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3,481 results for “data set”
Visualization of SARS-CoV-2 particles in naso/oropharyngeal swabs by thin section electron microscopy – data set 06
<p>We developed a sedimentation method using desktop ultracentrifugation (see description below) to visualize SARS-CoV-2 particles in suspensions from oro- and/or nasopharyngeal swabs by thin section electron microscopy. A detailed description of the methods and the data set is provided in the download container.</p> <p>Data set 06 comprises three stitched image montages recorded from an area of a thin section through the sediment obtained from a swab sample which was negative by quantitative PCR (control). Ciliated cells and extracellular material, such as vesicles and needle-like crystals, are visible, but no coronavirus particles.</p> <p>Related publication: Laue M, Hoffmann T, Michel J, Nitsche A. Visualization of SARS-CoV-2 particles in naso/oropharyngeal swabs by thin section electron microscopy. Virol J. 2023 Feb 6;20(1):21. doi: 10.1186/s12985-023-01981-9. PMID: 36747188; PMCID: PMC9901382.</p>
ArtTabGen Benchmarking Data Sets V1.0
<p>These datasets can be used to benchmark information extraction systems. To see an exemplary benchmarking script, please<br> refer to our PLIX publication. For more information regarding the generation of this dataset, please check out our<br> ArtTabGen Generation Code repository and our paper.</p>
Data set associated to simulations performed within the manuscript "Endosperm turgor pressure both promotes and restricts seed growth and size".
<p>This dataset contains the following files</p> <ul> <li>2F4-Col0-iku2-Fig.3f and Supp. Fig.9 <ul> <li>Slices of seeds from 3 to 9 Days post-anthesis (DPA) stained with calcofluor (channel 1) and whose unesterified pectins are labelled with the 2F4 antibody (channel 2)</li> <li>2 genotypes: Col0 and iku2</li> <li>3 independent experiments</li> </ul> </li> <li>JIM5-Col0-ap2-Fig. 4d and Supp Fig. 12b <ul> <li>Slices of seeds from 3 to 9 Days post-anthesis (DPA) stained with calcofluor (channel 1) and whose demethylesterified pectins are labelled with the JIM5 antibody (channel 2)</li> <li>2 genotypes: Col0 and ap2-6</li> <li>2 independent experiments</li> </ul> </li> <li>JIM5-Col0-iku2-Fig. 3h and Supp Fig. 10 <ul> <li>Slices of seeds from 3 to 9 Days post-anthesis (DPA) stained with calcofluor (channel 1) and whose demethylesterified pectins are labelled with the JIM5 antibody (channel 2)</li> <li>2 genotypes: Col0 and iku2</li> <li>3 independent experiments</li> </ul> </li> <li>LM19-Col0-ap2-Fig. 4b and Supp Fig. 12a <ul> <li>Slices of seeds from 3 to 9 Days post-anthesis (DPA) stained with calcofluor (channel 1) and whose demethylesterified pectins are labelled with the LM19 antibody (channel 2)</li> <li>2 genotypes: Col0 and ap2-6</li> <li>2 independent experiments</li> </ul> </li> <li>LM19-Col0-iku2-Fig. 3d and Supp Fig. 8 <ul> <li>Slices of seeds from 3 to 9 Days post-anthesis (DPA) stained with calcofluor (channel 1) and whose demethylesterified pectins are labelled with the LM19 antibody (channel 2)</li> <li>2 genotypes: Col0 and iku2</li> <li>3 independent experiments</li> </ul> </li> <li>pELA1-VENUS-Col0-iku2-Fig3c <ul> <li>Confocal stack of developing seeds expressing <em>pELA1::3X-VENUS-N7</em></li> <li>2 genotypes: Col0 and iku2</li> <li>1 independent experiments</li> </ul> </li> <li>pELA1-VENUS-Col0-iku2-Supp Fig. 6 <ul> <li>Confocal stack of developing seeds expressing <em>pELA1::3X-VENUS-N7</em></li> <li>2 genotypes: Col0 and iku2</li> <li>1 independent experiments</li> </ul> </li> <li>Seed-size-ap26-iku2-Fig.5e-Supp-Fig. 12c <ul> <li>Pictures of dry seeds</li> <li>4 genotypes: Col0, iku2, ap2-6 and iku2 ap2-6</li> <li>2 independent experiments</li> </ul> </li> <li>Wall-rupture-Col0-iku2-Fig3k <ul> <li>Confocal stack of developing seeds expressing <em>LTi6b-GFP </em>(First channel) and dyed with FM4-64 (second channel) imaged after a 40 µm indentation to break testa wall</li> <li>2 genotypes: Col0 and iku2</li> <li>2 replicates</li> </ul> </li> <li>Wall-rupture-Col0-iku2-Supp Fig. 11 <ul> <li>Confocal stack of developing seeds expressing <em>LTi6b-GFP </em>(First channel) and dyed with FM4-64 (second channel) imaged after a 30 µm or a 50µm indentation to break testa wall</li> <li>2 genotypes: Col0 and iku2</li> <li>2 replicates</li> </ul> </li> <li>181211-Col0-iku2-Timelapse-Seed-Size <ul> <li>Pictures of developing seeds from 0 (ovules) days post-anthesis (DPA) to 10 DPA</li> <li>2 genotypes: Col0 and iku2</li> </ul> </li> <li>190125-Col0-iku2-Timelapse-Seed-Size <ul> <li>Pictures of developing seeds from 0 (ovules) days post-anthesis (DPA) to 10 DPA (no 9DPA)</li> <li>2 genotypes: Col0 and iku2</li> </ul> </li> <li>190523-Col0-ede13-Timelapse-Seed-Size <ul> <li>Pictures of developing seeds from 0 (ovules) days post-anthesis (DPA) to 9DPA</li> <li>2 genotypes: Col0 and <em>ede1-3</em></li> </ul> </li> <li>200724-Col0-iku2-Timelapse-Seed-Size <ul> <li>Pictures of developing seeds from 0 (ovules) days post-anthesis (DPA) to 10DPA</li> <li>2 genotypes: Col0 and <em>iku2</em></li> </ul> </li> <li>200921-Col0-iku2-Timelapse-Seed-Size <ul> <li>Pictures of developing seeds from 0 (ovules) days post-anthesis (DPA) to 10DPA</li> <li>2 genotypes: Col0 and <em>iku2</em></li> </ul> </li> <li>201023-Col0-ede13-Timelapse-Seed-Size <ul> <li>Pictures of developing seeds from 0 (ovules) days post-anthesis (DPA) to 10DPA</li> <li>2 genotypes: Col0 and <em>ede1-3</em></li> </ul> </li> <li>210519-Col0-Timelapse-invitro-Sorbitol <ul> <li>Picture of developing WT seeds (Col-0) at 3, 6, 9 and 12DPA</li> <li>Fruits were grown <em>in planta </em>(uncut) or <em>in vitro</em> from 3DPA onwards</li> <li>Fruits growing <em>in vitro</em> were cultivated in ½ MS + 1% Sucrose + 0.1X PPM (Plant Preservative Medium) + 1X Gamborg Vitamins + 0 to 200mM Sorbitol</li> <li>Note that the file containing the pictures from this experiment was too large for Zenodo, the pictures were thus transformed into 8 bit black/white pictures, a 2x2 binning was applied, before a saving into tiff. The original pictures are available at: <a href="http://flower.ens-lyon.fr/">http://flower.ens-lyon.fr/</a></li> </ul> </li> <li>210709-Col0-Timelapse-invitro-Sorbitol <ul> <li>Picture of developing WT seeds (Col-0) at 3, 6, 9 and 12DPA</li> <li>Fruits were grown <em>in planta </em>(uncut) or <em>in vitro</em> from 3DPA onwards</li> <li>Fruits growing <em>in vitro</em> were cultivated in ½ MS + 1% Sucrose + 0.1X PPM (Plant Preservative Medium) + 1X Gamborg Vitamins + 0 to 200mM Sorbitol</li> <li>Note that the file containing the pictures from this experiment was too large for Zenodo, the pictures were thus transformed into 8 bit black/white pictures, a 2x2 binning was applied, before a saving into tiff. The original pictures are available at: <a href="http://flower.ens-lyon.fr/">http://flower.ens-lyon.fr/</a></li> </ul> </li> <li>data.zip file: <ul> <li>Measurements of seed growth tracking experiments performed on WT plants as well as iku2 and ede1-3 mutants.</li> <li>Measurements of endosperm pressure performed on WT plants and iku2 mutants.</li> <li>Simulation results from a parameter space exploration of the system of ODEs we studied within the scope of the work described in the manuscript.</li> </ul> </li> </ul>
Large data set for Ng, Poon, et al. 2017
<p>Accompanies a manuscript on the presence of the aristolochic acid mutational signature in liver cancers from Taiwan and other countries. Contains:</p> <p>1. Output from ASCAT (copy number alterations and aneuploidy)</p> <p>2. Output from GISTIC (significantly amplified and deleted genomic regions)</p> <p>3. IGV screenshots used in estimating false discovery rate for somatic single base substitutions and small insertions and deletions.</p>
0.48 Angstrom 3,5-dinitrobenzoic acid (3,5-DNBA) C2/c polymorph single crystal X-ray diffraction data set recorded at Diamond Light Source I19-1
<p>Data set from 3,5-dinitrobenzoic acid (3,5-DNBA) C2/c polymorph recorded during in house research (DLS proposal: NR18193). Each run is saved as a single compressed tar file for convenience, runs 1, 2, 3 correspond to 3 x 170 degree omega scans at phi 0, 120, 240 degrees with 2-theta of 30 degrees, run 4 phi scan at 2-theta 0, runs 5-8 omega scans at 2-theta 55 degrees, giving data to 0.48A.</p> <p> </p> <p>Now including scale factor graph & report from processing</p>
Data set for the paper "Predicting Relevance of Change Recommendations"
<p>Data set for the paper Predicting Relevance of Change Recommendations by Thomas Rolfsnes, Leon Moonen, and David Binkley, In International Conference on Automated Software Engineering (ASE), pp. 694–705. 2017, IEEE.</p> <p>Please cite this work by referring to the corresponding conference publication (a preprint is included in this package).</p> <p>Abstract: Software change recommendation seeks to suggest artifacts (e.g., files or methods) that are related to changes made by a developer, and thus identifies possible omissions or next steps. While one obvious challenge for recommender systems is to produce accurate recommendations, a complimentary challenge is to rank recommendations based on their relevance. In this paper, we address this challenge for recommendation systems that are based on evolutionary coupling. Such systems use targeted association-rule mining to identify relevant patterns in a software system's change history. Traditionally, this process involves ranking artifacts using interestingness measures such as confidence and support. However, these measures often fall short when used to assess recommendation relevance. We propose the use of random forest classification models to assess recommendation relevance. This approach improves on past use of various interestingness measures by learning from previous change recommendations. We empirically evaluate our approach on fourteen open source systems and two systems from our industry partners. Furthermore, we consider complimenting two mining algorithms: CO-CHANGE and TARMAQ. The results find that random forest classification significantly outperforms previous approaches, receives lower Brier scores, and has superior trade-off between precision and recall. The results are consistent across software system and mining algorithm.</p>
Minimal data set about Cipro intercalation on NaFh
<p>The Excel file contains 8 sheets with all minimal data set. It includes the optimization of chemical-physical parameters and the data corresponding to solid samples characterization.</p>
Nsense v1.0 Data Set II
<p>This data set comprises experiment carried out considering Nine Android devices, each named Copelabs1, 2, 3, 4, 5, 6, 7, 8 and 12, respectively. These devices carried by people sharing the same affiliation during their daily routines (commuting between home and office, going to leisure activities, attending meetings in the office). All the data was collected each and every one minute. We set up experiments making use of Samsung Galaxy S3 devices. For each experiment, there is the following set of data files: * SocialProximity.dat has three columns: Timestamp, DeviceName, Encounter Duration, Average Encounter Duration, Social Strength (Per hour) and Social Strength(Per minute) towards * DistanceOutput.dat has three columns: Timestamp, DeviceName, and Distance towards * Microphone.dat has two columns: Timestamp, and Sound level(QUIET, NORMAL, ALERT, and NOISY) * PhysicalActivity.dat has two columns: Timestamp, and Activity as STATIONARY, WALKING, and RUNNING The experiment was conducted for the period of 12 days from 12th September to 23rd September 2016 . All devices were carried by users sharing affiliation and following their individual daily routines.</p>
Comparing mail-in self-collected specimens sent via United States Postal Service versus clinic-collected specimens for the detection of Chlamydia trachomatis and Neisseria gonorrhoeae in extra-genital sites data set
<p>This data set was used to evaluate the concordance between clinic-collected extra-genital specimens and self-collected mailed-in extra-genital specimens among participants seeking sexually transmitted infection testing at a free clinic in Hollywood, CA. The newest version of the file reflects sample adequacy control (SAC) cycle threshold values for each participant.</p>
FDHMF: Experimental Loop Recirculation Data Set - 250G
<p>Data set containing experimental results on the propagation of frequency-domain hybrid modulation formats (FDHMF) optical signals over pure silica core fiber (PSCF) inside a recirculating loop. The net bit-rate is fixed at 250G.</p>
Data set: methanol formation via oxygen insertion chemistry in ices
<p>This data set corresponds to the experiments appearing in the article "Methanol Formation via Oxygen Insertion Chemistry in Ices" (Bergner, Oberg, & Rajappan, The Astrophysical Journal, 2017, 845:29). Please refer to the article for experimental details & methods.</p> <p>The data set consists of infrared spectra from 600-4000 wavenumbers. Each file contains the spectra taken for a single experiment. The first column holds the spectrum wavenumber values, and all subsequent columns hold the IR absorbance values for spectra taken during ice irradiation. The first row lists column headings, including the time increments (in minutes) of the irradiation spectra. </p> <p>File names are formatted: "IR_N.txt" where N corresponds to the Experiment # listed in Table 1 of the corresponding article. All details about the experiment (irradiation temperature, ice composition) can be retrieved from Table 1.</p>
Data Set for the Journal Article "SCINE - Software for Chemical Interaction Networks"
<p>This data archive contains all data and software described and used in the following publication:</p> <p>Thomas Weymuth, Jan P. Unsleber, Paul L. Türtscher, Miguel Steiner, Jan-Grimo Sobez, Charlotte H.<br>Müller, Maximilian Mörchen, Veronika Klasovita, Stephanie A. Grimmel, Marco Eckhoff, Katja-Sophia<br>Csizi, Francesco Bosia, Moritz Bensberg, Markus Reiher, "SCINE --- Software for Chemical Interaction<br>Networks", in preparation.</p> <p>The directory structure is as follows:</p> <ul> <li>software: contains all software used for the example exploration <ul> <li>requirements.txt: lists all Python packages needed to create the virtual environment with which the exploration has been carried out; the virtual environment was created with Python 3.6.8.</li> <li>start.py: script to initialize the database with the reactants</li> <li>step_1.py: script to create the first set of reaction trials; after having set up the trials, execute the script "start.py" with the option "continue"</li> <li>step_2.py: script to create the second set of reaction trials; after having set up the trials, execute the script "start.py" with the option "continue"</li> <li>puffin_1.3.0.sif: Singularity image containing a full Puffin instance (version 1.3.0) to execute all calculations of the exploration</li> <li>submit_container.sh: script to submit the Puffin image to the queueing system</li> </ul> </li> <li>data: contains a complete dump of the database created during the example exploration; additionally, this directory contains a script called "import.sh" which can be used to reimport the data into a MongoDB instance</li> </ul>
Data set for spectral and FT-ICR-MS analysis of dissolved organic matter in sediments of the New Britain Trench axis station
<p> </p> <p>数据集包括原始数据和简单处理所需的数据、图表和文章。</p> <p> </p> <p>表格包含样品数量、收集深度、样品名称以及相应光谱和 FT-ICR-MS 数据的名称。</p> <p> </p> <p>例如,光谱数据包括荧光相对强度、荧光指数,而 FT-ICR-MS 光谱数据包括化合物类型相对强度以及化学式、元素比、等效双键数 (DBE) 和每个样品的芳香指数 (AImod)。</p> <p> </p>
Data set for the figures in the manuscript "Real-Time Identification of Aerosol-Phase Carboxylic Acid Production Using Extractive Electrospray Ionization Mass Spectrometry"
Open the record for dataset details and reuse information.
ScintiPi3 data sets for "First observations of severe scintillation over low-to-mid latitudes driven by quiet-time extreme equatorial plasma bubbles: conjugate measurements enabled by citizen science initiatives"
<p>ScintPi 3.0 data sets for "First observations of severe scintillation over low-to-mid latitudes driven by quiet-time extreme equatorial plasma bubbles: conjugate measurements enabled by citizen science initiatives" by Sousasantos et al. (2024).</p>
Multimodal data set for the investigation of the early stage of plasticity in a polycrystalline titanium sample
<p>This dataset is the result of several experiments to study the early stage of plasticity in a polycrystalline sample of a commercially pure alpha phase grade 2 titanium (CP-Ti family). The study aimed to achieve three critical goals: first, the acquisition of a 3D representation of the microstructure; second, the conduction of in situ measurements capturing grain-scale plasticity dynamics during a controlled tensile test; and third, a rigorous comparison of these experimental observations against the predictions derived from a microstructure-sensitive crystal plasticity simulation. This simulation was conducted on a digital twin of the titanium sample, aiming to assess the predictive accuracy of the model at the local scale. The data set was assembled from the different sources using the Pymicro package. </p>
Supplementary File 8; The full data set derived from formal quantitative surveys of land cover types and activities of humans, livestock and wildlife (Section 2.3) that were used for the analyses described in sections 2.4, 2.5 and 2.7
Open the record for dataset details and reuse information.
Null effect of perceived drum pattern complexity on the experience of groove (data set)
Open the record for dataset details and reuse information.
VCF for neutral data set and potential connectivity matrices of Harpagifer antarcticus, along the Western Antarctic Peninsula
<p>Connectivity is a fundamental process of population dynamics in marine ecosystems. In the last decade, with the emergence of new methods, combining different approaches to understand the patterns of connectivity among populations and their regulation has become increasingly feasible. The Western Antarctic Peninsula (WAP) is characterized by complex oceanographic dynamics, where local conditions could act as barriers to population connectivity. Here, the notothenioid fish <em>Harpagifer antarcticus</em>, a demersal species with a complex life cycle (adults with poor swim capabilities and pelagic larvae), was used to assess connectivity along the WAP by combining biophysical modeling and population genomics methods. Both approaches showed congruent patterns. Areas of larvae retention and low potential connectivity, observed in the biophysical model output, coincide with four genetic groups within the WAP: (1) South Shetland Islands, (2) Bransfield Strait, (3) the central, and (4) the southern area of WAP (Marguerite Bay). These genetic groups exhibited limited gene flow between them, consistent with local oceanographic conditions, which would represent barriers to larval dispersal. The joint effect of geographic distance and larval dispersal by ocean currents, had a greater influence on the observed population structure, than each variable evaluated separately. The combined effect of geographic distance and a complex oceanographic dynamic would be generating limited levels of population connectivity in the fish <em>H. antarcticus</em>along the WAP. Based on this population connectivity estimations, priority areas for conservation were discussed, considering the Marine Protected Area proposed for this threatened region of the Southern Ocean.</p>
Smart Cable Air (SCA) and Smart Cable Water (SCW) public data sets, april 2024
<p>These datasets are supporting material for the publication<br>"An ASIC-based system-in-package MEMS gas sensor with impedance spectroscopy readout and AI-enabled identification capabilities"<br>by CNR-IMM Bologna, Univerisity of Pisa and Sensichips.</p> <p>These are some data sets as acquired to date using the Smart Cable Air and Smart Cable Water devices, for public use by data scientists and AI developers.</p> <p>SCA.zip contains datasets for the "Smart Cable Air" sensor: <a href="https://sensichips.com/air-sensor/">https://sensichips.com/air-sensor/</a></p> <p>SCW.zip contains datasets for the "Smart Cable Water" sensor: <a href="https://sensichips.com/water-sensor/">https://sensichips.com/water-sensor/</a></p> <p>The contents are described in the readme files contained in the subdirectories.</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.