cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.mabxv7
title: Occurrence Download

description: A dataset containing 1060970490 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is EOD – eBird Observation Dataset"
 ]
}

 The dataset includes 1060970490 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0243520-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xhalgi
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001359-160509122628363/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.672zad
title: Occurrence Download

description: A dataset containing 71283210 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((-100.29543 19.18669,-97.97199 -14.36852,-59.24788 -18.0859,-40.66031 -2.90306,-40.66031 17.71741,-100.29543 19.18669))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 71283210 records from 2726 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0242789-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.at37qw
title: Occurrence Download

description: A dataset containing 26547252 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Mexico"
 ]
}

 The dataset includes 26547252 records from 3763 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0237508-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34973/gqxq-m550
title: Reappraisal is less effective than distraction in downregulation of neural responses to physical threats - An event-related potential investigation

description: Evolutionary threats (ETs), such as predatory animals and heights, elicit stronger fear responses and are more often the subject of specific phobias, as compared to modern threats (MTs, such as guns and motorcycles). Since processing of ET depends on lower-order, phylogenetically conserved neural fear circuits, it may be less susceptible to higher-order (vs. simpler) cognitive emotion regulation. Given the relevance for treatment of specific phobias, we tested this hypothesis in an ERP study. Sixty-one female participants passively watched high- and low-threat pictures of evolutionary (snakes, lizards) and modern (guns, water-guns) origin, and downregulated responses to the high-threat pictures (snakes and guns) using either cognitive reappraisal or a simpler cognitive distraction strategy. ET elicited stronger early (EPN) and sustained (LPP) attention processing compared to MT. Both strategies successfully downregulated subjective and LPP (but not EPN) responses compared to passive watching. Although reappraisal was more effective subjectively, distraction downregulated the LPP earlier and stronger than reappraisal, irrespective of the threat type. These findings provide novel evidence that neural responses to physical threat might be less susceptible to cognitive emotion regulation via higher-order (reappraisal) versus simpler (distraction) strategies, irrespective of the evolutionary or modern relevance of threat. Combining both strategies could be beneficial for the emotion regulation-enhancing interventions for specific phobias. Distraction could be used during initial exposure, to reduce immediate emotion responding and help endure the contact with the feared stimulus, whereas reappraisal could be used subsequently, when emotions are less intense, to change maladaptive thoughts about the stimulus for future encounters. In this collection, you can find raw as well as preprocessed behavioural and EEG data, materials and procedures, analysis scripts, and figures visualizing the results.
DOI: 10.57702/zgx72iga
title: IP2P dataset

description: The dataset used for image editing and scene editing tasks.
DOI: 10.34973/71n3-vk61
title: How well does a spreading activation mechanism account for the auditory family size effect?

description: Words with more morphologically related words are recognized more quickly. We investigated the cognitive mechanisms underlying these family size effects in auditory word recognition, by studying how well they are accounted for by different versions of DIANA, a model of auditory word recognition. First, we found that part of the family size effects can be accounted for without incorporating morphological processing. This raises the question of what drives this part of family size effects. Second, we found that morphological processing in the form of the spreading of activation between morphologically related words does not account for auditory family size effects, at least not how we implemented this spreading. Third, we found that discriminative learning accounts somewhat better for family size effects, except for those that rely on phonological similarity. Together these results suggest that family size effects are more driven by phonological properties of the words than is commonly assumed.

This Data Sharing Collection (DSC) includes: a) DIANA-based predictions (with and without spreading activation) of reaction times (RTs) in BALDEY, b) LDL-AURIS-based predictions of reaction times (RTs) in BALDEY. c) A BALDEY dataset enriched with three different family size (FS) measures. d) Control variables used in the associated experiment. e) All necessary scripts to derive the above materials Please note that the collection does not include the CELEX or CGN databases used for computing FS measures and training the LDL-AURIS model, as we do not have the license to share them. Researchers with access to CELEX and CGN can use the provided scripts to recreate the LDL-AURIS model and FS measures. Those without access will need to use the enriched materials provided in this collection.
DOI: 10.15468/dl.bgjecb
title: Occurrence Download

description: A dataset containing 9968 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (USA.34_1, USA.41_1, USA.43_1, USA.11_1)",
 "TaxonKey is one of (Monarda didyma, Heliopsis helianthoides, Symphyotrichum laeve, Vernonia gigantea, Solidago curtisii, Verbesina virginica, Eutrochium fistulosum, Rudbeckia laciniata, Monarda fistulosa)",
 "Year 2015-2026"
 ]
}

 The dataset includes 9968 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080222-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/laapsq58
title: Efficient GAN-based Anomaly Detection

description: Efficient GAN-based anomaly detection.
DOI: 10.34973/n401-xx29
title: Urinary proteomics as a non-invasive readout of obesity-associated inflammation

description: Supplemental data accompanying the paper titled "Urinary proteomics as a non-invasive readout of obesity-associated inflammation". 

The supplemental data consists of more demographic data presented in tables. More information on the methods is also added in form of a figure. 
Furthermore, more information is provided on the analysis, as this contains the loadings of the PCA in a graph and the raw results from the WGCNA analysis.

Background:
The objective of this study was to use a non-invasive approach to determine obesity-induced inflammation by measuring the urinary proteome of individuals with and without obesity.
This was achieved by OLINK analysis of urine samples, which measured 384 inflammation associated proteins in the urine samples.
DOI: 10.34973/rsjg-a025
title: High working memory load impairs reappraisal but facilitates distraction – An event-related potential investigation

description: The present experiments investigated the impact of working memory (WM) load on emotion regulation (ER) efficacy using reappraisal (Experiment 1, n = 30) and distraction (Experiment 2, n = 30). Considering that WM is necessary for storage, elaboration, and manipulation of information and that reappraisal acts by storing, elaborating, and manipulating the stimulus meaning, we hypothesized that high (versus low) WM-load would reduce reappraisal efficacy. By contrast, given that distraction acts by blocking elaborated processing of the stimulus meaning, we expected that high WM-load would enhance distraction efficacy. To test these predictions, we employed a dual-task paradigm in which a low- or high WM-load task was combined with an ER (reappraisal or distraction) task. We measured the Late Positive Potential (LPP)–an electrocortical marker of sustained motivated attention, and a well-established index of emotional arousal–in response to negative pictures. Results confirmed that although reappraisal successfully reduced the LPP amplitude in the down- compared to up-regulation condition in low WM-load trials, high WM-load eliminated this difference, suggesting the disrupting influence of high WM-load on ER for reappraisal (Experiment 1). By contrast, although distraction failed to modulate the LPP amplitude in low WM-load trials, the difference between down- and no-regulation conditions was significant when distraction was combined with high WM-load, suggesting the facilitatory influence of high WM-load on ER for distraction (Experiment 2). Our findings show that the effect of WM-load on ER is strategy-dependent, and that the availability of WM resources is an important situational moderator of ER efficacy in healthy young adults. In this collection, you can find raw as well as preprocessed behavioural and EEG data, all materials and procedures, analysis scripts, and figures visualizing the results.
DOI: 10.57702/ju729x5y
title: Faculty Friendship Network

description: The dataset used in the paper is the faculty friendship network.
DOI: 10.57702/eq7mzlth
title: IASI dataset for surface dew point temperature estimation

description: Remote sensing data from the Infrared Atmospheric Sounding Interferometer (IASI) used for surface dew point temperature estimation.
DOI: 10.57702/v37on1g9
title: Google Trends Data

description: Google Trends data on Respiratory Syncytial Virus (RSV) and West Nile Virus (WNV) in the United States (US).
DOI: 10.57702/cv1k4u01
title: Amazon instances

description: The dataset used in this paper is the Amazon instances, which are a collection of networks representing the relationships between users and items on the Amazon website.
DOI: 10.57702/v5qdv84v
title: Class-Conditional Self-Rewarding for Text-to-Image Models

description: Self-rewarding mechanism for Text-to-Image models, using image captioning methods.
DOI: 10.5281/zenodo.18175870
title: BTC Treasury Governance & Custody Control System (Family Office Edition)

description:  

Short Description

This bundle provides a formal, audit-ready governance and decision architecture for Bitcoin treasury and custody operations, designed for family offices and similar asset-holding entities.

The artefacts define a vendor-agnostic control plane that separates decision logic from execution tooling (e.g., multi-signature wallets, MPC systems, custodians, HSMs). Core components include typed policy specifications, deterministic fail-closed decision semantics, adversarial and robustness models, an evidence-based audit schema, and a reference integration architecture.

The system is intended to be directly integrable into existing operational, risk, or custody environments via machine-readable schemas (JSON Schema, OpenAPI) and human-readable specifications. It enables verifiable separation of duties, explicit escalation and freeze logic, recovery governance, and post-incident auditability without reliance on specific vendors or software stacks.

This work is not investment advice, trading guidance, or legal/compliance advice. It is a design-level governance artefact focused on decision integrity, operational resilience, and auditability for Bitcoin-native treasury infrastructures.

Licensing Note

This bundle is published as licensable design IP.Use, modification, and internal deployment require an explicit license grant. Redistribution, resale, or inclusion in third-party products is prohibited without prior authorization. Both exclusive and non-exclusive licenses may be offered separately.
DOI: 10.5281/zenodo.18175871
title: BTC Treasury Governance & Custody Control System (Family Office Edition)

description:  

Short Description

This bundle provides a formal, audit-ready governance and decision architecture for Bitcoin treasury and custody operations, designed for family offices and similar asset-holding entities.

The artefacts define a vendor-agnostic control plane that separates decision logic from execution tooling (e.g., multi-signature wallets, MPC systems, custodians, HSMs). Core components include typed policy specifications, deterministic fail-closed decision semantics, adversarial and robustness models, an evidence-based audit schema, and a reference integration architecture.

The system is intended to be directly integrable into existing operational, risk, or custody environments via machine-readable schemas (JSON Schema, OpenAPI) and human-readable specifications. It enables verifiable separation of duties, explicit escalation and freeze logic, recovery governance, and post-incident auditability without reliance on specific vendors or software stacks.

This work is not investment advice, trading guidance, or legal/compliance advice. It is a design-level governance artefact focused on decision integrity, operational resilience, and auditability for Bitcoin-native treasury infrastructures.

Licensing Note

This bundle is published as licensable design IP.Use, modification, and internal deployment require an explicit license grant. Redistribution, resale, or inclusion in third-party products is prohibited without prior authorization. Both exclusive and non-exclusive licenses may be offered separately.
DOI: 10.57702/rdqf3ud8
title: variableInfo

description: Information on the metabolic features.
DOI: 10.57702/pjv2z44l
title: Simulated Financial Data

description: Simulated financial data with an underlying structure, including a mean-reverting time series with an Ornstein-Uhlenbeck process.
DOI: 10.57702/hkk6i3qz
title: OOD

description: Unsupervised multi-object segmentation using attention and soft-argmax
DOI: 10.57702/yvcxpwqf
title: AIOptimizer

description: AIOptimizer is a cost-optimized software performance optimisation tool. It includes a recommendation system driven by reinforcement learning to improve software system efficiency and affordability.
DOI: 10.57702/q3p9eb7r
title: Network-based detection of mobile malware exhibiting obfuscated or silent network behavior

description: Network-based detection of mobile malware exhibiting obfuscated or silent network behavior
DOI: 10.57702/cxp46iaf
title: TurboSquid

description: The dataset used in the paper for text-driven photorealistic 3D style transfer.
DOI: 10.57702/jpr8h43b
title: Parallel architectures for fuzzy triadic similarity learning

description: The dataset used in this paper for document co-clustering, which combines fuzzy sets in a three-partite graph.
DOI: 10.57702/0nfbw7vk
title: FitzHugh-Nagumo

description: The dataset is used to test the proposed tree-structured recurrent switching linear dynamical systems (TrSLDS) model.
DOI: 10.57702/5w53la99
title: DAVIS2017

description: One-shot Video Object Segmentation (VOS) is the task of pixel-wise tracking an object of interest within a video sequence, where the segmentation mask of the ﬁrst frame is given at inference time.
DOI: 10.57702/x587lll4
title: MULTIWOZ-ENTR

description: A new dataset named MULTIWOZ-ENTR, specifically designed for studying lexical entrainment (LE) in conversational systems.
DOI: 10.57702/o3rr84rn
title: VideoVista

description: VideoVista is a comprehensive video evaluation benchmark for Video-LLMs that covers both video understanding and reasoning across 27 tasks.
DOI: 10.15156/bio/sh0156560.10fu
title: SH0156560.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0156561.10fu
title: SH0156561.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0156562.10fu
title: SH0156562.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0156563.10fu
title: SH0156563.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0156564.10fu
title: SH0156564.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0156565.10fu
title: SH0156565.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.