cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/74xrbd4vxy
title: Dataset Costumer Review Indonesia

description: This dataset contains 203,786 Indonesian-language customer reviews collected from a publicly accessible e-commerce platform, covering 4,422 unique product items. The corpus reflects authentic, short-form, and informal user-generated content typical of digital marketplace interactions.

The dataset is released in two structured versions:
1. Raw dataset, preserving the original review text and associated metadata, including product identifier, rating (1–5), purchase date, and client platform (Android app, desktop, mobile app).
2. Processed dataset, containing cleaned review text along with additional derived features, including sentiment label (positive, neutral, negative) and sentiment confidence score generated using a pretrained IndoBERT-based sentiment classification model.

The processed version applies minimal text cleaning while preserving linguistic authenticity. No synthetic data were introduced. The sentiment annotations are provided to facilitate benchmarking and downstream NLP research rather than to present a new modeling contribution.

Descriptive analyses indicate that the corpus exhibits brevity-driven structure, lexical variation, and measurable vocabulary coverage gaps relative to IndoBERT vocabulary, reflecting realistic informal Indonesian digital communication patterns. The dataset is suitable for sentiment analysis, short-text classification, opinion mining, and robustness evaluation in low-resource language settings.

The dataset is released to promote reproducible research and to expand publicly available resources for Indonesian natural language processing.
DOI: 10.13018/bmr51649
title: Ded1p RecA2 domain
DOI: 10.17632/74xrbd4vxy.1
title: Dataset Costumer Review Indonesia

description: This dataset contains 203,786 Indonesian-language customer reviews collected from a publicly accessible e-commerce platform, covering 4,422 unique product items. The corpus reflects authentic, short-form, and informal user-generated content typical of digital marketplace interactions.

The dataset is released in two structured versions:
1. Raw dataset, preserving the original review text and associated metadata, including product identifier, rating (1–5), purchase date, and client platform (Android app, desktop, mobile app).
2. Processed dataset, containing cleaned review text along with additional derived features, including sentiment label (positive, neutral, negative) and sentiment confidence score generated using a pretrained IndoBERT-based sentiment classification model.

The processed version applies minimal text cleaning while preserving linguistic authenticity. No synthetic data were introduced. The sentiment annotations are provided to facilitate benchmarking and downstream NLP research rather than to present a new modeling contribution.

Descriptive analyses indicate that the corpus exhibits brevity-driven structure, lexical variation, and measurable vocabulary coverage gaps relative to IndoBERT vocabulary, reflecting realistic informal Indonesian digital communication patterns. The dataset is suitable for sentiment analysis, short-text classification, opinion mining, and robustness evaluation in low-resource language settings.

The dataset is released to promote reproducible research and to expand publicly available resources for Indonesian natural language processing.
DOI: 10.13018/bmr51650
title: Ded1p N-terminal IDR
DOI: 10.13018/bmr51651
title: Rev7/Rev3-RBM1
DOI: 10.17632/7d6wrcz9vj
title: Electrolyzers patents analysis using TIP

description: The patent dataset analyzed is based on search criteria dealing with electrolyzer technology for hydrogen production, namely focusing on electrolytic water splitting systems, while incorporating comprehensive materials analysis to assess critical element dependencies. The dataset is defined through a dual-strategy approach combining keyword-based detection with IPC classification filtering from the EPO database PATSTAT (Spring 2025 ed.), targeting patent documents containing hydrogen production patterns alongside specific IPC codes including C25B 1/02 (electrolysis of water), C25B 1/04 (electrolysis of inorganic compounds), and C25B 1/042 (electrolysis of alkaline compounds). The first step involves comprehensive dataset creation from multiple sources, generating 18,811 unique patent families spanning 2000-2023, with enhanced bibliographic data extraction achieving 99.99% success rate across titles, abstracts, and claims.

The analysis focuses on applications filed worldwide across 69+ patent authorities (including national and supranational jurisdictions such as EPO, WIPO, USPTO, and CNIPA) to evaluate meaningful trends in electrolyzer innovation from early-stage development through recent commercialization acceleration. Patent filing patterns reveal distinct innovation waves, with particular acceleration during 2010-2014 and 2020-2023 periods, indicating technology maturation phases. A subsequent critical enhancement involves patent family dimension analysis, examining geographical diversity and family sizes across publication authorities using hierarchical priority selection (EP → WO → US → CN → Others), revealing strategic differentiation between comprehensive international protection (EP: avg 5.84 authorities per family) and domestic market focus (CN: avg 1.01 authorities per family).

The assessment encompasses triadic family analysis identifying 327 elite patents with simultaneous US-granted, EP, and JP presence, representing highest commercial value innovations. Subsequently, comprehensive materials analysis addresses strategic element dependencies, examining rare earth elements (REE), platinum group metals (PGM), base metals, and critical raw materials to assess supply chain risks and manufacturing scalability. Forward citation analysis of 69,134 citation relationships maps knowledge transfer patterns and technological influence networks. The methodology culminates in applicant ranking analysis across 12,711 unique entities, revealing competitive landscape dynamics with Chinese Academy of Sciences leading innovation output (308 families) while maintaining distributed innovation patterns (top 10 applicants control only 7.6% of families).

All analytic steps described above were performed by means of "Technology Intelligence Platform" (TIP) the tool recently made available by the European Patent Office (https://www.epo.org/en/searching-for-patents/data/technology-intelligence-platform).
DOI: 10.5281/zenodo.18788218
title: Thermographic data for manuscript Mus.4189-E-13,5 (SLUB)

description: This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
DOI: 10.13018/bmr51652
title: Rev7/Rev3-RBM2
DOI: 10.17632/7d6wrcz9vj.1
title: Electrolyzers patents analysis using TIP

description: The patent dataset analyzed is based on search criteria dealing with electrolyzer technology for hydrogen production, namely focusing on electrolytic water splitting systems, while incorporating comprehensive materials analysis to assess critical element dependencies. The dataset is defined through a dual-strategy approach combining keyword-based detection with IPC classification filtering from the EPO database PATSTAT (Spring 2025 ed.), targeting patent documents containing hydrogen production patterns alongside specific IPC codes including C25B 1/02 (electrolysis of water), C25B 1/04 (electrolysis of inorganic compounds), and C25B 1/042 (electrolysis of alkaline compounds). The first step involves comprehensive dataset creation from multiple sources, generating 18,811 unique patent families spanning 2000-2023, with enhanced bibliographic data extraction achieving 99.99% success rate across titles, abstracts, and claims.

The analysis focuses on applications filed worldwide across 69+ patent authorities (including national and supranational jurisdictions such as EPO, WIPO, USPTO, and CNIPA) to evaluate meaningful trends in electrolyzer innovation from early-stage development through recent commercialization acceleration. Patent filing patterns reveal distinct innovation waves, with particular acceleration during 2010-2014 and 2020-2023 periods, indicating technology maturation phases. A subsequent critical enhancement involves patent family dimension analysis, examining geographical diversity and family sizes across publication authorities using hierarchical priority selection (EP → WO → US → CN → Others), revealing strategic differentiation between comprehensive international protection (EP: avg 5.84 authorities per family) and domestic market focus (CN: avg 1.01 authorities per family).

The assessment encompasses triadic family analysis identifying 327 elite patents with simultaneous US-granted, EP, and JP presence, representing highest commercial value innovations. Subsequently, comprehensive materials analysis addresses strategic element dependencies, examining rare earth elements (REE), platinum group metals (PGM), base metals, and critical raw materials to assess supply chain risks and manufacturing scalability. Forward citation analysis of 69,134 citation relationships maps knowledge transfer patterns and technological influence networks. The methodology culminates in applicant ranking analysis across 12,711 unique entities, revealing competitive landscape dynamics with Chinese Academy of Sciences leading innovation output (308 families) while maintaining distributed innovation patterns (top 10 applicants control only 7.6% of families).

All analytic steps described above were performed by means of "Technology Intelligence Platform" (TIP) the tool recently made available by the European Patent Office (https://www.epo.org/en/searching-for-patents/data/technology-intelligence-platform).
DOI: 10.13018/bmr51653
title: the carboxyl terminus of A Family A G protein coupled receptor
DOI: 10.13018/bmr51654
title: Backbone N and HN Chemical Shift Assignments for RBPMS-A (1-122)
DOI: 10.5281/zenodo.18788217
title: Thermographic data for manuscript Mus.4189-E-13,5 (SLUB)

description: This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.
DOI: 10.13018/bmr51655
title: UBE3A isoform 2 AZUL
DOI: 10.13018/bmr51656
title: The 1H, 15N chemical shifts of carboxyl terminus of A Family A G protein coupled receptor with Gs
DOI: 10.13018/bmr51657
title: Human BLVRB with Bilirubin and NADP
DOI: 10.17632/w48msjz2v5
title: Survery Data on Urban Roaming and Place Attachment in Community Tourism

description: This dataset consists of questionnaire survey data related to urban roaming and community urban tourism, used for structural equation modeling (SEM) analysis to examine the relationships among place attachment, physical environment, in-person experience sharing, electronic word-of-mouth, and travel intention.
It contains three files:
Raw questionnaire data in SPSS format.
Data standardized for model analysis.
AMOS model file (.amw) used for path analysis and hypothesis testing.
Data were collected through formal questionnaires. Variables include place attachment (place identity, place dependence), physical environment, in-person experience sharing, electronic word-of-mouth, and travel intention. Data standardization was performed to facilitate normality tests and model fitting.
The data can be directly imported into SPSS and AMOS for result replication, statistical analysis, or related tourism behavior studies.
DOI: 10.13018/bmr51658
title: Identifying the structural and dynamic changes of BLVRB through the catalytic cycle
DOI: 10.17632/w48msjz2v5.2
title: Survery Data on Urban Roaming and Place Attachment in Community Tourism

description: This dataset consists of questionnaire survey data related to urban roaming and community urban tourism, used for structural equation modeling (SEM) analysis to examine the relationships among place attachment, physical environment, in-person experience sharing, electronic word-of-mouth, and travel intention.
It contains three files:
Raw questionnaire data in SPSS format.
Data standardized for model analysis.
AMOS model file (.amw) used for path analysis and hypothesis testing.
Data were collected through formal questionnaires. Variables include place attachment (place identity, place dependence), physical environment, in-person experience sharing, electronic word-of-mouth, and travel intention. Data standardization was performed to facilitate normality tests and model fitting.
The data can be directly imported into SPSS and AMOS for result replication, statistical analysis, or related tourism behavior studies.
DOI: 10.13018/bmr51659
title: Backbone Chemical Shift Assignments of human glutathione peroxidase 4 (GPx4)
DOI: 10.13018/bmr51661
title: 1H, 13C, and 15N resonance assignments of SarA monomer from Staphylococcus aureus in complex with DNA
DOI: 10.17632/73cb4rht58
title: Rising Temperature and International Trade Dynamics

description: This repository contains the replication package for the paper “Rising Temperature and International Trade Dynamics”. It provides analysis-ready Stata datasets and do-files that reproduce the main empirical results, robustness checks, channel tests, heterogeneity analyses, and extended analyses reported in the paper (Tables 1–15 and Figures 1–3).

Contents

Datasets (Stata .dta):

Panel A main.dta – core city-by-month panel with trade growth outcomes and local climate variables. Key variables include export/import growth (dlnex, dlnim), price and output changes (dlncpi, dlnind), and climate measures (tem, pre, sun, hum) with constructed lags (ltem, l2tem, etc.).

Panel B heterogeneity.dta – extended outcomes and subsamples for heterogeneity tests, including domestic vs. foreign trade indicators (dlnex1–dlnex5, dlnex2, dlnim2) and product-level outcomes used to build Figure 3.

Panel C extended.dta – variables for export structure and diversification analyses, including pm, nep, lc, pdiv, sdiv and external temperature shock measures (extem and lags).

Code (Stata do-files):
01_baseline_regression.do, 02_robustness_checks.do, 03_channel_analysis.do, 04_heterogeneity_analysis.do, 05_extended_analysis.do.

Replication guide: README.pdf (software requirements, variable notes, and execution steps).

Software requirements
Stata ≥15 (tested on Stata 16/17). Required packages: reghdfe and estout (install via ssc install reghdfe and ssc install estout).

How to run
Set the working directory to the folder containing the data and do-files, then run do-files in order:

01_baseline_regression.do

02_robustness_checks.do

03_channel_analysis.do

04_heterogeneity_analysis.do

05_extended_analysis.do

These files generate the regression outputs used in the manuscript. Figures 1–2 are plotted from reported bin estimates; Figure 3 is constructed from cumulative effect estimates across products (see README for details).
DOI: 10.13018/bmr51662
title: 1H, 13C and 15N NMR chemical shift assignments of LytM N-terminal domain (residues 26-184)
DOI: 10.5281/zenodo.18788082
title: labeobarbus_progenys_decontaminated_FSCR.fasta.gz
DOI: 10.17632/73cb4rht58.1
title: Rising Temperature and International Trade Dynamics

description: This repository contains the replication package for the paper “Rising Temperature and International Trade Dynamics”. It provides analysis-ready Stata datasets and do-files that reproduce the main empirical results, robustness checks, channel tests, heterogeneity analyses, and extended analyses reported in the paper (Tables 1–15 and Figures 1–3).

Contents

Datasets (Stata .dta):

Panel A main.dta – core city-by-month panel with trade growth outcomes and local climate variables. Key variables include export/import growth (dlnex, dlnim), price and output changes (dlncpi, dlnind), and climate measures (tem, pre, sun, hum) with constructed lags (ltem, l2tem, etc.).

Panel B heterogeneity.dta – extended outcomes and subsamples for heterogeneity tests, including domestic vs. foreign trade indicators (dlnex1–dlnex5, dlnex2, dlnim2) and product-level outcomes used to build Figure 3.

Panel C extended.dta – variables for export structure and diversification analyses, including pm, nep, lc, pdiv, sdiv and external temperature shock measures (extem and lags).

Code (Stata do-files):
01_baseline_regression.do, 02_robustness_checks.do, 03_channel_analysis.do, 04_heterogeneity_analysis.do, 05_extended_analysis.do.

Replication guide: README.pdf (software requirements, variable notes, and execution steps).

Software requirements
Stata ≥15 (tested on Stata 16/17). Required packages: reghdfe and estout (install via ssc install reghdfe and ssc install estout).

How to run
Set the working directory to the folder containing the data and do-files, then run do-files in order:

01_baseline_regression.do

02_robustness_checks.do

03_channel_analysis.do

04_heterogeneity_analysis.do

05_extended_analysis.do

These files generate the regression outputs used in the manuscript. Figures 1–2 are plotted from reported bin estimates; Figure 3 is constructed from cumulative effect estimates across products (see README for details).
DOI: 10.13018/bmr51663
title: Backbone resonance assignments for a 21-residue peptide corresponding to the SARS-CoV-2 spike C-terminal tail
DOI: 10.5281/zenodo.18788081
title: labeobarbus_progenys_decontaminated_FSCR.fasta.gz
DOI: 10.13018/bmr51672
title: GRASP peptide
DOI: 10.13018/bmr51673
title: 1H, 13C, and 15N Chemical Shift Assignments for amyloidogenic SEM1(45-67) peptide
DOI: 10.13018/bmr51674
title: DinB-PAD
DOI: 10.13018/bmr51675
title: DinB-Thumb
DOI: 10.17632/zsrzxdddmg
title: Quantifying and Interpreting Non-Technical Losses in Smart Grids: An RFE-Optimized XGBoost Regression Methodology with Uncertainty Analysis

description: The following data is a processed version of the Low Carbon London dataset, prepared for this research.
DOI: 10.13018/bmr51676
title: DinBdeltaPAD
DOI: 10.17632/zsrzxdddmg.1
title: Quantifying and Interpreting Non-Technical Losses in Smart Grids: An RFE-Optimized XGBoost Regression Methodology with Uncertainty Analysis

description: The following data is a processed version of the Low Carbon London dataset, prepared for this research.
DOI: 10.15468/dl.3kenk8
title: Occurrence Download

description: A dataset containing 2116 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aloysia wrightii"
 ]
}

 The dataset includes 2116 records from 99 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003655-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p2n63k
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Scytalopus gonzagai)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 62 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003654-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13018/bmr51677
title: DinB
DOI: 10.13018/bmr51678
title: 13C and 15N Resonance Assignments of Alpha Synuclein Fibrils Amplified from Dementia with Lewy Bodies Tissue
DOI: 10.13018/bmr51681
title: Assignment for optoallosteric GTPase, Cdc42Lov
DOI: 10.13018/bmr51682
title: Chemical_shift_FAM122A_29-120
DOI: 10.6084/m9.figshare.31424078
title: Covariate-Adjusted Response-Adaptive Design with Delayed Outcomes

description: Covariate-adjusted response-adaptive (CARA) designs have gained widespread adoption for their clear benefits in enhancing experimental efficiency and participant welfare. These designs dynamically adjust treatment allocations during interim analyses based on participant responses and covariates collected during the experiment. However, delayed responses can significantly compromise the effectiveness of CARA designs, as they hinder timely adjustments to treatment assignments when certain participant outcomes are not immediately observed. In this paper, we propose a fully forward-looking CARA design that dynamically updates treatment assignments throughout the experiment as response delay mechanisms are progressively estimated. Our design strategy is informed by novel semiparametric efficiency calculations that explicitly account for outcome delays in a multi-stage setting. Through both theoretical investigations and simulation studies, we demonstrate that our proposed design offers a robust solution for handling delayed outcomes in CARA designs, yielding significant improvements in both statistical power and participant welfare.
DOI: 10.6084/m9.figshare.31424078.v1
title: Covariate-Adjusted Response-Adaptive Design with Delayed Outcomes

description: Covariate-adjusted response-adaptive (CARA) designs have gained widespread adoption for their clear benefits in enhancing experimental efficiency and participant welfare. These designs dynamically adjust treatment allocations during interim analyses based on participant responses and covariates collected during the experiment. However, delayed responses can significantly compromise the effectiveness of CARA designs, as they hinder timely adjustments to treatment assignments when certain participant outcomes are not immediately observed. In this paper, we propose a fully forward-looking CARA design that dynamically updates treatment assignments throughout the experiment as response delay mechanisms are progressively estimated. Our design strategy is informed by novel semiparametric efficiency calculations that explicitly account for outcome delays in a multi-stage setting. Through both theoretical investigations and simulation studies, we demonstrate that our proposed design offers a robust solution for handling delayed outcomes in CARA designs, yielding significant improvements in both statistical power and participant welfare.
DOI: 10.17632/zxk6vgjtms
title: Unified Apple Detection Benchmark Dataset for YOLO-Series Model Comparison

description: This dataset is released to support reproducible benchmarking of YOLO-series object detection models for apple detection under a unified evaluation setting. The dataset contains 52,710 annotated apples and was used to evaluate representative YOLO models on the same data for fair performance comparison.
DOI: 10.13018/bmr51683
title: UGT2B17-C terminus
DOI: 10.17632/zxk6vgjtms.1
title: Unified Apple Detection Benchmark Dataset for YOLO-Series Model Comparison

description: This dataset is released to support reproducible benchmarking of YOLO-series object detection models for apple detection under a unified evaluation setting. The dataset contains 52,710 annotated apples and was used to evaluate representative YOLO models on the same data for fair performance comparison.
DOI: 10.13018/bmr51684
title: Backbone 1H, 13C and 15N Chemical Shift Assignments and Relaxation Parameters for USP14-Ubl domain
DOI: 10.13018/bmr51685
title: Backbone 1H, 13C and 15N Chemical Shift Assignments and Relaxation Parameters for Ubl domain and Linker in Full-length USP14
DOI: 10.13018/bmr51687
title: Backbone and CB chemical shifts of HPy1 repetitive unit from Argiope argentata
DOI: 10.15468/dl.3pbvyv
title: Occurrence Download

description: A dataset containing 10731 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cedrela odorata"
 ]
}

 The dataset includes 10731 records from 202 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003656-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15692741
title: Importance of tributaries for fish reproduction and conservation in a highly anthropized river basin