cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/8fbdhh72gs.4
title: Database of influencers' tweets in cryptocurrency (2021-2023).

description: Authors, through Twitter API, collected this database over eight months. These data are tweets of over 50 experts regarding market analysis of 40 cryptocurrencies. These experts are known as influencers on social networks such as Twitter. The theory of Behavioral economics shows that the opinions of people, especially experts, can impact the stock market trend (here, cryptocurrencies). Existing databases often cover tweets related to one or more cryptocurrencies. Also, in these databases, no attention is paid to the user's expertise, and most of the data is extracted using hashtags. Failure to pay attention to the user's expertise causes the irrelevant volume to increase and the neutral polarity to increase considerably. This database has a main table named "Tweets1" with 11 columns and 40 tables to separate comments related to each cryptocurrency. The columns of the main table and the cryptocurrency tables are explained in the attached document. Researchers can use this dataset in various machine learning tasks, such as sentiment analysis and deep transfer learning with sentiment analysis. Also, this data can be used to check the impact of influencers' opinions on the cryptocurrency market trend. The use of this database is allowed by mentioning the source.
Also, in this version, we have added the excel version of the database and Python code to extract the names of influencers and tweets.
in Version(3): In the new version, three datasets related to historical prices and sentiments related to Bitcoin, Ethereum, and Binance have been added as Excel files from January 1, 2023, to June 12, 2023. Also, two datasets of 52 influential tweets in cryptocurrencies have been published, along with the score and polarity of sentiments regarding more than 300 cryptocurrencies from February 2021 to June 2023. Also, two Python codes related to the sentiment analysis algorithm of tweets with Python have been published. This algorithm combines RoBERTa pre-trained deep neural network and BiGRU deep neural network with an attention layer (see code Preprocessing_and_sentiment_analysis with python).
DOI: 10.17632/35tbrd38dt.1
title: Sustainability, Business Models in Italian Wine firms

description: Analysis of Business Models of Italian Wine firms in Italy, with particular emphasis on their Business Models
DOI: 10.17632/nk4y768v9c.1
title: Raw data for Association Between Physician Burnout and Patient Safety, Professionalism, and Patient Satisfaction A Systematic Review and Meta-analysis

description: Raw data, computed data and state commands for all main analyses (Fig 2, 3 and 4) and subgroup analyses presented in JAMA Intern Med. 2018;178(10):1317-1331. doi:10.1001/jamainternmed.2018.3713
DOI: 10.17632/2phnpkvz8z.1
title: Variables_of_Twitters_ brand_activity_influence_spreading_behavior
DOI: 10.17632/822gpnyv4j.1
title: Supplemental material - van der Kolk et al., 2020

description: Supplemental Material related to "Topical anti-microbial peptide omiganan recovers cutaneous dysbiosis but does not improve clinical symptoms in patients with mild-to-moderate atopic dermatitis in a phase 2 randomized controlled trial. T. Niemeyer - van der Kolk et al., 2020, Journal of the American Academy of Dermatology." Supplemental Material S1. Clinical study protocol. Supplemental Material S2. Microbiome report. Supplemental Material S3. Study flow chart. Supplemental Material S4. Staphylococcus abundance over time. A) Staphylococcus abundance over time of the target lesion in the omiganan 1% treatment group, B) Staphylococcus abundance of the target lesion over time in the omiganan 1.75% treatment group, C) Staphylococcus abundance of the target lesion over time in the omiganan 2.5% treatment group, D) Staphylococcus abundance of the target lesion over time in the vehicle treatment group, E) Summary of the change in Staphylococcus abundance of the target lesion, boxplots and median (blue text), and F). Supplemental Material S5. Transepidermal water loss. A) Transepidermal water loss lesional vs. non-lesional skin, B) mRNA expression of IL-13 relative to GAPDH lesional vs. non-lesional skin, C) mRNA expression of eotaxin relative to GAPDH lesional vs. non-lesional skin, D) mRNA expression of IL-31 relative to GAPDH lesional vs. non-lesional skin.
DOI: 10.17632/bw9md35c29.1
title: Identifying User Stories in Issues records

description: Nowadays most software development companies have adopted agile development methodologies, which suggest capturing requirements through user stories. However, user stories are too often poorly written in practice and exhibit inherent quality defects. In addition, it is common to find the user stories of a software project immersed in large volumes of issues request logs from software quality tracking systems, which makes difficult to process them later. In order to solve these defects and to formulate high quality requirements, a current trend is the application of computational linguistic techniques to identify and then process user stories. To train the models, data were taken from public sources that contain issues from real software development projects. These sources contain positive examples of user stories in the format “As a (type of user), I want (goal), [so that (some reason)]” and negative examples (erroneous user stories or sentences with a similar syntaxis to user stories but with a different purpose). To obtain a larger data set suitable for testing the models, an algorithm was implemented for generating additional examples by splitting and mixing positive examples into random parts using the Tokenizer of TensorFlow. In order to differentiate the examples to which each classification class belonged, a manual classification work was performed, which may have introduced to the model some human error index since there was no record of the previously classified data. The resulting dataset includes a total of 7997 positive and negative examples, of which 2618 are positive, and the rest are negative. Therefore, a binary classification problem is presented, where the issues classified as user stories belong to the positive class and the rest to the negative class.
DOI: 10.17632/4mfy92h6rf.1
title: Data for: Hair cortisol and work related stress: importance of the measured stress model (JDC or ERI) and sample characteristics

description: Dataset beloning to article: Hair cortisol and work stress: importance of workload and stress model (JDCS or ERI)
DOI: 10.17632/fyw6ps2d2j.1
title: Data for: End-to-end visual detection, tracking and activity analysis of interacting earthmoving equipment

description: Dataset of 10 videos of interacting pairs of excavators and dump trucks performing earthmoving operations, accompanied with annotations for training and evaluation of algorithms for object detection, object tracking and activity analysis.
DOI: 10.17632/fm5hy2ksk8.1
title: Data for: Voice Disorders are Associated with Stress among Teachers: A Cross-Sectional Study

description: The data involves the variables and the values related to the article.
DOI: 10.17632/3d4vr4dwjs.1
title: Dataset for "Agreement and predictive power of six fall risk assessment methods in community-dwelling older adults"

description: The dataset contained data from 52 (female: n=44, 85%) community-dwelling residents aged [median (interquartile range)] 74 (69–80) years who seek care in a private physiotherapy clinic.25 Most participants reported being regularly engaged in physical activity (n=42, 81%) for 2 (2–2) days/week. No evidence of dementia was observed in the sample as the group scored 29 (28–29) points in the Mini-Mental State Examination.29–31 Handgrip strengths were measured bilaterally using a portable Jamar hydraulic hand dynamometer (model J00105, Lafayette Instrument Company, USA) according to the standard recommendations34 were 20 (16–24) kgf and 20 (18–24) kgf for the dominant and non-dominant hands, respectively. Participants also frequently reported poor sight (n=47, 90%) with use of corrective lenses (n=36, 69%). Only two (4%) participants needed a walking assistive device.
DOI: 10.17632/fp7vktdjfx.1
title: Diagnostic Evaluation of MOOCs

description: This study proposes a diagnostic MOOC evaluation (DME) method that combines the Analytic Hierarchy Process algorithm and learner review mining to integrate expert opinions, standardized rubrics, and learner feedback into the evaluation process. For this purpose, 30 MOOCs from the Coursera website were purposively selected and evaluated using the DME method and the results compared with expert evaluation and learner rating scores. The preliminary findings, in general, support the feasibility, accuracy, and diagnostic utility of the DME method and its suitability as a low-cost, sophisticated, and accurate method for MOOC evaluation.
DOI: 10.17632/2r9wzh9z5v
title: Lithium, Magnesium and Zinc Isotope Systematics of Late Jurassic Mafic Dikes from the Eastern North China Craton

description: The petrological characteristics and geochemical compositions of Late Jurassic Mafic Dikes from the Eastern North China Craton
DOI: 10.17632/33tcb6xwg5.1
title: Influence of work experience and academic background on the understanding of agility and creativity enhancement in software development

description: The document ‘Appendix_I-Components and elements of educational games’ shows the comparative tables with the components and elements included in the different educational resources analysed for this study.
On the other hand, the document, ‘Appendix_II-Surveys provided to participants’ contains the surveys used in each of the experiments carried out for data collection.
DOI: 10.17632/86y667257h.1
title: Coral reef dataset

description: This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos.
DOI: 10.17632/2pcpmp22fx.1
title: Modelling photovoltaic soiling losses through optical characterization

description: Data and additional plots for the Scientific Reports paper titled, "Modelling photovoltaic soiling losses through optical characterization". This includes the spectral transmittance data and all of the optical microscopy. The manuscript presents the results of an international collaboration that investigated the spectral effects of soiling and dust naturally deposited on PV glass exposed outside at seven locations worldwide. These places were chosen to represent a wide variety of climates and environmental conditions. They are also relevant to the continued growth of installed PV systems. We report on one of the largest pools of naturally deposited soiling on glass. While most of the published soiling work focuses on a single site, there are few comparative studies of soiling from multiple locations. The glass coupons were analyzed after an 8-week outdoor exposure, but were not meant to reflect a complete picture of soiling at a given site. Our focus was on the fundamental aspects of soiling from the perspective of both the spectral shape of the transmittance and the corresponding particle size distribution. The optical transmittance and the particle size distribution of the soiling were compared in order to find correlations that could be universally valid, and that could open possibilities to modelling PV soiling losses. Together with this, we present the first effort where empirical models from other disciplines are applied in order to describe both the spectral characteristics of the soiled samples and their corresponding particle size distributions. The spectral hemispherical transmittance of the soiled coupons was taken using a Cary 500 spectrophotometer. The transmittance was fit to a modified form of the Ångström turbidity equation. Microscope images were captured at 100x and 500x magnification for the coupons soiled at each of the seven sites. Micrographs for each glass coupon were taken using a Keyence VHX-5000 microscope at a resolution of 1200 pixels x 800 pixels. The micrographs were analyzed with ImageJ to obtain the particle size distribution.
DOI: 10.17632/wtbpcrc6n6.2
title: Dataset Inertial Sensors for Hip Arthroplasty Rehabilitation

description: Review of the scope of inertial systems used in different applications to measure movements of the human body, postural sway and anticipatory movements related to the diagnosis and evaluation for Hip Arthroplasty Rehabilitation.
DOI: 10.17632/r46c6bpfpf.1
title: Coffee and Cashew Nut Dataset

description: Our research focuses on using machine learning and drone technology to improve yield estimation in agriculture. We introduce the "Coffee and Cashew Nut Dataset," containing 6,086 images with annotations of coffee and cashew nut crops. We collected this data from different coffee and cashew growing sites across Uganda through geo-tagged and time stamped drone imagery, capturing details about crop type and fruit maturity. We meticulously curated and annotated the drone image dataset, involving agricultural experts for validation. This high-quality dataset is publicly available for various machine learning experiments. Our dataset has significant implications, offering precise, rapid, and cost-effective yield estimation solutions for farmers. It supports the development of machine learning models for crop classification, detection, and yield estimation, especially when combined with vegetation indices. The dataset enables the creation of machine learning systems to assist farmers in refining yield estimates and sales predictions by detecting and counting unripe, ripe, and spoilt fruits. It's a valuable resource for advancing agriculture in Uganda and other African nations.
DOI: 10.17632/9szmkdyyjk.1
title: CEOs’ Early-life Famine Experience and Corporate Donations: Evidence from the Great Chinese Famine

description: For the data of this paper on CEOs’ Early-life Famine Experience and Corporate Donations: Evidence from the Great Chinese Famine, please refer to the article.
DOI: 10.17632/hzdgd2xttr.2
title: Survey of Data Scientists in Industry

description: This dataset includes the tool use and skills of data scientists, the challenges faced by data scientists, and much more. The number of countries participants from 32 Total Responses 132 Total number of questions were asked 22
DOI: 10.17632/6p52w7d5xd.2
title: PathCare: A Dataset for Road Fault Diagnosis

description: This dataset containing 386 images and 4 videos. The images were captured using a GoPro Hero 9 camera mounted on a moving vehicle. The purpose of the recording was to monitor road conditions. The recorded videos, featuring various road types, were later converted into individual frames. The dataset is categorized into three distinct classes: Crack, Pothole, and Uneven Surface
DOI: 10.15468/dl.a6t9wv
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Bangladesh",
 "TaxonKey is Ptyas mucosa (Linnaeus, 1758)"
 ]
}

 The dataset includes 7 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009317-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/vxhx934tbn.2
title: Movement Sensor Dataset for Dog Behavior Classification

description: The dataset includes movement sensor data from sensors placed on the collar and the harness of a dog and recorded while the dog is given tasks or activities to perform. The task are: galloping, lying on chest, sitting, sniffing, standing, trotting, and walking. The movement sensors used are: ActiGraph GT9X Link (ActiGraph LLC, Florida, USA) and they include 3D accelerometer and 3D gyroscope. The sampling rate used is 100 Hz. 

The dataset is described in more detail in the data description article: Vehkaoja, A., Somppi, S., Törnqvist, H., Valldeoriola Cardó, A.,  Kumpulainen, P., Väätäjä, H., Majaranta, P., Surakka, V.,  Kujala, M. V., Vainio, O., Description of Movement Sensor Dataset for Dog Behavior Classification, Data in Brief, 2022.

The behavior classification results obtained with the dataset are published in: Kumpulainen, P., Valldeoriola Cardó, A., Somppi, S., Törnqvist, H., Väätäjä, H., Majaranta, P., Gizatdinova, Y., Hoog Antink, C., Surakka, V., Kujala, M. V., Vainio, O., and Vehkaoja, A., Dog behaviour classification with movement sensors placed on the harness and the collar, Applied Animal Behavior Science, 241 (2021): 105393. https://doi.org/10.1016/j.applanim.2021.105393

The authors of the dataset request researchers to refer to the aforementioned publications when using the data and publishing results produced using it.
DOI: 10.17632/yxg6zvgjnm.1
title: Supplementary information files: Gene co-expression network and differential expression analyses of subcutaneous white adipose tissue reveal novel insights into the pathological mechanisms underlying ketosis in dairy cows

description: Supplymentary information files for the article "Gene co-expression network and differential expression analyses of subcutaneous white adipose tissue reveal novel insights into the pathological mechanisms underlying ketosis in dairy cows"
DOI: 10.17632/vfd5vzm6rm.1
title: Data for: A 2000-year sediment record reveals rapidly changing sedimentation and land use since the 1960s in the Upper Mara-Serengeti Ecosystem

description: The Mara River basin in East Africa is a trans-boundary river basin that highlights many of the development and conservation challenges in East Africa. The Mara River flows from its headwaters in the Mau Forest of Kenya through the northern portion of the Serengeti-Mara Ecosystem and into Lake Victoria in Tanzania, where it forms part of the headwaters of the Nile River basin. Changes in land use and landcover in the basin have raised concerns about the quality and quantity of water in the Mara River. We analyzed sediment cores from the Mara Wetland (near the river’s outlet into Lake Victoria) to evaluate how sedimentation rates and sources have changed historically, through a period marked by major changes in human and livestock population densities, land use, and disease epidemics (rinderpest). We collected sediment cores in August 2015 along a transect through the Mara Wetland from the upstream reaches to Lake Victoria. Slices of sediment cores collected from four distinct regions of the wetland were age-calibrated using radiocarbon and lead-210 dating methods. Core slices were then analyzed for sediment sources using a sediment fingerprinting approach, nitrogen and carbon stable isotope signatures, and mercury. Our results suggest that ecological conditions in the Mara River basin were fairly stable over paleoecological time scales (2000-1000 years before present), but there has been a period of rapid change in the basin over the last 250 years, particularly since the 1960s, likely due to anthropogenic factors. We also observed that downstream effects of landcover and land use change can be exacerbated by increasing occurrence of extreme rainfall events in the region. The Mara Wetland likely plays an important role in mitigating the impact of those factors on Lake Victoria. This work was the result of a partnership between Yale University, the Cary Institute of Ecosystem Studies, WWF-UK, WWF-Kenya and WWF-Tanzania.
DOI: 10.17632/cnr8bgf394.1
title: Impact of Impact Investing

description: This code will reproduce all figures and tables in the paper. The package does NOT contain the underlying data because we do not have rights to distribute the data.
DOI: 10.17632/r7x7mw936k.2
title: HCTZ and skin cancer supplementary material

description: Supplementary material - Hydrochlorothiazide use and risk of keratinocyte carcinoma and melanoma: A multi-site population-based cohort study
DOI: 10.17632/96zvxh6h52.1
title: Slamming classification dataset

description: The file contains 11 (eleven) columns, each one related to the features extracted from the analysis of the time series directly or indirectly measured on a ship scaled physical model tested in the wave basin (towing tank) at the Institute of Marine Engineering of the Consiglio Nazionale delle Ricerche (National Research Council), Rome, Italy (formerly, INSEAN). The dataset allows the user to set up a procedure for the identification of slamming events by using Machine Learning algorithms, as explained in the paper entitled "Bow slamming detection and classification by Machine Learning approach" by Dessi, Sanchez-Alayo, Shabani and Lavroff in Ocean Engineering, 2023, 287, 115646. The reader can also refer to Table 5 for further explanation of the columns. The last column (12) indicates what type of slamming event occurred, and is necessary to employ a supervised learning approach, as described in the paper. All the data are expressed at the scale of the physical model tested in the towing-tank. The tests were carried out in 2002 but Machine Learning analysis has been done recently. The dataset is a collection of several towing-tank tests relative to different speed and sea state conditions as reported in Table 4 of the cited paper. Fewer significant digits for numbers in certain columns indicate the suggested maximum precision (VAR09-10-11). The column relative to the frequency at which the wavelet peak was calculated (VAR06) reports repeated values of the (peak) frequencies. This depends on the frequency quantization of the wavelet algorithm.
DOI: 10.17632/jzn7xgfk94.1
title: conflict_regulation

description: conflict regulation