cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18503500
title: A multimodal biomechanics and electromyography dataset of drop vertical jump under virtual-reality visual height perturbations in individuals with and without chronic ankle instability

description: This dataset contains multimodal biomechanical data of drop vertical jump (DVJ) performed under controlled virtual-reality (VR) visual height perturbations. Data were collected from 28 participants, including individuals with chronic ankle instability (CAI) and healthy control participants. Each participant completed one real-world control condition (30 cm) and four VR visual-height conditions (0, 10, 30 and 50 cm), in which the physical drop height was fixed while the perceived visual height was manipulated.

Synchronous whole-body kinematics, ground reaction forces and bilateral surface electromyography (EMG) signals from key lower-limb muscles were recorded during each trial. Motion capture data were collected using a 38-marker Plug-in-Gait model. The dataset provides raw and processed data in C3D, OpenSim-compatible (.trc and .mot), and ASCII formats, together with participant-level metadata including demographics and lower-limb anthropometrics.

This dataset can be reused to investigate jump–landing biomechanics under visual perturbation, perception–action coupling, musculoskeletal simulation, inverse dynamics analysis, and data-driven modeling in CAI and non-CAI populations.
DOI: 10.5281/zenodo.18503499
title: A multimodal biomechanics and electromyography dataset of drop vertical jump under virtual-reality visual height perturbations in individuals with and without chronic ankle instability

description: This dataset contains multimodal biomechanical data of drop vertical jump (DVJ) performed under controlled virtual-reality (VR) visual height perturbations. Data were collected from 28 participants, including individuals with chronic ankle instability (CAI) and healthy control participants. Each participant completed one real-world control condition (30 cm) and four VR visual-height conditions (0, 10, 30 and 50 cm), in which the physical drop height was fixed while the perceived visual height was manipulated.

Synchronous whole-body kinematics, ground reaction forces and bilateral surface electromyography (EMG) signals from key lower-limb muscles were recorded during each trial. Motion capture data were collected using a 38-marker Plug-in-Gait model. The dataset provides raw and processed data in C3D, OpenSim-compatible (.trc and .mot), and ASCII formats, together with participant-level metadata including demographics and lower-limb anthropometrics.

This dataset can be reused to investigate jump–landing biomechanics under visual perturbation, perception–action coupling, musculoskeletal simulation, inverse dynamics analysis, and data-driven modeling in CAI and non-CAI populations.
DOI: 10.15468/dl.qxwp38
title: Occurrence Download

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

 The dataset includes 53 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016074-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/dans-2c3-9dmq
title: Archeologisch onderzoek uitbreiding Spittaal te Zutphen
title: GAR 040

description: &lt;p&gt;onderzoeksrapport&lt;/p&gt;
description: &lt;p&gt;inventariserend veldonderzoek&lt;/p&gt;
DOI: 10.5281/zenodo.18503651
title: ENGLISH FOR MEDICAL STUDENTS: OPENAI TEXNOLOGIYALARI ASOSIDA O'QITISH PLATFORMASINI YARATISH

description: Mazkur ilmiy maqolada tibbiyot yo‘nalishida tahsil olayotgan talabalar uchun ingliz tilini o‘qitishga mo‘ljallangan, sun’iy intellekt texnologiyalariga asoslangan zamonaviy raqamli ta’lim platformasini ishlab chiqish va uni o‘quv jarayoniga joriy etish masalalari har tomonlama yoritiladi. Tadqiqotning asosiy e’tibori ingliz tilining tibbiyot sohasidagi kasbiy ahamiyatini hisobga olgan holda, talabalar uchun moslashtirilgan va interaktiv o‘quv muhitini yaratishga qaratilgan.

Maqolada OpenAI texnologiyalarining ta’lim jarayonidagi o‘rni chuqur tahlil qilinib, xususan, ushbu sun’iy intellekt modellarining tibbiy ingliz tilini o‘rgatishdagi ustun jihatlari ilmiy asosda yoritib beriladi. Jumladan, murakkab tibbiy terminologiyani soddalashtirib tushuntirish, klinik holatlarga asoslangan dialog va mashqlarni avtomatik yaratish, shuningdek, talabaning bilim darajasi va ehtiyojlariga mos individual o‘quv yo‘llarini shakllantirish imkoniyatlari batafsil ko‘rib chiqiladi.

Taklif etilayotgan platforma talabalarning nafaqat til bilish darajasini oshirish, balki ularning mustaqil o‘rganish ko‘nikmalarini rivojlantirish, tanqidiy fikrlash va kasbiy muloqot kompetensiyalarini shakllantirishga xizmat qiladi. Bundan tashqari, sun’iy intellektga asoslangan baholash va fikr-mulohaza mexanizmlari orqali o‘quv jarayonining samaradorligini oshirish, o‘qituvchilar yuklamasini kamaytirish hamda ta’lim sifatini yangi bosqichga olib chiqish imkoniyatlari  asoslab beriladi.
DOI: 10.5281/zenodo.18503650
title: ENGLISH FOR MEDICAL STUDENTS: OPENAI TEXNOLOGIYALARI ASOSIDA O'QITISH PLATFORMASINI YARATISH

description: Mazkur ilmiy maqolada tibbiyot yo‘nalishida tahsil olayotgan talabalar uchun ingliz tilini o‘qitishga mo‘ljallangan, sun’iy intellekt texnologiyalariga asoslangan zamonaviy raqamli ta’lim platformasini ishlab chiqish va uni o‘quv jarayoniga joriy etish masalalari har tomonlama yoritiladi. Tadqiqotning asosiy e’tibori ingliz tilining tibbiyot sohasidagi kasbiy ahamiyatini hisobga olgan holda, talabalar uchun moslashtirilgan va interaktiv o‘quv muhitini yaratishga qaratilgan.

Maqolada OpenAI texnologiyalarining ta’lim jarayonidagi o‘rni chuqur tahlil qilinib, xususan, ushbu sun’iy intellekt modellarining tibbiy ingliz tilini o‘rgatishdagi ustun jihatlari ilmiy asosda yoritib beriladi. Jumladan, murakkab tibbiy terminologiyani soddalashtirib tushuntirish, klinik holatlarga asoslangan dialog va mashqlarni avtomatik yaratish, shuningdek, talabaning bilim darajasi va ehtiyojlariga mos individual o‘quv yo‘llarini shakllantirish imkoniyatlari batafsil ko‘rib chiqiladi.

Taklif etilayotgan platforma talabalarning nafaqat til bilish darajasini oshirish, balki ularning mustaqil o‘rganish ko‘nikmalarini rivojlantirish, tanqidiy fikrlash va kasbiy muloqot kompetensiyalarini shakllantirishga xizmat qiladi. Bundan tashqari, sun’iy intellektga asoslangan baholash va fikr-mulohaza mexanizmlari orqali o‘quv jarayonining samaradorligini oshirish, o‘qituvchilar yuklamasini kamaytirish hamda ta’lim sifatini yangi bosqichga olib chiqish imkoniyatlari  asoslab beriladi.
DOI: 10.15468/dl.n47exc
title: Occurrence Download

description: A dataset containing 275 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Campanula specularioides"
 ]
}

 The dataset includes 275 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016075-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18051746
title: Supplementary Materials for: Agentic Explainable Artificial Intelligence (Agentic XAI) Approach To Explore Better Explanation

description: This dataset contains the supplementary materials for the manuscript "Agentic Explainable Artificial Intelligence (Agentic XAI) Approach To Explore Better Explanation."The repository documents the complete implementation of an iterative refinement process designed to generate actionable farmer recommendations from agricultural data.It includes all prompts, source code, visualization artifacts, and textual outputs across all refinement rounds.

Contents





"Figures" Folder Archives all visualization outputs and statistical artifacts generated throughout the iterative refinement process (Rounds 0–10). These files document the autonomous expansion of the system's analytical scope, progressing from fundamental bivariate relationships in early rounds to complex multi-way interactions, temporal pattern decompositions, and comprehensive correlation matrices in later iterations.




"Prompts" Folder Contains the three sequential prompts that control the agentic workflow, mapped to specific analysis stages:





Prompt 1 (Initial Interpretation): Used in Round 0 to request baseline recommendations based solely on SHAP visualizations.




Prompt 2 (Gap Analysis and Code Generation): Used in Rounds 1–10 to trigger self-reflection, instructing the model to identify analytical gaps and provide Python code for generating supplementary figures.




Prompt 3 (Synthesis and Update): Used in Rounds 1–10 to guide the synthesis of original insights with newly generated supplementary analyses for updated recommendations.






PythonCode.ipynb A Jupyter Notebook comprising the complete execution history, including the initial XAI analysis code and all supplementary Python scripts autonomously generated via Prompt 2 during Rounds 0–10. The notebook serves as evidence of escalating analytical complexity, demonstrating the system's ability to autonomously implement advanced statistical analyses and multi-dimensional data explorations.




"Recommendations" Folder Stores the textual recommendations for farmers generated at the baseline (Round 0, via Prompt 1) and throughout the refinement phase (Rounds 1–10, via Prompt 3). These documents illustrate the progressive enhancement of advice quality resulting from the agent's self-reflection and integration of supplementary analyses.



This organizational structure ensures full transparency and reproducibility of the Agentic XAI workflow. It traces the entire pipeline from initial explainability analysis to the final, farmer-oriented recommendations, while explicitly documenting the autonomous escalation of analytical complexity that characterizes the agentic refinement process.
DOI: 10.5281/zenodo.17876329
title: Supplementary Materials for: Agentic Explainable Artificial Intelligence (Agentic XAI) Approach To Explore Better Explanation

description: This dataset contains the supplementary materials for the manuscript "Agentic Explainable Artificial Intelligence (Agentic XAI) Approach To Explore Better Explanation."The repository documents the complete implementation of an iterative refinement process designed to generate actionable farmer recommendations from agricultural data.It includes all prompts, source code, visualization artifacts, and textual outputs across all refinement rounds.

Contents





"Figures" Folder Archives all visualization outputs and statistical artifacts generated throughout the iterative refinement process (Rounds 0–10). These files document the autonomous expansion of the system's analytical scope, progressing from fundamental bivariate relationships in early rounds to complex multi-way interactions, temporal pattern decompositions, and comprehensive correlation matrices in later iterations.




"Prompts" Folder Contains the three sequential prompts that control the agentic workflow, mapped to specific analysis stages:





Prompt 1 (Initial Interpretation): Used in Round 0 to request baseline recommendations based solely on SHAP visualizations.




Prompt 2 (Gap Analysis and Code Generation): Used in Rounds 1–10 to trigger self-reflection, instructing the model to identify analytical gaps and provide Python code for generating supplementary figures.




Prompt 3 (Synthesis and Update): Used in Rounds 1–10 to guide the synthesis of original insights with newly generated supplementary analyses for updated recommendations.






PythonCode.ipynb A Jupyter Notebook comprising the complete execution history, including the initial XAI analysis code and all supplementary Python scripts autonomously generated via Prompt 2 during Rounds 0–10. The notebook serves as evidence of escalating analytical complexity, demonstrating the system's ability to autonomously implement advanced statistical analyses and multi-dimensional data explorations.




"Recommendations" Folder Stores the textual recommendations for farmers generated at the baseline (Round 0, via Prompt 1) and throughout the refinement phase (Rounds 1–10, via Prompt 3). These documents illustrate the progressive enhancement of advice quality resulting from the agent's self-reflection and integration of supplementary analyses.



This organizational structure ensures full transparency and reproducibility of the Agentic XAI workflow. It traces the entire pipeline from initial explainability analysis to the final, farmer-oriented recommendations, while explicitly documenting the autonomous escalation of analytical complexity that characterizes the agentic refinement process.
DOI: 10.15468/dl.sgm8ex
title: Occurrence Download

description: A dataset containing 113 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eremospatha cuspidata",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 113 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016076-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tg4kpc
title: Occurrence Download

description: A dataset containing 401 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.2_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Garrulax davidi",
 "Year is 2022"
 ]
}

 The dataset includes 401 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016077-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18503672
title: LANGUAGE ATTITUDES TOWARD ENGLISH AMONG UNIVERSITY STUDENTS

description: This article examines language attitudes toward English among university students, focusing on their perceptions, motivations, and emotional responses to the language in academic and social contexts. English has become a global lingua franca, playing a crucial role in higher education, professional development, and international communication. As a result, students’ attitudes toward English significantly influence their language learning outcomes and academic success. The study explores whether university students view English as a valuable tool for personal and professional growth or merely as an academic requirement. It also investigates the impact of globalization, media exposure, and institutional policies on shaping these attitudes. Using a quantitative research approach, data were collected through structured questionnaires administered to undergraduate students from various academic disciplines. The findings reveal that most students demonstrate a generally positive attitude toward English, associating it with career opportunities, global mobility, and access to knowledge. However, some negative attitudes persist, mainly due to anxiety, lack of confidence, and limited exposure to authentic language use. The article highlights the importance of supportive learning environments and effective teaching strategies in fostering positive language attitudes. Understanding students’ attitudes toward English can help educators and policymakers design more effective language programs that enhance motivation, reduce language anxiety, and promote successful language acquisition in higher education settings.
DOI: 10.5281/zenodo.18503673
title: LANGUAGE ATTITUDES TOWARD ENGLISH AMONG UNIVERSITY STUDENTS

description: This article examines language attitudes toward English among university students, focusing on their perceptions, motivations, and emotional responses to the language in academic and social contexts. English has become a global lingua franca, playing a crucial role in higher education, professional development, and international communication. As a result, students’ attitudes toward English significantly influence their language learning outcomes and academic success. The study explores whether university students view English as a valuable tool for personal and professional growth or merely as an academic requirement. It also investigates the impact of globalization, media exposure, and institutional policies on shaping these attitudes. Using a quantitative research approach, data were collected through structured questionnaires administered to undergraduate students from various academic disciplines. The findings reveal that most students demonstrate a generally positive attitude toward English, associating it with career opportunities, global mobility, and access to knowledge. However, some negative attitudes persist, mainly due to anxiety, lack of confidence, and limited exposure to authentic language use. The article highlights the importance of supportive learning environments and effective teaching strategies in fostering positive language attitudes. Understanding students’ attitudes toward English can help educators and policymakers design more effective language programs that enhance motivation, reduce language anxiety, and promote successful language acquisition in higher education settings.
DOI: 10.15468/dl.2pghf9
title: Occurrence Download

description: A dataset containing 4220 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (September, October, November, December, January, February)",
 "OccurrenceStatus is Present",
 "TaxonKey is Trochalopteron lineatum",
 "Year 2019-2020"
 ]
}

 The dataset includes 4220 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016078-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jjgj7j
title: Occurrence Download

description: A dataset containing 3748201 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "HasCoordinate is true",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2019",
 "Geometry POLYGON((-25.0 59.0, 45.0 59.0, 45.0 64.0, -25.0 64.0, -25.0 59.0))"
 ]
}

 The dataset includes 3748201 records from 201 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016055-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zb5efy
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eugeissona tristis",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 27 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016079-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18503677
title: Botanical Insecticide Market Accelerates as Sustainable Crop Protection Gains Global Priority

description: The global Botanical Insecticide market is witnessing strong growth within the Materials & Chemicals industry under the agrochemicals category, driven by the increasing adoption of eco-friendly and plant-based crop protection solutions. Botanical insecticides, derived from natural plant extracts such as neem, pyrethrum, and essential oils, are widely used to control pests while minimizing environmental and human health risks. According to Market Intelo, the market was valued at USD 925 million in 2024 and is projected to reach USD 1.85 billion by 2032, expanding at a CAGR of 9.1% during the forecast period from 2025 to 2032.
DOI: 10.5281/zenodo.18503678
title: Botanical Insecticide Market Accelerates as Sustainable Crop Protection Gains Global Priority

description: The global Botanical Insecticide market is witnessing strong growth within the Materials & Chemicals industry under the agrochemicals category, driven by the increasing adoption of eco-friendly and plant-based crop protection solutions. Botanical insecticides, derived from natural plant extracts such as neem, pyrethrum, and essential oils, are widely used to control pests while minimizing environmental and human health risks. According to Market Intelo, the market was valued at USD 925 million in 2024 and is projected to reach USD 1.85 billion by 2032, expanding at a CAGR of 9.1% during the forecast period from 2025 to 2032.
DOI: 10.15468/dl.k67xdb
title: Occurrence Download

description: A dataset containing 6789 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (September, October, November, December, January, February)",
 "OccurrenceStatus is Present",
 "TaxonKey is Trochalopteron lineatum",
 "Year 2021-2022"
 ]
}

 The dataset includes 6789 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016080-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nztu45
title: Occurrence Download

description: A dataset containing 4220 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Month is one of (September, October, November, December, January, February)",
 "OccurrenceStatus is Present",
 "TaxonKey is Trochalopteron lineatum",
 "Year 2019-2020"
 ]
}

 The dataset includes 4220 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016082-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mbw54b
title: Occurrence Download

description: A dataset containing 185215 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Milium effusum",
 "BasisOfRecord is one of (Human Observation, Observation, Specimen)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 185215 records from 1103 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016051-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60712/si-id257294.1
title: StrainInfo SI-ID 257294.1

description: StrainInfo dataset 257294 about a strain of Unidentified. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id257350.1
title: StrainInfo SI-ID 257350.1

description: StrainInfo dataset 257350 about a strain of Phytophthora palmivora. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id257351.1
title: StrainInfo SI-ID 257351.1

description: StrainInfo dataset 257351 about a strain of Phytophthora palmivora. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.
DOI: 10.60712/si-id257217.1
title: StrainInfo SI-ID 257217.1

description: StrainInfo dataset 257217 about a strain of Synstelium polycarpum. StrainInfo is a service developed to provide a resolution of microbial strain identifiers by storing culture collection numbers, their relations, and culture-associated data. StrainInfo is part of NFDI4Microbiota consortium.