cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.mnt85v
title: Occurrence Download

description: A dataset containing 931 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "NetworkKey is 99d66b6c-9087-452f-a9d4-f15f2c2d0e7e",
 "TaxonKey is Chordata"
 ]
 },
 "TaxonKey is one of (Tremarctos ornatus [GBIF Backbone Taxonomy])"
 ]
}

 The dataset includes 931 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004752-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bne83b
title: Occurrence Download

description: A dataset containing 318 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptoglossus zonatus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 318 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004755-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cetwb2
title: Occurrence Download

description: A dataset containing 81 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.26_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rhodiola fastigiata"
 ]
}

 The dataset includes 81 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004757-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9tynnz
title: Occurrence Download

description: A dataset containing 24701 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chinese Taipei",
 "OccurrenceStatus is Present",
 "TaxonKey is Lycaenidae",
 "Year 2013-2025"
 ]
}

 The dataset includes 24701 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004751-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ybvdqk
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gibsonnemertes spectabilis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004759-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17426044
title: LiveBench benchmark - Snapshot - October 23, 2025

description: Snapshot taken from LiveBench benchmark on October 23, 2025.
DOI: 10.5281/zenodo.17426045
title: LiveBench benchmark - Snapshot - October 23, 2025

description: Snapshot taken from LiveBench benchmark on October 23, 2025.
DOI: 10.15468/dl.yptz53
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oberholzeria etendekaensis",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004760-260126135527185/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.31169026
title: EEG, PPG, GSR Multimodal Physiological Signals for Rehabilitation Fatigue Detection (2025)

description: This dataset provides de-identified multimodal physiological signals and corresponding analysis codes dedicated to the research of <b>rehabilitation fatigue detection</b>, covering the whole research process from raw signal acquisition to machine learning model training. The dataset includes electroencephalogram (EEG) raw signals and combined photoplethysmography (PPG) and galvanic skin response (GSR) raw signals, all of which have been strictly de-identified in accordance with the ethical approval requirements (Ethics No.: HFUT20251208001H) to protect the privacy of research participants, with written informed consent obtained from all volunteers prior to data collection.The preprocessed and feature-extracted data files are also included, among which the EEG data is segmented into 3s, 5s, and 10s time scales for diverse research needs; in addition, the integrated preprocessed feature data of PPG-GSR and the fusion feature data of EEG-PPG-GSR are provided to support multi-modal signal analysis. Corresponding core MATLAB codes (developed and tested based on MATLAB R2018b) are attached, including training and validation codes for three classic machine learning models: K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Decision Tree (DT). All codes rely on MATLAB's Signal Processing Toolbox and Statistics and Machine Learning Toolbox, with independent running logic, which can directly load the dataset for experimental reproduction without additional plug-ins.This dataset belongs to the research field of systems physiology and biomedical engineering and integrates the technical application of information and computing sciences. It can provide reliable data and code support for the research on physiological signal processing, human fatigue assessment, and the application of machine learning in rehabilitation medicine, and effectively improve the reproducibility of relevant cross-disciplinary research. All data files are in .mat format, and the code files are in .m format, with a clear file structure and standard naming, which is convenient for academic research and experimental reuse.
DOI: 10.6084/m9.figshare.31169026.v4
title: EEG, PPG, GSR Multimodal Physiological Signals for Rehabilitation Fatigue Detection (2025)

description: This dataset provides de-identified multimodal physiological signals and corresponding analysis codes dedicated to the research of <b>rehabilitation fatigue detection</b>, covering the whole research process from raw signal acquisition to machine learning model training. The dataset includes electroencephalogram (EEG) raw signals and combined photoplethysmography (PPG) and galvanic skin response (GSR) raw signals, all of which have been strictly de-identified in accordance with the ethical approval requirements (Ethics No.: HFUT20251208001H) to protect the privacy of research participants, with written informed consent obtained from all volunteers prior to data collection.The preprocessed and feature-extracted data files are also included, among which the EEG data is segmented into 3s, 5s, and 10s time scales for diverse research needs; in addition, the integrated preprocessed feature data of PPG-GSR and the fusion feature data of EEG-PPG-GSR are provided to support multi-modal signal analysis. Corresponding core MATLAB codes (developed and tested based on MATLAB R2018b) are attached, including training and validation codes for three classic machine learning models: K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Decision Tree (DT). All codes rely on MATLAB's Signal Processing Toolbox and Statistics and Machine Learning Toolbox, with independent running logic, which can directly load the dataset for experimental reproduction without additional plug-ins.This dataset belongs to the research field of systems physiology and biomedical engineering and integrates the technical application of information and computing sciences. It can provide reliable data and code support for the research on physiological signal processing, human fatigue assessment, and the application of machine learning in rehabilitation medicine, and effectively improve the reproducibility of relevant cross-disciplinary research. All data files are in .mat format, and the code files are in .m format, with a clear file structure and standard naming, which is convenient for academic research and experimental reuse.
DOI: 10.6084/m9.figshare.31169026.v3
title: 脑电图、PPG、GSR 康复疲劳检测多模态生理信号（2025）

description: 该数据集提供了去识别的多模态生理信号及相应的分析代码<b>康复疲劳检测</b>，涵盖从原始信号采集到机器学习模型训练的整个研究过程。该数据集包括脑电图（EEG）原始信号以及综合光电容析（PPG）和皮肤电反应（GSR）原始信号，所有这些数据均严格去标识化，符合伦理审批要求（伦理编号：HFUT20251208001H），以保护研究参与者的隐私，并在数据收集前获得所有志愿者的书面知情同意。还包括预处理和特征提取的数据文件，其中脑电图数据被细分为3、5和10个时间尺度，以满足不同的研究需求;此外，还提供了PPG-GSR的集成预处理特征数据和EEG-PPG-GSR的融合特征数据，以支持多模态信号分析。附带了基于MATLAB R2018b开发和测试的MATLAB核心代码，包括三种经典机器学习模型的训练和验证代码：K最近邻（KNN）、支持向量机（SVM）和决策树（DT）。所有代码都依赖于 MATLAB 的信号处理工具箱和统计与机器学习工具箱，这些工具具有独立运行逻辑，可以直接加载数据集进行实验复制，无需额外插件。该数据集属于系统生理学和生物医学工程的研究领域，整合了信息科学和计算科学的技术应用。它能够为生理信号处理、人体疲劳评估以及机器学习在康复医学中的应用等研究提供可靠的数据和代码支持，并有效提升相关跨学科研究的可重复性。所有数据文件均为.mat格式，代码文件为.m格式，文件结构清晰且命名标准，便于学术研究和实验重用。
DOI: 10.5281/zenodo.17425930
title: Aider benchmark - Snapshot - October 23, 2025

description: Snapshot taken from Aider benchmark on October 23, 2025.
DOI: 10.5281/zenodo.17425929
title: Aider benchmark - Snapshot - October 23, 2025

description: Snapshot taken from Aider benchmark on October 23, 2025.
DOI: 10.15468/dl.hes5ad
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Eriochloa succincta"
 ]
}

 The dataset includes 20 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004763-260126135527185/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.31145221
title: Source Data - Cleaned - Predictive Factors in Team Formation in Software Engineering Education: A Ten-Year Longitudinal Study of Student Attributes and Performance

description: To provide a multi-dimensional view of student performance and team dynamics, the research team tracks a comprehensive set of attributes for each student. This dataset moves beyond broad binary indicators of technical experience by capturing specific proficiencies, development orientations, and self-assessed leadership styles. The datasets describe candidates across five primary dimensions, beginning with Academic Attributes such as normalized undergraduate GPA, university prestige, and country of origin. This is complemented by Technical Experience, which considers self-reported proficiency in frontend, backend, or full-stack development along with familiarity in specific frameworks like Node.js and Java. To ensure collaborative success, we measure Communication Fluency on a 4-point scale (ranging from Very Comfortable to Very Uncomfortable) and assess Leadership Dynamics based on individual roles and preferences. Finally, performance is validated through Peer Evaluation Ratings sourced from CATME, which specifically track contributions to the team, interpersonal interaction, ability to keep the project on track, possession of relevant KSAs (Knowledge, Skills, and Abilities), and a consistent expectation of quality.
DOI: 10.6084/m9.figshare.31145221.v2
title: Source Data - Cleaned - Predictive Factors in Team Formation in Software Engineering Education: A Ten-Year Longitudinal Study of Student Attributes and Performance

description: To provide a multi-dimensional view of student performance and team dynamics, the research team tracks a comprehensive set of attributes for each student. This dataset moves beyond broad binary indicators of technical experience by capturing specific proficiencies, development orientations, and self-assessed leadership styles. The datasets describe candidates across five primary dimensions, beginning with Academic Attributes such as normalized undergraduate GPA, university prestige, and country of origin. This is complemented by Technical Experience, which considers self-reported proficiency in frontend, backend, or full-stack development along with familiarity in specific frameworks like Node.js and Java. To ensure collaborative success, we measure Communication Fluency on a 4-point scale (ranging from Very Comfortable to Very Uncomfortable) and assess Leadership Dynamics based on individual roles and preferences. Finally, performance is validated through Peer Evaluation Ratings sourced from CATME, which specifically track contributions to the team, interpersonal interaction, ability to keep the project on track, possession of relevant KSAs (Knowledge, Skills, and Abilities), and a consistent expectation of quality.
DOI: 10.15468/dl.k3yr22
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bergia cerina",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004762-260126135527185/datasets/export for details.
DOI: 10.6084/m9.figshare.31145221.v1
title: Source Data - Cleaned - Predictive Factors in Team Formation in Software Engineering Education: A Ten-Year Longitudinal Study of Student Attributes and Performance

description: To provide a multi-dimensional view of student performance and team dynamics, the research team tracks a comprehensive set of attributes for each student. This dataset moves beyond broad binary indicators of technical experience by capturing specific proficiencies, development orientations, and self-assessed leadership styles. The datasets describe candidates across five primary dimensions, beginning with Academic Attributes such as normalized undergraduate GPA, university prestige, and country of origin. This is complemented by Technical Experience, which considers self-reported proficiency in frontend, backend, or full-stack development along with familiarity in specific frameworks like Node.js and Java. To ensure collaborative success, we measure Communication Fluency on a 4-point scale (ranging from Very Comfortable to Very Uncomfortable) and assess Leadership Dynamics based on individual roles and preferences. Finally, performance is validated through Peer Evaluation Ratings sourced from CATME, which specifically track contributions to the team, interpersonal interaction, ability to keep the project on track, possession of relevant KSAs (Knowledge, Skills, and Abilities), and a consistent expectation of quality.
DOI: 10.15468/dl.4aan3q
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oddoniodendron gambanum",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 53 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004764-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aevwbk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tetrastemma humilis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004767-260126135527185/datasets/export for details.
DOI: 10.15468/dl.s9ad8h
title: Occurrence Download

description: A dataset containing 666 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Olneya tesota",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 666 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004768-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mqgu7a
title: Occurrence Download

description: A dataset containing 13848 records in GBIF matching the query:
SELECT
 '531' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= 56.135291543055025
 AND decimalLatitude &lt;= 61.2993700571118
 AND decimalLongitude &gt;= -158.20848680943462
 AND decimalLongitude &lt;= -136.71469357869645
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 13848 records were derived from 127 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004754-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18408617
title: Source Data for "Shortcuts to topological state transfers in synthetic Rydberg lattices"
DOI: 10.5281/zenodo.18408618
title: Source Data for "Shortcuts to topological state transfers in synthetic Rydberg lattices"
DOI: 10.15468/dl.t8nncn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Emplectonema rubea",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004770-260126135527185/datasets/export for details.
DOI: 10.15468/dl.7gk2zx
title: Occurrence Download

description: A dataset containing 2230 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Onobrychis viciifolia",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 2230 records from 227 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004771-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gzcc7u
title: Occurrence Download

description: A dataset containing 130 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Emplectonema neesii",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 130 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004773-260126135527185/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.31175641
title: The source code of "Confined non-Hermitian skin effect in a semi-infinite Fock-state lattice".

description: The source code of "Confined non-Hermitian skin effect in a semi-infinite Fock-state lattice".
DOI: 10.6084/m9.figshare.31175641.v1
title: The source code of "Confined non-Hermitian skin effect in a semi-infinite Fock-state lattice".

description: The source code of "Confined non-Hermitian skin effect in a semi-infinite Fock-state lattice".
DOI: 10.15468/dl.a5zwcq
title: Occurrence Download

description: A dataset containing 19255 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Oenothera laciniata"
 ]
}

 The dataset includes 19255 records from 416 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004774-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pfsrxx
title: Occurrence Download

description: A dataset containing 498 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Centrochelys sulcata"
 ]
}

 The dataset includes 498 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004726-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bfxgpb
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dissomeria crenata",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004727-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18448115
title: THE LINGUISTIC CHARACTERISTICS OF ISOLATING (AMORPHIC) LANGUAGES: A THEORETICAL AND CONTRASTIVE STUDY

description: This thesis examines the main linguistic features of isolating (amorphic) languages, which are characterized by minimal morphological complexity and a predominance of free morphemes. Unlike agglutinative or fusional languages, isolating languages convey grammatical relations primarily through word order, function words, and contextual cues rather than through affixation or inflection. Each word typically corresponds to a single morpheme, and grammatical categories such as tense, aspect, number, and case are expressed syntactically rather than morphologically.
DOI: 10.5281/zenodo.18448116
title: THE LINGUISTIC CHARACTERISTICS OF ISOLATING (AMORPHIC) LANGUAGES: A THEORETICAL AND CONTRASTIVE STUDY

description: This thesis examines the main linguistic features of isolating (amorphic) languages, which are characterized by minimal morphological complexity and a predominance of free morphemes. Unlike agglutinative or fusional languages, isolating languages convey grammatical relations primarily through word order, function words, and contextual cues rather than through affixation or inflection. Each word typically corresponds to a single morpheme, and grammatical categories such as tense, aspect, number, and case are expressed syntactically rather than morphologically.
DOI: 10.15468/dl.54bvm6
title: Occurrence Download

description: A dataset containing 1729 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Culex gelidus)"
 ]
}

 The dataset includes 1729 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004728-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qhm47f
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "MediaType is Image",
 "TaxonKey is Hyalomma dromedarii"
 ]
}

 The dataset includes 9 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004729-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.thzxd9
title: Occurrence Download

description: A dataset containing 685 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Nepal",
 "OccurrenceStatus is Present",
 "TaxonKey is Axis axis",
 "Year 2010-2026"
 ]
}

 The dataset includes 685 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004730-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18447897
title: Assimilation of topo and bathy data Layer 2_Res-1 arc-second in Flores area

description: Assimilation of topo and bathy data Layer 2_Res-1 arc-second in Flores area