cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/3rztrysnvp
title: Russian Drug Use Disorders, Drug Crimes, Drug Court, Drug Police Data for 2019

description: Official indicators, officially published:

- Population in the regions of Russia,
- Drug dependence incidence,
- Harmful drug use prevalence,
- Injecting drug users (IDU) Prevalence per 100000,
- Number of HIV positive IDUs,
- Percent of HIV positive among registred IDUs,
- Incidence of Injection drug use,
- Relative rate of patients who inject drugs (rate among incidence),
- Prevalence of people with substance use (drugs+alcohol),
- Drugs dependence prevalence (no alcohol),
- Harmful drug use prevalence,
- HIV Incidence overall (not speciifc to drug users),
- HIV prevalence overall,
- Number of multidisciplinary institutions with outpatient narcological departments (offices),
- Bed occupancy (days per year),
- The average length of stay of the patient in the bed,
- Duration of treatment (days per patient),
- The number of schoolchildren and students tested for drugs,
- The number of schoolchildren and students who refused to test,
- The number of schoolchildren and students who refused to test,
- The number of schoolchildren and students testing positive for drugs,
- The number of schoolchildren and students testing positive for drugs,
- The involvement of drug users in illicit trafficking 2018,
- The criminality of drug addiction (the effect of drug addiction on drugs situation) 2018,
- Proportion of humans of drug related crimes to all humans with crimes,
- Proportion of youth (under 18) who are convicted for drug use among all who are convicted for drug use,
- Prevalence of drug use based on social studies (percent in a cohort),
- Prevalence of drug users based on police data,
- Death from drug poisoning based on pathology report,
- Opioid dependese prevalence (registered),
- Cannabis dependence prevalence (registered),
- Opioid dependese incidence (registered),
- Cannabis dependence incidence (registered)

All variables was downloaded from the Official published sources and was available online on January 2022.
Collected for the study (JMIR Preprints 08/01/2024:56006)
DOI: https://doi.org/10.2196/preprints.56006
DOI: 10.17632/3yrcvyk3dv
title: Undergraduate Admission and Graduation Dataset from a Colombian Public University: Trends in Equity, Retention, and Academic Performance

description: This dataset provides detailed records on undergraduate admissions and graduations from a public university in Colombia, covering students admitted from 2016 to 2024 and those who graduated in 2023 and 2024. It includes key variables such as enrollment numbers, tuition fees, time-to-degree completion, and special admission categories for vulnerable populations, including victims of armed conflict, Indigenous students, and Afro-Colombian communities.

The data enable researchers to analyze gender disparities in higher education, assess retention and dropout risks, and explore academic trajectories across different programs. Additionally, by comparing admission and graduation trends, the dataset supports investigations into shifts in academic demand and the effectiveness of special enrollment pathways.

This dataset serves as a valuable resource for studying equity, retention, and academic performance in Colombian higher education.
DOI: 10.17632/35hhxm63z3
title: Numerical evaluation of harmonic polylogarithms

description: Abstract Harmonic polylogarithms H(a→;x), a generalization of Nielsen's polylogarithms S_(n,p)(x), appear frequently in analytic calculations of radiative corrections in quantum field theory. We present an algorithm for the numerical evaluation of harmonic polylogarithms of arbitrary real argument. This algorithm is implemented into a FORTRAN subroutine hplog to compute harmonic polylogarithms up to weight 4. Title of program: hplog version 1.0 Catalogue Id: ADPG_v1_0 Nature of problem Numerical evaluation of the harmonic polylogarithms up to weight 4 for arbitrary real argument. These functions are emerging in Feynman graph integrals involving more than one mass scale. Versions of this program held in the CPC repository in Mendeley Data ADPG_v1_0; hplog version 1.0; 10.1016/S0010-4655(01)00411-8 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.17632/rfp4c7gv95
title: The Impact of Cryptocurrency on Traditional Financial Markets

description: This research explores the impact of cryptocurrency on traditional financial markets, with a focus on how banking systems, payment methods, and market dynamics have been transformed by the rise of digital currencies like Bitcoin and Ethereum. By comparing the decentralized nature of cryptocurrencies to the regulated structure of traditional financial markets, the study highlights key areas of disruption. These include changes in transaction methods, the introduction of blockchain technology, and shifts in investor behavior. Furthermore, the research examines the role of behavioral economics, exploring how cryptocurrencies have altered perceptions of money, value, and risk in both institutional and individual contexts. The paper also investigates the regulatory challenges posed by cryptocurrencies and their potential influence on the future of global financial markets. The findings suggest that while cryptocurrencies offer innovative solutions, their volatility and lack of regulation present significant challenges to traditional market structures.
DOI: 10.6084/m9.figshare.21814602.v2
title: Genotypes and phenotypes of rainbow trout

description: This dataset is composed of 10 files. <br> 2 files are the <strong>raw genotypes (Trout_CD.ped) and map (Omykiss_57K.map)</strong> obtained with the 57K SNP Axiom Trout Genotyping Array in PLINK 1.9 format prior to quality control filtering after SNP calling with Axiom Analysis Suite. <strong>Files containing both challenged offspring and fish from the previous generation (including parents)</strong> <br> 3 files (<strong>Trout_CD.bed ; Trout_CD.bim ; Trout_CD. fam</strong>) are the genetic data in PLINK 1.9 binary format after quality controls <strong>of the challenged fish (2,874 offspring).</strong> <br> 1 file (<strong>Trout_CD_phenotype.txt</strong>) is a table of <strong>phenotype</strong> and covariates for the challenged fish. <br> 1 file (<strong>Trout_CD.pedigree</strong>) is the <strong>pedigree file </strong>with ID, Sire, Dam, Sex. <br> 3 files (<strong>AquaImpact_trout_all.bed, .bim .fam</strong>) are the genetic data in PLINK 1.9 binary format, after quality control of <strong>both offspring and fish from the previous generation</strong> (including parents) used for imputation of the ossfpring genotype. <strong>3,435 individuals</strong>
DOI: 10.17632/8k9bmpb972
title: Vocabulary Data in Central Javanese Folk Myths

description: Data was collected from 9 cities/districts in Central Java Province, Indonesia and was conducted through literature review, interviews with cultural experts and local community leaders, and documentation of oral traditions between January-December 2024.
DOI: 10.17632/p9b62ck834
title: Experimental dataset of biochar improved soil

description: The dataset contains 113 sets of data and is intended for the training of machine learning models. The data include the chemical properties of biochar (e.g., pH, cation exchange capacity,electrical conductivity), experimental time, amount of biochar added, soil properties before and after improvement(e.g., pH, cation exchange capacity,electrical conductivity), and pH value. The dataset covers a variety of biochar types and soil types, and the types of biochar come from a wide range of sources, involving a variety of organic wastes and agricultural and forestry wastes, among which the soil is mainly divided into weakly acidic, weakly alkaline and neutral. The action time of biochar is uniformly measured in days, and its mass fraction (wt%) represents the ratio of biochar to soil mass. This study provides an accurate numerical basis for the analysis of the effect of biochar on soil improvement. These diverse data provide rich information support for the study of the application effect of biochar.
DOI: 10.17632/s58z23mvpw
title: ANALYSIS OF DATA ON ANTIMICROBIAL USE AND THE OCCURRENCE OF ACUTE RENAL INJURY IN PATIENTS ADMITTED TO A HOSPITAL IN WESTERN PARÁ, BRAZIL

description: In hospital units, the evaluation and pharmaceutical follow-up of medical prescriptions is an important source for pharmaceutical care and pharmaceutical clinical services (BATISTA, 2014; BERNARDI et al., 2014). One common problem that has high hospital incidence rates is the occurrence of acute kidney injury (AKI) (MELLO et al., 2021). Pharmacovigilance among other activities is implemented in hospitals for the purpose of receiving and monitoring reports of adverse effects related to medications administered to patients (PEZATO et al., 2015). The survey evaluated the incidence of acute kidney injury in patients hospitalized and exposed to antimicrobials in a public hospital in the state of Pará, Brazil. A prospective and observational cohort was carried out, whose outcome of interest is the occurrence of AKI in patients admitted to the hospital between October 2018 and January 2019. The data were recorded and stored in a database, then descriptive analysis was performed in the GraphPad Prism 6.0 program. Quantitative variables were expressed as standard deviation (SD) of the mean and the number of cases as a percentage. We collected data from 70 patients who were admitted to the hospital and needed to use any of the antimicrobials selected in the observation period during hospital treatment. The survey results showed that mostly male (64.29%; n = 45). Age ranged from 19 to 96 years, with a mean of 52.49 years (SD = 20.31). The patients included were mostly from the oncology clinic (34.29%; n = 24) those that had had surgery (27.14%; n = 19). Most critically ill patients admitted to the adult ICU (26.47 %; n = 9) developed AKI. Regarding the number of medications used by patients, there was a variation from 5 to 17, with a mean of 10.26 (SD = 2.90) medications prescribed per patient. In the data regarding the antimicrobials, most patients took ceftriaxone (n = 29), cefepime (n = 27) and piperacillin/tazobactam (n = 23). In terms of the number of antimicrobials prescribed per patient, 60% (n = 42) of patients took only one, 30% (n = 21) took two and 10% (n = 7) took three or more antimicrobials for treatment of infections. The plasma concentrations of vancomycin ranged from 3.0 μg/mL to 22.5 μg/mL. Of the 10 samples collected, 10.0% (n = 1) were above the therapeutic range established by the literature (between 10 to 20 µg/mL), 30.0% (n = 3) were within the reference values and 60.0% (n = 6) of the patients had values below the reference values. Patients who developed AKI (60.0%; n = 6) during vancomycin use had concentration values between 3 µg/mL and 15.9 µg/mL, most of whom had values below the recommended therapeutic range. Of these patients with AKI, 83.33% (n = 5) used more than one nephrotoxic antimicrobial during hospital treatment. The concentrations of patients who were not diagnosed with AKI (40.0%; n = 4) ranged from 3.0 µg/mL to 22.5 µg/mL.
DOI: 10.17632/y6y4j4k3vx
title: Survey Questionnaire

description: The suvey is mainly conducted in a scientific manner which includes an empirical approach of collection of data. This includes a circulation of a questionnaire based on the research questions, one to one interaction with teachers, management of the school, students and their parents to analyse the effectiveness of the e- tools and techniques of online education. it was concluded on 153 samples (Students and teachers). Additionally, 31 more responses were collected through a face to face interview to take the views of school management and parents on whether they are satisfied or not satisfied with this new regime. 
Sample size: Initial sample size of the study was 160 (including teachers and students and for last research question even parents and school management was also on count) using various internet tools but responses of questionnaires were found invalid due to several reasons so the actual sample size reduced to 153 (Students and teachers) and 31 (School management and parents).
Data collection tools: This study was basically based on primary data collected using a structured questionnaire and interview techniques, administered to 184 respondents (153 and 31).  
Data analysis tool:  A demographic presentation through tables and charts.
DOI: 10.6084/m9.figshare.13187141.v1
title: Supplementary Material for: Clinical Outcomes of Proximal Gastrectomy versus Total Gastrectomy for Proximal Gastric Cancer: A Systematic Review and Meta-Analysis

description: <b><i>Introduction:</i></b> The extent of optimal gastric resection for proximal gastric cancer (PGC) continues to remain controversial, and a final consensus is yet to be met. The current study aimed to compare the perioperative outcomes, postoperative complications, and overall survival (OS) of proximal gastrectomy (PG) versus total gastrectomy (TG) in the treatment of PGC through a meta-analysis. <b><i>Methods:</i></b> We systematically searched PubMed, Embase, The Cochrane Library, and Web of Science for articles published in English since database establishment to October 2019. Evaluated endpoints were perioperative outcomes, postoperative complications, and long-term survival outcomes. <b><i>Results:</i></b> A total of 2,896 patients in 25 full-text articles were included, of which one was a prospective randomized study, one was a clinical phase III trial, and the rest were retrospective comparative studies. The PG group showed a higher incidence of anastomotic stenosis (OR = 2.21 [95% CI: 1.08–4.50]; <i>p</i> = 0.03) and reflux symptoms (OR = 3.33 [95% CI: 1.85–5.99]; <i>p</i> &lt; 0.001) when compared with the TG group, while no difference was found in PG patients with double-tract reconstruction (DTR). The retrieved lymph nodes were clearly more in the TG group (WMD = −10.46 [95% CI: −12.76 to −8.17]; <i>p</i> &lt; 0.001). The PG group was associated with a better 5-year OS relative to TG with 11 included studies (OR = 1.35 [95% CI: 1.03–1.77]; <i>p</i> = 0.03). After stratification for early gastric cancer and PG with DTR groups, however, there was no significant difference between the 2 groups (OR = 1.35 [95% CI: 0.59–2.45]; <i>p</i> = 0.62). <b><i>Conclusion:</i></b> In conclusion, PG was associated with a visible improved long-term survival outcome for all irrespective of tumor stage, while a similar 5-year OS for only early gastric cancer patients between the 2 groups. Future randomized clinical trials of esophagojejunostomy techniques, such as DTR following PG, are expected to prevent postoperative complications and assist surgeons in the choice of surgical approach for PGC patients.
DOI: 10.6084/m9.figshare.26086264.v1
title: Vertebrate taxonomic and functional hotspots in the Brazilian Atlantic Forest - FILES

description: The dataset has all the shapefiles, raster, tables, codes, appendices, supplementary materials and other necessary files to replicate all analysesin the manuscript. <b>Vertebrate taxonomic and functional hotspots in the Brazilian Atlantic Forest</b> (2024) is published in the Diversity & Distribution
DOI: 10.17632/jhgnxz25n8
title: Exploring factors contributing to student dropout: A case study of IBB University

description: -The reality of dropout 
In order to study the reality of dropout at IBB University, data related to the following colleges was used (Human Medicine, Dentistry, Engineering, Science, Agriculture, Literature, Management sciences, Education_IBB, Education_Alnadira and Quality Law) from (2017/2018) to (2020/2021). This data includes the number of enrolled students and the number of dropout students (Withdrawn and Suspended). 

-Factors of dropout 
The questionnaire was designed, which consists of 24 factors distributed over five axes: economic, academic, social, cultural, and psychological-health. Data were collected from 161 students from undergraduate programs in the Faculty of Science at IBB University.
DOI: 10.17632/zhtvkny53n
title: Medicinal Products in Bangladesh - A Dataset of Generic and Brand Names, Dosage Strengths, and Manufacturers

description: This dataset provides detailed information on medicinal products available in Bangladesh, including generic names, brand names, dosage strengths, and manufacturers. It is designed primarily to fine-tune open-source large language models, such as LLAMA, GPT-Neo, BLOOM, and others, with country-specific pharmaceutical data. By utilizing this dataset, researchers and developers can enhance models' capabilities to provide accurate, localized insights into the pharmaceutical sector in Bangladesh. The dataset is also suitable for healthcare policy research and analysis of drug manufacturing trends in the region, making it a valuable resource for both AI development and pharmaceutical studies.
DOI: 10.6084/m9.figshare.28485518.v1
title: <b>Public Perceptions and Engagement on Personalized Medicine: A European Survey</b>

description: The database comprises data from a pan-European survey aimed at examining public perceptions, usage patterns, and engagement with personalized medicine. It includes responses on health app usage, attitudes toward data sharing, privacy concerns, and various sociodemographic factors. This resource provides a detailed look at how individuals across Europe interact with digital health solutions and their willingness to engage with mHealth technologies. Data was collected via a structured online survey disseminated across multiple European countries. Anonymized responses were obtained following ethical protocols and informed consent procedures, ensuring data protection compliance. The survey instrument was designed to capture multidimensional aspects of mHealth engagement. It included sections on personal demographics, frequency and types of health app usage, levels of trust in digital health solutions, and attitudes toward sharing personal health data. Variables include age, gender, educational attainment, and country of residence, allowing users to conduct stratified analyses of the data. The primary dataset is provided in CSV format, which is accompanied by a comprehensive data dictionary detailing each variable, its coding, and relevant metadata to support reproducibility and transparency.
DOI: 10.17632/p8sc2x2cg8
title: Burnout, work-related daily negative affect and rumination: A mediation model combining an intensive and longitudinal design

description: The study aims to examine the relationship between daily negative affect and rumination in the context of work, and to verify their mediating role in the development of burnout. A classical longitudinal design was combined with ten-day online daily measurements among 235 civil servants. A random intercept cross-lagged panel model was implemented. From a within-person perspective, carryover, spillover and synchronic relationships between work-related negative affect and rumination were analysed. At the between-person level, a mediation model of the random intercepts of negative affect and rumination between two burnout measurements was tested.
DOI: 10.17632/r4vwy2j852
title: AM Simulation Data 

description: Here we present an AM simulation data generated from Autodesk Netfabb Local Simulation, a non-linear finite element thermo-mechanical solver for additive manufacturing (AM) processes. The dataset contains two simulation trials based  on Ti-6Al-4V material under various processing conditions. The simulation software generates fine-scale thermal data of laser scanning path and corresponding mechanical properties data across all time frames. Each dataset contain timestep folders and all related thermal and mechanical properties data can be found within timestep folders.
DOI: 10.6084/m9.figshare.6874871.v9
title: EEG anticipation of random high and low arousal faces and sounds

description: Materials related to the paper "EEG anticipation of random high and low arousal faces and sounds" available at https://f1000research.com/articles/8-1508/v2<br>Auditory stimuli must be requested to the corresponding author due to copyright restrictions.<br>It also includes the Extended data related to the paper "Applying machine learning EEG signal classification to emotion‑related brain anticipatory activity" <br><br>
DOI: 10.17632/rgpf24tbs2
title: Banana_Corupá_Inflorescence_Bracts_Dataset

description: Relevant raw data about bioactive compounds from the inflorescence bracts of Brazil's Sweetest Banana (Musa acuminata Cavendish) ". Data for antioxidant capacity analysis with the respective curve; standard curves of essential fatty acids and reading area of ​​each sample; LOD, LOQ, means, and standard deviations of the analysis of phytochemical compounds; Extraction curves for MAE, PLE, and SFE for the solvents: water, ethanol and ethanol and water mixture.
DOI: 10.17632/rzjww3vdxt
title: Advanced Dataset on Money Plant Diseases for AI Pathology Research

description: 1. The horticulture industry places a high value on money plants because of their hardiness and aesthetic attractiveness. Nevertheless, several illnesses might have a substantial negative influence on their well-being and output, making cultivation difficult. For a therapy to be effective, leaf diseases must be accurately and quickly identified. High-resolution photos of money plant leaves were taken at the Savar demonstration site in Dhaka, Bangladesh, and are included in this dataset. The photos are divided into three different classes: Manganese Toxicity (596 images), Bacterial Wilt Disease (576 images), and Healthy (700) images. These classes represent both damaged and healthy leaves. The dataset has 2100 images in total. Comprehensive comments that describe the nature and severity of the condition are included with every photograph. For accurate and trustworthy model training and validation, this data is essential. The information also contains metadata that records the location and surrounding circumstances at the time the photograph was taken. Understanding the environmental factors influencing the prevalence of disease and enhancing the accuracy of predictive models require this contextual information.
2. At the moment, there are a lot of potential deep learning and computer vision techniques to handle these kinds of categorization and detection problems.
3. To create deep learning techniques, an extensive money plant disease dataset is provided. The subject matter expert from an agricultural institute collaborated with us to construct the classifications for this dataset.
4. From the Savar demonstration place in Dhaka, Bangladesh, a total of 1872 images depicting Bacterial Wilt Disease (576), Healthy (700), and Manganese Toxicity (596) were collected. Then, using methods like flipping, width shifting, height shifting, brightening, rotating, shearing, and zooming, 6000 augmented images are made from these original photos to increase the quantity of data sets.
DOI: 10.6084/m9.figshare.14745435.v1
title: MEGNET-mp-2019-04-01 JARVIS-Atoms format

description: Megnet training dataset (mp-2019-04-01 ) with pymatgen structures converted into jarvis.core.Atoms