cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.d3tekq
title: Occurrence Download

description: A dataset containing 14713 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Adinetidae, Brachionidae, Gastropodidae, Dicranophoridae, Asplanchnidae, Euchlanidae, Proalidae, Notommatidae, Philodinidae, Collothecidae, Lepadellidae, Conochilidae, Trichocercidae, Epiphanidae, Trochosphaeridae, Flosculariidae, Habrotrochidae, Hexarthridae, Ituridae, Lecanidae, Lindiidae, Mytilinidae, Trichotriidae, Microcodidae, Philodinavidae, Synchaetidae, Testudinellidae, Scaridiidae, Tetrasiphonidae, Centropagidae, Diaptomidae, Cyclopidae, Halicyclopidae, Lernaeidae, Canthocamptidae, Ameiridae, Laophontidae, Phyllognathopodidae, Miraciidae, Ergasilidae, Daphniidae, Moinidae, Bosminidae, Chydoridae, Macrothricidae, Ilyocryptidae, Neothricidae)",
 "Geometry POLYGON ((-184.327583 -34.707187, -187.698326 -33.281463, -189.31881 -33.815381, -186.336708 -37.569617, -190.740509 -41.729305, -193.888779 -44.657909, -195.358887 -46.156529, -192.10556 -47.917493, -187.955475 -45.637567, -184.267502 -42.739952, -180.087204 -38.058364, -181.541176 -36.445866, -184.327583 -34.707187))"
 ]
}

 The dataset includes 14713 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011339-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.me2szv
title: Occurrence Download

description: A dataset containing 752 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "OccurrenceStatus is Present",
 "TaxonKey is Troglodytes aedon"
 ]
}

 The dataset includes 752 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011340-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30795017
title: AI ROI Dataset: 200 B2B Deployments Analysis (2022-2025)

description: AI ROI Analysis: Evidence from 200 B2B Deployments (2022-2025)ABSTRACT :This working paper presents a comprehensive analysis of Return on Investment (ROI) from 200 AI projects deployed in French B2B companies between 2022 and 2025.Methodology & Data Provenance:Using structured data collection methods including CRM exports, quarterly interviews, and financial audits, we document the reality of AI adoption in SMEs and Mid-Market companies. * Sample: 200 deployments (Rhône-Alpes, France). * Quality Control: 30% of the dataset is cross-validated with financial audits to mitigate self-reporting bias.Key Findings (Audited Metrics): * Median ROI: +159.8% over 24 months (Conservative metric). * Mean ROI: +347% (Driven by outliers, excluded from primary benchmarks). * Success Rate: 73% (Projects reaching production with verified value). * Failure Rate: 27% (Initiatives killed or frozen). * Breakeven: 8 months median time-to-value.Conclusion:Our findings challenge the "bigger is better" assumption: projects with smaller budgets (&lt;€15K) achieved 2.1x higher ROI than large-scale deployments. We identify Human-in-the-Loop governance as the critical factor, reducing critical incidents by 4.3x.Dataset:The full anonymized dataset is publicly available on Zenodo (DOI: 10.5281/zenodo.17795133)
DOI: 10.6084/m9.figshare.30795017.v1
title: AI ROI Dataset: 200 B2B Deployments Analysis (2022-2025)

description: AI ROI Analysis: Evidence from 200 B2B Deployments (2022-2025)ABSTRACT :This working paper presents a comprehensive analysis of Return on Investment (ROI) from 200 AI projects deployed in French B2B companies between 2022 and 2025.Methodology & Data Provenance:Using structured data collection methods including CRM exports, quarterly interviews, and financial audits, we document the reality of AI adoption in SMEs and Mid-Market companies. * Sample: 200 deployments (Rhône-Alpes, France). * Quality Control: 30% of the dataset is cross-validated with financial audits to mitigate self-reporting bias.Key Findings (Audited Metrics): * Median ROI: +159.8% over 24 months (Conservative metric). * Mean ROI: +347% (Driven by outliers, excluded from primary benchmarks). * Success Rate: 73% (Projects reaching production with verified value). * Failure Rate: 27% (Initiatives killed or frozen). * Breakeven: 8 months median time-to-value.Conclusion:Our findings challenge the "bigger is better" assumption: projects with smaller budgets (&lt;€15K) achieved 2.1x higher ROI than large-scale deployments. We identify Human-in-the-Loop governance as the critical factor, reducing critical incidents by 4.3x.Dataset:The full anonymized dataset is publicly available on Zenodo (DOI: 10.5281/zenodo.17795133)
DOI: 10.15468/dl.4v7vdw
title: Occurrence Download

description: A dataset containing 80 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lasiocaryum munroi",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 80 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011341-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gus6ss
title: Occurrence Download

description: A dataset containing 47 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "OccurrenceStatus is Present",
 "TaxonKey is Conepatus chinga"
 ]
}

 The dataset includes 47 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011342-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2hb5py
title: Occurrence Download

description: A dataset containing 167 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lennoa madreporoides",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 167 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011343-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5jrymp
title: Occurrence Download

description: A dataset containing 54 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ireland",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Physeter macrocephalus"
 ]
}

 The dataset includes 54 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011345-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xsas4v
title: Occurrence Download

description: A dataset containing 11084198 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-11.57605 50.64719,-4.90426 50.64719,-4.90426 55.70482,-11.57605 55.70482,-11.57605 50.64719))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 11084198 records from 1143 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011322-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gswmrs
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Rhododendron searsiae Rehder & E.H.Wilson"
 ]
}

 The dataset includes 36 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001803-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31173704
title: Item storage reassignment problem in robotic mobile fulfillment systems under customer order characteristic fluctuations

description: This article studies the item storage reassignment problem (ISRP) in the robotic mobile fulfilment system (RMFS). As the demand pattern evolves, the item storage assignment should be adapted accordingly to avoid potential workload. Hence, the item storage reassignment becomes an indispensable process of warehouse operations. This paper proposes an Interchange-Guided Sequencing Algorithm (IGSA) that identifies the interchange dependencies between item groups and constructs the corresponding group interchange sequence. Computational experiments demonstrate the effectiveness of the proposed algorithm and further analyse when reassignment should be performed under different item varieties and warehouse capacities. E-commerce warehouses using robotic mobile fulfilment systems already rely on robots to ease picking pressure, but they still face the challenge of constantly changing customer order preferences. The closer the item storage assignment matches current order demand, the fewer pod movements are required during picking. When the original and new demand patterns differ significantly, robots may need to retrieve more pods, increasing travel distance and reducing overall system productivity. Evolving customer demand eventually renders existing storage assignments inefficient, but frequent adaptation to restore efficiency risks creating additional pod movements if not handled carefully. This study introduces a practical method for reorganising item storage by identifying which product groups should exchange their items and determining an efficient sequence for completing these exchanges. Through computational experiments, we further examine warehouses of different product varieties and storage capacities, and we offer practical recommendations on suitable timing for performing storage reassignment. Overall, this study helps practitioners reduce unnecessary pod movements and maintain high picking efficiency under changing demand conditions.
DOI: 10.6084/m9.figshare.31173704.v1
title: Item storage reassignment problem in robotic mobile fulfillment systems under customer order characteristic fluctuations

description: This article studies the item storage reassignment problem (ISRP) in the robotic mobile fulfilment system (RMFS). As the demand pattern evolves, the item storage assignment should be adapted accordingly to avoid potential workload. Hence, the item storage reassignment becomes an indispensable process of warehouse operations. This paper proposes an Interchange-Guided Sequencing Algorithm (IGSA) that identifies the interchange dependencies between item groups and constructs the corresponding group interchange sequence. Computational experiments demonstrate the effectiveness of the proposed algorithm and further analyse when reassignment should be performed under different item varieties and warehouse capacities. E-commerce warehouses using robotic mobile fulfilment systems already rely on robots to ease picking pressure, but they still face the challenge of constantly changing customer order preferences. The closer the item storage assignment matches current order demand, the fewer pod movements are required during picking. When the original and new demand patterns differ significantly, robots may need to retrieve more pods, increasing travel distance and reducing overall system productivity. Evolving customer demand eventually renders existing storage assignments inefficient, but frequent adaptation to restore efficiency risks creating additional pod movements if not handled carefully. This study introduces a practical method for reorganising item storage by identifying which product groups should exchange their items and determining an efficient sequence for completing these exchanges. Through computational experiments, we further examine warehouses of different product varieties and storage capacities, and we offer practical recommendations on suitable timing for performing storage reassignment. Overall, this study helps practitioners reduce unnecessary pod movements and maintain high picking efficiency under changing demand conditions.
DOI: 10.6084/m9.figshare.31173707
title: Bioaerosol reductions: paper pads versus wood chips in a multi-stage scrubber of a pig barn

description: A commercial three-stage scrubber of a pig barn usually used to reduce ammonia, odour and dust was investigated regarding the reduction of indicator bioaerosols (mesophilic bacteria, haemolytic streptococci, methicillin-resistant <i>Staphylococcus aureus</i>, endotoxins as well as molds and yeasts). The bio-scrubber stage (third stage), was filled half with wood chips and half with paper pads as an alternative material in order to compare the reduction rates. Air samples were taken simultaneously with emission impingers from the untreated air, downstream of the acid scrubber (second stage) and downstream of the two bio-scrubber halves (third stage). The total reduction rate of indicator bacteria was at least 93% throughout all stages. However, both materials in the bio-scrubber stage significantly reduced an additional portion of the bioaerosols and therefore contributed to the overall reduction. This applied equally for endotoxins downstream of the wood chips half. In contrast, the cultivable mold and yeast numbers were not significantly reduced and increased downstream of the wood chips. Considering the reduction of potentially pathogenic bacteria, resistant bacteria and endotoxins of approximately log<sub>10</sub>, it can be concluded that three-stage scrubbers can mitigate the risk of harmful bioaerosol emissions for residents and animals on neighbouring farms. In terms of the reduction of microorganisms, paper pads can be used as an alternative material to wood chips in the bio-scrubber stage.
DOI: 10.6084/m9.figshare.31173707.v1
title: Bioaerosol reductions: paper pads versus wood chips in a multi-stage scrubber of a pig barn

description: A commercial three-stage scrubber of a pig barn usually used to reduce ammonia, odour and dust was investigated regarding the reduction of indicator bioaerosols (mesophilic bacteria, haemolytic streptococci, methicillin-resistant <i>Staphylococcus aureus</i>, endotoxins as well as molds and yeasts). The bio-scrubber stage (third stage), was filled half with wood chips and half with paper pads as an alternative material in order to compare the reduction rates. Air samples were taken simultaneously with emission impingers from the untreated air, downstream of the acid scrubber (second stage) and downstream of the two bio-scrubber halves (third stage). The total reduction rate of indicator bacteria was at least 93% throughout all stages. However, both materials in the bio-scrubber stage significantly reduced an additional portion of the bioaerosols and therefore contributed to the overall reduction. This applied equally for endotoxins downstream of the wood chips half. In contrast, the cultivable mold and yeast numbers were not significantly reduced and increased downstream of the wood chips. Considering the reduction of potentially pathogenic bacteria, resistant bacteria and endotoxins of approximately log<sub>10</sub>, it can be concluded that three-stage scrubbers can mitigate the risk of harmful bioaerosol emissions for residents and animals on neighbouring farms. In terms of the reduction of microorganisms, paper pads can be used as an alternative material to wood chips in the bio-scrubber stage.
DOI: 10.15468/dl.v75y96
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lychnophora pseudovillosissima"
 ]
}

 The dataset includes 56 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004019-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31173712
title: Prefrontal cortex-extracellular vesicle RNAs coupling in alcohol use disorder: towards non-invasive biomarkers and targeted therapeutics

description: Alcohol use disorder (AUD) poses a substantial global health burden, with its molecular mechanism remaining elusive. This study integrated datasets (GSE253155, GSE180722, GSE182173 and GSE176122) and clinical specimens to identify non-invasive biomarkers and therapeutic candidates for AUD. Transcriptomic analysis of post-mortem prefrontal cortex identified 34 differentially expressed genes (DEGs), significantly enriched in TNF/IL-17 signalling, ribosome, cytokine-cytokine receptor interaction and endoplasmic reticulum protein processing. Among multiple machine learning algorithms, the support vector machine demonstrated superior classification performance, prioritizing <i>MDK</i>, <i>FAM225B</i> and <i>SERPINA3</i> as critical biomarkers. These were incorporated into a highly predictive diagnostic nomogram. Intersection with plasma extracellular vesicle (EV) RNAs showed that all three biomarkers were detectable and upregulated in AUD patients versus controls, which was confirmed by quantitative real-time PCR (qRT-PCR) in a clinical validation cohort. <i>SERPINA3</i> exhibited a particularly robust association with AUD, maintaining significance after adjustment for confounders and suggesting direct effects via mediation analysis. Cross-species validation confirmed a conserved dysregulation of murine Serpina3n. Computational drug repurposing identified loratadine, doxepin, citalopram and imipramine as promising therapeutic candidates targeting <i>SERPINA3</i>. Collectively, this work delineated PFC signature genes, proposed a EVs-supported brain–periphery molecular crosstalk, and provided translatable biomarkers and repurposable candidates for AUD precision medicine.
DOI: 10.6084/m9.figshare.31173712.v1
title: Prefrontal cortex-extracellular vesicle RNAs coupling in alcohol use disorder: towards non-invasive biomarkers and targeted therapeutics

description: Alcohol use disorder (AUD) poses a substantial global health burden, with its molecular mechanism remaining elusive. This study integrated datasets (GSE253155, GSE180722, GSE182173 and GSE176122) and clinical specimens to identify non-invasive biomarkers and therapeutic candidates for AUD. Transcriptomic analysis of post-mortem prefrontal cortex identified 34 differentially expressed genes (DEGs), significantly enriched in TNF/IL-17 signalling, ribosome, cytokine-cytokine receptor interaction and endoplasmic reticulum protein processing. Among multiple machine learning algorithms, the support vector machine demonstrated superior classification performance, prioritizing <i>MDK</i>, <i>FAM225B</i> and <i>SERPINA3</i> as critical biomarkers. These were incorporated into a highly predictive diagnostic nomogram. Intersection with plasma extracellular vesicle (EV) RNAs showed that all three biomarkers were detectable and upregulated in AUD patients versus controls, which was confirmed by quantitative real-time PCR (qRT-PCR) in a clinical validation cohort. <i>SERPINA3</i> exhibited a particularly robust association with AUD, maintaining significance after adjustment for confounders and suggesting direct effects via mediation analysis. Cross-species validation confirmed a conserved dysregulation of murine Serpina3n. Computational drug repurposing identified loratadine, doxepin, citalopram and imipramine as promising therapeutic candidates targeting <i>SERPINA3</i>. Collectively, this work delineated PFC signature genes, proposed a EVs-supported brain–periphery molecular crosstalk, and provided translatable biomarkers and repurposable candidates for AUD precision medicine.
DOI: 10.15468/dl.n8mw8v
title: Occurrence Download

description: A dataset containing 70 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mugil brevirostris",
 "HasCoordinate is true",
 "DecimalLatitude is greater than -90",
 "DecimalLatitude is less than 90",
 "DecimalLongitude is greater than -180",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1950",
 "Year is less than or equal to 2014"
 ]
}

 The dataset includes 70 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004021-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18059559
title: Data Dataset for "Through Thick and Thin: The Cosmic Evolution of Disk Scale Height"

description: This dataset provides measured global disk vertical scale heights, modeled with a $\mathrm{sech}^2$ profile and effectively averaging thin and thick components when present, for 2631 edge-on (q_d < 0.4) disk galaxies with stellar masses $M_* > 10^{10}\,M_\odot$ over the redshift range $0 < z < 3.5$, drawn from the JWST COSMOS-Web survey. The measurements are presented in Yu et al. (2026). The dataset also includes the correction curves associated with the method developed in Yu et al. (2026) to account for systematic overestimation of scale heights arising from deviations from a perfectly edge-on orientation.
DOI: 10.5281/zenodo.18059558
title: Data Dataset for "Through Thick and Thin: The Cosmic Evolution of Disk Scale Height"

description: This dataset provides measured global disk vertical scale heights, modeled with a $\mathrm{sech}^2$ profile and effectively averaging thin and thick components when present, for 2631 edge-on (q_d < 0.4) disk galaxies with stellar masses $M_* > 10^{10}\,M_\odot$ over the redshift range $0 < z < 3.5$, drawn from the JWST COSMOS-Web survey. The measurements are presented in Yu et al. (2026). The dataset also includes the correction curves associated with the method developed in Yu et al. (2026) to account for systematic overestimation of scale heights arising from deviations from a perfectly edge-on orientation.