cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15620590
title: Simulation data for "Monitored Fluctuation Hydrodynamics"

description: Simulation data for figures 1 and 2 of S. Gopalakrishnan, E. McCulloch, R. Vasseur, "Monitored Fluctuating Hydrodynamics" (https://arxiv.org/abs/2504.02734).This dataset contains trajectory-averaged simulation data from two monitored stochastic models presented in Figures 1 and 2 of Gopalakrishnan et al., 2025. The files include:



monitored_tasep_static_correlator.csv: Trajectory averaged static two-point function data from a monitored totally asymmetric exclusion process as described in Gopalakrishnan et al., 2025. File format:



Column grouped by measurement frequency.

Subcolumns: x (position), corr (two-point function value).






U1_semidirect_Z2_monitoring_posterior_entropy.csv: Trajectory averaged entropy data for the posterior charge distribution after time t = L (system size) for a U(1) ⨁ Z₂ symmetric stochastic lattice gas as described in Gopalakrishnan et al., 2025. File format:



Columns grouped by system size.

Subcolumns: p (measurement frequency), S (posterior entropy).






U1_semidirect_Z2_monitoring_autocorrelator.csv: Trajectory averaged dynamical autocorrelator data for a U(1) ⨁ Z₂ symmetric stochastic lattice gas as described in Gopalakrishnan et al., 2025. File format:



Columns grouped by bond dimension (used for matrix-product-state simulation). 

Subcolumns: t (time), corr (autocorrelation function value), smooth corr (gaussian smoothed autocorrelation function value).






U1_semidirect_Z2_monitoring_full_correlator.csv: Trajectory averaged spatially resolved dynamical two-point function data for a U(1) ⨁ Z₂ symmetric stochastic lattice gas as described in Gopalakrishnan et al., 2025. File format:



Columns grouped by simulation time

Subcolumns: x (position), corr (dynamical two-point function value), smooth corr (gaussian smoothed dynamical two-point function value).




Data are in CSV format. Details on models/simulation parameters are provided in the accompanying article.
DOI: 10.34740/kaggle/dsv/12101839
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.57967/hf/5749
title: ClinVar-STXBP1-NLP-Dataset-Pathogenic
DOI: 10.15468/dl.bykwsc
title: Occurrence Download

description: A dataset containing 1729761 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Morocco",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1729761 records from 1389 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029730-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e209669
title: Baseline Resilience Indicators for Communities (BRIC) Index

description: The Baseline Resilience Indicators for Communities Index aims to help
identify communities that are resilient to natural hazards. This BRIC data set
contains polygon layers for the overall Hazards Vulnerability and Resilience
Institute (HVRI) BRIC using six capitals (Social, Economic, Community,
Economic, Institutional, Housing and Infrastructural, and Environmental) based
on county-level inputs from 2010, 2015, and 2020. The files contain all six
capital scores and the BRIC score for each county. BRIC values range from 0 to
6 based on the six capital scores ranging from 0 to 1. Capital scores are
calculated from min-maxed values of each of their component variables. For all
variables, capitals, and the BRIC values, 0 represents the lowest community
resilience, and higher values represent the most resilient counties. The data
are provided for the entire United States following the county geography of the
year the BRIC was created and for the contiguous United States following the
county geography of the year the BRIC was created. 2010 BRIC is only available
for the contiguous United States.
description: The data are not weighted.
description: Counties in the United States, excluding U.S. island territories. Smallest Geographic Unit: County
DOI: 10.3886/e209669v2-181162
title: Baseline Resilience Indicators for Communities (BRIC) Index

description: The Baseline Resilience Indicators for Communities Index aims to help
identify communities that are resilient to natural hazards. This BRIC data set
contains polygon layers for the overall Hazards Vulnerability and Resilience
Institute (HVRI) BRIC using six capitals (Social, Economic, Community,
Economic, Institutional, Housing and Infrastructural, and Environmental) based
on county-level inputs from 2010, 2015, and 2020. The files contain all six
capital scores and the BRIC score for each county. BRIC values range from 0 to
6 based on the six capital scores ranging from 0 to 1. Capital scores are
calculated from min-maxed values of each of their component variables. For all
variables, capitals, and the BRIC values, 0 represents the lowest community
resilience, and higher values represent the most resilient counties. The data
are provided for the entire United States following the county geography of the
year the BRIC was created and for the contiguous United States following the
county geography of the year the BRIC was created. 2010 BRIC is only available
for the contiguous United States.
description: The data are not weighted.
description: Counties in the United States, excluding U.S. island territories. Smallest Geographic Unit: County
DOI: 10.3886/e209669v2-181163
title: Baseline Resilience Indicators for Communities (BRIC) Index

description: The Baseline Resilience Indicators for Communities Index aims to help
identify communities that are resilient to natural hazards. This BRIC data set
contains polygon layers for the overall Hazards Vulnerability and Resilience
Institute (HVRI) BRIC using six capitals (Social, Economic, Community,
Economic, Institutional, Housing and Infrastructural, and Environmental) based
on county-level inputs from 2010, 2015, and 2020. The files contain all six
capital scores and the BRIC score for each county. BRIC values range from 0 to
6 based on the six capital scores ranging from 0 to 1. Capital scores are
calculated from min-maxed values of each of their component variables. For all
variables, capitals, and the BRIC values, 0 represents the lowest community
resilience, and higher values represent the most resilient counties. The data
are provided for the entire United States following the county geography of the
year the BRIC was created and for the contiguous United States following the
county geography of the year the BRIC was created. 2010 BRIC is only available
for the contiguous United States.
description: The data are not weighted.
description: Counties in the United States, excluding U.S. island territories. Smallest Geographic Unit: County
DOI: 10.15468/dl.k6qhp3
title: Occurrence Download

description: A dataset containing 23596 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (iNaturalist Research-grade Observations, Kenneth S. Norris Center for Natural History, University of California Santa Cruz, Insect Collection, Global distribution of marine forests [literature records], Great Backyard Bird Count, Sea spray aerosols at Three California Beaches, NOAA Deep-Sea Coral Research and Technology Program, MARINe/PISCO: Intertidal: MARINe Long-Term Monitoring Surveys: Photo Plots and Transects Summarized, UCSC Herbarium - Kenneth S. Norris Center for Natural History, University of California Santa Cruz, Species-specific associations between bacterioplankton and photosynthetic picoeukaryotes)",
 "Geometry POLYGON((-122.07433 37.00686,-122.03373 37.00686,-122.03373 37.0524,-122.07433 37.0524,-122.07433 37.00686))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 23596 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029731-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.69zwhu
title: Occurrence Download

description: A dataset containing 12953 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.45322 6.05059,-75.46314 6.03244,-75.45865 6.00883,-75.43121 6.00068,-75.41309 6.00484,-75.40012 6.01315,-75.39622 6.02465,-75.39503 6.03771,-75.40234 6.05342,-75.41231 6.05741,-75.42279 6.05824,-75.43061 6.05924,-75.45322 6.05059))",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 12953 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029732-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29265061
title: Global burden and epidemic trends of chronic kidney disease attributable to high body mass index: insights from the Global Burden of Disease Study 2021

description: High body mass index (BMI) is associated with an increased risk of chronic kidney disease (CKD). However, studies on the CKD burden due to high BMI are limited. This research uses data from the Global Burden of Disease (GBD) study to analyze the epidemiological characteristics of CKD due to high BMI from 1990 to 2021, including mortality rate and disability-adjusted life years (DALYs). Age-standardized mortality rate (ASMR) and age-standardized DALY rate (ASDR) were calculated, with stratified analyses by sex, age, and socio-demographic index (SDI) regions. The estimated annual percentage change (EAPC) assessed the trends over 32 years, and a Bayesian age-period-cohort (BAPC) model predicted the disease burden for the next 15 years. In 2021, the ASMR and ASDR for CKD attributable to high BMI globally were estimated at 5.06 [95% uncertainty interval (UI): 2.70–7.51] and 122.08 (95% UI: 66.25–180.18) per 100,000 population, respectively. Significant variations in these metrics were observed across sex, age groups, and regions. Between 1990 and 2021, both ASMR and ASDR exhibited an upward trajectory, with projections indicating a continued rise through to 2040. Our findings indicate that the CKD burden due to high BMI is increasing, with notable disparities across sex, age, and geographic regions. Targeted public health interventions, particularly those focusing on males and older adults, are essential to address this growing health challenge.
DOI: 10.6084/m9.figshare.29265061.v1
title: Global burden and epidemic trends of chronic kidney disease attributable to high body mass index: insights from the Global Burden of Disease Study 2021

description: High body mass index (BMI) is associated with an increased risk of chronic kidney disease (CKD). However, studies on the CKD burden due to high BMI are limited. This research uses data from the Global Burden of Disease (GBD) study to analyze the epidemiological characteristics of CKD due to high BMI from 1990 to 2021, including mortality rate and disability-adjusted life years (DALYs). Age-standardized mortality rate (ASMR) and age-standardized DALY rate (ASDR) were calculated, with stratified analyses by sex, age, and socio-demographic index (SDI) regions. The estimated annual percentage change (EAPC) assessed the trends over 32 years, and a Bayesian age-period-cohort (BAPC) model predicted the disease burden for the next 15 years. In 2021, the ASMR and ASDR for CKD attributable to high BMI globally were estimated at 5.06 [95% uncertainty interval (UI): 2.70–7.51] and 122.08 (95% UI: 66.25–180.18) per 100,000 population, respectively. Significant variations in these metrics were observed across sex, age groups, and regions. Between 1990 and 2021, both ASMR and ASDR exhibited an upward trajectory, with projections indicating a continued rise through to 2040. Our findings indicate that the CKD burden due to high BMI is increasing, with notable disparities across sex, age, and geographic regions. Targeted public health interventions, particularly those focusing on males and older adults, are essential to address this growing health challenge.
DOI: 10.6084/m9.figshare.29265056
title: Chilean household food-demand MDCEV outputs and price-scenario predictions, stratified by socio-economic status (EPF IX, 2021-2022)

description: This study investigates how Chilean households would adjust their food purchasing patterns—and how their welfare would change—if they moved toward the healthy-sustainable diet recommended by the EAT-Lancet Commission. We merge nationally representative micro-data from the 2021-2022 Family Budget Survey (EPF IX, 5 682 urban households) with nutrient conversion factors and EAT-Lancet intake targets for 17 food groups. A Multiple-Discrete Continuous Extreme Value (MDCEV) demand system is estimated separately for three socio-economic strata (low, middle, high income). The model captures both the discrete choice of which food groups are purchased and the continuous decision of how much to spend on each, while allowing for corner solutions.Using the fitted MDCEV coefficients, we run virtual-price simulations that make the EAT-Lancet basket just affordable for the median household in each stratum. These counterfactual prices generate predicted quantities and expenditure shares, from which we calculate Laspeyres, Paasche, Fisher and a novel “Naïve” price index. Compensating‐variation measures link the indices to consumer welfare, revealing which income groups would gain or lose from the dietary transition once realistic adoption frictions are acknowledged.The accompanying data files include:γ, δ and β parameter estimates (with robust standard errors) for each income stratumsimulated price predictions under the EAT-Lancet scenario.All R scripts required to clean the raw EPF data, estimate the MDCEV models (via the <b>apollo</b> package), and reproduce every figure and table will be released in an open repository upon publication. The work provides the first demand-system-based affordability and welfare assessment of the EAT-Lancet diet in Latin America, offering actionable insights for nutrition and fiscal-policy design aimed at equitable, sustainable dietary change.
DOI: 10.6084/m9.figshare.29265056.v1
title: Chilean household food-demand MDCEV outputs and price-scenario predictions, stratified by socio-economic status (EPF IX, 2021-2022)

description: This study investigates how Chilean households would adjust their food purchasing patterns—and how their welfare would change—if they moved toward the healthy-sustainable diet recommended by the EAT-Lancet Commission. We merge nationally representative micro-data from the 2021-2022 Family Budget Survey (EPF IX, 5 682 urban households) with nutrient conversion factors and EAT-Lancet intake targets for 17 food groups. A Multiple-Discrete Continuous Extreme Value (MDCEV) demand system is estimated separately for three socio-economic strata (low, middle, high income). The model captures both the discrete choice of which food groups are purchased and the continuous decision of how much to spend on each, while allowing for corner solutions.Using the fitted MDCEV coefficients, we run virtual-price simulations that make the EAT-Lancet basket just affordable for the median household in each stratum. These counterfactual prices generate predicted quantities and expenditure shares, from which we calculate Laspeyres, Paasche, Fisher and a novel “Naïve” price index. Compensating‐variation measures link the indices to consumer welfare, revealing which income groups would gain or lose from the dietary transition once realistic adoption frictions are acknowledged.The accompanying data files include:γ, δ and β parameter estimates (with robust standard errors) for each income stratumsimulated price predictions under the EAT-Lancet scenario.All R scripts required to clean the raw EPF data, estimate the MDCEV models (via the <b>apollo</b> package), and reproduce every figure and table will be released in an open repository upon publication. The work provides the first demand-system-based affordability and welfare assessment of the EAT-Lancet diet in Latin America, offering actionable insights for nutrition and fiscal-policy design aimed at equitable, sustainable dietary change.
DOI: 10.6084/m9.figshare.29261420
title: CTD_Linedata_Marshall_2024-2025.xlsx

description: Vertical profile of water temperature and salinity in Majuro Lagoon
DOI: 10.6084/m9.figshare.29261420.v2
title: CTD_Linedata_Marshall_2024-2025.xlsx

description: Vertical profile of water temperature and salinity in Majuro Lagoon
DOI: 10.6084/m9.figshare.29261420.v1
title: CTD_Linedata_Marshall_2024-2025.xlsx

description: Vertical profile of water temperature and salinity in Majuro Lagoon
DOI: 10.5517/cc85ydr
title: CCDC 244044: Experimental Crystal Structure Determination

description: Related Article: H.Arslan, U.Florke, N.Kulcu|2004|Acta Chim.Slov.|51|787|
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/cc85ycq
title: CCDC 244043: Experimental Crystal Structure Determination

description: Related Article: V.N.Britsun, A.N.Borisevich, L.S.Samoilenko, A.N.Chernega, M.O.Lozinsky|2005|Izv.Akad.Nauk SSSR,Ser.Khim.||757|
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: 10.5281/zenodo.15620697
title: Test dataset for weed detection in lettuce farms

description: Results of weed recognition tests utilizing R-CNN or DETR models, followed by post-analysis with Segment Anything.
DOI: 10.5281/zenodo.15620698
title: Test dataset for weed detection in lettuce farms

description: Results of weed recognition tests utilizing R-CNN or DETR models, followed by post-analysis with Segment Anything.
DOI: 10.5281/zenodo.15620716
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250608x Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250608x Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.15620717
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250608x Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250608x Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.48610/449d8e0
title: LSAC Logistic Regression Syntax

description: Logistic regression using Longitudinal Study of Australian Children (LSAC), K Cohort data. Includes missing data analysis, case selection, bivariate associations, reliability analysis, descriptive analyses, variable transformation, logistic regression. Moderated logistic regression was conducted to examine the effect of parenting (warmth, hostility, monitoring, communication) on the relationship between mothers’ ACEs and adolescents’ risk for poor resilience, controlling for demographic characteristics. 

Original LSAC data dictionaries are available at http://aifs.gov.au/growing-up-in-australia. LSAC data access is available on application to Australian Government Department of Social Services, https://www.dss.gov.au/long-term-research/accessing-our-datasets.
DOI: 10.15468/dl.r7h49f
title: Occurrence Download

description: A dataset containing 3279 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atelopus ignescens (Cornalia, 1849)"
 ]
}

 The dataset includes 3279 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029734-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7zzu8j
title: Occurrence Download

description: A dataset containing 3170 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Boana boans (Linnaeus, 1758)"
 ]
}

 The dataset includes 3170 records from 149 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0300434-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r3myps
title: Occurrence Download

description: A dataset containing 23362 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Castor canadensis Kuhl, 1820",
 "HasCoordinate is true"
 ]
}

 The dataset includes 23362 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0264275-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xmg9rp
title: Occurrence Download

description: A dataset containing 2996 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Continent is Europe",
 "Year is greater than 1978",
 "Year is less than 2014",
 "HasGeospatialIssue is false",
 "TaxonKey is Coincya richeri (Vill.) Greuter & Burdet"
 ]
}

 The dataset includes 2996 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0109583-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h6pzp6
title: Occurrence Download

description: A dataset containing 14684 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bembidion lampros (Herbst, 1784))",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 14684 records from 221 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0232801-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aifkzm
title: Occurrence Download

description: A dataset containing 239765 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is MVZ Mammal Collection (Arctos)"
 ]
}

 The dataset includes 239765 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049621-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.