cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.6fuhqp
title: Occurrence Download

description: A dataset containing 1813 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bolitoglossa franklini"
 ]
}

 The dataset includes 1813 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064188-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17832558
title: Structural Homology of HHV-6B Epitopes as Candidates for Molecular Mimicry Triggers  of Type One Diabetes Mellitus Onset

description: Molecular mimicry is a mechanism by which an infectious agent may trigger an autoimmune response through structural or sequence similarity to self-antigens. Identifying potential molecular mimics is critical to understanding autoimmune disorders, including type 1 diabetes mellitus (T1DM). Human herpesvirus 6B (HHV-6B), a common childhood virus implicated in multiple autoimmune conditions, has been epidemiologically linked to a significant increased risk of T1DM for individuals with a genetic predisposition. However, the connection between HHV-6B and T1DM remains unresolved, as known HHV-6B epitopes show minimal sequence homology with T1DM autoantigens. This study explores whether HHV-6B can act as a molecular mimic by assessing structural and biding similarities between HHV-6B-derived and T1DM autoantigen-derived epitopes. Epitope peptide structures and their interactions with T1DM autoantigens were modeled using Boltz-2. Several HHV-6B epitopes studied here demonstrated high structural alignment with T1DM epitopes, but even when structural homology is lacking, the HHV-6B and T1DM epitopes fit into the same binding region of HLA molecules, suggesting a plausible mechanism for T cell cross-reactivity. These findings provide computational evidence that HHV-6B may act as a molecular mimic contributing to autoimmune responses in T1DM genetically susceptible individuals. This study demonstrates that structural modeling is a useful tool for identifying potential mimicry candidates that sequence-based methods may not find, underscoring the importance of integrating structure-based modeling including docking into molecular mimicry prediction pipelines. 

Structural modeling of  both the 50 epitopes from the 25 candidate pairs from the Suleman studies and those three from Bach’s paper was performed with Boltz-2 (v.2.2.0), an open-source deep learning method that predicts biomolecular structures and binding sites with great accuracy. Boltz-2 requires protein inputs of at least ten amino acids, and many of the epitopes considered here (Table 1 and 2) did not meet this requirement, so each epitope sequence was expanded symmetrically using the full protein sequences from UniProt (https://www.uniprot.org/). The extended sequences are given in Table S1 of the Supplementary maerial.  In all cases selected for analysis, model 0 from Boltz-2 consistently exhibited the highest confidence scores, and these models were used in subsequent analyses. The confidence scores for all the calculations  average 0.74 for the structures of the isolated epitopes and 0.87 for the structures of the epitopes bound to the HLA molecules. These values are within the range of good Boltz-2 prediction.
DOI: 10.5281/zenodo.17832559
title: Structural Homology of HHV-6B Epitopes as Candidates for Molecular Mimicry Triggers  of Type One Diabetes Mellitus Onset

description: Molecular mimicry is a mechanism by which an infectious agent may trigger an autoimmune response through structural or sequence similarity to self-antigens. Identifying potential molecular mimics is critical to understanding autoimmune disorders, including type 1 diabetes mellitus (T1DM). Human herpesvirus 6B (HHV-6B), a common childhood virus implicated in multiple autoimmune conditions, has been epidemiologically linked to a significant increased risk of T1DM for individuals with a genetic predisposition. However, the connection between HHV-6B and T1DM remains unresolved, as known HHV-6B epitopes show minimal sequence homology with T1DM autoantigens. This study explores whether HHV-6B can act as a molecular mimic by assessing structural and biding similarities between HHV-6B-derived and T1DM autoantigen-derived epitopes. Epitope peptide structures and their interactions with T1DM autoantigens were modeled using Boltz-2. Several HHV-6B epitopes studied here demonstrated high structural alignment with T1DM epitopes, but even when structural homology is lacking, the HHV-6B and T1DM epitopes fit into the same binding region of HLA molecules, suggesting a plausible mechanism for T cell cross-reactivity. These findings provide computational evidence that HHV-6B may act as a molecular mimic contributing to autoimmune responses in T1DM genetically susceptible individuals. This study demonstrates that structural modeling is a useful tool for identifying potential mimicry candidates that sequence-based methods may not find, underscoring the importance of integrating structure-based modeling including docking into molecular mimicry prediction pipelines. 

Structural modeling of  both the 50 epitopes from the 25 candidate pairs from the Suleman studies and those three from Bach’s paper was performed with Boltz-2 (v.2.2.0), an open-source deep learning method that predicts biomolecular structures and binding sites with great accuracy. Boltz-2 requires protein inputs of at least ten amino acids, and many of the epitopes considered here (Table 1 and 2) did not meet this requirement, so each epitope sequence was expanded symmetrically using the full protein sequences from UniProt (https://www.uniprot.org/). The extended sequences are given in Table S1 of the Supplementary maerial.  In all cases selected for analysis, model 0 from Boltz-2 consistently exhibited the highest confidence scores, and these models were used in subsequent analyses. The confidence scores for all the calculations  average 0.74 for the structures of the isolated epitopes and 0.87 for the structures of the epitopes bound to the HLA molecules. These values are within the range of good Boltz-2 prediction.
DOI: 10.7298/8x1k-zw39
title: Data from: Fully Contained Laboratory Earthquakes: The Effect of Asperity Aspect Ratio and Free Surfaces
DOI: 10.15468/dl.pje98h
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bolitoglossa gomezi"
 ]
}

 The dataset includes 19 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064190-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18023199
title: The Influence of Religiosity on Financial Reporting Quality Across Countries: The Moderating Effect of Legal Origin
DOI: 10.5281/zenodo.18023198
title: The Influence of Religiosity on Financial Reporting Quality Across Countries: The Moderating Effect of Legal Origin
DOI: 10.6084/m9.figshare.30940871
title: Desarrollo de la comunidad macrobentónica en un sustrato artificial con inicio en dos temporadas climáticas en el suroeste del golfo de México

description: La colonización y desarrollo de la comunidad macrobentónica está influenciada por las condiciones ambientales, por lo que el objetivo de este trabajo fue contrastar los patrones de desarrollo de la comunidad macrobentónica en sustratos artificiales durante dos temporadas climáticas. El seguimiento del desarrollo se registró mediante fotografías de cuadrantes fijos a lo largo de un pecio. Se describe una comunidad diversa de organismos macrobentónicos compuesta por 148 unidades taxonómicas operativas distribuidas en nueve grupos taxonómicos. El grupo Bryozoa fue dominante en ambas temporadas y en el grupo control. Los patrones comunitarios de ambas temporadas fueron diferentes, aunque convergieron con el grupo control después de 18 meses. Las condiciones ambientales de cada temporada fueron importantes para el establecimiento de las comunidades macrobentónicas. El molusco <i>Elysia ornata</i> es nuevo registro para el Sistema Arrecifal Veracruzano.
DOI: 10.6084/m9.figshare.30940871.v1
title: Desarrollo de la comunidad macrobentónica en un sustrato artificial con inicio en dos temporadas climáticas en el suroeste del golfo de México

description: La colonización y desarrollo de la comunidad macrobentónica está influenciada por las condiciones ambientales, por lo que el objetivo de este trabajo fue contrastar los patrones de desarrollo de la comunidad macrobentónica en sustratos artificiales durante dos temporadas climáticas. El seguimiento del desarrollo se registró mediante fotografías de cuadrantes fijos a lo largo de un pecio. Se describe una comunidad diversa de organismos macrobentónicos compuesta por 148 unidades taxonómicas operativas distribuidas en nueve grupos taxonómicos. El grupo Bryozoa fue dominante en ambas temporadas y en el grupo control. Los patrones comunitarios de ambas temporadas fueron diferentes, aunque convergieron con el grupo control después de 18 meses. Las condiciones ambientales de cada temporada fueron importantes para el establecimiento de las comunidades macrobentónicas. El molusco <i>Elysia ornata</i> es nuevo registro para el Sistema Arrecifal Veracruzano.
DOI: 10.15468/dl.xsqxvx
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bolitoglossa gracilis"
 ]
}

 The dataset includes 10 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064192-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18150/fue0sy
title: Structure and magnetic properties of Eu- and Nd-doped ﬂux-grown icosahedral Al-Cu-Fe quasicrystals: raw data

description: The dataset contain raw data and Python scripts discussed and analyzed in the related publication: Structure and magnetic properties of Eu- and Nd-doped ﬂux-grown icosahedral Al-Cu-Fe quasicrystals, Piotr Józef Bardziński, Dagmara Kulesza , Paul D. Asimow ,Jinping Hu ,Stephen Armstrong, Daniel M. Silevitch , T. F. Rosenbaum; PHYSICAL REVIEW MATERIALS 00, 000000 (2025).Project was aimed at development of the novel multi-phase aluminum-based alloy compositions that contain quasicrystalline phases and exhibit long-range magnetic order at near-room temperature. The task includes determination of structure, thermal stability and fundamental magnetic properties of the studied materials. Another aim was the unequivocal assignment of the investigated magnetic properties to the certain quasicrystalline microstructural phases of the chosen alloys.
DOI: 10.15468/dl.hpqcvf
title: Occurrence Download

description: A dataset containing 3916 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((-80.03887 -58.96731,-60.87013 -58.96731,-60.87013 -35.72333,-64.57669 -44.65561,-70.23741 -44.40852,-80.03887 -35.72333,-80.03887 -58.96731))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (January, December, November)",
 "OccurrenceStatus is Present",
 "TaxonKey is Muscisaxicola capistratus",
 "Year 1970-2025"
 ]
}

 The dataset includes 3916 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064193-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e241545
title: Replication Package for Edutainment, Savings and Empowerment in Rural Areas of Peru

description: This repository contains the data and code necessary to replicate Chong and Valdivia (2025), Edutainment, Savings and Empowerment in Rural Areas of Peru.
DOI: 10.3886/e241545v1
title: Replication Package for Edutainment, Savings and Empowerment in Rural Areas of Peru

description: This repository contains the data and code necessary to replicate Chong and Valdivia (2025), Edutainment, Savings and Empowerment in Rural Areas of Peru.
DOI: 10.15468/dl.94x5p8
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bolitoglossa guaneae"
 ]
}

 The dataset includes 36 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064194-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s4dust
title: Occurrence Download

description: A dataset containing 142325 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "TaxonKey is one of (Danaus plexippus, Aglais io, Papilio machaon, Morpho menelaus, Vanessa atalanta, Pieris brassicae, Gonepteryx rhamni)",
 "Year 2025-2025"
 ]
}

 The dataset includes 142325 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064191-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18037184
title: Buddhist Classics AI Translation Series Vol.15:Chinese Tripiṭaka in Tibetan, Pāli, Japanese, Korean Version(藏巴利日韩译汉文大藏经三藏原典) 1.0

description:  

This is Volume 15 of the "Buddhist Classics AI Translation Series," containing AI-generated translations of the Chinese Tripitaka (Sutras, Vinaya, and Abhidharma of South Asian origin) into Tibetan, Pali, Japanese, and Korean (Version 1.0).

Key Features:1. Multilingual Coverage: Includes translations into Tibetan, Pali, Japanese, and Korean.2. Pali in Multiple Scripts: The Pali section features a "Mahayana Hybrid Pali" style. In addition to the primary Romanized Pali translation, it includes transliterations into eight regional scripts: Thai, Myanmar, Sinhala, Lao, Khmer, Tai Le (Dehong), Shan, and Lanna (Tai Tham), totaling nine script systems.3. Tibetan Translation: Integrates the millennial tradition of Tibetan Buddhist translation with AI, achieving high terminological standardization and supplementing texts missing from the Tibetan Canon.4. Japanese and Korean: Japanese translations use the Kundoku style (quasi-classical), while Korean translations balance modernity with tradition for academic accessibility.

Technical Note:Produced by the BCAITS Team. Translation primarily powered by Gemini 2.5 Flash  System architecture and evaluation assisted by Claude 4.5 Sonnet and Grok 4. Pali script transliteration utilizes the Aksharamukha engine and custom Python algorithms.

Disclaimer:These translations are AI-generated for academic reference and experimental purposes. The Pali translations utilize a reconstructed Mahayana terminology system.
description: 【中文摘要】

本卷为《佛典AI译丛》第十五卷,收录了汉文大藏经中译自南亚的三藏(经、律、论)原典的藏文、巴利文、日文及韩文AI翻译版(1.0版)。本卷并非完整的汉传佛教大藏经,仅包含历史上由梵文或中亚语言译入汉文的经典部分。

主要内容与特色:1. 多语种覆盖:包含藏文、巴利文、日文、韩文四种主要目标语言。2. 巴利文多文字系统:巴利文部分首创“大乘混合巴利语”风格,除罗马字(Romanized Pali)初翻外,还进一步转写为八种地区文字:泰文、缅文、僧伽罗文、老挝文、高棉文、德宏傣文、掸文及兰纳文,共涉及九种文字系统。3. 藏文翻译:利用AI融合了藏传佛教千年翻译传统,术语标准化程度高,补充了藏文大藏经中缺失的汉传经典(如部分早期中观、唯识论典)。4. 日韩翻译:日文采用训读体(準文語体),韩文兼顾现代性与传统性,便于学术对照与阅读。

技术说明:本项目由“佛典AI译丛”团队制作。翻译工作主要由 Gemini 2.5 Flash完成,程序架构与评估由 Claude 4.5 Sonnet 与 Grok 4 协助。

免责声明:本译本由人工智能生成,旨在填补学术空白并提供多语种对照参考,属于学术实验性质。巴利文翻译采用了重构的大乘术语体系,并非历史原典的还原。

【English Abstract】
DOI: 10.5281/zenodo.18037183
title: Buddhist Classics AI Translation Series Vol.15:Chinese Tripiṭaka in Tibetan, Pāli, Japanese, Korean Version(藏巴利日韩译汉文大藏经三藏原典) 1.0

description:  

This is Volume 15 of the "Buddhist Classics AI Translation Series," containing AI-generated translations of the Chinese Tripitaka (Sutras, Vinaya, and Abhidharma of South Asian origin) into Tibetan, Pali, Japanese, and Korean (Version 1.0).

Key Features:1. Multilingual Coverage: Includes translations into Tibetan, Pali, Japanese, and Korean.2. Pali in Multiple Scripts: The Pali section features a "Mahayana Hybrid Pali" style. In addition to the primary Romanized Pali translation, it includes transliterations into eight regional scripts: Thai, Myanmar, Sinhala, Lao, Khmer, Tai Le (Dehong), Shan, and Lanna (Tai Tham), totaling nine script systems.3. Tibetan Translation: Integrates the millennial tradition of Tibetan Buddhist translation with AI, achieving high terminological standardization and supplementing texts missing from the Tibetan Canon.4. Japanese and Korean: Japanese translations use the Kundoku style (quasi-classical), while Korean translations balance modernity with tradition for academic accessibility.

Technical Note:Produced by the BCAITS Team. Translation primarily powered by Gemini 2.5 Flash  System architecture and evaluation assisted by Claude 4.5 Sonnet and Grok 4. Pali script transliteration utilizes the Aksharamukha engine and custom Python algorithms.

Disclaimer:These translations are AI-generated for academic reference and experimental purposes. The Pali translations utilize a reconstructed Mahayana terminology system.
description: 【中文摘要】

本卷为《佛典AI译丛》第十五卷,收录了汉文大藏经中译自南亚的三藏(经、律、论)原典的藏文、巴利文、日文及韩文AI翻译版(1.0版)。本卷并非完整的汉传佛教大藏经,仅包含历史上由梵文或中亚语言译入汉文的经典部分。

主要内容与特色:1. 多语种覆盖:包含藏文、巴利文、日文、韩文四种主要目标语言。2. 巴利文多文字系统:巴利文部分首创“大乘混合巴利语”风格,除罗马字(Romanized Pali)初翻外,还进一步转写为八种地区文字:泰文、缅文、僧伽罗文、老挝文、高棉文、德宏傣文、掸文及兰纳文,共涉及九种文字系统。3. 藏文翻译:利用AI融合了藏传佛教千年翻译传统,术语标准化程度高,补充了藏文大藏经中缺失的汉传经典(如部分早期中观、唯识论典)。4. 日韩翻译:日文采用训读体(準文語体),韩文兼顾现代性与传统性,便于学术对照与阅读。

技术说明:本项目由“佛典AI译丛”团队制作。翻译工作主要由 Gemini 2.5 Flash完成,程序架构与评估由 Claude 4.5 Sonnet 与 Grok 4 协助。

免责声明:本译本由人工智能生成,旨在填补学术空白并提供多语种对照参考,属于学术实验性质。巴利文翻译采用了重构的大乘术语体系,并非历史原典的还原。

【English Abstract】
DOI: 10.5281/zenodo.18038432
title: Dataset: Operando measurement of transition metal deposition in a NMC Li-ion battery using laboratory confocal micro-X-ray fluorescence spectroscopy

description: HDF5 with all meta data of Mn Map ex-situ
DOI: 10.5281/zenodo.18038431
title: Dataset: Operando measurement of transition metal deposition in a NMC Li-ion battery using laboratory confocal micro-X-ray fluorescence spectroscopy

description: HDF5 with all meta data of Mn Map ex-situ
DOI: 10.6084/m9.figshare.30940976
title: <b><i>SKIMS-ECG:</i></b><b> A Clinically Validated ECG Feature Dataset for Multi-Class Cardiovascular Disease Detection</b>

description: <b>SKIMS-ECG</b> is a clinically validated cardiovascular disease dataset derived from real-time <b>12-lead electrocardiogram (ECG)</b> recordings collected at the <b>Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, India</b>. The dataset comprises <b>24,894 ECG examinations</b>, each independently reviewed and annotated by experienced cardiologists, ensuring high diagnostic reliability and clinical relevance.The dataset includes <b>20 attributes per record</b>, consisting of <b>10 ECG morphological features</b>, <b>9 demographic and clinical risk-factor variables</b>, and <b>1 target class label</b>. ECG features capture key physiological characteristics such as heart rate, PR interval, QRS duration, QT/QTc interval, electrical axes (P, QRS, R, and T), RV5/SV1 voltage, and R-wave amplitude in lead aVR. Demographic and clinical attributes include age, gender, systolic and diastolic blood pressure, diabetes status, cholesterol status, smoking history, medication usage, and family history of cardiovascular disease.Each ECG record is classified into one of <b>six major cardiovascular disease categories</b>: <b>normal, cardiac arrhythmia, coronary heart disease (CHD), cardiomyopathy, stroke-related ECG patterns, and heart failure.</b> The dataset is <b>balanced</b>, with an equal number of samples in each class, making it well-suited for unbiased multi-class classification and benchmarking studies.This release contains <b>two CSV files</b>:<br>(i) a <b>raw feature dataset</b> with original extracted ECG and clinical attributes, and<br>(ii) a <b>min-max normalized dataset</b>, where all numerical features are scaled to the range [0,1] to support stable and reproducible machine learning experiments. Both files share identical structure, column names, and row ordering.ECG recordings were acquired using the <b>BioCare ECG-1210 system</b> at a sampling rate of <b>250 Hz</b> with a <b>10-second duration</b>, following standard resting ECG protocols. Signal processing, feature extraction, and data management were performed using <b>BioCare ECG-1000 software</b>, followed by expert cardiologist verification.The dataset was created in full compliance with ethical research standards. Ethical approval was obtained from the <b>Institutional Ethics Committee, Lovely Professional University, Punjab, India (Ref. No.: IEC-LPU/2025/1/19)</b>. All data are fully anonymized, and no personally identifiable information is included.<b>SKIMS-ECG</b> is intended for <b>academic and non-commercial research</b> and supports a wide range of applications, including <b>machine learning and deep learning-based cardiovascular disease detection, soft-computing and optimization studies, explainable AI (XAI), clinical decision-support systems</b>, and research on <b>underrepresented Himalayan populations</b>.
DOI: 10.6084/m9.figshare.30940976.v1
title: <b><i>SKIMS-ECG:</i></b><b> A Clinically Validated ECG Feature Dataset for Multi-Class Cardiovascular Disease Detection</b>

description: <b>SKIMS-ECG</b> is a clinically validated cardiovascular disease dataset derived from real-time <b>12-lead electrocardiogram (ECG)</b> recordings collected at the <b>Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Srinagar, India</b>. The dataset comprises <b>24,894 ECG examinations</b>, each independently reviewed and annotated by experienced cardiologists, ensuring high diagnostic reliability and clinical relevance.The dataset includes <b>20 attributes per record</b>, consisting of <b>10 ECG morphological features</b>, <b>9 demographic and clinical risk-factor variables</b>, and <b>1 target class label</b>. ECG features capture key physiological characteristics such as heart rate, PR interval, QRS duration, QT/QTc interval, electrical axes (P, QRS, R, and T), RV5/SV1 voltage, and R-wave amplitude in lead aVR. Demographic and clinical attributes include age, gender, systolic and diastolic blood pressure, diabetes status, cholesterol status, smoking history, medication usage, and family history of cardiovascular disease.Each ECG record is classified into one of <b>six major cardiovascular disease categories</b>: <b>normal, cardiac arrhythmia, coronary heart disease (CHD), cardiomyopathy, stroke-related ECG patterns, and heart failure.</b> The dataset is <b>balanced</b>, with an equal number of samples in each class, making it well-suited for unbiased multi-class classification and benchmarking studies.This release contains <b>two CSV files</b>:<br>(i) a <b>raw feature dataset</b> with original extracted ECG and clinical attributes, and<br>(ii) a <b>min-max normalized dataset</b>, where all numerical features are scaled to the range [0,1] to support stable and reproducible machine learning experiments. Both files share identical structure, column names, and row ordering.ECG recordings were acquired using the <b>BioCare ECG-1210 system</b> at a sampling rate of <b>250 Hz</b> with a <b>10-second duration</b>, following standard resting ECG protocols. Signal processing, feature extraction, and data management were performed using <b>BioCare ECG-1000 software</b>, followed by expert cardiologist verification.The dataset was created in full compliance with ethical research standards. Ethical approval was obtained from the <b>Institutional Ethics Committee, Lovely Professional University, Punjab, India (Ref. No.: IEC-LPU/2025/1/19)</b>. All data are fully anonymized, and no personally identifiable information is included.<b>SKIMS-ECG</b> is intended for <b>academic and non-commercial research</b> and supports a wide range of applications, including <b>machine learning and deep learning-based cardiovascular disease detection, soft-computing and optimization studies, explainable AI (XAI), clinical decision-support systems</b>, and research on <b>underrepresented Himalayan populations</b>.