cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/jm7n7p6rg2
title: Computer generated subgroup-symmetry adapted irreducible representations and CG coefficients of space groups by the Eigenfunction method

description: Abstract A program package is described which can compute ab-initio without the input of any complicated results the characters, subgroup-symmetry adapted projective (both single- and double-valued) irreducible representations of the little co-group and the full representation matrices of the space group, the wave-vector selection rules, the Clebsch-Gordan (CG) series and CG coefficients in 230 space groups, as well as the characters, irreducible representations and CG coefficients of the 32 point gro... Title of program: IR, CGC Catalogue Id: ABHE_v1_0 Nature of problem The program computes the characters, subgroup-symmetry adapted projective (both single- and double-valued) irreducible representations (irreps) of the little co-group and the ground representations, the wave-vector selection rules, the Clebsch-Gordan (CG) series and CG coefficients in 230 space groups. The program can also be used for computing the characters, irreps and CG coefficients of the 32 point groups. Versions of this program held in the CPC repository in Mendeley Data ABHE_v1_0; IR, CGC; 10.1016/0010-4655(89)90111-2 ABHE_v2_0; PGSG; 10.1016/S0010-4655(99)00201-5 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.6084/m9.figshare.26342317.v1
title: Reaction Agility and Stroke Effect

description: based on the actual movement characteristics and striking actions of table tennis players, this study designed a reaction agility testing scheme suitable for table tennis using the SpeedCourt agility testing system. The scheme tested athletes’ movement speed, turning time, lateral movement ability on both sides, reaction time of both feet, and lower limb explosive strength to comprehensively evaluate table tennis players’ reaction agility and compared the differences in reaction agility among players of different skill levels. Additionally, by analyzing the impact of reaction agility on stroke effect in different movement scenarios, this study aims to provide a theoretical basis for developing more targeted reaction agility training methods for table tennis players.
DOI: 10.17632/cvrrw88wry
title: Supplementary Material - Welk et al. 2024 - Effect of nonsteroidal anti-inflammatory drugs on neonatal calf diarrhea when administered at a disease alert generated by automated milk feeders

description: Supplementary Material (table outlining statistical models used) for manuscript: Welk et al., 2024 - Effect of nonsteroidal anti-inflammatory drugs on neonatal calf diarrhea when administered at a disease alert generated by automated milk feeders. Journal of Dairy Science.
DOI: 10.6084/m9.figshare.25655325.v1
title: TOBIAS results

description: This file contains the concatenated bindetect_results.txt files from the TOBIAS output from the 4 paired control and IFNg treated CVPCs.
DOI: 10.17632/jvny2fpybf
title: The use of MRs in mechanics problem-solving dataset

description: The research aimed to evaluate how engineering students use multiple representations in mechanics problems solving and this data represent how they performed in using different representations
DOI: 10.17632/pc88nwxwh2
title: Supplementary files for “Modeling clinical radioiodine uptake by using organoids derived from differentiated thyroid cancer"

description: Supplementary files for “Modeling clinical radioiodine uptake by using organoids derived from differentiated thyroid cancer"
DOI: 10.17632/yvy76m266p
title: Survey data on hybrid work in Germany: challenges, tools and support

description: The data include information on the situation of hybrid work in Germany. After the COVID-19 crisis and increased home office work, many employees are engaged in hybrid work, i.e. sharing on-site and sharing in the home office. Data from 263 participants from Germany were collected in December 2021 using an online questionnaire.  The only prerequisite was that the participants work hybrid. The survey contains data on (1) demographic information, (2) tools for use in hybrid work, and (3) perceived support (POS) and perceived success (4). Central to the survey is the evaluation of 36 challenges in hybrid work (5), which were rated in terms of importance.
DOI: 10.6084/m9.figshare.14183060.v1
title: Australian Public Library COVID Survey

description: This data set relates to a survey of Australian public library service managers, conducted in August 2020 by researchers from Charles Sturt University. The survey sought to understand how public libraries in Australia were affected by and responded to the COVID-19 crisis.<br>Three files are included: a PDF version of the survey, an XLSX file with all survey responses, and an XLSX file detailing the data coding. The data coding file also includes infromation about the distribution of the survey, and explains why free-text responses are not included in the published data set.
DOI: 10.17632/4vyb67d4vw
title: Quantifying magma water contents constrain a new entrainment model for charnockite formation

description: This database contains the zircon Hf-O isotopic data, SIMS water content, Raman results, major minerals chemical compositions, bulk-rock major and trace compositions, from the Gaozhou charnockite-granite association in Yunkai terrane, South China, along with compilations including the ages of early Paleozoic granitoids and metamorphic rocks in the Yunkai terrane, and peak P-T conditions of high-grade metamorphic rocks in the Wuyi-Yunkai orogen.
DOI: 10.6084/m9.figshare.14605425.v1
title: Codes&data for "Detecting interchanges in road networks using a graph convolutional network approach"

description: The data and codes that support the findings of our study entitled "Detecting interchanges in road networks using a graph convolutional network approach"
DOI: 10.17632/bm43b33s3s
title: Dataset for “From Commands to Intent: Rethinking Digital Informal Learning in the Era of Intent‐Based Interaction”

description: This dataset comprises raw survey responses collected from undergraduate students investigating factors that predict the decision to use ChatGPT as an informal learning tool. The study examined how digital competence and online learning self‐efficacy influence the decision to use generative AI (GenAI) in educational contexts. Data were gathered using validated instruments adapted for higher education, offering insights into both traditional command‐based digital skills and emerging intent‐based interaction paradigms.

Data Collection and Methodology:

Study Design: Cross‐sectional survey.
Participants: A convenience sample of 1,309 undergraduate students recruited via university email lists, learning management systems, and social media.
Instruments:
Teacher’s Digital Competence Scale (46 items) assessing six dimensions: (likert, min 1- max 5)
Information and Data Literacy (IDL, 9 items)
Communication and Collaboration (CC, 7 items)
Digital Content Creation (DCC, 6 items)
Safety (S, 10 items)
Problem‐Solving (PS, 9 items)
Ethics (E, 5 items)
Online Learning Self‐Efficacy Scale (OLSS) (31 items) covering four subscales: (likert, min 1- max 6)
Technology Use Self‐Efficacy (TU, 7 items)
Online Learning Task Self‐Efficacy (OLT, 4 items)
Instructor and Peer Interaction and Communication Self‐Efficacy (IPC, 7 items)
Self‐Regulation and Motivation Efficacy (SRM, 13 items)
Additional Measures:
A single-item measure classifying respondents based on their decision to use ChatGPT (Users = 1 vs. Non-Users = 0) as an informal learning tool according to their self-reported usage.

Potential Uses:
This dataset is suitable for secondary analyses in educational technology and digital literacy research, particularly for studies interested in:

Examining the interplay between digital competence and the decision to use AI tools in learning.
Evaluating how specific digital skills (e.g., Information and Data Literacy) and online learning self‐efficacy influence the decision to use generative AI.
Conducting replication studies or meta-analyses on GenAI use decisions in higher education.
Data Format:

The primary data file is provided in Excel format (.xlsx) along with an accompanying codebook detailing variable definitions and measurement scales, items both in the original language and the translated versions.
Ethical Considerations:

Data collection was conducted in accordance with ethical guidelines, and all participants provided informed consent.
The dataset has been de-identified to protect participant confidentiality.
DOI: 10.17632/dx8d8hymwt
title: ADLSET

description: ADLSET contains a collection of audio-4D landmark pairs captured from one specific male subject. It contains about 80𝑚𝑖𝑛 news audio spoken in Mandarin. The news from the THUCNews dataset includes sports, real estate, entertainment topics, etc. For the landmarks, It contains 13 cheek landmarks and 12 outer lip landmarks. Users can use plot_lm.py file to plot the landmarks and get the animations.
DOI: 10.17632/hmjtdzkfh3
title: A Comprehensive dataset on diseases affecting rose leaves: Identification, Symptoms, and Control Strategies

description: A Comprehensive dataset on diseases affecting rose leaves: contains 3,113 high-resolution images and 15,500 augmented images (resized to 640x480) of rose leaves, categorized by disease type to assist in identification and control strategy research. The dataset is designed for training deep learning and machine learning models and studying plant pathology, pest management, and disease prevention in rose cultivation. The images were taken from October 30 - November 6, 2024 , approximately 8 days.

 Total Original Images: 3,113 images
 Total Augmented Images: 15,500 images
 Resolution: Resized to 640x480 pixels
 Categories: Four disease classes
 Class 1: Black Spot
 Class 2: Healthy Leaf
 Class 3: Dry Leaf
 Class 4: Leaf Holes
 Image Count per Class: At least 300 images per category in original data
 Purpose: Disease detection, research in plant pathology, and development of control strategies
DOI: 10.6084/m9.figshare.8061959.v2
title: Mycobacterium bovis BCG Danish delta-sapM genome annotation

description: Mycobacterium bovis BCG Danish delta-sapM genome annotation
DOI: 10.17632/sf96c62dvk
title: Data for: Proactive gaze is driven by the translational movement reaching an object regardless of the type of kinematics

description: The file Data proactive.xlsx reports the latency of participants' gaze shifts towards the end of a dots configuration translational movement, calculated from the time of dots configuration movement onset, in five different Experiments. The total duration of dots configuration movement was 1600 ms. Each sheet separately reports gaze latency in milliseconds recorded from each participant, during each trial, in each Experiment. The folder Stimuli contains 9 videos used as stimuli in Experiment 1 (Video 1, and 2), Experiment 2 (Video 3, and 4), Experiment 3 (Video 5, and 6), Experiment 4 (Video 7, and 8), and Experiment 5 (Video 9). The file Videos legends.docx describes each video.
DOI: 10.17632/cmh7p57cxn
title: Melasma

description: Supplemental Material
DOI: 10.17632/hzxv9mb3xs
title: Theoretical Screening of Dielectric/Metal Mirrors for Enhanced Photon Recycling in GaAs Solar Cells

description: Data supporting the plots in 'Theoretical Screening of Dielectric/Metal Mirrors for Enhanced Photon Recycling in GaAs Solar Cells', by M. van Eerden, J. van Gastel, G. Bauhuis, E. Vlieg and J.J. Schermer.
Supplemented with additional data not specifically shown in the paper such as eta,ext and all values of Pabs, Pesc, and Pmirror (Ppar in the paper).
DOI: 10.17632/jvg8dmm3xp
title: Measurement data on the window opening behavior and climate in a strongly daylit office building

description: Long-term measurement data of temperature and relative humidity and window openings from an open-plan office as well as wind speed and temperature of the outdoor situation are presented. Dataset 1: Indoor temperature and relative humidity (Sep 02, 2020 – Aug 31, 2022); Dataset 2: Outdoor temperature (Sep 02, 2020 – Aug 31, 2022); Dataset 3: Wind speed, measured on the building roorf (July 01, 2021 – Aug 31, 2022); Dataset 4: Window openings (Sep 02, 2020 – Aug 31, 2022). Further details about the study object, the sensors, the measurement setup, the limitations and especially the data structure can be found in the Data in Brief: https://doi.org/10.1016/j.dib.2022.108794
DOI: 10.6084/m9.figshare.5002082.v2
title: Susceptibility to persuasion datafiles

description: The three SPSS encoded data files used in the PLoSONE article on Susceptibility to Persuasion.
DOI: 10.17632/rnmjj78ymw
title: Air quality and occupancy dataset

description: In collaboration with the elementary school in Ajdovščina, 8 air quality sensors were placed in classrooms and air quality parameters (VoC, CO2, Luminance, Temperature, and Humidity) were monitored for 6 months.
During the monitoring period, school staff collected anonymous data about the classroom occupancy. The air quality data was paired with external weather data as well as occupancy to train the model. 
The sensors were placed in elementary school Danila Lokarja where 8 IAQ sensors were deployed to monitor classrooms, the mess hall, and hallway. The elementary school was completed in 2016 with a little more than 5000 square meters of surface area and 27 bigger classrooms, and a few smaller ones. The building being relatively new is noteworthy as newer materials used in construction can impact the IAQ. Among the deployed sensors, 6 were used to monitor the dynamics of classrooms. The sensors measure multiple parameters, namely temperature, relative humidity(RH), Luminance, CO2, and Volatile organic compounds (VOC). The sensors used LED lighting to inform the staff about the general air quality.
DOI: 10.6084/m9.figshare.25726887.v1
title: Numerical data

description: Numerical data for 'Tau mediated synaptic dysfunction is coupled with HCN channelopathy'
DOI: 10.6084/m9.figshare.988671.v2
title: Pollen data from Ruppert Lake, south-central Brooks Range, Alaska

description: Data from:<br>Higuera, P. E., L. B. Brubaker, P. M. Anderson, F. S. Hu, and T. A. Brown. 2009.<br>Vegetation mediated the impacts of postglacial climate change on fire regimes<br>in the south-central Brooks Range, Alaska. Ecological Monographs 79:201-219. For each site, Code (CO), Ruppert (RP), Wild Tussock (WK), and Xindi (XI), there<br>are the six files: 1. xx_age_depth_data.txt – Depth (cm) and age (cal yr BP) from the published<br>age-depth model. 2. xx_age_depth_fig.pdf – Figure of the age-depth model, ¼ of Fig. 2 in Higuera<br>et al. (2009) 3. xx_charData.csv – Charcoal data in a CharAnalysis input file. Units are in the<br>column headers: See https://sites.google.com/site/charanalysis/ for more details. 4. xx_charParams.csv – Parameter file CharAnalysis, with parameters as used in the<br>original publication. See https://sites.google.com/site/charanalysis/ for more details. 5. xx_charResults.csv – CharAnalysis results file. Units are in the<br>column headers: See https://sites.google.com/site/charanalysis/ for more details. 6. xx_pollen.xls – Pollen counts for each sample. The tab “pollen_counts” and<br>“pollen_cm” contains raw the same data as in the tab “data” but in a raw format<br>used for plotting. Ages associated with each pollen sample have to be obtained<br>from the “xx_age_depth_data.txt” file, or from the appropriate column in the<br>“charData” file in the “xx_char.xls” file. Radiocarbon dates from each site are in the file “Higuera_et_al_2009_Table_B1”<br>in the folder titled “C14_dates” as published here:<br>http://www.esapubs.org/archive/mono/M079/007/ CONTACT:<br>Philip Higuera<br>phiguera@uidaho.edu<br>pehiguera@gmail.com Key words: Arctic, boreal forest, climate change, pollen analysis, tundra, shrub tundra,<br>paleoecology, Gates of the Arctic National Park Taxa: Alnus, Artemisia, Cyperaceae, Betula, Picea mariana, Picea glauca, Populus, Poaceae,<br>Salix, Sphagnum, Pediastrum
DOI: 10.17632/cp27yppcwp
title: Financial resilience in Mexican college students

description: Financial resilience is a phenomenon of increasing academic interest. There has been significant progress in research literature, where various impacts are measured, ranging from knowledge, behavior, and culture to financial skills. This study contributes evidence of how students perceive financial resilience based on their perception, lived experiences, and actions taken to confront any recent adverse financial situation they may have encountered. Mexican college students from both public and private universities (N=256) responded to a survey based on the by Flores et al. (2024), developed from the financial health indicators proposed by the Center for Education and Financial Capabilities of BBVA (2020) in line with the Center for Financial Services Innovation (CFSI). Findings reveal a three-factor model explaining perception towards financial health indicators, with lived experiences and resilient actions taken when facing adverse financial situations. The three-dimensional model is not fully supported, as indicators that do not favor the final model due to low factorial loads are excluded. Responses are in Spanish.
DOI: 10.17632/nph2cnh6r2
title: Loyalty Status of Hotel Guests: Simulated Dataset for Predicting Customer Loyalty

description: This dataset consists of 2,000 simulated records of hotel guests, designed for customer loyalty prediction based on several key features. Each guest's loyalty status ("Yes" for loyal, "No" for non-loyal) indicates their eligibility for loyalty discounts, with "loyal" signifying that the individual can enjoy these discounts. The dataset includes factors such as frequency of bookings, days since the last booking, total revenue generated, average stay duration, and total meal charges.

The dataset was generated using Python with the Faker library to create realistic guest names and emails, featuring names in different languages to reflect a diverse international perspective. The countries represented include India, the United States, the United Kingdom, France, Germany, Spain, Italy, Japan, and China.

A Python code file is provided alongside this dataset for those interested in the methodology used to create it. This resource serves as a practical tool for exploring machine learning techniques and data analysis in the hospitality sector.

We are building this dataset as part of a dynamic pricing project for hotels, aiming to enhance decision-making through customer segmentation.
DOI: 10.17632/r9h2ykvzcn
title: Data for: Determining the Most Favorable Settings for Low-fidelity 3D Printers to Attain Optimal Print Quality with Minimal Wastage

description: The data contains 4 kinds of files. Files are organized in folders for easy interpretation: 1) An Excel file. This has all the data collected from the measurement. This file can be opened using Microsoft excel. 2) Minitab project files (MPJ) . These files can be opened using the statistical software Minitab version 17. They include the data, analyses and plots used to interpret the results of the research. 3) A PDF document. This has all the plots related obtained through the research data to determine the optimal settings. This can be opened in any PDF reader. 4) Original TIF and BMP images obtained from the CT scan. Only one relevant image from each data-set is shown because it contains hundreds of images. These can be opened using most image viewing applications such as windows photo viewer.
DOI: 10.17632/wnvbty8y83
title: Dataset for Non-isotropic contraction and expansion of samples in diamond anvil cells: Implications for thermal conductivity at the core-mantle boundary

description: The dataset contains thickness (diamond-to-diamond) distances measured at the center of the diamond anvil cell cavity filled with MgO, KCl, NaCl, Al2O3, aSiO2 (fused silica), and argon upon compression and decompression.
DOI: 10.17632/3xm88g6m6d
title: A Public Domain Dataset for Real-Life Human Activity Recognition Using Smartphone Sensors

description: *In recent years, human activity recognition has become a hot topic inside the scientific community. The reason to be under the spotlight is its direct application in multiple domains, like healthcare or fitness. Additionally, the current worldwide use of smartphones makes particularly easy to get this kind of data from people in a non-intrusive and cheaper way, without the need of other wearables. In this paper, we introduce our orientation-independent, placement-independent and subject-independent human activity recognition dataset. The information in this dataset is the measurements from the accelerometer, gyroscope, magnetometer, and GPS of the smartphone. Additionally, each measure is associated with one of the four possible registered activities: inactive, active, walking and driving. This work also proposes an SVM model to perform some preliminary experiments on the dataset. Considering that this dataset was taken from smartphones in their actual use, unlike other datasets, the development of a good model on such data is an open problem and a challenge for researchers. By doing so, we would be able to close the gap between the model and a real-life application. Data collection was made through an Android app, for each smartphone of every individual from the 19 that got part in the study. The data collected, by focusing such gathering on a real-life environment, does not have a fixed orientation or placement of the smartphone, leaving each individual to use their device as they would for each of the specified actions. The activities performed were four: Inactive: not carrying the mobile phone. For example, the device is on the desk while the individual performs another kind of activities. Active: carrying the mobile phone, moving, but not going to a particular place. In other words, this means that, for example, making dinner, being in a concert, buying groceries or doing the dishes count as "active" activities. Walking: Moving to a specific place. In this case, running or jogging count as a "walking" activity. Driving: Moving in a means of transport powered by an engine. This would include cars, buses, motorbikes, trucks and any similar. The data collected comes from four different sensors: accelerometer, gyroscope, magnetometer and GPS. We saved the data of the accelerometer, the gyroscope and the magnetometer with their tri-axial values. In the case of GPS, we stored the device's increments in latitude, longitude and altitude, as well as the bearing, speed and accuracy of the collected measurements. Note that these measures do not have a fixed frequency, as it is not possible to set it on Android devices. In addition, some of the people who took part in the study did not have all these sensors available on their smartphone, so there are certain sessions that do not have a gyroscope, or neither a gyroscope nor a magnetometer together. Inside each .zip file, there is a README file with details for each part.