cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5879022
title: Global forest management data at a 100m resolution for the year 2015

description: We provide four data records: 1.The reference data set as a comma-separated file ("reference_data_set.csv") with the following attributes: “ID” is a unique location identifier “Latitude, Longitude” are centroid coordinates of a 100m x 100m pixel. “Land_use_ID “is a land use class: 11 - Naturally regenerating forest without any signs of human activities, e.g., primary forests. 20 - Naturally regenerating forest with signs of human activities, e.g., logging, clear cuts etc. 31 - Planted forest. 32 - Short rotation plantations for timber. 40 - Oil palm plantations. 53 - Agroforestry. “Flag” identifies a data origin: 1- the crowdsourced locations, 2- the control data set, 0 – the additional experts' classifications following the opportunistic approach. 2. The 100 m forest management map in a geoTiff format with the classes presented - "FML_v3.2.tif ". 3. The predicted class probability from the Random Forest classification in a geoTiff format - "ProbaV_LC100_epoch2015_global_v2.0.3_forest-management--layer-proba_EPSG-4326.tif" 4. Validation data set as a comma-separated file ("validation_data_set.csv) with the following attributes: “ID” is a unique location identifier “pixel_center_x” , “pixel_center_y ” are centroid coordinates of a 100m x 100m pixel in lat/lon projection “first_landuse_class “is a land use class, as in (1). “second_landuse_class “is a second possible land use class, as in (1), identified in case it was difficult to assign one class with high confidence. 5. Original crowdsourced data set as a .csv table. 6. Compiled FAO FRA forest statistics and mapped classes by countries into one table (.csv format).
description: NatureMap project (https://naturemap.earth/) Funder Norway's International Climate and Forest Initiative (NICFI): https://www.norad.no/en/front/thematic-areas/climate-change-and-environment/norways-international-climate-and-forest-initiative-nicfi/ This is a similar data set on zenodo (Lesiv, M. et al. Global planted trees extent 2015. Zenodo https://doi.org/10.5281/zenodo.3931930, 2020) This is the version that was used in one of the follow up studies, which was needed as a reference. Please ignore it and instead use this zenodo record.
DOI: 10.5281/zenodo.6984619
title: A comprehensive geospatial database of nearly 100,000 reservoirs in China

description: Data components
Folder "CRD v1.1" contains the recorded (5,143) reservoirs from yearbook and document data and all (97,435) reservoirs from CRD v1.1 (China Reservoir Database) two parts:
• CRD_v11_all_reservoirs (in both shapefile format and the comma-separated values (csv) format): This database catalogs the location information of 97,435 reservoirs in China, with an aggregated area of 50,085.21 km2 and an estimated total storage capacity of 979.62 Gt. The attributes of all the CRD v1.1 reservoirs (in all cases) include location information (longitude, latitude, province, prefecture, and county), inundation area, estimated storage capacity, river order, discharge, and residence time of reservoirs.
• CRD_v11_record_reservoirs (in both shapefile and csv): The 5,143 reservoirs in the CRD v1.1 database were directly derived from the yearbook and other documents data, accounting for 59% and 82% of the total reservoir area and storage capacity of the CRD v1.1 database, respectively. This reservoir information was mainly obtained through manual compilation. The attributes of the recorded reservoirs include the longitude and latitude of the reservoir, name, province, prefecture, and county where the reservoir is located, water area, water level of normal storage capacity, storage capacity, reservoir class, main use, and regulation type.
Note: Thank you for accessing the CRD v1.1 dataset, which is available through the new link: https://www.scidb.cn/s/zqIFVr; DOI: 10.57760/sciencedb.05331
DOI: 10.5281/zenodo.7898409
title: Global gridded GDP under the historical and future scenarios

description: We have extended the time series of global GDP based on Version 5 at https://zenodo.org/record/5880037#.Yyx4lsi5fRQ, which makes the following changes: a) includes annual global GDP from 2000 - 2020, the unit is PPP 2005 international dollars. b) updates the GDP projections for the period 2025 - 2100 at five-year intervals under five SSPs, and the unit is PPP 2005 international dollars, which allows for comparsion against the historical values mention above. This dataset consists of a total of 101 tif images with spatial resolutions of 1 km (in 7 zip files) and 0.25-degree, respectively. The gridded GDP are distributed over land, with Antarctica, oceans, and some non-illuminated or depopulated areas marked as zero. The spatial extents are 90S - 90N and 180E - 180W in standard WGS84 coordinate system. For more details, please refer to the article: Global gridded GDP data set consistent with the shared socioeconomic pathways that is consistent with Version 5 (GDP unit is PPP 2005 U.S. dollars).
description: {"references": ["Geiger, T.: Continuous national gross domestic product (GDP) time series for 195 countries: past observations (1850\u20132005) harmonized with future projections according to the Shared Socio-economic Pathways (2006\u20132100), Earth System Science Data, 10, 847\u2013856, 2018.", "Dellink, R., Chateau, J., Lanzi, E., and Magn\u00e9, B.: Long-term economic growth projections in the Shared Socioeconomic Pathways, Global Environmental Change, 42. 200-214, 2015.", "Wang, X., Meng, X., Long, Y. (2022) Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways. Scientific data 9, 1-13."]}
DOI: 10.5285/5f331c418e9f4935b8eb1b836f8a91b8
title: ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2010, 2017 and 2018, v3

description: This dataset comprises estimates of forest above-ground biomass for the years 2010, 2017 and 2018. They are derived from a combination of Earth observation data, depending on the year, from the Copernicus Sentinel-1 mission, Envisat’s ASAR instrument and JAXA’s Advanced Land Observing Satellite (ALOS-1 and ALOS-2), along with additional information from Earth observation sources. The data has been produced as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme by the Biomass CCI team. This release of the data is version 3. Compared to version 2, this is a consolidated version of the Above Ground Biomass (AGB) maps. This version also includes a preliminary estimate of AGB changes for two epochs. The data products consist of two (2) global layers that include estimates of: 1) above ground biomass (AGB, unit: tons/ha i.e., Mg/ha) (raster dataset). This is defined as the mass, expressed as oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees excluding stump and roots 2) per-pixel estimates of above-ground biomass uncertainty expressed as the standard deviation in Mg/ha (raster dataset) In addition, files describing the AGB change between 2018 and the other two years are provided (labelled as 2018_2010 and 2018_2017). These consist of two sets of maps: the standard deviation of the AGB change and a quality flag of the AGB change. Note that the change itself can be simply computed as the difference between two AGB maps, so is not provided directly. Data are provided in both netcdf and geotiff format.
DOI: 10.5439/1025186
title: dlppi

description: ARM Instrument: Doppler Lidar
DOI: 10.6084/m9.figshare.17104244
title: data (20201.1-20201.7).xlsx

description: The development of many intelligent technologies, such as artificial intelligence and the Internet of Things, has brought new opportunities for water industry intelligence. Based on intelligent pressure regulation technology, the intelligent pressure regulating vehicle (IPRV) was designed. The S-cell of Tie Gang Village, Baoan District, Shenzhen, China was selected as the experimental case.A one-week trial was conducted from January 1 to January 7, 2020, and measured data were collected at 5-minute intervals for <i>P</i><sub>1 </sub>(pressure at PRV inlet point), <i>P</i><sub>3 </sub>(pressure at critical point), and <i>Q </i>(flow at zone inlet point). The IPRV has the functions of developing pressure regulating scheme, pressure reduction potential analysis, etc. by analysis the data.
DOI: 10.6084/m9.figshare.25777452
title: Aquatic Coleoptera and Heteroptera occurrence data from the Huyck Preserve, New York during summer 2022

description: Aquatic and semiaquatic insects were documented from the Edward Niles Huyck Preserve and Biological Research Station in Albany County, New York, United States during June and August 2022. A total of 54 species of Heteroptera were recorded from 13 families, while 127 species of aquatic Coleoptera were recorded from 13 families.
DOI: 10.6084/m9.figshare.26965444
title: Ultra-Sensitive Hydrogen Sulfide Detection via Hybrid Small-Molecule Nano-arrays

description: The source data underlying Figs. 2d, 3b, and 4b and Supporting Information Figs. S2a-b, S3a–b, S4a-b, S5, S6a-b, S7d-e, S8, S9, S11, and S14 are provided as a Source Data file.
DOI: 10.15468/dl.7gw3fs
title: Occurrence Download

description: A dataset containing 2342 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Kenya",
 "OccurrenceStatus is Present",
 "TaxonKey is Aleyrodidae"
 ]
}

 The dataset includes 2342 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061718-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15485/1841748
title: The Advanced Global Atmospheric Gases Experiment (AGAGE) Data

description: In the ALE/GAGE/AGAGE global network program, continuous high frequency gas chromatographic measurements of four biogenic/anthropogenic gases (methane, CH4; nitrous oxide, N2O; hydrogen, H2; and carbon monoxide, CO) and several anthropogenic gases that contribute to stratospheric ozone destruction and/or to the greenhouse effect have been carried out at five globally distributed sites for several years. The program, which began in 1978, is divided into three parts associated with three changes in instrumentation: the Atmospheric Lifetime Experiment (ALE), which used Hewlett Packard HP5840 gas chromatographs; the Global Atmospheric Gases Experiment (GAGE), which used HP5880 gas chromatographs; and the present Advanced GAGE (AGAGE). AGAGE uses two types of instruments: a gas chromatograph with multiple detectors (GC-MD), and a gas chromatograph with mass spectrometric analysis (GC-MS). Beginning in January 2004, an improved cryogenic preconcentration system (Medusa) replaced the absorption-desorption module in the GC-MS systems at Mace Head and Cape Grim; this provided improved capability to measure a broader range of volatile perfluorocarbons with high global warming potentials. The Medusa GC-MS systems were subsequently used at other AGAGE stations (Trinidad Head, Barbados, American Samoa, Zeppelin, Jungfraujoch, and Goan) after the initial setup at Mace Head and Cape Grim. More information may be found at the AGAGE home page: https://agage.mit.edu/instruments.Compared to the previous version (https://data.ess-dive.lbl.gov/datasets/doi: doi:10.15485/1781803), the latest update (Agage_gcmd_gcms.data.2022_01_03.tar.gz) includes 6 months of new data through the end of September 2020. For a complete list of released compounds and used standard scales, please see “AGAGE_scale_2021_v1.pdf” file. Additional information can also be found on the AGAGE website (https://agage.mit.edu).
DOI: 10.3886/e199282v1
title: Data and Code for: "Dynamic Inconsistency in Risky Choice: Evidence from the Lab and Field"

description: We document a robust dynamic inconsistency in risky choice. Using a unique brokerage dataset and a series of experiments, we compare people’s initial risk-taking plans to their subsequent decisions. Across settings, people accept risk as part of a “loss-exit” strategy --- planning to continue taking risk after gains and stopping after losses. Actual behavior deviates from initial strategies by cutting gains early and chasing losses. More people accept risk when offered a commitment to their initial strategy. Our results help reconcile seemingly contradictory findings on risk-taking in static versus dynamic contexts. We explore implications for theory and welfare.
description: all observations are equal-weighted
description: Response Rates: above 95% in each experiment
description: Presence of Common Scales: The main variables are binary investment choices and numerical values (gain and loss limits). Several Likert-type scales were used for the elicitation of demographic variables.
description: In total, we ran experiments with 2621 participants. Thereof, 1085 subjects were recruited from the online platform Prolific and 1536 were recruited from Amazon Mechanical Turk via Cloud Research. In both cases, we used standard sample selection criteria. For experiments on Prolific we included subjects with an approval rating of at least 97% with location in the US, UK or Ireland. For experiments on MTurk via Cloud Research, we included subjects with approval rate of 95 or higher, less than 10k HITs and location in the US. We further apply the suspicious geocode block provided by Cloud Research. Furthermore, within each online platform, we excluded subjects who had already participated in previous experiments. Last but not least, experiments conducted on Prolific included a set of attention checks, a bot check and a language check. Subjects, who did not pass either one of these checks, were not allowed to proceed with the experiment.
description: Participants in online experiments recruited from the platform for academic studies Prolific. . Smallest Geographic Unit: english-speaking world
description: web-based survey;
DOI: 10.5281/zenodo.13895326
title: Dataset for "On the quantification of thermodynamic phases of raining clouds: insights from multi-year CloudSat and ground-based radar observations over Longmen, Southern China"
DOI: 10.5281/zenodo.13926360
title: Integrative determination of atomic structure of mutant huntingtin exon 1 fibrils implicated in Huntington disease — data files

description: This zenodo entry contains MD and solid-state NMR data files for the paper:

 

Mahdi Bagherpoor Helabad et al. (2024)  Integrative determination of atomic structure of mutant huntingtin exon 1 fibrils implicated in Huntington disease

 

 

MD datasets and code

We provide here (in MD_simulations_data_codes.zip) the MD simulations files for the MD runs and also data, and their respective codes, shown in the figures of the above papers.

 

Data file structure: 

MD_data 



The MD simulation run files for three fully periodic systems—PolyQ15 and HTTex1—include the following: .gro files for both minimization and final structures, production .tpr files, force field parameters, GROMACS .mdp files, and position and dihedral restraint files.



fully_periodic_systems

polyQ15

HTTex1




Figs_Data_Codes





The data and in-house Python scripts associated with creating the figures:



Fig2B_S4 for Figure 2B and Supplementary Figure 4

Fig2D_S5 for Figure 2D and Supplementary Figure 5

Fig3C_S10 for Figure 3C and Supplementary Figure 10

Fig4_S12_S13_S14 for Figure 4C and Supplementary Figures 12–14

Fig6C for Figure 6C

FigS3B_S6 for Supplementary Figures 3B and 6

FigS8 for Supplementary Figure 8

FigS9_S11 for Supplementary Figures 9–11

FigS16_to_S21 for Supplementary Figures 16–21

FigS22 for Supplementary Figure 22

readMe.txt

 






Fig6_c_barplot_data.xlsx





Excel file with data plotted in Figure 6C.


N17_SecStr_convergence.xlsx





Excel file with convergence data for N17 domain.




Solid-state NMR data

We provide here the solid-state NMR spectrum files for the data shown in figures of the above paper.

 

Data file structure:

 

SSNMR_data_listing_20241011a.txt





text file describing the ssNMR data files



SSNMR_data.zip



Figure_1 - data for Figure 1F

Figure_5 - data for Figure 5

Figure_6 - data for Figure 6

Figure_S7 - data for Figure 2G and Supplementary Figure 7

Figure_S15 - NMR data for HDX ssNMR of fibrils – Supplementary Figure 15


Fig6_b_barplot_data.xlsx





Excel file with data plotted in Figure 6B, based on previously reported results (DOI 10.1038/ncomms15462)



 

Data are provided in either Bruker Topspin format, or in NMRPIPE format (ft2 extension).

Experimental parameters are described in the published paper and its Supplementary Information files. In general, these are all data from magic-angle-spinning (MAS) NMR studies of intact amyloid fibrils made with isotope labeled HTTex1 fibrils. Experimental types include 2D CP-DARR, 2D TOBSY, 2D HETCOR spectra as well as relaxation measurements.  Aside from NMR datafiles, also documents with interpreted and integrated data are included, used to make data curves in the figure (e.g. for Prism software).
DOI: 10.5281/zenodo.6637599
title: Tallo database

description: The <strong>Tallo database</strong> (v1.0.0) is a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. Data were compiled from 61,856 globally distributed sites and include measurements for 5,163 tree species. For a full description of the database, see: <strong>Jucker <em>et al</em>. (2022) Tallo </strong>–<strong> a global tree allometry and crown architecture database. Global Change Biology, https://doi.org/10.1111/gcb.16302</strong>. If using the Tallo database in your work please cite the original publication listed above, as well as this repository using the corresponding DOI (10.5281/zenodo.6637599).
DOI: 10.15468/dl.yz8btz
title: Occurrence Download

description: A dataset containing 40308 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "GadmGid is USA.1.31_1",
 "TaxonKey is Passeriformes",
 "Year 1994-2023"
 ]
}

 The dataset includes 40308 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053000-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.832cdk
title: Occurrence Download

description: A dataset containing 27624 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ctenolabrus rupestris (Linnaeus, 1758)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 27624 records from 134 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053001-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.taedb9
title: Occurrence Download

description: A dataset containing 3038186287 species occurrences available in GBIF matching the query:
{
 "OccurrenceStatus" : [
 "is Present"
 ]
}

 The dataset includes 3038186287 records from 70158 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052969-241126133413365/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.28120409
title: Observed and modeled cloud absorption

description: <i>R</i>、<i>α</i><sub><em>c</em></sub> and <i>α</i><sub><em>ca</em></sub> across different sites
DOI: 10.6084/m9.figshare.28120409.v1
title: Observed and modeled cloud absorption

description: <i>R</i>、<i>α</i><sub><em>c</em></sub> and <i>α</i><sub><em>ca</em></sub> across different sites
DOI: 10.15468/dl.rvdqqm
title: Occurrence Download

description: A dataset containing 5785 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Chinese Taipei)",
 "OccurrenceStatus is Present",
 "TaxonKey is Leucaena leucocephala (Lam.) de Wit"
 ]
}

 The dataset includes 5785 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053003-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qbzdm5
title: Occurrence Download

description: A dataset containing 78399 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "TaxonKey is Epilobium ciliatum subsp. ciliatum"
 ]
}

 The dataset includes 78399 records from 367 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053005-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k9cnrz
title: Occurrence Download

description: A dataset containing 26353 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "GadmGid is GBR.3.16_1",
 "TaxonKey is Passeriformes",
 "Year 1994-2023"
 ]
}

 The dataset includes 26353 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053007-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u2nkx2
title: Occurrence Download

description: A dataset containing 7770756 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Hong Kong, Macao)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year 1970-2025"
 ]
}

 The dataset includes 7770756 records from 2154 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053006-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17316335
title: Failure Mechanism of the May 2024 Meizhou–Dapu Expressway Embankment Landslide
DOI: 10.5281/zenodo.17316336
title: Failure Mechanism of the May 2024 Meizhou–Dapu Expressway Embankment Landslide
DOI: 10.13012/b2idb-9953689_v1
title: Data for Conversion of High-Solids Hydrothermally Pretreated Bioenergy Sorghum to Lipids and Ethanol Using Yeast Cultures

description: Glucose and xylose are the major sugars present in cellulosic hydrolysates. The cellulosic sugars can be used for the production of platform chemicals. In this study, productions of lipid and ethanol by yeasts were compared for concentrated bioenergy sorghum syrup. Bioenergy sorghum was hydrothermally pretreated at 50% w/w solids in a continuous industrial reactor and sequentially mechanically refined using a burr mill to improve biomass accessibility for hydrolysis. Fed-batch enzymatic hydrolysis was conducted with 50% w/v solids loading and cellulase cocktail (50 FPU/g biomass) to achieve 230 g/L sugar concentration. Various strains of Rhodosporidium toruloides were evaluated for converting sugars into lipids, and strain Y-6987 had the highest lipid titer (9.2 g/L). The lipid titer was improved to 19.0 g/L by implementing a two-stage culture scheme, where the first stage was optimized for yeast growth and the second for lipid production. For ethanol production, the engineered Saccharomyces cerevisiae SR8ΔADH6 was used to coferment glucose and xylose. Ethanol fermentation was optimized for media nutrients (YP, YNB/urea, and urea), cellulosic sugar concentration, and sulfite conditioning to maximize the ethanol concentration from sorghum syrups. Fermentation of 70% v/v concentrated hydrolysate conditioned with sulfite produces 50.1 g/L ethanol from 141 g/L of sugars.