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

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Peltocalathos baurii (Mac Owan) M.Tamura",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((27.1332 -20.158,25.5395 -23.2724,25.5395 -24.0715,30.5701 -24.0715,30.5701 -20.3186,29.6496 -19.6123,28.947 -19.4003,28.1821 -19.4609,27.6072 -19.7214,27.1332 -20.158))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050543-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.29335937
title: SRR3414636 big wig

description: Just doing omics homework
DOI: 10.6084/m9.figshare.29335937.v1
title: SRR3414636 big wig

description: Just doing omics homework
DOI: 10.5281/zenodo.15680559
title: Discovery of 82-Hz Universal Quantum Resonance - Experimental Dataset

description: This dataset contains the complete experimental evidence for the discovery of a universal 82-Hz quantum resonance frequency in superconducting quantum processors. The key finding is a single-shot (1 Hz) quantum operation exhibiting an anomalous execution time of 5,881.74 seconds (98 minutes), compared to the expected ~1 second. This suggests quantum-nuclear interactions at 15 millikelvin.

Key discoveries:- 82 Hz optimal resonance (log₁₀(82) = 1.914 ≈ |α| = 1.92)- 98-minute execution anomaly at 1 Hz- Inverse K-index correlation (K^-1.92)- Evidence of quantum fusion at absolute zero

Files included:- multiscale_experiment_20250616_153911.json - Contains the 98-minute anomaly- ihp_controlled_experimentV2.py - Discovery script- space_weather_now.json - Environmental conditions during experiments
DOI: 10.5281/zenodo.15680560
title: Discovery of 82-Hz Universal Quantum Resonance - Experimental Dataset

description: This dataset contains the complete experimental evidence for the discovery of a universal 82-Hz quantum resonance frequency in superconducting quantum processors. The key finding is a single-shot (1 Hz) quantum operation exhibiting an anomalous execution time of 5,881.74 seconds (98 minutes), compared to the expected ~1 second. This suggests quantum-nuclear interactions at 15 millikelvin.

Key discoveries:- 82 Hz optimal resonance (log₁₀(82) = 1.914 ≈ |α| = 1.92)- 98-minute execution anomaly at 1 Hz- Inverse K-index correlation (K^-1.92)- Evidence of quantum fusion at absolute zero

Files included:- multiscale_experiment_20250616_153911.json - Contains the 98-minute anomaly- ihp_controlled_experimentV2.py - Discovery script- space_weather_now.json - Environmental conditions during experiments
DOI: 10.25592/uhhfdm.12012
title: An Account on The History of Kaabu (NCAC_RDD_TAPE_0568A_B)

description: Cntinuation of TAPE_0567


 Rulers
 Civil war
 Religion 
 Kooring
 Clan names
 Resources 
 Janke Waali


<em><sup>Alternative names: Wali, Wally, Kuyateh, Sanna, Sidibeh, Bakary, Bakari, Bakery, </sup></em> <em><sup>Kebba</sup></em>
description: Published by NCAC - National Digital Archive of The Gambia, initiated by University of Hamburg, Asia-Africa-Institute, Germany, funded by Gerda Henkel Foundation, Germany
DOI: 10.25592/uhhfdm.12011
title: An Account on The History of Kaabu (NCAC_RDD_TAPE_0568A_B)

description: Cntinuation of TAPE_0567


 Rulers
 Civil war
 Religion 
 Kooring
 Clan names
 Resources 
 Janke Waali


<em><sup>Alternative names: Wali, Wally, Kuyateh, Sanna, Sidibeh, Bakary, Bakari, Bakery, </sup></em> <em><sup>Kebba</sup></em>
description: Published by NCAC - National Digital Archive of The Gambia, initiated by University of Hamburg, Asia-Africa-Institute, Germany, funded by Gerda Henkel Foundation, Germany
DOI: 10.6084/m9.figshare.29335934.v1
title: Annotated prey capture dive from a Magellanic penguin using VeSBA⁺

description: Annotated prey capture dive from a Magellanic penguin using VeSBA⁺
DOI: 10.6084/m9.figshare.29335934
title: Annotated prey capture dive from a Magellanic penguin using VeSBA⁺

description: Annotated prey capture dive from a Magellanic penguin using VeSBA⁺
DOI: 10.15468/dl.u6w9fs
title: Occurrence Download

description: A dataset containing 1063785 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Sus scrofa Linnaeus, 1758"
 ]
}

 The dataset includes 1063785 records from 2927 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050537-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.47xju3
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "DatasetKey is Canadian Museum of Nature Insect Collection",
 "Geometry POLYGON((-98.59157 48.93627,-72.56897 48.93627,-72.56897 61.07727,-98.59157 61.07727,-98.59157 48.93627))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 10 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005298-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t8a7mx
title: Occurrence Download

description: A dataset containing 66 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Uncifera acuminata Lindl."
 ]
}

 The dataset includes 66 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025273-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ek6h6j
title: Occurrence Download

description: A dataset containing 212 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Estrategia de conservación de grandes felinos en el departamento del Meta"
 ]
}

 The dataset includes 212 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001049-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mwqsnu
title: Occurrence Download

description: A dataset containing 1445 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Marsilea minuta L."
 ]
}

 The dataset includes 1445 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025278-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q7ncf7
title: Occurrence Download

description: A dataset containing 188623 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dianthus chinensis L., Dipterocarpus turbinatus C.F.Gaertn., Elettaria cardamomum (L.) Maton, Erigeron acris L., Eucommia ulmoides Oliv., Euryale ferox Salisb. ex K.D.Koenig & Sims, Fagopyrum tataricum (L.) Gaertn., Foeniculum vulgare Mill., Fraxinus chinensis Roxb., Gossypium arboreum L.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 188623 records from 1343 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016528-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.as8x64
title: Occurrence Download

description: A dataset containing 35860 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mirabilis jalapa L."
 ]
}

 The dataset includes 35860 records from 651 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003635-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gzgrkx
title: Occurrence Download

description: A dataset containing 2556 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is NEON Biorepository Terrestrial Plant Collection (Belowground Biomass [Megapit])"
 ]
}

 The dataset includes 2556 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001011-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14716608
title: The Impact of Digital Financial Literacy and Attitudes on Digital Investment Decisions

description: This study aims to analyze the effect of Digital Financial Literacy and other financial factors on making Digital Investment Decisions in Indonesia, especially in the Jakarta, Bogor, Depok, Tangerang and Bekasi (JABODETABEK) areas. By using the Structural Equation Modeling (SEM) approach with SMART-PLS 4.0 which is used as a statistical tool to test hypotheses. Questionnaires were distributed via social media from December 18, 2024 to January 2, 2025. From the questionnaire, data was obtained from 403 respondents who had used the digital investment platform. Which then, left 381 respondents after removing outliers. This study explores seven hypotheses involving seven variables: Financial Attitude (FA), Financial Behavior (FB), Financial Knowledge (FK), Financial Well-Being (FWB), Financial Confidence (FC), and Digital Investment Decision (DID). The results showed that all hypotheses tested had a significant effect.
DOI: 10.5281/zenodo.14716609
title: The Impact of Digital Financial Literacy and Attitudes on Digital Investment Decisions

description: This study aims to analyze the effect of Digital Financial Literacy and other financial factors on making Digital Investment Decisions in Indonesia, especially in the Jakarta, Bogor, Depok, Tangerang and Bekasi (JABODETABEK) areas. By using the Structural Equation Modeling (SEM) approach with SMART-PLS 4.0 which is used as a statistical tool to test hypotheses. Questionnaires were distributed via social media from December 18, 2024 to January 2, 2025. From the questionnaire, data was obtained from 403 respondents who had used the digital investment platform. Which then, left 381 respondents after removing outliers. This study explores seven hypotheses involving seven variables: Financial Attitude (FA), Financial Behavior (FB), Financial Knowledge (FK), Financial Well-Being (FWB), Financial Confidence (FC), and Digital Investment Decision (DID). The results showed that all hypotheses tested had a significant effect.
DOI: 10.15468/dl.8dcwqq
title: Occurrence Download

description: A dataset containing 2014 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Euonymus fortunei (Turcz.) Hand.-Mazz."
 ]
}

 The dataset includes 2014 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001013-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xfdk46
title: Occurrence Download

description: A dataset containing 1020 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Fosterella L.B.Sm.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1020 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001014-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14716465
title: FACS_L003_R1_001.fastq
DOI: 10.5281/zenodo.14716464
title: Hello
DOI: 10.5281/zenodo.14716547
title: Hello
DOI: 10.6084/m9.figshare.24086037
title: Deciphering molecular inputs to CRH neurons from POMC neurons

description: Classical neurophysiological studies have provided great insights into the adaptive role of stress hormones in energy homeostasis and survival-related behaviors in responses to external and internal threats. More recent viral tracing studies revealed that physically restrained activated mouse corticotropin-releasing hormone neurons (CRHNs) in the paraventricular nucleus (PVN) of the hypothalamus have direct synaptic input from proopiomelanocortin (POMC) neurons in the hypothalamic arcuate nucleus (ARC), which is known to be associated with satiety. <b>However</b>, the regularity mechanism underlying these complex neural connections remains to be fully elucidated.<b>In this study</b>, we have leveraged a bioinformatic approach to understand cell-cell communication by analyzing publicly available single-cell RNA sequencing (scRNA-seq) datasets and uncovered a dominance of glutamatergic signaling in POMC-CRHNs interactions. This was further confirmed by viral tracing experiments, indicating that restraint-activated POMC neurons primarily employ glutamatergic marker expression. Our study provides and comprehensive understanding of molecular mechanisms underpinning glutamatergic signaling in POMC-CRHNs<sup> </sup>in stress-responsive networks.<br>
DOI: 10.6084/m9.figshare.24086037.v3
title: Deciphering molecular inputs to CRH neurons from POMC neurons

description: Classical neurophysiological studies have provided great insights into the adaptive role of stress hormones in energy homeostasis and survival-related behaviors in responses to external and internal threats. More recent viral tracing studies revealed that physically restrained activated mouse corticotropin-releasing hormone neurons (CRHNs) in the paraventricular nucleus (PVN) of the hypothalamus have direct synaptic input from proopiomelanocortin (POMC) neurons in the hypothalamic arcuate nucleus (ARC), which is known to be associated with satiety. <b>However</b>, the regularity mechanism underlying these complex neural connections remains to be fully elucidated.<b>In this study</b>, we have leveraged a bioinformatic approach to understand cell-cell communication by analyzing publicly available single-cell RNA sequencing (scRNA-seq) datasets and uncovered a dominance of glutamatergic signaling in POMC-CRHNs interactions. This was further confirmed by viral tracing experiments, indicating that restraint-activated POMC neurons primarily employ glutamatergic marker expression. Our study provides and comprehensive understanding of molecular mechanisms underpinning glutamatergic signaling in POMC-CRHNs<sup> </sup>in stress-responsive networks.<br>
DOI: 10.15468/dl.c4mvx4
title: Occurrence Download

description: A dataset containing 4365 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Coptodon zillii (Gervais, 1848)"
 ]
}

 The dataset includes 4365 records from 91 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001017-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14716576
title: Deep-Drawn U-Shaped Sheet Metal Mesh Files Excerpted from NHTSA Crash Vehicles

description: This dataset contains 90 U-shaped mesh geometries that are excerpted from the NHTSA crash vehicle simulation models. The geometries undergo the following process:



Shape Filtering: Select meshes suitable for deep drawing with a U-shaped profile.

Duplicate Removal: Exclude symmetrical duplicates from vehicle structures.

Model Transformation: Orient models with drawing direction along -z, length along x, and width along y.


The meshes represent the final development state of the parts, as assembled in a car chassis. Geometries are provided in the LS-DYNA keyword file format, each accompanied by an image. Further specifications are given in the associated publication(s).

We want to thank the National Highway Traffic Safety Administration for providing the crash models and the allowance to publish a dataset.
DOI: 10.5281/zenodo.14716577
title: Deep-Drawn U-Shaped Sheet Metal Mesh Files Excerpted from NHTSA Crash Vehicles

description: This dataset contains 90 U-shaped mesh geometries that are excerpted from the NHTSA crash vehicle simulation models. The geometries undergo the following process:



Shape Filtering: Select meshes suitable for deep drawing with a U-shaped profile.

Duplicate Removal: Exclude symmetrical duplicates from vehicle structures.

Model Transformation: Orient models with drawing direction along -z, length along x, and width along y.


The meshes represent the final development state of the parts, as assembled in a car chassis. Geometries are provided in the LS-DYNA keyword file format, each accompanied by an image. Further specifications are given in the associated publication(s).

We want to thank the National Highway Traffic Safety Administration for providing the crash models and the allowance to publish a dataset.
DOI: 10.5281/zenodo.14716784
title: ILK MATEMATIK TUSHUNCHALARNI RIVOJLANTIRISHGA QARATILGAN O'YINLAR

description: Ilk matematik tushunchalarni rivojlantirishga qaratilgan o‘yinlar maktabgacha yoshdagi bolalar uchun juda muhimdir, chunki ular matematik bilimlarni o‘rganishadi. Matematik tushunchalarni o‘rgatish jarayonida o‘yinlar bolalar uchun aqliy rivojlanishni qo‘llab-quvvatlaydi, ular yoshiga mos ravishda soddalashtirilgan, qiziqarli va interaktiv tarzda matematik ko‘nikmalarni shakllantirishga yordam beradi. Masalan, raqamlar, shakllar va ranglar kabi asosiy tushunchalar bolalarga o‘yin orqali tanishtiriladi, bu ularning matematik bilimlarni qabul qilish va eslab qolishni osonlashtiradi. Ushbu maqolada o‘yinlar bolalar uchun matematik faoliyatlarni qiziqarli qilish orqali ularning motivatsiyasini oshirish  yo‘llari haqida bayon qilingan.
DOI: 10.5281/zenodo.14716785
title: ILK MATEMATIK TUSHUNCHALARNI RIVOJLANTIRISHGA QARATILGAN O'YINLAR

description: Ilk matematik tushunchalarni rivojlantirishga qaratilgan o‘yinlar maktabgacha yoshdagi bolalar uchun juda muhimdir, chunki ular matematik bilimlarni o‘rganishadi. Matematik tushunchalarni o‘rgatish jarayonida o‘yinlar bolalar uchun aqliy rivojlanishni qo‘llab-quvvatlaydi, ular yoshiga mos ravishda soddalashtirilgan, qiziqarli va interaktiv tarzda matematik ko‘nikmalarni shakllantirishga yordam beradi. Masalan, raqamlar, shakllar va ranglar kabi asosiy tushunchalar bolalarga o‘yin orqali tanishtiriladi, bu ularning matematik bilimlarni qabul qilish va eslab qolishni osonlashtiradi. Ushbu maqolada o‘yinlar bolalar uchun matematik faoliyatlarni qiziqarli qilish orqali ularning motivatsiyasini oshirish  yo‘llari haqida bayon qilingan.
DOI: 10.14473/csda/uz6wlg
title: Development and validation of Food and Nutrition Literacy Survey 2024
title: FANSY

description: The research aimed to develop and validate a general food and nutrition literacy (FNL) assessment tool, which will be used to measure the FNL in the adult population - The Food and Nutrition Literacy Survey (FANSy). To validate the tool, the preliminary version of the questionnaire was administered to representative sample of adults living in the United Kingdom. This data was used for validation and preparation of the final version of the survey.
description: Primary data from the research will be made available after the end of the SYRI project.
DOI: 10.15468/dl.6tydnb
title: Occurrence Download

description: A dataset containing 772 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Freshwater Lamprey Survey Data"
 ]
}

 The dataset includes 772 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001018-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9fsr99
title: Occurrence Download

description: A dataset containing 431 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Idesia polycarpa var. vestita Diels"
 ]
}

 The dataset includes 431 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001019-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14457/tu.the.2024.49
title: Machine learning algorithms for predicting ESG scores: evidence from the Stock Exchange of Thailand

description: This research applies machine learning algorithms to develop models for predicting sustainability ratings, focusing on both the overall Environmental, Social, and Governance (ESG) score and the individual pillar scores: environment (E score), social (S score), and governance (G score). These scores are essential for investors, regulators, and companies assessing corporate sustainability performance. The models evaluated include linear regression, decision trees, random forests, and artificial neural networks, using financial data from 2020 to 2022. Prediction accuracy was measured using the coefficient of determination (R²), mean absolute error (MAE), root mean squared error (RMSE), and mean absolute percentage error (MAPE). Among the models, the random forest model demonstrated superior performance, achieving the highest R² value of 0.47 for the overall ESG score, along with lower error rates (MAE: 0.09, RMSE: 0.12, and MAPE: 23.52%). The results also indicate that company size significantly influences the prediction of ESG scores, particularly in the environmental and social dimensions. These findings highlight the random forest model’s robust predictive capability, making it a reliable tool for ESG score assessment. This study demonstrates the potential of machine learning to improve sustainability ratings.
DOI: 10.14457/tu.the.2024.50
title: A comparative analysis of deep learning techniques for android spyware classification

description: The General Data Protection Regulation (GDPR) emphasizes safeguarding personal data globally, underscoring the need to protect sensitive information from cyber threats like spyware. Spyware covertly infiltrates devices, collecting personal details, private activities, and financial data. With smartphones as primary devices for daily activities, this research focuses on Android spyware classification to address these growing risks. This study compares spyware classification techniques using the MalNet dataset, evaluating deep learning, transfer learning, and hybrid approaches. The models CNN, CNN-BiLSTM, and ResNet152 were tested with a balanced dataset and 10-fold cross validation. ResNet152 outperformed other models with an accuracy of 0.8541, precision of 0.8940, recall of 0.8035, and an F1-score of 0.8464. By contrast, CNN achieved an accuracy of 0.5 with zero precision, recall, and F1-score while CNN-BiLSTM recorded an accuracy of 0.5, precision of 0.5, recall of 1, and an F1-score of 0.6670. These findings demonstrate ResNet152 has superior consistency and reliability to identify spyware effectively, making it a robust model for malware classification. While CNN offers simplicity and efficiency but struggles with complex patterns. CNN-BiLSTM’s high recall underscores its potential for real-world applications where minimizing missed detections of spyware is critical. This research provides a strong foundation for advancing Android spyware detection and highlights promising directions for enhancing malware classification with deep learning.