cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/bcgzzg23cx.1
title: Could the rumor clarification pacify the stock market：Evidence from China

description: Our initial sample consists of all the Chinese A-share listed firm samples spans from January 1, 2014 to December 31. The 5-min frequency price data and the trade and quote data are collected from the CSMAR high-frequency database; the former data are used to calculate the RV. The clarifications are collected from the CNRDS database, we retains only the rumor clarified in pessimistic announcement as these rumors may represent malicious attacks and more likely to attract the managers’ keen attention, the clarification variable Clari,t takes the value of 1 if observing a clarification during the (t-15, t-1) trading days for firm i in day t, and 0 otherwise. We use the fraud punishments as the negative measurement of the companies’ reputation (Fraud), Fraudi,t is a dummy variable get the value 1 if there is fraud punishments happened during the past 6 years, which are collected from CSMAR database. We delete the firms without rumor clarification, the sample-firms going public and the firms with trading days less than two years, and the samples with missing variables. Finally we get 515137 daily samples comprising 599 firms, with the maximum length of 1219 trading days.
DOI: 10.17632/7cxccpv4hg.1
title: Proper acquisition of cell class identity in organoids allows definition of fate specification programs of the human cerebral cortex. Uzquiano Kedaigle et al.

description: This is supplemental data related to the Cell manuscript "Proper acquisition of cell class identity in organoids allows definition of fate specification programs of the human cerebral cortex" by Ana Uzquiano & Amanda Kedaigle, et. al. For detailed descriptions of each dataset included here, please see the file "DataDescription.docx".
DOI: 10.17632/znkxcpkk6w.1
title: Trade under lockdown JIE

description: This folder includes all the required data and codes to replicate the article "Trade under lockdown", by Antoine Berthou and Sebastian Stumpner, paper accepted for publication at the Journal of International Economics.
DOI: 10.15468/dl.m6cqux
title: Occurrence Download

description: A dataset containing 2309 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Prunus cerasifera Ehrh.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 2309 records from 166 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009312-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/m6g4c3hm9m.1
title: Patch for including ice shelf cavities ice shelf cavities in the unstructured-grid, Finite Volume Community Ocean Model

description: The patch for implementing iceshelf cavities into FVCOM4.0 consits of 1. A text file, git_diff_FVCOM4.0_iceshelf.txt, containing all the code modifications related to the inclusion of ice shelf cavities into FVCOM4.0 source code, generated by git diff. The FVCOM4.0 source code that has been used for this implementataion is published on https://gitlab.ecosystem-modelling.pml.ac.uk/fvcom/uk-fvcom/tags/FVCOM-v4.0. Alternatively, the source can also be obatined from the official FVCOM website http://fvcom.smast.umassd.edu/ and is available to all members of the FVCOM community. 2. A folder, R1CON, contains the input files, namelists and apps options to run the testcase R1CON. Do not hesitate to contact the authors for further instructions / help for applying FVCOM-ice-shelf applications!
DOI: 10.17632/6tw3k24c8n.1
title: Data for: What are the appropriate thresholds for High Quality Performance Indicators for Breast Surgery in Australia and New Zealand?

description: Raw data of all surgeon member's of BreastSurgANZ performance at pre-selected thresholds for high quality performance indicators
DOI: 10.17632/ks9vbv5pb2.1
title: Horizontal Scaling in Kubernetes Dataset Using Artificial Neural Networks for Load Forecasting

description: This dataset provides comprehensive data collected from experiments to enhance horizontal scaling in Kubernetes clusters using Artificial Neural Networks (ANNs) for load forecasting. The dataset includes measurements of CPU load, packet reception rates, and the number of pods gathered under various traffic scenarios. These metrics were meticulously collected and preprocessed to train and evaluate the performance of the ANN-based scaling solution compared to the traditional Horizontal Pod Autoscaler (HPA). The dataset is divided into two main parts: training data and test data, each serving a specific purpose in developing and validating the scaling models.

The training dataset (TrainData.csv) consists of averaged metrics from multiple experiments, capturing the mean CPU load, mean packet reception rates, and mean number of pods under different stress conditions. This data was collected using a controlled setup with varying numbers of virtual users and replicas, ensuring a robust and diverse set of inputs for training the ANN model. By analyzing these averaged values, the ANN can learn to predict the optimal number of replicas needed to handle specific loads, aiming to improve resource utilization and maintain service quality.

The test dataset is split into two components: data collected from the Kubernetes cluster (TestK8sData.csv) and data from the JMeter tool (TestJMeterData.csv). The TestK8sData.csv file includes timestamped records of CPU usage, packet reception rates, number of pods, and additional parameters such as experiment type (HPA or ANN) and CPU thresholds. The TestJMeterData.csv file provides detailed logs of HTTP requests, including response times, success rates, and other performance metrics. Together, these datasets enable a comprehensive evaluation of the ANN-based scaling approach, allowing for comparisons against the traditional HPA method regarding efficiency, responsiveness, and adherence to service level agreements (SLAs).
DOI: 10.17632/ds45yy9jrc.2
title: Mulberry Leaf Dataset

description: The mulberry leaf dataset is a collection of 10 cultivars that are taken in the natural environments using DSLR cameras and smartphones. We collected the data from three regions of Thailand: northern (Chiang Mai), central (Phit- sanulok), and northeast (Nakhon Ratchasima, Buriram, and Maha Sarakham).

The mulberry leaf images were captured from the natural environments. We recorded the images from different perspectives. There is a shadow that appears in the photo when holding the camera at a low position. However, when shooting from an eye-level position, the resulting image is sharp and the backlit image does not appear. All leaf images are recorded in the JPEG format. The mulberry leaf images were resized into 224 × 224 pixel resolution.

The mulberry leaf dataset includes ten cultivars, which are four cultivars from Thailand: Chiang Mai 60 (386 images), Buriram 60 (500 images), Kamphaeng Saen 42 (640 images), and 761 images of mixed-breed mulberry (Chiang Mai 60 + Buriram 60). Three cultivars of Australia consist of King Red (500 images), King White (350 images), and Black Australia (637 images). Two cultivars of Taiwan consist of Taiwan Maechor (500 images) and Taiwan Strawberry (500 images). Also, 488 images of the Black Austurkey are from Turkey. This dataset contains 5,262 images in total. Note that mulberry experts advised examination of each mulberry species to label the data and avoid the errors due to the similarity pattern and shape of the leaves.
DOI: 10.17632/v7y3s2kk2c.1
title: Data for: Geological carbon sequestration: Modeling mafic rock carbonation using point-source flue gases

description: Mineral precipitation results from reaction path geochemical modeling of reacting 11 mafic rock samples from Nevada, USA with CO2 at a fixed concentration and SO2 at three concentrations. Data are all reported in moles.
DOI: 10.6084/m9.figshare.27934782
title: Raw data of learning style survey for junior doctors

description: Raw data of learning style survey for junior doctors
DOI: 10.17632/9bbwcytc7j.1
title: Navigating Ethical Dilemmas in AI-Enhanced Language Education: Addressing Bias and Ensuring Inclusivity

description: Purpose: This study investigates the ethical, practical, and educational implications of integrating artificial intelligence (AI) into language education. The focus is on identifying the challenges of algorithmic bias, data privacy, inclusivity, and the impact on teacher-student dynamics, aiming to 
provide insights that can guide the responsible and effective use of AI in education. Findings: The research reveals that algorithmic bias poses a significant threat to educational equity, potentially perpetuating existing inequalities. Data privacy concerns are prevalent, necessitating strict regulatory measures. Inclusivity remains a challenge, with AI risks widening 
the educational gap between socio-economic groups. Additionally, the study highlights the potential erosion of the teacher-student relationship due to over-reliance on AI, which could undermine the human elements crucial to the learning process. Design/Methodology/Approach: The study employs a qualitative research methodology, utilizing thematic analysis to explore literature, case studies, and expert interviews. This approach allows for an in-depth understanding of the multifaceted issues surrounding AI in language education and provides a nuanced perspective on its implications.
Originality/Value: This research contributes to the emerging discourse on AI in education by addressing the often-overlooked ethical and social dimensions. It offers a unique perspective by examining the intersection of AI with cultural and socio-economic factors, providing valuable insights for educators, policymakers, and AI developers.
DOI: 10.17632/t49cyrgtct.4
title: Dataset for "Coupling Reservoir Operation and Rainfall-Runoff Processes for Streamflow Simulation in Watersheds"

description: This dataset includes all code used to run and evaluate the coupled watershed models described in 'Coupling Reservoir Operation and Rainfall-Runoff Processes for Streamflow Simulation in Watersheds.'

Prior to model calibration and performance evaluation, the codes in Step_A_DataPreprocessing, and Step_B_CreateReservoirModels are to be run for creating set-up files. Outputs from the codes in both folders are already included in the dataset. Separate readme.txt files inside both folders describe each codes' application.

Within the root folder, "Calibrate_Models_Using_NSGA2.R" is run first to obtain optimized/calibrated coupled model parameters; outputs are stored in the folders "Optimized_Paras". 
Subsequently, the "Generating_Calibration_DWM_and_SWM_Sims.R" and "Generating_Validation_DWM_and_SWM_Sims.R" codes are run to generate calibration and validation period streamflow simulations (both deterministic and stochastic), respectively, using the calibrated parameters.
Results of "Generating_Calibration_DWM_and_SWM_Sims.R" are stored in the "Stored_Simulations_And_Pred_Uncertainty_Paras" folder.
Results of "Generating_Validation_DWM_and_SWM_Sims.R" are stored in the "Validation_Period_Results/Stored_Simulations_And_Pred_Uncertainty_Paras" folder.

The following codes are used to generate the results in the paper:
"Plots_Calibration_Period.R" -&gt; Plots boxplots of KGE and LNSE (for reservoir inflow and watershed outflow) for the calibration period; outputs stored in "Boxplot" folder.
"Plots_Validation_Period.R" -&gt; Plots boxplots of KGE and LNSE (for reservoir inflow and watershed outflow) for the validation period; outputs stored in "Validation_Period_Results/Boxplot" folder.
"Checking_Distributions_Of_Parameters.R" -&gt; Plots probability distribution functions of calibrated watershed model parameters; outputs stored in "Parameter_PDFs" folder.
"LMoment_Errors_CalibrationPeriod.R" -&gt; Calculates and plots the errors in estimated L-moments for the calibration period; results written in "LMoment_Errors" folder.
"LMoment_Errors_ValidationPeriod.R" -&gt; Calculates and plots the errors in estimated L-moments for the validation period; results written in "Validation_Period_Results/LMoment_Errors" folder.
"Plotting_Calib_FDCs_And_Hydrographs_DWM_SWM.R" -&gt; Plots calibration period flow duration curves (FDCs) and hydrographs simulated by the watershed models to "Hydrographs_and_FDCs" folder.
"Plotting_Valid_FDCs_And_Hydrographs_DWM_SWM.R" -&gt; Plots validation period FDCs and hydrographs simulated by the watershed models to "Validation_Period_Results/Hydrographs_and_FDCs" folder.

Apart from the above codes, all other codes in the root folder are function files.
DOI: 10.17632/htk59pp5wx.1
title: Run-to-failure vibration dataset of self-aligning double-row ball bearings - PART 1

description: Data sourced from actual operational systems constitutes a pivotal asset for scholarly investigations in the domain of machine diagnostics and prognostics. The exigency for such data has witnessed a notable surge in recent times, primarily propelled by the burgeoning interest in prognostic methodologies and the advancement of artificial intelligence (AI) technologies tailored for predictive maintenance applications. When harnessed for fault detection and prognostic endeavors, data must inherently possess the capacity to furnish insights into the degradation phenomena inherent to machinery. Moreover, a fundamental aim of prognostics entails the anticipation of the remaining useful life (RUL), a task necessitating substantial datasets for the application of data-driven techniques or the validation of physics-based models.

Bearings, being subjected to a diverse spectrum of loads and fatigue stresses, carry the potential for catastrophic failure, thereby impacting the operational integrity of entire machinery systems or industrial plants. 

The Department of Engineering at the University of Ferrara has undertaken an extensive experimental campaign aimed at documenting the temporal evolution of vibration signals over the lifecycle of self-aligning double row rolling element bearings. Six accelerated run-to-failure trials were conducted, during which acceleration signals were continuously captured utilizing a uniaxial accelerometer. Concurrently, a radial load was imposed on the bearing housing and regulated via a load cell. Ensuring consistency, the shaft speed was maintained at a constant level, facilitated by an electric motor actuated by an inverter.

The resultant dataset encapsulates acceleration signals along the radial axis spanning the entirety of the experimental tests, thereby offering a valuable resource for both scholarly inquiry and industrial applications alike.

This dataset provides the Part 1 of data collected during the experimental campaign.
Data is provided in .mat format and each file contains two variables: the acceleration signal in radial direction and the sampling frequency.
DOI: 10.17632/k42rjx4m7n.1
title: JAAD Dermatology Images - Pityriasis Rubra Pilaris

description: Supplemental images for JAAD Dermatology Images - Pityriasis Rubra Pilaris
DOI: 10.17632/b8mc5byy7g.1
title: Multilevel assessment of restaurant profitability: Evidence with European data

description: Microeconomic data provided by Amadeus database, and contextual variables provided by World Tourism Organization, OECD, and Eurostat. Two measures of corporate profitability are considered in this dataset: Return on equity (ROE) and Return of assets (ROA). Additional financial indicators are included as control variables. Country heterogeneity may be checked using macroeconomic variables and tourism indicators.
DOI: 10.17632/pyhv9h52pk.1
title: Data for: Asian Financial Market Integration and the Role of Chinese Financial Market

description: Data consists of 10 Asian countries, Japan, China, Hong Kong, Taiwan, South Korea, Singapore, Malaysia, Thailand, Indonesia, Philippines plus U.S., total 11 countries. Monthly stock market index and nominal exchange rates (end of the month in local currency terms) are collected from Datastream from January 1990 to December 2013 total 288 monthly observations. Monthly dividend yield is obtained from the Bloomberg for the sample period.
DOI: 10.17632/cyg6c47mh6
title: Pg Wave Tomography around the 2022 Ms 6.8 Luding Earthquake region

description: Waveform data and 2_D P-wave velocity model of the southeastern segment of the Xianshuihe fault zone
DOI: 10.17632/b73b5kmcwm.1
title: Comprehensive database of test transportation problems (balanced and unbalanced)

description: The database of test transportation problems presented with this article is a useful aid in assessing the accuracy of existing and new methods for finding initial basic feasible (IBF) or optimal solution of transportation problems. The optimal solutions of these using MODI method, and IBF solutions using some conventional methods are planned to be presented in a forthcoming research paper for easiness of the researchers working in this domain.
DOI: 10.17632/2kmstzchrm.1
title: Data for: How are frames generated? Insights from the industry lobby against the sugar tax in Ireland.

description: Table 2: The frame typology, with illustrative examples Table 3: Categorising different framing actions
DOI: 10.17632/4jvmdyzkb6.1
title: Data for: Development and evaluation of a surface-densified wood composite with an asymmetric structure

description: The dataset belongs to the physical and mechanical properties of the surface-densified wood.
DOI: 10.17632/ktxwhcfkt2.1
title: Hybrid Version of the Game - Website

description: The video shows the website developed for our Phishing awareness game.
DOI: 10.17632/k7jjrs4wnk.1
title: Mbeya city CSEE 2022 Single sex schools

description: CSEE 2022 results of only single sex schools in Mbeya city compared to the best six coeducation schools.
DOI: 10.17632/49v6fx7ssg.1
title: Social Media and Body Image

description: Asked college students questions about their social media use, their perceptions of its impact on body image, as well as self-objectification, internalization, and appearance comparison
DOI: 10.17632/wf5d5b2j52.1
title: Social Communication Database

description: The dataset was generated by real world text communication in the group conversation. So, maintain the anonymity of the usernames and the mobile numbers of those who participated in the survey. This dataset can be used for education and research purpose only. The main contribution of this research in text mining is to bring into being a standard dataset for research purpose in the realm of mining the chat conversation. We have observed that this dataset has an immense density to be utilized for research purpose. Our applications based on this dataset, you can utilize this dataset into semantic search, sentiment analysis, semantic clustering of conversation, topic extraction, spam detection, etc. We wish to offer this dataset for others to collaborate and research on further possibilities. We have used our algorithms to extract the textual information from whatsapp logs and stored it in a sqlite database file named as "social conversation.db". This dataset contains 16225 text messages and 839 distinct users. We have considered 17 whatsapp groups for extracting the textual information. Paper: Analysis of foul language usage in social media text conversation Authors: Sumit Kawate and Kailas Patil In the Proceedings of the Int. J. Social Media and Interactive Learning Environments (IJSMILE), Vol: 05, Issue: 03, Pages: 227-251, Inderscience, 201 DOI: https://doi.org/10.1504/IJSMILE.2017.087976 The data is stored in an .zip compressed archives. The uncompressed archive is in 6,020 KB (5.87 MB). Extract with any uncompressed standard software. ## The archive contains the following items: ## DATABASE/ | + Executable/ Directory containing executable files. | | + Social Conversation.db This file contains records of the database in .db format | + Source Code/ Directory containing source code files. | + Social Conversation (csv).csv This file contains records of the database in .csv format + Social Conversation (db).db This file contains records of the database in .db format + Social Conversation (html).html This file contains records of the database in .html format. | + Read Me/ Directory containing read me file. | | read me.txt This file contains detail information about dataset. ## The data format of the dataset are: ## =Table Name= -&gt; CONVERSATION =Atttributes= =Meaning= USER_ID User id of the text message TEXT_MSG TextActual text message CONTACT_NUMBER Contact number of the user (We have masked the few digits of contact number of the user) DATE Date of the text message TIME Time of the text message =Atttributes= =Format= USER_ID User Id TEXT_MSG (text messsage in any format) CONTACT_NUMBER +contactnumber DATE dd/mm/yy TIME hh:mm AM or hh:mm PM =Atttributes= =Sample Example= USER_ID User 514 TEXT_MSG Any deal on formal shoes with prime CONTACT_NUMBER +919xxxxx927 DATE 04/12/17 TIME 1:35 AM --------------------------------------------------
DOI: 10.17632/4tyf28fvrm.1
title: Data for: Human vocal behavior within competitive and courtship contexts and its relation to mating success

description: Data contains personnal and ascoustics information on every participant in the study. Corrigendum: This dataset has been updated (update on 26.07.2019). A few errors were reported in the previous one, so use this one instead if you want to re-run the analyses. Also note that the individuals marked as MD_17012017_14 and MD_08022017_56 were not used in the analyses, and this was unfortunately not mentioned in the article. Those individuals were removed as they presented an unusually high number of mating partners. However, adding or removing these two individuals from the analyses did not change qualitatively the results.
DOI: 10.17632/9jfvz2jpgb.1
title: The effect of problem-solving and decision-making education on problem-solving and decision-making skills of nurse managers: A randomized controlled trial

description: Raw data on experimental and control group problem solving and decision making skills (SPSS)
DOI: 10.17632/br4cdprntv.2
title: Data in manuscript titled 'Fracture mechanism of adhesive single-lap joints with composite adherends under quasi-static tension'

description: The research is aimed to understanding of the fracture mechanism of Single-lap joints (SLJs) with composite adherends. The main findings of the research are as follow.  Fracture surface of SLJs are observed in detail with scanning electron microscope.  Crack initiation of both types of SLJs are captured by high-speed camera.  Fracture process of SLJs are demonstrated based on experimental results.  Sand paper treatment shows an effect on the failure modes of SLJs.  CZM with experimentally obtained parameters predicts the failure modes and failure loads well. The raw data include the results of tensile test and short beam shear test of a CFRP as well as the tensile test results of 4 types of SLJs. The processed data are derived from the raw data, mainly in the form of figure.
DOI: 10.17632/vk77k9gvg3.2
title: AnLoCOV

description: AnLoCOV is a large anonymized longitudinal GPS location dataset for studies spanning over pre- and post-COVID periods in Ecuador. This project contains data collected using the Global Positioning System (GPS) from mobile devices. This GPS data was acquired using the Google Location History, accessible in the Google Maps application. It includes data from 338 people over ten years (2012–2022). The dataset's goal is to promote studies on human mobility behavior and activity spaces using GPS data from mobile devices.