qualitatively analyzed using Atlas.ti 9.0. The analysis process started with immersive listening to the recorded interviews, reading the interview notes and subsequent coding, and the practice of content tagging of recurrent topics. Topics were then grouped and arranged into themes - available in this codebook. The themes provide an in-depth view of the dimensions of the challenges and opportunities for campus managers responsible for the implementation of campus innovation. Based on projects mentioned by campus managers during the qualitative interviews, a list of on-campus innovations and experiments was compiled and verified through internet searches of projects and publications.
DOI: 10.4121/21220784
title: Implementation of campus innovation: Atlas.ti codebook and innovations list

description: Interviews were held with Campus Real Estate management units about implementation of innovation on campus. This dataset was qualitatively analyzed using Atlas.ti 9.0. The analysis process started with immersive listening to the recorded interviews, reading the interview notes and subsequent coding, and the practice of content tagging of recurrent topics. Topics were then grouped and arranged into themes - available in this codebook. The themes provide an in-depth view of the dimensions of the challenges and opportunities for campus managers responsible for the implementation of campus innovation. Based on projects mentioned by campus managers during the qualitative interviews, a list of on-campus innovations and experiments was compiled and verified through internet searches of projects and publications.
DOI: 10.4121/21494520.v1
title: Dataset underlying the publication 'Optimization of Capture ELISAs for Chicken Cytokines Using Commercially Available Antibodies''

description: The research is about optimization and validation of capture ELISA for chicken IL-2, IL-6, IL-10, IL-12p40, and IFN-y using commercially available antibodies and recombinant cytokines. To optimize antibody concentrations, checkerboard titration was performed. Then, validation tests for capture ELISAs were performed to assess lower limit of detection (LLOD), matrix effect, parallelism, and inter-assay variation.
DOI: 10.4121/21494520
title: Dataset underlying the publication 'Optimization of Capture ELISAs for Chicken Cytokines Using Commercially Available Antibodies''

description: The research is about optimization and validation of capture ELISA for chicken IL-2, IL-6, IL-10, IL-12p40, and IFN-y using commercially available antibodies and recombinant cytokines. To optimize antibody concentrations, checkerboard titration was performed. Then, validation tests for capture ELISAs were performed to assess lower limit of detection (LLOD), matrix effect, parallelism, and inter-assay variation.
DOI: 10.4121/16886977.v1
title: Supplementary Data of "Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach"

description: Supplementary data accompanying the article "Transport Patterns of Global Aviation NO<sub>x</sub> and their Short-term O<sub>3</sub> Radiative Forcing – A Machine Learning Approach". <br> This data tracks the global transport of emitted NO<sub>x </sub>throughout a 90-day period since its emission from a representative aircraft cruising altitude of 250 hPa (~10.4 km) in 5 regions (North America, South America, Eurasia, Africa and Australasia) during the first day of January and July of 2014. <br> The short-term NO<sub>x</sub>-induced net O<sub>3</sub> production is also calculated as well as its associated instantaneous radiative forcing impact. The Lagrangian modelling approach adopted in this study allows for the amount of NO<sub>x</sub> emitted and consequent O<sub>3</sub> produced to be accompanied along each point of every air parcel trajectory. Lastly, information regarding the background NO<sub>x</sub> conditions during the times of emission is also included.
DOI: 10.4121/16886977
title: Supplementary Data of "Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach"

description: Supplementary data accompanying the article "Transport Patterns of Global Aviation NO<sub>x</sub> and their Short-term O<sub>3</sub> Radiative Forcing – A Machine Learning Approach". <br> This data tracks the global transport of emitted NO<sub>x </sub>throughout a 90-day period since its emission from a representative aircraft cruising altitude of 250 hPa (~10.4 km) in 5 regions (North America, South America, Eurasia, Africa and Australasia) during the first day of January and July of 2014. <br> The short-term NO<sub>x</sub>-induced net O<sub>3</sub> production is also calculated as well as its associated instantaneous radiative forcing impact. The Lagrangian modelling approach adopted in this study allows for the amount of NO<sub>x</sub> emitted and consequent O<sub>3</sub> produced to be accompanied along each point of every air parcel trajectory. Lastly, information regarding the background NO<sub>x</sub> conditions during the times of emission is also included.
DOI: 10.4121/21644789.v1
title: A low-fidelity model for the preliminary design phase of full-lattice wind support structures: dataset used for the data-driven model.

description: This data set includes two pieces of information: (1) the frequency of the first five modes of a large variety of straight lattice support structures and (2) the first five frequencies and the tuning coefficients relative to the low-fidelity model created for each of the lattice structures. This information was used to develop a surface response model in the paper listed in the section References.
DOI: 10.4121/21644789
title: A low-fidelity model for the preliminary design phase of full-lattice wind support structures: dataset used for the data-driven model.

description: This data set includes two pieces of information: (1) the frequency of the first five modes of a large variety of straight lattice support structures and (2) the first five frequencies and the tuning coefficients relative to the low-fidelity model created for each of the lattice structures. This information was used to develop a surface response model in the paper listed in the section References.
DOI: 10.3886/icpsr38514.v1
title: Federal Justice Statistics Program: Offenders in Prison at Year-End, 2019
title: Version 1

description: The data contain records of sentenced offenders in the custody of the Bureau of Prisons (BOP) at year-end of fiscal year 2019. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database 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: Offenders in Prison at Year-End, 2019
description: Offenders in the custody of the United States Bureau of Prisons at year-end of fiscal year 2019.
DOI: 10.3886/icpsr38514
title: Federal Justice Statistics Program: Offenders in Prison at Year-End, 2019
title: Archival Version

description: The data contain records of sentenced offenders in the custody of the Bureau of Prisons (BOP) at year-end of fiscal year 2019. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database 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: Offenders in Prison at Year-End, 2019
description: Offenders in the custody of the United States Bureau of Prisons at year-end of fiscal year 2019.
DOI: 10.4121/21688928
title: Phase-Coded FMCW PARSAX Radar Dataset

description: Dataset collected with the TU Delft PARSAX S-band coherent radar using the frequency-modulated continuous-wave (FMCW) and Phase-coded FMCW waveforms. This dataset accompanies the PhD dissertation of Utku Kumbul entitled: "Phase-coded FMCW for automotive radars". More details about the PARSAX radar used in the measurements can be seen in: O. A. Krasnov, L. P. Ligthart, Zhijian Li, P. Lys and F. van der Zwan, "The PARSAX - full polarimetric FMCW radar with dual-orthogonal signals," 2008 European Radar Conference, 2008, pp. 84-87. <strong>Referencing the dataset</strong> Kumbul, Utku; Petrov, Nikita; van der Zwan, Fred (2022): Phase-Coded FMCW PARSAX Radar Dataset. 4TU.ResearchData. Dataset. https://doi.org/10.4121/21688928 <br> <pre><code><strong>@misc</strong>{Kumbul2022, </code></pre> <pre><code>author = "Utku Kumbul and Nikita Petrov and Fred van der Zwan", </code></pre> <pre><code>title = "{Phase-Coded FMCW PARSAX Radar Dataset}", </code></pre> <pre><code>year = "2022", </code></pre> <pre><code>month = "Dec", </code></pre> <pre><code>url = "", </code></pre> <pre><code>doi = "10.4121/21688928 " } </code></pre> <pre><code> </code></pre> <strong>Paper references are:</strong> U. Kumbul, N. Petrov, F. van der Zwan, C. S. Vaucher and A. Yarovoy, "Experimental Investigation of Phase Coded FMCW for Sensing and Communications," <em>2021 15th European Conference on Antennas and Propagation (EuCAP)</em>, 2021, pp. 1-5, doi: 10.23919/EuCAP51087.2021.9411464. U. Kumbul, N. Petrov, C. S. Vaucher and A. Yarovoy, "Receiver Structures for Phase Modulated FMCW Radars," <em>2022 16th European Conference on Antennas and Propagation (EuCAP)</em>, 2022, pp. 1-5, doi: 10.23919/EuCAP53622.2022.9769268. U. Kumbul, N. Petrov, C. S. Vaucher and A. Yarovoy, "Smoothed Phase-Coded FMCW: Waveform Properties and Transceiver Architecture," in <em>IEEE Transactions on Aerospace and Electronic Systems</em>, 2022, doi: 10.1109/TAES.2022.3206173.
DOI: 10.4121/21687485.v1
title: Data and scripts of macrobenthos analysis Westerschelde

description: These are the data underlying the Deltares report "De Schelde, op weg naar een mooie toekomst?" by Peter Herman. The data have been provided by Rijkswaterstaat, but they were not yet in a final stage of quality check and formatting. A script is included that has done the formatting for the purpose of this analysis. Users should refer to Rijkswaterstaat if they want to use the same data - as soon as Rijkswaterstaat's own checks and formatting are completed, that will be the more authorative dataset. However, the current data are archived to document how the analysis in the report was done. Data were gathered in the framework of the MWTL monitoring programme in the S.W. Netherlands. Details of the fieldwork and a general data report is available in a report by Bureau Waardenburg (Kruijt, D. B., O. Duijts, M. Japink, and R. P. Middelveld. 2020. Macrozoöbenthosbemonstering in de Zoute Rijkswateren, Hoofdrapport MWTL 2019. Waterlichamen: Westerschelde, Veerse Meer en Grevelingenmeer. Bureau Waardenburg, Culemborg.) <br>
DOI: 10.4121/21687485
title: Data and scripts of macrobenthos analysis Westerschelde

description: These are the data underlying the Deltares report "De Schelde, op weg naar een mooie toekomst?" by Peter Herman. The data have been provided by Rijkswaterstaat, but they were not yet in a final stage of quality check and formatting. A script is included that has done the formatting for the purpose of this analysis. Users should refer to Rijkswaterstaat if they want to use the same data - as soon as Rijkswaterstaat's own checks and formatting are completed, that will be the more authorative dataset. However, the current data are archived to document how the analysis in the report was done. Data were gathered in the framework of the MWTL monitoring programme in the S.W. Netherlands. Details of the fieldwork and a general data report is available in a report by Bureau Waardenburg (Kruijt, D. B., O. Duijts, M. Japink, and R. P. Middelveld. 2020. Macrozoöbenthosbemonstering in de Zoute Rijkswateren, Hoofdrapport MWTL 2019. Waterlichamen: Westerschelde, Veerse Meer en Grevelingenmeer. Bureau Waardenburg, Culemborg.) <br>
DOI: 10.3886/icpsr38222.v1
title: Federal Justice Statistics Program: Suspects in Federal Criminal Matters, 2017
title: Version 1

description: The data contain records of suspects in federal criminal matters received by United States attorneys or filed before the United States magistrates during fiscal year 2017. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central System file. Records include suspects in criminal matters, and are limited to suspects whose matters were not declined immediately by the United States attorneys. 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 and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.
description: Datasets: DS1: Federal Justice Statistics Program: Suspects in Federal Criminal Matters, 2017
description: Suspects in federal criminal matters received by United States attorneys or filed before United States magistrates during fiscal year 2017.
DOI: 10.3886/icpsr38222
title: Federal Justice Statistics Program: Suspects in Federal Criminal Matters, 2017
title: Archival Version

description: The data contain records of suspects in federal criminal matters received by United States attorneys or filed before the United States magistrates during fiscal year 2017. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central System file. Records include suspects in criminal matters, and are limited to suspects whose matters were not declined immediately by the United States attorneys. 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 and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.
description: Datasets: DS1: Federal Justice Statistics Program: Suspects in Federal Criminal Matters, 2017
description: Suspects in federal criminal matters received by United States attorneys or filed before United States magistrates during fiscal year 2017.
DOI: 10.3886/icpsr38393.v1
title: Capital Punishment in the United States, 1973-2020
title: Version 1

description: CAPITAL PUNISHMENT IN THE UNITED STATES, 1973-2020 provides annual data on prisoners under a sentence of death, as well as those who had their sentences commuted or vacated and prisoners who were executed. This study examines basic sociodemographic classifications including age, sex, race and ethnicity, marital status at time of imprisonment, level of education, and state and region of incarceration. Criminal history information includes prior felony convictions and prior convictions for criminal homicide and the legal status at the time of the capital offense. Additional information is provided on those inmates removed from death row by yearend 2020. The dataset consists of one part which contains 9,636 cases. The file provides information on inmates whose death sentences were removed in addition to information on those inmates who were executed. The file also gives information about inmates who received a second death sentence by yearend 2020 as well as inmates who were already on death row.
description: Datasets: DS1: Capital Punishment in the United States, 1973-2020
description: All inmates on death row since 1973 in the United States. Smallest Geographic Unit: state
description: mail questionnaire; web-based surveyThe inmate identification numbers were assigned by the Bureau of the Census and have no purpose outside this data collection.To see the BJS report on this data collection, please go to Capital Punishment, 2020 - Statistical Tables.