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1,705 results for “vector”
Eurex-LUNa Abisko Trials Lawnmower Vectoring
<p>Navigation data of the AUV DeepLeng during field trials in an ice-covered lake in Abisko, Sweden.</p> <p>For more information on this field trials: <a href="https://www.dfki.de/web/forschung/eurex-abisko">https://www.dfki.de/web/forschung/eurex-abisko</a></p> <p>This dataset is described in the paper</p> <p>M. Hildebrandt, T. Creutz, B. Wehbe, M. Wirtz and M. Zipper, "Under-Ice Field tests with an AUV in Abisko/Torneträsk," OCEANS 2022, Hampton Roads, Hampton Roads, VA, USA, 2022, pp. 1-7, doi: 10.1109/OCEANS47191.2022.9977094.</p> <p>For more details on how to use the data files, please refer to the Readme.md</p> <p>Contact: tom.creutz@dfki.de, bilal.wehbe@dfki.de</p> <p><br> Funded by BMWi (Kennziffer 50 NA 2002)</p>
Dataset of acoustic intensity vector measurements around an upscaled ear model
<p>A dataset of acoustic vector (particle velocity vector and scalar sound pressure) measurements of the sound field around an upscaled model of an ear. Data collected in July 2022 at the Aalto Acoustics Lab in Espoo, Finland.</p> <p>See the companion paper at AES for information about the contents of the dataset, measurement methodology, and example scripts.</p> <p>See the companion repository <a href="https://github.com/aaron-geldert/upscaled-ear-model-scripts">github.com/aaron-geldert/upscaled-ear-model-scripts</a> for example MATLAB scripts using the dataset.</p> <p>Correspondence should be directed to <a href="mailto:aarongeldert@gmail.com?subject=RE%20Big%20Ear%20Dataset%20(Zenodo)">Aaron Geldert (aarongeldert@gmail.com)</a>. <br> </p>
Data and code associated with the paper 'Mode-Specific Coupling of Nanoparticle-on-Mirror Cavities with Cylindrical Vector Beams'
<p>Data and code associated with the following paper: <a href="https://doi.org/10.1021/acs.nanolett.3c00561">V. Vento et al, Nano Lett. 2023</a></p> <p>A thorough explanation of the experiment performed is available there.</p> <p>The name of each sub-folder and file in <strong>Maps_data_code.zip</strong> indicates the corresponding figure number ("FIG #") and the type of content ("raw_data", "data", "plot", "analysis", "calculation", "simulation").</p> <p>The Raman maps data are analyzed through the script <em>Raman_maps_analysis.m</em>. The photoluminescence maps data in the supplementary information are analyzed through the script <em>PL_maps_analysis.m.</em> </p> <p>Used softwares: Matlab R2021a, Python 3.9, Comsol Multiphysics 5.6</p> <p> </p>
Dataset of Feasible, Edmonds' and Geographic Bi-vectors and Tri-vectors
<p>The dataset consists of two sets of files in JSON format. Each file consists of an array of elements and each element is presented by a vector (it can be a bi-vector in the case of the first set or a tri-vector in the latter case). This vector is followed by the Euler characteristic of surface and a set of Edmonds’ realizations, described as a concatenation of two incidence matrices. Such bi-matrix gives rise to the corresponding graph, its dual, as well as one-to-one correspondence between their edges.</p> <p>The first set consists of 7 files, each containing all possible bi-vectors with all Edmonds’ realizations in a form of bi-matrices for a fixed ell (ranging from 2 to 7).</p> <p>The bi-vectors are stored in files with the value of ell at the end:</p> <ul> <li>edmonds-bi-vector-realization-ell2.json</li> <li>edmonds-bi-vector-realization-ell3.json</li> <li>edmonds-bi-vector-realization-ell4.json</li> <li>edmonds-bi-vector-realization-ell5.json</li> <li>edmonds-bi-vector-realization-ell6.json</li> <li>edmonds-bi-vector-realization-ell7.json</li> </ul> <p>The second set consists of 9 files, each containing all possible tri-vectors with all Edmonds’ realizations in a form of bi-matrices for a fixed ell (ranging from 2 to 8). The last file (for ell 9, contains only one Edmond’s realization per vector (if existing) due to time complexity).</p> <p>The tri-vectors are stored in files with the ell mentioned at the end:</p> <ul> <li>edmonds-tri-vector-realization-ell2.json</li> <li>edmonds-tri-vector-realization-ell3.json</li> <li>edmonds-tri-vector-realization-ell4.json</li> <li>edmonds-tri-vector-realization-ell5.json</li> <li>edmonds-tri-vector-realization-ell6.json</li> <li>edmonds-tri-vector-realization-ell7.json</li> <li>edmonds-tri-vector-realization-ell8.json</li> <li>edmonds-tri-vector-realization-ell9.json</li> </ul> <p>A set of utilities show use cases:</p> <ul> <li> <p>Parsing functions with examples implemented in Sage:</p> </li> </ul> <p>edmonds_import.sage</p> <ul> <li> <p>Parsing functions with examples implemented in Java:</p> </li> </ul> <p>EdmondsReaderBivector.java</p> <p>EdmondsReader.java</p>
Detailed experimental results for VNS-based matheuristics for the two dimensional vector bin packing problem
<p>This dataset is a result of the research: Đorđe Stakić, Tatjana Davidović, Ana Anokić, Dragan Urošević "VNS-based matheuristics for the two dimensional vector bin packing problem", SYM-OP-IS, 2023.</p>
The upper bounds for the number of bins and the total number of variables before and after reducing for the two dimensional vector bin packing problem
<p>The upper bounds for the number of bins and the total number of variables before and after reducing for the two dimensional vector bin packing problem, This dataset is a result of the research: Đorđe Stakić, Tatjana Davidović, Ana Anokić, Dragan Urošević "VNS-based matheuristics for the two dimensional vector bin packing problem", SYM-OP-IS, 2023.</p>
All data for the preprint Population genetics of Glossina palpalis gambiensis in the sleeping sickness focus of Boffa (Guinea) before and after eight years of vector control: no effect of control despite a significant decrease of human exposure to the disease
<p>Data set for the paper titled "Population genetics of <em>Glossina palpalis gambiensis</em> in the sleeping sickness focus of Boffa (Guinea) before and after eight years of vector control: no effect of control despite a significant decrease of human exposure to the disease"</p>
Targeting AAV vectors to the CNS via de novo engineered capsid-receptor interactions
<p>Dataset for "Targeting AAV vectors to the CNS via <em>de novo</em> engineered capsid-receptor interactions."</p>
Susceptible and infectious states for both vector and host in a dynamic pathogen-vector-host system
<p>Deformed wing virus (DWV) is a resurgent insect pathogen of honey bees that is efficiently transmitted by vectors and through host social contact. Continual transmission of DWV between hosts and vectors is required to maintain the pathogen within the population, and this vector-host-pathogen system offers unique disease transmission dynamics for pathogen maintenance between vectors and a social host. In a series of experiments, we measured vector-vector, host-host and host-vector transmission routes and show how these maintain DWV in honey bee populations. We found co-infestations on shared hosts allowed for movement of DWV from mite to mite. Additionally, two social behaviors of the honey bee, trophallaxis and cannibalization of pupae, provide routes for horizontal transmission from bee to bee. Circulation of the virus solely amongst hosts through communicable modes provides a reservoir of DWV for naïve Varroa to acquire and subsequently vector the pathogen. Our findings illustrate the importance of community transmission between hosts and vector transmission. We use these results to highlight the key avenues used by DWV during maintenance and infection and point to similarities with a handful of other infectious diseases of zoonotic and medical importance.</p>
A Study of the Efficacy and Safety of Hematopoietic Stem Cells Transduced With Lenti-D Lentiviral Vector for the Treatment of Cerebral Adrenoleukodystrophy (CALD)
ClinicalTrials.gov study NCT01896102. IPD Sharing: YES. Countries: 6. Publications: 3.
Data from: Virus infection and host plant suitability affect feeding behaviors of cannabis aphid (Hemiptera: Aphididae), a newly described vector of potato virus Y
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Data from: Transformation of measurement uncertainties into low-dimensional feature vector space
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Data from: Double-strand break repair pathways differentially affect processing and transduction by dual AAV vectors
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Susceptible and infectious states for both vector and host in a dynamic pathogen-vector-host system
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Data from: Genetic reconstruction of a bullfrog invasion to elucidate vectors of introduction and secondary spread
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A plant virus differentially alters DNA methylation in two cryptic species of a hemipteran vector
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Improving distribution models of sparsely-documented disease vectors by incorporating information on related species via joint modeling
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Data from: Transinfection of Wolbachia wAlbB into Culex quinquefasciatus mosquitoes does not alter vector competence for Hawaiian avian malaria (Plasmodium relictum GRW4)
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Path-finding algorithm as a dispersal assessment method for invasive species with human-vectored long-distance dispersal event
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Climatic niche conservatism in a clade of disease vectors (Diptera: Phlebotominae)
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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.