cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/gb5r92cp3d.1
title: Data set of Bariatric surgeries - Sleeve gastrectomy and OAGB - short term complications analysis

description: Data set of Bariatric surgeries - Sleeve gastrectomy and OAGB - short term complications analysis
DOI: 10.17632/hn84wp556f
title: LINF_270016800

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/hn84wp556f.1
title: LINF_270016800

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/82b4cp5nfj
title: LINF_270017300

description: EXPERA domain-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/82b4cp5nfj.1
title: LINF_270017300

description: EXPERA domain-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/hp72rn3x5z
title: LINF_270017600

description: TSR2-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/hp72rn3x5z.1
title: LINF_270017600

description: TSR2-like protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/6y96dnhpzp
title: LINF_270018000

description: Armadillo-type fold-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/6y96dnhpzp.1
title: LINF_270018000

description: Armadillo-type fold-containing protein; Leishmania infantum (strain JPCM5)
DOI: 10.17632/mzk6ymf8fj
title: Exogenous melatonin alleviates heat stress-induced metabolic slowdown affecting broiler growth by improving lipid metabolism
DOI: 10.17632/mzk6ymf8fj.1
title: Exogenous melatonin alleviates heat stress-induced metabolic slowdown affecting broiler growth by improving lipid metabolism
DOI: 10.34740/kaggle/dsv/13070666
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.17632/jbz48r9ybf
title: Seasonal and interannual dynamics of Weddell seal ecology in East Antarctica: influences of sea ice and topography

description: In this study, we tried to:
i) provide a detailed description of the foraging ecology of the Dumont d'Urville Weddell seal population, describing their distribution throughout the year and the seasonal and circadian dive cycles in relation to key physical parameters of their habitat;
ii) examine the potential interannual variability in their diving and foraging behaviour and its relationship with landfast ice dynamics;
iii) investigate the link with fish distribution in the area, for known Weddell seals’ prey.

Three types of data are available in this dataset: 
i) Conductivity Temperature Depth Satellite Relayed Data Loggers (CTD-SRDLs) were deployed on Weddell seals in Terre Adélie (East Antarctica) at Dumont d'Urville Station (−66.66◦, 140.00◦) between 2066 and 2024, to study animals’ movements and dives. The tags transmit information on their behaviour and location using the Argos satellite system. The data presented here includes the raw data transmitted by the tag, and the filtered data for analysis. 
ii) In February 2006 and 2007, 33 high-definition video surveys were performed at the Pierre Lejay Bay, around the Dumont d’Urville station using a remotely operated vehicle (ROV). The data presented here include all fish data observed on the ROV footage (number of individuals per hour per ROV station), and summarised data for Weddell seals prey species.
iii) Antarctic landfast ice data were obtained from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellite visible and thermal infrared imagery with a spatial resolution of 1 km and a fifteen-day time stamp. Prior to March 2018, landfast ice data were taken from the dataset of Fraser et al. (2020, Earth Syst. Sci. Data, doi: 10.5194/essd-12-2987-2020). After March 2018, landfast ice maps were produced ad hoc for the Dumont d'Urville region using individual cloud-free MODIS visible and thermal infrared imagery.

Weddell seals exhibited benthic, epibenthic, and pelagic dive patterns. Dive behaviour varied among years with no consistent inter-annual trends. Typical seasonal cycle in foraging behaviour was observed, with deeper dives and shorter hunting times in the autumn than during the winter. The foraging range this population is more restricted than that of other populations. They foraged within 50 km of Dumont d’Urville station (75% of locations). Most used areas featured shallow depths (&lt;190 m) and steeper slopes (&gt;3°), likely associated with canyon edges. As landfast ice formed in April, dive locations were concentrated near Dumont d’Urville. Fish were more abundant near canyons, dominated by Nothotenioidei (99.9%), mainly Trematomus newnesi, with Pleuragramma antarcticum larvae along canyon edges. Seal dive patterns aligned with fish distributions, with spatial and vertical overlap.

Further details on the data are presented in the ReadMe file.
DOI: 10.17632/jbz48r9ybf.1
title: Seasonal and interannual dynamics of Weddell seal ecology in East Antarctica: influences of sea ice and topography

description: In this study, we tried to:
i) provide a detailed description of the foraging ecology of the Dumont d'Urville Weddell seal population, describing their distribution throughout the year and the seasonal and circadian dive cycles in relation to key physical parameters of their habitat;
ii) examine the potential interannual variability in their diving and foraging behaviour and its relationship with landfast ice dynamics;
iii) investigate the link with fish distribution in the area, for known Weddell seals’ prey.

Three types of data are available in this dataset: 
i) Conductivity Temperature Depth Satellite Relayed Data Loggers (CTD-SRDLs) were deployed on Weddell seals in Terre Adélie (East Antarctica) at Dumont d'Urville Station (−66.66◦, 140.00◦) between 2066 and 2024, to study animals’ movements and dives. The tags transmit information on their behaviour and location using the Argos satellite system. The data presented here includes the raw data transmitted by the tag, and the filtered data for analysis. 
ii) In February 2006 and 2007, 33 high-definition video surveys were performed at the Pierre Lejay Bay, around the Dumont d’Urville station using a remotely operated vehicle (ROV). The data presented here include all fish data observed on the ROV footage (number of individuals per hour per ROV station), and summarised data for Weddell seals prey species.
iii) Antarctic landfast ice data were obtained from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellite visible and thermal infrared imagery with a spatial resolution of 1 km and a fifteen-day time stamp. Prior to March 2018, landfast ice data were taken from the dataset of Fraser et al. (2020, Earth Syst. Sci. Data, doi: 10.5194/essd-12-2987-2020). After March 2018, landfast ice maps were produced ad hoc for the Dumont d'Urville region using individual cloud-free MODIS visible and thermal infrared imagery.

Weddell seals exhibited benthic, epibenthic, and pelagic dive patterns. Dive behaviour varied among years with no consistent inter-annual trends. Typical seasonal cycle in foraging behaviour was observed, with deeper dives and shorter hunting times in the autumn than during the winter. The foraging range this population is more restricted than that of other populations. They foraged within 50 km of Dumont d’Urville station (75% of locations). Most used areas featured shallow depths (&lt;190 m) and steeper slopes (&gt;3°), likely associated with canyon edges. As landfast ice formed in April, dive locations were concentrated near Dumont d’Urville. Fish were more abundant near canyons, dominated by Nothotenioidei (99.9%), mainly Trematomus newnesi, with Pleuragramma antarcticum larvae along canyon edges. Seal dive patterns aligned with fish distributions, with spatial and vertical overlap.

Further details on the data are presented in the ReadMe file.
DOI: 10.15468/dl.vvqd5t
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is New Zealand forest-dwelling skinks of the Oligosoma oliveri (McCann) species-complex (Reptilia: Scincidae): reinstatement of O. pachysomaticum (Robb) and an assessment of historical distribution ranges"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004759-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vpzk3v
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Micropterus dolomieu",
 "Country is Mauritius",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004760-250914085247600/datasets/export for details.
DOI: 10.17632/d255x2pnvz
title: Supplementary material for “Multiscale modeling and swelling behaviors of Wyoming sodium montmorillonite systems”

description: Supplementary material for “Multiscale modeling and swelling behaviors of Wyoming sodium montmorillonite systems” (Marked version)
DOI: 10.15468/dl.tj9stj
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Micropterus dolomieu",
 "Country is Sweden",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004762-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n49xxw
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A new species of Liolaemus (Reptilia: Squamata) of the Liolaemus capillitas clade (Squamata, Liolaemini, Liolaemus elongatus-kriegi group) from Sierra de Velasco La Rioja Province, Argentina"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004761-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/d255x2pnvz.1
title: Supplementary material for “Multiscale modeling and swelling behaviors of Wyoming sodium montmorillonite systems”

description: Supplementary material for “Multiscale modeling and swelling behaviors of Wyoming sodium montmorillonite systems” (Marked version)
DOI: 10.15468/dl.y6jnnh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Micropterus dolomieu",
 "Country is Tanzania, United Republic of",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004763-250914085247600/datasets/export for details.
DOI: 10.15468/dl.8ka2s2
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Determinación de la clase Reptilia presente en el corregimiento de Juanchaco, Valle del Cauca, Colombia para el mes de Septiembre de 2017"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004764-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/gtpjw4jj5j
title: Supplementary material for “Multiscale modeling and swelling behaviors of Wyoming sodium montmorillonite systems”

description: Supplementary material for “Multiscale modeling and swelling behaviors of Wyoming sodium montmorillonite systems” (Clean version)
DOI: 10.17632/gtpjw4jj5j.1
title: Supplementary material for “Multiscale modeling and swelling behaviors of Wyoming sodium montmorillonite systems”

description: Supplementary material for “Multiscale modeling and swelling behaviors of Wyoming sodium montmorillonite systems” (Clean version)
DOI: 10.17632/fjm32x36h5
title: Monte Carlo Simulation Data
DOI: 10.17632/fjm32x36h5.1
title: Monte Carlo Simulation Data
DOI: 10.17632/42bcyncfhy.1
title: Image Dataset of Red and White Onion Bulbs and Leaves

description: This dataset provides a structured collection of 24,000 images of red and white onion (Allium cepa L.) bulbs and leaves, developed to facilitate research in agriculture, computer vision, and machine learning. Bulb images are organized into red onion and white onion categories, which are further divided into healthy and unhealthy groups, and sub-categorized into single and multiple bulb samples. The dataset also includes pure red onion, pure white onion, and mixed samples (e.g., 1WO9RO indicates 1 White Onion and 9 Red Onions), enabling both variety identification and mixed-sample recognition. Leaf images are classified into healthy, unhealthy, single-leaf, and multiple-leaf categories, making the dataset suitable for plant health assessment and phenotyping tasks. All images have been standardized to a uniform resolution of 1024 × 720 pixels using IrfanView software, with serial numbering applied for traceability. The dataset provides only raw images, allowing users to perform their own augmentation and preprocessing.
DOI: 10.17632/szjvcpy7g2
title: Land-use change simplifies microbiome networks ahead of diversity shifts in river sandbar soils

description: Bacterial functional groups were classified based on their roles in carbon (C), nitrogen (N), sulfur (S), and iron (Fe) cycling. While fungal trophic modes were categorized into symbiotrophs and pathotrophs .
DOI: 10.17632/szjvcpy7g2.1
title: Land-use change simplifies microbiome networks ahead of diversity shifts in river sandbar soils

description: Bacterial functional groups were classified based on their roles in carbon (C), nitrogen (N), sulfur (S), and iron (Fe) cycling. While fungal trophic modes were categorized into symbiotrophs and pathotrophs .
DOI: 10.17632/vz3tmrkj4t
title: Data for "Particle retention triggered by trace amounts of polymers in 'clean' water"

description: Original data for the manuscript "Particle retention triggered by trace amounts of polymers in 'clean' water"
DOI: 10.17632/vz3tmrkj4t.1
title: Data for "Particle retention triggered by trace amounts of polymers in 'clean' water"

description: Original data for the manuscript "Particle retention triggered by trace amounts of polymers in 'clean' water"
DOI: 10.17632/2nbd2hhdwy
title: From intention to informed practice: Data from an experimental study of hands-on training effects on teachers’ mobile learning acceptance

description: Anonymized dataset from an experimental pre/post study on teachers’ acceptance of an adaptive, collaborative and free mobile learning application (Artefac). 

A total of 114 teachers in France were randomly assigned to a hands-on training group (experimental) or an unrelated training group (control). 

Measures were collected before and after the intervention for five Technology Acceptance Model (TAM) dimensions: perceived usefulness for teaching (PUFT), perceived usefulness for students (PUFS), perceived ease of use (PEOU), perceived enjoyment (PE), and intention to use (IU). Additional variables include: group (control/training), status (pre-service/in-service), school level (primary/secondary), priority context (yes/no), gender, age (years), and frequency of digital tool use (1–6 Likert). TAM items are on 1–5 Likert scales; missing values are empty cells.

All direct identifiers were removed. Variables not used in the article and potentially re-identifying (e.g., subject area, year of examination, classes) were excluded. This dataset enables reproduction of the descriptive and inferential analyses reported in the article. See README for file structure and the codebook for detailed variable definitions and coding.
DOI: 10.17632/2nbd2hhdwy.1
title: From intention to informed practice: Data from an experimental study of hands-on training effects on teachers’ mobile learning acceptance

description: Anonymized dataset from an experimental pre/post study on teachers’ acceptance of an adaptive, collaborative and free mobile learning application (Artefac). 

A total of 114 teachers in France were randomly assigned to a hands-on training group (experimental) or an unrelated training group (control). 

Measures were collected before and after the intervention for five Technology Acceptance Model (TAM) dimensions: perceived usefulness for teaching (PUFT), perceived usefulness for students (PUFS), perceived ease of use (PEOU), perceived enjoyment (PE), and intention to use (IU). Additional variables include: group (control/training), status (pre-service/in-service), school level (primary/secondary), priority context (yes/no), gender, age (years), and frequency of digital tool use (1–6 Likert). TAM items are on 1–5 Likert scales; missing values are empty cells.

All direct identifiers were removed. Variables not used in the article and potentially re-identifying (e.g., subject area, year of examination, classes) were excluded. This dataset enables reproduction of the descriptive and inferential analyses reported in the article. See README for file structure and the codebook for detailed variable definitions and coding.
DOI: 10.17632/hbm96hmdry.1
title: Replication Package for "Bank Consolidation and Uniform Pricing"

description: This replication package accompanies the paper Bank Consolidation and Uniform Pricing. The analysis uses both publicly available datasets and proprietary RateWatch data.
DOI: 10.17632/d3n3mgjjbv
title: MH-Weed16:An Indian Multiclass Annotated Weed Dataset for Computer Vision Tasks

description: Weeds are invasive plants that compete with crops for vital nutrients and often attract pests, significantly impacting agricultural productivity. They account for approximately 45% of the annual productivity loss in farming. Manual weeding methods, while effective, are labor-intensive and financially burdensome, particularly for smallholder farmers. Conversely, excessive reliance on chemical herbicides has led to herbicide resistance in several weed species, creating additional challenges in weed management.

Emerging technologies, particularly artificial intelligence (AI) and computer vision, are revolutionizing agriculture by automating labor-intensive tasks. Computer vision enables the precise identification of crops and weeds from images, supporting autonomous systems for selective weeding and targeted herbicide application. To develop robust AI models, high-quality datasets are critical. Addressing this need, we introduce the MH-Weed16 Image Dataset, collected from soybean fields in the Maharashtra region of India between July 2023 and November 2023 under diverse natural field conditions.
The dataset comprises a total of 18,677 images of 16 weed species, annotated with the guidance of agricultural experts. It also includes 7,577 representative crop samples, with 6,656 weed samples annotated using bounding boxes. Images of crop–weed interactions were captured from a top-down perspective to allow accurate weed area estimation based on bounding box annotations.
Importantly, the dataset incorporates 282 UAV-captured images, providing a large-scale aerial perspective that complements ground-based close-range details. These UAV images enhance the dataset’s diversity by introducing varying resolutions, field scales, and occlusion conditions, making it suitable for both macro-level weed distribution mapping and micro-level species identification. This multi-platform inclusion strengthens the dataset’s applicability to precision agriculture, enabling the training and evaluation of advanced computer vision models for object detection, classification, and weed–crop discrimination under real-world field conditions.
DOI: 10.15468/dl.c7gmfs
title: Occurrence Download

description: A dataset containing 531579 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Occurrence evidence",
 "Country is Mexico",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 531579 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004752-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/d3n3mgjjbv.2
title: MH-Weed16:An Indian Multiclass Annotated Weed Dataset for Computer Vision Tasks

description: Weeds are invasive plants that compete with crops for vital nutrients and often attract pests, significantly impacting agricultural productivity. They account for approximately 45% of the annual productivity loss in farming. Manual weeding methods, while effective, are labor-intensive and financially burdensome, particularly for smallholder farmers. Conversely, excessive reliance on chemical herbicides has led to herbicide resistance in several weed species, creating additional challenges in weed management.

Emerging technologies, particularly artificial intelligence (AI) and computer vision, are revolutionizing agriculture by automating labor-intensive tasks. Computer vision enables the precise identification of crops and weeds from images, supporting autonomous systems for selective weeding and targeted herbicide application. To develop robust AI models, high-quality datasets are critical. Addressing this need, we introduce the MH-Weed16 Image Dataset, collected from soybean fields in the Maharashtra region of India between July 2023 and November 2023 under diverse natural field conditions.
The dataset comprises a total of 18,677 images of 16 weed species, annotated with the guidance of agricultural experts. It also includes 7,577 representative crop samples, with 6,656 weed samples annotated using bounding boxes. Images of crop–weed interactions were captured from a top-down perspective to allow accurate weed area estimation based on bounding box annotations.
Importantly, the dataset incorporates 282 UAV-captured images, providing a large-scale aerial perspective that complements ground-based close-range details. These UAV images enhance the dataset’s diversity by introducing varying resolutions, field scales, and occlusion conditions, making it suitable for both macro-level weed distribution mapping and micro-level species identification. This multi-platform inclusion strengthens the dataset’s applicability to precision agriculture, enabling the training and evaluation of advanced computer vision models for object detection, classification, and weed–crop discrimination under real-world field conditions.
DOI: 10.17632/ygrxvm2t7p
title: Supplemental Methods for "Negative association of psoriasis with female sex hormone levels: a case-control study using TriNetX"

description: Supplemental Methods for "Negative association of psoriasis with female sex hormone levels: a case-control study using TriNetX"
DOI: 10.17632/ygrxvm2t7p.1
title: Supplemental Methods for "Negative association of psoriasis with female sex hormone levels: a case-control study using TriNetX"

description: Supplemental Methods for "Negative association of psoriasis with female sex hormone levels: a case-control study using TriNetX"
DOI: 10.60873/fk2/olsizd
title: Recife RM - Passageiros Equivalentes Ônibus [2024-2025]

description: Dados diários sobre o número de passageiros equivalentes transportados no sistema de ônibus municipal e intermunicipal da Região Metropolitana do Recife (PE). Dados diários identificados pelo código da linha e nome da empresa responsável.