cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ss8cgt
title: Occurrence Download

description: A dataset containing 3119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Spain, Portugal)",
 "TaxonKey is Syllidae"
 ]
}

 The dataset includes 3119 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0219820-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4jazqb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Freycinetia leuserensis Pasaribu"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0219829-230224095556074/datasets/export for details.
DOI: 10.15468/dl.xcmtsv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryozoa",
 "DatasetKey is ATBI Parc national du Mercantour / Parco naturale Alpi Marittime-Jeux de données provenant de l'ATBI Mercantour",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0219838-230224095556074/datasets/export for details.
DOI: 10.15468/dl.eb2dx6
title: Occurrence Download

description: A dataset containing 2185881214 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 2185881214 records from 44139 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0257989-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/pgmh4trx5b
title: Lead and Tin in Tomato Mix: Data on Concentration, Consumption, and Market Display Model Analysis

description: The dataset encompasses various participant characteristics and consumption habits, including Participant ID, Gender, and Date of Birth, as well as physical attributes like Level and Body Weight. Display model preferences are also captured. The dataset further explores consumption patterns of three food items: Stew (quantity consumed, frequency per day, week, and year), Soup (quantity consumed, frequency per day, week, and year), and Jollof Rice (quantity consumed, frequency per day, week, and year). Additionally, the dataset includes concentration levels of certain substances.
DOI: 10.17632/pgmh4trx5b.1
title: Lead and Tin in Tomato Mix: Data on Concentration, Consumption, and Market Display Model Analysis

description: The dataset encompasses various participant characteristics and consumption habits, including Participant ID, Gender, and Date of Birth, as well as physical attributes like Level and Body Weight. Display model preferences are also captured. The dataset further explores consumption patterns of three food items: Stew (quantity consumed, frequency per day, week, and year), Soup (quantity consumed, frequency per day, week, and year), and Jollof Rice (quantity consumed, frequency per day, week, and year). Additionally, the dataset includes concentration levels of certain substances.
DOI: 10.34863/jct5-r220
title: Dataset: Compensation Doping of the Qubit Host Ba2CaWO6-δ

description: Dataset associated with https://doi.org/10.1016/j.mtquan.2025.100029 which synthesized single crystals of nominal composition Ba2CaW1-xMxO6-δ (M = Zr4+, Ge4+) for x = 0-0.20. Electron paramagnetic resonance (EPR) and DC magnetic susceptibility measurements were used to understand the changes in spin-active defects as a function of substitution. We find that x = 0.01 (M = Zr4+) and x = 0.03 (M = Ge4+) are sufficient to quench the W5+ S = ½ EPR response (g = 2.00) within our limit of detection. Further substitution results in the appearance of a narrow S = ½ response (g = 1.98-2.00) that again fades away at higher compositions. The data support the conclusion that compensation doping is an effective strategy for modulation of single ion centers in Ba2CaWO6-δ and identify future steps that are needed to bring such complex materials to viability for QIS technologies, including proposal of an easily measured figure of merit for rapid materials iteration and optimization.
DOI: 10.17632/thfx7cnt6w.3
title: FAKE NEWS IN THE DIGITAL ENVIRONMENT AND ITS NEGATIVE EFFECTS ON SOCIETY
DOI: 10.17632/3gzy4bjjk6.1
title: When Online Subscription Services Are Attractive: A Construal Level Perspective

description: Today’s online subscription marketplace is experiencing tremendous growth, with some estimates suggesting this exceeding a $1 trillion-dollar global market in the coming few years. Our research investigates how people perceive online subscription services from a construal-level perspective. We propose that a construal match may exist between the various characteristics of the subscription itself and how it may be advertised, potentially resulting in perceptions of a more attractive offer. Our results are novel. We first demonstrate that a monthly (annual) payment schedule or a bundle of subscription products perceived as substitutes (complements) elicit lower (higher) construal mindsets. When these are paired together, either with a congruent ad copy (e.g., a low versus high construal ad) or congruent subscription characteristics (e.g., a monthly bundle of substitutes or annual bundle of complements), the result is more favorable consumer evaluations and intentions. Our results suggest this effect may be more pronounced for low-construal conditions and less so for high-construal conditions. We also provide evidence that perceived fit and positive affect may be potential underlying mechanisms explaining these effects but may differ in their relative importance depending on subscription type. A number of theoretical and practical implications arise from our findings. 

Two data files (Study 1 and Study 2) accompany this research to test hypotheses H2, H5, H6, and H7.

H1a: A monthly subscription is processed at a low-level construal.
H1b: An annual subscription is processed at a high-level construal.
H2: A match (vs. a mismatch) between the subscription type (monthly vs. annual) and the construal level of the advertising message (low vs. high) will lead to more positive evaluations and intentions. 
H3a: A subscription bundle offering similar subscription services is perceived as offering substitutes.
H3b: A subscription bundle offering dissimilar subscription services is perceived as offering complements.
H4a: A subscription bundle offering substitutable services is processed at a low-level construal.
H4b: A subscription bundle offering complementary services is processed at a high-level construal.
H5: A match (vs. a mismatch) between the subscription type (monthly vs. annual) and the subscription bundle (substitutes vs. complements) will lead to more positive evaluations and intentions.
H6: The effect of the match between the subscription plan (monthly vs. annual) and the construal level (low vs. high) of the advertisement copy on consumer evaluations is mediated by a) perceived cognitive fit and b) positive affect.
H7: The effect of the match between the subscription plan (monthly vs. annual) and the bundle type (substitutes vs. complements) on consumer evaluations is mediated by a) perceived cognitive fit and b) positive affect.
DOI: 10.17632/k8cwxkfb92.1
title: dataset for old mdx mice with BLS-M22

description: This dataset includes all the experimental data for old mdx mice treated with BLS-M22.
DOI: 10.15468/dl.wf5n4h
title: Occurrence Download

description: A dataset containing 36817 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Streptomyces Waksman & Henrici, 1943"
 ]
}

 The dataset includes 36817 records from 429 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004029-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15530210
title: Calculation and figure data for https://doi.org/10.1103/f761-wf13

description: calculation.nb is Wolfram Mathematica file where results of https://doi.org/10.1103/f761-wf13 are computed. Other files are data for figures 5-8 computed in calculation.nb
DOI: 10.5281/zenodo.15530211
title: Calculation and figure data for https://doi.org/10.1103/f761-wf13

description: calculation.nb is Wolfram Mathematica file where results of https://doi.org/10.1103/f761-wf13 are computed. Other files are data for figures 5-8 computed in calculation.nb
DOI: 10.17632/mt4mj23j73.5
title: Planetary Health: A Comprehensive View of Food in Brazil - PHFood Brazil

description: This dataset is a result of the "Integrating national open databases for a comprehensive view on food, environment and health in Brazil", an initiative that integrates diverse national open databases to provide insights into food production, consumption, environmental impact, and public health in Brazil from 1974 to 2022. The primary hypothesis behind the dataset is that analyzing food systems, nutrition, and agricultural practices over time will reveal patterns that can inform sustainable food policies and health interventions.
We hypothesize that by aggregating and harmonizing data from various national sources, it will be possible to identify critical relationships between food production, nutrient availability, and environmental sustainability. This integrated dataset allows us to evaluate how agricultural practices and food consumption patterns have evolved in response to changing environmental, economic, and societal conditions in Brazil.
Food Production and Nutrient Data: The dataset includes detailed information on harvested areas, food production (in tons), and nutrient availability (e.g., energy, protein, fiber, vitamins, and minerals) for various food groups across different Brazilian regions and states.
Water and Environmental Data: Water usage, deficit, and environmental impact data are linked to agricultural activities, allowing the assessment of water efficiency in food production.
Pesticides and Residue Monitoring: Information on pesticide usage, maximum residue levels (MRL), and residue percentage in food items is provided, with additional details on authorized pesticide types, toxicity classifications, and environmental risks. Food Consumption: Data on food acquisition and consumption patterns, broken down by food groups (e.g., beans, vegetables, fruits), are presented, highlighting dietary trends across various population groups.
Data Collection and Methodology: The dataset was constructed by linking several government datasets, including agricultural statistics, water use reports, and residue monitoring programs. Each dataset was meticulously harmonized to ensure compatibility and completeness, following Extract, Transform, Load (ETL) processes. The data was collected over several decades, representing longitudinal trends in food systems and health. The harmonization process ensures that all data fields are consistent and comparable across time and regions.
Interpretation and Use: This dataset can be used to explore the connections between food systems, health, and the environment. It supports studies in agrifood systems, sustainability, public health, and climate change. Researchers can investigate the impacts of food production on nutrient availability, water consumption, and pesticide use over time. It can also be used to model future food system sustainability under different climate scenarios and dietary patterns, contributing to the development of food policies that balance human and planetary health.
DOI: 10.17632/mt4mj23j73.8
title: Planetary Health: A Comprehensive View of Food in Brazil - PHFood Brazil

description: This dataset is a result of the "Integrating national open databases for a comprehensive view on food, environment and health in Brazil", an initiative that integrates diverse national open databases to provide insights into food production, consumption, environmental impact, and public health in Brazil from 1974 to 2022. The primary hypothesis behind the dataset is that analyzing food systems, nutrition, and agricultural practices over time will reveal patterns that can inform sustainable food policies and health interventions.
We hypothesize that by aggregating and harmonizing data from various national sources, it will be possible to identify critical relationships between food production, nutrient availability, and environmental sustainability. This integrated dataset allows us to evaluate how agricultural practices and food consumption patterns have evolved in response to changing environmental, economic, and societal conditions in Brazil.
Food Production and Nutrient Data: The dataset includes detailed information on harvested areas, food production (in tons), and nutrient availability (e.g., energy, protein, fiber, vitamins, and minerals) for various food groups across different Brazilian regions and states.
Water and Environmental Data: Water usage, deficit, and environmental impact data are linked to agricultural activities, allowing the assessment of water efficiency in food production.
Pesticides and Residue Monitoring: Information on pesticide usage, maximum residue levels (MRL), and residue percentage in food items is provided, with additional details on authorized pesticide types, toxicity classifications, and environmental risks. Food Consumption: Data on food acquisition and consumption patterns, broken down by food groups (e.g., beans, vegetables, fruits), are presented, highlighting dietary trends across various population groups.
Data Collection and Methodology: The dataset was constructed by linking several government datasets, including agricultural statistics, water use reports, and residue monitoring programs. Each dataset was meticulously harmonized to ensure compatibility and completeness, following Extract, Transform, Load (ETL) processes. The data was collected over several decades, representing longitudinal trends in food systems and health. The harmonization process ensures that all data fields are consistent and comparable across time and regions.
Interpretation and Use: This dataset can be used to explore the connections between food systems, health, and the environment. It supports studies in agrifood systems, sustainability, public health, and climate change. Researchers can investigate the impacts of food production on nutrient availability, water consumption, and pesticide use over time. It can also be used to model future food system sustainability under different climate scenarios and dietary patterns, contributing to the development of food policies that balance human and planetary health.
DOI: 10.17632/bnc9r2vwj9.2
title: Datasets for Analyzing Riverine Bridges: A Hydrological Vulnerability Appraisal

description: The authors present two datasets designed to assess the hydrological vulnerability of riverine bridges under extreme weather conditions. These datasets aim to support infrastructure resilience studies by providing open, reproducible data for researchers and policymakers to enhance the analysis and management of flood-prone bridge systems.
See the latest version.
DOI: 10.17632/c8xyt5sdtt.1
title: Supplemental Figures

description: Supplementary figures for Chida et al., 2025.
DOI: 10.5067/p4hzb9n27eku
title: NCEP/CPC L3 Half Hourly 4km Global (60S - 60N) Merged IR V1
DOI: 10.17632/55vp52kjvg
title: Original code

description: This is the matlab source program for the article Propagation of Tricomi-Gaussian beams in a strongly nonlocal nonlinear medium.
DOI: 10.17632/55vp52kjvg.1
title: Original code

description: This is the matlab source program for the article Propagation of Tricomi-Gaussian beams in a strongly nonlocal nonlinear medium.
DOI: 10.17632/py96f2h669
title: Microdatos Gran Encuesta Integrada de Hogares (GEIH)-Redes de Cuidado

description: The dataset consists of microdata from the 2024 GEIH, provided by DANE. It includes information on general, household, labor, and other forms of work characteristics of the surveyed population. The data is freely accessible and available to the public through the official DANE website. In addition, this database contains variables created to carry out the corresponding statistical analysis.
DOI: 10.17632/py96f2h669.1
title: Microdatos Gran Encuesta Integrada de Hogares (GEIH)-Redes de Cuidado

description: The dataset consists of microdata from the 2024 GEIH, provided by DANE. It includes information on general, household, labor, and other forms of work characteristics of the surveyed population. The data is freely accessible and available to the public through the official DANE website. In addition, this database contains variables created to carry out the corresponding statistical analysis.
DOI: 10.17632/8386pzvpsj
title: Artificial rainfall on the Loess Plateau
DOI: 10.17632/8386pzvpsj.1
title: Artificial rainfall on the Loess Plateau
DOI: 10.17632/cd2hhwh6sy
title: data for “Divergent Occupational Heat Stress Strategies Required...”

description: data and code for 
"Divergent Occupational Heat Stress Strategies Required for Northern and Southern China in the Face of Climate Warming"

(1)
代码文件夹（num_*_code）和其中的代码文件已经标好序号，依次运行输出即可；
中间过程文件较大，需要自己跑出来;
由于程序分别在多台电脑上运行并优化过，可能存在代码过旧或者缺失，
请联系作者liuzhy223@mail2.sysu.edu.cn

(2)
ArcGIS_china_lossmap文件夹为在Arcgis上作的图

(3)
origin_data(share)文件夹对应了代码中读取原始数据时的路径/share
其中应当包含对应气象要素的两个GCM数据和CN05.1观测数据、CLARA-A3卫星辐射数据、ERA5再分析数据，详见文章的补充材料
这里由于网站上传限制，需要自行下载并预处理

(4)
otherdata文件夹包括了作图需要的shp文件、计算经济损失需要的人口与薪酬数据、以及主要的表格输出数据


p.s. 有缺漏的情况欢迎联系作者liuzhy223@mail2.sysu.edu.cn指出，会尽快将数据检查并更新



(1) 
The code folders (num_*_code) and their code files are numbered sequentially. Simply run them in order to generate outputs. 
Intermediate files are large and need to be generated by running the code yourself. 
Since the programs were developed and optimized across multiple computers, some code may be outdated or missing. 
Please contact the author at liuzhy223@mail2.sysu.edu.cn for assistance. 

(2) 
The **ArcGIS_china_lossmap** folder contains maps created using ArcGIS. 

(3) 
The **origin_data(share)** folder corresponds to the `/share` path referenced in the code when reading raw data. 
This should include two sets of GCM data corresponding to meteorological elements, CN05.1 observational data, 
CLARA-A3 satellite radiation data, and ERA5 reanalysis data. For details, refer to the Supplementary Materials of the article.
Note: Due to website upload restrictions, these datasets must be downloaded and preprocessed independently.

(4) 
The **otherdata** folder includes: 
- Shapefiles (shp) required for mapping, 
- Population and wage data needed for economic loss calculations, 
- Key table output data. 

**Note:** If you encounter any missing or incomplete data, please notify the author at liuzhy223@mail2.sysu.edu.cn. 
We will verify and update the data promptly.
DOI: 10.17632/cd2hhwh6sy.1
title: data for “Divergent Occupational Heat Stress Strategies Required...”

description: data and code for 
"Divergent Occupational Heat Stress Strategies Required for Northern and Southern China in the Face of Climate Warming"

(1)
代码文件夹（num_*_code）和其中的代码文件已经标好序号，依次运行输出即可；
中间过程文件较大，需要自己跑出来;
由于程序分别在多台电脑上运行并优化过，可能存在代码过旧或者缺失，
请联系作者liuzhy223@mail2.sysu.edu.cn

(2)
ArcGIS_china_lossmap文件夹为在Arcgis上作的图

(3)
origin_data(share)文件夹对应了代码中读取原始数据时的路径/share
其中应当包含对应气象要素的两个GCM数据和CN05.1观测数据、CLARA-A3卫星辐射数据、ERA5再分析数据，详见文章的补充材料
这里由于网站上传限制，需要自行下载并预处理

(4)
otherdata文件夹包括了作图需要的shp文件、计算经济损失需要的人口与薪酬数据、以及主要的表格输出数据


p.s. 有缺漏的情况欢迎联系作者liuzhy223@mail2.sysu.edu.cn指出，会尽快将数据检查并更新



(1) 
The code folders (num_*_code) and their code files are numbered sequentially. Simply run them in order to generate outputs. 
Intermediate files are large and need to be generated by running the code yourself. 
Since the programs were developed and optimized across multiple computers, some code may be outdated or missing. 
Please contact the author at liuzhy223@mail2.sysu.edu.cn for assistance. 

(2) 
The **ArcGIS_china_lossmap** folder contains maps created using ArcGIS. 

(3) 
The **origin_data(share)** folder corresponds to the `/share` path referenced in the code when reading raw data. 
This should include two sets of GCM data corresponding to meteorological elements, CN05.1 observational data, 
CLARA-A3 satellite radiation data, and ERA5 reanalysis data. For details, refer to the Supplementary Materials of the article.
Note: Due to website upload restrictions, these datasets must be downloaded and preprocessed independently.

(4) 
The **otherdata** folder includes: 
- Shapefiles (shp) required for mapping, 
- Population and wage data needed for economic loss calculations, 
- Key table output data. 

**Note:** If you encounter any missing or incomplete data, please notify the author at liuzhy223@mail2.sysu.edu.cn. 
We will verify and update the data promptly.
DOI: 10.3535/lsb-t85-zka
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7jj-flr-yd2
title: Chondrichthyes

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/v8l-zq1-wdm
title: Foraminifera d'Orbigny, 1826

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/cqm-jty-q5t
title: Foraminifera d'Orbigny, 1826

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/s1w-ml3-bte
title: Crinoidea Miller, 1821

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/9fv-hva-gae
title: Cnidaria

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ksb-yqs-gsx
title: Cervidae Goldfuss, 1820

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/wbv-j6b-1kl
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/nsv-fka-78b
title: Physeter Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/w3s-ydy-kp8
title: Homo sapiens Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/097-fq7-8e7
title: Canis lupus familiaris Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ssg-d7c-l7y
title: Equus Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/mp2-vas-90v
title: †Echinocorys scutata Leske, 1778

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/sha-h3n-976
title: Cervidae Goldfuss, 1820

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/he2-p6e-234
title: †Palorbitolina lenticularis (Blumenbach, 1805)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/tzs-v1c-haz
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/6d4-6zd-p10
title: Allomorphina Reuss in Cžjžek, 1849

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/zeg-jxy-01b
title: Isurus

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/zqe-fpd-std
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/9z4-8vs-zr4
title: Foraminifera d'Orbigny, 1826

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.