cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10044976
title: Dataset for the project "Evaluation of the effects of trace elements from street dust under urban – industrial conditions on the ecophysiology of Acer platanoides L. and Tilia cordata Mill.

description: Description of the project: The rapid growth of cities, industry and transport has significantly deteriorated environmental quality, especially in areas with the highest population densities. It applies to water, soil, and air, especially in urban areas. Air pollutants include particulate matter (PM), which harms human health. According to WHO reports (2021), PM pollution is the cause of cardiovascular and respiratory diseases, leading to 4.2 million premature deaths worldwide in 2016. Although improving every year, the situation in Poland is still worse than in many European countries. The particulate matter also includes heavy metals, which have a toxic effect on plants. Plants in urban areas are particularly vulnerable, especially trees, which perform several vital functions, including mitigating climate change, filtering pollutants, and improving air quality. The aim of the project was to determine and compare the morphological and physiological responses of selected tree species to particulate pollution stress under urban conditions. Tree leaves are an essential barrier to atmospheric dust by trapping it on their surface. However, this may come at the cost of reduced light absorption, increased leaf temperature, damage to leaf blades and consequently impaired photosynthesis and plant productivity. However, the ability to absorb dust varies between tree species. It depends on the leaf surface structure, and the response may be due to the species' sensitivity to pollutants. Investigations were conducted in the Upper Silesian Industrial Area around various emission sources, such as heavy metal smelters, combined heat and power plants, and busy streets. The research focused on two tree species common in urban areas, the Norway maple (Acer platanoides) and the small-leaved lime (Tilia cordata). It included measurement of heavy metal concentrations in leaf blades and dust collected on their surface, analysis of concentrations of selected pigments and ascorbic acid as markers of environmental stress. The study provided a preliminary assessment of the impact of particulate pollution on tree function under harsh urban conditions and determined the potential of the studied species to reduce atmospheric dust.
DOI: 10.5281/zenodo.10044975
title: Dataset for the project "Evaluation of the effects of trace elements from street dust under urban – industrial conditions on the ecophysiology of Acer platanoides L. and Tilia cordata Mill.

description: Description of the project: The rapid growth of cities, industry and transport has significantly deteriorated environmental quality, especially in areas with the highest population densities. It applies to water, soil, and air, especially in urban areas. Air pollutants include particulate matter (PM), which harms human health. According to WHO reports (2021), PM pollution is the cause of cardiovascular and respiratory diseases, leading to 4.2 million premature deaths worldwide in 2016. Although improving every year, the situation in Poland is still worse than in many European countries. The particulate matter also includes heavy metals, which have a toxic effect on plants. Plants in urban areas are particularly vulnerable, especially trees, which perform several vital functions, including mitigating climate change, filtering pollutants, and improving air quality. The aim of the project was to determine and compare the morphological and physiological responses of selected tree species to particulate pollution stress under urban conditions. Tree leaves are an essential barrier to atmospheric dust by trapping it on their surface. However, this may come at the cost of reduced light absorption, increased leaf temperature, damage to leaf blades and consequently impaired photosynthesis and plant productivity. However, the ability to absorb dust varies between tree species. It depends on the leaf surface structure, and the response may be due to the species' sensitivity to pollutants. Investigations were conducted in the Upper Silesian Industrial Area around various emission sources, such as heavy metal smelters, combined heat and power plants, and busy streets. The research focused on two tree species common in urban areas, the Norway maple (Acer platanoides) and the small-leaved lime (Tilia cordata). It included measurement of heavy metal concentrations in leaf blades and dust collected on their surface, analysis of concentrations of selected pigments and ascorbic acid as markers of environmental stress. The study provided a preliminary assessment of the impact of particulate pollution on tree function under harsh urban conditions and determined the potential of the studied species to reduce atmospheric dust.
DOI: 10.5281/zenodo.10045007
title: Hyperspectral Oblique Plane Microscopy -- CAD model and PSF

description: CAD model (without Raman laser) and PSF data
DOI: 10.3886/e103500v5-19707
title: Jacob Kaplan's Concatenated Files: Uniform Crime Reporting (UCR) Program Data: Hate Crime Data 1991-2017
DOI: 10.3886/e103500v3-7681
title: Uniform Crime Reporting (UCR) Program Data: Hate Crime Data 1992-2016

description: Version 3 release notes: <br>Adds data for 2016.Order rows by year (descending) and ORI.Version 2 release notes: <br>Fix bug where Philadelphia Police Department had incorrect FIPS county code. The Hate Crime data is an FBI data set that is part of the annual Uniform Crime Reporting (UCR) Program data. This data contains information about hate crimes reported in the United States. The data sets here combine all data from the years 1992-2015 into a single file. Please note that the files are quite large and may take some time to open.<br><br>Each row indicates a hate crime incident for an agency in a given 
year. I have made a unique ID column ("unique_id") by combining the 
year, agency ORI9 (the 9 character Originating Identifier code), and incident number columns together. Each column is a variable related to that incident or to the reporting agency. <br>Some of the important columns are the incident date, what crime occurred (up to 10 crimes), the number of victims for each of these crimes, the bias motivation for each of these crimes, and the location of each crime. It also includes the total number of victims, total number of offenders, and race of offenders (as a group). Finally, it has a number of columns indicating if the victim for each offense was a certain type of victim or not (e.g. individual victim, business victim religious victim, etc.). <br><br>All the data was downloaded from NACJD as ASCII+SPSS Setup files and read into R using the package asciiSetupReader.
 All work to clean the data and save it in various file formats was also
 done in R. For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data. <br><br>The only changes I made to the data are the following. Minor changes to column names to make all column names 32 characters or fewer (so it can be saved in a Stata format), changed the name of some UCR offense codes (e.g. from "agg asslt" to "aggravated assault"), made all character values lower case, reordered columns. I also added state, county, and place FIPS code from the LEAIC (crosswalk) and generated incident month, weekday, and month-day variables from the incident date variable included in the original data. <br><br>The zip file contains the data in the following formats and a codebook: <br>.csv - Microsoft Excel<br>.dta - Stata<br>.sav - SPSS<br>.rda - R<br><br>If you have any questions, comments, or suggestions please contact me at jkkaplan6@gmail.com.<br><br><br>
description: Smallest Geographic Unit: police agency
DOI: 10.3886/e103500v4-9782
title: Uniform Crime Reporting (UCR) Program Data: Hate Crime Data 1992-2017

description: Version 4 release notes: <br>Adds data for 2017.Adds rows that submitted a zero-report (i.e. that agency reported no hate crimes in the year). This is for all years 1992-2017. Made changes to categorical variables (e.g. bias motivation columns) to make categories consistent over time. Different years had slightly different names (e.g. 'anti-am indian' and 'anti-american indian') which I made consistent. <br>Made the 'population' column which is the total population in that agency. <br><br>Version 3 release notes: <br>Adds data for 2016.Order rows by year (descending) and ORI.Version 2 release notes: <br>Fix bug where Philadelphia Police Department had incorrect FIPS county code. The Hate Crime data is an FBI data set that is part of the annual Uniform Crime Reporting (UCR) Program data. This data contains information about hate crimes reported in the United States. The data sets here combine all data from the years 1992-2015 into a single file. Please note that the files are quite large and may take some time to open.<br><br>Each row indicates a hate crime incident for an agency in a given year. I have made a unique ID column ("unique_id") by combining the year, agency ORI9 (the 9 character Originating Identifier code), and incident number columns together. Each column is a variable related to that incident or to the reporting agency. <br>Some of the important columns are the incident date, what crime occurred (up to 10 crimes), the number of victims for each of these crimes, the bias motivation for each of these crimes, and the location of each crime. It also includes the total number of victims, total number of offenders, and race of offenders (as a group). Finally, it has a number of columns indicating if the victim for each offense was a certain type of victim or not (e.g. individual victim, business victim religious victim, etc.). <br><br>All the data was downloaded from NACJD as ASCII+SPSS Setup files and read into R using the package asciiSetupReader. All work to clean the data and save it in various file formats was also done in R. For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data. <br><br>The only changes I made to the data are the following. Minor changes to column names to make all column names 32 characters or fewer (so it can be saved in a Stata format), changed the name of some UCR offense codes (e.g. from "agg asslt" to "aggravated assault"), made all character values lower case, reordered columns. I also added state, county, and place FIPS code from the LEAIC (crosswalk) and generated incident month, weekday, and month-day variables from the incident date variable included in the original data. <br><br>The zip file contains the data in the following formats and a codebook: <br><br>.dta - Stata.rda - R<br><br>If you have any questions, comments, or suggestions please contact me at jkkaplan6@gmail.com.<br><br>
description: Smallest Geographic Unit: police agency
DOI: 10.5281/zenodo.10045041
title: Diversity in Software Engineering Conferences and Journals

description: This repository includes the data used in the research in the article "Diversity in Software Engineering Conferences and Journals" submitted to the Journal of Systems and Software in October 2023. This repository contains .csv and .json files that include the data of all research papers published in the conferences ICSE, ASE, and FSE, along with the journals IEEE TSE and ACM TOSEM from the years 2010-2022 along with the list of names of Programming and Organizing Committee members and Editorial Board members. This data was sourced from DBLP and the conference websites/journal front matter pages. The names of the authors and committee members have been processed using NamSor to obtain the corresponding ethnicity (using the "Name US Race" feature) and gender (using the "Genderize name from first name and last name" feature). The affiliated institution and corresponding country for each first author were determined using the Scopus database.
DOI: 10.5281/zenodo.10045042
title: Diversity in Software Engineering Conferences and Journals

description: This repository includes the data used in the research in the article "Diversity in Software Engineering Conferences and Journals" submitted to the Journal of Systems and Software in October 2023. This repository contains .csv and .json files that include the data of all research papers published in the conferences ICSE, ASE, and FSE, along with the journals IEEE TSE and ACM TOSEM from the years 2010-2022 along with the list of names of Programming and Organizing Committee members and Editorial Board members. This data was sourced from DBLP and the conference websites/journal front matter pages. The names of the authors and committee members have been processed using NamSor to obtain the corresponding ethnicity (using the "Name US Race" feature) and gender (using the "Genderize name from first name and last name" feature). The affiliated institution and corresponding country for each first author were determined using the Scopus database.
DOI: 10.5281/zenodo.10045044
title: Pure--No Build--POPE OpenFF Fix Attempt 1

description: Reused 200 ns 64:64 POPE bilayer hydrated with 5000 TIP3P waters.
DOI: 10.5281/zenodo.10045043
title: Pure--No Build--POPE OpenFF Fix Attempt 1

description: Reused 200 ns 64:64 POPE bilayer hydrated with 5000 TIP3P waters.
DOI: 10.6084/m9.figshare.24446086
title: LOCUST structure tracking demo dataset.

description: This is a demo data set for use with the structure tracking code hosted at https://github.com/colinrr/locustBased on the algorithm featured in the following manuscript:Rowell, Colin R., A. Mark Jellinek, Johan T. Gilchrist, Tracking volcanic plume thermal evolution and eruption source unsteadiness in ground-based thermal imagery using spectral-clustering. Journal of Geochemistry, Geophysics, Geosystems.
DOI: 10.6084/m9.figshare.24446086.v1
title: LOCUST structure tracking demo dataset.

description: This is a demo data set for use with the structure tracking code hosted at https://github.com/colinrr/locustBased on the algorithm featured in the following manuscript:Rowell, Colin R., A. Mark Jellinek, Johan T. Gilchrist, Tracking volcanic plume thermal evolution and eruption source unsteadiness in ground-based thermal imagery using spectral-clustering. Journal of Geochemistry, Geophysics, Geosystems.
DOI: 10.5281/zenodo.10045038
title: Pure POPE OpenFF Fix Attempt 1

description: 200 ns 64:64 POPE bilayer hydrated with 5000 TIP3P waters.
DOI: 10.5281/zenodo.8336387
title: Replication Package for "Wealth Inequality in a Low Rate Environment"
DOI: 10.5281/zenodo.10045037
title: Pure POPE OpenFF Fix Attempt 1

description: 200 ns 64:64 POPE bilayer hydrated with 5000 TIP3P waters.
DOI: 10.5281/zenodo.8336386
title: Replication Package for "Wealth Inequality in a Low Rate Environment"
DOI: 10.5517/ccdc.csd.cc28kx5y
title: CCDC 2102580: Experimental Crystal Structure Determination

description: Related Article: Philip Koblischek, Reinhard Brückner|2023|Eur.J.Org.Chem.|26|e202300648|doi:10.1002/ejoc.202300648
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cj446
title: CCDC 2190247: Experimental Crystal Structure Determination

description: Related Article: Alexander J. Auty, Paul A. Scattergood, Theo Keane, Tao Cheng, Guanzhi Wu, Heather Carson, James Shipp, Andrew Sadler, Thomas Roseveare, Igor V. Sazanovich, Anthony J. H. M. Meijer, Dimitri Chekulaev, Paul I. P. Elliot, Mike Towrie, Julia A. Weinstein|2023|Chemical Science|14|11417|doi:10.1039/D2SC06409J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dnktg
title: CCDC 2224306: Experimental Crystal Structure Determination

description: Related Article: Yarden Lavi, Michael Montag, Yael Diskin-Posner, Liat Avram, Linda J.W. Shimon, Yehoshua Ben-David, David Milstein|2023|Inorg.Chim.Acta|559|121787|doi:10.1016/j.ica.2023.121787
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dnkxk
title: CCDC 2224309: Experimental Crystal Structure Determination

description: Related Article: Yarden Lavi, Michael Montag, Yael Diskin-Posner, Liat Avram, Linda J.W. Shimon, Yehoshua Ben-David, David Milstein|2023|Inorg.Chim.Acta|559|121787|doi:10.1016/j.ica.2023.121787
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dqrkg
title: CCDC 2226406: Experimental Crystal Structure Determination

description: Related Article: Abraham Mensah, Wei-Min Chen, Ennin Vendish Kweku, Peng-Lai Liu, Juan-Juan Shao, Fang-Ming Wang, Li-Zhuang Chen|2023|CrystEngComm|25|5722|doi:10.1039/D3CE00815K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dqrws
title: CCDC 2226416: Experimental Crystal Structure Determination

description: Related Article: Abraham Mensah, Wei-Min Chen, Ennin Vendish Kweku, Peng-Lai Liu, Juan-Juan Shao, Fang-Ming Wang, Li-Zhuang Chen|2023|CrystEngComm|25|5722|doi:10.1039/D3CE00815K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dqs42
title: CCDC 2226424: Experimental Crystal Structure Determination

description: Related Article: Abraham Mensah, Wei-Min Chen, Ennin Vendish Kweku, Peng-Lai Liu, Juan-Juan Shao, Fang-Ming Wang, Li-Zhuang Chen|2023|CrystEngComm|25|5722|doi:10.1039/D3CE00815K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dqs53
title: CCDC 2226425: Experimental Crystal Structure Determination

description: Related Article: Abraham Mensah, Wei-Min Chen, Ennin Vendish Kweku, Peng-Lai Liu, Juan-Juan Shao, Fang-Ming Wang, Li-Zhuang Chen|2023|CrystEngComm|25|5722|doi:10.1039/D3CE00815K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fcq1l
title: CCDC 2245579: Experimental Crystal Structure Determination

description: Related Article: Hao-Hui Xie, Jiao-Lin Weng, Ji-Xing Song, Wen-Jing Yang, Qin Wang, Meng Cui, Fa-Kun Zheng, Ren-Hui Qiu, Jian-Gang Xu|2023|Dalton Trans.|52|14632|doi:10.1039/D3DT01804K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2g3rgt
title: CCDC 2267726: Experimental Crystal Structure Determination

description: Related Article: Darshini Gowda, Kachigere B. Harsha, Veeresha Gowda Shalini, Shobith Rangappa, Kanchugarakoppal S. Rangappa|2023|RSC Advances|13|28362|doi:10.1039/D3RA05235D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ghrj8
title: CCDC 2279260: Experimental Crystal Structure Determination

description: Related Article: Ana L. Pérez, Axel Kemmerer, Alejandro J. Zapata, Rosana Sartoris, Pablo J. Gonzalez, Raul Urteaga, Ricardo Baggio, Sebastián Suarez, Carlos A. Ramos, Sergio D. Dalosto, Alberto C. Rizzi, Carlos D. Brondino|2023|Dalton Trans.|52|14595|doi:10.1039/D3DT02115G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ghrk9
title: CCDC 2279261: Experimental Crystal Structure Determination

description: Related Article: Ana L. Pérez, Axel Kemmerer, Alejandro J. Zapata, Rosana Sartoris, Pablo J. Gonzalez, Raul Urteaga, Ricardo Baggio, Sebastián Suarez, Carlos A. Ramos, Sergio D. Dalosto, Alberto C. Rizzi, Carlos D. Brondino|2023|Dalton Trans.|52|14595|doi:10.1039/D3DT02115G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.22905368
title: Supplementary Data Files for "Power of inclusion: Enhancing polygenic prediction with admixed individuals"

description: Please read README.md for more information. We also provide the iPGS browser (https://ipgs.mit.edu/), where you can browse and download the coefficients of our iPGS models.