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

description: A dataset containing 24467 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Catharus aurantiirostris (Hartlaub, 1850)"
 ]
}

 The dataset includes 24467 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027249-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k8sdyd
title: Occurrence Download

description: A dataset containing 3260 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atelopus ignescens (Cornalia, 1849)"
 ]
}

 The dataset includes 3260 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027252-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jkddg5
title: Occurrence Download

description: A dataset containing 3260 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atelopus ignescens (Cornalia, 1849)"
 ]
}

 The dataset includes 3260 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027253-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jr6bv9
title: Occurrence Download

description: A dataset containing 3260 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atelopus ignescens (Cornalia, 1849)"
 ]
}

 The dataset includes 3260 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027254-241126133413365/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.27988730
title: data_multi-trait_multi-site.txt

description: For additional information see https://github.com/RESFOR/quantitative_genetics_R/tree/main
DOI: 10.6084/m9.figshare.27988730.v1
title: data_multi-trait_multi-site.txt

description: For additional information see https://github.com/RESFOR/quantitative_genetics_R/tree/main
DOI: 10.15468/dl.nrxcxt
title: Occurrence Download

description: A dataset containing 308 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Apis mellifera mellifera"
 ]
}

 The dataset includes 308 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027255-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.edvfuy
title: Occurrence Download

description: A dataset containing 3260 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atelopus ignescens (Cornalia, 1849)"
 ]
}

 The dataset includes 3260 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027256-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qrrj95
title: Occurrence Download

description: A dataset containing 3260 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atelopus ignescens (Cornalia, 1849)"
 ]
}

 The dataset includes 3260 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027257-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jvxgd3
title: Occurrence Download

description: A dataset containing 3260 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atelopus ignescens (Cornalia, 1849)"
 ]
}

 The dataset includes 3260 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027258-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/jhf57r7rnn.1
title: Capital Connectivity in Integrated Reports: Datasets from International Companies

description: The panel dataset provides information on the degree of capital connectivity disclosed in 840 integrated reports from 80 Asia-Australian, 78 European, and 10 American firms over a five-year period from 2018 to 2022. The sample includes firms from eleven different sectors, as defined by the Global Industry Classification Standards (GICS). The dataset focuses on international firms that voluntarily adopt integrated reporting, with these reports available in the official IR database. 

Data extraction is performed using a robotic software, which systematically codes the quantity and sequence of specific capitals in the reports. The software uses a list of keywords related to the six capitals outlined in the IR Framework: Financial, Manufactured, Intellectual, Human, Social & Relationship, and Natural. A self-calculated connectivity score is then generated to assess firms’ capital connectivity, by counting the average number of different types of capital coded within a specific context in each integrated report. This score ranges from a minimum of one (1) and a maximum of six (6), reflecting the average number of different types of capital codes. Additional scoring is calculated based on the percentage of capital disclosed directly, followed by another capital. The perfect score of 100% indicates that a different capital follows every other capital disclosure, while the lowest possible score of zero means none. Please refer to the excel file for detailed scoring measurement. 

Experts from industries and academicians have validated the instrument used to measure capital connectivity. To assess the reliability of the connectivity score, ten (10) integrated reports were randomly selected and manually coded, and the score was calculated based on the manual coding. Weighted Cohen’s Kappa inter-rater reliability test was used to compare Connectivity Score (CS) 1 and 2 using manual and automated coding. A coefficient of .99 (CS1) and .94 (CS2) indicates almost perfect agreement between manual and automated coding. In addition, a Pearson correlation is used to compare the manual and automated coding for Connectivity Score 3. A coefficient of .90 (CS3) shows that the manual score is statistically related with automated score at a .01 level of significance. This suggests that the scores calculated using robotic software is reliable.

The dataset is a valuable indicator of how committed IR adopters are to achieving connectivity, reflecting the integrative thinking involved in producing the integrated report.
DOI: 10.17632/jhf57r7rnn.2
title: Capital Connectivity in Integrated Reports: Datasets from International Companies

description: The panel dataset provides information on the degree of capital connectivity disclosed in 840 integrated reports from 80 Asia-Australian, 78 European, and 10 American firms over a five-year period from 2018 to 2022. The sample includes firms from eleven different sectors, as defined by the Global Industry Classification Standards (GICS). The dataset focuses on international firms that voluntarily adopt integrated reporting, with these reports available in the official IR database. 

Data extraction is performed using a robotic software, which systematically codes the quantity and sequence of specific capitals in the reports. The software uses a list of keywords related to the six capitals outlined in the IR Framework: Financial, Manufactured, Intellectual, Human, Social & Relationship, and Natural. A self-calculated connectivity score is then generated to assess firms’ capital connectivity, by counting the average number of different types of capital coded within a specific context in each integrated report. This score ranges from a minimum of one (1) and a maximum of six (6), reflecting the average number of different types of capital codes. Additional scoring is calculated based on the percentage of capital disclosed directly, followed by another capital. The perfect score of 100% indicates that a different capital follows every other capital disclosure, while the lowest possible score of zero means none. Please refer to the excel file for detailed scoring measurement. 

Experts from industries and academicians have validated the instrument used to measure capital connectivity. To assess the reliability of the connectivity score, ten (10) integrated reports were randomly selected and manually coded, and the score was calculated based on the manual coding. Weighted Cohen’s Kappa inter-rater reliability test was used to compare Connectivity Score (CS) 1 and 2 using manual and automated coding. A coefficient of .99 (CS1) and .94 (CS2) indicates almost perfect agreement between manual and automated coding. In addition, a Pearson correlation is used to compare the manual and automated coding for Connectivity Score 3. A coefficient of .90 (CS3) shows that the manual score is statistically related with automated score at a .01 level of significance. This suggests that the scores calculated using robotic software is reliable.

The dataset is a valuable indicator of how committed IR adopters are to achieving connectivity, reflecting the integrative thinking involved in producing the integrated report.
DOI: 10.15468/dl.dzs797
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mico acariensis (M.van Roosmalen, T.van Roosmalen, Mittermeier & Rylands, 2000)"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027259-241126133413365/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.27997124
title: plankton

description: plankton
DOI: 10.6084/m9.figshare.27997124.v1
title: plankton

description: plankton
DOI: 10.6084/m9.figshare.26122567.v6
title: bystander model and data

description: bystander model and data
DOI: 10.15468/dl.pprzz2
title: Occurrence Download

description: A dataset containing 3260 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atelopus ignescens (Cornalia, 1849)"
 ]
}

 The dataset includes 3260 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027260-241126133413365/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.27988733
title: data_EDA_analysis.txt

description: For additional information see: https://github.com/RESFOR/quantitative_genetics_R/tree/main
DOI: 10.6084/m9.figshare.27988733.v1
title: data_EDA_analysis.txt

description: For additional information see: https://github.com/RESFOR/quantitative_genetics_R/tree/main
DOI: 10.17632/k3dn7xcrcd
title: PAR-RGs and AMI JNZK-10204-10_re

description: This is the research data of all the bioinformatic analysis of Identification and validation of polyamine metabolism related genes as novel biomarkers for acute myocardial infarction and their correlation with immune infiltration
DOI: 10.17632/k3dn7xcrcd.1
title: PAR-RGs and AMI JNZK-10204-10_re

description: This is the research data of all the bioinformatic analysis of Identification and validation of polyamine metabolism related genes as novel biomarkers for acute myocardial infarction and their correlation with immune infiltration
DOI: 10.17632/bsr2pkhf9h
title: DSB clustering

description: To simulate the fusion of DSBs, we assume that they undergo restricted Brownian motion. In the absence of other influences, they are subject to binding forces arising from their own structure, which can be simplified using a restoring force F ⃗=-kr ⃗. With the Langevin equation and based on Euler’s scheme, the displacement at time t+∆t is modeled as:
r ⃗(t+∆t)=r ⃗(t)+(F ⃗∆t)/γ+σ√2D∆t
where σ is a standard normal variable, γ=6πr_0 η is the damping coefficient, and 〖D=k〗_B T/γ is the diffusion coefficient. r_0 is the radius of 53BP1 foci; η is the viscosity coefficient of water; k_B is the Boltzmann constant, and T is temperature.
Using this equation, the mean displacement at each time point can be simulated through the Monte Carlo method. This simulated displacement is then fitted against experimentally measured mean squared displacement (MSD) to determine the value of k. It is noted that, since the experimentally measured MSD is a two-dimensional quantity, the above equation must also be simulated in two dimensions. Due to the independence of motion in each dimension and assuming that k is equal in all three directions, simulating the motion in each dimension separately and then summing them does not affect the outcome. By computation, an appropriate value for k/γ was selected as 10 /s.
DOI: 10.17632/bsr2pkhf9h.1
title: DSB clustering

description: To simulate the fusion of DSBs, we assume that they undergo restricted Brownian motion. In the absence of other influences, they are subject to binding forces arising from their own structure, which can be simplified using a restoring force F ⃗=-kr ⃗. With the Langevin equation and based on Euler’s scheme, the displacement at time t+∆t is modeled as:
r ⃗(t+∆t)=r ⃗(t)+(F ⃗∆t)/γ+σ√2D∆t
where σ is a standard normal variable, γ=6πr_0 η is the damping coefficient, and 〖D=k〗_B T/γ is the diffusion coefficient. r_0 is the radius of 53BP1 foci; η is the viscosity coefficient of water; k_B is the Boltzmann constant, and T is temperature.
Using this equation, the mean displacement at each time point can be simulated through the Monte Carlo method. This simulated displacement is then fitted against experimentally measured mean squared displacement (MSD) to determine the value of k. It is noted that, since the experimentally measured MSD is a two-dimensional quantity, the above equation must also be simulated in two dimensions. Due to the independence of motion in each dimension and assuming that k is equal in all three directions, simulating the motion in each dimension separately and then summing them does not affect the outcome. By computation, an appropriate value for k/γ was selected as 10 /s.
DOI: 10.17632/7rx9mk8v4m.1
title: BanglaBlend: A Large-Scale Nobel Dataset of Bangla Sentences Categorized by Saint(Sadhu) and Common(Cholito) Form of Bengali Language

description: This BanglaBlend dataset is a comprehensive collection of Bangla (Bengali) sentences meticulously categorized based on two specific forms: Saint(Sadhu) and Common(Cholito). This dataset is comprised of a total 7350 annotated Bangla sentences. This dataset is designed to facilitate research and development in natural language processing (NLP) and computational linguistics, particularly for Bangla, a widely spoken language in Bangladesh and parts of India. Specially, this dataset can be leveraged for several natural language processing task such as text summarization, text classification, sentiment analysis, automatic language translation.
DOI: 10.17632/7rx9mk8v4m.2
title: BanglaBlend: A Large-Scale Nobel Dataset of Bangla Sentences Categorized by Saint(Sadhu) and Common(Cholito) Form of Bengali Language

description: This BanglaBlend dataset is a comprehensive collection of Bangla (Bengali) sentences meticulously categorized based on two specific forms: Saint(Sadhu) and Common(Cholito). This dataset is comprised of a total 7350 annotated Bangla sentences as well as it is preprocessed dataset where several data preprocessing techniques have been applied. This dataset is designed to facilitate research and development in natural language processing (NLP) and computational linguistics, particularly for Bangla, a widely spoken language in Bangladesh and parts of India. Specially, this dataset can be leveraged for several natural language processing task such as text summarization, text classification, sentiment analysis, automatic language translation.
DOI: 10.17632/7rx9mk8v4m.3
title: BanglaBlend: A Large-Scale Nobel Dataset of Bangla Sentences Categorized by Saint(Sadhu) and Common(Cholito) Form of Bengali Language

description: This BanglaBlend dataset is a comprehensive collection of Bangla (Bengali) sentences meticulously categorized based on two specific forms: Saint(Sadhu) and Common(Cholito). This dataset is comprised of a total 7350 annotated Bangla sentences as well as it is preprocessed dataset where several data preprocessing techniques have been applied. This dataset is designed to facilitate research and development in natural language processing (NLP) and computational linguistics, particularly for Bangla, a widely spoken language in Bangladesh and parts of India. Specially, this dataset can be leveraged for several natural language processing task such as text summarization, text classification, sentiment analysis, automatic language translation.
DOI: 10.15468/dl.x5bu6d
title: Occurrence Download

description: A dataset containing 348 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mico argentatus (Linnaeus, 1771)"
 ]
}

 The dataset includes 348 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027263-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5067/atlas/atl16.001
title: ATLAS/ICESat-2 L2A Global Geolocated Photon Data, Version 1
DOI: 10.5067/atlas/atl04.002
title: ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles, Version 1
DOI: 10.5067/bsep59adc6xn
title: SnowEx23 Laser Snow Microstructure Specific Surface Area Data, Version 1
DOI: 10.5067/zvm5xeky242a
title: GLAS/ICESat L1B Global Elevation Data, Version 33
DOI: 10.15468/dl.ny2jwp
title: Occurrence Download

description: A dataset containing 5814 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Catharus frantzii Cabanis, 1861"
 ]
}

 The dataset includes 5814 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027264-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5067/aquarius/aq2_sm.003
title: Aquarius L2 Swath Single Orbit Soil Moisture, Version 3
DOI: 10.5067/aquarius/aq3_ansm.002
title: Aquarius L3 Gridded 1-Degree Annual Soil Moisture, Version 2
DOI: 10.5067/aquarius/aq3_ansm.004
title: Aquarius L3 Gridded 1-Degree Annual Soil Moisture, Version 4
DOI: 10.5067/aquarius/aq3_ansm.003
title: Aquarius L3 Gridded 1-Degree Annual Soil Moisture, Version 3
DOI: 10.17632/gf67wvrhbs.1
title: Semi-supervised non-negative matrix factorization with structure preserving for image clustering

description: The code for paper '' Semi-supervised non-negative matrix factorization with structure preserving for image clustering''. This paper constructs a new label matrix with weights and further construct a label constraint regularizer to both utilize the label information and maintain the intrinsic structure of NMF. Based on the label constraint regularizer, the basis images of labeled data are extracted for monitoring and modifying the basis images learning of all data by establishing a basis regularizer. By incorporating the label constraint regularizer and the basis regularizer into NMF, a new semi-supervised NMF method is introduced. The proposed method is applied to image clustering and experimental results demonstrate the effectiveness of the proposed method in contrast with state-of-the-art unsupervised and semi-supervised algorithms.
DOI: 10.5067/aquarius/aq3_dysm.002
title: Aquarius L3 Gridded 1-Degree Daily Soil Moisture, Version 2
DOI: 10.5067/aquarius/aq3_dysm.004
title: Aquarius L3 Gridded 1-Degree Daily Soil Moisture, Version 4
DOI: 10.5067/aquarius/aq3_dysm.003
title: Aquarius L3 Gridded 1-Degree Daily Soil Moisture, Version 3
DOI: 10.5067/aquarius/aq3_mcsm.004
title: Aquarius L3 Gridded 1-Degree Monthly Soil Moisture Climatology, Version 4
DOI: 10.5067/aquarius/aq3_mosm.002
title: Aquarius L3 Gridded 1-Degree Monthly Soil Moisture, Version 2
DOI: 10.5067/aquarius/aq3_mosm.004
title: Aquarius L3 Gridded 1-Degree Monthly Soil Moisture, Version 4
DOI: 10.5067/aquarius/aq3_mosm.003
title: Aquarius L3 Gridded 1-Degree Monthly Soil Moisture, Version 3
DOI: 10.5067/aquarius/aq3_nrcs.005
title: Aquarius L3 Weekly Polar-Gridded Normalized Radar Cross Section, Version 5
DOI: 10.5067/aquarius/aq3_nrcs.004
title: Aquarius L3 Weekly Polar-Gridded Normalized Radar Cross Section, Version 4
DOI: 10.5067/aquarius/aq3_scsm.004
title: Aquarius L3 Gridded 1-Degree Seasonal Soil Moisture Climatology, Version 4
DOI: 10.5067/aquarius/aq3_snsm.002
title: Aquarius L3 Gridded 1-Degree Seasonal Soil Moisture, Version 2
DOI: 10.5067/99ox04yqqnub
title: SMEX04 San Miguel Watershed Soil Moisture Data: Sonora, Version 1
DOI: 10.5067/c8achjl21odj
title: SMEX04 Landsat TM/ETM+ NDVI and NDWI, Arizona, Version 1
DOI: 10.5067/s66uxqxzt5g4
title: SMEX04 Terra MODIS Data, Arizona, Version 1
DOI: 10.5067/58oxqcojaewe
title: SMEX04 Multispectral Radiometer Data: Arizona, Version 1
DOI: 10.5067/dcodsyu2n0cw
title: SMEX04 Leaf Area Index Data: Arizona, Version 1
DOI: 10.5067/etymzaa89nbn
title: SMEX04 Vegetation Water Content Data, Arizona, Version 1
DOI: 10.5067/asnjww6gme8y
title: SMEX04 Regional Soil Moisture Data: Sonora, Version 1
DOI: 10.5067/4ooamjxd6133
title: SMEX04 Surface Temperature Data: Arizona, Version 1
DOI: 10.5067/fsdsdfp595s0
title: SMEX04 Meteorological Network Data: Arizona, Version 1
DOI: 10.5067/zln0h6vo46xl
title: SMEX04 Precipitation Network Data: Arizona, Version 1
DOI: 10.5067/08x5yuizers9
title: SMEX04 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Data: Arizona, Version 1
DOI: 10.5067/34lstxksg9we
title: SMEX04 Aircraft Polarimetric Scanning Radiometer (PSR) Data, Arizona, Version 1
DOI: 10.5067/aquarius/aq3_snsm.004
title: Aquarius L3 Gridded 1-Degree Seasonal Soil Moisture, Version 4
DOI: 10.5067/aquarius/aq3_snsm.003
title: Aquarius L3 Gridded 1-Degree Seasonal Soil Moisture, Version 3
DOI: 10.5067/aquarius/aq3_sss.005
title: Aquarius L3 Weekly Polar-Gridded Sea Surface Salinity, Version 5
DOI: 10.5067/aquarius/aq3_sss.004
title: Aquarius L3 Weekly Polar-Gridded Sea Surface Salinity, Version 4
DOI: 10.5067/aquarius/aq3_tb.005
title: Aquarius L3 Weekly Polar-Gridded Brightness Temperature and Sea Surface Salinity, Version 5
DOI: 10.5067/aquarius/aq3_tb.004
title: Aquarius L3 Weekly Polar-Gridded Brightness Temperature and Sea Surface Salinity, Version 4
DOI: 10.5067/aquarius/aq3_wksm.002
title: Aquarius L3 Gridded 1-Degree Weekly Soil Moisture, Version 2
DOI: 10.5067/aquarius/aq3_wksm.004
title: Aquarius L3 Gridded 1-Degree Weekly Soil Moisture, Version 4
DOI: 10.5067/aquarius/aq3_wksm.003
title: Aquarius L3 Gridded 1-Degree Weekly Soil Moisture, Version 3
DOI: 10.5067/atlas/atl11.005
title: ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series, Version 5
DOI: 10.5067/qflmqi76moja
title: CLASIC07 Land Cover Classification Map, Version 1
DOI: 10.5067/75zb400qv98n
title: CLASIC07 PALS Backscatter Data, Version 1
DOI: 10.5067/58ilbivgp1rc
title: CLASIC07 PALS Brightness Temperature Data, Version 1
DOI: 10.5067/w2wmlruqoca8
title: CLASIC07 In Situ Soil Moisture Data, Version 1
DOI: 10.5067/yg89ec2ts7vt
title: CLASIC07 Soil Texture Data, Version 1