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6,452 results for “Application”
Reproduction of PANDA: processed data for simulations and applications
<p>These data are processed data for simulations and applications used to reproduce the results in the paper "Dual decoding of cell types and gene expression in spatial transcriptomics with PANDA".</p> <p>To ensure that the file paths match those used in the code, please place the files in the following directories within your working directory before extracting them:</p> <p>"Data/processed_data/simulations/paired_scenario.zip"</p> <p>"Data/processed_data/simulations/unpaired_scenario.zip"</p> <p>"Data/processed_data/simulations/merfish.zip"</p> <p>"Data/processed_data/simulations/reference_choice.zip"</p> <p>"Data/processed_data/applications/melanoma.zip"</p> <p>"Data/processed_data/applications/mouse_brain.zip"</p> <p>"Data/processed_data/applications/human_heart.zip"</p>
Reproduction of PANDA: results for applications
<p>These data are the results obtained from applying PANDA to applications and can be used to reproduce the analysis in the paper "Dual decoding of cell types and gene expression in spatial transcriptomics with PANDA".</p> <p>To ensure that the file paths match those used in the code, please place the files in the following directories within your working directory before extracting them:</p> <p>"Results/applications/melanoma.zip"</p> <p>"Results/applications/mouse_brain.zip"</p> <p>"Results/applications/human_heart.zip"</p>
Supplementary data for the article: "Towards an widely applicable earthquake detection algorithm for fibreoptic and hybrid fibreoptic-seismometer networks"
<p>Repository of supporting data associated with the article submitted to GJI, titled: "Towards an widely applicable earthquake detection algorithm for fibreoptic and hybrid fibreoptic-seismometer networks".</p> <p> </p> <p>Contents include:</p> <ol> <li>A full working example of modified QuakeMigrate version and seismic time-series data used to detect an earthquake.</li> <li>Earthquake catalogues for the three datasets described in the publication.</li> </ol>
HCPN Model for the article A Self-Sovereign Identity-based Authentication and Reputation Protocol for IoV Applications
<p>HCPN modules of the entire formal validation model of the article A Self-Sovereign Identity-based Authentication and Reputation Protocol for IoV Applications.</p>
Wave Simulation Results Using XBeach and Application Results at Kansai International Airport (KIX)
<p>The dataset includes input files for the numerical simulations (grids, topography, boundary conditions, and parameter settings), XBeach simulation results for a wind speed of 30 m/s, and the application results for Kansai International Airport (KIX).</p>
XPS investigation of Co-Ni oxidized compounds surface using peak on satellites ratio. Application to Co20Ni80 passive layer structure and composition.
<p>The .xls files contain the data of the Ni2p and Co2p spectra recorded on the spontaneously oxidized alloy sample, during sputtering.</p>
A bench-stable fluorophosphine nickel(0) complex and its catalytic application
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A Developer-Centric Study Exploring Mobile Application Security Practices and Challenges
<p>This is the dataset for the paper: <strong>A Developer-Centric Study Exploring Mobile Application Security Practices and Challenges</strong></p> <p>This paper was accepted for publication at the International Conference on Software Maintenance and Evolution (ICSME 2024) - Industry Track</p> <p>Preprint: <a href="https://arxiv.org/abs/2408.09032">https://arxiv.org/abs/2408.09032</a></p> <p> </p> <h2><strong>Artifacts</strong></h2> <p>The table below describes the artifacts associated with this study.</p> <table> <tbody> <tr> <td><strong>File</strong></td> <td><strong>Purpose</strong></td> </tr> <tr> <td>SurveyResponse.csv</td> <td>The results of the online survey. This file contains only responses from participants who completed all required survey questions.</td> </tr> <tr> <td>SurveyQuestions.pdf & SurveyQuestions.tex</td> <td>These files contain the survey questions in the form they were presented to participants. They are in PDF and LaTeX format.</td> </tr> <tr> <td>ParticipantLocation.xlsx </td> <td>This file shows the location (based on Qualtircs metadata) of participants who responded to the survey.</td> </tr> <tr> <td>IRB_Approval.pdf</td> <td>This is the IRB approval document.</td> </tr> <tr> <td>freetext-responses-categorized.xlsx</td> <td>This file is related to survey questions #20, #22, and #23. It is a manual categorization of free-text responses by the authors. </td> </tr> <tr> <td>likert-figures\*.pdf</td> <td>The files in this directory are the Likert figures used in the paper.</td> </tr> <tr> <td>multichoice-questions\*.csv</td> <td>The files in this directory show the frequency of occurrence for the answer options associated with single-choice and multi-choice questions.</td> </tr> <tr> <td>code\</td> <td>Python code to generate the Likert charts and the CSV files that show the frequency of occurrence for the answer options.</td> </tr> <tr> <td>LICENSE.txt</td> <td>Open-source license compliant with OSI.</td> </tr> </tbody> </table> <h2>Code</h2> <p>The code is written in Python. Below is a description of the files:</p> <ol> <li>requirements.txt - Required packages</li> <li>MultiChoiceAnalysis.py - This file contains the logic to analyze the multichoice questions to generate the frequency of occurrence of the answer options. The CSV files are created in the parent directory</li> <li>main-mobileSecurity.py - This file reads SurveyResponse.csv (in the parent directory) and has the code to generate the likert charts and calls MultiChoiceAnalysis.py. The Likert charts are created in the parent directory.</li> </ol> <p>Perform the below steps to execute the code:</p> <ol> <li> Create a Python virtual environment: <blockquote> python -m venv venv</blockquote> </li> <li>Activate the virtual environment: <blockquote> venv\Scripts\activate</blockquote> </li> <li>Install packages <blockquote> pip install -r requirements.txt</blockquote> </li> <li>Run the Python code: <blockquote> python main-mobileSecurity.py</blockquote> </li> </ol> <p>Below are details about the code execution output:</p> <ul> <li>The CSV and PDF files will be created in the parent directory.</li> <li>The Likert charts (i.e., PDF files) are created in a directory called "likert-figures"</li> <li>The CSV files are created in a directory called "multichoice-questions"</li> <li>Elements from the CSV files are part of the write-up in the Results section of the manuscript. The numeric digits that are part of the file name correspond to the survey question.</li> <li>The data present in Tables 2 to 5 in the manuscript is obtained from the CSV files generated by the Python code. Specifically: <ul> <li>Table 2 - \multichoice-questions\survey-11-frequency_single_choice.csv</li> <li>Table 3 - \multichoice-questions\survey-12-frequency_single_choice.csv</li> <li>Table 4 - \multichoice-questions\survey-13-frequency_single_choice.csv</li> <li>Table 5 - \multichoice-questions\survey-14-frequency_single_choice.csv and \multichoice-questions\survey-15-frequency_single_choice.csv</li> </ul> </li> </ul> <p><em>Note: We include these output files in the artifacts package by default. The user can delete these directories and run the code to regenerate the files.</em></p>
Accelerating Python Applications with Dask and ProxyStore
<p>Applications are increasingly written as dynamic workflows underpinned by an execution framework that manages asynchronous computations across distributed hardware. However, execution frameworks typically offer one-size-fits-all solutions for data flow management, which can restrict performance and scalability. ProxyStore, a middleware layer that optimizes data flow via an advanced pass-by-reference paradigm, has shown to be an effective mechanism for addressing these limitations. Here, we investigate integrating ProxyStore with Dask Distributed, one of the most popular libraries for distributed computing in Python, with the goal of supporting scalable and portable scientific workflows. Dask provides a easy-to-use and flexible framework, but is less optimized for scaling certain data-intensive workflows. We investigate these limitations and detail the technical contributions necessary to develop a robust solution for distributed applications and demonstrate improved performance on synthetic benchmarks and real applications.</p>
Towards the Use of Lichens as a Source of Bioactive Substances for Topical Applications
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Trained Surface Layer Models and Metrics for "Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications"
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High-Capacity Mesoporous Silica Nanocarriers of siRNA for Applications in Retinal Delivery
<p>The main cause of subretinal neovascularisation in wet age-related macular degeneration (AMD) is an abnormal expression in the retinal pigment epithelium (RPE) of the vascular endothelial growth factor (VEGF). Current approaches for the treatment of AMD present considerable issues that could be overcome by encapsulating anti-VEGF drugs in suitable nanocarriers, thus providing better penetration, higher retention times, and sustained release. In this work, the ability of large pore mesoporous silica nanoparticles (LP-MSNs) to transport and protect nucleic acid molecules is exploited to develop an innovative LP-MSN-based nanosystem for the topical administration of anti-VEGF siRNA molecules to RPE cells. siRNA is loaded into LP-MSN mesopores, while the external surface of the nanodevices is functionalised with polyethylenimine (PEI) chains that allow the controlled release of siRNA and promote endosomal escape to facilitate cytosolic delivery of the cargo. The successful results obtained for VEGF silencing in ARPE-19 RPE cells demonstrate that the designed nanodevice is suitable as an siRNA transporter.</p>
Replication package tied with the paper "WasteLess: An Optimal Provisioner for Self-Adaptive Second-Generation Serverless Applications"
<p>This is the replication package tied with paper "WasteLess: An Optimal Provisioner for Self-Adaptive Second-Generation Serverless Applications" submitted to the 20th International Conference on Software Engineering for Adaptive and Self-Managing Systems (SEAMS'25)</p> <p><strong>Contents<br></strong>The package contains a single zip file (WlessPackage.zip) with all the material used for conducting the paper experimentsation. Refer to the README.md file contained in the zip package for a detailed description of its content.</p>
Replication package for "Application Barriers and the Socioeconomic Gap in Child Care Enrollment"
<p>This package contains the readme, data, and dofiles to replicate the results of the paper</p> <p>"Application Barriers and the Socioeconomic Gap in Child Care Enrollment"</p> <p>by Henning Hermes, Philipp Lergetporer, Frauke Peter & Simon Wiederhold</p> <p>forthcoming at JEEA.</p>
Analyzing Efficiency of High-Performance Applications
<p>This dataset contains the measurement data, plots and scripts of the bachelor's thesis "Analyzing Efficiency of High-Performance Applications".</p>
Automatic Bottom-Up Taxonomy Construction: A Software Application Domain Study - Data
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Dataset for Automatic motion estimation with applications to hiPSC-CMs
<p>Supplementary data for paper Automatic motion estimation with applications to hiPSC-CMs</p>
Model input for initial submission of "A regional physical-biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0)" to GMD
<p>This dataset contains the numerical model input files that were used to produce the model simulation presented in the initual submission "A regional physical-biogeochemical ocean model for marine resource applications in the Northeast Pacific (MOM6-COBALT-NEP10k v1.0)" to Geoscientific Model Development.</p> <p>When using these files to run a model, most files should be placed inside a directory named INPUT/ that resides in the working directory where the model is being run. The following files should be at the top level in the working directory: data_table, diag_table, field_table, input.nml.</p> <p>For large files, a subset in time is provided for the first year of the simulation. This dataset does not include the ERA5 atmospheric data, which can be downloaded directly from https://doi.org/10.24381/cds.adbb2d47.</p> <p>Portions of the initial and boundary condition data were generated using E.U. Copernicus Marine Service Information:https://doi.org/10.48670/moi-00021. Refer to the manuscript for references to other data sources.</p> <p>Codes for generating regional MOM6 initial conditions, boundary conditions and other necessary model inputs as well as diagnostic scripts are maintained on the NOAA CEFI GitHub Repository: https://github.com/NOAA-GFDL/CEFI-regional-MOM6/. </p>
Ancillary files for "Graded transcendental functions: an application to four-point amplitudes with one off-shell leg"
<p>We provide ancillary files to "Graded transcendental functions: an application to four-point amplitudes with one off-shell leg".</p> <p>All attached files are in Mathematica format. See also appendix C of the manuscript for details on the ancillary files. </p> <ul> <li><strong>Families.zip: </strong><br>For each integral family, we provide in a single file <em>familyname.m</em> the list of propagators, a canonical basis and the corresponding differential equations, and a regularised boundary vector at the point (x, y) = (0, 0). <br>Files contain a list of Mathematica replacement rules in the format {prop["familyname"]-> {...}, basis["familyname"]-> {...}, boundaries["familyname"]-> {....}, DE["familyname"]-> {...}}. </li> <li><strong>BoundariesDemo.zip</strong>: An executable notebook implementing the fixing of boundary constants using the method for a two-loop example.</li> <li><strong>TridentFunctions.zip</strong>: For each relevant canonical integral and kinematic crossing listed in <em>basis_labels.m</em>, we provide a map to the trident functions in the form of a sparse rational array of size 13812 × 1282 in <em>mapping_positions.m</em> and <em>mapping_values.m</em>. We also provide the UT Laurent expansions of the trident functions in terms of 42258 iterated integrals and transcendental constants in <em>sb_labels.m</em>, again as a sparse array in <em>expansion_positions.m</em> and <em>expansion_values.m</em>.</li> <li><strong>FormFactor.zip</strong>: We provide the three-loop finite remainders R(3) and E(3) of the N = 4 sYM form factor in terms of Chen iterated integrals and MPLs.</li> <li><strong>Hjet.zip</strong>: The three independent helicity coefficients for the decay of a H boson to three partons at three loops are given in terms of iterated integrals and in a manifestly real MPL representation. In particular, we provide the part of the finite remainders containing new letters, with rational coefficients evaluated at x = 3/13, y = 11/17. </li> </ul>
Data for the manuscript "The impact of dealiasing biases on bird and insect data products of C-band weather radars and consequences for aeroecological applications" by Weisshaupt et al.
<p>Netcdf files of the analyses in the manuscript "The impact of dealiasing biases on bird and insect data products of C-band weather radars and consequences for aeroecological applications" by Weisshaupt et al. containing flight directions, flight speeds and animal densities in 200-m height layers between 0-1 km from four single PRF and one dual-PRF scans from 10 Finnish polarimetric C-band weather radars between 1-30 Sept 2022 and from the Kankaanpää weather radar between 10 Sept – 30 Oct 2023 and 10 April - 10 June 2024. Bird and insect echoes were identified by the classifier developed by Mäkinen, T., J. Ritvanen, S. Pulkkinen, N. Weisshaupt, and J. Koistinen, 2022: Bayesian Classification of Nonmeteorological Targets in Polarimetric Doppler Radar Measurements. <em>J. Atmos. Oceanic Technol.</em>, <strong>39</strong>, 1561–1578, <a href="https://doi.org/10.1175/JTECH-D-21-0177.1" target="_blank" rel="noopener">https://doi.org/10.1175/JTECH-D-21-0177.1</a>.</p> <p>File names indicate the PRF mode, processing mode (either untreated ("raw") or dealiased ("no_classif")), date and a 5-letter radar id.</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.