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4,182 results for “universities”
Mechanisms Influencing Group Teaching Learning Achieve-ment in University Students: The Mediating Role of Social Loafing
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Animations of the Longitudinal Beam Dynamics lecture - Proceedings of the Joint Universities Accelerator School (JUAS)
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Fig. 1. Incagonum jcbradleyi, new species. A in The Cornell University Entomological Expedition to South America of 1919-1920, Scientific Results: Incagonum jcbradleyi Liebherr and Will, New Species (Coleoptera: Carabidae: Platynini) from Peru
Fig. 1. Incagonum jcbradleyi, new species. A) Dorsal habitus, B) Lateral view of vestigial flight wing (w) beneath partially opened elytron, the wing extended just past posterior margin of metanotum (m), C) Male aedeagus, left view (everted position), including left paramere (lp) and right paramere (rp), D) Male laterotergite VIII (VIII) and medioterg- ite IX, or ring sclerite (IX).
Article dataset: "Assessing inclusivity at Ukrainian universities during wartime: studentsʼ voices"
<p>This dataset accompanies the study "Assessing inclusivity at Ukrainian universities during wartime: studentsʼ voices", which investigates the state of inclusivity in Ukrainian universities. This article examines the assessment of inclusivity by Ukrainian students in the context of war, emphasizing the crucial role of universities in supporting Sustainable Development Goals (SDGs), particularly SDG 4 aimed at ensuring quality education and promoting lifelong learning opportunities for all. In the context of warfare and its impact on the educational process, the article reveals how students overall assess the level of inclusivity and how students' assessment of inclusivity varies depending on the year of study and self-identification with vulnerable groups. The total number of university students who participated in the study was 4,389. Analyzing responses from the majority of students who perceive the university environment as highly inclusive, the study also identifies critical points where inclusivity measures could be improved, especially for students belonging to vulnerable groups, including those with disabilities and gender nonconforming individuals. </p> <p><strong>Contents of the dataset:</strong><br>1. Research program – a comprehensive outline of the research program detailing the study's objectives, methodology, and the analytical framework applied.<br>2. Survey questionnaire – the instrument employed to gather data from students, encompassing questions about their year of study and perceptions of inclusivity.<br>3. Raw responses – the unprocessed data obtained from 4,389 participants, including their anonymized answers to the survey questions.</p> <p><strong>Note: </strong>all data is presented in Ukrainian.</p> <p>Usage notes:<br>Researchers and practitioners are encouraged to use this dataset to further explore inclusivity in higher education, especially in contexts undergoing significant social and political transformations. Proper attribution should be given when using this dataset in any publication or presentation.</p> <p><strong>For any questions or additional information regarding this dataset, please contact:</strong></p> <p><strong>Dr. Yana Suchikova</strong><br>Vice-Rector for Research<br>Berdyansk State Pedagogical University, Ukraine <br>yanasuchikova@gmail.com</p>
Argumentative Skills in Higher Education: An analysis of university course Syllabus.
<p>Argumentative skills are personally and professionally essential to digest complicated information (CoI) associated with the critical reconstruction of meaning (critical thinking - CT). This is a vital goal, especially in the age of social media and artificial intelligence-mediated information. Recently, the introduction of generative artificial intelligence (GenAI), particularly ChatGPT (OpenAI, 2022), has made it much simpler to collect and exchange knowledge. New tools are desperately needed to deal with the glut of post-digital information without becoming lost.</p> <p>After exploring the landscape of argumentative skills and techniques for their development, an investigation of practices in use in Italian universities was undertaken. The analysis used university syllabi, which are considered key educational tools, to provide a comprehensive overview of the course to be undertaken. The syllabi contain key information such as objectives, competencies, assignments and assessment strategies. </p> <p>The research examined education science courses to understand the importance of argumentative skills, using stratified random sampling to proportionally represent all public universities with education science departments. 133 syllabi were selected through web scraping and web crawling techniques using R software (https://cran.r-project.org/bin/windows/base/), with manual addition to overcome technical limitations. </p> <p>The analysis included text mining techniques to identify documents containing keywords related to argumentative skills. These documents were then subjected to quantitative and qualitative content analysis. Biggs' (2003) "Constructive Alignment" principles were used to assess the alignment of goals, activities, and assessments in the syllabi. Categories of analysis included the detection of argumentative skills, their alignment, and connection to the course, with a focus on presence, level of treatment, and consistency of alignment.</p> <p>This Zenodo record follows the full analysis process with R and Nvivo (https://lumivero.com/products/nvivo/) composed of the following datasets, script and results:</p> <p>1. List of Universities with URLs - Elenco Università.xlsx</p> <p>2. Web Scraping Script - WebScarping.R</p> <p>3. Text Mining Script - TextMining.R</p> <p>4. List of the most frequent words - Vocabulary.csv</p> <p>5. Sentiment Analysis of the corpus - Sentiment Analysis.R</p> <p>6. List of documents from sorting by Keywords - frasi_chiave.docx</p> <p>7. Codebook qualitative Analysis with Nvivo - Codebook.xlsx</p> <p>8. Results Nvivo Analysis Syllabi - Codebook-Syllabi.docx</p> <p> </p> <p>Any comments or improvements are welcome!</p>
Evaluating the Impact of Education on Sustainability Knowledge, Attitudes, and Intentions Among University Students
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Simulation data on ORF6 from SARS-CoV-2 for a PhD thesis submitted to University College London
<p><strong>Unpublished data from a thesis submitted to University College London in September 2024 </strong></p> <p><em>Thesis title: Biophysical characterisation of ORF6 from SARS-CoV-2</em></p> <p><em><strong>Chapter 5 - full-length ORF6 metadynamic simulations in the AMBER03ws force field </strong></em></p> <p>The `Metadynamic_ORF6_full_length_simulations_Zenodo.tar.xz` directory contains data for a 61-residue disordered protein. The protein is ORF6 from SARS-CoV-2. The data were produced by metadynamics simulations in the AMBER03ws force field. I used PLUMED version 2.7.1 and GROMCS 2021.2. All the data and PLUMED input files required to reproduce the simulation results are available on PLUMED-NEST. This data should be used with the code provided on GitHub at [`https://github.com/alicejpettitt/thesis_2024/tree/main/chapter_5/full-length_orf6`](https://github.com/alicejpettitt/thesis_2024/tree/main/chapter_5/full-length_orf6)</p> <p>Once downloaded, this directory should be extracted using the following command: </p> <p>tar -xzvf Metadynamic_ORF6_full_length_simulations_Zenodo.tar.xz</p> <p>The directory should be saved with the name `Metadynamic_ORF6_full_length_simulations_Zenodo.tar.xz`` and placed in the same directory as the GitHub `README_metadynamic_simulations.md` file. </p> <p><strong>This dataset contains: </strong></p> <ul> <li> .pdb - atomic coordinate files for full-length ORF6 in the a03ws force field.</li> <li>_traj.trr - single concatenated trajectory files for the a03ws (ctr is just the last 21 residues of the full-length simulation).</li> <li>_weights_corr.dat - weights for each frame in _traj.trr for the a03ws run. Here, the weights of frames in which the peptide interacts with its periodic image have been set to zero. The cutoff was 1.2 nm.</li> <li>top_frames_.npy - numpy array of frames index for the a03ws simulations. Frames were selected based on weights_corr.dat.</li> <li>top_frames_.trr - trajectory of frames for the a03ws. Frames were selected based on weights_corr.dat</li> <li>CS_COLVAR_{system} - experimental and CamShift predicted chemical shifts for the last 21-residues of the full-length ORF6 simulation. </li> <li>Contacts directory: Contains Coulomb and LJ input files to make the contact maps. </li> </ul> <p><em><strong>Chapter 5 - ORF6-RAE1-NUP98_GLEBS metadynamic simulations in the AMBER99SB-disp force field </strong></em></p> <p>The `Metadynamic_ORF6_complex_simulations_Zenodo.tar.xz` directory contains data for the RAE1-NUP98-ORF6 complex. This was built upon the crystal structure: [`https://www.rcsb.org/structure/7VPH`](https://www.rcsb.org/structure/7VPH). The data were produced by metadynamics simulations in the AMBER99SB-disp force field. I used PLUMED version 2.7.1 and GROMCS 2021.2. This data should be used with the code provided on GitHub at [`https://github.com/alicejpettitt/thesis_2024/tree/main/chapter_5/orf6-rae1-nup98`](https://github.com/alicejpettitt/thesis_2024/tree/main/chapter_5/orf6-rae1-nup98)</p> <p>Once downloaded, this directory should be extracted using the following command: </p> <p>tar -xzvf Metadynamic_ORF6_complex_simulations_Zenodo.tar.xz</p> <p><strong>This dataset contains: </strong></p> <ul> <li>.pdb - atomic coordinate files for the complex in the AMBER99SB-disp force field</li> <li>traj.trr - single concatenated trajectory files for the</li> <li>_weights_corr.dat - weights for each frame in _traj.trr for the AMBER99SB-disp force field. Here, the weights of frames in which the peptide interacts with its periodic image have been set to zero. The cutoff was 1.2 nm. weights.dat is before this process.</li> <li>COLVAR files </li> </ul> <p>128 starting conformations (gro) files for each system listed above. </p>
ALFRAGANUS UNIVERSITY TALABALARINING VOLEYBOL SPORT TURI ORQALI SAKROVCHANLIK SIFATINI TAKOMILLASHTIRISH
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Entrance to Hamilton Hall, McMaster University
 Scan created on May 22, 2021 at https://w3w.co/evening.smoker.drip Created with Polycam Source: Objaverse 1.0 / Sketchfab
Sundail of Tsinghua University
**Photoscan:** Sundail of Tsinghua University, Beijing, China **Camera:** Canon 5D Mark III **Software:** Photoscan, Blender **Date:** May, 2016 Source: Objaverse 1.0 / Sketchfab
Clinical Comparison of Universal Adhesives in Terms of Different Application Modes on the Restoration of NCCLs
ClinicalTrials.gov study NCT03415516. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Cognitive Behavioral Intervention and Adventure Training for Chinese University Students in Hong Kong
ClinicalTrials.gov study NCT04560348. IPD Sharing: NO. Countries: 0. Publications: 0.
Universal CAR-T Cell Therapy for Refractory Lupus Nephritis
ClinicalTrials.gov study NCT06681337. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Effect of the Physical Activity Courses on the Physical Activity Level at University Students
ClinicalTrials.gov study NCT04299061. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Evaluation of Volume Status Changes in Children on Regular Hemodialysis at Assiut University Children,s Hospital
ClinicalTrials.gov study NCT06194019. IPD Sharing: NO. Countries: 0. Publications: 0.
Incidence of Perioperative Cerebrovascular Stroke in Assuit University Hospitals , Hospital Based Study
ClinicalTrials.gov study NCT06314269. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Evaluation of Cardiac Affections in Patients With Mucopolysaccharidosis (MPS) in Assuit University Children Hospital (AUCH)
ClinicalTrials.gov study NCT04637646. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Randomized Clinical Trial of Fissure Sealants Comparing Universal Adhesive With Etch-And-Rinse Adhesive After 24 Month
ClinicalTrials.gov study NCT04837469. IPD Sharing: NO. Countries: 0. Publications: 0.
Universal Hemoglobin A1c Versus Risk-based Screening for Early Gestational Diabetes Mellitus (EARLY GDM): A Randomized Controlled Trial
ClinicalTrials.gov study NCT06190405. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Urinary Activin A as Apredictive Marker for Assessement of Acute Kidney Injury Severity in Patient Admitted at Assuit University Hospital
ClinicalTrials.gov study NCT06188533. IPD Sharing: Not stated. Countries: 0. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.