cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/8vzg3v6mkv.1
title: Pancreatic Cancer Case Report - CT Scan Slices - with Contrast

description: Pancreatic Cancer Case Report - CT Scan Slices - with Contrast
DOI: 10.17632/cjfrd9p5jt.1
title: Data for: Nutrient cycling in the Lower St. Lawrence Estuary: response to environmental perturbations

description: In these files, you will find the code and instructions to install a software of the Box Model of the Lower St. Lawrence Estuary.
DOI: 10.17632/yzcwfyrxy2.2
title: A data set exploring the link and associated factors of internet addiction, loneliness, and depression among adolescents in Bangladesh

description: Recently, internet addiction, loneliness, and depression have emerged as significant concerns among adolescents, exacerbated by the increasing use of social media and other factors. This dataset aimed to evaluate the patterns of these issues among adolescents. Utilizing a cross-sectional design, data were collected from 819 adolescents (65.2% female and 34.8% male) aged 13 to 19. The dataset includes information on the frequency and type of internet addiction (IA), loneliness, and depression among the participants. The dataset gathered data using the Internet Addiction Test (IAT) scale, UCLA Loneliness Scale (Version 3), and Patient Health Questionnaire (PHQ-9) scale to measure IA, loneliness, and depression. The questionnaire covers a wide range of adolescents’ lives and actions-related variables, such as sociodemographic information, technology, and media uses behavioral and lifestyle as well as academic variables. A researcher can effectively utilize the data set to assess the prevalence rate of IA, loneliness, and depression; generate meaningful insights, follow explanatory data analysis (EDA), formulate a hypothesis and relationship between different variables, and conduct inferential statistics to conclude. The dataset also offers useful information to stakeholders so they may create plans and regulations to lessen these mental health issues.
DOI: 10.17632/52dw6mfkg5.1
title: IMPACT OF SOCIAL MEDIA IN PROMOTING FOOD PRODUCTS

description: Impacts of social media on promoting food products were assessed through survey questions and interviews. Facebook was the most utilized social media platform and good feedback or reviews from clients were used for promotion. Advantages in utilizing social medial includes; broad access, accessible, cost-efficient and trendy. While the disadvantages are the business can easily be imitated, can be easily affected by negative feedbacks and prone to bogus buyers. These findings suggest that social media has a strong impact in promoting food products.
DOI: 10.17632/j5f6r56jnb.1
title: Deep Learning Approach to Natural Convection Heat Transfer in a Cavity: A Simulation Dataset for Nano-Encapsulated Phase Change Material Suspensions

description: Big data images for natural convection flow and heat transfer (nano-encapsulated phase change suspensions)
The related paper has been published here:
Edalatifar, M., M.B. Tavakoli, and F. Setoudeh, A Deep Learning Approach to Predict the Flow Field and Thermal ‎Patterns of Nonencapsulated Phase Change Materials ‎Suspensions in an Enclosure‎. Journal of Applied and Computational Mechanics, 2021.
Links: 
https://doi.org/10.22055/JACM.2021.37805.3092
https://jacm.scu.ac.ir/article_16903.html

Keywords: Deep convolutional neural networks - Loss function - Heat transfer images - Physical images - Artificial intelligence - CFD - Computational fluids dynamics - Finite element method -Dirichlet boundary condition
Nano-encapsulated phase-change suspension;  natural convection flow and heat transfer; deep convolutional neural networks; deep learning
DOI: 10.17632/zjckp3b259.1
title: MS-Excel tool for MCDA methods

description: This work presents a novel MS-Excel tool that has 4 different MCDA methods and two case studies. Any case study can loaded and different MCDA methods can be applied. There is a summary sheet at the end that compares the outputs from the individual MCDA methods and provides overall ranking. Instructions to the users are provided on the cover sheet itself. Users can load which ever case study they want, even input data can be edited. Further, users can create their own problems with their own input data sets; and then use the tool to study the outputs.
DOI: 10.17632/2cygy6y4rk.1
title: Multi-domain vibration dataset with various bearing types under compound machine fault scenarios: subset 3 (tapered roller bearing)

description: Note: Due to the data storage limitation, our dataset is divided into three subsets for each bearing type. This subset includes the data collected from the tapered roller bearing (NTN 30204).

This dataset provides vibration data collected under various fault conditions, including compound faults, and multiple domain environments. The faults include three single-bearing faults, seven single rotating component faults, and 21 compound faults. The domain configurations are categorized into the rotating speed, bearing type, and sampling rate. The data were collected for 160 seconds at an 8 kHz sampling rate and 80 seconds at a 16 kHz sampling rate, resulting in a uniform sample length of 1,280,000 for each raw vibration signal.

The data files are organized in a hierarchical directory structure. The top-level directories are based on the sampling rate (8 kHz and 16 kHz). Each sampling rate directory has subdirectories for six rotating speeds (600, 800, 1,000, 1,200, 1,400, and 1,600 RPM). Each rotating speed subdirectory contains 32 files collected under different fault conditions.

Data samples are stored in binary MATLAB (MAT) file. The naming convention of each file follows the format comprising five properties: {rotating component condition}_{bearing condition}_{sampling rate}_{bearing model}_{rotating speed}.mat.

The fault conditions are denoted by one capital letter, and unbalance and misalignment faults include three severity levels, where a higher number indicates that a more significant fault occurs. Available values of each property in the file name are as follows:
1. Rotating component condition
- ‘H’: healthy (no severity level)
- ‘M’: misalignment (severity level 1-3)
- ‘U’: unbalance (severity level 1-3)
- ‘L’: looseness (no severity level)
2. Bearing condition
- ‘H’: healthy
- ‘B’: ball fault
- ‘IR’: inner race fault
- ‘OR’: outer race fault
3. Sampling rate
- ‘8’: 8 kHz
- ‘16’: 16 kHz
4. Bearing model
- ‘30204’: bearing model for H, B, IR, and OR conditions
5. Rotating speed
- ‘600’, ‘800’, ‘1000’, ‘1200’, ‘1400’, or ‘1600’: numbers represent RPM.

The data are available in two formats: 1-D raw vibration signal and 2-D spectrogram. These time and time-frequency domain data are stored in separate fields of a MAT file. Data fields in each MAT file are as follows:
1. ‘Data’: raw vibration signal (unit: g [9.80665 m/s2]).
2. ‘Spectrogram’: spectrograms (unit: dB scale magnitude).
3. ‘STFTFreq’: frequency instant vector of the spectrogram (unit: Hz).
4. ‘STFTTime’: time instant vector of the spectrogram (unit: seconds).

For each data file, 78 spectrograms with a size of 128 x 128 were generated by the short-time Fourier transform (STFT) method with the Kaiser window function. In doing so, raw vibration data were sliced into 16,384-length segments without overlapping. Each segment was then converted to a spectrogram with a window size of 192, an FFT size of 256, and an overlap size of 65.
DOI: 10.17632/9kwjrxgvmy.1
title: Calcium bentonite and sodium bentonite as stabilizers for roads unbound

description: The dataset deals with a laboratory investigation of bentonite clay employed as a stabilization technology for road unbound layers. Two types of bentonite clays are investigated, namely calcium based bentonite (CaB) and sodium based bentonite (NaB). Two types of aggregates are characterized as stabilized materials, namely crushed rock aggregates (CRA) and natural gravel aggregates (NGA). Untreated aggregates (Unbound Granular Material, UGM) are also tested for comparison purpose.

A total of 12 samples – 2 replicate samples for each condition – are tested dried (w=0%) by means of Repeated Load Triaxial Test (RLTT). The dataset reports raw data and pictures. 

RLTTs are performed following the code “EN 13286-7 Cyclic load triaxial test for unbound mixtures” according to Multi-Stage Low Stress Level (MS LSL) testing procedure. The spreadsheets displaying the RLTTs results report the dynamic stress and the triaxial stress exerted in the testing device as well as the axial strains and the radial strains measured by a total of six Linear Variable Differential Transformers (LVDTs).
DOI: 10.17632/f7z9ppz982.1
title: Palmi_Shear_Zone_Calabria-Italy

description: 3D virtual outcrop models of Palmi shear zone as KMZ files
DOI: 10.17632/gxxszgy85t.1
title: ANN dual-fluid PV/T data and code in R programming - Architecture of the Artificial Neural Network

description: This dataset provides the artificial neural network architecture for a dual-fluid photovoltaic thermal (PV/T) collector which was experimentally tested in the outdoor environment of Malaysia. The system was set up and tested in three modes, which are (i) air mode, (ii) water mode and (iii) simultaneous mode. For modes (i), (ii) and (iii) air flows through the cooling channels, water flows through the cooling channels and both air and water flow together. To create this dataset, the following steps were carried out: 1. Select input variables: 5 data inputs were selected, which are Ambient temperature, wind speed, solar irradiance, inlet air temperature and inlet water temperature. 2. Select Algorithm: for training, the Backpropagation neural network (BPNN) was used. 3. Select output variables: 6 data output were selected, which are PV surface temperature, PV temperature, temperature of the back plate, the temperature of the outlet air and outlet water, in addition to the electrical efficiency. Step 1: Import the data Step 2: Normalize the data Step 3: Split the dataset into training and testing data Step 4: Create the NN model in R studio. The package 'Neuralnet' in the R programming language was used. The coding in R studio is provided in the attached file.
DOI: 10.17632/czvpk9vrwx.1
title: Selected Studies

description: This dataset consists of the filtering process of the studies selected for the observability journal.
DOI: 10.17632/4m5nbwktbf.1
title: The Effect of Heterogeneous National Technological Capabilities on a Net-Zero Energy System. 

description: GCAM is an open-source tool and the version used for the study can be downloaded from the is linked https://github.com/JGCRI/gcam-core/releases/tag/gcam-v5.4. To replicate the results of the study please use the XML files in the GCAM XML file folder. 
This Technological Capability Index folder contains country-level data and code used to generate and validate the low-carbon technological capability index. 
The analysis was conducted using Stata 14.
DOI: 10.17632/x8ssjp5h7s.2
title: Dataset: Real Effective Exchange Rate Volatility for West African Monetary Zone

description: The dataset provides real effective exchange rate volatility series for West African Monetary Zone (WAMZ), which can be reused without restriction. The data covers the whole member nations in WAMZ namely Liberia, Nigeria, Sierra Leone, Gambia, Ghana and Guinea, and ranges between 1980m1 to 2024m8. The data, therefore, has the potential to be reused for forecasting future unanticipated movements in exchange rates in WAMZ, and also for conducting empirical research relating to exchange rate volatility and trade performance in the region.
DOI: 10.17632/6ps7gtp2wg.1
title: Spoiled and fresh fruit inspection dataset

description: The design of quality control systems in food has become an essential element in research to ensure a state suitable for consumption. It is necessary to develop automatic and efficient systems that can verify their condition before distribution. The proposed dataset can be used with a deep learning-based algorithm for the identification of the fruits and the state in which they are. The data set has 8 different fruits: -banana -lemon -lulo -mango -orange -strawberry -tamarillo -tomato. Two thousand images of each one of the types of fruits are acquired for a total of 16000 samples. Half of them correspond to fresh fruits and the other half to non-fresh or spoiled fruits. For the acquisition of the dataset, changing of backgrounds, rotation of the fruits, distance of capture, and light variations were made, in order to make it robust.
DOI: 10.17632/s6kkgc3x5v.1
title: Data for: Depression Biomarkers Using Non-Invasive EEG: A Review

description: Also available at: https://github.com/FernandoSAguiarNeto/SystematicReviewDepressionBiomarkers2018 Depression Biomarkers Using EEG: A Review Supplementary material for systematic mapping Disclaimer: Please cite the original article if any of the material is used. File: ReviewMethodology.pdf Information: Detailed description of the review methodology used. Table 1: Accepted Articles References Information: Reference keys matching the article, title and year of accepted and reported articles. File: AcceptedArticlesTable.pdf BibTex with accepted articles: BibTex(RevSys-DepressBiom2018).bib Table 2: Accepted Articles Summary Information: BibTex Keys, year, summarized information by article, pie chart with biomarker approaches. File: AcceptedArticlesSummary.csv Table 3: Data extraction form Information: Data extraction form used to organize the reading using Parsifal to aid the systematic review. This spreadsheet also has some charts. File: ExtractionForm.csv
DOI: 10.17632/m262xxpgn2.1
title: A Deep Generative Modeling Architecture for Designing Lattice-Constrained Materials

description: This dataset supports the article: contains all Crystallographic Information Files (CIF) and Quantum Espresso (QE) geometry optimization output files for the 124 perovskite materials that were newly designed using the Lattice-Constrained Materials Generative Model (LCMGM). CIF files were written using the Python Materials Genomics (Pymatgen) software package. For geometrical optimization, QE performs spin-polarized plane-wave calculations using the Perdew-Burke-Ernzerhof (PBE) pseudopotential class. The preprocessed dataset used for deep learning, relevant source codes for developing the LCMGM model, and Crystallographic Information Files (CIF) of newly designed materials are equally made available on GitHub: http://github.com/chenebuah/LCMGM
DOI: 10.17632/x4nfg7p7p4.2
title: Data for:Review on Current Research Directions in Energy Harvesting Power Conversion (EHPC) System

description: Original excel files of tabular data that have been used to generate the visual presentation using graphs and charts of the techniques for the current research trends within 6 years (from years 2013 to 2018).
DOI: 10.17632/6vjsv6v48p.1
title: The equation of state package FEOS for high energy density matter

description: Adequate equation of state (EOS) data is of high interest in the growing field of high energy density physics and especially essential for hydrodynamic simulation codes. The semi-analytical method used in the newly developed Frankfurt equation of state (FEOS) package provides an easy and fast access to the EOS of –in principle –arbitrary materials. The code is based on the well known QEOS model (More etal., 1988; Young and Corey, 1995) and is a further development of the MPQeos code (Kemp and Meyer-ter Vehn, 1988; Kemp and Meyer-ter Vehn, 1998) from Max-Planck-Institut für Quantenoptik (MPQ) in Garching Germany. The list of features contains the calculation of homogeneous mixtures of chemical elements and the description of the liquid–vapor two-phase region with or without a Maxwell construction. Full flexibility of the package is assured by its structure: A program library provides the EOS with an interface designed for Fortran or C/C++ codes. Two additional software tools allow for the generation of EOS tables in different file output formats and for the calculation and visualization of isolines and Hugoniot shock adiabats. As an example the EOS of fused silica (Si02) is calculated and compared to experimental data and other EOS codes.
DOI: 10.17632/yfrzxkrcvr.1
title: GLISSANDO 3: GLauber Initial-State Simulation AND mOre, ver. 3

description: We present ver. 3 of GLISSANDO, a versatile Monte-Carlo generator for Glauber-like models of the initial stages of ultra-relativistic heavy-ion collisions. The present version incorporates the wounded parton model, which is phenomenologically successful in reproducing multiplicities of particle production at the RHIC and the LHC. Within this model, one can study the nucleon substructure fluctuation effects, recently explored in p-A collisions. In addition, the code includes the possibility of investigating collisions of light nuclei, such as 3He and 3H, or the alpha-clustered 7,9Be, 12C, and 16O, where the deformation of the intrinsic wave function influences the transverse shape of the initial state. The current version, being down-compatible, retains the functionality of the previous releases, such as incorporation of various variants of Glauber-like models, a smooth NN inelasticity profile in the impact parameter obtained from a parametrization of experimental data, fluctuating strength of the entropy deposition, or realistic nuclear distributions of heavy nuclei with deformation. The code can provide output in the format containing the event-by-event source location, which may be further used in modeling the intermediate evolution phase, e.g., with hydrodynamics or transport models. The interface is simplified, such that in the control input file the user may supply only the very basic information, such as the collision energy, the mass numbers of the colliding nuclei, and the model type. GLISSANDO 3 is integrated with the CERN ROOT platform. The package includes numerous illustrative and useful ROOT scripts to compute and plot various results.
DOI: 10.15468/dl.nxzn3u
title: Occurrence Download

description: A dataset containing 354 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-74.25443 -4.17810,-53.74557 -4.17810,-53.74557 10.17810,-74.25443 10.17810,-74.25443 -4.17810))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Myriocladus Swallen"
 ]
}

 The dataset includes 354 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009351-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/4dh2h3tsf4.1
title: Graphite-based electrodes for Li-ion batteries: Formulation and manufacturing process optimization via machine learning

description: Cycling Data for Cells
DOI: 10.17632/8sndpz4s8k.1
title: reflective writing

description: reflective writing scheme and scale
DOI: 10.17632/d7grg846wv.3
title: Hedonic dataset of the four metropolitan housing market in South Korea

description: This dataset was generated for analyzing the economic impacts of subway networks on housing prices in metropolitan areas. The provision of transit networks and accompanying improvement in accessibility induce various impacts and we focused on the economic impacts realized through housing prices. As a proxy of housing price, we consider the price of condominiums, the dominant housing type in South Korea. Although our focus is transit accessibility and housing prices, the presented dataset is applicable to other studies. In particular, it provides a wide range of variables closely related to housing price, including housing properties, local amenities, local demographic characteristics, and control variables for the seasonality. Many of these variables were scientifically generated by our research team. Various distance variables were constructed in a geographic information system environment based on public data and they are useful not only for exploring environmental impacts on housing prices, but also for other statistical analyses in regard to real estate and social science research. The four metropolitan areas covered by the data—Busan, Daegu, Daejeon, and Gwangju—are independent of the transit systems of Greater Seoul, providing accurate information on the metropolitan structure separate from the capital city.
DOI: 10.17632/smwv23ttmz.1
title: Insights into the accuracy of the World’s Top 2% of Scientists list by Stanford University

description: The tools and methods used to measure the impact of an individual’s research work are H-index, citations, Altmetrics, and impact factor of journals where the work is published. The databases widely used for the H-index and citations are Web of Science, Scopus, and Google Scholar. Web of Science indexes over 10000 journals while Scopus indexed over 15,000 journals. Google Scholar has more journals indexed and more publication types than the other databases but it is not comprehensive and accurate, because individual researchers determine the results, unlike the other two. The h-index is considered a measure of both the scientific productivity and scientific impact of a scientist. In citation analysis, the number of times an article is cited by other works is used to measure the impact of a publication/author. Altmetrics is based on the attention of a published work through social media, citations, and article downloads. Impact factor (IF) is a measure of the importance or rank of a journal, it is based on the citations published papers the previous two years. A few years ago John Ioannidis and co-authors of Stanford University created a unique publicly available database of top-cited scientists in the world using Scopus data from Elsevier, which has enthralled the scientific community, institutions, and media[1-3]. This database, touted as a new approach to eliminate the misuse of citation metrics, has enthralled the scientific community, institutions, and media. Many institutions used this as a yardstick to assess the quality of researchers, some institutions widely publicized the list and gave rewards to researchers who were listed. At the same time, some researchers look at this list with skepticism by citing problems with the methodology used in the c-score-based ranking. To evaluate the accuracy of c-score-based ranking, being my name figured in both the career and individual year lists, I have done a detailed analysis of the matrix parameters. 2578 and 4635 Indian authors appear in the career and single-year categories, respectively. For comparison of the ranking, the last 25 years (1998-2022) of Nobel laureates of Physics, chemistry, and medicine, and the top 100 rank holders in the list are chosen. The latest career-long, and single-year-based databases (2022) were used for this analysis. The details of the analysis are presented here. Though the article says the selection is based on the top 100,000 scientists by c-score (with and without self-citations) or a percentile rank of 2% or above in the sub-field, the actual career-based ranking list has 204644 names [1]. The single-year database contains 210199 names. So, the list contains names of the top 4 %, if we assume 100000 scientists on the list as 2%! The entry of many authors having single digit H index and a very meager total number of citations indicates serious shortcomings of the c-score-based ranking methodology.
DOI: 10.17632/w258xptpnv.1
title: Tomato_ImagetoAudio

description: Tomato leaf diseases image dataset converted into audio dataset
DOI: 10.17632/yvp2b4rtp3.1
title: Event Log Dwelling Time Dataset

description: This dataset contains event logs on the Container Dwell Time process at the Container Terminal. The Dwelling Time process is the process and time calculated from the time the container is unloaded and lifted from the ship until the container leaves the port terminal through the main door.
DOI: 10.17632/2cpnjmbbyk.1
title: Raw data-Effects of a multifactorial ecosustainable isocaloric diet on liver fat in patients with type 2 diabetes: randomized clinical trial

description: research data of the work