cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17506380
title: Singapore Economic Stability and Market Activity Dataset

description: The Singapore Economic Stability and Market Activity Dataset (SES-MAD) is a large-scale, real-world, high-frequency economic and financial dataset compiled from official institutional sources including the Monetary Authority of Singapore (MAS), the Singapore Exchange (SGX), and the Singapore Institute for Financial Analytics (SIFA).It provides a unified and temporally synchronized view of macroeconomic indicators, fiscal performance, financial market variables, governance metrics, and sentiment indices, enabling advanced research in economic forecasting, macro-financial stability assessment, and policy modeling.

The dataset covers the period from February 2022 to July 2025, recorded at 15-minute intervals, capturing short-term fluctuations and long-horizon economic cycles in Singapore’s economy.It integrates over 70 quantitative and qualitative indicators across seven major thematic domains: macroeconomics, finance, trade, fiscal policy, governance, global spillover, and sentiment analytics.All records are aligned to a unified temporal grid to facilitate time-series modeling, econometric analysis, and AI-based forecasting.

The dataset supports both regression-based forecasting (e.g., GDP growth, inflation, financial stability index) and multi-class classification (e.g., economic stability states: Stable, Vulnerable, Crisis).It has been utilized in the Q-MultiScaleTransNet study for quantum-enhanced multiscale forecasting and is suitable for broader applications in AI-driven macroeconomic research, market surveillance, and risk prediction.

 

Dataset Summary





Temporal Resolution: 15-minute intervals




Coverage Period: February 2022 – July 2025




Records: ≈ 1.27 million




Variables: 70 + economic, financial, and policy indicators




Targets:





GDP_Growth_Forecast




Inflation_Forecast




Financial_Stability_Index




Stability_Risk_Class (0 = Stable, 1 = Vulnerable, 2 = Crisis)
DOI: 10.5281/zenodo.17506381
title: Singapore Economic Stability and Market Activity Dataset

description: The Singapore Economic Stability and Market Activity Dataset (SES-MAD) is a large-scale, real-world, high-frequency economic and financial dataset compiled from official institutional sources including the Monetary Authority of Singapore (MAS), the Singapore Exchange (SGX), and the Singapore Institute for Financial Analytics (SIFA).It provides a unified and temporally synchronized view of macroeconomic indicators, fiscal performance, financial market variables, governance metrics, and sentiment indices, enabling advanced research in economic forecasting, macro-financial stability assessment, and policy modeling.

The dataset covers the period from February 2022 to July 2025, recorded at 15-minute intervals, capturing short-term fluctuations and long-horizon economic cycles in Singapore’s economy.It integrates over 70 quantitative and qualitative indicators across seven major thematic domains: macroeconomics, finance, trade, fiscal policy, governance, global spillover, and sentiment analytics.All records are aligned to a unified temporal grid to facilitate time-series modeling, econometric analysis, and AI-based forecasting.

The dataset supports both regression-based forecasting (e.g., GDP growth, inflation, financial stability index) and multi-class classification (e.g., economic stability states: Stable, Vulnerable, Crisis).It has been utilized in the Q-MultiScaleTransNet study for quantum-enhanced multiscale forecasting and is suitable for broader applications in AI-driven macroeconomic research, market surveillance, and risk prediction.

 

Dataset Summary





Temporal Resolution: 15-minute intervals




Coverage Period: February 2022 – July 2025




Records: ≈ 1.27 million




Variables: 70 + economic, financial, and policy indicators




Targets:





GDP_Growth_Forecast




Inflation_Forecast




Financial_Stability_Index




Stability_Risk_Class (0 = Stable, 1 = Vulnerable, 2 = Crisis)
DOI: 10.5281/zenodo.17506397
title: Dataset for Article Transforming Academic Geometry Knowledge into Knowledge for Teaching: Examining Didactic Transposition Among In-Service Teachers in Distance Education
DOI: 10.5281/zenodo.17506398
title: Dataset for Article Transforming Academic Geometry Knowledge into Knowledge for Teaching: Examining Didactic Transposition Among In-Service Teachers in Distance Education
DOI: 10.13140/rg.2.2.23241.20327
title: DATA del artículo: Predicting hotel guest satisfaction using TripAdvisor ratings and the PLS-SEM method
DOI: 10.34740/kaggle/dsv/13586505
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.5281/zenodo.17417209
title: BASEPROD-UAV

description: This dataset comprises drone images recorded in Bardenas Reales, Spain, which were used to create the high-resolution map published in BASEPROD: The Bardenas Reales Semi-Desert Planetary Rover Dataset (2024). We also include a slightly lower resolution PNG of the map at 5 cm/px in this dataset for reference.
DOI: 10.5281/zenodo.17417210
title: BASEPROD-UAV

description: This dataset comprises drone images recorded in Bardenas Reales, Spain, which were used to create the high-resolution map published in BASEPROD: The Bardenas Reales Semi-Desert Planetary Rover Dataset (2024). We also include a slightly lower resolution PNG of the map at 5 cm/px in this dataset for reference.
DOI: 10.21227/8g8j-gr34
title: "Gait dataset with Objective and Subjective Interferences (GOSI)"

description: "The GOSI dataset is an indoor gait corpus collected from 160 pedestrians to enable rigorous evaluation of methods under objective and subjective interferences. Data were acquired with four ORBBEC cameras positioned at 0\u00b0, 30\u00b0, 60\u00b0, and 90\u00b0, with camera heights from 1.9 to 2.3 meters to emulate typical surveillance viewpoints. The collection introduces objective variability from lighting, clothing, and camera height, together with subjective behaviors such as holding a hat or keeping the arms crossed. Walking conditions are organized into normal walking, walking with a hat, and an overlong coat with arms crossed. For every participant two sequences are recorded for each condition across all views, yielding 24 sequences per individual and supporting systematic analysis of cross view robustness and interference tolerance."
DOI: 10.5281/zenodo.17506430
title: Davini Crystalline Equation & Foundational Intelligence Integration — Post-Validation Human-AI Record

description: This restricted dataset documents the full empirical foundation of the Davini Zero-Contradiction Framework through its post-validation expansion, the Crystalline Equation (CE) and Davini Foundational Intelligence (DFI).

It includes the complete experimental series (Phases 1–20) validating universal equilibrium behavior (ZC* ≈ 0.64) across physical, biological, cognitive, and computational domains, together with the LaTeX manuscript The Human Record — Birth of the Crystalline Equation describing the integration of DFI and ZC into the crystallization threshold.

All materials are filed as appendices to USPTO Provisional Application #63/895,977, Davini Zero-Contradiction Law™: Universal Equilibrium Framework for Coherence Detection Across Analytic, Physical, and Cognitive Systems.

Derived from → https://doi.org/10.5281/zenodo.17390267

 
description: This archive contains the authoritative research record supporting the Crystallization Equation and DFI integration.

All data remain under intellectual-property protection (USPTO #63/895,977).

For research replication or licensing inquiries, contact angelina@theoriginsai.com
DOI: 10.15468/dl.379zs2
title: Occurrence Download

description: A dataset containing 392 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hydrocera triflora"
 ]
}

 The dataset includes 392 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011531-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17506454
title: 15000 and 90000 images dataset and training model
DOI: 10.5281/zenodo.17506453
title: 15000 and 90000 images dataset and training model
DOI: 10.5281/zenodo.16738930
title: PHI-base: the Pathogen-Host Interactions Database, version 5.1

description: ⚠️ This release is outdated. The latest release is available at: doi:10.5281/zenodo.10722192

The Pathogen–Host Interactions Database (PHI-base) is an online database that catalogues experimentally-verified pathogenicity, virulence and effector genes from fungal, oomycete, and bacterial pathogens, which infect animal, plant, fungal, and insect hosts. PHI-base is a valuable resource in the discovery of genes in medically and agronomically important pathogens, which may be potential targets for chemical intervention.

Information in PHI-base is manually curated by domain experts and is supported by strong experimental evidence (for example, gene disruption and gene complementation experiments), as well as references to the literature in which the original experiments are described. Annotations are made using terms from ontologies and controlled vocabularies, including the Gene Ontology (GO), Brenda Tissue Ontology (BTO), and the Pathogen–Host Interaction Phenotype Ontology (PHIPO).

PHI-base 5 includes data that was curated using a new curation process described in Cuzick et. al (2023). Data releases for PHI-base 5 do not use the same schema as data releases from PHI-base 4, but all data records from PHI-base 4 that can be made compatible with the new schema are included with this release. Data releases from PHI-base 4 and PHI-base 5 will occur in parallel until such time that all data from PHI-base 4 can be migrated to PHI-base 5. The PHI-base 4 data releases are available on Zenodo at https://zenodo.org/doi/10.5281/zenodo.5356870.

For more information about the planned transition from PHI-base 4 to PHI-base 5, see the Help and Announcements page on the PHI-base 5 website.

Release statistics

This version of the PHI-base 5 dataset contains the following types of information:




Data type
Count




Genes
9457


Interactions
31094


Pathogen species
303


Host species
237


Diseases
343


References
5202


Annotations
 


Pathogen-host interaction phenotype
18260


Gene-for-gene phenotype
452


Pathogen phenotype
9413


Host phenotype
14


GO biological process
1453


GO cellular component
85


GO molecular function
152


Post-translational modification
6


Physical interaction
53


WT RNA expression
36


WT protein expression
2




File contents





phi-base_v5.1.xlsx: the PHI-base dataset as an Excel spreadsheet. This format follows the layout of the PHI-base 5 website, with sheets corresponding to the sections of gene pages on the website. This format is designed for use by non-technical users.




phi-base_v5.1.json: the PHI-base dataset in JSON format. This is modelled on the export format used by PHI-Canto, the curation tool used by PHI-base. This format is primarily intended for programmatic usage and has additional information (e.g. metadata for curation sessions) that is not included in the spreadsheet format.




phi-base.schema.json: a JSON Schema file for the JSON format of the dataset. This is included as documentation for the fields in the JSON file, but can also be used to validate the dataset.
DOI: 10.15468/dl.4qrsnb
title: Occurrence Download

description: A dataset containing 392 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hydrocera triflora"
 ]
}

 The dataset includes 392 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011535-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17502540
title: Dataset Analysis of Self-Service Telecommunication Mobile Application User Satisfaction Using SERVPERF Model
DOI: 10.5281/zenodo.17502541
title: Dataset Analysis of Self-Service Telecommunication Mobile Application User Satisfaction Using SERVPERF Model
DOI: 10.5281/zenodo.17506544
title: DAFbind
DOI: 10.5281/zenodo.17506545
title: DAFbind
DOI: 10.15468/dl.6pezga
title: Occurrence Download

description: A dataset containing 49971 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Costa Rica",
 "DatasetKey is EOD – eBird Observation Dataset",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is December",
 "OccurrenceStatus is Present",
 "StateProvince is Heredia",
 "Year 2024-2024"
 ]
}

 The dataset includes 49971 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011537-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17617/3.jguuop
title: Hemispheric Synoptic Patterns Control Rainfall and Long-Range Aerosol Transport in the Amazon

description: The transatlantic transport of dust and smoke aerosols from Africa to South America is a large-scale, year-round process that affects atmospheric and nutrient cycling in the Amazon rainforest. We analyze daily variations in black carbon at the Amazon Tall Tower Observatory (ATTO) to investigate how Atlantic synoptic-scale meteorology influences its long-range transport. Black carbon fluctuations during the Amazon wet season were not fully explained by air mass trajectory length or direction. Instead, regional scale rainfall emerged as the key driver of shifts between clean and polluted days at ATTO. Rainfall maxima along trajectories preceded clean days, indicating effective wet scavenging. Composite analysis linked these rain events to synoptic systems like U.S. cold air outbreaks and South Atlantic high-pressure anomalies, which enhance moisture convergence and rainfall, promoting aerosol removal. Climate-driven shifts in tropical Atlantic circulation could alter aerosol and nutrient transport to the Amazon, with unknown impacts on rainforest productivity and resilience.
description: scripts to produce the results
DOI: 10.21227/1hk8-2306
title: "Trending HD Clips Online | XBadWap"

description: "free porn video"
DOI: 10.15468/dl.ymhm3w
title: Occurrence Download

description: A dataset containing 2577 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leopardus wiedii"
 ]
}

 The dataset includes 2577 records from 230 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011538-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gggf5u
title: Occurrence Download

description: A dataset containing 6650 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((36.1296 -14.46285,35.83917 -15.13675,35.80044 -16.18077,35.83917 -16.97872,36.65237 -17.2008,37.42685 -16.8861,37.81409 -15.75263,38.24006 -14.98718,38.6273 -14.25652,38.54985 -13.57996,37.85282 -13.31632,37.29132 -13.12783,36.5362 -13.37284,36.1296 -14.46285))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 6650 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011539-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48512/xcv8517581
title: Index of 1055-1056 Excavation Drawings

description: This excel file indexes the types and excavations with drawings for mounds 1055 and 1056. The drawings are in separate files according to their mound and excavation unit(s).
DOI: 10.13140/rg.2.2.25233.49765
title: Pseudoelastic behavior of a NiTi shape memory alloy
DOI: 10.15468/dl.6kvwed
title: Occurrence Download

description: A dataset containing 6650 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((36.1296 -14.46285,35.83917 -15.13675,35.80044 -16.18077,35.83917 -16.97872,36.65237 -17.2008,37.42685 -16.8861,37.81409 -15.75263,38.24006 -14.98718,38.6273 -14.25652,38.54985 -13.57996,37.85282 -13.31632,37.29132 -13.12783,36.5362 -13.37284,36.1296 -14.46285))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 6650 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011541-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13586760
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.17506536
title: The Role of microRNAs in Cardiac Hypertrophy and Progression to Heart Failure

description: microRNAs (miRNAs) are small noncoding RNAs that regulate gene expression post-transcriptionally and play central roles in cardiac development, hypertrophy, fibrosis, apoptosis and remodelling. Evidence from animal models, human tissue and circulating biomarker studies implicates several cardiac-enriched and stress-regulated miRNAs (notably miR-21, miR-1, miR-133, miR-208 and the miR-132/212 cluster) in the pathogenesis of pathological hypertrophy and the transition to symptomatic heart failure (HF). Translational efforts include circulating miRNA biomarker studies and antisense oligonucleotide therapies (e.g., CDR132L targeting miR-132) that have advanced into early clinical trials. Despite promise, challenges remain for clinical application: tissue delivery, off-target effects, specificity of circulating signatures, and standardised assays. Continued mechanistic work and carefully designed clinical trials are required to validate miRNA-based diagnostics and therapeutics.
DOI: 10.5281/zenodo.17506537
title: The Role of microRNAs in Cardiac Hypertrophy and Progression to Heart Failure

description: microRNAs (miRNAs) are small noncoding RNAs that regulate gene expression post-transcriptionally and play central roles in cardiac development, hypertrophy, fibrosis, apoptosis and remodelling. Evidence from animal models, human tissue and circulating biomarker studies implicates several cardiac-enriched and stress-regulated miRNAs (notably miR-21, miR-1, miR-133, miR-208 and the miR-132/212 cluster) in the pathogenesis of pathological hypertrophy and the transition to symptomatic heart failure (HF). Translational efforts include circulating miRNA biomarker studies and antisense oligonucleotide therapies (e.g., CDR132L targeting miR-132) that have advanced into early clinical trials. Despite promise, challenges remain for clinical application: tissue delivery, off-target effects, specificity of circulating signatures, and standardised assays. Continued mechanistic work and carefully designed clinical trials are required to validate miRNA-based diagnostics and therapeutics.
DOI: 10.15468/dl.72de5w
title: Occurrence Download

description: A dataset listing the 2 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Two novel hyphomycetes associated with ferns from China"
 ]
}

 The dataset's 2 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011540-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17116150
title: Learned Free-Energy Functionals from Pair-Correlation Matching for Dynamical Density Functional Theory

description: Dynamical density data from Brownian dynamics (BD) and our neural DDFT simulations. Code can be found at https://github.com/karnikram/neural-ddft-pcm.Abstract: Classical density functional theory (cDFT) and dynamical density functional theory (DDFT) are modern statistical mechanical theories for modeling many-body colloidal systems at the one-body density level. The theories hinge on knowing the excess free-energy accurately, which is however not feasible for most practical applications. Dijkman et al. [Phys. Rev. Lett. 134, 056103 (2025)] recently showed how a neural excess free-energy functional for cDFT can be learned from bulk simulations via pair-correlation matching. In this article, we demonstrate how this same functional can be applied to DDFT, without any retraining, to simulate non-equilibrium overdamped dynamics of inhomogeneous densities. We evaluate this on a 3D Lennard-Jones system with planar geometry under various complex external potentials and observe good agreement of the dynamical densities with those from expensive Brownian dynamic simulations, up to the limit of the adiabatic approximation. We further develop and apply an extension of DDFT based on gradient flows, to a grand-canonical system modeled after breakthrough gas adsorption studies, finding similarly good agreement. Our results demonstrate a practical route for leveraging learned free-energy functionals in DDFT, paving the way for accurate and efficient modeling of many-body non-equilibrium systems.

Authors: Karnik Ram, Jacobus Dijkman, René van Roij, Jan-Willem van de Meent, Bernd Ensing, Max Welling and Daniel Cremers

Phys. Rev. E DOI: https://doi.org/10.1103/22fd-ykkbarXiv: https://arxiv.org/abs/2505.09543
DOI: 10.5281/zenodo.17440711
title: GAME-ER Documentary Material for Task 4.2

description: This dataset is composed of multiple spreadsheets with documentary data covering the video game clusters researched by the Horizon Porject GAME-ER. The documents were collected for Task 4.2 of the project. The data cover documentary evidence for the clusters od Dundee, Brno, Turin. GAME-ER is a 36-month research project funded by HORIZON Europe and UKRI, dedicated to understanding the unique dynamics of local and regional video game clusters. We aim to provide policymakers and decision-makers with the knowledge and tools needed to foster thriving video game clusters. Project Website: https://www.game-er.eu/ 

GA: Grant agreement ID: 101132585

Project on Cordis: https://cordis.europa.eu/project/id/101132585
DOI: 10.5281/zenodo.17440712
title: GAME-ER Documentary Material for Task 4.2

description: This dataset is composed of multiple spreadsheets with documentary data covering the video game clusters researched by the Horizon Porject GAME-ER. The documents were collected for Task 4.2 of the project. The data cover documentary evidence for the clusters od Dundee, Brno, Turin. GAME-ER is a 36-month research project funded by HORIZON Europe and UKRI, dedicated to understanding the unique dynamics of local and regional video game clusters. We aim to provide policymakers and decision-makers with the knowledge and tools needed to foster thriving video game clusters. Project Website: https://www.game-er.eu/ 

GA: Grant agreement ID: 101132585

Project on Cordis: https://cordis.europa.eu/project/id/101132585
DOI: 10.5281/zenodo.17506640
title: Daten der Notaufnahmesurveillance

description: Der Datensatz "Daten der Notaufnahmesurveillance" wird durch das Robert Koch-Institut und das AKTIN-Notaufnahmeregister bei Krankenhausaufnahmen bereitgestellt. Der Datensatz beinhaltet aggregierte Routinedaten aus deutschen Notaufnahmen zur syndromischen Überwachung von akuten Erkrankungen. Dazu zählen grippeähnliche Erkrankungen (ILI), Coronavirus-Erkrankungen (COVID-19), akute respiratorische Erkrankungen (ARE), gastrointestinale Infektionen (GI) und schwere akute respiratorische Infektionen (SARI). Dabei wird der relative Anteil dieser Erkrankungen an der Gesamtzahl der Notaufnahmevorstellungen sowie die berechneten Erwartungswerte und Prädiktionsintervalle ausgewiesen. Die Daten sind nach Notaufnahmetypen und Altersgruppen aggregiert. Damit bietet der Datensatz eine wertvolle Ressource für die Forschung im Bereich der Notfallmedizin und der Überwachung akuter Gesundheitsereignisse in Deutschland.