cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.dx9yff
title: Occurrence Download

description: A dataset containing 427 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bolitoglossa engelhardti"
 ]
}

 The dataset includes 427 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064134-251120083545085/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.30940613
title: FidlTrack - SPT fidelity raw SPT simulation data

description: Raw SPT simulation data for the FidlTrack SPT fidelity paper
DOI: 10.6084/m9.figshare.30940613.v2
title: FidlTrack - SPT fidelity raw SPT simulation data

description: Raw SPT simulation data for the FidlTrack SPT fidelity paper
DOI: 10.6084/m9.figshare.30940613.v1
title: qqq

description: aaaa
DOI: 10.6084/m9.figshare.30850829
title: Feasibility, acceptance, and workflow integration of an AI-enabled clinical decision support system for non-communicable diseases in Kiambu County, Kenya: A mixed-methods implementation evaluation

description: This repository contains the datasets generated during the development and evaluation of the NCDAI clinical decision support system for noncommunicable disease (NCD) management across primary health facilities in Kenya.The files comprise the following datasets:De-identified demographic, medical history, and clinical parameters collected from participating health facilities with foundational patient characteristics used to evaluate the NCDAI platform’s clinical recommendations and performance. Expert physician ratings and qualitative comments on AI-generated recommendations used to assess clinical appropriateness, guideline adherence, and inter-expert agreement.Anonymised responses from healthcare workers evaluating usability, workflow integration, and perceptions of the NCDAI system.Supplementary materialsStructured AI prompt framework used in the NCDAI study to support AI-assisted clinical decision support for hypertension and diabetes, including system-level context instructions and dynamic patient-data prompt construction aligned with evidence-based guidelines. This R script demonstrates the logic used to assemble AI prompts in the NCDAI study. All patient information shown is synthetic and provided for methodological illustration only.<br>
DOI: 10.6084/m9.figshare.30850829.v3
title: Feasibility, acceptance, and workflow integration of an AI-enabled clinical decision support system for non-communicable diseases in Kiambu County, Kenya: A mixed-methods implementation evaluation

description: This repository contains the datasets generated during the development and evaluation of the NCDAI clinical decision support system for noncommunicable disease (NCD) management across primary health facilities in Kenya.The files comprise the following datasets:De-identified demographic, medical history, and clinical parameters collected from participating health facilities with foundational patient characteristics used to evaluate the NCDAI platform’s clinical recommendations and performance. Expert physician ratings and qualitative comments on AI-generated recommendations used to assess clinical appropriateness, guideline adherence, and inter-expert agreement.Anonymised responses from healthcare workers evaluating usability, workflow integration, and perceptions of the NCDAI system.Supplementary materialsStructured AI prompt framework used in the NCDAI study to support AI-assisted clinical decision support for hypertension and diabetes, including system-level context instructions and dynamic patient-data prompt construction aligned with evidence-based guidelines. This R script demonstrates the logic used to assemble AI prompts in the NCDAI study. All patient information shown is synthetic and provided for methodological illustration only.<br>
DOI: 10.6084/m9.figshare.30850829.v2
title: Feasibility, acceptance, and workflow integration of an AI-enabled clinical decision support system for non-communicable diseases in Kiambu County, Kenya: A mixed-methods implementation evaluation

description: This repository contains the datasets generated during the development and evaluation of the NCDAI clinical decision support system for noncommunicable disease (NCD) management across primary health facilities in Kenya.The files comprise the following datasets:<b> </b>De-identified demographic, medical history, and clinical parameters collected from participating health facilities with foundational patient characteristics used to evaluate the NCDAI platform’s clinical recommendations and performance. Expert physician ratings and qualitative comments on AI-generated recommendations used to assess clinical appropriateness, guideline adherence, and inter-expert agreement. Anonymised responses from healthcare workers evaluating usability, workflow integration, and perceptions of the NCDAI system. Supplementary materials
DOI: 10.15468/dl.sdyq3b
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((13.19649 41.22494,13.72972 41.23206,13.72423 41.51365,13.1887 41.50646,13.19649 41.22494))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lasiommata megera",
 "Year 1990-2025"
 ]
}

 The dataset includes 19 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064135-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2qhj0s
title: CCDC 2517355: Experimental Crystal Structure Determination

description: Related Article: Dong-En Wu|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34808/8n7r-s357
title: Gdańsk University of Technology graduates’ satisfaction with graduating from a given faculty – years 2015-2018

description: The dataset includes data from the survey on the Gdańsk University of Technology graduates' from the years 2015-2018 on their satisfaction with graduating from a given faculty. The survey was conducted in the period from 2017 to 2020, two years after the respondents obtained graduate status. The research sample included 7409 respondents. To summarize, the vast majority of Gdańsk University of Technology graduates are satisfied with graduation from a given faculty.
DOI: 10.34808/n3ye-v907
title: The causes of labour inactivity of Gdańsk University of Technology graduates – years 2014-2018

description: The dataset includes data from the survey on the Gdańsk University of Technology graduates from the years 2014-2018 on the causes of their labour inactivity. The survey was conducted in the period from 2016 to 2020, two years after the respondents obtained graduate status. The research sample included 9413 respondents. To summarize, the most common cause of labour inactivity is continuing education or also the inability to find a job.
DOI: 10.34808/0jbh-nv76
title: Gdańsk University of Technology graduates’ satisfaction with graduating from university – years 2015-2018

description: The dataset includes data from the survey on the Gdańsk University of Technology graduates' from the years 2015-2018 on their satisfaction with graduating from university. The survey was conducted in the period from 2017 to 2020, two years after the respondents obtained graduate status. The research sample included 7409 respondents. To summarize, the vast majority of Gdańsk University of Technology graduates are satisfied with graduation from GdańskTech.
DOI: 10.34808/eq1h-vn39
title: Measurement of the tram rail profile during a year of operation - supplementary data

description: The aim of the work was to analyze the wear of rails during operation and to analyze the supplementation of heavy metals in the soil around the tram route, originating from wearing out rails and tram wheels.The dataset contains measurements of rail head coordinates in 9 research sections made in 8 measurement series. The wear of the rails in selected sections was examined using a profilometer. Measurements were performed on 8 dates: 26/06/2023, 31/08/2023, 23/10/2023, 19/12/2023, 01/02/2024, 14/03/2024, 02/04/2024, 09/05/2024.
Measurements were performed at 9 measurement points in the cross-section relative to traction poles 34/39, 34/38, 32-34/43, 32-34/42, 32-34/36, 32-34/33, 32-34/11, 32-34/7, 32-34/6
Rail wear was related to the measurement of rail wear made before the route was put into operation, which took place on March 2, 2023 The data was saved in DXF files and PNG files
Individual files have been described according to the following scheme: m.n_o.dxf and m.n.o.pngWherem - number of measuring point according to the number of the pole: 1 - 34/39, 2 - 34/38, 3 - 32-34/43, 4 - 32-34/42, 5 - 32-34/36, 6 - 32-34/33, 7 - 32-34/11, 8 - 32-34/7, 9 - 32-34/6.n - rail : 1 - track 1 rail, 2 - track 1 right rail, 3 - track 2 left rail, 4 - track 2, right rail.o - measurement date: 8 - 09/05/2024.
The dataset contains also picures showing the measurements and the the pdf file showing the increase in rail wear in individual measure points.
DOI: 10.34808/vsrh-ed73
title: Raising own qualifications by Gdańsk University of Technology graduates – years 2015-2018

description: The dataset includes data from the survey on the Gdańsk University of Technology graduates from the years 2015-2018 on raising their own qualifications. The survey was conducted in the period from 2017 to 2020, two years after the respondents obtained graduate status. The research sample included 7409 respondents. To summarize, the vast majority of Gdańsk University of Technology graduates continue to improve their own qualifications after graduation.
DOI: 10.34808/zvqt-fs66
title: Gdańsk University of Technology graduates’ satisfaction with graduating from a given field of study – years 2015-2018

description: The dataset includes data from the survey on the Gdańsk University of Technology graduates' from the years 2015-2018 on their satisfaction with graduating from a given field of study. The survey was conducted in the period from 2017 to 2020, two years after the respondents obtained graduate status. The research sample included 7409 respondents. To summarize, the vast majority of Gdańsk University of Technology graduates are satisfied with graduation from a given field of study.
DOI: 10.34808/gjm5-0v59
title: The sources of financing for raising qualifications of Gdańsk University of Technology graduates – years 2013-2016

description: The dataset includes data from the survey on the Gdańsk University of Technology graduates from the years 2013-2016 on the sources of financing for raising qualifications. The survey was conducted in the period from 2015 to 2018, two years after the respondents obtained graduate status. The research sample included 8281 respondents. To summarize, Gdańsk University of Technology graduates most often finance the development of their qualifications from their own funds.
DOI: 10.34808/9gv5-3903
title: Raising own qualifications by Gdańsk University of Technology graduates – years 2010-2014

description: The dataset includes data from the survey on the Gdańsk University of Technology graduates from the years 2010-2014 on raising their own qualifications. The survey was conducted in the period from 2012 to 2016, two years after the respondents obtained graduate status. The research sample included 5367 respondents. To summarize, the vast majority of Gdańsk University of Technology graduates continue to improve their own qualifications after graduation.
DOI: 10.15468/dl.tv3y9m
title: Occurrence Download

description: A dataset containing 24003 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is HST - Herbário Sérgio Tavares"
 ]
}

 The dataset includes 24003 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064137-251120083545085/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.28207862
title: ChIP-seq peak files

description: Purified DNA was quantified using a Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, cat. #Q32854, Waltham, MA, USA), and size and integrity was verified with a Fragment Analyzer (Agilent, Santa Clara, CA, USA). Libraries were prepared as 75 bp paired end reads with the TruSeq ChIP Library Preparation Kit (Illumina, Inc., cat. #IP-202-1012, San Diego, CA, USA) following manufacturer’s instructions. Libraries for H3K4me3, H3K27ac, and Input were sequenced to achieve at least 20 million uniquely mapped reads, and H3K4me1 and H3K27me3 libraries were sequenced to achieve at least 45 million uniquely mapped reads to comply with ENCODE standards for ChIP-seq1. The peaks of H3K4me3, H3K27ac, H3K4me1, and H3K27me3 were called by chipseq model of Nextflow v24.04.247 with Bowtie2 aligner and MACS2 peak caller with ‘-macs_pavalue 0.005’, for narrow histone marks H3K4me3 and H3K27ac with additional parameter ‘--narrow_peak’. The reference genome for alignment was from NCBI (ARS-UI_Ramb_v2.0, GenBank accession GCF_016772045.1).
DOI: 10.6084/m9.figshare.28207862.v1
title: ChIP-seq peak files

description: Purified DNA was quantified using a Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, cat. #Q32854, Waltham, MA, USA), and size and integrity was verified with a Fragment Analyzer (Agilent, Santa Clara, CA, USA). Libraries were prepared as 75 bp paired end reads with the TruSeq ChIP Library Preparation Kit (Illumina, Inc., cat. #IP-202-1012, San Diego, CA, USA) following manufacturer’s instructions. Libraries for H3K4me3, H3K27ac, and Input were sequenced to achieve at least 20 million uniquely mapped reads, and H3K4me1 and H3K27me3 libraries were sequenced to achieve at least 45 million uniquely mapped reads to comply with ENCODE standards for ChIP-seq1. The peaks of H3K4me3, H3K27ac, H3K4me1, and H3K27me3 were called by chipseq model of Nextflow v24.04.247 with Bowtie2 aligner and MACS2 peak caller with ‘-macs_pavalue 0.005’, for narrow histone marks H3K4me3 and H3K27ac with additional parameter ‘--narrow_peak’. The reference genome for alignment was from NCBI (ARS-UI_Ramb_v2.0, GenBank accession GCF_016772045.1).
DOI: 10.6084/m9.figshare.30940598
title: Data set for acceptance model of reuse water in Jakarta

description: The data were collected to analyze the factors influencing household intentions to adopt the Greywater Reuse System with Material Value Conservation (GWRS-MVC) in Jakarta, using an extended Technology Acceptance Model (TAM).
DOI: 10.6084/m9.figshare.30940598.v1
title: Data set for acceptance model of reuse water in Jakarta

description: The data were collected to analyze the factors influencing household intentions to adopt the Greywater Reuse System with Material Value Conservation (GWRS-MVC) in Jakarta, using an extended Technology Acceptance Model (TAM).
DOI: 10.34740/kaggle/dsv/14271438
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.6084/m9.figshare.29833163
title: <b>The CspC:CspA heterodimer transduces germinant and co-germinant signals during </b><b><i>Clostridioides difficile</i></b><b> spore germination.</b>

description: This dataset includes the raw data for the optical density-based germination assays found in Figures
DOI: 10.6084/m9.figshare.29833163.v1
title: <b>The CspC:CspA heterodimer transduces germinant and co-germinant signals during </b><b><i>Clostridioides difficile</i></b><b> spore germination.</b>

description: This dataset includes the raw data for the optical density-based germination assays found in Figures
DOI: 10.6084/m9.figshare.29833163.v2
title: <b>The CspC:CspA heterodimer transduces germinant and co-germinant signals during </b><b><i>Clostridioides difficile</i></b><b> spore germination.</b>

description: This dataset includes the raw data for the optical density-based germination assays found in Figures
DOI: 10.5281/zenodo.18037143
title: Beyond Leaf Mass per Area: Anatomical and Economic Drivers of Toughness in Evergreen and Deciduous Oaks

description: Dataset corresponding with the research paper called "Beyond Leaf Mass per Area: Anatomical and Economic Drivers of Toughness in Evergreen and Deciduous Oaks".



Oak_fiber Dataset.xlsx: Dataset used in the analyses. Average values per species are provided.

Supplementary Data.docx: Supplementary figures of the article.
DOI: 10.5281/zenodo.18037142
title: Beyond Leaf Mass per Area: Anatomical and Economic Drivers of Toughness in Evergreen and Deciduous Oaks

description: Dataset corresponding with the research paper called "Beyond Leaf Mass per Area: Anatomical and Economic Drivers of Toughness in Evergreen and Deciduous Oaks".



Oak_fiber Dataset.xlsx: Dataset used in the analyses. Average values per species are provided.

Supplementary Data.docx: Supplementary figures of the article.
DOI: 10.15468/dl.vjwevp
title: Occurrence Download

description: A dataset listing the 1657 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Inventario de flora, avifauna, mamíferos, mariposas y peces realizado en el sector de Puerto Abeja y durante la expedición científica en la ventana Mesay en el sector sur del Parque Nacional Natural Serranía de Chiribiquete"
 ]
}

 The dataset's 1657 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064136-251120083545085/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.28622969
title: Fidelity in co-diversified symbiosis

description: Raw data and R scripts for statistical analyses of the manuscript entitled "Fidelity in co-diversified symbiosis."
DOI: 10.6084/m9.figshare.28622969.v1
title: Fidelity in co-diversified symbiosis

description: Raw data and R scripts for statistical analyses of the manuscript entitled "Fidelity in co-diversified symbiosis."
DOI: 10.6084/m9.figshare.30940745
title: Supplementary Material for: Hepatic Angiosarcoma (HA) Associated with Chronic Schistosomiasis in a Patient with Decompensated Cirrhosis: A Rare Case Report

description: We present a rare case of hepatic angiosarcoma associated with Schistosoma infection in a 64-year-old Filipina living in the UAE. Initially diagnosed as acute decompensated liver cirrhosis with hepatic encephalopathy, the clinical course was complicated by spontaneous intra-abdominal hemorrhage, hepatic dysfunction, acute kidney injury, and sepsis. Imaging raised suspicion of Budd-Chiari syndrome, which was later discounted by radiological assessments. Liver biopsy confirmed both angiosarcoma and Schistosoma eggs, suggesting a potential association between the chronic parasitic infection and hepatic malignancy. Despite intensive management, the patient's clinical condition rapidly deteriorated, highlighting the aggressive nature and diagnostic challenges associated with hepatic angiosarcoma.
DOI: 10.6084/m9.figshare.30940745.v1
title: Supplementary Material for: Hepatic Angiosarcoma (HA) Associated with Chronic Schistosomiasis in a Patient with Decompensated Cirrhosis: A Rare Case Report

description: We present a rare case of hepatic angiosarcoma associated with Schistosoma infection in a 64-year-old Filipina living in the UAE. Initially diagnosed as acute decompensated liver cirrhosis with hepatic encephalopathy, the clinical course was complicated by spontaneous intra-abdominal hemorrhage, hepatic dysfunction, acute kidney injury, and sepsis. Imaging raised suspicion of Budd-Chiari syndrome, which was later discounted by radiological assessments. Liver biopsy confirmed both angiosarcoma and Schistosoma eggs, suggesting a potential association between the chronic parasitic infection and hepatic malignancy. Despite intensive management, the patient's clinical condition rapidly deteriorated, highlighting the aggressive nature and diagnostic challenges associated with hepatic angiosarcoma.
DOI: 10.6084/m9.figshare.30940748
title: Supplementary Material for: Exploring the impact of an artificial intelligence-based intraoperative image navigation system in laparoscopic surgery on clinical outcomes: A protocol for a multicenter randomized controlled trial

description: Introduction: Artificial intelligence (AI), particularly deep learning-based computer vision technology, has been used in surgery as real-time intraoperative navigation; however, its clinical relevance remains unclear. To address this gap, well-designed randomized controlled trials (RCTs) are necessary to evaluate the effects of these systems by comparing surgical outcomes with and without their use. In this study, we will investigate a deep learning-based intraoperative image navigation system that operates in real time and uses semantic segmentation to help identify the ureter and autonomic nerves during laparoscopic colorectal surgery. We propose a multicenter RCT to compare the procedure of using this system against those that do not.
Methods: The ImNavi trial is a Japanese multicenter RCT involving 1:1 randomization between the use and non-use of the deep learning-based intraoperative image navigation system. The participating institutions will include three high-volume centers with sufficient laparoscopic colorectal surgery caseloads (&gt;100 cases/year), including one national cancer center and two university hospitals in Japan. All patients will provide written informed consent. Patients aged between 18 and 80 years scheduled to undergo laparoscopic left-sided colorectal resection will be included in the study. The primary outcome is the time required for each target organ, including the ureter and autonomic nerves, to be recognized by the surgeon after its initial appearance on the monitor. Secondary outcomes include intraoperative target organ injuries, intraoperative complications, operation time, blood loss, duration of postoperative hospital stay, postoperative complications within 30 days, postoperative male erectile and ejaculatory dysfunction 1 month post-surgery, surgeon’s confidence in recognizing each target organ, and the postoperative fatigue of the primary surgeon. 
Conclusion: The impact of AI-based surgical applications on clinical outcomes beyond numerical expression will be explored from diverse viewpoints while evaluating quantitative items, including intraoperative complications and operation time, as secondary endpoints. The findings of this RCT can contribute to advancing research in the domain of AI in surgery.