cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/tphtkn9c4y.2
title: Hair and Salivary Steroids in Men with AGA and Controls

description: Hair and saliva samples were collected in the receding hairline and occipital region of men with androgentic alopecia (AGA) and in frontal, temporal, mid-scalp, vertex regions of control participants. Saliva samples were collected immediately upon wakening from nocturnal sleep (0 min), 30 min after, and 60 min after awakening form the participants of both groups. Cortisol, testosterone, and dihydrotestosterone (DHT) levels in hair and saliva samples were determined using radoimmunoassay. The levels of steroids in hair and saliva samples in control participants and men with AGA were described in sheet of "Controls" and "Men with AGA" respectively.
In both sheets, ID represents the identification of each participant, Family history represents the present (1) or absence (0) of a family history of hair loss, and BMI represents body mass index.
DOI: 10.17632/sxtmmr6mvk.1
title: Surah Al-Ikhlas of the Holy Qur'an Error Detection Dataset

description: This dataset presents surah Al-Ikhlas (112th chapter of the Holy Qur'an) as a Standard Arabic data for the automatic detection of people's Quran recitation to determine whether their recitation is correct or not. The data (the sound of the reciter) were collected from 1-08-2021 to 1-09-2021 using Google forms and Qur’anic audio websites and then checked and labeled manually by 5 Qur’an experts. The data contain 1506 records. These data can be used to develop machine-learning and classification models to detect users’ Holy Qur'an (Standard Arabic) reading (recitation) mistakes.
DOI: 10.17632/4jmv6p4355.1
title: Data for: The Minimum Wage and Annual Earnings Inequality

description: STATA dataset
DOI: 10.17632/6gp8m72s9p.1
title: Indonesian Query Answering Dataset for Online Essay Test System

description: This data is related to Indonesian query answering system research for online essay examination system. This data is derived from the bachelor thesis work of Trisna Ari Roshinta, under the supervision of Faisal Rahutomo.
DOI: 10.17632/yfhgn8py5f.1
title: Dry Fruit Image Dataset

description: The "Dry Fruit Image Dataset" is a collection of 11500+ processed high-quality images representing 12 distinct classes of dry fruits. The 4 dry fruits—Almonds, Cashew Nuts, Raisins, and Dried Figs (Anjeer)—along with 3 sub-types of each are contained in the sub-folders, making a total of 12 distinct classes. These pictures were taken with a high-definition camera on cell phones. The dataset contains images in different lighting conditions as well as with different backgrounds. This dataset can be used for building machine learning models for the classification and recognition of Dry Fruits, requiring neat, appropriately tagged, and high-quality images. The dry fruit classification algorithm can be trained, tested, and validated using this dataset. Furthermore, it is beneficial for dry fruit research, education, and medicinal purposes.
DOI: 10.17632/gxc6j5btrx.1
title: Wind and solar power generation dataset

description: This dataset contains time-series data for analyzing and predicting wind and solar power generation. The data comes from wind farms and photovoltaic power plants in a certain location, covering detailed meteorological and power generation data for multiple quarters.

Dataset Usage:

Power generation prediction: This dataset can be used to train and evaluate machine learning models, especially deep learning models, to improve the prediction accuracy of wind and solar power generation.

Renewable energy management: helps optimize the scheduling of wind and solar power generation and improve the stability of grid connection.

Research analysis: Support academic research on the impact of meteorological conditions on renewable energy generation, and help understand the relationship between seasonal changes and power generation performance.

Content description:

Wind power data:

Input features: wind speed, air density, etc.
Output variable: Wind power generation.
Data frequency: recorded every hour.
Photovoltaic data:

Input features: temperature, humidity, ground irradiance, atmospheric irradiance, etc.
Output variable: photovoltaic power generation.
Data frequency: recorded every hour.
DOI: 10.17632/rdr2vkszrc.1
title: Thermal image dataset of construction workers unsafe actions

description: Title of Dataset:Thermal image dataset of construction workers unsafe actions

Description of the Data and file structure:This dataset consists of 2000 thermal images of construction workers' acitons. There are 500 safe actions (climbing with two hands) and 1500 unsafe actions (climbing with one hand, reaching far, and standing). The image size is 200 × 200 pixels.
DOI: 10.17632/skfg3w7wdm.1
title: Data to assessment of current and future land use/cover changes in soil erosion in the Rio da Prata basin (Brazil)

description: These data are to assessment of current and future land use/cover changes in soil erosion in the Rio da Prata basin (Brazil):

Digital elevation model (raster): DEM_SRTM.rar
Rainfall erosivity index (R) (raster): FACTOR_R.rar
Soi erodibility (raster): FACTOR_K.rar
Land-use/Land-Cover (raster): FACTOR_LUC.rar
Watershed: BASIN_BOUNDARY.rar
Biophysical table for 2016, 2050 and 2100 (csv): biophysical table _2016.csv
Biophysical table for 1986, 1999 and 2007 (csv): biophysical table _1986_1999_2007.csv
DOI: 10.17632/2gkg7vvcrm.3
title: A Brazilian dataset for screening the risk of the Chronic Kidney Disease

description: We collected the medical data (60 real-world medical records) from physical medical records of adult subjects (age ≥ 18) under the treatment of University Hospital Prof. Alberto Antunes of the UFAL, Brazil. The data collection was approved by the Brazilian ethics committee of the Federal University of Alagoas, approval number 47350313.9.0000.5013. The 60 real-world medical records are related to the four risk classes: low risk (30 records), moderate risk (11 records), high risk (16 records), and very high risk (3 records). An experienced nephrologist, with more than 30 years of CKD treatment and diagnosis in Brazil, labeled the risk classification based on the KDIGO guideline. We only translated the dataset to English and converted the gender of subjects from string to a binary representation to enable the usage of different machine learning algorithms. We augmented the dataset to decrease the impact of imbalanced data and improve the data analysis (more 54 records) by duplicating real-world medical records and carefully modifying the attributes, i.e., increasing each CKD biomarker by 0.5. We selected the constant 0.5 with no other purpose than differ the instances and maintain the new one with the same label as the original. The augmented data was also reviewed by the experienced nephrologist to increase confidence in the data augmentation. The dataset does not contain duplicated and missing values. Therefore, we provide two datasets: original and augmented.
DOI: 10.17632/68z25wzfbv.2
title: Russian Regional Knowledge Economy Index (Russian RKEI)

description: Grounding on the World Bank's Knowledge Economy Index indicators, the authors developed the Russian Regional Knowledge Economy Index (Russian RKEI).
DOI: 10.17632/6sg29rkxss.1
title: Dupilumab treatment improves signs, symptoms, quality of life and work productivity in patients with atopic hand and foot dermatitis: results from a phase 3, randomized, double blind, placebo-controlled trial

description: Contents
Plain Language Summary ....................................................................................................................... 2
Supplementary methods........................................................................................................................ 4
Supplementary Table I. Instruments used to assess efficacy outcomes .............................................. 11
Supplementary Table II. Endpoints pre-specified in the testing hierarchy .......................................... 14
Supplementary Table III. Additional baseline disease characteristics.................................................. 15
Supplementary Table IV. Use of rescue medication during the treatment period .............................. 16
Supplementary Fig 1. Study flow diagram. .......................................................................................... 17
Supplementary Figure 2. Patient disposition. ...................................................................................... 18
Supplementary Fig 3. (A) Percent change from baseline in HF-mTLSS over time through week 16. (B)
Percent change from baseline in weekly average of daily HF-Peak Pruritus NRS over time through
week 16. (C) Change from baseline in weekly average of daily HF-Peak Pain NRS over time through
week 16. (D) Percent change from baseline in HECSI score over time through week 16. (E) Proportion
of patients achieving HECSI-75 over time through week 16. (F) Change from baseline in percent
surface area of hand and involvement with AD over time through week 16. (G) Change from baseline
in QoLHEQ over time through week 16. (H) Change from baseline in weekly average of daily Sleep
NRS over time through week 16. .......................................................................................................... 19
Supplementary Fig 4. Time to first rescue treatment use during the 16-week treatment period....... 21
Supplementary Fig 5. Sensitivity analyses............................................................................................ 22
DOI: 10.17632/ymgfx4g9mc.2
title: Vaccination and confidence of events during Covid-19 in Malaysia

description: Vaccination and confidence of events during Covid-19 in Malaysia between the months of March and April 2021.
DOI: 10.17632/f6sjz6by8k.1
title: Brazilian datasets classified to support differential diagnosis of Severe Acute Respiratory Syndrome (SARS) caused by COVID-19 and influenza

description: The SIVEP-Gripe database contains 3,395,398 records with 166 attributes, covering the years 2020 to 2022. These records document cases of Severe Acute Respiratory Syndrome (SARS) caused by COVID-19, Influenza, other etiological agents, various respiratory viruses, and unspecified cases. Of the total records, 1,872,106 are related to SARS due to COVID-19, and 21,490 are related to SARS due to Influenza, highlighting the need for class balancing.

Four datasets were created with different balancing configurations:
* Balanced by age range (1BAR): The majority class was reduced to match the number of records in the minority class, based on age ranges. Specifically, records from the majority class were selected to match the minimum and maximum age ranges of the minority class.
* Balanced by age, sex, and same distribution (2BASD): For each record in the minority class, an equal number of records with the same sex and age were selected from the majority class.
* Balanced by age, sex, region, and same distribution (3BARD): This approach included balancing by region, in addition to age and sex.
* Balanced by age, sex, outcome, and same distribution (4BASED): This method balanced records by age, sex, and outcome (recovery or death) to maintain consistent distributions of these factors across both classes.

After preprocessing, all datasets retained 24 attributes and one target class, "classi_fin", where 1 represents SARS due to influenza and 5 represents SARS due to COVID-19.
These subsets were created to evaluate the performance of machine learning models during training.
DOI: 10.17632/k8mkczry5h.1
title: Impact of Conversational Chatbots on Learning of University Students

description: To examine the impact of conversational chatbots on electronic learning in Bulgaria, an online survey was conducted using a Google Forms-based questionnaire from May 14 to May 31, 2023. The survey link was distributed via email and social media to student organizations and groups, resulting in 131 complete responses during the study period. 
With the recent advancements in large language models, generative AI chatbots have gained popularity due to their enhanced capabilities in natural language processing. The majority of respondents (89%) reported having prior experience using conversational chatbots as an educational tool. The respondents evaluated their AI chatbot experience based on criteria such as frequency of use, perceived usefulness, trust and security, and facilitating conditions. The findings indicate that students who are aware of the capabilities and benefits of smart chatbots are more likely to use them frequently. 
The second part of this study aims to evaluate the effectiveness of educational chatbots in handling university learning tasks, particularly in the field of mathematics. Two mathematics tasks were chosen and solved using different conversational chatbots. Here we can find information about cases where chatbots make mistakes and the types of errors. Further analysis provides valuable insights into the efficacy of chatbots in supporting mathematics learning at the university level. Among the seven evaluated conversational chatbots, ChatGPT Plus demonstrated the highest overall performance.
DOI: 10.17632/h4df4mgrfb.3
title: Bearing run-to-failure datasets of UNSW

description: The run-to-failure experiments data were collected at the University of New South Wales in 2019-2020, regarding the development of bearing fault severity assessment methods.
The following journal paper [1] contains the description of the experiments and test rig information.
[1] H. Zhang, P. Borghesani, R. B. Randall, and Z. Peng, “A benchmark of measurement approaches to track the natural evolution of spall severity in rolling element bearings,” Mech. Syst. Signal Process., vol. 166, p. 108466, 2022, doi: 10.1016/j.ymssp.2021.108466.
Please consider citing this resource if relative to your work.

Data of four run-to-failure experiments, named Test 1 to 4 according to Ref. [1], are stored in four folders respectively.
Each folder contains two subfolders, one has all collected signals at 6 Hz, and the other has selected samples at 4 speeds (6,12,15,20 Hz).
Each data file is named as vib_aaaaaaaaa_bb.mat:
•	aaaaaaaaa: is the running cycle of the shaft in this measurement
•	bb: is the shaft speed in Hz

Each data file contains the following variables:
•	Fs: the sampling frequency
•	accH: acceleration (V) in horizontal direction
•	accV: acceleration (V) in vertical direction
•	enc1: encoder signal channel 1 (1024 pulses/rev)
•	enc2: encoder signal channel 2 (1024 pulses/rev)
•	loadCell: the applied radial load (V) on the test bearing
•	tacho: tacho signal of the shaft (1/rev)

For any further information, please contact the Author or the Tribology and Machine Condition Monitoring group of UNSW Sydney.

The version of datasets is updated due to the nomenclature issue of variables.
DOI: 10.17632/jwbpzzcx4t.1
title: The effects of adding nano ZrO2 in physical and some mechanical properties of cement paste

description: the effect of nano ZrO2 particles in cement paste dry density (g/cm3) the effect of nano ZrO2 particles in cement paste porosity the effect of nano ZrO2 particles in cement paste water adsorption the effect of nano-ZrO2 into compressive strength
DOI: 10.17632/t67pmwmsfw.1
title: Data for: Foraging decisions as multi-armed bandit problems: applying reinforcement learning algorithms to foraging data

description: Data for the manuscript "Foraging decisions as multi-armed bandit problems: applying reinforcement learning algorithms to foraging data". This is an excel file with 4 tabs, each containing the data set for a group size (i.e., 10, 25, 50, and 100 larvae).
DOI: 10.17632/zb7hwyj3hp.1
title: Insights into land plant evolution garnered from the Marchantia polymorpha genome, supplementary material

description: Supplementary material for: Insights into land plant evolution garnered from the Marchantia polymorpha genome. Marchantia genome Suppl. Phylogenetic analyses Table M1 Sporeling gene expression Table M2 LRR genes in Viridiplantae
DOI: 10.17632/bpxfvzxzg2.1
title: PCA-Chinese Stocks

description: We examine the prediction performance using a principal component analysis (PCA). In particular, we perform a PCA to identify significant factors (principal components) and then use these factors to form predictions of stock price movements. We apply this strategy on the Chinese stock markets. Using data from January 2, 2019 till September 16, 2021, the empirical results show substantial out-performances from the PCA-based predictions against a naïve buy-and-hold strategy and also single time-series predictions of individual stocks
DOI: 10.17632/bb7b8vtwry.4
title: Saudi Arabia Public Roads Visual Pollution Dataset 

description: Visual Pollution (VP) is the visible deterioration and bad aesthetic quality of the natural and human-made landscapes. It also refers to the disruptive occurrence that limits the movability of the people on the public roads such as excavation barriers, potholes, and dilapidated sidewalks. The real VP dataset is collected from the kingdom of Saudi Arabia (KSA) regions via the Ministry of Municipal and Rural Affairs and Housing (MOMRAH) and used to develop the proposed deep learning framework. 

If you are using this dataset for research purpose kindly cite the following papers: 

1. Article Paper: "AlElaiwi, Mohammad, Mugahed A. Al-antari, Hafiz Farooq Ahmad, Areeba Azhar, Badar Almarri, and Jamil Hussain. "VPP: Visual Pollution Prediction Framework Based on a Deep Active Learning Approach Using Public Road Images." Mathematics 11, no. 1 (2022): 186."

2. Data repository itself: AlElaiwi, Mohammad; Ahmad, Hafiz; Hussain, Jamil; Al-antari, Mugahed; Almarri, Badar; Azhar, Areeba (2023), “Saudi Arabia Public Roads Visual Pollution Dataset ”, Mendeley Data, V3, doi: 10.17632/bb7b8vtwry.3
DOI: 10.17632/4hz2vcvxhp.1
title: T10I4D100K transactional database

description: T10I4D100K is a renowned synthetic database generated using the IBM Quest generator. This database is widely used to evaluate various frequent and correlated pattern mining algorithms.
DOI: 10.17632/dpgvc22rth.1
title: Data for: Research on Fatigue Driving Detection Based on Adaptive Multi-scale Entropy

description: EEG data for 8 male and 8 female individuals
DOI: 10.17632/xm232yxf7t.1
title: Arabic Natural Audio Dataset

description: This is the first Arabic Natural Audio Dataset (ANAD) developed to recognize 3 discrete emotions: Happy,angry, and surprised. Eight videos of live calls between an anchor and a human outside the studio were downloaded from online Arabic talk shows. Each video was then divided into turns: callers and receivers. To label each video, 18 listeners were asked to listen to each video and select whether they perceive a happy, angry or surprised emotion. Silence, laughs and noisy chunks were removed. Every chunk was then automatically divided into 1 sec speech units forming our final corpus composed of 1384 records. Twenty five acoustic features, also known as low-level descriptors, were extracted. These features are: intensity, zero crossing rates, MFCC 1-12 (Mel-frequency cepstral coefficients), F0 (Fundamental frequency) and F0 envelope, probability of voicing and, LSP frequency 0-7. On every feature nineteen statistical functions were applied. The functions are: maximum, minimum, range, absolute position of maximum, absolute position of minimum, arithmetic of mean, Linear Regression1, Linear Regression2, Linear RegressionA, Linear RegressionQ, standard Deviation, kurtosis, skewness, quartiles 1, 2, 3 and, inter-quartile ranges 1-2, 2-3, 1-3. The delta coefficient for every LLD is also computed as an estimate of the first derivative hence leading to a total of 950 features.
DOI: 10.17632/hpp82wtxfr.1
title: Benchmark data instances for the Multi-Objective Flexible Job shop Scheduling Problem with Worker flexibility

description: The proposed data consist of benchmark test instances for the Multi-Objective Flexible Job shop Scheduling Problem with Worker flexibility (MO-FJSPW). To the best of our knowlage, the MO-FJSPW is proposed for the first time by (Gong et al., 2017) [DOI:10.1080/00207543.2017.1388933], where the authors created data instances only for the total worker flexibility case: any machine can be operated by all the workers. That is why, we propose new benchmark data instances named “SFJW” and “MFJW” considering the MO-FJSPW with the partial worker flexibility case: each machine can be processed by a sub-set of workers.
DOI: 10.17632/39nrzzn8v6.1
title: Inclusive Total Factor Productivity based on Biennial Malmquist–Luenberger Productivity Index

description: We conceptualise and define inclusive economic development and propose a productivity perspective for evaluating inclusive economic development and construct the inclusive total factor productivity index on the most relevant components of inclusive economic development based on data envelopment analysis.
DOI: 10.17632/5hrmwfmh5w.1
title: Supplementary Information: Location-Specific Design of Biogenic Negative Emissions Hubs

description: This a supplementary information for a conference paper entitled, "Location-Specific Design of Biogenic Negative Emissions Hubs" at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 on 20th -24th October 2024 in Calgary, Canada.
DOI: 10.17632/mz6byjwxhj.1
title: Data for: Modification of surface characteristics and electrochemical corrosion behavior of selective laser melted stainless steel 316L after laser polishing

description: CSV files containing the data plotted in figures that are presented in the paper of stainless steel 316L before and after laser remelting: i.e., laser polishing. The data includes: surface topography, surface roughness metrics, x-ray diffraction, micro-hardness, residual stress, electrochemical analysis for corrosion behavior.
DOI: 10.17632/xwcyp5j9pz.1
title: Data PVT

description: Data of PVT System in Ifes - São Mateus
DOI: 10.17632/2pxd7nb54f.2
title: Inteligencia Artificial

description: Historia de la inteligencia artificial tomando en cuenta autores y evidencia.
DOI: 10.17632/5wsg9d52dk.1
title: CoOMBE: A suite of open-source programs for the integration of the optical Bloch equations and Maxwell-Bloch equations

description: The programs described in this article and distributed with it aim (1) at integrating the optical Bloch equations governing the time evolution of the density matrix representing the quantum state of an atomic system driven by laser or microwave fields, and (2) at integrating the 1D Maxwell-Bloch equations for one or two laser fields co-propagating in an atomic vapour. The rotating wave approximation is assumed. These programs can also be used for more general quantum dynamical systems governed by the Lindblad master equation. They are written in Fortran 90; however, their use does not require any knowledge of Fortran programming. Methods for solving the optical Bloch equations in the rate equations limit, for calculating the steady-state density matrix and for formulating the optical Bloch equations in the weak probe approximation are also described.