cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/v2f89fjcpd.1
title: Systematic Review and Analysis of Dupilumab Use on the Stage of Mycosis Fungoides Presentation

description: To investigate the impact of dupilumab use on the stage of mycosis fungoides presentation, we performed and compared two systematic reviews - one for patients with MF/CTCL and history of dupilumab intervention and one for population studies of MF. In this systematic assessment of the literature, dupilumab treatment was associated with a higher-stage MF diagnosis even after adjusting for age and sex.

The following supplemental materials include tables of the search strategies, patient characteristics, references for the reviewed articles, and figures of the PRISMA diagrams for both systematic reviews.
DOI: 10.17632/x5nmsprjc9.1
title: Echocardiogram dataset for survival analysis

description: Dataset Documentation: Extended UCI Echocardiogram Dataset
1. Overview
The Extended UCI Echocardiogram Dataset is a synthetic dataset based on the original UCI Echocardiogram dataset. It comprises 100,000 samples and 17 variables, representing patients who either survived or died within one year after a heart attack. The dataset was expanded using statistical techniques to maintain realistic variability while preserving the integrity of the original dataset's patterns. It is designed for survival analysis, predictive modelling, and clinical decision-making research.

2. Dataset Purpose
The dataset is intended for:

Survival Analysis: Predicting the likelihood of survival post-heart attack.

Feature Importance Analysis: Identifying key clinical predictors of survival.

Machine Learning Model Development: Training and evaluating predictive models for survival outcomes.

Clinical Research: Exploring relationships between clinical variables and patient outcomes.

3. Variables
The dataset contains 17 variables, including 16 features and one target variable. Below is a detailed description of each variable:

Features
Survival:

Type: Float



5. Dataset Statistics
Number of Rows: 100,000

Number of Columns: 17

Target Variable Distribution:

Survived (alive_at_one = 1): ~30.32%

Deceased (alive_at_one = 0): ~69.68%
DOI: 10.17632/v2f89fjcpd.2
title: Systematic Review and Analysis of Dupilumab Use on the Stage of Mycosis Fungoides Presentation

description: To investigate the impact of dupilumab use on the stage of mycosis fungoides presentation, we performed and compared two systematic reviews - one for patients with MF/CTCL and history of dupilumab intervention and one for population studies of MF. In this systematic assessment of the literature, dupilumab treatment was associated with a higher-stage MF diagnosis even after adjusting for age and sex.

The following supplemental materials include tables of the search strategies, patient characteristics, references for the reviewed articles, and figures of the PRISMA diagrams for both systematic reviews.
DOI: 10.17632/xj4hccbhm8.1
title: Data and analyses cross-validation EPICC Tool-it

description: Source data in file format .dat for the all dataset and for the two subsamples; Mplus input-output files for the EFA and CFA performed.
The multicentre, cross-sectional validation study to which the data belongs aimed to cross-culturally adapt and psychometrically test the Italian version of the EPICC Spiritual Care Competency Self-Assessment Tool for nurses (EPICC Tool-It).
The 28-item EPICC Tool was translated into Italian and culturally adapted following a rigorous methodology. A nationwide survey was conducted. Psychometric evaluation included content validity, structural validity (exploratory and confirmatory factor analyses), construct validity (known group analysis), and reliability using Cronbach's alpha, McDonald's omega, and factor score determinacy.
The sample included 725 nurses (76% female, 80% hospital-based), on average 38.7 years old (SD 11.33), with 14.6 (SD 11.03) years of experience. Confirmatory factor analysis supported a four-factor model (Knowledge of spirituality, Attitudes towards spirituality and spiritual care, Knowledge of spiritual care, and Skills in spiritual care), with a second-order factor for the EPICC Tool-It. Construct validity was supported through known group analysis, showing score variation based on nurses' experience, education, and religiosity. Internal consistency was excellent across all factors and the overall scale.
A valid, multidimensional instrument is provided to assess spiritual care competencies in Italian-speaking nurses. The EPICC Tool-It is suitable for research and practice, facilitating evaluation of self-perceived competencies and educational effectiveness.
Implications for the Profession and/or Patient Care: The use of the EPICC Tool-It by nursing managers, educators, and clinicians is recommended in both clinical and research settings to support education on spiritual care competencies.
DOI: 10.17632/gpj7pz6wzx.1
title: Political Patronage, Rent-Extraction, and Social Costs: Evidence from China’s Environmental Cleanup

description: This research examines the interplay of political patronage, environmental regulation, and business dynamics in China’s governance. We reveal that local leaders’ patronage ties shield polluting firms from regulations, resulting in adverse environmental consequences. Additionally, we demonstrate that the rent-seeking behavior of politically connected officials frequently supersedes their motivations for economic growth and fiscal revenue. Further analysis shows the political patronage brings only industrial expansion of local polluters, without corresponding gains in productivity or profitability. And ultimately, it leads to the deterioration of the local business environment. Our findings extend beyond formal institutions, highlighting the impact of local leaders' informal networks on local environmental governance, as well as regional business environments and economic growth. These insights have broad implications for regulatory dynamics in autocratic and democratic contexts, emphasizing the role of power and influence.
DOI: 10.17632/xn44yz596n.1
title: Bangladeshi Currency (Coins & Notes) Recognition Dataset

description: The Bangladeshi Currency (Coins & Notes) Recognition Dataset is a comprehensive collection of high-quality images of Bangladeshi coins and banknotes. It is designed to facilitate machine learning and computer vision applications for currency recognition, classification, and detection.

This dataset is organized into various denominations of coins and notes, with each folder representing a specific currency denomination. Each folder contains 10,000 images, providing a total of 100,000 images in the dataset.

The images have been resized to a uniform dimension of 256x256 pixels, ensuring consistency and enabling easy integration into machine learning workflows. The images are saved in JPEG format to optimize storage and speed for large-scale training tasks.

Currency Denominations Included:
10 Poisha (Small denomination coin)
1 Poisha
1 Taka
25 Poisha
2 Taka
50 Poisha
5 Poisha
5 Taka
Commemorative Coins
Demonetized Notes
Features:
Image Size: All images have been resized to 256x256 pixels (Width x Height).
Image Format: JPEG.
Total Images: 100,000 (10,000 images per folder, one per denomination).
Categories: Each folder corresponds to a unique denomination of currency. The folder names are aligned with the specific denominations such as 10_Poisha, 1_Taka, 5_Taka, etc.
Objective:
This dataset is ideal for training and evaluating models for the following tasks:

Currency Classification: Identifying the denomination of a given image of a coin or banknote.
Currency Recognition: Detecting and recognizing specific Bangladeshi coins and notes from real-world images.
Coin and Note Detection: Identifying and classifying multiple coins and notes in a single image.
Possible Use Cases:
Currency detection systems: Automated systems in ATMs, vending machines, or cash counting machines that recognize Bangladeshi coins and banknotes.
Banknote and Coin Classification: Machine learning models that classify various denominations of coins and notes for digital payment applications.
Real-world Applications: Currency recognition for mobile apps, kiosks, or any system that needs to automatically recognize Bangladeshi currency.
Research in Currency Image Recognition: Researchers working on currency recognition problems using computer vision techniques.

Note for Researchers Using the dataset
This dataset was created by Shuvo Kumar Basak. If you use this dataset for your research or academic purposes, please ensure to cite this dataset appropriately. If you have published your research using this dataset, please share a link to your paper. Good Luck.
DOI: 10.17632/xn44yz596n.2
title: Bangladeshi Currency (Coins & Notes) Recognition Dataset

description: The Bangladeshi Currency (Coins & Notes) Recognition Dataset is a comprehensive collection of high-quality images of Bangladeshi coins and banknotes. It is designed to facilitate machine learning and computer vision applications for currency recognition, classification, and detection.

This dataset is organized into various denominations of coins and notes, with each folder representing a specific currency denomination. Each folder contains 10,000 images, providing a total of 100,000 images in the dataset.

The images have been resized to a uniform dimension of 256x256 pixels, ensuring consistency and enabling easy integration into machine learning workflows. The images are saved in JPEG format to optimize storage and speed for large-scale training tasks.

Currency Denominations Included:
10 Poisha (Small denomination coin)
1 Poisha
1 Taka
25 Poisha
2 Taka
50 Poisha
5 Poisha
5 Taka
Commemorative Coins
Demonetized Notes
Features:
Image Size: All images have been resized to 256x256 pixels (Width x Height).
Image Format: JPEG.
Total Images: 100,000 (10,000 images per folder, one per denomination).
Categories: Each folder corresponds to a unique denomination of currency. The folder names are aligned with the specific denominations such as 10_Poisha, 1_Taka, 5_Taka, etc.
Objective:
This dataset is ideal for training and evaluating models for the following tasks:

Currency Classification: Identifying the denomination of a given image of a coin or banknote.
Currency Recognition: Detecting and recognizing specific Bangladeshi coins and notes from real-world images.
Coin and Note Detection: Identifying and classifying multiple coins and notes in a single image.
Possible Use Cases:
Currency detection systems: Automated systems in ATMs, vending machines, or cash counting machines that recognize Bangladeshi coins and banknotes.
Banknote and Coin Classification: Machine learning models that classify various denominations of coins and notes for digital payment applications.
Real-world Applications: Currency recognition for mobile apps, kiosks, or any system that needs to automatically recognize Bangladeshi currency.
Research in Currency Image Recognition: Researchers working on currency recognition problems using computer vision techniques.
Collected (https://www.bb.org.bd/currency) + own 
Note for Researchers Using the dataset
This dataset was created by Shuvo Kumar Basak. If you use this dataset for your research or academic purposes, please ensure to cite this dataset appropriately. If you have published your research using this dataset, please share a link to your paper. Good Luck.
DOI: 10.17632/p35dmcf8my.1
title: The community assembly of tropical macroinvertebrates significantly changes with functional groups and habitat degradation

description: Macroinvertebrate community and environmental variables data in natural streams and degraded streams during wet season and dry season.
DOI: 10.17632/47zk74jcd7.1
title: QUITREM - QTNANO - Influence of Co Doping on Copper Nanoclusters for CO2 Electroreduction - ACS Omega 2024, 9, 47, 47114–47121

description: This dataset outlines the key inputs and outputs from the published work Influence of Co Doping on Copper Nanoclusters for CO2 Electroreduction (DOI: 10.1021/acsomega.4c07514) and is organized into the following categories: 
1) Cu55_clean: Includes calculations performed on the cluster without molecules and without dopants. 
2) Cu55_dopant: Contains calculations related to substrates with single-atom (SA) dopants (Fe, Ni, Co) but without molecules. 
3) Cu55_molecules: Represents calculations for clusters with molecules (CO, CHO, COH) but without dopants. 
4) Cu55_molecules_dopant: Encompasses calculations for clusters with molecules (CO, CHO, COH) and SA dopants. 
5) DOS: Includes density of states (DOS) calculations for the clusters. 
6) Vibrational_frequencies: Contains vibrational frequency calculations for the structures of molecules adsorbed on the clusters.
7) Molecules: Gas-phase isolated molecules calculations.
DOI: 10.15468/dl.2sw2z6
title: Occurrence Download

description: A dataset containing 88 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chamaecrista cultrifolia (Kunth) Britton & Rose ex Britton & Killip"
 ]
}

 The dataset includes 88 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004704-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/xbrw4k2yyz.1
title: QUITREM - QTNANO - Computational screening of silver-based single-atom alloys catalysts for CO2 reduction - J. Chem. Phys. 160, 094706 (2024)

description: This dataset outlines the key inputs and outputs from the published work Computational screening of silver-based single-atom alloys catalysts for CO2 reduction (DOI: 10.1063/5.0192055) and is organized into the following categories: 
 1) low_muller_Ag: Calculations of Ag(100), Ag(110), and Ag(111).
 2) Ag211_Clean: Clean calculations of Ag(211) without dopants and molecules.
 3) Ag211_dopant: Calculations of Ag(211) doped with (Cu, Co, Fe, Ni, Rh, and Ir) without molecules.
 4) Ag211_dopant_molecule: Adsorption of molecules on doped Ag(211) surface.
 5) bulk: Bulk calculations for Ag.
 6) isolated_molecules: Gas-phase molecules calculations.
DOI: 10.15468/ruvr34
title: Records of White-headed Duck (Oxyura leucocephala) in Central Asia

description: This dataset compiles records of White-headed Duck (Oxyura leucocephala) observations across Central Asia, with a primary focus on Kazakhstan and neighboring regions. It provides information on sighting locations, population estimates, sex and age distribution, and references to scientific publications supporting these records. The data are derived from literature sources. This dataset is valuable for monitoring population trends, tracking changes in abundance and distribution, and assessing habitat conditions for this species.
DOI: 10.6084/m9.figshare.27247956
title: Masterchart.xlsx

description: Induction of labour is one of the most common interventions done in obstetrics in women where delivery of fetus outweighs the risks of continuation. If the success or failure for such an intervention can be predicted, it will help clinicians in counselling and prognosticating women before undertaking the procedure.
DOI: 10.6084/m9.figshare.27247956.v2
title: Masterchart.xlsx

description: Induction of labour is one of the most common interventions done in obstetrics in women where delivery of fetus outweighs the risks of continuation. If the success or failure for such an intervention can be predicted, it will help clinicians in counselling and prognosticating women before undertaking the procedure.
DOI: 10.6084/m9.figshare.27247956.v1
title: Masterchart.xlsx

description: Induction of labour is one of the most common interventions done in obstetrics in women where delivery of fetus outweighs the risks of continuation. If the success or failure for such an intervention can be predicted, it will help clinicians in counselling and prognosticating women before undertaking the procedure.
DOI: 10.48436/hfkat-ag945
title: Vienna Terrestrial Reference Frame S/X 2020 for VLBI scale study

description: Description

The dataset contains three terrestrial reference frames, S0, S1 and S2, determined from Very Long Baseline Interferometry (VLBI) observations analysed by the Vienna International VLBI Service for Geodesy and Astrometry (IVS) Analysis Center (VIE). 

Context and methodology



S0: 1980.0-2021.0, S/X VLBI sessions with more than 3 stations

S1: 1980.0-2021.0, S/X VLBI sessions with more than 3 stations + 4 additional discontinuity breaks for NYALES20 due to PDIM (proposed by Le Bail. 2023)

S2: 1980.0-2021.0, S/X VLBI sessions with more than 3 stations + 2 additional discontinuity breaks for NYALES20 due to PDIM (realized in ITRF2020-u2023 (IERS ITRF Center 2024))

These terrestrial reference frames were used to calculate session-wise estimated VLBI scale factors to analyse the impact of a modfied station movement model for the VLBI station NYALES20 (Norway, Svalbard) on the VLBI scale. Thus, additional discontinuity intervals have been introduced in the determination of S1 and S2 to more accurately account for the climate change-related processes happening in Svalbard. 

The two reference frames were computed using VieCompy (Kern et al. 2023), a combination software under the umbrella of VieVS (Vienna VLBI and Satellite Software; Böhm et al. 2018) written in Python. 

The corresponding publication with the title Terrestrial Reference Frame Scale Drift Anomalies in VLBI and the Contribution of Ny-Ålesund Radio Telescopes has been submitted to the Earth, Planets and Space Journal. 


Technical details



The dataset contains the position and velocities of 82 VLBI stations and considers the discontinuities in station position of 19 (S0)/20 (S1, S2) stations.
DOI: 10.48436/rqf6q-dt861
title: Vienna Terrestrial Reference Frame S/X 2020 for VLBI scale study

description: Description

The dataset contains three terrestrial reference frames, S0, S1 and S2, determined from Very Long Baseline Interferometry (VLBI) observations analysed by the Vienna International VLBI Service for Geodesy and Astrometry (IVS) Analysis Center (VIE). 

Context and methodology



S0: 1980.0-2021.0, S/X VLBI sessions with more than 3 stations

S1: 1980.0-2021.0, S/X VLBI sessions with more than 3 stations + 4 additional discontinuity breaks for NYALES20 due to PDIM (proposed by Le Bail. 2023)

S2: 1980.0-2021.0, S/X VLBI sessions with more than 3 stations + 2 additional discontinuity breaks for NYALES20 due to PDIM (realized in ITRF2020-u2023 (IERS ITRF Center 2024))

These terrestrial reference frames were used to calculate session-wise estimated VLBI scale factors to analyse the impact of a modfied station movement model for the VLBI station NYALES20 (Norway, Svalbard) on the VLBI scale. Thus, additional discontinuity intervals have been introduced in the determination of S1 and S2 to more accurately account for the climate change-related processes happening in Svalbard. 

The two reference frames were computed using VieCompy (Kern et al. 2023), a combination software under the umbrella of VieVS (Vienna VLBI and Satellite Software; Böhm et al. 2018) written in Python. 

The corresponding publication with the title Terrestrial Reference Frame Scale Drift Anomalies in VLBI and the Contribution of Ny-Ålesund Radio Telescopes has been submitted to the Earth, Planets and Space Journal. 


Technical details



The dataset contains the position and velocities of 82 VLBI stations and considers the discontinuities in station position of 19 (S0)/20 (S1, S2) stations.
DOI: 10.48436/z5kk9-2c184
title: Vienna Terrestrial Reference Frame S/X 2020 for VLBI scale study

description: Description

The dataset contains two terrestrial reference frames, S0 and S1, determined from Very Long Baseline Interferometry (VLBI) observations analysed by the Vienna International VLBI Service for Geodesy and Astrometry (IVS) Analysis Center (VIE). 

Context and methodology



S0: 1980.0-2021.0, S/X VLBI sessions with more than 3 stations

S1: 1980.0-2021.0, S/X VLBI sessions with more than 3 stations + additional discontinuity breaks for NYALES20 due to PDIM, GIA

These terrestrial reference frames were used to calculate session-wise estimated VLBI scale factors to analyse the impact of a modfied station movement model for the VLBI station NYALES20 (Norway, Svalbard) on the VLBI scale. Thus, additional discontinuity intervals have been introduced in the determination of S1 to more accurately account for the climate change-related processes happening in Svalbard. 

The two reference frames were computed using VieCompy (Kern et al. 2023), a combination software under the umbrella of VieVS (Vienna VLBI and Satellite Software; Böhm et al. 2018) written in Python. 

The corresponding publication with the title Terrestrial Reference Frame Scale Drift Anomalies in VLBI and the Contribution of Ny-Ålesund Radio Telescopes has been submitted to the Earth, Planets and Space Journal. 


Technical details



The dataset contains the position and velocities of 82 VLBI stations and considers the discontinuities in station position of 19 (S0)/20 (S1) stations.
DOI: 10.15468/dl.tvfrz2
title: Occurrence Download

description: A dataset containing 35121487 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 35121487 records from 12033 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004629-250117142028555/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yvkhcz
title: Occurrence Download

description: A dataset containing 47 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Gomphus vulgatissimus Linnaeus, 1758",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Country is Ukraine"
 ]
}

 The dataset includes 47 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0134607-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34816/ifao.archives.158900
title: OUCHEBTI DEIR EL-MÉDINA_nb_1971_07691

description: Référence : nb_1971_07691<br />Site : Deir el-Médina<br />Type : photographie<br />
DOI: 10.15468/dl.93qsem
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-105.6308 21.97815,-105.55939 20.56091,-103.79608 20.55542,-103.77411 22.03857,-105.6308 21.97815))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Osgoodomys banderanus (J.A.Allen, 1897)"
 ]
}

 The dataset includes 46 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055460-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34816/ifao.archives.158901
title: OUCHEBTI DEIR EL-MÉDINA_nb_1971_07692

description: Référence : nb_1971_07692<br />Site : Deir el-Médina<br />Type : photographie<br />
DOI: 10.34816/ifao.archives.158902
title: OUCHEBTI DEIR EL-MÉDINA_nb_1971_07693

description: Référence : nb_1971_07693<br />Site : Deir el-Médina<br />Type : photographie<br />
DOI: 10.15468/dl.b9xv6g
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammillaria hahniana Werderm.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 96 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0066637-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.