cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/sxzgn6xkj9.1
title: Optimization of a photovoltaic solar water pumping system in terms of pumping performance using response surface methodology

description: Prior to the industrial revolution, heat, electricity, and energy were mainly generated by burning plant biomass, such as wood and charcoal. Subsequently, as industrialization progressed, the use of fossil fuels such as coal, oil, and natural gas became widespread owing to their higher energy density and availability for the generation of electrical energy. In contrast, fossil fuels, such as coal, natural gas, and oil, continue to play an important role in energy production in many regions of the world. This leads to increased greenhouse gas emissions. Efforts are being made worldwide to transition to cleaner energy sources and reduce greenhouse gas emissions in the electricity sector. Currently, the era of transition in terms of global electricity generation is shifting towards alternative energy sources such as solar, wind, hydroelectric, biomass, and geothermal energy. These technologies result in significantly low or no direct CO2 emissions compared with fossil fuels . Solar water pumping technology is an environment-friendly and sustainable technology. The present study demonstrates the potential of solar water pumps as a dependable, cost-efficient, and environment-friendly solution for bolstering agriculture in remote regions.
DOI: 10.17632/ymgs23x3j8.1
title: Compressive Strength Prediction of Nano-Modified Concrete.

description: Original database presents the datasets compiled from multiple literature sources, comprising a total of 94 data points.Figure 5 presents the correlation coefficients among the nine variables, clearly indicating the specific instances of positive or negative correlation between each pair of variables as well as the varying intensities of their relationships. Figure 6 displays the model performance evaluation metrics for each fold in the 10-fold cross-validation of the four models. Figure 7 provides numerical values for five evaluation indicators based on the prediction results of the four machine learning models on the test set. Figure 8 demonstrates the determination coefficients of each model by comparing the outcomes of the respective algorithms' computer code runs with the actual values. Figure 9 presents the specific predicted values, allowing for an assessment of whether the models tend to underestimate or overestimate the actual values through a comparison of the differences between them.
DOI: 10.17632/yv85ckvvvb.1
title: Data for: Modelling and Statistical Analysis of YouTube's Educational Videos: A Channel Owner's Perspective

description: The data contains YouTube analytics of a channel owner. It is of the format of excel and has sheets corresponding to video, geography, date, subscription status, YouTube Product, translation use, Device etc. Each of these data is in the form of a sheet in the excel file. It contains columns like Video title, Video ID, Video length (minutes), Video created, Watch time (minutes), Views, YouTube Red watch time (minutes), YouTube Red views, Average view duration (minutes),Card clicks, Cards shown, Clicks per card shown, Ad impressions, YouTube Red watch time (hours), Annotation clicks, Likes, Likes added, Likes removed, Dislikes, Dislikes added, Dislikes removed, Shares Comments, Videos in playlists, Videos added to playlists Videos removed from playlists, Subscribers, Subscribers gained Subscribers lost Average percentage viewed, Watch time (hours). Value of the data This data could be used by the scientific community to get a lot of information about the YouTube Educational videos, their statistics and user preferences and behaviours. Acknowledgements saurabhschool: https://www.youtube.com/user/saurabhschool References https://www.youtube.com/user/saurabhschool
DOI: 10.17632/fkdxyxyxds.1
title: Supplementary Data and Code

description: Supplementary Data and Code
DOI: 10.17632/kbvssyjhcj.1
title: Concrete pressure test- thermal images

description: The thermal dataset consists of 11,145 colour images of thermal images captured using a Hikmicro G60 in a laboratory experiment where pressure was applied to eight concrete specimens. From the recordings of the specimens, noisy and blurry data has been removed and the data has been split to give a thermal image dataset of 5,651 cracked concrete images and 5,494 uncracked concrete images. For training the AI model, we resized each image to 256 x 256 and converted it to greyscale. for more information refer to the dataset description
DOI: 10.17632/rpdznnstd6.1
title: Data for: DISTRIBUTION AND COMPOSITIONAL FINGERPRINTS OF PRIMARY AND SECONDARY CHERT SOURCES IN NORTHERN APULIA (ITALY)

description: The results of NM-PCI method applied on the analysed pebbles (supplementary material). Abbreviations: h = homogeneous; sh = shaded; m = mottled; sp = spotted; l = laminated; b = banded; st = streaked; c = conchoidal; s = subconchoidal; u = uneven; ND = non determined; Rad = radiolarians; Spi = sponge spiculae; For = foraminifers; FeOx = iron oxides; Org = organic matter. This dataset is cited in the text as Table 3.
DOI: 10.17632/rczrcyttsr.1
title: Dataset of imported-local products switching intention

description: The current dataset is the results of a survey of 528 consumers to investigate imported-local product switching intention by using partial least square structural equation modeling (PLS-SEM). The current dataset includes raw data, PLS-SEM results, outer model, and inner model. The current dataset has seven variables, namely: environmental concern, environmental knowledge, social concern, perceived knowledge of social issues, and switching intention.
DOI: 10.17632/dnxhzj65sj.1
title: Second order CpC method

description: Some codes, data and figures for the new second order stable method. The manuscript is submitted to Journal.
DOI: 10.17632/3hckgznc67.1
title: Skin Disease Classification Dataset

description: The biggest contribution and most time-consuming task are preparing a self-collected dataset. However, there are several benefits in biomedical research, such as using newly identified skin images that other researchers have not used in their methodology. On the contrary, the most challenging aspect is that self-collected images are not preprocessed beforehand, making model training quite difficult. In regards to skin disease images, there are various internationally available collections of dermatological images, such as ISIC2019 and HAM10000, which are the two largest datasets for melanoma skin disease. These datasets cover several skin conditions, including actinic keratosis, basal cell carcinoma, benign keratosis, dermatofibroma, melanoma, melanocytic nevus, squamous cell carcinoma, and vascular lesions. However, we have collected images of a few skin diseases that rarely occur in the human body, such as acne, vitiligo, hyperpigmentation, nail psoriasis, and SJS-TEN. Our dataset consists of 5 categories of skin images, each with detailed depictions of skin sores and injuries in various ways. We collected a total of 9,548 dermatoscopic images from different hospitals and online resources of patients from different countries. This indicates that transfer learning can be used to detect all types of skin diseases. Specifically, we worked on the categories of acne (1148), vitiligo (2016), hyperpigmentation (700), nail-psoriasis (2520), and SJS-TEN (3164).
DOI: 10.17632/jv988xgnps.1
title: Han et al iScience 2020
DOI: 10.17632/tm97scgg94.1
title: Readability of Online Dermatology Patient Education Resources

description: Here we provide the data that was used for our health literacy project assessing the readability of various online resources used to educate patients about common dermatological conditions. Included is a spreadsheet of the raw data we collected via 'Readable' and links to all of the individual articles used in the data collection process. The second spreadsheet organizes the results of our data after analysis with various bio-statistical measures.
DOI: 10.17632/x63cs3hfzx.1
title: Overview of FACS gating strategies in PolyloxExpress HSC experiment

description: Surface marker combinations used for isolation of indicated cell populations. Surface markers indicated above the first plot of each panel were used to pre-define the indicated population. Pre-gatings for size (FSC, SSC) and live cells (Sytox blue-) not shown. (A) Sort gates of erythrocyte progenitors (EryP II and EryP III) from bone marrow. (B) Sort gates for HSC (LT+ST), MPP from LSK compartment (upper right), and CMP, GMP, MEP from LK compartment (lower right) from bone marrow. (C) Sort gates for CLP in bone marrow. (D) Sort gates for proB cells (fraction (Fra) B and Fr. C) in bone marrow. (E) Sort gates of CD4+ or CD8+ T cells from spleen. (F) Sort gates of granulocytes from bone marrow. (G and H) Sort gates of conventional B (B2) cells (G), and monocytes (H) from spleen. (I) Sort gates of preT cells (DN2 and DN3) from the thymus.
DOI: 10.17632/9vr83n7z5j.1
title: Driver Behavior Detection Using Smartphone - Dataset

description: Dataset for driver behavior classification (normal, aggressive, risky) based on accelerometer (X,Y,Z axis in meters per second squared (m/s2)) and gyroscope (X,Y, Z axis in degrees per second (°/s) ) data. Sampling Rate: 50 Hz default Cars: Ford Figo 1.2, Maruti Suzuki Swift VXI, Tata Nexon XMS Drivers: 3 different drivers with the ages between 35-40 yrs. Driver Behaviors: Normal, Aggressive, and Risky Smartphone Sensor: Accelerometer, Gyroscope Smartphone Device: Redmi 4, MI A3
DOI: 10.17632/vkv4p34fvp.1
title: Data for: Application of Terahertz Time Domain Spectroscopy for NDT of Oxide-Oxide Ceramic Matrix Composites

description: In this paper the measurement results show the feasibility of the pulsed terahertz technique for NDT of oxide-oxide CMC materials. Hidden defects, delamination or moist areas can be detected quantitatively. Furthermore, the boundary reflections of layered materials can be revealed more clearly by using deconvolution algorithms.
DOI: 10.17632/7sg66d9hmk.1
title: Supporting Information for: Estimating net biomass production and loss from repeated measurements of trees in forests and woodlands: formulae, biases and recommendations

description: Supporting Information. R code for urnover rate calculation We provide these available on web: R code “prod.r” for calculating simple (Eqs (5)–(6)), instantaneous (Eqs (1)–(2)), and species-structured instantaneous turnover rates (Eqs (18)–(19)), with sample data “greenTunnel.txt” for 1996 and 2015 censuses of 4-ha plot in Tomakomai primary mixed forest.
DOI: 10.17632/vyyjk7m6m4.1
title: Single-cell sequencing of dermal CD45+ cells from psoriasis patients and healthy donors

description: Single-cell sequencing of dermal CD45+ cells from psoriasis patients and healthy donors. Cell Ranger output files of 10X single-cell sequencing data.
DOI: 10.17632/tym7x3b85s.2
title: A Retrospective Cohort Study Investigating Cutaneous Vasculitis in the Setting of COVID-19 Notes Higher Rates of IgA Vasculitis

description: We aimed to evaluate this relationship, focusing on cutaneous vasculitis’s clinical
presentation and specifically immunoglobulin A (IgA) vasculitis, given the latter’s association
with infection and potential systemic ramifications. To our knowledge, this is the first study of its kind in the
United States, with several ethnic representations. Frequency of IgA-associated vasculitis cases
within our COVID-19 cohort is similar to rates previously noted. Similarly, our study found
that lower extremity involvement is most common. Earlier work found a median time of 11.5
and 7 days from vaccination/infection to symptom onset, respectively; our study found a longer
lag time of 19.5 and 31 days. We additionally noted significantly higher prevalence of renal
involvement, potentially higher prevalence of blistering disease, and significantly increased need
for systemic corticosteroids in COVID-associated cases. Our study suggests dermatologists should consider obtaining direct immunofluorescence studies to investigate for IgA vasculitis when encountering vasculitis in the setting of COVID-19 and to closely monitor these patients for renal disease.
DOI: 10.17632/zvpg53tc2p.1
title: Corn Crop Growth

description: This dataset contains information on environmental and soil variables that influence the growth of corn crops. The data was collected from 2010 to 2019 with the aim of predicting and optimizing management practices to improve corn productivity.

Variables

Temperature
Description: Ambient temperature in degrees Celsius.
Data Type: Numeric (float)
Value Range: 10°C to 35°C
Importance: Temperature directly influences the growth rate and development of corn. Temperatures within the optimal range promote ideal plant growth.

Humidity
Description: Relative humidity in percentage.
Data Type: Numeric (float)
Value Range: 30% to 90%
Importance: Relative humidity is crucial for transpiration and gas exchange in corn leaves, affecting nutrient and water absorption.

Soil_Moisture
Description: Soil moisture in percentage.
Data Type: Numeric (float)
Value Range: 10% to 40%
Importance: Soil moisture is fundamental for water availability to corn roots, especially during critical stages of germination and vegetative growth.

Growth
Description: Corn growth in centimeters.
Data Type: Numeric (float)
Value Range: Dependent on environmental and soil conditions
Importance: Direct measure of plant health and development, influenced by environmental and soil variables. It is the target variable for regression models.
DOI: 10.17632/h5rcnxpk8w.2
title: Management of hyperglycaemia in type 2 diabetes. Consensus report ADA/EASD 2018 and update 2022  

description: Details of the systematic search
DOI: 10.17632/w393cchcb7.2
title: Mal-API-2019

description: This study seeks to obtain data which will help to address machine learning based malware research gaps. The specific objective of this study is to build a benchmark dataset for Windows operating system API calls of various malware. This is the first study to undertake metamorphic malware to build sequential API calls. It is hoped that this research will contribute to a deeper understanding of how metamorphic malware change their behavior (i.e. API calls) by adding meaningless opcodes with their own dissembler/assembler parts.
DOI: 10.17632/rw9yk3c559.1
title: A dataset for conduction heat transer and deep learning

description: Big data images for conduction heat transfer The related paper has been published here: M. Edalatifar, M.B. Tavakoli, M. Ghalambaz, F. Setoudeh, Using deep learning to learn physics of conduction heat transfer, Journal of Thermal Analysis and Calorimetry; 2020. https://doi.org/10.1007/s10973-020-09875-6 Steps to reproduce: The dataset is saved in two format, .npz for python and .mat for matlab. *.mat has large size, then it is compressed with winzip. ReadDataset_Python.py and ReadDataset_Matlab.m are examples of read data using python and matlab respectively. For use dataset in matlab download Dataset/HeatTransferPhenomena_35_58.zip, unzip it and then use ReadDataset_Matlab.m as an example. In case of python, download Dataset/HeatTransferPhenomena_35_58.npz and run ReadDataset_Python.py.
DOI: 10.17632/3k2vjy455s.1
title: COVID-19-related articles in the Economic and Business research

description: The dataset includes bibliographic information of 3917 COVID-19-related articles in the Economic and Business research in the Scopus database
DOI: 10.17632/hy29cy2v9f.1
title: Refinancing Cross-Subsidies in the Mortgage Market

description: This repository contains the code and public version of the data for "Refinancing Cross-Subsidies in the Mortgage Market" by Jack Fisher, Alessandro Gavazza, Lu Liu, Tarun Ramadorai and Jagdish Tripathy.
DOI: 10.17632/5bvx4g39dw.1
title: ECOGEN: An open-source tool for multiphase, compressible, multiphysics flows

description: ECOGEN, a new open-source computational fluid dynamics code is presented. It is a multi-model tool devoted to the simulation of compressible flows. A large range of problems can be solved, from single-phase gas dynamics to multiphase, multiphysics flows including interface problems between pure fluids. This code is suited for strongly unsteady flows. The numerical solver of ECOGEN is implemented in a flexible structure making the code able to compute such complex flows on different kinds of discretization grids. The implemented hyperbolic solver is able to deal with Cartesian geometries as well as unstructured grids. A recent adaptive mesh refinement method is also implemented. Its numerical implementation is presented in detail to help the enthusiastic developer to contribute to this open-source project. Representative test cases are presented to show the tool abilities and to open the gate for future developments.
DOI: 10.17632/jybm8hkp9y.1
title: PVRP-DC-SO instances

description: These are the 36 instances used in the article "The Periodic Vehicle Routing Problem with Driver Consistency and Service Time Optimization", written by Inmaculada Rodríguez-Martín and Hande Yaman, and published in …………….. These data files have the same format as the classical PVRP instances from the literature. We have kept this format, but in for the PVPR-DC-SO we skip some of the information in the files. The infomation we do not consider is: - The maximum duration of a route (denoted by D bellow) - The vehicles’capacity (denoted by Q bellow) - The service duration for each customer (denoter by d bellow) Taking this into account, the files are read in the following way: The first line contains the following information: type m n t where type = 1 (PVRP), m = number of vehicles, n = number of customers, t = number of days. The next t lines contain, for each day ,the following information: D Q where D = maximum duration of a route (0 means 'unbounded'), Q = maximum load of a vehicle. The next lines contain, for the depot and each customer, the following information: i x y d q f a list where i = customer number (0 corresponds to the depot), x = x coordinate, y = y coordinate, d = service duration, q = demand, f = frequency of visit, a = number of possible visit combinations, list = list of all possible visit combinations. Each visit combination is coded with the decimal equivalent of the corresponding binary bit string. For example, in a 5-day period, the code 10 which is equivalent to the bit string 01010 means that a customer is visited on days 2 and 4. (Days are numbered from left to right.)
DOI: 10.17632/65hpcv8fwj.1
title: Data for: 3665024

description: Data for: Ghodsi Mohammadi Ziarani, Fatemeh Mohajer, Seyedh Mahboobeh Jamali, Nader Ale Ebrahim, Quantitative and Qualitative bibliometric scope toward the Synthesis of Rose Oxide as a Natural Product in perfumery, July 2020, Current Organic Synthesis, Current Organic Synthesis, vol. 17, no. 8, DOI: 10.2174/1872208314666200722161044
DOI: 10.17632/zd4yrcczkj.3
title: Code for: Electrochemical Characterization Tools for Lithium-ion Batteries

description: The MATLAB codes developed to extract lithium-ion battery performance and health metrics from diagnostic tests. The MATLAB codes replicate the results shown in the journal paper: "Electrochemical Characterization Tools for Lithium-ion Batteries" by Sara Ha, Gabriele Pozzato, and Simona Onori [1]. The diagnostic tests considered are the capacity test, high pulse power characterization (HPPC) test, and electrochemical impedance spectroscopy (EIS). The diagnostic tests used in our codes come from a publicly available battery aging dataset [2] that was generated from INR21700-M50T cylindrical cells with NMC811 cathode and graphite-silicon anode. The cells were subjected to a constant current (CC)-constant voltage (CV) charging protocol and urban dynamometer driving schedule (UDDS) discharge driving profile to replicate electric vehicle driving scenarios. To view the original dataset: https://osf.io/qsabn/?view_only=2a03b6c78ef14922a3e244f3d549de78 References: [1] S. Ha, G. Pozzato, and S. Onori, “Electrochemical Characterization Tools for Lithium-ion Batteries,” Journal of Solid State Electrochemistry, 2023. Accepted. [2] G. Pozzato, A. Allam, and S. Onori, “Lithium-ion battery aging dataset based on electric vehicle real-driving profiles,” Data in Brief, vol. 41, p. 107995, Apr. 2022, doi: 10.1016/j.dib.2022.107995.
DOI: 10.17632/r7t3jt9sxk.4
title: Brown Adipocyte Lipid Droplet Lipolysis Is Not Essential for Cold-Induced Thermogenesis in Mice. Shin et al.

description: Raw data for Brown Adipocyte Lipid Droplet Lipolysis Is Not Essential for Cold-Induced Thermogenesis in Mice. Shin et al.
DOI: 10.17632/vckdnhtw26.1
title: BUSC Dataset

description: The Mendeley ultrasound dataset [1] includes 100 benign images and 150 malignant cancer images. The original resolution of ultrasound images is 64 × 64 pixels, later in our research [2] transformed into 128 × 128 pixels. This dataset is basically classification-based dataset, and no ground truth images are provided. Therefore, with the help of an experienced radiologist, benign and malignant tumor images are annotated for segmentation task.

If you use this dataset, Please cite:

[1] Rodrigues, Paulo Sergio (2017), "Breast Ultrasound Image", Mendeley Data, V1, doi: 10.17632/wmy84gzngw.1

[2] Ahmed Iqbal, Muhammad Sharif, "PDF-UNet: A semi-supervised method for segmentation of breast tumor images using a U-shaped pyramid-dilated network", Expert Systems with Applications, 2023. https://doi.org/10.1016/j.eswa.2023.119718
DOI: 10.17632/4h62p9tdfx.2
title: Data and Program Files for "Measuring Macroeconomic Tail Risk"

description: Data and Program Files for "Measuring Macroeconomic Tail Risk" Roberto Marfè and Julien Pénasse, Journal of Financial Economics.