cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12888008.v1
title: Buoy Seno Ballena

description: 10 months (2018) time series data of pCO<sub>2</sub>, pH, temperature, salinity, and dissolved oxygen at Seno Ballena fjord in the Chilean Patagonia.The sensors (SAMI-CO<sub>2</sub>, SAMI-pH, SBE37, Aanderaa 5331A) recorded data every 4 hour from March to December. Lat 53.67461 S, Long 72.56061 W.
DOI: 10.5281/zenodo.4289364
title: Benchmark data used in the evaluation of ChiRA tool-suite.

description: The reads generated mimic CLASH experimental data. Each read is a fusion of a human hg38 miRBase mature miRNAs and some random TargetScan target sequences. The numbers 10, 12, 15, 18, and 20 in the file names represent the length of the chimeric arms. The are 1million reads in FASTA file. Files with "Insert" in their names contain a short 5 nt random sequence, whereas the "noInsert" files do not. TargetScanSites_merged.fa.fasta and hg38_MIR_mature.fa.fasta contain the reference sequences. The sequence identifiers in the FASTA file are in the following format: &gt;hsa-miR-193b-5p_MIMAT0004767:1-20||chr7:114656010-114656173+:82-95 where, hsa-miR-193b-5p_MIMAT0004767 is the sequence ID of the miRNA from which first chimeric arm of this read was derived from. This ID can be found in hg38_MIR_mature.fa.fasta. 1-20 represents the 1-based start and end positions on hsa-miR-193b-5p_MIMAT0004767 representing the origin of the first chimeric arm. chr7:114656010-114656173+ is the sequence ID of the TargetScan target site from which the second chimeric arm of this read was derived from. This ID can be found in TargetScanSites_merged.fa.fasta 82-95 represents the 1-based start and end positions on chr7:114656010-114656173+ representing the origin of the second chimeric arm.
DOI: 10.5281/zenodo.4289403
title: Interactions of fungal entomopathogens with synthetic insecticides for the control of Kuschelorhynchus macadamiae (Coleoptera: Curculionidae)

description: This is the raw data of lab and glasshouse experiments.
DOI: 10.5281/zenodo.4289402
title: Interactions of fungal entomopathogens with synthetic insecticides for the control of Kuschelorhynchus macadamiae (Coleoptera: Curculionidae)

description: This is the raw data of lab and glasshouse experiments.
DOI: 10.3886/e116366v1-70640
title: Replication data for: Children and Gender Inequality: Evidence from Denmark

description: Using Danish administrative data, we study the impacts of children on gender inequality in the labor market. The arrival of children creates a long-run gender gap in earnings of around 20 percent driven by hours worked, participation, and wage rates. We identify mechanisms driving these "child penalties" in terms of occupation, sector, and firm choices. We find that the fraction of gender inequality caused by child penalties has featured a dramatic increase over the last three to four decades. Finally, we show that child penalties are transmitted through generations, from parents to daughters, suggesting an influence of childhood environment on gender identity.
DOI: 10.3886/e115622v1-70660
title: Data and Code for: Interest Rates Under Falling Stars

description: Macro-finance theory implies that trend inflation and the equilibrium real interest rate are fundamental determinants of the yield curve. However, empirical models of the term structure of interest rates generally assume that these fundamentals are constant. We show that accounting for time variation in these underlying long-run trends is crucial for understanding the dynamics of Treasury yields and predicting excess bond returns. We introduce a new arbitrage-free model that captures the key role that long-run trends play for interest rates. The model also provides new, more plausible estimates of the term premium and accurate out-of-sample yield forecasts.
DOI: 10.3886/e115622v1-70661
title: Data and Code for: Interest Rates Under Falling Stars

description: Macro-finance theory implies that trend inflation and the equilibrium real interest rate are fundamental determinants of the yield curve. However, empirical models of the term structure of interest rates generally assume that these fundamentals are constant. We show that accounting for time variation in these underlying long-run trends is crucial for understanding the dynamics of Treasury yields and predicting excess bond returns. We introduce a new arbitrage-free model that captures the key role that long-run trends play for interest rates. The model also provides new, more plausible estimates of the term premium and accurate out-of-sample yield forecasts.
DOI: 10.3886/e127301
title: Data Repository for: Explore, Exploit, and Prune in the Classroom: Strategic Resource Management Behaviors Predict Performance

description: [This is a data repository for a paper accepted at AERA Open.]<br><br>Self-regulated learners strategically manage physical, technological, online, and social resources for learning—by selecting resources that could be useful, reflecting on how useful these resources have been, and adjusting resource use accordingly. We propose a model that conceptualizes resource management as learners’ intentional, self-reflective decisions to explore new resources, exploit (continue to use) previously useful resources, and prune (stop using) previously ineffective resources. We modeled 4,766 students’ reported exploration, exploitation, and pruning between three class exams among four cohorts of an Organic Chemistry class (i.e., over 100,000 discrete data points of resource use). Each of these behavioral mechanisms of resource management predicted students’ academic achievement: The more students reported exploring, exploiting, and pruning between their exams, the higher they performed on their subsequent exams, controlling for prior performance. These findings enrich self-regulated learning theories by concretizing the behavioral mechanisms of resource management by which learners take control of their learning.
DOI: 10.3886/e127301v1
title: Data Repository for: Explore, Exploit, and Prune in the Classroom: Strategic Resource Management Behaviors Predict Performance

description: [This is a data repository for a paper accepted at AERA Open.]<br><br>Self-regulated learners strategically manage physical, technological, online, and social resources for learning—by selecting resources that could be useful, reflecting on how useful these resources have been, and adjusting resource use accordingly. We propose a model that conceptualizes resource management as learners’ intentional, self-reflective decisions to explore new resources, exploit (continue to use) previously useful resources, and prune (stop using) previously ineffective resources. We modeled 4,766 students’ reported exploration, exploitation, and pruning between three class exams among four cohorts of an Organic Chemistry class (i.e., over 100,000 discrete data points of resource use). Each of these behavioral mechanisms of resource management predicted students’ academic achievement: The more students reported exploring, exploiting, and pruning between their exams, the higher they performed on their subsequent exams, controlling for prior performance. These findings enrich self-regulated learning theories by concretizing the behavioral mechanisms of resource management by which learners take control of their learning.
DOI: 10.3886/e117922
title: Data and code for: The looming threat of tariff hikes: entry into exporting under trade agreement renegotiation

description: We examine how the looming threat of tariff hikes under a trade agreement renegotiation impacts firm entry into a trading partner's market by exploiting uncertainty over the future UK-EU trade relationship brought about by the June 2016 Brexit referendum. Using the universe of UK export transactions at the firm and product level, we find that uncertainty over future market access to the EU deterred entry modestly in the months immediately after the Brexit vote, but the deterrent effect increased over time.<br>
description: Data accessible in Her Majesty's Revenue and Customs Datalab after an application process.
description: Firms exporting goods from the United Kingdom between 2012 and 2016. .
DOI: 10.3886/e117922v1
title: Data and code for: The looming threat of tariff hikes: entry into exporting under trade agreement renegotiation

description: We examine how the looming threat of tariff hikes under a trade agreement renegotiation impacts firm entry into a trading partner's market by exploiting uncertainty over the future UK-EU trade relationship brought about by the June 2016 Brexit referendum. Using the universe of UK export transactions at the firm and product level, we find that uncertainty over future market access to the EU deterred entry modestly in the months immediately after the Brexit vote, but the deterrent effect increased over time.<br>
description: Data accessible in Her Majesty's Revenue and Customs Datalab after an application process.
description: Firms exporting goods from the United Kingdom between 2012 and 2016. .
DOI: 10.3886/e113182v1-70740
title: Replication data for: The Logic of Insurgent Electoral Violence

description: Competitive elections are essential to establishing the political legitimacy of democratizing regimes. We argue that insurgents undermine the state's mandate through electoral violence. We study insurgent violence during elections using newly declassified microdata on the conflict in Afghanistan. Our data track insurgent activity by hour to within meters of attack locations. Our results suggest that insurgents carefully calibrate their production of violence during elections to avoid harming civilians. Leveraging a novel instrumental variables approach, we find that violence depresses voting. Collectively, the results suggest insurgents try to depress turnout while avoiding backlash from harming civilians. Counterfactual exercises provide potentially actionable insights for safeguarding at-risk elections and enhancing electoral legitimacy in emerging democracies.
DOI: 10.3886/icpsr30022.v2
title: NCAA Division I and II Graduation Success Rate and Academic Success Rate, 1995-2008 Cohorts [United States]

description: This study includes the federal graduation rate for all NCAA member institutions who participated in Division I or Division II sports. It also describes the Graduation Success Rate (GSR) for all Division I institutions and the Academic Success Rate (ASR) of all Division II institutions. The rates included in this study are based on championship sport student-athletes who first began their full-time postsecondary education in academic years 1995-96 through 2008-09.Each cohort was tracked for 6 years for college completion. For example, the graduation status for the latest cohort (2008-09 cohort) was tracked through the spring of 2014. At their core, all three measures are based on a comparison of the number of students who entered a college or university in a given year and the number of those who graduated within six years of their initial enrollment, though each measure has a slightly different cohort definition. Federal graduation rates are based on the Integrated Postsecondary Education Data System Graduation Rates (IPEDS-GRS) which is defined as a six-year proportion of those student-athletes who graduated versus those who entered an institution on institutional aid. Federal graduation rates are included for both an institution's student-athletes and its general student body. In addition to the student-athlete data in the graduation-rates data, the Division I Graduation Success Rate (GSR) accounts for student-athletes who transfer into an institution while discounting student-athletes who separate from the institution and would have been academically eligible to compete had they returned. The definition of the Division II Academic Success Rate (ASR) cohort is identical to that of the GSR with the exception that it also includes freshmen who did not receive athletics aid, but did participate in athletics.
description: Presence of Common Scales: federal graduation rate graduation success rate academic success rate
description: Datasets: DS0: Study-Level Files DS1: Division I National Aggregation Overall DS2: Division I National Aggregation Student-Athletes DS3: Division I National Aggregation Student Body DS4: Division I School Student-Athletes and Student Body DS5: Division I Squad Level Graduation Success Rate DS6: Division II National Aggregation Overall DS7: Division II National Aggregation Student-Athletes DS8: Division II National Aggregation Student Body DS9: Division II School Student-Athletes and Student Body DS10: Division II Squad Level Academic Success Rate
description: record abstracts
description: Population of student-athletes and NCAA member institutions who participated in Division I or Division II athletics from 1995-2008.
DOI: 10.3886/icpsr26801.v3
title: NCAA Division I Academic Progress Rate, 2003-2014

description: This study was created, by the National Collegiate Athletic Association (NCAA), to provide public access to team-level Academic Progress Rates (APRs), eligibility rates, retention rates, and penalty and award information on Division I student-athletes starting with the 2003-2004 season through the 2013-2014 season, as well as to provide efficient analysis and linking of these data to other educational data.
description: College presidents across the nation recognized a need to track how student-athletes are doing academically prior to graduation. Beginning in 2003, colleges and universities in NCAA Division I -- the largest and highest profile athletics programs -- implemented a comprehensive academic reform package designed to improve the academic success and graduation of all student-athletes. The centerpiece of the academic reform package was the development of a real-time academic measurement for sports teams, known as the Academic Progress Rate (APR). The APR includes student-athlete eligibility, retention and graduation as factors in a formula that yields a single number, providing a much clearer picture of the current academic culture on each Division I sports team in the country. Since its inception, the APR has become an important measure of student-athlete academic success. For high APR scores, the NCAA recognizes member institutions for ensuring that student-athletes succeed in the classroom. If, however, low APR scores are earned consistently, member institutions can be subjected to penalties including scholarship reductions and the loss of eligibility to compete in championships.
description: The dataset contains a listing of the school name, the school's division and sub-division, the sport played, the size of the team or squad, the yearly and four-year APR, retention and eligibility rates, as well as, public award and penalty information.
description: Presence of Common Scales: Academic Progress Rate (APR)
description: Datasets: DS1: NCAA Division I Academic Progress Rate, 2003-2014
description: To protect confidentiality, some data have been blanked. Results derived from this dataset may not exactly replicate national aggregates provided by the NCAA in other formats. This may be due to updates to the data since the release of other reports, or changes made to the data to protect confidentiality.
description: Population of student athletes who participated in NCAA Division I championship sponsored sports from 2004-2014 academic years. Smallest Geographic Unit: university
DOI: 10.25345/c50b67
title: MassIVE MSV000086516 - GNPS_Synthetic cannabinoids_DDA_0.7_decov
title: Oral fulid synthetic cannabinoids DDA deconvoluted MS2 specta
DOI: 10.25387/g3.13206221
title: Supplemental Material for Paulson et al., 2020

description: These are supplementary data tables for the original research article: "<i>In vivo </i>transcriptome analysis provides insights into host-dependent expression of virulence factors by <i>Yersinia entomophaga </i>MH96, during infection of <i>Galleria mellonella</i>" published in 2020 in G3: Genes, Genomes, Genetics. Table S5 contains results of the differential expression analysis and Table S6 contains genes identified as in-host putative virulence factors using fuzzy <i>c-</i>mean clustering and BLAST search against the Virulence Factor Database.<br>Supplementary figures and small supplementary tables (Table S1, S2, S3, S4, S7, S8). <br>
DOI: 10.6084/m9.figshare.13204085
title: ASV Table

description: This is the ASV table and taxonomic assignments (and sequences) used for the 16S rRNA gene based analyses.
DOI: 10.6084/m9.figshare.13244870
title: 16S rRNA gene amplicon sequences

description: These are the raw sequences. Each folder contains the associated mapping file for the run.
DOI: 10.5281/zenodo.4288387
title: 1 km Monthly Precipitation Dataset for China from 1952 to 2019 (ChinaClim_timeseries)

description: ChinaClim_timeseries is a monthly temperatures and precipitation dataset in China for the period of 1952-2019 of 1km spatial resolution, the data was generated by superimposing monthly anomaly surface and baseline climatology surface (ChinaClim_baseline) based on climatologically aided interpolation (CAI). The scale factor of the data is 0.1.
DOI: 10.5519/qd.85y30g0m
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (11977 records)
DOI: 10.5281/zenodo.4288390
title: 1 km Monthly Maximum Temperature Dataset for China from 1952 to 2019 (ChinaClim_timeseries)

description: ChinaClim_timeseries is a monthly temperatures and precipitation dataset in China for the period of 1952-2019 of 1km spatial resolution, the data was generated by superimposing monthly anomaly surface and baseline climatology surface (ChinaClim_baseline) based on climatologically aided interpolation (CAI). The scale factor of the data is 0.1.
DOI: 10.5281/zenodo.4288389
title: 1 km Monthly Maximum Temperature Dataset for China from 1952 to 2019 (ChinaClim_timeseries)

description: ChinaClim_timeseries is a monthly temperatures and precipitation dataset in China for the period of 1952-2019 of 1km spatial resolution, the data was generated by superimposing monthly anomaly surface and baseline climatology surface (ChinaClim_baseline) based on climatologically aided interpolation (CAI). The scale factor of the data is 0.1.
DOI: 10.34740/kaggle/dsv/1679751
title: German News Dataset
DOI: 10.5281/zenodo.4158935
title: New Bubble Transport Model Coupled with Multiple Hydrate Behaviors for Quantifying the Greenhouse Gas Emissions from the Deep Ocean

description: Data sets for the Publication 'New Bubble Transport Model Coupled with Multiple Hydrate Behaviors for Quantifying the Greenhouse Gas Emissions from the Deep Ocean' in Journal of Geophysical Research - Oceans
DOI: 10.6084/m9.figshare.13249574
title: Plasma volume and micronutrient biomarker data

description: This dataset contain information on healthy women who participated in a research on plasma volume and micronutrient biomarkers. Data blood samples were collected during the menstrual phase of their menstrual cycles to standardized the effect of ovarian hormones influences.
DOI: 10.6084/m9.figshare.13249574.v1
title: Plasma volume and micronutrient biomarker data

description: This dataset contain information on healthy women who participated in a research on plasma volume and micronutrient biomarkers. Data blood samples were collected during the menstrual phase of their menstrual cycles to standardized the effect of ovarian hormones influences.
DOI: 10.6084/m9.figshare.13284338
title: shuju

description: The population structure, pathogenicity and fungicide sensitivity of <i>Colletotrichum</i> <i>siamense</i><i> </i>from rubber tree , coffee and areca palm crops in Hainan, China were study.
DOI: 10.5281/zenodo.4289426
title: VentMon PCB and COTS BOM

description: This is a spreadsheet Bill of Materials for the parts for both the Commercial Off-The-Shelf (COTS) v0.2T and v0.3T PCB-based version of the VentMon Tester for rapidly manufactured pandemic ventilators.
description: This is an evolving product.
DOI: 10.5281/zenodo.4289425
title: VentMon PCB and COTS BOM

description: This is a spreadsheet Bill of Materials for the parts for both the Commercial Off-The-Shelf (COTS) v0.2T and v0.3T PCB-based version of the VentMon Tester for rapidly manufactured pandemic ventilators.
description: This is an evolving product.
DOI: 10.6084/m9.figshare.13284377
title: Lombardo, Thorpe, Otieno, Weglarz, Hawker - Factors associated with the mass of eggs laid by Tree Swallows (Tachycineta bicolor) varied yearly between 2008-2016 in Michigan

description: Raw data for Lombardo et al. "Factors associated with the mass of eggs laid by Tree Swallows (<i>Tachycineta bicolor</i>) varied yearly between 2008-2016 in Michigan
DOI: 10.6084/m9.figshare.13284377.v1
title: Lombardo, Thorpe, Otieno, Weglarz, Hawker - Factors associated with the mass of eggs laid by Tree Swallows (Tachycineta bicolor) varied yearly between 2008-2016 in Michigan

description: Raw data for Lombardo et al. "Factors associated with the mass of eggs laid by Tree Swallows (<i>Tachycineta bicolor</i>) varied yearly between 2008-2016 in Michigan
DOI: 10.6084/m9.figshare.12442733
title: Source Data for Swelling Manuscript

description: This is all the raw data files generated in novel experiments for the swelling manuscript. Mostly excel files. Also includes the protocol for synthesizing PVA hydrogels.Following Nov 2020 second revision for manuscript resubmission.<br>
DOI: 10.6084/m9.figshare.12442733.v5
title: Source Data for Swelling Manuscript

description: This is all the raw data files generated in novel experiments for the swelling manuscript. Mostly excel files.Following October 2020 revision for manuscript resubmission.<br>
DOI: 10.6084/m9.figshare.12805292
title: Graphpad Prism files for Swelling Manuscript

description: All the graphpad prism files used in analysis and figure generation for the swelling manuscript.Corrected lingering "CI=" in the figures.<br>Following November 2020 second revision for manuscript resubmission.
DOI: 10.6084/m9.figshare.12805292.v2
title: Graphpad Prism files for Swelling Manuscript

description: All the graphpad prism files used in analysis and figure generation for the swelling manuscript.Following October 2020 revision for manuscript resubmission.
DOI: 10.5519/qd.8dr1ucwg
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4677202 records)
DOI: 10.5519/qd.buyx0www
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (183 records)
DOI: 10.5281/zenodo.4287637
title: QTL Mapping for Resistance to Cankers Induced by Pseudomonas syringae pv. actinidiae (Psa) in a Tetraploid Actinidia chinensis Kiwifruit Population

description: Raw Illumina R2 sequence reads for individual plants genotyped for the study entitled "QTL Mapping for Resistance to Cankers Induced by <em>Pseudomonas syringae</em> pv. <em>actinidiae</em> (Psa) in a Tetraploid <em>Actinidia chinensis</em> Kiwifruit Population" accepted in MDPI Pathogen journals, Special issue <em>"</em><em>Pseudomonas syringae</em> Species Complex"
DOI: 10.5281/zenodo.4287636
title: QTL Mapping for Resistance to Cankers Induced by Pseudomonas syringae pv. actinidiae (Psa) in a Tetraploid Actinidia chinensis Kiwifruit Population

description: Raw Illumina R2 sequence reads for individual plants genotyped for the study entitled "QTL Mapping for Resistance to Cankers Induced by <em>Pseudomonas syringae</em> pv. <em>actinidiae</em> (Psa) in a Tetraploid <em>Actinidia chinensis</em> Kiwifruit Population" accepted in MDPI Pathogen journals, Special issue <em>"</em><em>Pseudomonas syringae</em> Species Complex"
DOI: 10.25345/c5vn4b
title: MassIVE MSV000086517 - GNPS_Synthetic cannabinoids_DDA_0.7_centroid
title: xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx