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394 results for “thesis”
Supplementary tables master's thesis Carolin Mattausch 2023
<p>These table contain information about ChIP-seq files from different sources used in Carolin Mattausch's master's thesis "Integration of transcriptome and epigenome for comparative analysis of various chondrocyte subtypes" conducted November 2022 to June 2023 in the Department of Developmental Biology at the Center of Medical Biotechnology, University Duisburg-Essen, under the supervision of Prof. Dr. Andrea Vortkamp, Dr. Manuela Wuelling, and Christoph Neu.</p> <p><strong>Supplementary table 4</strong>: Metadata, experiment, and file accession numbers for ChIP-seq files downloaded from <a href="https://www.encodeproject.org/">ENCODE</a>. These files were used in in comparison of H3K27me3 level between different murine and human tissues.</p> <p><strong>Supplementary table 5</strong>: Metadata, experiment, and file accession numbers for ChIP-seq files downloaded from <a href="https://egg2.wustl.edu/roadmap/web_portal/">Roadmap</a>. These files were used in in comparison of H3K27me3 level between different murine and human tissues.</p> <p><strong>Supplementary table 6</strong>: Metadata, experiment, and file accession numbers for ChIP-seq files downloaded from <a href="https://www.ncbi.nlm.nih.gov/geo/">Gene Expression Omnibus</a>. These files were used in in comparison of H3K27me3 level between different murine and human tissues.</p>
SIVA FINAL THESIS ..........controls.csv
<p>This data includes controls - sociodemographic factors, lab parameters, biochemical characteristics, hospital stay and outcome</p>
Data repository - BSc thesis Jara Schrandt
<p>This repository contains all data necessary to reproduce data of the BSc. thesis of Jara Schrandt [12645028]. Bsc. Future Planet Studies at the University of Amsterdam. Additionally, the thesis can be requested by contacting the author.</p>
Data for thesis titled: The impact of processing conditions on enzymatic protein hydrolysis performance from sardine (Sardina pilchardus) by-products using Alcalase 2.4L, and the influence on final spray dried hydrolysate powder properties
<p>The data answer the objectives that focused on:</p> <ol> <li>determining the substrate-specific optimum hydrolysis temperature and pH for the particular enzyme-substrate (Alcalase-sardine by-product) combination,</li> <li>investigating the effect of mixing speed, solids concentration and enzyme dosage on dry solids yield and protein recovery during enzymatic hydrolysis of sardine processing by-products,</li> <li>evaluating the influence of solids concentration on emulsion formation during enzymatic hydrolysis,</li> <li>determining the effect of solids concentration and emulsion formation on molecular weight distribution of protein hydrolysates,</li> <li>investigating the effect of mixing speed and solids concentration on the viscosity and mixing regime of material during enzymatic hydrolysis,</li> <li>establishing the role played by processing conditions (degree of hydrolysis (DH), maltodextrin addition and inlet air temperature) on powder recovery during spray drying, and</li> <li>investigating the role of DH, maltodextrin concentration and spray drying temperature on handling and storage properties of spray dried protein hydrolysates.</li> </ol> <p>This data also appears in journal papers with the following titles:</p> <p>Chiodza, K. & Goosen, N.J. 2023a. Evaluation of handling and storage stability of spray dried protein hydrolysates from sardine (Sardina pilchardus) processing by-products: Effect of enzymatic hydrolysis time, spray drying temperature and maltodextrin concentration. <em>Food and Bioproducts Processing</em>. (June, 30). DOI: <a href="https://www.sciencedirect.com/science/article/pii/S0960308523000743?via%3Dihub">https://doi.org/10.1016/j.fbp.2023.06.009</a>.</p> <p>Chiodza, K. & Goosen, N.J. 2023b. Influence of mixing speed, solids concentration and enzyme dosage on dry solids yield and protein recovery during enzymatic hydrolysis of sardine (Sardina pilchardus) processing by-products using Alcalase 2.4L: a multivariable optimisation approach. <em>Biomass Conversion and Biorefinery</em>. 1:1–23. DOI: <a href="https://link.springer.com/article/10.1007/s13399-023-03829-2">https://doi.org/10.1007/s13399-023-03829-2</a>. </p> <p>Chiodza, K. & Goosen, N.J. 2023c. Emulsion formation during enzymatic protein hydrolysis and its effect on protein recovery and molecular weight distribution of protein hydrolysates from sardine (Sardina pilchardus) by-products. <em>Biomass Conversion and Biorefinery</em>. 1:1–12. DOI: <a href="https://link.springer.com/article/10.1007/s13399-023-04438-9">https://doi.org/10.1007/s13399-023-04438-9</a>.</p>
Badia_additional_info_bachelor_thesis
<p>This is the appendix of my Bachelor Thesis: <em><strong><span>A first approach to the morphological evolution of the Agamidae lizards (Iguania: Acrodonta) and its relationship with their habitat and lifestyles.</span></strong></em></p> <p>It contains my R script, my raw data table with the habitat categorizations for each agamid species and notes, the phylogenetic tree I used, as well as some graphs illustrating morphological features.</p>
Thesis: Transcriptome analysis of insecticide resistant Drosophila suzukii
Open the record for dataset details and reuse information.
Lichen abundance and biodiversity along a chronosequence from young managed stands to ancient forest, 1993 (Neitlich thesis)
The diversity of epiphytic lichens in old growth forests has stimulated considerable research (e.g., Howe 1978, Pike et al. 1975; Hoffman and Kazmierski 1969). We possess few data on the lichen communities of younger stands or the manner in which they develop as the forest ages. As our society grapples with the consequences of habitat loss and pressure on existing natural populations, such data are acutely needed (FEMAT 1993). This paper seeks to describe the relationship between forest age and the abundance and diversity of lichens in one region, and in doing so, to invite more rigorous assessment of the conservation needs of lichens with respect to forest management. Moveover, that documenting these patterns will facilitate research into age- related processes directly influencing lichen abundance and diversity.
Thesis-Supplementary Tables
<p>The uploaded excel file contains all the supplementary tables for Marwa Almosailleakh Doctoral Thesis tilted '' Insights into cellular and molecular mechanisms of normal and malignant hematopoiesis from mouse models'' </p> <p> </p>
Dataset experience 4 PHD Thesis - Données expérience 4 Thèse
<p><strong>FR: Fichier "VérifDataXP4" :</strong> Données brutes pour la réalisation d'un geste technique (point de suture) de 44 étudiants en médecine. Il regroupe les données chronométriques de consultation des instructions (LEC), de réalisation de la tâche (REAL) et d'exécution du geste (EXE) en minutes et centièmes.<br> La qualité des sutures a également été évaluée, avec une échelle OSATS (OSATS) et une échelle d'erreurs (ERR).<br> Toutes ces variables dépendantes ont été mesurées sur 5 essais pour étudier les différentes étapes de l'apprentissage du geste.<br> Les participants avaient des instructions soit présentées selon une perspective égocentrée (GP EGO) ou hétérocentrée (GP HETE). Ils avaient des capacités de rotation mentale élevées (RM +) ou faibles (RM-).</p> <p><strong>Fichier "Résultats questionnaireXP4" :</strong> Données brutes pour les questionnaires pré et post-expérience liés à cette recherche.</p> <p><strong>ENG : File "VérifDataXP4" :</strong> Raw data for the realization of a technical gesture (suture) of 44 medical students. It groups together the data for consultation (LEC), task completion (REAL) and execution (EXE) times in minutes and hundredth. The quality of the sutures were also assessed, with an OSATS scale (OSATS) and an error scale (ERR). All these dependent variables were measured on 5 suture trials to study the different steps in learning a gesture. The participants had instructions either in an egocentric (GP EGO) or heterocentric (GP HETE) perpective. They had either high (RM+) or low (RM-) mental rotation abilities.</p> <p><strong>File "Résultats questionnaireXP4" : </strong> Raw data for pre- and post-experience questionnaires related to this research.</p>
Dataset experience 3 PHD Thesis - Données expérience 3 Thèse
<p><strong>FR: Fichier "DonnéesVérif XP3" :</strong> Données brutes pour la réalisation d'un geste technique (point de suture) de 44 étudiants en médecine. Il regroupe les données chronométriques de consultation des instructions (LEC), de réalisation de la tâche (REAL) et d'exécution du geste (EXE). Ces données sont disponibles en millisecondes, en secondes, ou en minutes et centièmes.<br> La qualité des sutures a également été évaluée, avec une échelle OSATS (OSATS) et une échelle d'erreurs (ERR).<br> Toutes ces variables dépendantes ont été mesurées sur 5 essais lors d'une première sessions pour étudier les différentes étapes de l'apprentissage du geste, puis le temps d'exécution (EXE), le score OSATS (OSATS) et le nombre d'erreurs (ERR) ont été mesurés sur une seconde session.<br> Les participants avaient des instructions soit présentées selon une perspective égocentrée (GP e1) ou hétérocentrée (GP h2). Etaient également prises en compte: leur aptitude à la rotation mentale (RM) et à la prise de perspective (VISU).</p> <p><strong>Fichier "Données questionnaireXP3" :</strong> Données brutes pour les questionnaires pré et post-expérience liés à cette recherche.</p> <p><strong>ENG : File "DonnéesVérif XP3" : </strong>Raw data for the realization of a technical gesture (suture) of 44 medical students. It groups together the data for consultation (LEC), task completion (REAL) and execution (EXE) times. This data is available in milliseconds, seconds, or minutes and hundredths. The quality of the sutures were also assessed, with an OSATS scale (OSATS) and an error scale (ERR). All these dependent variables were measured on 5 suture trials in a first session to study the different steps in learning a gesture , then the execution time (EXE), the OSATS score (OSATS) and the number of errors. (ERR) were measured on a second session. The participants had instructions either in an egocentric (GP e1) or heterocentric (GP h2) perspective. Also taken into account: their aptitude for mental rotation (RM) and perspective taking (VISU).</p> <p><strong>File "Données questionnaireXP3" : </strong> Raw data for pre- and post-experience questionnaires related to this research.</p>
Dataset experience 5 PHD Thesis - Données expérience 5 Thèse
<p><strong>FR: Fichier "Données XPblended learning" :</strong> Données brutes pour la réalisation d'un geste technique (point de suture) de 43 étudiants en médecine. La moitié des participants réalisait un apprentissage combinant e-learning et simulation avant la première évaluation, puis un apprentissage en atelier présentiel avant la deuxième évaluation, une semaine plus tard (GP 1). L'autre moitié des participants commençait par l'atelier en présentiel puis réalisait l'apprentissage en e-learning une semaine plus tard (GP 2).</p> <p>Il regroupe les données concernant la qualité des sutures, évaluée avec une échelle OSATS (OSATS) et une échelle d'erreurs (ERR). Une évaluation subjective de la part des participants de la qualité de la réalisation a également été réalisée par les participants (AUTOEVAL). Ces variables dépendantes ont été mesurées sur 3 essais lors d'une première session puis 3 autres essais une semaine plus tard. Le temps de réalisation de la procédure (REAL) à également été mesuré lors de la deuxième évaluation.</p> <p><strong>Fichier "Résultats questionnaires" :</strong> Données brutes pour les questionnaires pré et post-expérience liés à cette recherche.</p> <p><strong>ENG : File "Données XPblended learning" :</strong> Raw data for the performance of a technical gesture (suture) of 43 medical students. The experiment was carried out in two sessions, an e-learning session and a workshop session. Both sessions were followed with the assessment of participants’ acquired skills. Twenty-four participants started with the e-learning session and went to the workshop session one week later (Group 1). Nineteen participants started with the workshop session and came to the e-learning session one week later (Group 2) (Fig. 1).<br> <br> It groups data concerning the quality of sutures, evaluated with an OSATS scale (OSATS) and an error scale (ERR). A subjective assessment by the participants of the quality of their realization was also carried (AUTOEVAL). These dependent variables were measured on 3 trials during a first session then on 3 other trials a week later. The task completion time (REAL) was also measured during the second evaluation.</p> <p><strong>File "Résultats questionnaires" : </strong> Raw data for pre- and post-experience questionnaires related to this research.</p>
Dataset experience 1 PHD Thesis - Données expérience 1 Thèse
<p><strong>FR: Fichier "XPeye-tracker" :</strong> Données brutes pour la réalisation d'un geste technique (point de suture) de 67 étudiants en médecine confrontés à des instructions vidéo (GP 2=VID) ou photo (GP 1=IMG). Il regroupe les données chronométriques (évaluées à l'aide d'un eye-tracker) de consultation des instructions (LEC), de réalisation de la tâche (REAL), d'exécution du geste (EXE), et de la durée moyenne d'une consultation (CONSULT) en secondes ou en minutes et centièmes. Le nombre d'alternances entre consultation et exécution (ALTER) est également pris en compte.<br> La qualité des sutures a également été évaluée, avec une échelle OSATS (OSATS) et une échelle d'erreurs (ERR). L'effort mental (EM) et la difficulté perçue de la tâche (DIFF) à fait l'objet d'une évaluation subjective de la part des participants.<br> Toutes ces variables dépendantes ont été mesurées sur 5 essais pour étudier les différentes étapes de l'apprentissage du geste.</p> <p><strong>Fichier "QuestionnaireXPeye-tracker" :</strong> Données brutes pour les questionnaires pré et post-expérience liés à cette recherche.</p> <p><strong>ENG : File "XPeye-tracker" :</strong> Raw data for the realization of a technical gesture (suture) of 67 medical students confronted with video (GP 2 = VID) or photo (GP 1 = IMG) instructions. It groups together chronometric data (evaluated using an eye-tracker) for instructions consultation (LEC), task completion (REAL), gesture execution (EXE), and the average duration of a consultation (CONSULT) in seconds or in minutes and hundredths. The number of alternations between consultation and execution (ALTER) is also measured.<br> The quality of the sutures was also assessed, using an OSATS scale (OSATS) and an error scale (ERR). The mental effort (EM) and the perceived difficulty of the task (DIFF) were subjectivly evaluated by the participants.<br> All these dependent variables were measured on 5 trials to study the different stages of learning the gesture.</p> <p><strong>File "QuestionnaireXPeye-tracker" : </strong> Raw data for pre- and post-experience questionnaires related to this research.</p>
Supplementary material to the masters thesis: NUTS-3 Regionalization of Industrial Load Shifting Potential in Germany using a Time-Resolved Model
<p>This is the supplementary material to the masters thesis:</p> <p>"NUTS-3 Regionalization of Industrial Load Shifting Potential in Germany using a Time-Resolved Model"</p> <p><strong>LICENSE</strong></p> <p>All output data provided is under Creative Commons Attribution 4.0 International Public License. All Python scripts provided are under Apache License, Version 2.0. Refer to the ‘Input data documentation’ file for source and data license information for the input data. For license information, refer to the LICENSE files.</p> <p><strong>DATASET DESCRIPTION</strong></p> <p>The supplementary material is organized into four different subdirectories:</p> <ul> <li>The subdirectory ‘Industrial processes’ contains the input data, Python scripts, and output data for the estimation of NUTS-3 load shifting potential of suitable electrically powered industrial processes (cement milling, mechanical pulping, paper production, air separation).</li> <li>The subdirectory ‘Process heat’ contains the input data, Python scripts, and output data for the estimation of NUTS-3 load shifting potential of industrial process heat applications that are powered by electricity.</li> <li>The subdirectory ‘Future projections’ contains the input data, Python scripts, and output data for the estimation of NUTS-0 annual average industrial processes load shifting potential in the future up until 2050.</li> <li>The subdirectory ‘Other tables for reference’ contains data tables that are not used as input data to the Python scripts, but which may serve as useful further reference for the reader. These tables are the original or intermediate tables from which the input data tables were created.</li> </ul> <p>For more information refer to the README file.</p> <p>For a detailed description of the approach developed by the author, the input data used and the generated results, refer to the masters thesis "NUTS-3 Regionalization of Industrial Load Shifting Potential in Germany using a Time-Resolved Model", available here: <a href="https://elib.dlr.de/134116/">https://elib.dlr.de/134116/</a></p> <p>In case of questions please contact: bruno.schyska@dlr.de or wilko.heitkoetter@dlr.de</p> <p> </p>
PhD thesis supporting material
<p>This dataset contains the archive of the supporting code and simulation data for my doctoral thesis at the University of Bonn available here (http://hdl.handle.net/20.500.11811/8443).</p>
Thesis DRIS leaf nutrient analysis results
<p>The data file contains results from leaf nutrient analysis that have been analyzed with the Florida citrus DRIS program, created by Arnold Schumann (UF IFAS Citrus Research and Education Center, Soil and Precision Agricultura Lab). This data was used to train an AI model to recognize nutrient deficiencies of citrus. </p>
Public Defense of Doctoral Thesis: "Improving the Resilience of the Constrained Internet of Things" (raw video)
<p>This is the raw video footage of Renzo E. Navas' public PhD Thesis Defense: "Improving the Resilience of the Constrained Internet of Things". Original date: Wednesday 9th of December 2020.</p>
Code and data used in thesis Chapter 2 of 'Determining the biases and consistencies in the evidence for conservation'
<p>Code and data used in thesis Chapter 2 of 'Determining the biases and consistencies in the evidence for conservation'.</p>
bachelor-thesis: Rapid Review - Identified Tools to Support SLR Including Features and Supported Stages
<p>This item presents the identified tools to support SLR and the supported stages and features of these tools.</p>
bachelor-thesis: Rapid Review - SLR Tools and their Characteristics
<p>This item contains releveant artefacts for the conducted Rapid Review. Therefore it includes the set of included papers and the tools to support SLR presented in a tabular form with tool characteristics.</p>
ComedyLab: As per thesis, v1.0
<p>Data and scripts for the experimental programme of my PhD</p> <p>-- Toby Harris</p>
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.