cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/w5gy4j7gt3
title: Evolution of graphite during low-energy ball milling.

description: To study the microstructural evolution of graphite and its allotropes under milling, graphite powder was processed using horizontal stainless-steel ball mills. A Ball-to-Powder Volume Ratio (BPVR) of 90 was maintained. Milling durations of 8, 16, 32, and 64 hours were investigated. 
This dataset comprises raw laser diffraction particle size analysis results. For the analysis, samples were dispersed in a 0.2% sodium hexametaphosphate solution (pH 10) and subjected to 5 minutes of ultrasonic bath treatment to ensure complete particle deagglomeration. The data reveal the dominant stages of graphite exfoliation and fracture, as well as the formation of micrometric aggregates after 64 hours.
 Additionally, X-ray diffraction (XRD) data are included. Measurements were performed using an Inel EQUINOX 2000 X-ray diffractometer configured with: A curved position-sensitive detector, CoKα₁ radiation (λ = 1.78901 Å), and a germanium monochromator. The acquired data were post-processed to convert results to CuKα₁ radiation (λ = 1.5406 Å) for consistency with standard references. 2θ peak positions were calibrated using a high-purity graphite standard (99.99%, Aldrich). Thanks to this analysis, it was possible to detect changes in the intensity of the main peak, shifts in the 2θ peaks, and their broadening. From these results, the variation in the lattice parameters "a" and "c" was calculated, which proved crucial for understanding the microstructural changes caused by lattice expansión.
DOI: 10.17632/w5gy4j7gt3.1
title: Evolution of graphite during low-energy ball milling.

description: To study the microstructural evolution of graphite and its allotropes under milling, graphite powder was processed using horizontal stainless-steel ball mills. A Ball-to-Powder Volume Ratio (BPVR) of 90 was maintained. Milling durations of 8, 16, 32, and 64 hours were investigated. 
This dataset comprises raw laser diffraction particle size analysis results. For the analysis, samples were dispersed in a 0.2% sodium hexametaphosphate solution (pH 10) and subjected to 5 minutes of ultrasonic bath treatment to ensure complete particle deagglomeration. The data reveal the dominant stages of graphite exfoliation and fracture, as well as the formation of micrometric aggregates after 64 hours.
 Additionally, X-ray diffraction (XRD) data are included. Measurements were performed using an Inel EQUINOX 2000 X-ray diffractometer configured with: A curved position-sensitive detector, CoKα₁ radiation (λ = 1.78901 Å), and a germanium monochromator. The acquired data were post-processed to convert results to CuKα₁ radiation (λ = 1.5406 Å) for consistency with standard references. 2θ peak positions were calibrated using a high-purity graphite standard (99.99%, Aldrich). Thanks to this analysis, it was possible to detect changes in the intensity of the main peak, shifts in the 2θ peaks, and their broadening. From these results, the variation in the lattice parameters "a" and "c" was calculated, which proved crucial for understanding the microstructural changes caused by lattice expansión.
DOI: 10.17632/tcp6hx99vf
title: Material_Empresas que quieren ser “tu hada madrina”: el trabajo como reality show en ‘El Jefe Infiltrado’

description: Manual de codificación y datos de investigación_Empresas que quieren ser “tu hada madrina”: el trabajo como reality show en ‘El Jefe Infiltrado’
DOI: 10.17632/tcp6hx99vf.1
title: Material_Empresas que quieren ser “tu hada madrina”: el trabajo como reality show en ‘El Jefe Infiltrado’

description: Manual de codificación y datos de investigación_Empresas que quieren ser “tu hada madrina”: el trabajo como reality show en ‘El Jefe Infiltrado’
DOI: 10.6084/m9.figshare.30555632
title: test

description: test
DOI: 10.6084/m9.figshare.30555632.v1
title: test

description: test
DOI: 10.17632/3c3xtxtfb6.1
title: CryptoVision: A Comprehensive Dataset for Crypto News and Trend Prediction

description: This dataset presents a large-scale collection of 188,430 cryptocurrency news records published between 2017 and 2025. The data were gathered from six reputable and verified sources — BlockWorks, CoinDesk, CoinTelegraph, CryptoPanic, CryptoNews, and Decrypt — using Python-based automated collection pipelines. Each record provides rich and structured metadata about a cryptocurrency-related news article, including the title, publication date and time, cryptocurrency type, and source URL. No copyrighted article text is included; only publicly accessible metadata are shared to ensure full copyright compliance.

To align market behavior with news events, each article is matched with Binance OHLCV candle data of a 15-minute timespan, allowing researchers to study short-term price reactions following news releases.

Each record in the dataset consists of the following columns:
URL, Title, Date_Time, Coin_Type, Sentiment_Label, Sentiment_Score, Open, High, Low, Close, Volume, Movement_OpenClose_%, Movement_HighLow_%, and Market_Move.

This dataset enables comprehensive sentiment analysis, market impact assessment, and event-driven modeling in cryptocurrency research, offering a unique link between news sentiment and real-time price fluctuations.
DOI: 10.17632/r53r882ygt
title: Manually categorized defect-related commits in Programming-Language Infrastructure-as-Code (PL-IaC) repositories

description: This dataset was produced as part of a replication study that explored whether a defect taxonomy originally developed for Infrastructure-as-Code (IaC) scripts would also apply to Programming-Language-based Infrastructure-as-Code (PL-IaC) projects. The research aimed to investigate which defect categories would appear in PL-IaC code written in general-purpose languages such as TypeScript, Python, and Go.

To conduct this investigation, we used the PIPr dataset, the first systematically curated dataset that gathers open-source repositories employing Pulumi, AWS CDK, or Terraform CDK. For our purpose, repositories were selected using four inclusion criteria: (i) at least 11% PL-IaC files, (ii) non-fork status, (iii) at least two commits per month, and (iv) at least ten contributors. From these repositories, we extracted commit histories and applied a set of defect-related keywords to identify potentially relevant commits. This keyword filtering step produced 5,465 candidate commits.

Each commit was then manually inspected in a structured three-phase process. First, we verified whether each commit was genuinely defect-related, which yielded 2,220 confirmed defect-related commits. The remaining 3,245 commits, despite matching defect-related keywords, were determined not to represent defect fixes or introductions and were labeled as No Defect. Second, both authors independently performed descriptive coding of defect-related commits to identify the nature and cause of each defect. Third, we reconciled our individual codings and found that the same eight defect categories identified in the original IaC study—Conditional, Configuration Data, Dependency, Documentation, Idempotency, Security, Service, and Syntax—also appeared in the PL-IaC context. These categories are not mutually exclusive, and some commits exhibit multiple defect types separated by semicolon.

The resulting dataset consists of two UTF-8 encoded CSV files:
* categorized-pl-iac-commits.csv — all 5,465 filtered commits, including their GitHub links, full commit text (metadata and diff), and one or more defect category labels.
* repositories.csv — metadata describing the 67 source repositories, including URLs, license information, timestamps, and repository characteristics.

The findings show that the defect taxonomy originally defined for IaC scripts is also valid for PL-IaC projects, indicating that both types of infrastructure code share similar defect patterns despite being implemented in different language paradigms. 

Researchers can use this dataset to replicate or extend taxonomy validation studies, train and evaluate machine learning models for defect detection, develop static analyzers and linters for PL-IaC, or conduct cross-language analyses of defect characteristics and automated repair techniques.
DOI: 10.25824/redu/5qqkim
title: Dados experimentais FSP: temperatura e tamanho de partícula

description: Os dados apresentados referem-se a experimentos conduzidos para caracterização de nanopartículas sintetizadas via Flame Spray Pyrolysis (FSP). As medições de temperatura foram obtidas em diferentes regiões da chama utilizando técnicas apropriadas para mapeamento térmico. As análises morfológicas e dimensionais das partículas foram realizadas por meio de Microscopia Eletrônica de Transmissão (TEM), enquanto a área superficial específica foi determinada por adsorção de gás (método BET), permitindo a estimativa complementar do diâmetro médio das partículas. Os dados visam apoiar estudos de modelagem e validação de simulações computacionais do processo FSP.
DOI: 10.17632/r53r882ygt.1
title: Manually categorized defect-related commits in Programming-Language Infrastructure-as-Code (PL-IaC) repositories

description: This dataset was produced as part of a replication study that explored whether a defect taxonomy originally developed for Infrastructure-as-Code (IaC) scripts would also apply to Programming-Language-based Infrastructure-as-Code (PL-IaC) projects. The research aimed to investigate which defect categories would appear in PL-IaC code written in general-purpose languages such as TypeScript, Python, and Go.

To conduct this investigation, we used the PIPr dataset, the first systematically curated dataset that gathers open-source repositories employing Pulumi, AWS CDK, or Terraform CDK. For our purpose, repositories were selected using four inclusion criteria: (i) at least 11% PL-IaC files, (ii) non-fork status, (iii) at least two commits per month, and (iv) at least ten contributors. From these repositories, we extracted commit histories and applied a set of defect-related keywords to identify potentially relevant commits. This keyword filtering step produced 5,465 candidate commits.

Each commit was then manually inspected in a structured three-phase process. First, we verified whether each commit was genuinely defect-related, which yielded 2,220 confirmed defect-related commits. The remaining 3,245 commits, despite matching defect-related keywords, were determined not to represent defect fixes or introductions and were labeled as No Defect. Second, both authors independently performed descriptive coding of defect-related commits to identify the nature and cause of each defect. Third, we reconciled our individual codings and found that the same eight defect categories identified in the original IaC study—Conditional, Configuration Data, Dependency, Documentation, Idempotency, Security, Service, and Syntax—also appeared in the PL-IaC context. These categories are not mutually exclusive, and some commits exhibit multiple defect types separated by semicolon.

The resulting dataset consists of two UTF-8 encoded CSV files:
* categorized-pl-iac-commits.csv — all 5,465 filtered commits, including their GitHub links, full commit text (metadata and diff), and one or more defect category labels.
* repositories.csv — metadata describing the 67 source repositories, including URLs, license information, timestamps, and repository characteristics.

The findings show that the defect taxonomy originally defined for IaC scripts is also valid for PL-IaC projects, indicating that both types of infrastructure code share similar defect patterns despite being implemented in different language paradigms. 

Researchers can use this dataset to replicate or extend taxonomy validation studies, train and evaluate machine learning models for defect detection, develop static analyzers and linters for PL-IaC, or conduct cross-language analyses of defect characteristics and automated repair techniques.
DOI: 10.17632/h4r382dp7f.1
title: Real-world evaluation and comparative outcomes of bimekizumab versus adalimumab and secukinumab in moderate-to-severe hidradenitis suppurativa: A nationwide inverse probability of treatment-weighted cohort study on behalf of the HS-SIDeMaST task force

description: Supplementary Material 1: Statistical methods
Supplementary Material 2: Data stratified according to bimekizumab dose regimen
Supplementary Material 3: Data stratified according to bimekizumab bio-naïve status
Supplementary Material 4 - Figure 1: A 67-year-old woman with long-standing hidradenitis suppurativa, refractory to adalimumab, was switched to bimekizumab. (A) (C) show the baseline clinical presentation prior to bimekizumab initiation, with numerous draining fistulous lesions and severe skin pain. (B) (D) demonstrate the marked clinical improvement achieved after 36 weeks of treatment, characterised by a substantial reduction in purulent discharge and an overall improvement in patient-reported quality of life scores.
Supplementary Material 5: Comparison of baseline demographics and disease severity by treatment Group
DOI: 10.6084/m9.figshare.29086082
title: tunnel-28.zip

description: <b>Tunnel-28 Core Dataset:</b> This dataset provides original tunnel images paired with precise pixel-level segmentation maps, generated using LABELMA. The annotations focus on three critical regions: the Furthest Area (FA), the navigable road surface, and the arched tunnel walls (Arched).<b>Tunnel-28 for Robustness Evaluation:</b> This extension contains augmented versions of the core dataset, created by applying a suite of transformations to assess model resilience. These transformations include:Weighted grayscaleGaussian noise (σ² = 0.01)Gaussian noise (σ² = 0.05)Warm-tone simulationFog simulation
DOI: 10.6084/m9.figshare.29086082.v1
title: tunnel-28.zip

description: it focuses on three key regions: the Furthest Area (FA), the navigable road surface, and the arched tunnel walls(Arched).
DOI: 10.6084/m9.figshare.29086082.v2
title: tunnel-28.zip

description: <b>Tunnel-28 Core Dataset:</b> This dataset provides original tunnel images paired with precise pixel-level segmentation maps, generated using LABELMA. The annotations focus on three critical regions: the Furthest Area (FA), the navigable road surface, and the arched tunnel walls (Arched).<b>Tunnel-28 for Robustness Evaluation:</b> This extension contains augmented versions of the core dataset, created by applying a suite of transformations to assess model resilience. These transformations include:Weighted grayscaleGaussian noise (σ² = 0.01)Gaussian noise (σ² = 0.05)Warm-tone simulationFog simulation
DOI: 10.17632/yt26559939
title: Source data for Figure 2, Figure 3 and Figure S1 of Foltman et al (2013)

description: Source data that were used to generate Figure panels 2B, 3A, 3B, 3D, S1E, S1F, S1G and S1H of Foltman et al 2013 (doi: 10.1016/j.celrep.2013.02.028).
DOI: 10.17632/yt26559939.1
title: Source data for Figure 2, Figure 3 and Figure S1 of Foltman et al (2013)

description: Source data that were used to generate Figure panels 2B, 3A, 3B, 3D, S1E, S1F, S1G and S1H of Foltman et al 2013 (doi: 10.1016/j.celrep.2013.02.028).
DOI: 10.17632/zty5nxj8fr.2
title: Supplementary materials for AGA

description: Supplementary materials for the manuscript titled "Reduced Prostate Cancer Risk in Patients with Androgenetic Alopecia Using 5-Alpha Reductase Inhibitors: A Real-World Cohort Study".
DOI: 10.17632/np9bhzfp56
title: Tephra-mediated manganese cycling shapes coral responses to coastal sedimentation_original data

description: This dataset includes the results of physiological measurements on individual Stylophora pistillata coral nubbins, encompassing photosynthetic parameters, (such as chlorophyll fluorescence-derived effective quantum yield of PSII, gross and net photosynthesis rates, and respiration rates) as well as skeletal growth rates. It also contains geochemical analyses of the tephra used in the coral culture experiments, namely XRF on the bulk tephra samples and EPMA on the volcanic glass. In addition, it contains statistical analyses referenced in the main manuscript.
DOI: 10.17632/np9bhzfp56.3
title: Tephra-mediated manganese cycling shapes coral responses to coastal sedimentation_original data

description: This dataset includes the results of physiological measurements on individual Stylophora pistillata coral nubbins, encompassing photosynthetic parameters, (such as chlorophyll fluorescence-derived effective quantum yield of PSII, gross and net photosynthesis rates, and respiration rates) as well as skeletal growth rates. It also contains geochemical analyses of the tephra used in the coral culture experiments, namely XRF on the bulk tephra samples and EPMA on the volcanic glass. In addition, it contains statistical analyses referenced in the main manuscript.
DOI: 10.17632/2xd87bc5k7
title: Data set: Mixed-methods art therapy study with hospitalized adult burn patients

description: Dataset for 4-session art therapy intervention among 12 adult hospitalized burn patients on psychosocial outcomes of distress (Distress thermometer), affect (Positive and Negative Affect Schedule, PANAS), change-perception (Patient Global Impression of Change, PGIC), pain (Graphic Numeric Rating Scale), and self-expression and regulation (Self-Expression and Emotion Regulation in Art Therapy Scale, SERATS).

Outcomes at T1, T2, T3, T4 (session 1, 2, 3, 4) pre and post
Distress
Pain
Positive Affect
Negative Affect

Outcomes at T4 (post session 4)
PGIC
SERATS

Demographics: 
Age
Gender
Ethnicity
Race
Education
Art experience
Burn type 
Total Body Surface Area burned (TBSA)
DOI: 10.17632/2xd87bc5k7.1
title: Data set: Mixed-methods art therapy study with hospitalized adult burn patients

description: Dataset for 4-session art therapy intervention among 12 adult hospitalized burn patients on psychosocial outcomes of distress (Distress thermometer), affect (Positive and Negative Affect Schedule, PANAS), change-perception (Patient Global Impression of Change, PGIC), pain (Graphic Numeric Rating Scale), and self-expression and regulation (Self-Expression and Emotion Regulation in Art Therapy Scale, SERATS).

Outcomes at T1, T2, T3, T4 (session 1, 2, 3, 4) pre and post
Distress
Pain
Positive Affect
Negative Affect

Outcomes at T4 (post session 4)
PGIC
SERATS

Demographics: 
Age
Gender
Ethnicity
Race
Education
Art experience
Burn type 
Total Body Surface Area burned (TBSA)
DOI: 10.17632/kyxh45xb56
title: Unified Autism Screening Dataset (Toddler–Adolescent–Adult): Cleaned, Encoded, and Ethnicity-Linked Version

description: This dataset merges toddler, adolescent, and adult autism screening data using the Q-CHAT questionnaire, fully cleaned and standardized for machine learning research.
DOI: 10.17632/kyxh45xb56.1
title: Unified Autism Screening Dataset (Toddler–Adolescent–Adult): Cleaned, Encoded, and Ethnicity-Linked Version

description: This dataset merges toddler, adolescent, and adult autism screening data using the Q-CHAT questionnaire, fully cleaned and standardized for machine learning research.
DOI: 10.15468/dl.u4729j
title: Occurrence Download

description: A dataset containing 371 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Allogamus mendax"
 ]
}

 The dataset includes 371 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019850-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17541697
title: DL-based_Tumor_Grade_of_Lung_Adenocarcinoma_Dataset

description: This dataset of our DL-based Tumor Grade of Lung Adenocarcinoma study
DOI: 10.15468/dl.t5fr8m
title: Occurrence Download

description: A dataset containing 10470 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "OccurrenceStatus is Present",
 "TaxonKey is Cycadopsida"
 ]
}

 The dataset includes 10470 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019851-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f9djzg
title: Occurrence Download

description: A dataset containing 1142 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acer cissifolium",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1142 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019852-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sbwqcu
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Primulina argentea"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019853-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17543222
title: Supporting Energy Systems Modelling in Vietnam: Techno-economic, Environmental, and Social Data for the Power and Transport Sectors

description: Vietnam’s commitment to achieving net-zero emissions by 2050 has intensified the need for comprehensive, data-driven models to guide long-term energy system planning. Historically, such planning has been primarily concerned with technoeconomic considerations; however, growing societal and international expectations now require that environmental and social dimensions be incorporated in decision-making. This dataset therefore compiles technoeconomic, environmental, and social data for Vietnam’s power and transport sectors from 2020 to 2050. This includes data on demand, capacity factors, technical potential, as well as operational life, residual capacity, efficiencies, costs (investments, fixed, and fuel), emission factors and pollution costs (CO2, CH4, NOX, SO2, PM10, and PM2.5), and employment factors (construction, manufacturing, operation and maintenance) for both power plant and transport mode types. All data were obtained and processed from available online sources. The dataset is structured to ensure compatibility with widely used energy modelling tools, including OSeMOSYS, TIMES, and MESSAGE, facilitating integrated and comparative analyses across multiple models. It provides detailed metadata, including the Statistical Data and Metadata eXchange (SDMX) observation statuses, and a traffic-light quality system to enhance transparency and usability. Although the dataset is tailored to Vietnam, most of the data is technology-based and thus transferable to other national contexts. Overall, this dataset contributes to improving the accessibility and transparency of energy data, enabling policymakers and researchers in Vietnam and other developing countries to conduct evidence-based analyses in support of just energy transitions.