cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/47vj3yyb5v
title: Dataset on Bilateral Idiopathic Carpal Tunnel Syndrome: Crossover Study of Two Combined Physiotherapeutic Treatment Methods on Chirurgical and Clinical Patients

description: This data describe a randomized controlled crossover trial of 73 participants with idiopathic bilateral carpal tunnel syndrome (CTS) who underwent two combined physiotherapeutic treatment methods: myofascial mobilization (IASTM) and stretching; on chirurgical and clinical conditions.

Patients were randomly assigned to two groups: starting with stretching followed by IASTM and starting with IASTM followed by stretching. Then 43 patients underwent surgery on the hand with more severe involvement and physical therapy rehabilitation was started 30 days after for a period of 4 weeks. After the 1-week interval the participants who started with stretching were referred to IASTM and vice versa, following the same previous patterns. The outpatient reassessments took place at 3 to 6 months.

Likewise, for another 30 patients who did not undergo surgery (clinical patients) we followed the same protocol: selected at random into two groups: starting with stretching followed by IASTM or starting with IASTM followed by stretching. Before starting therapy, patients were assessed (baseline). Both stretching and IASTM were performed in two sessions per week over a period of four weeks, according to standardized protocols. After the one-week interval (wash-out 1), outcome measures were collected at time 1. Next, participants who initially performed stretching were referred to IASTM and vice-versa, following the same patterns as before. Assessment at time 2 occurred after a second interval period (wash-out 2), and outpatient reevaluations were done three and six months after time 2.

The sample allocation and the design of the experiment that originated this database are better illustrated in the Flowchart.pdf file.
DOI: 10.17632/v9p3zt6v52
title: Tensile acoustic emission signal data set for 7075-t6 aluminum alloy

description: Tensile AE data and external load deformation of 7075-t6 aluminum alloy
DOI: 10.17632/r9984s6rxd
title: The audio dataset of washing machine

description: The Sanyo pulsator washing machine model XQB60-B830SS is tested and working mode is standard-washing-mode. The SONY digital audio recorder of model ICD-PX470 is used to collect the audio data. The sampling rate is 44100Hz. 
A total of 60 sets of standard-washing-mode data were collected in the experiment. The data is divided into training data and test data sets according to 7:3. 42 sets of training data are used to train the SVM decision tree model and verify the decision tree model. 18 sets of test data are used to construct the state-sequence of the washing machine.
The 42 sets of training data are divided into a sample of 10s and the available data scale is as follows: water intake 1400, soaking 2100, washing 3400, dehydration 1400. Divide the data according to the ratio of training data: validation data=7:3
DOI: 10.17632/3kksgs4zc2
title: CIPN_NCKUH_2019

description: A data set for establishing a simplified diagnostic criteria of chemotherapy induced peripheral neuropathy.
DOI: 10.17632/xznbxgfpxx
title: GEMSTONE

description: Experimental data for GEMSTONE and GEMSTONE-NOE NMR pulse sequences applied to estradiol, synthetic carbocycles, and a mixture of cinchona alkaloids. Supporting information for DOIs: 10.1002/anie.202011642 and 10.1002/ange.202011642.
DOI: 10.17632/h8hhdcn83j
title: COVID-19 Vaccine Attitude Scale (COVID-19 VAS)

description: The data for the development and standardization of the "COVID-19 Vaccine Attitude Scale (COVID-19 VAS)" questionnaire are presented in English ("COVID-19 Vaccine Attitude Scale (Eng).xlsx") and in Russian ("COVID-19 Vaccine Attitude Scale (Rus).xlsx"). The study sample includes N = 1965 undergraduate, specialist and master students, of which N = 1592 (81%) women and N = 373 (19%) men aged 16 to 60 years, mean age M = 24.7, SD = 8.4, Me = 21.0. Study was conducted in Moscow State University of Psychology & Education (MSUPE). The questionnaire structure includes 5 scales identified by the method of exploratory factor analysis: Scale 1 "The benefits of vaccination against COVID-19 for an individual and society", Scale 2 "Fear of incidental effects of vaccination against COVID-19 and distrust of information about the vaccination safety", Scale 3 “Denial of the danger of coronavirus and hope for natural immunity”, Scale 4 “Confidence in the serious negative consequences of the coronavirus vaccine” and Scale 5 “Disbelief in the proven international level effectiveness of Russian vaccines”. The construct validity of the questionnaire was statistically proven. Confirmatory factor analysis verified satisfactory goodness-of-fit between the empirical data and the questionnaire structure. The scales correlate with each other moderate, the relationship directions correspond to the expected ones. The high internal reliability of all scales was statistically confirmed using Cronbach's alpha. Satisfactory convergent validity of the corresponding scales of the “COVID-19 Vaccine Attitude Scale (COVID-19 VAS)” with natural science literacy, intelligence and fear of COVID-19 disease was confirmed. All correlations are weak, but theoretically expected and explainable. Statistically proven differential validity. Stanines are calculated. The COVID-19 VAS can be recommended  to prepare, conduct and evaluate the effectiveness of educational activities on vaccine prevention against COVID-19 among university students
DOI: 10.17632/tt37566yvz
title: Associations between rheumatoid arthritis and skin cancer: A bidirectional two-sample Mendelian randomization study.

description: Chronic inflammation has the capacity to induce gene mutations and DNA damage, which can lead to tumorigenesis. Consequently, the relationship between chronic inflammatory diseases and tumors is a subject of significant interest in research. Rheumatoid arthritis (RA), as a chronic autoimmune inflammatory disease, has established the relationship between RA, biologic disease-modifying antirheumatic drugs (bDMARDs), and skin cancer.Observational studies have indicated that the utilization of bDMARDs in RA could elevate the risk of non-melanoma skin cancer (NMSC). However, the precise factors responsible for the increased risk of skin cancer remain unknown. Mendelian randomization (MR) employs genetic variation as a natural experiment to study associations between exposure and outcome, with the advantage of being less likely to be affected by confounding factors or reverse causation than observational studies. Here, we conducted a bidirectional MR analysis to investigate the associations between RA and skin cancer.
DOI: 10.17632/dnfx7b2g9s
title: Engagement inventory CFA 2020 Ossio

description: Data collected for the Confirmatory Factor Analysis for a new inventory to measure employee engagement (in Spanish). The items are 5 point likert were made to measure four dimensions of engagement proposed by Kahn (1992): Attentiveness (items 1-4), Conection (5-7), Integration (8-13), and Focus (14-16). Reverse items are: 5, 6, 7 (already reversed in the codified sheet). Missing values = 999. 541 responses collected on Surveymonkey.com in 2020.
DOI: 10.17632/dwywt7mz95
title: SaurKshetra: A Dataset for Solar Farms Potential Site Mapping using Suitability parameters in India

description: This dataset is a structured, high-precision compilation of environmental and solar irradiance data sourced from NASA POWER, covering India's major geographic zones over the span of one year (January to December 2022). It includes seven critical parameters—such as solar radiation, temperature, cloud cover, albedo, and precipitation—essential for evaluating solar power generation potential. The primary goal of the dataset is to aid in the identification of optimal locations for solar energy infrastructure by applying geospatial and machine learning techniques. Carefully preprocessed for consistency and organized for ease of use, this dataset is not only useful for current solar site suitability analysis but also offers long-term value to researchers, urban planners, and policymakers. It supports advanced analytics like clustering, classification, and visualizations, and can serve as a foundation for predictive modeling, transfer learning, and sustainability-oriented decision-making in the field of renewable energy.
DOI: 10.17632/ksvm6ts2s9
title: Data for: Model-free Simulation and Fed-batch Control of Cyanobacterial-Phycocyanin Production in Plectonema by Artificial Neural Network and Deep Reinforcement Learning

description: The supplementary data includes the raw data for fitting the cell density vs. absorbance, and the experimental data of Plectonema growth profiles used in the article.
DOI: 10.17632/7yr6ktj7gk
title: Map of the Llano Estacado of North America

description: The Llano Estacado is a physiographic region located in the southern Great Plains of North America.  Renowned for its remarkably level surface and the towering escarpments along its outer margins, the elevated plains of the Llano Estacado form an immense tableland that stands in high relief at the southern end of the Great Plains.  The Llano Estacado is not a complex region but there still remains some uncertainty regarding the precise definition of its boundaries.  Recognizing that a scientific study of the Llano Estacado region must include a firm definition of its boundaries, a recent attempt was made by the authors to better define the boundaries of this region. Here we provide digital map data in KML format.
DOI: 10.17632/dzv5t8zm8s
title: Data for: Production scheduling and lot streaming at flexible job shops environments using constraint programming

description: Data based in the Dataset provided by Fattahi, P., Saidi Mehrabad, M., & Jolai, F. (2007) “Mathematical modeling and heuristic approaches to flexible job shop scheduling problems”, Journal of Intelligent Manufacturing, 18, 331-342, and extended with lot sizes and lots sequence-dependent setups.
DOI: 10.6084/m9.figshare.22363012.v6
title: FracAtlas: A Dataset for Fracture Classification, Localization and Segmentation of Musculoskeletal Radiographs

description: FracAtlas is a musculoskeletal bone fracture dataset with annotations for deep learning tasks like classification, localization, and segmentation. The dataset contains a total of 4,083 X-Ray images with annotation in COCO, VGG, YOLO, and Pascal VOC format. This dataset is made freely available for any purpose. The data provided within this work are free to copy, share or redistribute in any medium or format. The data might be adapted, remixed, transformed, and built upon. The dataset is licensed under a CC-BY 4.0 license. It should be noted that to use the dataset correctly, one needs to have knowledge of medical and radiology fields to understand the results and make conclusions based on the dataset. It's also important to consider the possibility of labeling errors.Furthermore, any publication that utilizes this resource should acknowledge the original paper, and the authors are encouraged to share their code and models to assist the research community in replicating the experiments and promoting the field of medical imaging.
DOI: 10.15468/dl.dqgf4d
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Argentina Linnaeus, 1758",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((35.9648 -7.1504,26.9648 -7.1504,26.9648 -16.1504,35.9648 -16.1504,35.9648 -7.1504))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012857-250525065834625/datasets/export for details.
DOI: 10.17632/z2zfhhnsf2
title: Smarthome adoption dataset

description: The data file contains the coded dataset for the smart home adoption research project. Initial trust as a new variable of study in UTAUT2 model. The data was collected from 505 individuals on the established scale items for all constructs of UTAUT2 and Initial Trust. 
Independent variables:
1. Facilitating condition
2. Habit
3. Effort Expectancy
4. Social Influence
5. Hedonic motivation
6. Price Value
7. Performance expectancy
8. Firm Reputation
9. Structural assurance
10. Trust propensity
11. Information quality
12. Initial Trust (mediating variable)
13. Behavioural intention (Dependent variable)
Smart PLS was used to analyse the data and check the data fit using Partial least square structural equation model. The data contains information of the following demographics:
Age Range: 18-24 years/ 25-29 years/ 30-39 years/ 40-59 years/ &gt; 60 years 
Annual Income (in Rupees): Less than 5,00,000 /5,00,000 - 10,00,000/ 10,00,000 – 20,00,000/ More than 20,00,000 
Type of smart home device used 





DOI: 10.17632/2zpbjs22k3
title: Indonesian News Corpus

description: This corpus contains 150,466 news articles, which is derived from several freely accessible Indonesian news website. The corpus is designated for research purpose only. The news websites are: • kompas.com is a registered trademark of PT. Kompas Cyber Media. https://inside.kompas.com/about-us • tempo.co is a registered trademark of PT INFO MEDIA DIGITAL. https://www.tempo.co/about • merdeka.com is a registered trademark of PT KAPAN LAGI DOT COM NETWORKS. https://www.merdeka.com/company/tentang-kami.html • republika.co.id is a registered trademark of PT Republika Media Mandiri. https://www.republika.co.id/page/about • viva.co.id is a registered trademark of PT. Viva Media Baru. https://www.viva.co.id/tentang-kami • tribunnews.com is a registered trademark of PT Tribun Digital Online. http://www.tribunnews.com/about-us The corpus is a part of bachelor thesis work of Aad Miqdad Muadz Muzad under the supervision of Faisal Rahutomo. We crawled several categories of the websites for 6 months from July 2015 until December 2015.
DOI: 10.17632/vjdh9pr9sg
title: Source Code and Data for "Development and verification of prognostic nomogram for extraskeletal Ewing's sarcoma based on the SEER database"

description: Source Code and Data for "Development and verification of prognostic nomogram for extraskeletal Ewing's sarcoma based on the SEER database"
DOI: 10.17632/h2gzf2pggm
title: Railway network of Galicia and Austrian Silesia 1847 - 1914

description: The dataset presents the historical railway network of Galicia and Austrian Silesia – two regions of the Habsburg Empire, covering more than 80 000 km2, currently divided among Czechia, Poland and Ukraine. The network covers the times of railway appearance and the most dynamic development of the 19th and beginning of the 20th century, up to 1914 – the outbreak of the First World War. The data can be characterized by unprecedented positional accuracy, as they were reconstructed based on the current railway network, which resulted in almost no shifts in space. Most of the lines were reconstructed based on OpenStreetMap data, and the lines, which were closed-down between 1914 and 2019, and are no longer available in spatial datasets, were reconstructed based on high-resolution satellite imageries and historical maps. Altogether, the network covers more than 5000 km on 127 lines. The data are accompanied by a set of attributes, i.e. year of construction, length, starting and final point, type (normal, narrow-gauge, etc.). It can be used in many different applications including historical accessibility mapping, migrations, economic development, the impact of past human activities on current environmental and socio-economic processes, like land use change drivers, landscape fragmentation, invasion of new species and many more. Data are available for download in the shp format. Please note: Our work was focused on publicly accessible railway lines open for regular passenger traffic and hence did not contain the sidings constructed locally, e.g. to serve industrial sites or narrow gauge forest lines. Acknowledgments This research was funded by the Ministry of Science and Higher Education, Republic of Poland under the frame of “National Programme for the Development of Humanities” 2015–2020, as a part of the GASID project (Galicia and Austrian Silesia Interactive Database 1857–1910, 1aH 15 0324 83).
DOI: 10.17632/xd9zr7hh3z
title: Carry over effects of synchronization

description: Behavioral and fNIRS datasets, published in the paper "Post-interaction neuroplasticity of inter-brain networks underlies the development of social relationship"
DOI: 10.6084/m9.figshare.7800701.v1
title: EPOS Software Artifact

description: This dataset is the software artifact of I-EPOS, the <i>Iterative Economic Planning and Optimized Selections</i>. EPOS is collective learning algorithm for decentralized combinatorial optimization problems.<br>Information about the EPOS project is available here: http://epos-net.org
DOI: 10.6084/m9.figshare.27044473.v1
title: A causality investigation into stock prices and macroeconomic indicators in the Indian stock market.

description: The systematic impact of macroeconomic variables on stock market returns makes it crucial to comprehend the link between macroeconomic variables and the stock market. The autoregressive distributed lag (ARDL) model was used in this study to examine the causal links between specific macroeconomic factors and Indian stock prices
DOI: 10.15468/dl.p8ku56
title: Occurrence Download

description: A dataset containing 582 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Millotia muelleri (Sond.) P.S.Short",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 582 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012858-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/xcyv6dyhtx
title: Hausa Emotion-Tagged Tweets Dataset for Multi-Label Emotion Classification

description: The dataset comprises 19,757 Hausa tweets, each annotated with 11 distinct emotions: anger, sadness, disgust, fear, surprise, joy, trust, optimism, pessimism, anticipation, and neutrality. This dataset addresses a significant gap in Natural Language Processing (NLP) for underrepresented languages like Hausa and is specifically designed for multi-label classification tasks. Each tweet captures complex emotional states, making the dataset ideal for training machine learning and transformer-based models that can detect multiple emotions simultaneously.

The tweets were collected through Twitter’s API, focusing on culturally significant events to reflect a broad range of emotional responses. Native Hausa speakers manually labeled the tweets, ensuring high-quality annotations that accurately represent the complex emotional expressions common on social media. This dataset is essential for advancing emotion classification in low-resource languages and aiding the development of more robust models for multi-label text emotion classification.
DOI: 10.17632/crc7w6nws6
title: LINF_170012900

description: Mitoribosomal protein mL73; Leishmania infantum (strain JPCM5)
DOI: 10.17632/r23ss2gjhj
title: Learning style preferences and teaching methodology can influence academic achievement across diverse professional disciplines

description: Research question/hypothesis: Do the learning style preference and teaching methodology has impact on academic achievements. The learning style preferences is varying according to each stream and each year. However the teaching methodology was same across streams and years. we used VARK questionnaire to collect data from the students, the raw data was classified as V-Visual type of learning style preference, A-Aural type of learning style preference, R-Read/write type of learning style preference, K-Kinesthetic type of learning style preference. A google form was sent to the students and they filled the questionnaire. we also collected the percentage of marks achieved in the last examination. The type of learning style preference across stream at varying years of study can be interpreted, also the common teaching methodology used by teacher is reported by students. By understanding the preference of students the teaching methodology can be varied for better academic achievements by students. student centric teaching can enhance the knowledge and achievements.
DOI: 10.17632/w9wkd7g43f
title: BAAD6: Bangla Authorship Attribution Dataset

description: A dataset consisting of text samples from 6 authors with 350 samples per author and total word count of 2.3+ million.
DOI: 10.25452/figshare.plus.22114424.v2
title: Dataset for Deep Imaging Inside Scattering Media Through Virtual Spatiotemporal Wavefront Shaping - Hyperspectral Reflection Matrices of Dense Colloid Nanoparticle Sample

description: This dataset includes the experimental hyperspectral reflection matrices (complex-valued) more than 1 millimeter deep inside a dense TiO2 nanoparticle colloid, with which one can reconstruct high-resolution deep volumetric images of the sample using scattering matrix tomography (SMT). The SMT reconstruction code and more information can be found on GitHub. <br>
DOI: 10.17632/9cxnkhsmjk
title: Butyl acrylate polymerisation data generated using kinetic Monte Carlo simulation

description: The kMC simulations using in-house mcPolymer simulator (https://www.itc.tu-clausthal.de/forschung/mcpolymer/download-and-build-mcpolymer) were performed with Butyl Acrylate (BA) as monomer, AIBN as initiator, and 2-octanone as solvent. The following polymerization parameters were used: T ranging from 60 to 80 °C, cAIBN,0 in the range of 2.5 to 20.0 mmol∙L−1 and cBA,0 in the range of 0.5 to 3.0 mol∙L−1 with uniformly distributed grid size, thus resulting in 432 simulations of the process. Except for the reaction time prediction model the polymerization process was simulated for a constant reaction time of 3600 seconds and the properties of interest were recorded every 300 seconds, thus, obtaining 12 data points for different reaction times in total for each investigated property. For the reaction time prediction model, the simulation was stopped when the desired monomer conversion of 90 % was reached, which could take up to 17 hours in some cases. Under these conditions the simulations cover a range from 4800 to 256000 g∙mol−1 for Mn and a range from 12300 to 511000 g∙mol−1 for Mw.

We provide 4 csv files:
ba_raw_data.csv contains polymerization conditions and BA concentrations for each of 12 points.
mn-mw_raw_data.csv contains polymerization conditions and molecular mass averages Mn and Mw for each of 12 points.
mmd_raw_data.csv contains polymerization conditions and molecular mass distribution for each of 12 points.
rt_raw_data.csv contains polymerization conditions and reaction times necessary to reach 90% conversion of the monomer.

The whole polymerisation data can be obtained running the simulations with mcPlymer kinetic Monte Carlo simulator.