cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/vy7mxkkgx5.1
title: Dataset on validation of double U-tube borehole and seasonal solar thermal energy storage system TRNSYS models

description: This dataset includes data from the validation of double U-tube borehole and seasonal solar thermal energy storage system TRNSYS models. The simulated transient temperatures at various points of the systems were compared with the measured ones. To quantify the agreement between each simulated and measured temperature of interest, mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (CC) were applied.
DOI: 10.17632/zzjs4dpp5h.1
title: Dataset: Initiation and internal structure of temperate coral reef community over the past 7.3 kyr in Kushimoto, mainland of Japan

description: The dataset is composed of the following data:
(1) Figure 1. A photograph of the drilled core (WK-Ku-Gw-C3) 
(2) Table 1. A list of 193 tropical cyclones that passed within a 300 km radius of the survey site from 1951 to 2023
DOI: 10.17632/f5c9vbj93z.1
title: A cross-national investigation of the influence of linguistic identity on lnguage shift/maintenance dynamics in Ghana and Nigeria

description: this data were collected from university students in Nigeria and Ghana. It aims to understand how identity construction contributes to language shift/maintenance in African. The data looks into how cultural linguistic identity and elite linguistic identity contributes to the tendencies of language shift or maintenance among university students in Africa
DOI: 10.17632/kmyvjk3xmd.2
title: Evolving patterns of extreme publishing behavior across science

description: Author information for:
Hyperprolific physics authors by year 2000-2022 inclusive. Author needs to have 73 or more publications in a year to qualify and their main field from 2000 to 2022 is Physics & Astronomy
Hyperprolific non-physics authors by year 2000-2022 inclusive. Author needs to have 73 or more publications in a year to qualify and their main field from 2000 to 2022 must not be Physics & Astronomy
Almost Hyperprolific physics authors by year 2000-2022 inclusive. Author needs to have between 61 and 72 publications in a year to qualify and their main field from 2000 to 2022 is Physics & Astronomy
Almost Hyperprolific non-physics authors by year 2000-2022 inclusive. Author needs to have between 61 and 72 publications in a year to qualify and their main field from 2000 to 2022 must not be Physics & Astronomy
Data:
year - The year of publication of the articles, reviews, and conference proceedings analyzed in this study
author_field - The primary field assigned to the author based upon publications and share of publications in the field
field - The ScienceMetrix field classification of the journal the publication appears in
Pubs_in_field_year - Total number of publications by the author in the given year in the given field
Pubs_year_total - Total number of publications by the author in the given year
Pubs_in_field_2000_2022 - Total number of publications by the author in the period 2000 to 2022 in the given field,
Pubs_2000_2022_total - Total number of publications by the author in the period 2000 to 2022
rank - The author's rank, within their SM subfield, based on citation count
rank (ns) - The author's rank, within their SM subfield, based on citation count with self citations excluded
sm-subfield-1 - The author's SM subfield
rank sm-subfield-1 - The author's rank, within their SM subfield, based upon their citation score
rank sm-subfield-1 (ns) - The author's rank, within their SM subfield, based upon their citation score excluding self citations
sm-subfield-1 count - The number of authors in the SM subfield
Subfield_Percentile - 100 * rank/count
Subfield_Percentile_ns - 100 * rank (ns)/count
author_name - Author's name from their Scopus Author Profile
hidx - The author's career H-Index
affil_name - The name of the author's most recent affiliation
cntry - The country of the author's most recent affiliation
Total_Pubs - The number of articles, reviews, and conference proceedings from the affiliation in the period
Pubs_with_more_than_100_authors - The number of articles, reviews, and conference proceedings from the affiliation in the period with more than 100 authors
Pubs_with_more_than_500_authors - The number of articles, reviews, and conference proceedings from the affiliation in the period with more than 500 authors
Pubs_with_more_than_1000_authors - The number of articles, reviews, and conference proceedings from the affiliation in the period with more than 1000 authors
DOI: 10.17632/gw3fbp74ct.1
title: NPK Survey of Field Crops 2014-2017

description: Data set is a survey of nitrogen (N), phosphorous (P), and potassium (K) percentages in grains of corn, soybean, and wheat samples collected around the state of Illinois from 2014 to 2017. The survey was funded by the Illinois Nutrient Research and Education Council (NREC) Award# 2014-02377 to improve the accuracy of P and K removal values for corn, soybean, and wheat. We solicited grain samples from producers each fall using online bulletins and through appropriate producers associations and radio. Additional information included field location (Illinois county) and yield level (bushels per acre) of the field from which samples were taken. Due to the lack of measured association between crop yields and nutrient extraction levels, we removed the requirement of yield reporting for sample submission starting on the second year to improve participation. Samples were sent to a commercial laboratory (Brookside laboratories, Inc., New Bremen, OH) for the determination of N, P, and K in grain samples, reported as percentages.
DOI: 10.17632/vszzn7tnrn.1
title: A Meta-Analysis of Consumer Ethnocentrism Across 57 Countries International Journal of Research in Marketing

description: A Meta-Analysis of Consumer Ethnocentrism Across 57 Countries International Journal of Research in Marketing
DOI: 10.17632/zhvszymk7t.1
title: SEM-EDX data on respirable dust from 25 US coal mines

description: This database contains particle-level information (i.e., size, normalized elemental % values, estimated volume and mass, inferred mineralogy class) on 171 respirable dust samples collected in 25 underground mines in the United States. The data was obtained using two different computer controlled SEM-EDX routines to analyze submicron ("sub") and supramicron ("supra") particles. Information on the mines and underground sampling locations is available in: E. Sarver, C. Keles, S, Ghaychi Afrouz, Particle size and mineralogy distributions in respirable dust samples from 25 US underground coal mines, Int. J. Coal Geol. 247 (2021) 103851. https://doi.org/10.1016/j.coal.2021.103851

Following is a list of definitions for the table headers:
ParticleID = strings the SEM-EDX routine (sub or supra)_sample number_analysis frame number_ particle number
ExcelRow = Row number in original spreadsheet (internal reference only)
SubOrSupra = Analysis routine (submicron analysis or supramicron analysis)
SampleNo = Sample number
SampleName = strings the mine region, sample number, sampling location, and filter number (internal reference only)
Region = Mine Region
Mine = Sampled Mine
Location = Sampling Location
SubCount = total number of particles analyzed by the submicron routine
SupraCount = total number of particles analyzed by the supramicron routine 
SubArea = total area analyzed (square microns) by the submicron routine
SupraArea = total area analyzed (square microns) by the supramicron routine 
SubPLD = particles per analyzed area (#/square micron) for the submicron routine 
SupraPLD = particles per analyzed area (#/square micron) for the supramicron routine 
SubPercent = % of particles in the submicron range
SupraPercent = % of particles in the supramicron range 
Particle = Particle Number
Field = Frame Number
Area = projected area of particle (square microns)
Length = the longest dimension of particle (microns)
Width = dimension of particle perpendicular to length (microns) 
O = normalized % of oxygen in particle
Al = normalized % of aluminum in particle 
Si = normalized % of silicon in particle 
C = normalized % of carbon in particle 
Mg = normalized % of magnesium in particle
Ca = normalized % of calcium in particle
Ti = normalized % of titanium in particle
Fe = normalized % of iron in particle
PAD = projected area diameter (nanometers)
Volume = estimated particle volume (cubic microns) 
Mass = estimated particle mass (micrograms)
Class = Mineralogy class (C = carbonaceous; MC = mixed carbonaceous; ASK = kaolinite-like aluminosilicates; ASO = other silicates; SLO = other silicates ; S = silica; M = heavy minerals; CB = carbonates; O = other
DOI: 10.17632/vr8w6v6yj8.1
title: Article database

description: This database contains a list of journal articles used to write the research article titled "Multi-objective Urban Land Use Optimization using Spatial Data: A Systematic Review"
DOI: 10.17632/bnvg89fkf9.1
title: CoFlame: A Refined and Validated Numerical Algorithm for Modeling Sooting Laminar Coflow Diffusion Flames

description: Mitigation of soot emissions from combustion devices is a global concern. For example, recent EURO 6 regulations for vehicles have placed stringent limits on soot emissions. In order to allow design engineers to achieve the goal of reduced soot emissions, they must have the tools to so. Due to the complex nature of soot formation, which includes growth and oxidation, detailed numerical models are required to gain fundamental insights into the mechanisms of soot formation. A detailed description of the CoFlame FORTRAN code which models sooting laminar coflow diffusion flames is given. The code solves axial and radial velocity, temperature, species conservation, and soot aggregate and primary particle number density equations. The sectional particle dynamics model includes nucleation, PAH condensation and HACA surface growth, surface oxidation, coagulation, fragmentation, particle diffusion, and thermophoresis. The code utilizes a distributed memory parallelization scheme with strip-domain decomposition. The public release of the CoFlame code, which has been refined in terms of coding structure, to the research community accompanies this paper. CoFlame is validated against experimental data for reattachment length in an axi-symmetric pipe with a sudden expansion, and ethylene–air and methane–air diffusion flames for multiple soot morphological parameters and gas-phase species. Finally, the parallel performance and computational costs of the code is investigated.
DOI: 10.17632/7fhwrgfh2s.1
title: Dataset for High-Entropy Alloys Phases

description: The dataset contains microstructural phase experimental observations and metallurgy-specific features as introduced and reported in peer-reviewed research articles. 

Secondary data (i.e. composition-specific features, alloy processing and post-processing parameters, and the resulting phases) were collected. Some typical empirical HEA design parameters were calculated using known methods. Data was processed using Excel and R, a language and environment for statistical computing, for purposes of visualization and data analysis.
DOI: 10.17632/sdr42gtxr5.1
title: Correlation Analysis of YouTube Video Titles and Thumbnails  

description: This dataset consist of responses from survey of Correlation Analysis of YouTube Video Titles and Thumbnails.   This survey consist of multiple sets of questions. Each set consist of three questions qualitatively ask for responses with respect to title and thumbnail of video.
DOI: 10.17632/ydj9j88dpr.1
title: Code and Data for On Index Investing

description: This code and data recreates the tables in "On Index Investing" by Jeffrey L. Coles, Davidson Heath, and Matthew C. Ringgenberg.  Please see the "Read Me" file before using it.
DOI: 10.17632/n2c46ds4gn.1
title: Original WB Li et. al. Developmental Cell

description: Acinar cells have been proposed as a cell-of-origin for pancreatic ductal adenocarcinoma (PDAC) after undergoing acinar to ductal metaplasia (ADM). ADM can be triggered by pancreatitis causing acinar cells to de-differentiate to a ductal-like state. We identify FRA1 (gene name Fosl1) as the most active transcription factor during KrasG12D acute pancreatitis-mediated injury, and we have elucidated a functional role of FRA1 by generating an acinar-specific Fosl1 knockout mouse expressing KrasG12D. Using a gene regulatory network and pseudotime trajectory inferred from single nuclei ATAC-seq and bulk-RNA seq, we hypothesized a regulatory model of the acinar-ADM-PanIN continuum and experimentally validated that Fosl1 knockout mice are delayed in the onset of ADM and neoplastic transformation. Our study also identifies that pro-inflammatory cytokines, such as G-CSF, can regulate FRA1 activity to modulate ADM. Our findings reveal that FRA1 is a mediator of acinar cell plasticity and is critical for acinar cell de-differentiation and transformation.
DOI: 10.17632/689pm8s7jc.1
title: Entropy sorting of single cell RNA sequencing data reveals the inner cell mass in the human pre-implantation embryo

description: This repository stores the data and code used to generate the human pre-implantation embryo results in our publication titled, "Entropy sorting of single cell RNA sequencing data reveals the inner cell mass in the human pre-implantation embryo". In this work we present a mathematical framework that we term Entropy Sorting, that allows us to confidently isolate the previously elusive inner cell mass population in single cell RNA sequencing data (scRNA-seq).

The data is subset into four sub folders whose recommended order of usage is as follows:
1. Pre_Implantation_Embryo_Analysis_Code - Contains the code used to generate all the results in our publication. See the README.txt file within this folder for a summary of each workflow provided.
2. Mesitermann_Data - Contains an exact copy of the human pre-implantation embryo scRNA-seq data used in the Mesitermann et al. 2021 publication, which the authors kindly provided to us directly. This dataset was complied from 4 separate scRNA-seq datasets by Mesitermann et al. 2021. See their paper, cited in our publication, for a description of how they complied the 4 datasets. This folder also contains key outputs from the software we present in our work (FFAVES and ESFW), which allows others to re-create the results presented in our publication.
3. Yanagida_Data - An independent human pre-implantation embryo dataset from the Yanagida et al. 2021 paper (GEO ID = GSE171820), which was kindly provided to us by author, alongside a tSNE embedding used in their paper.
4. Nakamura_Data - An independent Macaca embryo dataset from the Nakamura et al. 2016 paper (GEO ID = GSE74767).

We would like to highlight that we have provided exact copies of the pre-implantation human embryo used in the paper to make our work as accessible as possible. However, we recommend that researchers who wish to use the datasets we used in their own work start from the source data (e.g. the Gene Expression Omnibus repositories) to maintain their integrity. Details of each dataset used for this work are provided in the experimental procedures section of our manuscript.
DOI: 10.17632/s6f9pgrw8v.1
title: Data for: Fueling Investments - The Effect of the Agreement on Basic Telecommunications

description: Stata code for data management and regressions.
DOI: 10.17632/p92gj2732w.1
title: Multi-mode Fault Diagnosis Datasets of Gearbox Under Variable Working Conditions

description: The gearbox is a critical component of electromechanical systems. The occurrence of multiple faults can significantly impact system accuracy and service life. The vibration signal of the gearbox is an effective indicator of its operational status and fault information. However, gearboxes in real industrial settings often operate under variable working conditions, such as varying speeds and loads. It is a significant and challenging research area to complete the gearbox fault diagnosis procedure under varying operating conditions using vibration signals. This data article presents vibration datasets collected from a gearbox exhibiting various fault degrees of severity and fault types, operating under diverse speed and load conditions. These faults are manually implanted into the gears or bearings through precise machining processes, which include health, missing teeth, wear, pitting, root cracks, and broken teeth. Several kinds of actual compound faults are also encompassed. The development of these datasets facilitates testing the effectiveness and reliability of newly developed fault diagnosis methods.
DOI: 10.17632/kwb8s3khbw.1
title: Survey dataset on the perfectionism, academic resilience, and subjective well-being in one university students, South Korea

description: The data of this article was done to identify the correlation among perfectionism, academic resilience and subjective well-being and identify factors that affect the subjective in undergraduate students. Data were collected from 245 students in one university located S city in South Korea.
DOI: 10.17632/w5nd8232nn.1
title: Number of hospitals in Republic Uzbekistan by region

description: Official Statistical Data: Number of hospitals and outpatient clinics by the Ministry of Health of the Republic of Uzbekistan.
DOI: 10.17632/zxc6sdsj8d.1
title: Dataset of Factors affecting online cheating by accounting students: the relevance of social factors and the fraud triangle model factors

description: • Data was fully used in its description of the way opportunities, pressures, rationalization, subjective norms, social trust, behavioral intention to cheat can influence the cheating behavior among accounting students in the context of Jordan during the Covid-19 pandemic; • The dataset is useful for further comparisons in further studies dedicated to distance learning issues among nations that have distinct contexts and are experiencing different stages of Covid-19 pandemic; • Data is useful in providing insights and direction on the way to understand the motivations underlying the behavioral intention to cheat while university exams are held online through the integrated theoretical framework that includes the social capital theory and the fraud triangle theory based on literature; • Dataset can be used as a guide and reference by the educators who are seeking to minimize the chances for dishonest students to cheat in online exams; • The dataset outcome not only can help educational universities to understand how severe is the online cheating problem among students in Jordan, but they can also help them identify the underlying motives behind the cheating behavior during these difficult times. Such understanding is particularly important to help these institutions producing a more fair assessment system for students' performance while adopting the online learning system as the primary approach of education in the country.
DOI: 10.17632/8pbbjf274w.1
title: Gastrointestinal Bleeding WCE images Dataset

description: The dataset contains the wireless capsule endoscopy (WCE) images of gastrointestinal (G) bleeding from Pakistan. All images were obtained with the help of Turkey Hospital Muzaffargarh (THM), Muzaffargarh, Pakistan, from January 2022 to May 2022. The dataset contains a total of 226 GI images, including 113 images of GI bleeding or lesions and 113 WCE images of normal patients.
DOI: 10.17632/w4vcwy5ww6.1
title: Raw Data: Empirical Study of Edmonton-Area Black Undergraduate Students’ Intentions and Views Regarding Applying to Law School

description: Survey of Black undergraduate students contemplating applying to law school regarding their intentions.
DOI: 10.17632/59r8vt4j6w.1
title: iCLO-dBOG

description: Paisaje sonoro plazas de mercado tradicionales. Contiene la obra sonora iCLO-dBOG y algunos registros sonoros de referencia.
La obra sonora iCLO-dBOG, es el resultado de una investigación centrada en la identidad sonora de las plazas de mercado en Colombia. Se enmarca en la investigación-creación como modo de producción artística relacionada con procesos académicos y describe la manera como el material documental obtenido de las grabaciones de campo se usa para la composición de la obra. Mediante una metodología que integra los hallazgos de la investigación con el proceso creativo, se busca expresar la identidad de las plazas en un relato sonoro. Esto implica llevar al oyente desde una escucha referencial, donde se reconocen sonidos típicos de las prácticas comerciales tradicionales, hasta una escucha reducida donde los sonidos cargados de significados causales son intervenidos en vivo desde dos ordenadores y separados de su referente figurativo para resaltar sus cualidades plásticas. La mediación tecnológica desvela las cualidades acústicas de bajo nivel, como la amplitud, frecuencia y timbre, expresando así el metabolismo sonoro que lleva la escucha desde lo referencial hasta el plano meramente estético donde la identidad se expresa desde atributos acústicos profundos. Esta intervención busca transformar la experiencia auditiva del oyente, pasando de una escucha pasiva, donde se reconocen los sonidos y referentes familiares, a una escucha activa que invita al discernimiento estético y a una apreciación más profunda de la identidad acústica de las plazas de mercado.
DOI: 10.17632/hx6f852hw4.2
title: Rice Leaf Bacterial and Fungal Disease Dataset

description: This is a rice leaf disease dataset: This data set contains an image dataset of eight different Bangladeshi rice leaf diseases—There are 1,701 original images in the entire collection. We gathered these photographs over a period of four months, from July 2023 to October 2023, from separate locations of Sirajganj and Pabna Zilla under a variety of outdoor lighting situations as well as inside lighting with acceptable backgrounds. The file also includes 5188 extra augmented photos. The data set contains eight rice leaf diseases,Bacterial Leaf Blight (Xanthomonas oryzae pv. oryzae), Brown Spot (Cochliobolus miyabeanus), Leaf scald (Microdochium oryzae), Narrow Brown Leaf Spot (Cercospora janseana), Rice Hispa (Dicladispa armigera), Sheath Blight (Rhizoctonia solani), Leaf Blast (Pyricularia oryzae) and Healthy Rice Leaf. This dataset will benefit researchers applying machine learning in several ways.