cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4211/hs.4190ad67b1824f92a2a146a20da10909
title: Spatial streamflow drought in the larger Alpine region

description: This dataset accompanies the paper "Spatiotemporal dynamics of streamflow drought in the larger Alpine region" by Janzing et al. (2026, WRR).
All data is based on the runs with the PCR-GLOBWB2.0 model, run at a spatial resolution of 30 arcsec over 1990-2019 as described in Janzing et al., (2025). The dataset contains all modelled data needed to recreate the figures in the manuscript.
The modelled domain is 2.5--18.5 degree longitude and 42.5--51.5 degree latitude, whereas the analysis was caried out over a smaller study domain (3--18 longitude and 43--51 latitude).
For an extended description of the variables and data, we refer the reader to the research paper.
References:
Janzing, J., Wanders, N., Van Tiel, M., & Brunner, M. I. (2026). Spatiotemporal dynamics of streamflow drought in the larger Alpine region.
Janzing, J., Wanders, N., Van Tiel, M., Van Jaarsveld, B., Karger, D. N., & Brunner, M. I. (2025). Hyper-resolution large-scale hydrological modelling benefits from improved process representation in mountain regions. Hydrology and Earth System Sciences, 29(23), 7041-7071.
DOI: 10.15468/dl.yjmp5p
title: Occurrence Download

description: A dataset containing 620 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Argentina",
 "OccurrenceStatus is Present",
 "TaxonKey is Melica macra"
 ]
}

 The dataset includes 620 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000299-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5gm8228p
title: MassIVE MSV000100963 - Cerebrospinal Fluid Proteomics Alterations in Individuals with Niemann-Pick Type C treated with VTS-270
title: Niemann-Pick type C is a fatal, autosomal recessive, neurodegenerative disease caused by mutations in either NPC1 or NPC2. These genes encode proteins that transport cholesterol out of the lysosome. With defective NPC1 or NPC2 proteins, cholesterol accumulates in lysosomes, a biochemical hallmark of NPC disease, reducing its bioavailability to cells. Although proteomics has been studied in NPC, pressing biomarkers that reflect therapeutic treatment response are needed. In this study, we leverage state-of-the-art mass spectrometry and apply both discovery and targeted approaches to identify biomarkers that represent either the disease state or response to therapeutic treatment with intrathecal 2-hydroxypropyl-beta-cyclodextrin (IT HPBCD, also known as VTS-270). Here, we report that calbindin 1 (CALB1), neuron-specific enolase (ENO2), and fatty acid binding protein 3 (FABP3) are significantly elevated in individuals with NPC1, which is in accordance with previous research. Both ENO2 and FABP3 could serve as biomarkers that respond to VTS-270 treatment. In addition, two novel biomarkers, significantly elevated neutral alpha-glucosidase AB (GANAB) and significantly reduced afamin (AFAM), which is a vitamin E transporter that crosses the blood-brain barrier, are reported here.
DOI: 10.5281/zenodo.18774092
title: LINF_340013000

description: Protein phosphatase; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.18774093
title: LINF_340013000

description: Protein phosphatase; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.18774134
title: OPTIMIZING STATIN THERAPY IN THE MANAGEMENT OF ISCHEMIC HEART DISEASE: A CLINICAL ASSESSMENT OF HIGH-INTENSITY REGIMENS AND ADHERENCE FACTORS

description: Ischemic heart disease (IHD) remains the leading cause of mortality in Uzbekistan, necessitating aggressive lipid-lowering strategies. Despite clear international guidelines, the utilization of high-intensity statin therapy remains suboptimal due to concerns regarding side effects and poor patient adherence. This article presents a prospective clinical study conducted at the Department of Cardiology of Andijan State Medical Institute. Using the IMRAD framework, the research evaluates the efficacy and safety of high-intensity Rosuvastatin therapy in patients with stable angina and post-myocardial infarction status. The study involved 200 patients randomized into a standard care group and an intensified education-monitoring group. The results demonstrate that patients receiving intensified support achieved guideline-directed LDL-cholesterol targets significantly more often (65 percent vs 30 percent) without a significant increase in hepatic or muscular adverse events. The study concludes that the primary barrier to effective statin therapy is not biological intolerance but rather psychosocial resistance, which can be overcome through targeted education and monitoring.
DOI: 10.5281/zenodo.18774133
title: OPTIMIZING STATIN THERAPY IN THE MANAGEMENT OF ISCHEMIC HEART DISEASE: A CLINICAL ASSESSMENT OF HIGH-INTENSITY REGIMENS AND ADHERENCE FACTORS

description: Ischemic heart disease (IHD) remains the leading cause of mortality in Uzbekistan, necessitating aggressive lipid-lowering strategies. Despite clear international guidelines, the utilization of high-intensity statin therapy remains suboptimal due to concerns regarding side effects and poor patient adherence. This article presents a prospective clinical study conducted at the Department of Cardiology of Andijan State Medical Institute. Using the IMRAD framework, the research evaluates the efficacy and safety of high-intensity Rosuvastatin therapy in patients with stable angina and post-myocardial infarction status. The study involved 200 patients randomized into a standard care group and an intensified education-monitoring group. The results demonstrate that patients receiving intensified support achieved guideline-directed LDL-cholesterol targets significantly more often (65 percent vs 30 percent) without a significant increase in hepatic or muscular adverse events. The study concludes that the primary barrier to effective statin therapy is not biological intolerance but rather psychosocial resistance, which can be overcome through targeted education and monitoring.
DOI: 10.5281/zenodo.18758377
title: Challenges of Team‑Based Learning in Post‑COVID New Normal and HyFlex Medical Education - Data From the Narrative Review
DOI: 10.5281/zenodo.18758378
title: Challenges of Team‑Based Learning in Post‑COVID New Normal and HyFlex Medical Education - Data From the Narrative Review
DOI: 10.6084/m9.figshare.31403838.v1
title: R script for sample coverage simulations

description: R code script for simulated communities and species removal for testing abundance-based sample coverage behavior. Script also contains code for creating the graphs in the manuscript submission.
DOI: 10.15468/dl.d8h73r
title: Occurrence Download

description: A dataset containing 53494 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oncorhynchus gorbuscha",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 }
 ]
}

 The dataset includes 53494 records from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000258-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18739089
title: Neonatal Anthropometric Image Dataset for Computer Vision–Based Growth Analysis

description: This dataset consists of clinically acquired neonatal images along with anthropometric measurements collected for artificial intelligence, computer vision, and medical research focused on neonatal growth analysis.

The data were collected from Combined District Hospital, Manjhanpur, Kaushambi, Uttar Pradesh, India and Madhuraj Hospital Kanpur, Uttar Pradesh, India under controlled clinical conditions using standardized infant positioning and imaging protocols to ensure measurement accuracy and reproducibility.

The dataset contains 83 neonates, including 55 male and 28 female infants. Each neonate has a dedicated folder (Baby-ID format) containing multiple images in JPG, JPEG, or PNG formats. Image filenames do not follow a fixed naming convention and may vary in resolution and orientation.

In addition to images, a structured CSV file (neonatal_measurements.csv) is provided containing anthropometric and clinical parameters including:

Name, Date of Birth, Head Circumference, Arm Length, Leg Length, Chest Girth, Total Body Length, Weight, and Gestation Week.

The dataset is intended for research purposes such as:- computer vision model development- deep learning training- automated anthropometric estimation- neonatal growth prediction- pediatric AI research- medical image analysis benchmarking

All data have been anonymized prior to publication. No personally identifiable information is intentionally disclosed.

This dataset is released for academic, research, and educational purposes only. Clinical or commercial use requires permission from the authors.
DOI: 10.5281/zenodo.18739090
title: Neonatal Anthropometric Image Dataset for Computer Vision–Based Growth Analysis

description: This dataset consists of clinically acquired neonatal images along with anthropometric measurements collected for artificial intelligence, computer vision, and medical research focused on neonatal growth analysis.

The data were collected from Combined District Hospital, Manjhanpur, Kaushambi, Uttar Pradesh, India and Madhuraj Hospital Kanpur, Uttar Pradesh, India under controlled clinical conditions using standardized infant positioning and imaging protocols to ensure measurement accuracy and reproducibility.

The dataset contains 83 neonates, including 55 male and 28 female infants. Each neonate has a dedicated folder (Baby-ID format) containing multiple images in JPG, JPEG, or PNG formats. Image filenames do not follow a fixed naming convention and may vary in resolution and orientation.

In addition to images, a structured CSV file (neonatal_measurements.csv) is provided containing anthropometric and clinical parameters including:

Name, Date of Birth, Head Circumference, Arm Length, Leg Length, Chest Girth, Total Body Length, Weight, and Gestation Week.

The dataset is intended for research purposes such as:- computer vision model development- deep learning training- automated anthropometric estimation- neonatal growth prediction- pediatric AI research- medical image analysis benchmarking

All data have been anonymized prior to publication. No personally identifiable information is intentionally disclosed.

This dataset is released for academic, research, and educational purposes only. Clinical or commercial use requires permission from the authors.
DOI: 10.5281/zenodo.18772986
title: The Prime Alphabet: An Information-Theoretic Formalization of Local Prime Geometry in the Ulam Spiral

description: A 4-bit geometric encoding of prime neighborhoods in the Ulam spiral, with mutual information analysis, FDR-corrected connected component testing against three null models, scale invariance verification (N=256–1024), cross-channel independence analysis, and cross-implementation validation. Includes complete reproducible Python pipeline (13 scripts), data files, and the full paper (.docx). Adversarial review conducted independently by five AI systems (Claude, ChatGPT, Copilot, Grok, Gemini) with zero cross-access, all converging on identical structural conclusions. Structure attribution: ~95% modular geometry, ~5% polynomial trace residual.
DOI: 10.5281/zenodo.15211782
title: Dissipate and Recentre

description: The dataset gathers all the information relative to the Dissipate and Recentre (D&R) project, including data and metadata.The project aimed at experimentally investigating the sway behaviour of large-scale GFRP frames. The objectives of the project were to assess the behaviour of these structures under lateral loading, assessing and proposing seismic design methods and guidelines. The experimental campaign was performed at the European Laboratory for Structural Assessment (ELSA) of the JRC, and the User Access Team comprises well-established senior experts, several young researchers and an industrial partner (SME). The members of the proposing team have a leading role in ongoing efforts for the development of European standards for the design of FRP structures, for which the results of the project can provide essential knowledge. Such standards will support the market uptake of this innovative technology in the construction sector.The test specimens consisted of 2-storey frames, with 2 longitudinal bays and a single transverse bay. The structures were made of pultruded GFRP profiles, with stainless-steel connections. Concrete precast slabs were installed on the GFRP beams creating the floors of the specimens, simulating the equivalent vertical loads on of a real application, and allowing to anchor the actuators. The experimental campaign included the testing of four specimens: two without lateral bracings and two with such bracings. The modal identification of all specimens was performed using data of snap-back tests. For both types of frames, the first specimen was tested under monotonic loading, while the second underwent cyclic pseudo-static loading with increasing displacement amplitude. All tests were performed under displacement control. During the tests, the monitoring system recorded the applied loads and displacements, as well as rotations and strains of joints and members at key locations.
DOI: 10.5281/zenodo.15211781
title: Dissipate and Recentre

description: The dataset gathers all the information relative to the Dissipate and Recentre (D&R) project, including data and metadata.The project aimed at experimentally investigating the sway behaviour of large-scale GFRP frames. The objectives of the project were to assess the behaviour of these structures under lateral loading, assessing and proposing seismic design methods and guidelines. The experimental campaign was performed at the European Laboratory for Structural Assessment (ELSA) of the JRC, and the User Access Team comprises well-established senior experts, several young researchers and an industrial partner (SME). The members of the proposing team have a leading role in ongoing efforts for the development of European standards for the design of FRP structures, for which the results of the project can provide essential knowledge. Such standards will support the market uptake of this innovative technology in the construction sector.The test specimens consisted of 2-storey frames, with 2 longitudinal bays and a single transverse bay. The structures were made of pultruded GFRP profiles, with stainless-steel connections. Concrete precast slabs were installed on the GFRP beams creating the floors of the specimens, simulating the equivalent vertical loads on of a real application, and allowing to anchor the actuators. The experimental campaign included the testing of four specimens: two without lateral bracings and two with such bracings. The modal identification of all specimens was performed using data of snap-back tests. For both types of frames, the first specimen was tested under monotonic loading, while the second underwent cyclic pseudo-static loading with increasing displacement amplitude. All tests were performed under displacement control. During the tests, the monitoring system recorded the applied loads and displacements, as well as rotations and strains of joints and members at key locations.
DOI: 10.15468/dl.z3mce9
title: Occurrence Download

description: A dataset containing 4077 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "TaxonKey is Acer saccharum"
 ]
 },
 "HasCoordinate is TRUE",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2024",
 "DecimalLatitude is greater than or equal to 44.08449",
 "DecimalLatitude is less than or equal to 46.46833",
 "DecimalLongitude is greater than or equal to -75.88698",
 "DecimalLongitude is less than or equal to -72.32801",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 4077 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000303-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gb7sc7
title: Occurrence Download

description: A dataset containing 7562 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "MediaType is Image",
 "TaxonKey is Alliaria petiolata"
 ]
}

 The dataset includes 7562 records from 194 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000304-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f7tvk5
title: Occurrence Download

description: A dataset containing 1196 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Glauconycteris"
 ]
}

 The dataset includes 1196 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000305-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8wr896
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Canis simensis",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000306-260225131425191/datasets/export for details.
DOI: 10.6084/m9.figshare.31403838
title: R script for sample coverage simulations

description: R code script for simulated communities and species removal for testing abundance-based sample coverage behavior. Script also contains code for creating the graphs in the manuscript submission.
DOI: 10.6084/m9.figshare.31403838.v2
title: R script for sample coverage simulations

description: R code script for simulated communities and species removal for testing abundance-based sample coverage behavior. Script also contains code for creating the graphs in the manuscript submission.
DOI: 10.6084/m9.figshare.31403838.v3
title: R script for sample coverage simulations

description: R code script for simulated communities and species removal for testing abundance-based sample coverage behavior. Script also contains code for creating the graphs in the manuscript submission.
DOI: 10.5281/zenodo.18774198
title: CAMBER Dataset – Road Survey Video #9

description: This dataset contains road survey video recordings collected within the CAMBER - European Road Infrastructure Monitoring Project. The videos capture forward-facing visual information on road infrastructure condition, including pavement defects, surface degradation, and road furniture elements.

**Data Generation Method:**
The video was recorded using mobile devices during road monitoring campaigns. Video frames were processed using YOLO-based computer vision models to detect road malfunctions including potholes, manholes, and speed breakers. Detections were geo-referenced using synchronized GPS track data.

**Type of Data:** Video / Image sequences

**Data Format(s):** MP4 (video), CSV (detection results), GPX (GPS track)

**Spatial Coverage:**
- Route distance: 1.73 km
- Geographic coordinates: WGS84 (EPSG:4326)

**Temporal Coverage:**
- Recording date: 2026-02-25 16:12:21 UTC

**Processing Information:**
- Video ID: 9
- Processing status: Pending
- Safety assessment: Green (Totally Safe)
- Associated Route ID: 9

**Machine Learning Model:**
- Model: models/Yolov8-fintuned-on-potholes.pt
- Detected classes: manhole,pothole,speedbreaker,potholes
- Confidence threshold: 0.45
- Minimum track age: 5 frames

**Data Access:**
The dataset files are stored on the CAMBER project infrastructure with S3-compatible storage. Zenodo serves as a persistent metadata record and DOI landing page. Access to the full dataset is provided via the related identifiers or upon request.

**Funding:**
This work was funded by the European Union under the Horizon Europe programme, Grant Agreement No. 101156387.
description: For access requests, technical questions, or further information about this dataset, please contact: data@camber-project.eu

Project website: https://camber-project.eu (TODO: Update with actual URL)
DOI: 10.5281/zenodo.18774199
title: CAMBER Dataset – Road Survey Video #9

description: This dataset contains road survey video recordings collected within the CAMBER - European Road Infrastructure Monitoring Project. The videos capture forward-facing visual information on road infrastructure condition, including pavement defects, surface degradation, and road furniture elements.

**Data Generation Method:**
The video was recorded using mobile devices during road monitoring campaigns. Video frames were processed using YOLO-based computer vision models to detect road malfunctions including potholes, manholes, and speed breakers. Detections were geo-referenced using synchronized GPS track data.

**Type of Data:** Video / Image sequences

**Data Format(s):** MP4 (video), CSV (detection results), GPX (GPS track)

**Spatial Coverage:**
- Route distance: 1.73 km
- Geographic coordinates: WGS84 (EPSG:4326)

**Temporal Coverage:**
- Recording date: 2026-02-25 16:12:21 UTC

**Processing Information:**
- Video ID: 9
- Processing status: Pending
- Safety assessment: Green (Totally Safe)
- Associated Route ID: 9

**Machine Learning Model:**
- Model: models/Yolov8-fintuned-on-potholes.pt
- Detected classes: manhole,pothole,speedbreaker,potholes
- Confidence threshold: 0.45
- Minimum track age: 5 frames

**Data Access:**
The dataset files are stored on the CAMBER project infrastructure with S3-compatible storage. Zenodo serves as a persistent metadata record and DOI landing page. Access to the full dataset is provided via the related identifiers or upon request.

**Funding:**
This work was funded by the European Union under the Horizon Europe programme, Grant Agreement No. 101156387.
description: For access requests, technical questions, or further information about this dataset, please contact: data@camber-project.eu

Project website: https://camber-project.eu (TODO: Update with actual URL)
DOI: 10.5281/zenodo.18774169
title: INFLUENCE OF URIC ACID ON RENIN-ANGIOTENSIN-ALDOSTERONE SYSTEM ACTIVITY IN CHRONIC KIDNEY DISEASE

description: Hyperuricemia plays a significant role in the progression of chronic kidney disease by modulating the activity of the renin-angiotensin-aldosterone system. Elevated uric acid levels promote oxidative stress, endothelial dysfunction, and inflammation, which contribute to increased renin, angiotensin II, and aldosterone production. These hormonal changes lead to vasoconstriction, sodium and water retention, hypertension, and renal fibrosis, accelerating kidney injury. Clinical and experimental evidence suggests that early management of hyperuricemia, combined with interventions targeting the renin-angiotensin-aldosterone system, can slow disease progression, reduce proteinuria, and improve patient outcomes. Understanding the interplay between uric acid and hormonal regulation is essential for developing effective therapeutic strategies in patients with chronic kidney disease.