cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.f9gxtn
title: Occurrence Download

description: A dataset containing 346 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Carex inops L.H.Bailey",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 346 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017800-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/bf94mddt98
title: LINF_280011300

description: Protein kinase | ULK4; Leishmania infantum (strain JPCM5)
DOI: 10.17632/bf94mddt98.2
title: LINF_280011300

description: Protein kinase | ULK4; Leishmania infantum (strain JPCM5)
DOI: 10.17632/c6y2zgs3f6
title: LINF_280011000

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/c6y2zgs3f6.1
title: LINF_280011000

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/3y3v5y4fyx
title: LINF_280010600

description: Modr-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/3y3v5y4fyx.1
title: LINF_280010600

description: Modr-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/ky9zt9x9f2
title: LINF_280010100

description: ZMYND10-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/ky9zt9x9f2.1
title: LINF_280010100

description: ZMYND10-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/22svbb4tv4
title: LINF_280010000

description: Tetratricopeptide repeat-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/22svbb4tv4.1
title: LINF_280010000

description: Tetratricopeptide repeat-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.15468/dl.m5mvdz
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chiasmia aestimaria",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 38 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053931-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/35y79xfwjn
title: LINF_280012100

description: BTB/POZ domain-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/35y79xfwjn.1
title: LINF_280012100

description: BTB/POZ domain-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/533j2mzd4s
title: A Comprehensive Dataset of Cotton Plant Diseases for National Disease Identification and Treatment Guidance

description: Cotton is one of the world’s most economically significant fiber crops, forming the backbone of the global textile industry and supporting over 250 million livelihoods worldwide. With India contributing approximately 23% of global cotton production, the sector faces annual yield losses of 20–30% due to foliar diseases caused by fungal, bacterial, and viral pathogens. To support disease management and decision-making, this dataset provides a systematically compiled and curated tabular resource on 12 major cotton leaf diseases: Wilt, Bacterial Blight, Herbicide Growth Damage, Leaf Hopper Jassids, Curl Virus, Aphids, Fall Armyworm, Powdery Mildew, Cotton Boll Rot, Leaf Redding, Leaf Variegation, and Target Spot, synthesized from over 70 authoritative agricultural sources, including government portals, crop protection manuals, peer-reviewed journals, and pesticide manufacturer databases. Each entry captures symptoms, favorable environmental conditions, physical and biological treatments, chemical controls with standardized dosages, and preventive practices.

This dataset can be used in multiple ways: farmers and agricultural extension workers can consult it as a practical field guide for identifying diseases and selecting appropriate management practices; agronomists and plant pathologists can analyze disease patterns, evaluate treatment effectiveness, and develop integrated crop protection strategies; and data scientists can leverage it to build predictive models, decision-support systems, and AI-powered disease detection tools. Its structured, source-driven format also allows users to compare recommendations across regions, explore the impact of environmental factors, and integrate the data into digital advisory platforms, making it a versatile resource for both practical field use and advanced research in sustainable cotton cultivation.
DOI: 10.7910/dvn/4b4z8j
title: Replication Data for: Enhancing sound absorption towards low frequency in graded anechoic coatings: from inclusion shape and orientation to triple-graded design

description: Data on the sound absorption coefficients of 169 cases with different angle configurations.
DOI: 10.17632/533j2mzd4s.1
title: A Comprehensive Dataset of Cotton Plant Diseases for National Disease Identification and Treatment Guidance

description: Cotton is one of the world’s most economically significant fiber crops, forming the backbone of the global textile industry and supporting over 250 million livelihoods worldwide. With India contributing approximately 23% of global cotton production, the sector faces annual yield losses of 20–30% due to foliar diseases caused by fungal, bacterial, and viral pathogens. To support disease management and decision-making, this dataset provides a systematically compiled and curated tabular resource on 12 major cotton leaf diseases: Wilt, Bacterial Blight, Herbicide Growth Damage, Leaf Hopper Jassids, Curl Virus, Aphids, Fall Armyworm, Powdery Mildew, Cotton Boll Rot, Leaf Redding, Leaf Variegation, and Target Spot, synthesized from over 70 authoritative agricultural sources, including government portals, crop protection manuals, peer-reviewed journals, and pesticide manufacturer databases. Each entry captures symptoms, favorable environmental conditions, physical and biological treatments, chemical controls with standardized dosages, and preventive practices.

This dataset can be used in multiple ways: farmers and agricultural extension workers can consult it as a practical field guide for identifying diseases and selecting appropriate management practices; agronomists and plant pathologists can analyze disease patterns, evaluate treatment effectiveness, and develop integrated crop protection strategies; and data scientists can leverage it to build predictive models, decision-support systems, and AI-powered disease detection tools. Its structured, source-driven format also allows users to compare recommendations across regions, explore the impact of environmental factors, and integrate the data into digital advisory platforms, making it a versatile resource for both practical field use and advanced research in sustainable cotton cultivation.
DOI: 10.17632/ztncd79yhk
title: A Comprehensive Dataset of Tomato Plant Diseases for National Predictive Analytics and Crop Health Management.

description: Tomato is one of the world's most valuable food crops, with the global market value projected to exceed US $166 billion in 2025 and annual production surpassing 180 million metric tons worldwide. This substantial economic impact is severely undermined by plant diseases, which can cause yield losses ranging from 30% to nearly 100% during severe epidemics of major pathogens like Late Blight making the development of reliable datasets crucial for effective disease management and enhancing decision-support systems. This dataset provides a systematically compiled and meticulously curated tabular resource on nine (9) economically important tomato diseases and pests: Early Blight, Late Blight, Leaf Miner, Leaf Mold, Mosaic Virus, Septoria, Spider Mites, Target Spot, and Yellow Leaf Curl Virus. The information was rigorously synthesized and validated from over 40 authoritative sources, including government agricultural portals, scientific articles, and peer-reviewed journals, and is organized in a columnar format. Each entry captures essential attributes for diagnosis and intervention, including visible symptoms (such as the distinct concentric rings of Early Blight or the white sporulation of Late Blight), favorable environmental conditions (like the warm, humid weather favoring Early Blight versus the cool, wet conditions favoring Late Blight), recommended physical and biological treatments, detailed pesticide and fungicide options with dosages standardized to the metric system, and crucial preventive measures like crop rotation and pruning. This openly available resource serves a critical dual utility, functioning as both an essential, field-ready reference guide for agricultural practitioners and a structured research resource for agronomists, data scientists, and plant pathologists developing novel crop protection strategies.
DOI: 10.17632/ztncd79yhk.1
title: A Comprehensive Dataset of Tomato Plant Diseases for National Predictive Analytics and Crop Health Management.

description: Tomato is one of the world's most valuable food crops, with the global market value projected to exceed US $166 billion in 2025 and annual production surpassing 180 million metric tons worldwide. This substantial economic impact is severely undermined by plant diseases, which can cause yield losses ranging from 30% to nearly 100% during severe epidemics of major pathogens like Late Blight making the development of reliable datasets crucial for effective disease management and enhancing decision-support systems. This dataset provides a systematically compiled and meticulously curated tabular resource on nine (9) economically important tomato diseases and pests: Early Blight, Late Blight, Leaf Miner, Leaf Mold, Mosaic Virus, Septoria, Spider Mites, Target Spot, and Yellow Leaf Curl Virus. The information was rigorously synthesized and validated from over 40 authoritative sources, including government agricultural portals, scientific articles, and peer-reviewed journals, and is organized in a columnar format. Each entry captures essential attributes for diagnosis and intervention, including visible symptoms (such as the distinct concentric rings of Early Blight or the white sporulation of Late Blight), favorable environmental conditions (like the warm, humid weather favoring Early Blight versus the cool, wet conditions favoring Late Blight), recommended physical and biological treatments, detailed pesticide and fungicide options with dosages standardized to the metric system, and crucial preventive measures like crop rotation and pruning. This openly available resource serves a critical dual utility, functioning as both an essential, field-ready reference guide for agricultural practitioners and a structured research resource for agronomists, data scientists, and plant pathologists developing novel crop protection strategies.
DOI: 10.25405/data.ncl.29400707
title: Biocomposite paper data: Mechanical Reinforcement of Paper Biocomposites Using Filamentous Cyanobacteria

description: This data backs up our study, which proposes and evaluates replacing cellulose fibres in paper-like biocomposites with the cyanobacterium <i>Leptolyngbya</i> sp. SB090721. The effect of using cyanobacteria as cellulose replacement (0%, 3%, 30% w/w) was evaluated. The study confirmed the feasibility of using unprocessed cyanobacterial biomass as a non-wood fibre source for paper and paperboard materials.
DOI: 10.25405/data.ncl.29400707.v1
title: Biocomposite paper data: Mechanical Reinforcement of Paper Biocomposites Using Filamentous Cyanobacteria

description: This data backs up our study, which proposes and evaluates replacing cellulose fibres in paper-like biocomposites with the cyanobacterium <i>Leptolyngbya</i> sp. SB090721. The effect of using cyanobacteria as cellulose replacement (0%, 3%, 30% w/w) was evaluated. The study confirmed the feasibility of using unprocessed cyanobacterial biomass as a non-wood fibre source for paper and paperboard materials.
DOI: 10.17632/k2f55crncj
title: Research Data - Wahyudi and Andrian (2025)

description: This study aims to examine the impact of good corporate governance, green culture, and green innovation on carbon emission disclosure. The study used a quantitative approach with secondary data obtained from annual reports and/or sustainability reports in energy sector companies listed on the main board of the Indonesia Stock Exchange during the period 2019–2023, analyzed by multiple linear panel regression using EViews 14. The results showed that green culture and green innovation had a significant positive effect on carbon emission disclosure, while good corporate governance had no effect. These findings confirm that green culture and innovation can increase the transparency of carbon emission disclosure as a form of commitment to sustainability while supporting SDG's 13 on climate change management. The implications of this research are the importance of strengthening green culture and green innovation within companies to increase the transparency of carbon emission disclosure as well as providing a basis for regulators in formulating environmental sustainability policies and encouraging companies to be more proactive in integrating sustainability strategies in business practices.
DOI: 10.17632/k2f55crncj.1
title: Research Data - Wahyudi and Andrian (2025)

description: This study aims to examine the impact of good corporate governance, green culture, and green innovation on carbon emission disclosure. The study used a quantitative approach with secondary data obtained from annual reports and/or sustainability reports in energy sector companies listed on the main board of the Indonesia Stock Exchange during the period 2019–2023, analyzed by multiple linear panel regression using EViews 14. The results showed that green culture and green innovation had a significant positive effect on carbon emission disclosure, while good corporate governance had no effect. These findings confirm that green culture and innovation can increase the transparency of carbon emission disclosure as a form of commitment to sustainability while supporting SDG's 13 on climate change management. The implications of this research are the importance of strengthening green culture and green innovation within companies to increase the transparency of carbon emission disclosure as well as providing a basis for regulators in formulating environmental sustainability policies and encouraging companies to be more proactive in integrating sustainability strategies in business practices.
DOI: 10.17632/cncbxjg2wz.1
title: Efficacy of ruxolitinib cream at different body sites in Chinese patients with nonsegmental vitiligo

description: Background: Despite emerging evidence supporting topical JAK inhibitors for vitiligo, population-specific efficacy and patterns remain underexplored. 
Objective: To evaluate the anatomic variation in treatment response to 1.5% ruxolitinib cream among Chinese patients with nonsegmental vitiligo (NSV).
Methods: In this 24-week observational study, 461 NSV patients applied ruxolitinib cream twice daily. The primary endpoint was achieving VASI50 (Vitiligo Area Scoring Index 50) across seven anatomic regions. Secondary outcomes included safety profiles and analyses of clinical subgroups, such as disease duration.
Results: Facial lesions showed a superior response, with 64.1% of patients achieving VASI50, followed by head/neck (44.5%). Distal extremities exhibited limited efficacy (hands: 15.4%; feet: 7.9%). Adverse events occurred in 11.9% of patients, predominantly mild application-site reactions. Disease duration may influence treatment efficacy; however, no differences were found in the other clinical subgroups.
Limitations：The study is retrospective and employs a 1-arm observational design without a control group, population exclusively consists of individuals from the Asian Han group and lack of relevant long-term follow-up data.
Conclusion: This real-world evidence confirms significant anatomic heterogeneity in ruxolitinib response, advocating for combination therapies in acral lesions and personalized treatment strategies and to start ruxolitinib cream treatment as early as possible.
Keywords: efficacy, Janus kinase inhibitor,ruxolitinib, safety, vitiligo
DOI: 10.17632/3kp7cxr43h
title: Indonesian Garment SMEs Business Model Data

description: This data quantitatively describes the activities and scale of Indonesian SME garment businesses. The data covered include sales, revenue, resources, and consumer consumption habits. This data was obtained from an online survey of 30 garment SMEs and 30 garment consumers in Indonesia.
DOI: 10.26023/bev0-a5kz-qa12
title: DC3: NASA DC-8 NOAA ESRL CSD Aerosol Photo-Acoustic Absorption Spectrometer (PAS) Data. Version 1.0

description: This data set contains NASA DC-8 NOAA ESRL CSD Aerosol Photo-Acoustic Absorption Spectrometer (PAS) Data collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 29 May 2012 through 22 June 2012. This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments.
DOI: 10.17632/3kp7cxr43h.2
title: Indonesian Garment SMEs Business Model Data

description: This data quantitatively describes the activities and scale of Indonesian SME garment businesses. The data covered include sales, revenue, resources, and consumer consumption habits. This data was obtained from an online survey of 30 garment SMEs and 30 garment consumers in Indonesia.
DOI: 10.17632/643wd79h3j.2
title: Proteomics in Patients with Allogeneic Stem Cell Transplant Treated with Topical Cyclosporine

description: Graft-Versus-Host Disease(GVHD) is a serious complication after transplantation, and ocular involvement is common. Ikervis is increasingly being used in the treatment of ocular symptoms in GVHD patients. Detecting cytokines in the tears of patients after using these eye drops helps to gain a deeper understanding of the drug's mechanism, evaluate treatment efficacy, and provide a basis for optimizing clinical treatment plans. This data collection aims to explore the situation of GVHD patients after using Ikervis.
Data Description included:
(1) Patient Basic Information: Includes patient number, ID, age, gender, etc. 
(2) Disease - related Information: disease diagnosis, disease stage, previous treatment history, etc. 
(3) Eye Drop Information: dosage and frequency.
(4) Ocular Examination Indicators: intraocular pressure, conjunctival hyperemia, tear osmolarity. 
(5) Cytokine Detection: Levels of various cytokines.
We find that a total of 2570 proteins were identified and quantified in this study. Significant differences in the expression of AGT, HRG, and SERPIND1 were observed between R and NR groups prior to HSCT (all P&lt;0.05). COL6A1, RAB11B, and XRCC6, PFKFB4, COL6A1, GNG12, APOA2, and GATAD1 were significantly differentially expressed between the two groups post-HSCT (all P&lt;0.05). These identified proteins were clustered into 6 modules by wWeighted gene co-expression network analysis (WGCNA), which are associated with immune response, lysosome, proteasome, neutrophil extracellular trap formation, and glycan biosynthesis and metabolism. These modules demonstrated a significant correlation with ocular clinical manifestations, including Schirmer test values, tear osmolarity, and conjunctival redness.
Through the analysis of the data on the detection of cytokines in the tears of GVHD patients after using Ikervis eye drops, we have proposed relevant research hypotheses and found some notable phenomena from the data. These findings help us better understand the therapeutic effects of eye drops, the impact of patient characteristics on treatment, and the association between cytokines and ocular symptoms. By reasonably interpreting and using these data, valuable references can be provided for clinical treatment and drug use, ultimately improving the ocular health of GVHD patients. However, it should be noted that this study still has certain limitations, such as a relatively small sample size. In the future, more in - depth research needs to be carried out to improve the relevant conclusions.
DOI: 10.15468/dl.6t345j
title: Occurrence Download

description: A dataset containing 65 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Berberis hieronymi"
 ]
}

 The dataset includes 65 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053934-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2v5ct7v7zj
title: Real time defect detection in FFF process

description: This contains the supplementary information for the manuscript titled "Real-time Defect Detection in Fused Filament Fabrication Using Computer Vision and Deep Learning"
DOI: 10.5281/zenodo.15722903
title: The AutoCorrelation Integral Drill (ACID) Test Set

description: This repository contains the scripts and StepUp workflows to regenerate the "AutoCorrelation Integral Drill" (ACID) test set. The ACID test set comprises a diverse collection of algorithmically generated time series designed to evaluate the performance of algorithms that compute the autocorrelation integral. The set contains in total 15360 test cases, and each case consists of one or more time series. The cases differ in the kernel characterizing the time correlations, the number of time series, and the length of the time series. For each combination of kernel, number of sequences and sequence length, 64 test cases are generated with different random seeds to allow for a systematic validation of uncertainty estimates. The total dataset, once generated, is about 80 GB in size.

In addition to the ACID test set, this repository also contains scripts and workflows to validate STACIE, a software package for the computation of the autocorrelation integral. The results of this analysis are discussed in the following paper:



Gözdenur, T.; Fauconnier, D.; Verstraelen, T. "STable AutoCorrelation Integral Estimator (STACIE): Robust and accurate transport properties from molecular dynamics simulations" Journal of Chemical Information and Modeling Article ASAP, 2025, doi:10.1021/acs.jcim.5c01475, arXiv:2506.20438.
DOI: 10.17632/2v5ct7v7zj.1
title: Real time defect detection in FFF process

description: This contains the supplementary information for the manuscript titled "Real-time Defect Detection in Fused Filament Fabrication Using Computer Vision and Deep Learning"
DOI: 10.17632/r7brkb4xft
title: Social Credit System Construction and Supply Chain Decision-making: Disclosure and Real Effect

description: This is the data processing file of the article "Social Credit System Construction and Supply Chain Decision-making: Disclosure and Real Effect". Including data files, code files and organized result files. These documents can be fully reproduced.
DOI: 10.17632/r7brkb4xft.2
title: Social Credit System Construction and Supply Chain Decision-making: Disclosure and Real Effect

description: This is the data processing file of the article "Social Credit System Construction and Supply Chain Decision-making: Disclosure and Real Effect". Including data files, code files and organized result files. These documents can be fully reproduced.
DOI: 10.17632/9jfctr5f4f
title: Berlin Consumption and Production Data

description: Consumption and Production profiles for each test case
DOI: 10.17632/9jfctr5f4f.1
title: Berlin Consumption and Production Data

description: Consumption and Production profiles for each test case