cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/xjsrpk5xv7.1
title: Love of Learning Survey

description: This data is a cross-sectional survey of 112 students from Spring 2023. 

The setting is Franklin University Switzerland, a small joint American-Swiss Liberal Arts college in Lugano, Switzerland. 

The variables include the students' year of study, major, academic travel frequency, as well as self-reported GPA, love of learning, and 10 classroom related psychological Flow variables, indexed via averaging.

Relationships between variables and differences between groups can be explored to better understand learning factors and create educational policy.
DOI: 10.17632/8m8fdd7vgv.1
title: Data for: Critical Causes Identification for Construction Accidents in China Based on System Thinking and Case Analysis

description: We provided the information of the 571 construction accident cases. We didn't provide each of the accident reports, because they were expatiated in Chinese. We just provided the names (in Chinese), area distribution, types, and severity levels of them in Excel tables.
DOI: 10.17632/gnb2dsjms2.1
title: Spatiotemporal transcriptomic map of glial cell response in a mouse model of acute brain ischemia

description: Hello, 

Welcome to the repository for the processed data objects for our manuscript titled "Spatiotemporal transcriptomic map of glial cell response in mouse model of acute brain ischemia" published in PNAS (doi: 10.1073/pnas.2404203121). In this study, we used spatial and single-cell transcriptomics to map out processes governing the response to ischemic stroke during the first week after the injury. Focusing on glial cells, we documented their activation, formation of glial scar and changes in cell-cell communication patterns. Here, we list seurat objects of the spatial and single-cell experiments.

List of files:
- seurat_1stSpatial.rds. A seurat object with Visium ST generated data (gene expression matrix, metadata and image). Clean, suitable for starting-anew analysis.
- seurat_2ndSpatial.rds. A complementary seurat object to the seurat_1stSpatial.rds.
- spatial_seurat_1DP_13_nygen.rds. A complete seurat object of the final Visium spatial dataset (modules scores, deconvolution, ligand-receptor pair values...)
- Seurat_sn_MCAO_Zucha2023_QCFiltered.Rds. Seurat object of pre-processed single-nucleus data.
- Seurat_OLs_integrated_annotated.Rds. Seurat object of processed oligodendrocyte data integrating the single-nucleus and single-cell experiment.

Corresponding author contact: lukas.valihrach@ibt.cas.cz
DOI: 10.17632/n24z7r2z28.2
title: Dataset for Leveraging Blockchain to Improve Automotive Supply Chain Traceability

description: The data set contains support documents and file for the project: Leveraging Blockchain to Improve Automotive Supply Chain Traceability Abstract - The automotive industry worldwide seems to be spontaneously changing with supply chain improvement being one of the main focus areas along with cost reduction, process optimization and enhancing timely throughput. The general success parameter for achieving a better output in all the said focus areas is having an effective traceability system in place. Traceability for the automotive industry is a system documenting the genealogy of parts involved in manufacturing a specific product. Even with companies having an enormous amount of capital invested for perfecting their supply chain and achieving traceability, it is seen that they still have limited visibility and insight into their supply chain at a given instance. This study aims to leverage blockchain technology to eliminate inefficiencies of the conventional automotive supply chains for increasing transparency, streamlining processes and decentralizing network while providing stakeholders and companies with a host of value-adding features that ensure smoother and faster transaction. The study demonstrates the advantages of blockchain enabled automotive supply chain. Hyperledger Composer is used for deployment of the said network.
DOI: 10.17632/wfsspy2gx8.1
title: PeerConf: A dataset for peer review aggregation

description: PaperConf is a dataset that contains various crucial information about peer reviews from several scientific conferences. These Peer reviews are collected from 5 different scientific conferences with the permission of the conference chairs of the respective conferences. The dataset contains a total of 3242 peer reviews of 1236 papers from multiple scientific conferences. The peer reviews contain important information like recommendation score, confidence score, the review given by the reviewer, the final decision and some identifying attributes. Features like paper title, paper abstract, author name etc. as well as the conference names are removed during dataset preparation in order to maintain the privacy of the authors and reviewers. The dataset can be used for training and testing Machine Learning models predicting acceptance decisions, Peer review summarization etc.
DOI: 10.17632/hmwsrp22yk.1
title: GBEDatset2022

description: This survey data was collected in the Zimbabwean upmarkets in Harare in December 2022. The survey examined the antecedents of green brand equity, specifically for organic food brands. The data was examined using SEM to evaluate research hypotheses and assess structural relationships.
DOI: 10.17632/9mrxwtfh6w.1
title: Dataset for 'Harnessing GenAI for Higher Education': A Mixed-Methods Study of Prof. Leodar, a Custom RAG Chatbot

description: This dataset accompanies the manuscript "Harnessing GenAI for Higher Education: A Study of a Retrieval Augmented Generation Chatbot's Impact on Learning". It contains the following components:

Survey results and analytics: Raw data and analysis from the structured surveys administered to students who used Prof. Leodar, the custom-built Retrieval Augmented Generation (RAG) chatbot.
Usage analytics: Data on the daily and weekly usage patterns of Prof. Leodar throughout the course duration, including query volumes and timing.
Code for Prof. Leodar: The implementation code for the RAG chatbot, including the architecture and integration with course materials.
List of questions asked by learners: A complete list of queries given to Prof. Leodar during its deployment over a single semester.
This dataset provides comprehensive information for researchers interested in the development, implementation, and evaluation of AI-powered educational tools in higher education. It supports the replication of our study and enables further analysis of the impact of GenAI chatbots on student learning and engagement.

Note: All data has been anonymized to protect student privacy, in accordance with the ethical guidelines outlined in the manuscript.
DOI: 10.17632/xphc8ctxr3.1
title: The new version of the FUMILIM minimization package

description: The suggested package FUMILIM, based on famous FUMILI minimization package, has the following advantages: multi-optional user interface; speed advantage when the number of parameters is high enough; there are options to ignore wrong experimental points and correct experimental errors. The preliminary scan is envisaged for complicated tasks. The new version of FUMILIM is capable to work efficiently with multidimensional experimental points, described by a vector function. For heavy user’s functions the parallel fit is envisaged by means of OpenMP service. The package contains intrinsic user’s functions, namely, polynomial, sum of Gauss and sum of Rayleigh functions. All of them can be used without the definition of the parameter initial values. The program of plane track reconstruction via drift chambers and straws, which can be combined with single detectors, is also included in the package. The capacity of this program is about of 0.5⋅1060.5⋅106 tracks per second (at 2.8 GHz). There is a number of less important improvements of the package. All programmes are written in FORTRAN-90. The investigation has been performed at the Veksler and Baldin Laboratory of High Energy Physics, JINR. The previous version of this program (AEQF_v1_0) may be found at http://dx.doi.org/10.1016/j.cpc.2013.08.001.
DOI: 10.17632/67htnzmwbb.1
title: Mexican Sign Language's Dactylology and Ten First Numbers - Labeled images and videos. From person #6 to #11

description: The dataset comprises edited recordings of Mexican sign language's Dactylology (29 signs) and Ten First Numbers (from 1 to 10), including static and continuous signs accordingly from person 6 to the person 11. The edited recordings are organized for easy access and management. Edited videos and screenshots of static signs are labeled in their file with corresponding sign language representations and stored in a consistent order per person, the number of the cycle of recording, and per hand. Static sign images can be exported in PASCAL VOC format with XML annotations too. The dataset is designed to facilitate feature extraction and further analysis in Mexican sign language recognition research.
DOI: 10.17632/y2hkn43sd8
title: Assessing the transformative abilities of imaginative education: A Comparative Study of Imaginative and Mainstream Elementary Schools.

description: Data for the 5 assessments activitie.
DOI: 10.17632/rb24cpc2hg.1
title: MEASURING GREENWASHING: DEVELOPING AND VALIDATING CONSTRUCTS

description: This dataset, titled MEASURING GREENWASHING: DEVELOPING AND VALIDATING CONSTRUCTS, was collected as part of a study aimed at understanding greenwashing practices within organisations. The survey assesses organisational behaviours across multiple constructs of greenwashing, including Misleading Environmental Claims, Selective Disclosure, Symbolic Corporate Environmentalism, ESG Metric Manipulation, Green Trust, Digital Greenwashing, Corporate Reputation and Consumer Trust, and Investor Decision-Making.
The dataset includes responses from 320 participants representing diverse organizational roles and demographics. For each construct, participants rated their agreement with statements on a 1–5 Likert scale, where 1 indicates "Strongly Disagree" and 5 indicates "Strongly Agree." This dataset provides valuable insights into how greenwashing practices impact stakeholder trust and perceptions, serving as a foundation for validating measurement constructs for greenwashing in organizational contexts.
DOI: 10.17632/fpfwxbhbty.1
title: Near-Range Nighttime Rubber Tapping Line RGB-D Image Dataset

description: NEARCAM Nighttime Rubber Tapping Line Image Dataset

- An image dataset for rubber tapping line detection
- 1400 Tapping Panels, Mixed of RRIT-251 and RRIM-600 Natural Rubber Tree, Aged Between 7-10 years, 
- Different Lighting Technique, Main Lighting RGB1, Shadowed Lighting RGB2, and Depth images Captured with Intel RealSense D435
- Data collection : August 2018 to September 2018, Trang Thailand, during nighttime
- Owner and contact: Rattachai Wongtanawijit, Computer Engineering, Prince of Songkla University, HatYai, Thailand
DOI: 10.17632/n4ypn8sp9m.2
title: Dataset for TPB, Data Security and Perceived Benefits

description: Repeated actions and behaviours are characteristic of people’s daily lives. However, there is a dilemma when this repeated action is associated with mobile phone recycling since convincing mobile users to recycle sustainably is challenging. This study analysed the four factors (i.e., actual knowledge, salience, environmental constraints, and habits) adopted from the Integrated Behavioural Model (IBM) theory and examined their impact on behavioural sustainability. A partial least squares structural equation modelling (PLS-SEM) approach was applied to evaluate 601 responses from a self- administered online survey collected from mobile user participants based in the United Arab Emirates (UAE). The survey findings indicated that habit has the strongest and statistically significant positive influence on behaviour; followed by knowledge and skills. Additionally, the salience of behaviour has a considerably negative influence on behaviour sustainability unaffected by environmental constraints. This study serves as a springboard for future research examining the IBM model to understand recycling behaviour in general and smartphone recycling sustainability in particular. Additionally, this research can assist smartphone manufacturers in understanding the factors that will maintain the recycling behaviour continuity, increasing the number of returned devices.
DOI: 10.17632/tz54knmmdm.1
title: Freshwater invertebrates and environmental characteristics of ponds in Vendée wetlands, France

description: Freshwater invertebrates and zooplankton (FIZ) play a key role in freshwater ecosystems and in food webs, but there is little research on their life cycle, ecology, and conservation. Therefore, this study focused on FIZ’ annual dynamics (abundance, diversity, and gross energy) in 30 ponds located in two wetlands: the Marais breton and Marais poitevin (Atlantic coast, France, Europe). These ponds had a FIZ abundance of 50,412 ind/m3 per site [range of 28,864-80,690] in a year. The study defined four typologies of ponds according to the environmental variables and the presence of some key FIZ taxa. The first group had a long flooding time, high silt content, and aquatic vegetation cover. The associated taxa were Chironomidae, Gammaridae and Atyidae. The second group of ponds had moderate slopes, high sand content in the sediment and a rich abundance of microcrustacea. The third group contained shallow ponds with soft slopes and a high aquatic vegetation cover (100%), which result in high FIZ diversity. Finally, the fourth group contained ponds with steep slopes, high silt content in the sediment, and Oligochaeta as the major taxon in this environment. Defining pond typologies based on environmental factors and FIZ is essential to adapting FIZ management and conservation measures implemented on ponds. In a context of global change, a reduction or even disappearance of FIZ communities would have a catastrophic impact on all faunal taxa dependent on FIZ as a food resource.
DOI: 10.17632/7v54nk37mf.1
title: Engagement with a mobile-based assessment application in English as a Second Language Courses

description: Data collected from the interaction of N=120 students with a mobile-based assessment application in eight English as a Second Language courses in Colombia. The purpose was to apply the survival analysis method to determine if the time at which students disengage from the application was influenced by the acceptance of the appliction and the student motivation. The data set has the following columns: ID=internal ID of student reported_effort=self-reported measure of effort. feedback=number of times that students received corrective feedback in the mobile-based assessment app. interface= self-reported measure of the perception of the interface. perceived_ease_of_use = self-reported measure perceived ease of use. perceived_usefulness=self-reported measure perceived usefulness. behavioral_intention= self-reported measure of behavioral intention. Importance= self-reported measure of perception of importance. correctAnswers=total number of correct answers provided by the students in the mobile-based assessment app. time_ontask= total amount of time automatically measured by the mobile-based assessment app of the time students were answering questions in the application status=if students failed to answer an adequate number of questions in the mobile-based assessment app.
DOI: 10.17632/4tt953xwk2.1
title: Bengali Medical Dataset for Multi-purpose

description: This dataset has been created for our country, Bangladesh where people will get help from it. This dataset is for the medical specialist classification and Bengali Named Entity Recognition which will play a vital role in multi-purpose.
DOI: 10.17632/89r26wzdsn.1
title: Roads and livelihood activity choices in the Greater Serengeti Ecosystem, Tanzania

description: See publication in Plos One 2019: Roads and livelihood activity choices in the Greater Serengeti Ecosystem, Tanzania
DOI: 10.17632/py2zkrb65h.1
title: Synthetic European road freight transport flow data based on ETISplus

description: This dataset describes estimated European truck traffic flows between 1,675 regions all over Europe and is based on the publicly available ETISplus project from 2010 (DOI: 10.13140/RG.2.2.16768.25605). The project collected Europe-wide freight volumes and calibrated the resulting origin-destination matrices with real world traffic flows. For the current dataset,  the truck results of the ETISplus project were updated using current Eurostat data (https://ec.europa.eu/eurostat/web/transport/data/database). Additionally, a forecast was added for 2030. Using Dijkstra's algorithm, the freight flows were finally transferred to the European highway network. Therefore, the dataset provides a synthetically generated truck traffic volume for each road section. 
The dataset can be a basis for developing, planning and sizing future road infrastructure, such as charging infrastructure for electric trucks. 
The dataset consists of four files: 01_Trucktrafficflow, 02_NUTS-3-Regions, 03_network-nodes, 04_network-edges. All of them are stored as comma separated values with commas as column separators and dots as decimal separators. The main dataset 01_Trucktrafficflow describes 1,514,573 directed transport flows in fifteen columns: (1) ID origin region, (2) name origin region, (3) ID destination region, (4) name destination region, (5) shortest path in the modeled E-road network, (6) distance from origin region to the E-road network, (7) distance within the E-road network, (8) distance from the E-road network to the destination region, (9) total distance, (10) road freight flow in tons for 2010, (11) road freight flow in tons for 2019, (12) road freight flow in tons for 2030, (13) truck traffic flow in number of vehicles for 2010, (14) truck traffic flow in number of vehicles for 2019, (15) truck traffic flow in number of vehicles for 2030. 
02_NUTS-3-Regions contains a list with the regions under investigation. 
03_network-nodes and 04_network-edges illustrate the highway network. The first contains the following information on each network node as columns: (1) node ID, (2) longitude of the location, (3) latitude of the location, (4) ID of the corresponding NUTS-3 region, (5) country code. The second contains information on the edges: (1) edge ID, (2) information whether the edge is manually added or part of the original ETISplus dataset, (3) length of the edge, (4) ID endpoint A, (5) ID endpoint B, (6) number of trucks in 2019 (both directions), (7) number of  trucks in 2030 (both directions).
DOI: 10.17632/vb2m5x5xhr.2
title: Survey Dataset on Face to Face Students' intention to use Social Media and Emerging Technologies for Continuous Learning

description: One of the sectors that felt the impact of the Corona Virus Disease 2019 (COVID-19) pandemic was the educational sector. The outbreak led to the immediate closure of schools at all levels thereby sending billions of students away from their various institutions of learning. However, the shut down of academic institutions was not a total one as some institutions that were solely running online programmes were not affected. Those who were running face to face and online modes quickly switched over to the online mode. Unfortunately, institutions that have not fully embraced online mode of study were greatly affected. 85% of academic institutions in Nigeria are operating face to face mode of study, therefore, majority of Nigerian students at all levels were affected by the COVID-19 lockdown. Social media platforms and emerging technologies were the major backbones of institutions that are running online mode of study, therefore, this survey uses the unified theory of acceptance and use of technology (UTAUT) model to capture selected Face to face Nigerian University students accessibility, usage, intention and willingness to use these social media platforms and emerging technologies for learning. The challenges that could mar the usage of these technologies were also revealed. Eight hundred and fifty undergraduate students participated in the survey. The dataset includes the questionnaire used to retrieve the data, the responses obtained in spreadsheet format, the charts generated from the responses received, the Statistical Package of the Social Sciences (SPSS) file and the descriptive statistics for all the variables captured. This second version contains the reliability statistics of the UTAUT variables using Cronbach's alpha. This measured the reliability as well as the internal consistency of the UTAUT variables. This was measured in terms of the reliability statistics, inter-item correlation matrix and item-total statistics. Authors believed that the dataset will enhance understanding of how face to face students use social media platforms and how these platforms could be used to engage the students outside their classroom activities. Also, the dataset exposes how familiar face to face University students are to these emerging teaching and learning technologies.
DOI: 10.17632/69dcnv2gzd.1
title: Mental Health Insights: Vulnerable Cancer Survivors & Caregivers Data

description: We collected over 10,087 posts from cancer patients and their caregivers on platforms like Reddit, Daily Strength, and the Health Board. The posts were related to five types of cancer: brain, colon, liver, leukemia, and lung cancer. Two team members scored each post based on the emotions expressed, using a scale from -2 to 1. Negative scores (-1 or -2) were given for posts showing grief or suffering, positive scores (1) for happy emotions like relief or accomplishment, and posts with no emotion received a score of 0 and were considered neutral. This analysis aims to understand the emotional aspects of cancer patients posts for a mental health study.
DOI: 10.17632/42r9grxr6g.1
title: Data for: Freedom and Stock Market Performance during Covid-19 Outbreak

description: The sheet "Indices" include all the data, whereas C stands for case, D stands for death. Any variable such as C43560 can be understood as follows: First letter,C, is the variable, the numbers follow stand for date.
DOI: 10.17632/p9y27y66jb.1
title: MI-EEG-BCI-VR

description: This Data describes a framework known as MI-EEG-BCI-VR, integrating Motor Imagery (MI) and electroencephalography (EEG)-based Brain-Computer Interface (BCI) technologies, enabling users to navigate Virtual Environments (VEs) by imagining movements. The subject-specific feature extraction approach was employed.
To enhance user-friendliness and facilitate easy interaction, this Data contains interactive MATLAB-based Graphical User Interfaces (GUIs) for data acquisition, processing, visualization, and running tasks.
DOI: 10.17632/pwctygncrj.3
title: Laptop Components: Image Dataset to Classify Different Components

description: This dataset consists of two primary directories, specifically "Raw Data" and "Augmented Data". Each of these directories encompasses twenty-six sub-directories with the category names of the components. These include- 1. Battery 2. DVDRom 3. Hinge 4. Keyboard 5. Motherboard 6. DCCable 7. PowerSwitch 8. RAM 9. ScrewKit 10. USBPort 11. WiFiCard 12. Speaker 13. CMOSBattery 14. HardDiskDrive 15. WebCam 16. LCDScreen 17. Bezel 18. Heatsink 19. SSD 20. CPUFan 21. TouchPad 22. Processor 23. RAMCover 24. BasePanel 25. TopPanel 26. LVDSCable. 

Each sub-directory within the "Raw Data" directory comprises 140 high-quality images, whereas the numbers for the "Augmented Data" directories amount to 560.
DOI: 10.17632/ydmz5c822h.1
title: Data for: Nonlinear Field Dependent Conductivity Dielectrics made of Graphite Nanoplatelets Filled Composites

description: DC electrical conductivity GnP nanoplatelets composite materials
DOI: 10.17632/6kbpr5j2r6.1
title: Data for: The influence of tourism experiences and well-being on destination attachment

description: This study is about the influence of positive psychology on consumer behaviours in the tourism context