cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/pktxwdvcbz.1
title: Exercise Training Remodels Inguinal White Adipose Tissue Through Adaptations in Innervation, Vascularization and the Extracellular Matrix_Raw data

description: The deposited data is presented in the manuscript by Nigro P. & Vamvini M., et al., with the title " Exercise Training Remodels Inguinal White Adipose Tissue Through Adaptations in Innervation, Vascularization and the Extracellular Matrix". Visium data in the format of Space Ranger output can be found for each individual section analyzed, which contains raw and filtered count matrices and spatial/image data. Sample metadata contains information for each sample with linked subject information. Seurat objects containing the downstream analyses can be found as well, which for instance contains the spot clustering information presented in the article. Output data from the stereoscope analysis described in the article can be found here as well.
These are raw data and script referred to normalized data published with DOI:10.17632/r6v7yktxnt.1
DOI: 10.17632/cy3d9vr2f4.1
title: Prevalence of depression, stress and anxiety in students.

description: The objective of this study was to assess prevalence of depression, anxiety and stress among college going physiotherapy students. This was an online survey and the sample was collected using DASS-21 through google forms. The sample size was calculated through a formula by putting p value and calculated sample size was 140. After sample collection result was obtained by DASS-21 scoring and it revealed the prevalence of anxiety was extremely severe among undergraduates.
DOI: 10.17632/rfbp7xchn9.1
title: Sustainable Leadership Research Dataset (1998-2019)

description: The Sustainable leadership research & publication dataset, which was indexed by Scopus from 1998 to 2019. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/2vk5khfn6v.2
title: MID: Medicines Information Dataset

description: Numerous studies on medicines are conducted day by day. To address shortcomings of medicines information generation, prediction, and classification models, the authors introduce a large medicines information dataset of textual data. For this motivation, the authors named our dataset ‘MID’.

• Value of the data
 - MID is the largest, to our knowledge, available and representative Medicines Information Dataset (MID) for a wide variety of drugs. It includes the names of over 192k medicines, making it a comprehensive collection of pharmaceutical products.
 - MID is the largest, making it robust for generating information about drugs such as indications or interactions.
 - MID offers over 192k rows distributed in 44 variety therapeutic classes, making it robust for drug classification to therapeutic label.
 - MID provides accurate, authoritative, and trustworthy information on medicines for enhancing predictions and efficiencies in clinical trial management.
 - MID includes details such as drug names, information URL, salt composition, drug introduction, therapeutic uses, side effects, drug benefits, how to use of drug, how to use of drug, how drug works, quick tips of drug, safety advice of drug, chemical class of drug, habit forming of drug, therapeutic class of drug, and action class of drug. This dataset aims to provide a useful resource for medical researchers, healthcare professionals, drug manufacturers, data scientists, and enthusiasts interested in exploring the world of medicines and healthcare products.
 - In contrast with the few small available datasets, MID's size makes it a suitable corpus for implementing both classical as well as deep learning models.

• MID.xlsx provides the raw data, including medicine information. The data collected to ensure an acceleration and save experimental efforts for medicines through help in predicting or generating or classifying of medicine information preclinically. 

• Therapeutic_class_counts.xlsx is summarize distribution of medicines per therapeutic class.
DOI: 10.17632/kkr4yhfm7v.2
title: Zhang et al IO wtCaCO3%

description: The data file provides coordinates, depth, wtCaCO3% of the surface/coretop marine sediments in the Indian Ocean and the sources for the data, as well as corrections we made based on the source of information.
DOI: 10.17632/w5tj2typgw.1
title: Computer Assisted Language Learning Research Data

description: The computer assisted language Learning reseach & publication dataset, which was indexed by Scopus from 1983 to 2020. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/dvmz6pkzvb.4
title: BigMHC Training and Evaluation Data

description: All training and evaluation data used in the BigMHC study

(https://doi.org/10.1101/2022.08.29.505690).

All code is freely available at https://github.com/KarchinLab/bigmhc 

--------------------------------------------------------------------------------
CSV Columns

mhc - MHC-I allele
pep - peptide sequence if epitope data or mutated peptide sequence if neoepitope data
tgt - target value of 1 (presented/immunogenic) or 0 (non-presented/non-immunogenic)

manafest.csv columns also include wtp (wild-type peptide) and gene (the name of the mutated gene)

pseudoseqs.csv columns include the MHC-I allele along with the index and amino acid of the aligned positions.

All other columns are the outputs of MHC-I epitope presentation and immunogenicity predictors. -------------------------------------------------------------------------------- 

datasets.zip contains the curated training, validation, and testing datasets along with a summary of the number of negatives and positives for each allele in each dataset (summary.csv):
- el_test.csv - epitope presentation evaluation data and all evaluated model predictions
- el_train.csv - epitope presentation training data
- el_val.csv - epitope presentation validation data
- im_test.csv - immunogenicity transfer learning evaluation data and all model predictions
- im_train.csv - immunogenicity transfer learning training data
- im_val.csv - immunogenicity transfer learning validation data
- iedb.csv - infectious disease epitope evaluation data and all model predictions
- summary.csv - table of positives and negatives across each allele for each dataset

- manafest.csv - neoepitope immunogenicity data validated using MANAFEST assays

- pseudoseqs.csv - one-hot encoded MHC representations

el.csv.zip contains the predictions of the BigMHC production models and all other methods on all EL data (train, val, test). The pMHCs were filtered so that all other methods can score them (e.g. peptide lengths 8-11).

eltrainval_models.zip contains the the models used to evaluate BigMHC on el_test.csv (the production models can be found in the GitHub repository)
-------------------------------------------------------------------------------- 

sha256 sums are below:

datasets.zip - 0d152a452756cf2e0014ffced6afc25118e7c11cf1f626b26e49f50f79edffaa
el.csv.zip - cb94b42406b96a3b13d941cf87dd43f4f53e9ebfbc3d1619f0e43327f1fb6395
eltrainval_models.zip - e8500173cb2afbe5f8e8c0ebc60785c0de6d91aab622f8b83fff3b4e65b43223
manafest.csv - accf19b8bb797ec842c3ee1b1ce1966feb35035df746f7a56b2994403ba1ad99
pseudoseqs.csv - cd1fa24fb4c9fc0ee592a3d753458c4e3abed0d5cc4ca76e325aa274df8e900a
DOI: 10.17632/5k773sxkcw.1
title: Integrative Omics Indicate FMRP Sequesters mRNA From Translation and Deadenylation In Human Neuronal Cells. Kurosaki et al

description: Unprocessed and uncompressed imaging data used in Kurosaki et al.
DOI: 10.17632/zf4dc6xj35.1
title: GravPack V.09 & Test Data

description: ZIP file include the main MATLAB script (gravpack.m), two data files for testing (menderes765.dat and AM.dat) and a folder called "lang" to contain language files (LANG_English.xlsx as default).
DOI: 10.17632/rczv8w3zm2.1
title: Risk of Exercise Addiction and Passion in Three Exercise forms After Controlling for Exercise Volume and Intensity

description: This is an online study of 424 exercisers who trained in aerobic, anaerobic or mixed (both, represented by CrossFit practitioners) forms of exercise. The study aimed to uncover whether after controlling for exercise volume and intensity there are differences between these three groups in passion and the risk of exercise addiction.
DOI: 10.17632/8ftcb2v4d8.2
title: Indian Ministry of Health and Family Welfare's annual yearbooks (1970-2000)

description: Digitalization of state-level information from the Indian Ministry of Health and Family Welfare's annual yearbooks, for the period 1970-71 to 2000-01. This work was financially supported by CEPREMAP.
DOI: 10.17632/8hrj49fthr.2
title: Data from Simbriger et al. Progress in Neurobiology 2020

description: Pathway Analysis and RNAseq (RPF and total RNA *bam *bai files)
DOI: 10.17632/6sbv7bpj5n.1
title: Proteogenomic Analysis of Salivary Adenoid Cystic Carcinomas Defines Molecular Subtypes and Identifies Therapeutic Targets

description: Data and code for "Proteogenomic Analysis of Salivary Adenoid Cystic Carcinomas Defines Molecular Subtypes and Identifies Therapeutic Targets"
DOI: 10.17632/9fp8w335xf.1
title: Data for: Utilizing Historical Data for Corporate Credit Rating Assessment

description: The dataset consists of 901 publicly-traded firms with 28 financial features that came from Quarterly reports.The financial features were collected from Bloomberg, a major financial institution which provides the financial data service in North America. The credit ratings of the firms were obtained from Standard and Poor's (S\&P); ; a total of 22 grades that are ordered from AAA rating, the most promising for investors, to D rating, the most risky one.
DOI: 10.17632/9mtjwg54zr.1
title: Indicadores Económicos

description: La Junta de Planificación produce y recopila indicadores económicos que sirven para medir y visualizar la actividad económica de Puerto Rico. Los indicadores incluyen datos históricos de variables como (1) grupo trabajador, (2) empleo y desempleo, (3) turismo, (4) construcción, (5) energía eléctrica, (6) ingresos netos al Fondo General, (7) comercio exterior, (8) quiebras por capítulos, (9) ventas al detalle, (10) índice de precios al consumidor y (11) precio promedio mensual de la gasolina al detal. Las tablas que se publican presentan información comparativa de los cambios absolutos y porcentuales de mes a mes y respecto al año anterior (las series se presentan sin ajustes estacionales, para cada año fiscal y para el año natural). Igualmente, se publican documentos y gráficas de series históricas seleccionadas.
DOI: 10.17632/75wgtgdk3d.1
title: Raw data for the study of cybersickness and sensory conflict theory using a motion-coupled virtual reality system

description: Includes: 1. Scores of Simulator Sickness Questionnaire 2. Scores of Misery Scale and Joyfulness Scale
DOI: 10.17632/2ndzc6nwpx.1
title: Dataset of original studies on schoolteachers' or pupils' real-life experiences, attitudes, and knowledge of epilepsy and seizures

description: This dataset contains results of a structured analysis of original papers (English-language articles published between 2004 and 2024) reporting questionnaire surveys aimed at examining the real-life experiences, knowledge, and attitudes of schoolteachers or pupils towards epilepsy and seizures. The dataset table collected the following data (sheet #1 "Dataset"): information about the author(s), year of publication, study geography, sample size, numbers and/or percentages of subjects who ever witnessed a seizure, who ever provided first aid for seizures, who expressed their willingness to give first aid to a person with seizures, who supposed they know how to/able to give first aid to a person with seizures, who received training on first aid for seizures, and who wished to learn first aid for seizures, as well as the number and/or percentage of subjects who considered certain actions appropriate to help the person with seizures. Sheet #2 ("Bibliography") of the dataset file contains a full bibliography of the publications included in the analysis.
The dataset was utilised for performing the related scoping review.
DOI: 10.17632/h2fvn2mpp3.1
title: LC-MS/MS amino acids quantification in a yeast conditioned medium

description: Amino acids in CDM35 medium conditioned with five different S. cerevisiae strains. Only amino acids not present in CDM35 were quantified. Concentrations are given in nM, corresponding OD600 values are also provided.
DOI: 10.17632/wb3ndt69gf.1
title: Dataset from the US Peer-to-peer Lending Platform with Macroeconomic Variables

description: We aggregate the United States (US) state-level data with LendingClub's loan book covering the period from 2008–2019. LendingClub is a FinTech lending company that provides loans through technology-driven platform. It was one of the pioneering and leading US peer-to-peer (P2P) lending platforms. Our dataset consists of over two million observations (N=2,703,430) with diverse loan, borrowers and state specific features. We provide the description of variables, descriptive statistics, and STATA code with the full dataset. The US possesses significant cross-state variation in terms of economic and demographic characteristics while having risk-sharing policies in the federal level to protect states' creditworthiness. This unique feature of our combined database creates an ideal opportunity to explore the P2P lending market within the context of macroeconomic variables. As the dataset covers 12-year period for all US states, it enables further cross-sectional and longitudinal analyses of FinTech lending market.
DOI: 10.17632/7h6p2hf65f.1
title: Business model innovation in family firms

description: Data from 112 family firms representative of the regional economy are presented. The companies are also associated with the Murcian Association of Family Businesses (Amefmur). The collaboration with this organization has made it possible to obtain very valuable and representative information thanks to the support provided. The collection of information was carried out through an electronic survey. These data could be especially useful for establishing business recommendations for this type of companies and for analyzing other possible interrelationships of the variables available in the database
DOI: 10.17632/byfp5y3x6b.1
title: Inclusive Economics Growth Determinants

description: This research focuses on inclusive economic growth and its determinants in Indonesia. It uses the yearly data from 2015 until 2021 in 34 provinces of Indonesia. The scope of this study includes inclusive growth, human capital development in term of health and education, public investment and private investments.

Meanwhile, the type of research data in this study is secondary data taken from the Central Bureau of Statistics and the Directorate General of Financial Balance (DPJK). The data used is annual data. Then, the term inclusive economic growth in this study borrows the definition by UNDP (Kjøller-Hansen & Sperling, 2020) Growth is beneficial and involves all levels of society, focusing on employment as an indicator of inclusive growth.
 
Since the concept of inclusive growth relates to economic growth in term of GDP and also the inclusion in the process and outcome of growth, this study accordingly utilizes log of GDP per person employed as a proxy for inclusive growth. The variable log of GDP per person employed represents the average participation opportunities available to the population and how those opportunities are distributed within the population.  Central Bureau of Statistics defines GDP growth per person employed as the average real GDP growth rate compared to the number of people employed yearly. The higher the GDP growth rate per person employed, the higher the region's inclusive growth. This study used real GRDP because of the study units at the provincial level. In addition, real GRDP or GRDP at constant prices eliminates the effects of inflation on economic growth.

Furthermore, this study uses high school attainment rate as the proxy for education level in correspondence to the reviewed literature. Meanwhile, the health level variable is defined as the percentage of population with chronic and acute health complains in a month. The higher the health complains, the lower health quality level in a population. Moreover, the public investment is represented by log of realized government capital expenditure and the private investment is measured by the log of sum of realized foreign direct investment and domestic investment. In addition, structural transformation is represented by the proportion of formal sector workers in percentage, while trade openness is measured using the proportion of sum of export and import, both international and interprovincial ones, to GDP. 

The finding of this research shows that high school graduation rate, private investment, trade openness and formal sector employment have statistically positive and significant impacts on inclusive growth. Meanwhile, health complains has a negative and significant impact on inclusive growth. In addition, public investment has a negative and insignificant impact on inclusive growth. The findings of this study underscore the importance of human development, infrastructure development and structural transformation as policy areas of focus for inclusive growth.
DOI: 10.17632/5839k8vdzx.1
title: Neotectonic subsidence along the Cenozoic Kunlun fault (Tibetan Plateau)

description: Data refer to grain size and LOI data against calibrated ages
DOI: 10.17632/yd9vp3ddy3
title: biochar-amended loess

description: This data provides the results of the triaxial tests, including consolidated drained shear tests and consolidated undrained shear tests, conducted on saturated biochar-amended loess specimens. The biochar used is derived from apple trees & branches, and the loess studied was collected from Shaanxi, China, and is a Malan loess.
DOI: 10.17632/749k3cwbnm.1
title: Dataset for Autism Diagnosis Based on DSM-5

description: Autism is a neurodevelopmental condition affecting individuals from childhood up to adulthood. Individuals living with Autism are said to be having challenges with cognitive, social, and communication skills. According to the DSM5 criteria, there are 3 levels of Autism: Level 1, Level 2, and Level 3. Knowing the severity level of an individual after diagnosis helps in providing the right therapy for the individual. Most research work has focused on the diagnosis of autism, as in discriminating autistic individuals from non-autistic individuals. Very few works have been done in classifying autism into its severity levels based on the DSM 5 criteria. In this study, we collected datasets from individuals based on the guidelines of the DSM5 criteria using the google forms questionnaire.
DOI: 10.17632/s48dkc6sxg.1
title: Dataset for “Blocking-like” effects in attentional set-shifting: redundant cues facilitate shifting in male rats with medial prefrontal cortex inactivation

description: Behavioural data presented in a paper with the title “Blocking-like” effects in the attentional set shifting task: redundant cues facilitate shifting in male rats with medial prefrontal cortex inactivation. The excel data sheet contains the raw, unprocessed data from an attentional set shifting task. This is a self-paced foraging task for the rat. Food is buried in one of two bowls that differ according to the media inside the bowl and the scent added to the media. In a single session on one day, the rat completes a series of two-choice discriminations to find the buried food. We inactivated medial prefrontal cortex and replicated a deficit in set-shifting seen after lesions of a comparable area. We then modified the task, introducing novel, predictive, but redundant cues prior to the shift stage. In this condition rats learned the subsequent set-shift discrimination more rapidly. Both results can be accounted for by a single impairment in the down regulation of attention to irrelevant cues. 
Each line in the Excel sheet corresponds to an individual 'trial' of an individual rat. The columns indicate treatment condition; stage of the test; progress through the stage; the exemplars in use; and whether the rat correctly identified the location of the food.
DOI: 10.17632/zh3wnddzxy.1
title: 10 Days DNS Network Traffic from April-May, 2016

description: Campus DNS network traffic consisting of more than 4000 active users (in peak load hours) for 10 random days in the month of April-May, 2016 is available in hourly PCAP files in the dataset. (At present only traffic for Day0(Full) and Day1(partial) could be uploaded due to 10GB data limit)
DOI: 10.17632/2pxd7nb54f.1
title: Inteligencia Artificial

description: Historia de la inteligencia artificial tomando en cuenta autores y evidencia.
DOI: 10.17632/vkpwndz8wr.2
title: Cross Correlation Function (CCF) Data Set and Methodology

description: In this data set, the dynamic causality relation between Turkey Credit default swaps (CDS) and BRICS countries (Brasil, Russia, India, China, South Africa) and most important EU economies (Germany, France, the UK, Italy, Spain) are analyzed with the Cross Correlation Function (CCF) approach. Cross Correlation Function (CCF) is a two-stage method. In the first stage, CDS of the countries are estimated with EGARCH models. In the second stage, the standardized residuals and squares obtained from the EGARCH models are used for causality test in the mean and variance for CDSs. In the data set, Excel formulas and EViews Outputs / Data set were shared.
DOI: 10.17632/8kj2rn7m9x.1
title: Dataset on Buy-Now-Pay-Later Adoption

description: This data contains the survey responses collected from 226 shoppers to understand their intention to adopt Buy Now Pay Later
DOI: 10.17632/b7c2h6cbc6.1
title: Multi-Modal User Modeling for Task Guidance (MUTMG): A Dataset for Real-Time Assistance with Stress and Interruption Dynamics

description: We introduce the Multi-Modal User Modeling for Task Guidance (MUMTG) to support the development of AI models for such purposes.
The dataset is created through human-subjects studies with users performing search and assembly procedures with help from virtual instructions provided by either a head-worn AR headset or a laptop screen.
The data-collection study uses a game-like scenario to guide participants through six guided tasks that vary in difficulty. Within each group, we manipulated task duration and induced several stress triggers to increase the task cognitive demand for three tasks. The dataset includes physiological data such as electrodermal activity, temperature, heart rate, pupil dilation, and gaze. We also collected subjective self-report ratings regarding task workload and emotional responses after each task. We offer this rich dataset as a valuable resource to facilitate the development of user models for task guidance in highly demanding contexts.