cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/xt2gxmfc8z.1
title: Mediterranean Peatland Water, Gas, and Soil content (Moltifau peatland, Corsica Island, France)

description: The present dataset is part of a research that aims to status the carbon storage function of a Mediterranean peatland in changing climate conditions. The scientific strategy relies on a seasonal geochemical survey sourcing the carbon origin in peatland water and interfaces with the atmosphere. This research on a representative Mediterranean peatland reveals the seasonality of hydrochemical processes and dissolved carbon inputs from primary production, organic matter oxidation, and time-changing recharge components within the catchment (atmospheric water, river water, shallow groundwater, deep groundwater). 
Mixing proportions of all recharge components known (Santoni et al., 2021), the study applies a “reverse” end-member mixing analysis to define the theoretical peat water δ13C-DIC value and compare it to the measured one. The model explains 65 % of the data, demonstrating the watershed's influence on peatland carbon content—such terrestrial carbon fluxes toward a peatland needed to be reported and quantified. Furthermore, in 35% of the cases, peatland processes such as primary production and organic matter oxidation drive the peat water's carbon content. Then, δ18O, δ2H, peat organic and inorganic properties, δ13C-TOC, and 13C-CO2 data demonstrate the dominance of primary production, evidencing the role of groundwater in CO2 production and carbon storage capacity of the Mediterranean peatland. This research proves the relevance of geochemistry and isotope hydrology tools to disentangle and rank peatland water and carbon processes. Thus, it constitutes an innovative methodology designed to provide the key elements to consider in order to set up a carbon balance diagnosis of peatlands worldwide.  Overall, the present research reveals the necessity to consider the interactions between water and carbon cycle processes, with particular consideration for groundwater as a CO2 source at the peatland-atmosphere interface, to build better models for the future evolution of the global climate.
(Publication in process)
DOI: 10.17632/xztwjmktrg.2
title: COVID-19 Chest X-ray Images

description: 368 Chest X-ray Images taken from confirmed COVID-19 subjects, which were admitted to hospital due to COVID-19 respiratory complications.
DOI: 10.17632/ckwc76xr2z.2
title: Dataset for multi-channel surface electromyography (sEMG) signals of hand gestures

description: This dataset contains electromyography (EMG) signals for use in human-computer interaction studies. The dataset includes 4-channel surface EMG data from 40 participants with an equal gender distribution. The gestures in the data are rest or neutral state, extension of the wrist, flexion of the wrist, ulnar deviation of the wrist, radial deviation of the wrist, grip, abduction of all fingers, adduction of all fingers, supination, and pronation. Data were collected from 4 forearm muscles when simulating 10 unique hand gestures and recorded with the BIOPAC MP36 device using Ag/AgCl surface bipolar electrodes. Each participant's data contains five repetitive cycles of ten hand gestures. A demographic survey was applied to the participants before the signal recording process. This data can be utilized for recognition, classification, and prediction studies in order to develop EMG-based hand movement controller systems. The dataset can also be useful as a reference to create an artificial intelligence model (especially a deep learning model) to detect gesture-related EMG signals. Additionally, it is encouraged to use the proposed dataset for benchmarking of current datasets or for validation of machine learning and deep learning models created with different datasets in accordance with the participant-independent validation strategy.
DOI: 10.17632/dsdnv2s7t3.1
title: Knowledge Management Research in Indonesia Dataset (1999-2019)

description: The knowledge management reseach dataset with affiliated research institutions is from Indonesia, which was indexed by Scopus from 1999 to 2019. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/jc3rwftjnf.1
title: the Korea National Health and Nutrition Examination Survey (KNHANES) 2007-2016

description: The Korea National Health and Nutrition Examination Survey (KNHANES) is a national surveillance system that has been assessing the health and nutritional status of Koreans since 1998. Based on the National Health Promotion Act, the surveys have been conducted by the Korea Centers for Disease Control and Prevention (KCDC). This nationally representative cross-sectional survey includes approximately 10 000 individuals each year as a survey sample and collects information on socioeconomic status, health-related behaviours, quality of life, healthcare utilization, anthropometric measures, biochemical and clinical profiles for non-communicable diseases and dietary intakes with three component surveys: health interview, health examination and nutrition survey. The health interview and health examination are conducted by trained staff members, including physicians, medical technicians and health interviewers, at a mobile examination centre, and dieticians’ visits to the homes of the study participants are followed up. KNHANES provides statistics for health-related policies in Korea, which also serve as the research infrastructure for studies on risk factors and diseases by supporting over 500 publications. KCDC has also supported researchers in Korea by providing annual workshops for data users. KCDC has published the Korea Health Statistics each year, and microdata are publicly available through the KNHANES website (http://knhanes.cdc.go.kr).
DOI: 10.17632/vzb8kvjn7n
title: MARINE CLAY

description: The data can describe the behavior of the bound water in marine clay.
DOI: 10.17632/2d3kr8zynf.4
title: Arbovirus clinical data, Brazil, 2013–2020

description: This data set presents clinical, sociodemographic, and laboratory information of confirmed patients of Dengue and Chikungunya, as well as patients cases discarded from these same diseases. The data were accounted for by the Health Problem and Notification Information System, from Portuguese Sistema de Informação de Agravo de Notificação (SINAN), that occurred in Brazil, from 2013 to 2020. The data set has 7,632,542 records and 56 attributes. This data set contains four CSV files, the "data set.csv" file contains the pre-processed data set, the "attributes.csv" file contains information about each attribute present in the data set, and the "dengue.csv" and "chikungunya.csv" files contain the data set originated from SINAN without the application of any pre-processing technique.

Some columns of the dataset have the IBGE code as a value, a code from the Brazilian Institute of Geography and Statistics. For better understanding, it is possible to use the institute's link to link the code with the city, state or country.
DOI: 10.17632/7bsc526pzn.1
title: Dataset of Indoor Air Pollutant Concentration using Low Cost IOT Based System

description: Indoor air pollutant concentration data is collected for all the seasons in Pune city, India, from internet of things-based system built using low cost sensors. The raw data contains 1,39,448 records collected from Nov 2020 to Dec 2021. Air pollutant PM2.5 (Particulate Matter) is measured using GP2Y1010AU0F Dust Smoke Particle Sensor, NO2 (Nitrogen Dioxide), NH3 (Ammonia) and CO (Carbon Monoxide) pollutant measured using MICS-6814 sensor. CO2 (Carbon Dioxide) and TVOC (Total Volatile Organic Compounds) measurement is done using CCS811 sensor, Ozone (O3) measured using MQ131 Semiconductor Sensor. Temperature, Humidity measured using BME 280 sensor. Measurement units of  NH3 is PPM, NO2 in PPM, CO in PPM, PM2.5 in ug/m3, Temperature in Celsius, Pressure in hPa, Altitude in ft, Humidity in RH, CO2 in PPM, TVOC in PPB, Ozone in PPB. This data can be used for study and evaluations of prediction models and low-cost sensor data. It can be used for the study of the pollutant’s patterns in COVID-19 pandemic.  It will help policymakers to develop policies to monitor air pollution impact.
DOI: 10.17632/tg7cttx777.1
title: The use of immunohistochemical staining in Mohs micrographic surgery for melanoma: a systematic review

description: Supplemental materials: PRISMA checklist, Search Query, and Methodological Quality Analysis.
DOI: 10.15468/dl.vc9wsn
title: Occurrence Download

description: A dataset containing 637 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Podocarpus totara G.Benn. ex D.Don",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 637 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009283-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/y3s8fvv59k.1
title: Indoor Environmental Quality database for a low-income housing in Merida, Yucatan, Mexico

description: Poor environmental quality represents a global challenge due to its influence on human and habitat health. Poor environmental quality is a problem of national interest in Mexico with limitations in the development of instrumentation and universal access. This problem is particularly more severe in extreme environments where the probability of technical failures increases due to climatic conditions. In this context, a low-cost measurement system was developed to measure environmental quality variables: Temperature (°C), Atmospheric Pressure (hPa), Relative Humidity (%), Particulate Matter PM1.0, PM2.5, PM10 (ug/m3), CO₂ (ppm), H₂S (ppm), and Noise (dB). The objective was to generate a database in a warm humid climate, to increase quantitative knowledge that will lead to actions to improve environmental quality in Mexican homes. To achieve this objective, an experimental method was developed with a low-cost prototype that followed a calibration and validation procedure that supports the obtained results. Measurements were performed in a social housing in Merida, Yucatan with intervals of 60 minutes for one year (July 12th, 2023, to July 12th, 2024). As a result, 7406 data points were obtained for each measured variable, which can be used by public and private actors interested in improving the user's quality of life under extreme climate conditions. It is important to note that the database with universal access to knowledge is part of the efforts to increase science-based decisions towards energy equity and security of housing in Latin America.
DOI: 10.17632/58byj59746.1
title: Imaging data and 3D reconstruction of neuronal dendrites

description: Three pairs of WT and Zfp661 KO mouse littermates, including both male and female pairs aged between 60 to 66 days, were used in this assay. The brains were isolated and processed for Golgi-Cox staining using FD Rapid GolgiStain Kit (FD NeuroTechnologies, PK401) according to the manufacturer’s protocol. The pyramidal neurons in the somatomotor area of Layer 2/3 (Bregma 1.70 mm to 1.18 mm) were sampled and imaged using a Leica DM6000B (20X/0.70) microscope and LAS X software with optimal z-step of 0.52 μm and the same settings for all imaging. To better trace neuronal dendrites from Golgi-Cox staining, Z-stacked images were pre-processed using Fiji/ImageJ2 (v2.9.0/1.53t) as follows: the image format was transformed into 8-bit type, both the signals and LUT were inverted, and the scale unit was set to microns. All dendrites from sampled neurons were traced using the SNT toolbox in Fiji/ImageJ2 with the “A* search algorithm” enabled, and the trace for each dendrite was further manually verified. 

The uploaded zip file contains the mouse information, preprocessed images and neuronal dendrite traces.
DOI: 10.17632/vxgfm2p5md.1
title: Датасет для диссертации по теме «Влияние нематериальных активов компании на ее рыночную капитализацию»

description: Данные для диссертации по теме «Влияние нематериальных активов компании на ее рыночную капитализацию»
DOI: 10.17632/dj95jh332j.1
title: AR-ASAG-Dataset

description: The ARabic Dataset for Automatic Short Answer Grading Evaluation V1. ISLRN 529-005-230-448-6. Our dataset consists of reported evaluations relate to answers submitted for three different exams submitted to three classes of students. The exams were conducted under natural conditions of evaluation. Each test consists of 16 short answer questions (a total of 48 questions). For each question, a model answer is proposed. Students submitted answers to these questions. The number of answers obtained is different from one question to another. The dataset includes a total of 2133 pairs (Model Answer, student answer). the Dataset encompasses 5 types of questions: • "عرف ": Define? • "إشرح": Explain? • "ما النتائج المترتبة على": What consequences? • "علل": Justify? • "ما الفرق": What is the difference AR-ASAG Dataset is available in different versions: TXT, XML, XML-MOODLE and Database (.DB). The .DB format allows making the necessary exports according to specific analysis needs. The XML-MOODLE format is used on Moodle e-learning Platforms For each pair, two grades (Mark1 and Mark2 ) are associated with a manual Average Gold Score Both manual grades are available in the dataset. Inter-Annotators Agreement: - (Pearson Correlation: r=0.8384) - (Root Mean Square Error : RMSE=0.8381). The Dataset can be also used for essay scoring as the students's answers responses take to reach 4-5 sentences. The Dataset exist in TXT, XML, XML-MOODLE Versions The name of the file is representative of its content. We use the term "Mark" to specify "Grade" For privacy reasons, no student identifiers are used in this Dataset.
DOI: 10.17632/9xjh66g4z2.1
title: InterPhon: Ab initio interface phonon calculations within a 3D electronic structure framework

description: This work provides the community with an easily executable open-source Python package designed to automize the evaluation of Interfacial Phonons (InterPhon). Its strategy of arbitrarily defining the interfacial region and periodicity alleviates the excessive computational cost in applying ab initio phonon calculations to interfaces and enables efficient extraction of interfacial phonons. InterPhon makes it possible to apply all of the phonon-based predictions that have been available for bulk systems, to interfacial systems. The first example, in which this package was applied to InAs surfaces, demonstrates a systematic structure search for unexplored surface reconstructions, navigated by the imaginary mode of surface phonons. It eventually explains the anisotropic surface vibrations of the polar crystal. The second example, involving oxygen adsorption on Cu, reveals adsorption-induced vibrational change and its contribution to energetic stability. The third example, on a Si/GaAs interface, shows distinct vibrational patterns depending on interfacial structures. It leads to a prediction regarding the structural transition of interfaces and unveils the processing conditions for spontaneous growth of GaAs nanowires on Si. High-level automation in InterPhon will be of great help in elucidating interfacial atomic dynamics and in implementing an automated computational workflow for diverse interfacial systems.
DOI: 10.17632/kf4rr6zth6.1
title: Summary

description: Since the research work is for summarizing short text which consists of news related to domains like travel, sports ,gadgets , automobile,politics, health etc.The maximum size of the data included is 10k words . The research is scalable and can be tried for large data sets also.
DOI: 10.17632/2c3xf92pk4.1
title: Ultrasound of Dairy Cows' Udder (Mammary Gland) & Sonogram Echotexture Analysis

description: This public dataset contains: 

1. A folder with B-mode sonograms (3072 in total) of the bovine mammary gland. 
2. A .csv file with the daily milk yield on measurement days of the dairy cows participating in this study.
3. A .csv file with the feature set deriving from echotexture analysis of the B-mode sonograms.
4. A "Data_Interpretation" file, explaining how to interpret and use the data.
 
Research Hypothesis: 
Ultrasonography is being utilized in the examination of dairy animals’ mammary gland for more than three decades. Recently, echotexture analysis has been employed by some researchers to gain deeper information from mammary gland's sonograms and investigate pathological conditions. In our research article "A Deep Learning Algorithm Predicts Milk Yield and Production Stage of Dairy Cows utilizing Ultrasound Echotexture Analysis of the Mammary Gland" we hypothesized that a deep neural network could utilize features from echotexture analysis of mammary gland sonograms to obtain predictions about the cows’ daily milk yield and production stage. 

Notable Findings: 
A deep neural network can utilize features from mammary sonograms’ echotexture analysis to predict a cows’ daily milk yield and production stage. 
Our research findings are presented in detail in our research article "A Deep Learning Algorithm Predicts Milk Yield and Production Stage of Dairy Cows utilizing Ultrasound Echotexture Analysis of the Mammary Gland". 

Data Interpretation:
Text file “Data_Interpretation” includes the information needed to interpret and use the data. An extensive description about the data collection methodology is provided in our research article "A Deep Learning Algorithm Predicts Milk Yield and Production Stage of Dairy Cows utilizing Ultrasound Echotexture Analysis of the Mammary Gland".
DOI: 10.17632/y4cpkdz77d.1
title: Mechanism of noncoding RNA associated N6-Methyladenosine recognition by an RNA processing complex during IgH DNA recombination

description: Immunoglobulin heavy chain (IgH) locus-associated G-rich long noncoding RNA (SµGLT) is important for physiological and pathological B cell DNA recombination. We demonstrate that the METTL3 enzyme-catalyzed N6-methyladenosine (m6A) RNA modification drives recognition and 3’-end processing of SµGLT by the RNA exosome, promoting class switch recombination (CSR) and suppressing chromosomal translocations. The recognition is driven by interaction of the MPP6 adaptor protein with nuclear m6A reader YTHDC1. MPP6 and YTHDC1 promote CSR by recruiting AID and the RNA exosome to actively transcribing SµGLT. Direct suppression of m6A modification of SµGLT or of m6A reader YTHDC1 reduces CSR. Moreover, METTL3, an essential gene for B cell development in the bone marrow and germinal center, suppresses IgH-associated aberrant DNA breaks and prevents genomic instability. Taken together, we propose coordinated and central roles for MPP6, m6A modification, and m6A reader proteins in controlling long noncoding RNA processing, DNA recombination and development in B cells.
DOI: 10.17632/2dc59y33n8.1
title: Who is buying green products?

description: This study uses empirical methods to uncover the underlying theoretical relationships between the variables : Independent variable is sustainability consciousness; mediator is environmental attitude; moderator is ecotourism, depentent variable is green purchase intention.
DOI: 10.17632/4cy9stxngg.1
title: Encuesta de Caracterización Socioeconómica y Ambiental de la Comuna Las Gilces de Portoviejo

description: Encuesta aplicada en la comuna Las Gilces del cantón Portoviejo, provincia de Manabí, Ecuador para generar datos de sus habitantes en el ámbito demográfico, económico, social y ambiental, que sirve de base para conocer su realidad y para la planificación, organización, diseño y aplicación de políticas públicas que permitan fortalecer la consecución del desarrollo económico local de este importante sector de la ciudad
DOI: 10.17632/rfscn9rj92.1
title: BOKASUN: A fast and precise numerical program to calculate the Master Integrals of the two-loop sunrise diagrams

description: Abstract We present the program BOKASUN for fast and precise evaluation of the Master Integrals of the two-loop self-mass sunrise diagram for arbitrary values of the internal masses and the external four-momentum. We use a combination of two methods: a Bernoulli accelerated series expansion and a Runge-Kutta numerical solution of a system of linear differential equations. Title of program: BOKASUN Catalogue Id: AECG_v1_0 Nature of problem Any integral arising in the evaluation of the two-loop sunrise Feynman diagram can be expressed in terms of a given set of Master Integrals, which should be calculated numerically. The program provides a fast and precise evaluation method of the Master Integrals for arbitrary (but not vanishing) masses and arbitrary value of the external momentum. Versions of this program held in the CPC repository in Mendeley Data AECG_v1_0; BOKASUN; 10.1016/j.cpc.2008.10.011 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.17632/ygwhjpp2c9.1
title: Replication files for: Quantitative Sovereign Default Models and the European Debt Crisis

description: We divided the replication files into three sub-folders: 1. Section 2 – this folder contains the Stata data and do files to replicate our graphs from Figure 1 and the regression results in Table 1. 2. Section 4 calibration targets – this folder contains a Matlab data and script file to compute the targeted moments for the two calibration exercises in Section 4.1. 3. Section 4 model – this folder contains the Julia files to compute the solution of the model.1 In addition to computing moments, the Julia files save a text file for Matlab with simulation results. This folder also contains the Matlab files to produce Figures 3-5 in the paper.
DOI: 10.17632/t4ck8gp3jh.1
title: Up-to-date earthquake and focal mechanism solutions datasets for the assessment of seismic hazard in the vicinity of the United Arab Emirates

description: The first dataset is an updated Poissonian and unified earthquake catalog for the UAE spanning the time period from the year 658 to 2019. The second file includes focal mechanism solutions data for the surrounding of the United Arab Emirates, for the time 1923 to 2015.
DOI: 10.17632/z4v48pb992.2
title: Learning about the Consumption Risk Exposure of Firms

description: This file contains the replication code for “Learning about the Consumption Risk Exposure of Firms”, published in the Journal of Financial Economics.
DOI: 10.17632/dcp9zb7scx.1
title: The impact of time devoted to video games on student achievement dataset

description: Dataset for the article "The impact of time devoted to video games on student achievement" consists of an SPSS database, questionnaire, Google Forms survey, and a Scimago Grafica graph.
DOI: 10.17632/nwkkd6k3gc.1
title: Handcrafted Indian Face (HIF) Dataset

description: This dataset consists of Indian face images of individuals with masks and without masks . Also it includes few images with occlusion viz. googles and spectacles alongwith masks. It includes images in varied illumination conditions as well. There are 11 subjects. Each subject has variable number of images.
DOI: 10.17632/8xrhw6svd5.1
title: Undulating Relativity + § 36 The Wave Function

description: § 36 The Wave Function