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6,782 results for “project”
The Angiosarcoma Project - Count Me In
The Angiosarcoma Project is an ongoing patient-driven initiative. This provisional dataset is currently derived from 328 samples, including tumor specimens (FFPE and cfDNA) from 274 angiosarcoma patients subjected to whole-exome sequencing (along with matched germline whole-exome sequencing). This study includes genomic data, medical record data (MedR), and pathology report data (PATH). All annotations have been de-identified. As these data were generated in a research laboratory, not a clinical laboratory, they are for research purposes only and cannot be used to inform clinical decision-making. The cases here are only those under the age of 40 years old.
Project dataset: predicting traffic volumes and congestion in road networks equipped with ANPR cameras
<p><a href="https://github.com/ppintosilva/anpr-predict">https://github.com/ppintosilva/anpr-predict</a></p>
Database of Measurement and Computation for PhD project
<p>This database is created for Fu Liye's Ph.D. project. This database is an organized collection of data Fu Liye obtain during his Ph.D. period. </p> <p>Since pursuing the Ph.D. is a so-called general project, in this database, the data is classified into different groups according to various sub-projects. </p>
Data for BSc project about Exposure, hazard and risk of the biocide triclosan in the aquatic environment
<p>This file contains all data used for the BSc project about Exposure, hazard and risk of the biocide triclosan in the aquatic environment.</p> <p> </p>
Anonymized Dataset for "How Difficult Can It Be? Assessing Workload Components and Predictors in Introductory CS Projects"
<p>Paper title: How Difficult Can It Be? Assessing Workload Components and Predictors in Introductory CS Projects</p> <p>This is a replication package using the anonymized dataset that we have collected including 161 entries of NASA-TLX surveys and the associated student source code metrics. Please cite the paper properly if you plan on using any parts of the dataset or the replication package.</p> <p> <br> <br> The following preprocessing steps proceed the work in this file: <br> 1- Collecting survey data and filtering incomplete entries, anonymizing data by replacing names with numbers. <br> 2- Calculating TLX and adding it as a feature to the data. <br> 3- Processing the code associated with each entry to calculate: loc, functions/methods, classes, style errors. <br> 4- Processing submission system logs to calculate number of commits/submissions. <br> <br> </p> <p><br> Dataset: anonymous-complete-preprocessed-TLX.csv <br> key: anonymous-dataset-key.txt</p>
Architecture Information Communication in Two OSS Projects: the Why, Who, When, and What: Complementary Material
<p>The complementary material of this study contains two files: - Architectural Posts, Architecture Elements, and Coding Results.xlsx We identified the architecture elements ("Architecture Elements Hibernate" and "Architecture Elements ArgoUML") from the developer mailing lists of two OSS projects (Hibernate and ArgoUML) based on our understanding of the ISO 42010:2011 standard. We also provided the coding results ("Coding Results Hibernate" and "Coding Results ArgoUML") based on the identified architecture elements of the two projects. Please note that column "Post ID" and "Thread ID" represent the ID of a post in the developer mailing list and the thread the post belongs to. The text in the column "Content" is excerpted from the architectural posts. The highlighted red text in the content indicates the related words used to identify the architecture element or code the concept from the architectural posts. The architecture elements are shown in column "Architecture Element", and the coding results of content are shown in column "Concept". - Criteria and Terms for Identifying Architecture Elements in Posts.pdf The table shows the inclusion criteria and terms employed for identifying architecture elements in posts of mailing lists based on our understanding of the ISO 42010:2011 standard.</p>
Architecture Information Communication in Two OSS Projects: the Why, Who, When, and What: Complementary Material
<p>The complementary material of this study contains two files:</p> <p>- <strong>Architectural Posts, Architecture Elements, and Coding Results.xlsx </strong></p> <p>We identified the architecture elements ("Architecture Elements Hibernate" and "Architecture Elements ArgoUML") from the developer mailing lists of two OSS projects (Hibernate and ArgoUML) based on our understanding of the ISO 42010:2011 standard. We also provided the coding results ("Coding Results Hibernate" and "Coding Results ArgoUML") based on the identified architecture elements of the two projects. Please note that column "Post ID" and "Thread ID" represent the ID of a post in the developer mailing list and the thread the post belongs to. The text in the column "Content" is excerpted from the architectural posts. The highlighted red text in the content indicates the related words used to identify the architecture element or code the concept from the architectural posts. The architecture elements are shown in the column "Architecture Element", and the coding results of content are shown in the column "Concept".</p> <p>- <strong>Criteria and Terms for Identifying Architecture Elements in Posts.pdf </strong></p> <p>The table shows the inclusion criteria and terms employed for identifying architecture elements in posts of mailing lists based on our understanding of the ISO 42010:2011 standard.</p>
Data Visualization - Project 1
<p>This project is a part of coursework for data visualization - 6401. The project analyzes G20 countries in the health, education and military areas from 2012 - 2017. HTML, CSS and Google Charts API have been used extensively for this project.</p>
Data Mining Project 2
<p>Data from a still-in-the-field survey conducted by Wayne State University's <a href="https://projectsupportwsu.org/">Project Support</a>. This analysis uses 3 peer-reviewed scales: Support, Outness, and Satisfaction.</p>
Workflow Diagram for GeoSoft "Geoscience Papers of the Future" (GPF) project - Tzeng
<p>This is a diagram for data provenance for a paper in progress, as part of a software sharing project. It is an earlier version of a the final diagram used in the paper.</p>
Pre-processed turbidity-temperature reads for project TLCST
<p>dataset.csv -----------</p> <p>V1: filename for the raw file</p> <p>V2: protein concentration in uM</p> <p>V3: rna concentration in ug/mL</p> <p>V4: nacl concentration in mM</p> <p>protien MW = 22000 g/mol</p> <p>results.csv --------------------</p> <p>output from the following pipeline</p> <p>dataset2cloudpoint.R</p> <p>https://github.com/yanxianUCSB/jascorscript/tree/master/jws2cloudpoint</p> <p>requirement: R >= 3.3.0</p>
Project New
<p>Music.</p>
Data and code for project "What makes users click: the effect of news values negativity and surprise in news headlines on the CTR"
<p>This repository includes the following files and corresponding Python codes saved in Jupiter Notebooks:</p> <p><strong>upworthy-archive-confirmatory-packages-03.12.2020.csv:</strong> Original dataset downloaded from The Upworthy Research Archive (https://osf.io/jd64p/)</p> <p><strong>cleaned_data.csv</strong>: <strong>upworthy-archive-confirmatory-packages-03.12.2020.csv</strong> cleaned with <strong>notebook_clean_data.ipynb</strong></p> <ul> <li>Data sorted by <em>clickability_test_id</em></li> <li>Headlines with 0 clicks deleted</li> <li>Variables <em>ctr</em>, <em>mean_ctr</em>, and <em>lift</em> created</li> <li>Variable <em>winner</em> converted to dummy variable</li> <li>Only kept first occurrence of headlines that occur multiple times in the dataset per test</li> <li>Deleted tests with only one headline</li> </ul> <p><strong>sample_manual_annotations.csv</strong>: sample of 300 headlines of <strong>cleaned_data.csv </strong>retrieved with <strong>notebook_sample_manual_annotations.ipynb</strong></p> <p><strong>inter-annotator_sentiment.csv</strong>: input for <strong>notebook_inter-annotator_scores_confusion_matrix.ipynb</strong> to calculate inter-annotator agreement scores with regard to annotating sentiment</p> <p><strong>inter-annotator_emotion.csv</strong>: input for <strong>notebook_inter-annotator_scores_confusion_matrix.ipynb</strong> to calculate inter-annotator agreement scores with regard to annotating emotion</p> <p><strong>input_sentiment.tsv</strong>: input for <strong>notebook_sentiment_emotion_test_set.ipynb </strong>for sentiment analysis on sample of 300 headlines in <strong>sample_manual_annotations.csv</strong></p> <p><strong>input_emotion.tsv</strong>: input for <strong>notebook_sentiment_emotion_test_set.ipynb </strong>for emotion analysis on sample of 300 headlines in <strong>sample_manual_annotations.csv</strong></p> <p><strong>input_all_headlines.tsv</strong>: input for <strong>notebook_sentiment_emotion_final_annotation.ipynb</strong> to annotate all headlines in <strong>cleaned_data.csv</strong></p> <p><strong>final_dataset.csv</strong>: output from <strong>notebook_merge_dataframes.ipynb</strong> that merges all csv output files from <strong>notebook_sentiment_emotion_final_annotation.ipynb </strong>with <strong>cleaned_data.csv</strong></p> <p><strong>notebook_descriptive_statistics.ipynb</strong>: Python code to retrieve descriptive statistics of various variables in <strong>cleaned_data.csv</strong></p> <p><strong>NRC-Emotion-Lexicon-Wordlevel-v0.92.txt:</strong> NRC Emotion Lexicon used in <strong>notebook_sentiment_emotion_test_set.ipynb </strong>and<strong> notebook_sentiment_emotion_final_annotation.ipynb</strong></p>
Management of potentially inappropriate drug prescriptions among Lebanese patients in primary care settings -the MGPIDP-L project: Description of an interventional prospective non-randomized study
<p>The aim of our study was to evaluate potentially inappropriate prescriptions among Lebanese geriatric population in primary care settings using the latest versions of Beers criteria, Laroche, European Union 7 (EU7), STOPP START, and STOPP Frail. Our secondary objectives were to assess disease related factors ,drug/therapy related factors, the proposed pharmaceutical interventions, and the satisfaction of the patients after performing the medication review.</p>
DIAPASON Project - Quality of residential facilities in Italy: satisfaction and quality of life of residents with schizophrenia spectrum disorders
<p>Datasets of the paper entitled <em>Quality of residential facilities in Italy: satisfaction and quality of life of residents with schizophrenia spectrum disorders. BMC Psychiatry. 2022 (DOI: </em>10.1186/s12888-022-04344-w) of the project "DAILY TIME USE, PHYSICAL ACTIVITY, QUALITY OF CARE AND INTERPERSONAL RELATIONSHIPS IN PSYCHIATRIC RESIDENTIAL FACILITIES: AN ITALIAN MULTICENTRE STUDY" Italian Ministry of Health, Italy, Ricerca Finalizzata (Grant RF-2018-12365514) (https://www.diapason-study.eu/)</p> <p> </p> <p> </p>
Growth of ice particle mass and projected area during riming
<p>There is a long-standing challenge in cloud and climate models to simulate the process of ice particle riming realistically, partly due to the unrealistic parameterization of the growth of ice particle mass (<em>m</em>) and projected area (<em>A</em>) during riming. This study addresses this problem, utilizing ground-based measurements of <em>m</em> and ice particle maximum dimension (<em>D</em>) as well as theory to formulate simple expressions describing the dependence of <em>m</em> and <em>A</em> on riming. It was observed that <em>β</em> in the <em>m</em> − <em>D</em> power law <em>m</em>  =&thinsp;<em>α</em> <em>D</em><sup><em>β</em></sup> appears independent of riming during the phase 1 (before the formation of graupel), with <em>α</em> accounting for the ice particle mass increase due to riming. This semi-empirical approach accounts for the degree of riming and renders a gradual and smooth ice particle growth process from unrimed ice particles to graupel, and thus avoids discontinuities in <em>m</em> and <em>A</em> during accretional growth. Once the graupel with quasi-spherical shape forms, <em>D</em> increases with an increase in <em>m</em> and <em>A</em> (phase 2 of riming). The treatment for riming is explicit, and includes the parameterization of the ice crystal–cloud droplet collision efficiency (<em>E</em><sub>c</sub>) for hexagonal columns and plates using hydrodynamic theory. In particular, <em>E</em><sub>c</sub> for cloud droplet diameters less than 10 µm are estimated, and under some conditions observed in mixed-phase clouds, these droplets can account for roughly half of the mass growth rate from riming. These physically meaningful yet simple methods can be used in models to improve the riming process.</p>
DIAPASON Project - Assessing adherence to and usability of Experience Sampling Method (ESM) and actigraph in patients with Schizophrenia Spectrum Disorder: A mixed-method study.
<p>Datasets of the paper entitled <em>Assessing adherence to and usability of Experience Sampling Method (ESM) and actigraph in patients with Schizophrenia Spectrum Disorder: A mixed-method study. Psychiatry Res. 2022 (</em>doi: 10.1016/j.psychres.2022.114675.)<em> </em> of the project "DAILY TIME USE, PHYSICAL ACTIVITY, QUALITY OF CARE AND INTERPERSONAL RELATIONSHIPS IN PSYCHIATRIC RESIDENTIAL FACILITIES: AN ITALIAN MULTICENTRE STUDY" Italian Ministry of Health, Italy, Ricerca Finalizzata (Grant RF-<a>2018-12365514</a>) (https://www.diapason-study.eu/)</p>
DIAPASON Project - Patterns of antipsychotic prescription and accelerometer-based physical activity levels in people with schizophrenia spectrum disorders: a multicenter, prospective study.
<p>Dataset of the paper entitled <em>Patterns of antipsychotic prescription and accelerometer-based physical activity levels in people with schizophrenia spectrum disorders: a multicenter, prospective study. Int Clin Psychopharmacol. 2023 (</em>doi: 10.1097/YIC.0000000000000433)<em> </em> of the project "DAILY TIME USE, PHYSICAL ACTIVITY, QUALITY OF CARE AND INTERPERSONAL RELATIONSHIPS IN PSYCHIATRIC RESIDENTIAL FACILITIES: AN ITALIAN MULTICENTRE STUDY" Italian Ministry of Health, Italy, Ricerca Finalizzata (Grant RF-<a>2018-12365514</a>) (https://www.diapason-study.eu/)</p>
DIAPASON Project - TIME WILL TELL: ASSOCIATIONS BETWEEN UNBALANCED TIME PERSPECTIVES AND SYMPTOM SEVERITY IN INDIVIDUALS WITH SCHIZOPHRENIA SPECTRUM DISORDERS
<p>Dataset of the paper entitled "<strong>TIME WILL TELL: ASSOCIATIONS BETWEEN UNBALANCED TIME PERSPECTIVES AND SYMPTOM SEVERITY IN INDIVIDUALS WITH SCHIZOPHRENIA SPECTRUM DISORDERS" </strong>of the project "DAILY TIME USE, PHYSICAL ACTIVITY, QUALITY OF CARE AND INTERPERSONAL RELATIONSHIPS IN PSYCHIATRIC RESIDENTIAL FACILITIES: AN ITALIAN MULTICENTRE STUDY" Italian Ministry of Health, Italy, Ricerca Finalizzata (Grant RF-<a>2018-12365514</a>) (https://www.diapason-study.eu/)</p>
DIAPASON Project - Needs for care of residents with schizophrenia spectrum disorders and association with daily activities and mood monitored with experience sampling method: the DIAPASON study.
<p>Dataset of the paper entitled <em>Needs for care of residents with schizophrenia spectrum disorders and association with daily activities and mood monitored with experience sampling method: the DIAPASON study. Epidemiol Psychiatr Sci. 2023 (DOI: </em>10.1017/S2045796023000124) of the project "DAILY TIME USE, PHYSICAL ACTIVITY, QUALITY OF CARE AND INTERPERSONAL RELATIONSHIPS IN PSYCHIATRIC RESIDENTIAL FACILITIES: AN ITALIAN MULTICENTRE STUDY" Italian Ministry of Health, Italy, Ricerca Finalizzata (Grant RF-<a>2018-12365514</a>) (https://www.diapason-study.eu/)</p>
ScienceDex guides
Understand access before you commit
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.