cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc285wfs
title: CCDC 2091025: Experimental Crystal Structure Determination

description: Related Article: Yaxuan Chen, Guocheng Liu, Xiuli Wang, Ying Zhao, Na Xu, Zhong Zhang, Zhihan Chang, Xiaohui Li|2022|Inorg.Chim.Acta|534|120816|doi:10.1016/j.ica.2022.120816
DOI: 10.5517/ccdc.csd.cc285wgt
title: CCDC 2091026: Experimental Crystal Structure Determination

description: Related Article: Yaxuan Chen, Guocheng Liu, Xiuli Wang, Ying Zhao, Na Xu, Zhong Zhang, Zhihan Chang, Xiaohui Li|2022|Inorg.Chim.Acta|534|120816|doi:10.1016/j.ica.2022.120816
DOI: 10.5517/ccdc.csd.cc287gff
title: CCDC 2092544: Experimental Crystal Structure Determination

description: Related Article: Mikhail G. Andronov, Alexey V. Kuzmin, Alexander F. Shestakov, Salavat S. Khasanov, Dmitri V. Konarev|2022|Inorg.Chim.Acta|533|120789|doi:10.1016/j.ica.2022.120789
DOI: 10.5517/ccdc.csd.cc282hzv
title: CCDC 2087787: Experimental Crystal Structure Determination

description: Related Article: Mikhail G. Andronov, Alexey V. Kuzmin, Alexander F. Shestakov, Salavat S. Khasanov, Dmitri V. Konarev|2022|Inorg.Chim.Acta|533|120789|doi:10.1016/j.ica.2022.120789
DOI: 10.5517/ccdc.csd.cc282jpl
title: CCDC 2087809: Experimental Crystal Structure Determination

description: Related Article: Mikhail G. Andronov, Alexey V. Kuzmin, Alexander F. Shestakov, Salavat S. Khasanov, Dmitri V. Konarev|2022|Inorg.Chim.Acta|533|120789|doi:10.1016/j.ica.2022.120789
DOI: 10.6084/m9.figshare.19089371
title: updated PCOS row data

description: excel file contain row data of PCOS patients
DOI: 10.5281/zenodo.5842199
title: Experimental data of geoplate bedload signal of single pebbles

description: Geophone raw data acquired during experiments carried out in the Hydraulics Laboratory of the Department of Civil, Environmental and Mechanical Engineering, University of Trento, Italy in dry and flow conditions. Experiments in dry conditions used a metal sphere hitting different locations on the plate. Signal was sampled with two different acquisition rates (10 and 30 kHz) Experiments in water flow conditions used 17 pebbles of different size and shape and 5 different flow conditions (F1 to F5). File "Metadata.txt" reports more information on how to read and use the dataset. These data have been used in the publication "Analysis of the vibration modes of impact geoplates and implications for bedload flux and grainsize measurements" by Portogallo et al., submitted to Water Resources Research.
DOI: 10.6084/m9.figshare.13337255
title: Data and Code for "Hysteresis stabilizes dynamic control of self-assembled army ant constructions"

description: Manuscript authors: Helen F. McCreery*, Georgina Gemayel, Ana Isabel Pais, Simon Garnier, and Radhika Nagpal<br><br>* corresponding author: HFM (hmccreery@gmail.com)<br><br><b>Please see the readMe.txt file for explanations.</b><br><br>These files contain the data and code associated with experiments, models, and analyses of how living army ant bridges respond to changes in the geometry of the terrain they are built on. Code is organized into three phases. Some raw data files (including video files of experiments) are excluded due to file size. These files are available upon request from the corresponding author. <br><b><br></b>Motivation, framework, and methods included in the accompanying manuscript: "Hysteresis stabilizes dynamic control of self-assembled army ant constructions."<br>
DOI: 10.5066/p9edm6l6
title: Stream Temperature in the Northern Great Basin region of Southeastern Oregon, 2016-2021

description: This dataset includes hourly stream and air temperature data from 124 sites throughout the Northern Great Basin region of SE Oregon. Data loggers were deployed June through September of 2016 and downloaded each subsequent summer through 2021. The SE_OR_Stream_Temps and SE_OR_Air_Temps files contain temperature data (in degrees Celsius) by logger serial number and site for the study period. The SE_OR_Wet_Dry delineation file contains daily flow status estimates derived from stream temperature data for each site. The SE_OR_Site_Visit_Stream and SE_OR_Site_Visit_Air files contain the date and time of the site visit along with associated information on site flow conditions, water depths, logger conditions, and stream logger water depths. The SE_OR_Points shapefile contains site locations, geographic information, data summaries, mean August stream temperatures, and modeled NorWeST stream temperatures.
DOI: 10.6084/m9.figshare.19089896
title: Starfleet Headache Treatment - Example Data for Repeated ANOVA

description: Fictitious data to look at the overall health of Starfleet volunteers on four different drugs. Since each volunteer is measured on each of the four drugs, we propose to use this datasets to look at repeater measures ANOVA to determine if the mean health scores differs between drugs.
DOI: 10.5281/zenodo.5501385
title: Isotopic Fuel Compositions in the Sangamon20 Model

description: The seven csv files each correspond to a different level of fuel burnup in the Sangamon20 (a 20 MWth pebble-bed HTGR) fuel pebbles. fresh_comp.csv provides the composition for UCO in fresh pebbles. 1pass_comp.csv provides the fuel composition in pebbles that have gone through one six month pass, 2pass_comp.csv have been through two six month passes, and so forth.
DOI: 10.5281/zenodo.5501384
title: Isotopic Fuel Compositions in the Sangamon20 Model

description: The seven csv files each correspond to a different level of fuel burnup in the Sangamon20 (a 20 MWth pebble-bed HTGR) fuel pebbles. fresh_comp.csv provides the composition for UCO in fresh pebbles. 1pass_comp.csv provides the fuel composition in pebbles that have gone through one six month pass, 2pass_comp.csv have been through two six month passes, and so forth.
DOI: 10.5066/p99oa4ku
title: Stream Temperature in the Donner und Blitzen basin, Southeastern Oregon, 2018-2021

description: This dataset includes stream temperature data from 34 sites in the Donner und Blitzen basin of SE Oregon. Data loggers were deployed in September of 2018 and downloaded each subsequent summer/fall through 2021. The EcoDrought_Temperature file contains temperature data (in degrees Celsius) by logger serial number and site for the study period. The EcoDrought_Points spatial data layer contains site locations, geographic information, data summaries, mean August stream temperatures, and modeled NorWeST stream temperatures. The EcoDrought_Wet_Dry delineation file contains daily flow status estimates derived from stream temperature data for each site. The EcoDrought_Site_Visit file contains the date and time of the site visit along with associated information on site flow conditions, water depths, logger conditions, and stream logger water depths.
DOI: 10.3886/e128143
title: Data and Code for: Yellow Vests, Pessimistic Beliefs, and Carbon Tax Aversion

description: Using a representative survey, we find that after the Yellow Vests movement, French people would largely reject a tax & dividend policy, i.e., a carbon tax whose revenues are redistributed uniformly to each adult. They overestimate their net monetary losses, wrongly think that the policy is regressive, and do not perceive it as environmentally effective. We show that changing people’s beliefs can substantially increase support. Although significant, the effects of our informational treatments on beliefs are small. Indeed, the respondents that oppose the tax tend to discard positive information about it, which is consistent with distrust, uncertainty, or motivated reasoning.
DOI: 10.3886/e128143v1
title: Data and Code for: Yellow Vests, Pessimistic Beliefs, and Carbon Tax Aversion

description: Using a representative survey, we find that after the Yellow Vests movement, French people would largely reject a tax & dividend policy, i.e., a carbon tax whose revenues are redistributed uniformly to each adult. They overestimate their net monetary losses, wrongly think that the policy is regressive, and do not perceive it as environmentally effective. We show that changing people’s beliefs can substantially increase support. Although significant, the effects of our informational treatments on beliefs are small. Indeed, the respondents that oppose the tax tend to discard positive information about it, which is consistent with distrust, uncertainty, or motivated reasoning.
DOI: 10.34740/kaggle/dsv/3107443
title: Health Workforce Shortage Areas
DOI: 10.5281/zenodo.5914778
title: When Less is More: Improving Choices in Health Insurance Markets

description: We study the impact of changing choice set size on the quality of choices in health insurance markets. Using novel data on enrollment and medical claims for school district employees in the state of Oregon, we document that the average employee could save $600 by switching to a lower cost plan. Structural modeling reveals large ``choice inconsistencies'' such as non-equalization of the dollar spent on premiums and out of pocket, and a novel form of ``approximate inertia'' where enrollees are excessively likely to switch to other plans that are close to the current plan on the plan design spreadsheet. Variation in the number of plan choices across districts and over time shows that enrollees make lower-cost choices when the choice set is smaller. We show that a curated restriction of choice set size improves choices more than the best available information intervention, partly because approximate inertia lowers gains from new information. We explicitly test and reject the assumption that this is because individuals choose worse from larger choice sets, or ``choice overload''. Rather, we show that this feature arises from the fact that larger choice sets feature worse choices on average that are not offset by individual re-optimization.
DOI: 10.5517/ccdc.csd.cc287gkk
title: CCDC 2092548: Experimental Crystal Structure Determination

description: Related Article: Mikhail G. Andronov, Alexey V. Kuzmin, Alexander F. Shestakov, Salavat S. Khasanov, Dmitri V. Konarev|2022|Inorg.Chim.Acta|533|120789|doi:10.1016/j.ica.2022.120789
DOI: 10.5517/ccdc.csd.cc288d32
title: CCDC 2093433: Experimental Crystal Structure Determination

description: Related Article: Lijuan Huang, Haiping Xu, Yan Zhao, Ling Huang, Jian Bi, Hongmei Zeng, Guohong Zou, Daojiang Gao, Zhien Lin|2021|CrystEngComm|23|6855|doi:10.1039/D1CE00873K
description: Related Article: Junfeng Zhang, Qing Lei, Lindong Luan, Hongmei Zeng, Guohong Zou, Zhien Lin|2022|CrystEngComm|24|743|doi:10.1039/D1CE01659H
DOI: 10.5517/ccdc.csd.cc289dss
title: CCDC 2094415: Experimental Crystal Structure Determination

description: Related Article: Elyse A. Schriber, Daniel W. Paley, Robert Bolotovsky, Daniel J. Rosenberg, Raymond G. Sierra, Andrew Aquila, Derek Mendez, Frédéric Poitevin, Johannes P. Blaschke, Asmit Bhowmick, Ryan P. Kelly, Mark Hunter, Brandon Hayes, Derek C. Popple, Matthew Yeung, Carina Pareja-Rivera, Stella Lisova, Kensuke Tono, Michihiro Sugahara, Shigeki Owada, Tevye Kuykendall, Kaiyuan Yao, P. James Schuck, Diego Solis-Ibarra, Nicholas K. Sauter, Aaron S. Brewster, J. Nathan Hohman|2022|Nature (London)|601|360|doi:10.1038/s41586-021-04218-3
DOI: 10.5517/ccdc.csd.cc289dtt
title: CCDC 2094416: Experimental Crystal Structure Determination

description: Related Article: Elyse A. Schriber, Daniel W. Paley, Robert Bolotovsky, Daniel J. Rosenberg, Raymond G. Sierra, Andrew Aquila, Derek Mendez, Frédéric Poitevin, Johannes P. Blaschke, Asmit Bhowmick, Ryan P. Kelly, Mark Hunter, Brandon Hayes, Derek C. Popple, Matthew Yeung, Carina Pareja-Rivera, Stella Lisova, Kensuke Tono, Michihiro Sugahara, Shigeki Owada, Tevye Kuykendall, Kaiyuan Yao, P. James Schuck, Diego Solis-Ibarra, Nicholas K. Sauter, Aaron S. Brewster, J. Nathan Hohman|2022|Nature (London)|601|360|doi:10.1038/s41586-021-04218-3
DOI: 10.5517/ccdc.csd.cc28k3wv
title: CCDC 2101827: Experimental Crystal Structure Determination

description: Related Article: Shun Sakurai, Tetsuya Inagaki, Takuya Kodama, Masahiro Yamanaka, Mamoru Tobisu|2022|J.Am.Chem.Soc.|144|1099|doi:10.1021/jacs.1c11497
DOI: 10.5517/ccdc.csd.cc28k3xw
title: CCDC 2101828: Experimental Crystal Structure Determination

description: Related Article: Shun Sakurai, Tetsuya Inagaki, Takuya Kodama, Masahiro Yamanaka, Mamoru Tobisu|2022|J.Am.Chem.Soc.|144|1099|doi:10.1021/jacs.1c11497
DOI: 10.5517/ccdc.csd.cc28nlp7
title: CCDC 2105169: Experimental Crystal Structure Determination

description: Related Article: Min Wan, Yan-Ning Wang, Jing-Yuan Liu, Liang Tong, Si-Yu Ye, Jun-Yi Li, Li-Zhuang Chen|2022|CrystEngComm|24|782|doi:10.1039/D1CE01488A
DOI: 10.5517/ccdc.csd.cc28nlq8
title: CCDC 2105170: Experimental Crystal Structure Determination

description: Related Article: Min Wan, Yan-Ning Wang, Jing-Yuan Liu, Liang Tong, Si-Yu Ye, Jun-Yi Li, Li-Zhuang Chen|2022|CrystEngComm|24|782|doi:10.1039/D1CE01488A
DOI: 10.5517/ccdc.csd.cc28nlr9
title: CCDC 2105171: Experimental Crystal Structure Determination

description: Related Article: Min Wan, Yan-Ning Wang, Jing-Yuan Liu, Liang Tong, Si-Yu Ye, Jun-Yi Li, Li-Zhuang Chen|2022|CrystEngComm|24|782|doi:10.1039/D1CE01488A
DOI: 10.5517/ccdc.csd.cc28nlsb
title: CCDC 2105172: Experimental Crystal Structure Determination

description: Related Article: Min Wan, Yan-Ning Wang, Jing-Yuan Liu, Liang Tong, Si-Yu Ye, Jun-Yi Li, Li-Zhuang Chen|2022|CrystEngComm|24|782|doi:10.1039/D1CE01488A
DOI: 10.5517/ccdc.csd.cc28vlg6
title: CCDC 2110928: Experimental Crystal Structure Determination

description: Related Article: André K. Eckhardt, Martin-Louis Y. Riu, Peter Müller, Christopher C. Cummins|2022|Inorg.Chem.|61|1270|doi:10.1021/acs.inorgchem.1c03753
DOI: 10.5517/ccdc.csd.cc28vlj8
title: CCDC 2110930: Experimental Crystal Structure Determination

description: Related Article: André K. Eckhardt, Martin-Louis Y. Riu, Peter Müller, Christopher C. Cummins|2022|Inorg.Chem.|61|1270|doi:10.1021/acs.inorgchem.1c03753
DOI: 10.5517/ccdc.csd.cc28vlh7
title: CCDC 2110929: Experimental Crystal Structure Determination

description: Related Article: André K. Eckhardt, Martin-Louis Y. Riu, Peter Müller, Christopher C. Cummins|2022|Inorg.Chem.|61|1270|doi:10.1021/acs.inorgchem.1c03753
DOI: 10.5517/ccdc.csd.cc28xp1y
title: CCDC 2112930: Experimental Crystal Structure Determination

description: Related Article: Jixing Wang, Suting Xu, Xiang Hu, Yanchen Huo, Xiaochao Shi|2022|Organometallics|41|115|doi:10.1021/acs.organomet.1c00557
DOI: 10.5517/ccdc.csd.cc28xp2z
title: CCDC 2112931: Experimental Crystal Structure Determination

description: Related Article: Jixing Wang, Suting Xu, Xiang Hu, Yanchen Huo, Xiaochao Shi|2022|Organometallics|41|115|doi:10.1021/acs.organomet.1c00557
DOI: 10.6084/m9.figshare.19087784
title: Early Islamic Qibla Database 2022

description: This is an Excel spreadsheet with over 200 mosques and prayer places listed in chronological order along with GPS coordinates and links to further information. These places date from the very first mosques built in Medina onwards. I have tried to produce an exhaustive list for the first three centuries of Islam, then followed by a few important later mosques. I published the first edition of this list in January 2021. <br> This is the second edition. (January 2022) I am grateful for the contributions made by Peter Harremoes for his research both in books and manuscripts, and also measuring Qibla direction on the ground in 2021. <br> There is an active up-to-date list that is published on my website: https://nabataea.net/ Follow the menu Founding of Islam /Qibla Tool. This tool provides a graphical overview of the data and is useful of analysis.<br> Dan Gibson, January 2022
DOI: 10.6084/m9.figshare.19087784.v1
title: Early Islamic Qibla Database 2022

description: This is an Excel spreadsheet with over 200 mosques and prayer places listed in chronological order along with GPS coordinates and links to further information. These places date from the very first mosques built in Medina onwards. I have tried to produce an exhaustive list for the first three centuries of Islam, then followed by a few important later mosques.<br> I published the first edition of this list in January 2021. <br>. This is the second edition. (January 2022) I am grateful for the<br>contributions made by Peter Harremoes for his research both in books and manuscripts, and also measuring Qibla direction on the ground in 2021. <br> There is an active up-to-date list that is published on my website: https://nabataea.net/ Follow the menu Founding of Islam /Qibla Tool. This tool provides a graphical overview of the <br>data and is useful of analysis.<br> Dan Gibson, January 2022
DOI: 10.5281/zenodo.5866730
title: Dataset for "Detailed cartography of Cotopaxi's 1877 primary lahar deposits obtained by drone-imagery and field surveys in the proximal northern drainage"

description: Contains the following datasets supporting the results in "Detailed cartography of Cotopaxi’s 1877 primary lahar deposits obtained by drone-imagery and field surveys in the proximal northern drainage": 1) Drone-NDVI 25cm/pixel imagery for the four surveyed plains. 2) Geospatial vector layer for the geological fieldwork control points. 3) Geospatial vector layer for the 1877 deposit contact lines. 4) Geospatial vector layer for the 1877 deposit polygons.
DOI: 10.5281/zenodo.5866729
title: Dataset for "Detailed cartography of Cotopaxi's 1877 primary lahar deposits obtained by drone-imagery and field surveys in the proximal northern drainage"

description: Contains the following datasets supporting the results in "Detailed cartography of Cotopaxi’s 1877 primary lahar deposits obtained by drone-imagery and field surveys in the proximal northern drainage": 1) Drone-NDVI 25cm/pixel imagery for the four surveyed plains. 2) Geospatial vector layer for the geological fieldwork control points. 3) Geospatial vector layer for the 1877 deposit contact lines. 4) Geospatial vector layer for the 1877 deposit polygons.
DOI: 10.6084/m9.figshare.17137007
title: Multifile Partitioning for Record Linkage and Duplicate Detection

description: Merging datafiles containing information on overlapping sets of entities is a challenging task in the absence of unique identifiers, and is further complicated when some entities are duplicated in the datafiles. Most approaches to this problem have focused on linking two files assumed to be free of duplicates, or on detecting which records in a single file are duplicates. However, it is common in practice to encounter scenarios that fit somewhere in between or beyond these two settings. We propose a Bayesian approach for the general setting of multifile record linkage and duplicate detection. We use a novel partition representation to propose a structured prior for partitions that can incorporate prior information about the data collection processes of the datafiles in a flexible manner, and extend previous models for comparison data to accommodate the multifile setting. We also introduce a family of loss functions to derive Bayes estimates of partitions that allow uncertain portions of the partitions to be left unresolved. The performance of our proposed methodology is explored through extensive simulations. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.17137007.v1
title: Multifile Partitioning for Record Linkage and Duplicate Detection

description: Merging datafiles containing information on overlapping sets of entities is a challenging task in the absence of unique identifiers, and is further complicated when some entities are duplicated in the datafiles. Most approaches to this problem have focused on linking two files assumed to be free of duplicates, or on detecting which records in a single file are duplicates. However, it is common in practice to encounter scenarios that fit somewhere in between or beyond these two settings. We propose a Bayesian approach for the general setting of multifile record linkage and duplicate detection. We use a novel partition representation to propose a structured prior for partitions that can incorporate prior information about the data collection processes of the datafiles in a flexible manner, and extend previous models for comparison data to accommodate the multifile setting. We also introduce a family of loss functions to derive Bayes estimates of partitions that allow uncertain portions of the partitions to be left unresolved. The performance of our proposed methodology is explored through extensive simulations. Supplementary materials for this article are available online.
DOI: 10.3886/e115467
title: Data and Code for: Imperfect Markets versus Imperfect Regulation in U.S. Electricity Generation

description: This deposit contains the code to replicate of "Imperfect Markets versus Imperfect Regulation in U.S. Electricity Generation."<br>
description: Hourly power plant and grid operations in the United States.
DOI: 10.48704/ird_pd5inas
title: IRD_Pd5InAs
DOI: 10.48704/ird_pd3in_ht
title: IRD_Pd3In_HT
DOI: 10.48704/ird_pd2as_pthg2
title: IRD_Pd2As_PtHg2
DOI: 10.48704/ird_pd5inas_hocoga5
title: IRD_Pd5InAs_HoCoGa5
DOI: 10.6084/m9.figshare.23105018
title: mgss_classifier.RDS

description: The random forest training models for vaginal metagenomic subspecies assignment.
DOI: 10.6084/m9.figshare.23105018.v2
title: mgss_classifier.RDS

description: The random forest training models for vaginal metagenomic subspecies assignment.
DOI: 10.6084/m9.figshare.23105018.v1
title: mgss_classifier.RDS

description: The random forest training models for vaginal metagenomic subspecies assignment.
DOI: 10.5281/zenodo.3897692
title: NJR-1 Dataset

description: NJR is a Normalized Java Resource. The <em>NJR-1</em> dataset consists of 293 Java bytecode programs, each of which executes at least 100 unique application methods at runtime. Additionally, 5 static analysis tools (SpotBugs, Wala, Doop, Soot, Petablox) successfully run on these programs. <br> These programs are repositories picked from the set of Java-8 projects on Github that compile and run successfully. <br> Each of these programs comes with an executable jar file, the compiled bytecode file, and the Java source code. There are 3 files available for download: <em>njr-1_dataset.zip, scripts.zip, benchmark_stats.csv.</em> <em>njr-1_dataset.zip</em> has the actual dataset programs. <em>scripts.zip</em> contains Python3 scripts to run analysis tools (SpotBugs, Wala, Doop, Soot, Petablox) on the entire dataset. The benchmark_stats.csv file lists, for each benchmark, the number of nodes and edges in its dynamic application call-graph, as well as the number of edges in its static application call-graph (as computed by Wala). <br> A summary of the same is listed here: <strong><em>Statistics Dynamic-Nodes Dynamic-Edges Static-Edges</em></strong><br> Mean 205 469 1404<br> St.Dev 199 464 2523<br> Median 149 327 610 To cite the dataset, please cite the following paper:<br> Jens Palsberg and Cristina V. Lopes, NJR: a Normalized Java Resource. <br> In Proceedings of ACM SIGPLAN International Workshop on State Of the Art in Program Analysis (SOAP), 2018.
description: Funded by the following NSF grant (https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823360&HistoricalAwards=false)