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2,983 results for “raw data”
Raw microclimate data from plots at burned areas from the 2020 Holiday Farm fire in the Andrews Experimental Forest and Hagan Block, 2022-2024
This dataset includes a suite of microclimate sensor data from areas burned by the 2020 Holiday Farm fire within the McKenzie River basin. A total of 42 microclimate sensor suites were installed in July and August of 2022 distributed across RS01, RS08, RS15, WS02, WS09, WS01, HGBK. All sensor locations are within the Holiday Farm Fire footprint and within Permanent Sample Plots (PSPs). An additional sensor was placed within the Primary meteorological station (PRIMET) of the HJ Andrews Experimental Forest for comparison and calibration between open-air measurements. Sites are stratified across three treatment variables including 1) fire severity: high or low; 2) management: managed or unmanaged; 3) water balance: moister or drier topographic positions. This resulted in eight treatment blocks, each with 5 sensor suite replicates. Each microclimate site includes a suite of measurements: Hobo temperature and relative humidity sensor installed at 1.5m within a gill shield (recording at 30 minute interval), one TOMST TMS-4 temperature and soil moisture sensor was located within 1 m of plot center (recording at 15 minute interval). The TOMST sensors include air temperature sensors at 15cm, 2cm, and soil temperature at -6cm in soil near-surface. Soil moisture is measured across the ~10cm near surface zone.
Lithic raw data for Sheppard's (1987) thesis on the Capsian
<div> <div> <div> <p>This is a collection of six lithic raw data spreadsheets created in the course of Peter Sheppard’s doctoral project on the prehistoric tradition of Northwest Africa known as the Capsian. Sheppard’s project investigated technological and stylistic variation in Capsian lithics. The spreadsheets provided here contain about 507,000 observations collected on some 20,100 artefacts (blanks, cores, burins, backed bladelets, and geometric microliths) from 16 sites. We recovered these data uncorrupted, byte-for-byte from a 40-year-old tape. In the provided PDF document, we restate with additional clarifications the data definitions from Sheppard (1987). We also detail the steps we took to transform the files found on the tape into usable data spreadsheets.</p> </div> </div> </div>
Silica Nanoparticles Enhance Disease Resistance in Arabidopsis Plants - RAW DATA
<p>These datasets are used to produce the figures/graphs published in our article</p> <p><strong>Silica Nanoparticles Enhance Disease Resistance in <em>Arabidopsis</em> Plants</strong></p> <p>in <em>Nat. Nanotechnol.</em> (2020). <a href="https://doi.org/10.1038/s41565-020-00812-0">https://doi.org/10.1038/s41565-020-00812-0</a></p> <p> </p><p><strong>Correspondence: </strong></p> <p></p> <p>fabienne.schwab@alumni.ethz.ch, Tel: +41 78 736 00 19;</p> <p>m.shetehy@uky.edu, Tel. +41 76 455 56 02</p> <p>Further raw data related to qPCR and microbiology are available upon reasonable request from M.H. El‑Shetehy.</p> <p>Further raw data related to the nanoparticles and plant microscopy are available upon reasonable request by F. Schwab.</p> <p> </p> <p><strong>Abstract</strong></p> <p>In plants, pathogen attack can induce an immune response known as systemic acquired resistance (SAR) that protects against a broad spectrum of pathogens. In the search for safer agrochemicals, silica nanoparticles (SiO<sub>2</sub>‑NPs, food additive E551) have recently been proposed as a new tool. However, initial results are controversial, and the molecular mechanisms of SiO<sub>2</sub>‑NP-induced disease resistance are unknown. Here, we show that SiO<sub>2</sub>‑NPs, as well as soluble orthosilicic acid (Si(OH)<sub>4</sub>), can induce SAR in a dose-dependent manner, that involves the defence hormone salicylic acid. Nanoparticle uptake and action occurred exclusively through stomata (leaf pores facilitating gas exchange) and involved extracellular adsorption in leaf air spaces of the spongy mesophyll. In contrast to treatment with SiO<sub>2</sub>‑NPs, induction of SAR by Si(OH)<sub>4 </sub>was problematic, since high concentrations caused stress. We conclude that SiO<sub>2</sub>‑NPs have the potential to serve as an inexpensive, highly efficient, safe, and sustainable alternative for plant disease protection.</p>
Raw data for "Development and characterization of a non-human primate model of disseminated synucleinopathy"
<p><span>In this study, the performance and biodistribution of the retrogradely-spreading AAV9-SynA53T vector was evaluated in the NHP brain. Conducted intraparenchymal deliveries of viral suspensions in the left putamen gave rise to a disseminated synucleinopathy in a circuit-specific basis.</span></p>
DNA Origami Raw AFM Data - NanoLocz: Image analysis platform for AFM, high-speed AFM and localization AFM
<p>The data file is in the original ARIS data format as captured on a Cypher VRS1250 AFM (Oxford Instruments)<br><br><br></p>
Data from Phenocam (PHE) measurements at Freiburg–Chemiehochhaus (FRCHEM) from 2023-07-04 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Raw data for the submitted manuscript entitled "Mapping and Disposal of Irrigation Pipes for a Sustainable Management of Agricultural Plastic Waste", authors Ileana Blanco, Giuliano Vox, Fabiana Convertino, and Evelia Schettini
<p><span>The file regards the evaluation of plastic indexes and agricultural plastic waste quantities in Apulia region due to the use of irrigation pipes. The data is used to identify the critical areas for plastic waste production due to irrigation pipes.</span></p>
Raw data for the submitted manuscript entitled "Prospective Scenarios for Addressing the Agricultural Plastic Waste Issue: Results of a Territorial Analysis"
<p><span>Agricultural activities have been positively affected by the use of plastic products, but this has resulted in the production of plastic waste and led to an increase in environmental pollution. </span><span>This file concerns plastic waste indices to different crop types and plastic products allowed quantifying and georeferencing actual plastic waste production. Two improved scenarios were considered, the first consisted of extending the lifespan of some plastics, and the second entailed the introduction of some biodegradable alternatives. </span></p>
Raw data mzXML and MATLAB code for Variation in chemical composition of dissolved organic matter during the winter to spring transition in the northern Barents Sea
<p>MATLAB code and raw data mzXML for Variation in chemical composition of dissolved organic matter during the winter to spring transition in the northern Barents Sea.</p> <p>Seawater samples were collected during three distinct periods: early winter (December 2019), late winter (March 2021), and spring (May 2021). The sampling transect extended from the northern Barents Sea into the Nansen Basin (76°N – 83°N) as part of <em>The Nansen Legacy</em> project (Research Council of Norway, RCN #276730). The molecular composition of dissolved organic matter (DOM) was analyzed using an Orbitrap mass spectrometer.</p>
In-situ grazing-incidence X-ray diffraction data of the crystallization process of organic-inorganic methylammonium lead bromide perovskite (MAPbBr3) via employing an isopropanol antisolvent. Raw Data
<p>The dataset contains 400 diffraction images from a 40 second in-situ grazing-incidence wide-angle X-ray scattering measurement of the crystallization process of organic-inorganic methylammonium lead bromide perovskite (MAPbBr3) on a glass substrate. The crystallization is initiated via employing an isopropanol antisolvent during the spin-coating of the perovskite precursor solution. 40 µL of MAPbBr3 solution (4:1 DMF/DMSO solvent mixture) was applied on plasma-cleaned glass substrate in a chamber with kapton windows. The two-phase spin-coating regime included 10 seconds at 1000 rpm followed by 30 seconds at 2000 rpm, 200 µL of antisolvent was dispensed at t = 30 s.</p> <p> </p> <p> </p> <p>The data was acquired at the P08 Beamline at PETRA III (DESY Hamburg). Acquisition parameters:</p> <p> </p> <ul> <li> <p>X-ray wavelength: 0.6888 nm</p> </li> <li> <p>Sample detector distance: 809 mm</p> </li> <li> <p>Incidence angle: 0.5 deg.</p> </li> <li> <p>Detector model: XRD 1621 CN3 EHS</p> </li> <li> <p>Acquisition rate : 10 frames per second (10 Hz)</p> </li> <li> <p>Direct beam position (pixels): 545, 222</p> </li> </ul>
Data from Phenocam (PHE) measurements at Paris – Romainville (PAROMA) from 2023-09-26 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Paris – SIRTA (PASIRT) from 2023-04-26 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Heraklion – FORTH (HEFORT) from 2023-03-24 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Berlin-Technical University of Berlin (BETUCC) from 2023-06-01 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Berlin – Rothenburgstrasse (BEROTH) from 2023-01-01 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Raw Data on Extracellular Particles in 613 Human and 163 Canine Diluted Plasma and Blood Samples Assessed by Interferometric Light Microscopy
<p><span>Extracellular nanoparticles (EPs) are cellular fragments. After being released in cell exterior, they become mediators of the cell-cell interaction. Their characterization in bodily fluids may reflect the clinical status of the organism. Here we present data on the number density <em>n</em> and hydrodynamic diameter <em>D</em><sub>h </sub>of EPs assessed directly in diluted plasma and blood by using a recently developed technique, Interferometric Light Microscopy (Romolo et al., 2022). The data are presented in the attached Table. </span></p> <p><span>We collected 613 blood and plasma samples from human patients with Inflammatory Bowel Disease (IBD) taken into tubes with trisodium citrate and ethylenediaminetetraacetic acid (EDTA) anticoagulants and 163 blood and plasma samples from canine patients with Brachycephalic Obstructive Airway Syndrome (BOAS). </span><span>The human study was conducted in accordance with the Declaration of Helsinki, and approved by the National Medical Ethics Committee of the Republic of Slovenia (0120-271/2022/4; KME 27 July 2022). All procedures in the animal study complied with the relevant Slovenian government regulations (Animal Protection Act, Official Gazette of the Republic of Slovenia, No. 43/2007). The animal study was approved by the Animals in Experiments Welfare Commission of the Veterinary Faculty, University of Ljubljana, approval number 18-3/2022-1. </span><span>Information regarding sample preparation is documented in the MIBlood-EV reports.</span></p> <div> <div> <div><span><a name="_msocom_1"></a></span></div> </div> </div>
[Dataset] Does Volunteer Engagement Pay Off? An Analysis of User Participation in Online Citizen Science Projects - Raw Data
<p><strong>Explanation/Overview:</strong></p> <p>Corresponding raw data for the analyses described in D3.3 (can be found here), which are the result of our research that culminated into the publication "Does Volunteer Engagement Pay Off? An Analysis of User Participation in Online Citizen Science Projects", a conference paper for the conference CollabTech 2022: <a href="https://link.springer.com/book/10.1007/978-3-031-20218-6">Collaboration Technologies and Social Computing</a> and published as part of the <a href="https://link.springer.com/bookseries/558">Lecture Notes in Computer Science</a> book series (LNCS,volume 13632) <a href="https://link.springer.com/chapter/10.1007/978-3-031-20218-6_5">here</a>. Usernames have been anonymised.</p> <p>The raw data is in the <code>.json</code> format and can be read by most languages/tools. It is recommended to import the data into a MongoDB to work with it.</p> <p><strong>Purpose:</strong></p> <p>The purpose of this dataset is to provide the basis for possible further examinations, involving additional (not yet analysed) features such as the content of the comments etc. and also new ways of extracting networks.</p> <p><strong>Relatedness:</strong></p> <p>The data of the different projects was derived from the forums of 7 Zooniverse projects based on similar discussion board features. The projects are: 'Galaxy Zoo', 'Gravity Spy', 'Seabirdwatch', 'Snapshot Wisconsin', 'Wildwatch Kenya', 'Galaxy Nurseries', 'Penguin Watch'.</p> <p><strong>Content:</strong></p> <p>The dataset contains three files:</p> <ul> <li><code>Comments.json</code> <ul> <li>contains the basic data representation with multiple fields (e.g., <code>time_created</code>, <code>user_login</code>). Each data field represents a comment.</li> </ul> </li> <li><code>Discussions.json</code> <ul> <li><code></code>contains all discussions. Each data field is a discussion, with multiple fields (e.g., <code>comments_count</code>, <code>user_login</code>)</li> </ul> </li> <li><code>Projects.json</code> <ul> <li><code></code>contains all projects. Each data field is a project, with multiple fields (e.g., <code>project_id</code>, <code>description</code>)</li> </ul> </li> </ul> <p><strong>Grouping:</strong></p> <p>The projects (and thus the corresponding discussions and comments) were collected on the basis of common forum features such as the discussion boards.</p>
Raw Particle Number Size-Distribution Data of twin-DMPS equipped with two CPCs for nanoparticle detection for SMEAR II station, Hyytiälä, Finland, Spring 2017
<p>Raw size-Distribution data from twin-DMPS system (Aalto et al., 2001), where the nano-DMA (measuring up to 40 nm, short Hauke type DMA) is quipped with two detectors:<br> a TSI 3776 and a modified Airmodus A20 (Kangasluoma et al., 2015)</p> <p>Data acquired during in March-May 2017 at the SMEAR II station in Hyytiälä, Finland.<br> Data associated with the publication Stolzenburg, Laurila et al. (2023), Atmos. Meas. Techn., "Improved counting statistics of an ultrafine differential mobility particle size spectrometer system"</p> <p>Files DMYYDDMM_A20.Dat contain the raw DMPS data, with YYMMDD indicating the day of the measurement.<br> Data are provided alternating between data acquired with the nano-DMA and with the long-DMA, on a scan by scan basis.<br> First line of each scan cycle (for both DMAs) always indicates the start and end times of the voltage scan.<br> Second line gives the parameters related to the DMPS as given below:<br> (sheath flow in [l per min], aerosol flow in [l per min], DMA inner electrode diameter in [m], DMA outer electrode diameter in [m], DMA classification length in [m], other parameters)<br> Following lines give<br> (for long-DMA): set voltage at DMA [in V], concentration measured by TSI3772 in [per cm3]<br> (for nano_DMA): et voltage at DMA [in V], concentration measured by TSI 3776 in [per cm3], concentration measured by mod. Airmodus A20 in [per cm3]</p> <p>File dmps_data_format_specifier.text gives a conversion from voltage to diameter and indicates the measurement time at each voltage during the stepping of the DMPS.<br> Needs to be used to convert measured concentrations in counts per set-interval.</p> <p>Files GR_J_overview.xlsx gives size-distribution derived quantities during that campaign.<br> Header defines Date, Growth Rate and Formation Rate measured at different sizes [in nm] and by the two different CPCs connected to the nano-DMA.<br> Growth rates in [nm per h], formation rate in [per cm3 per s].</p> <p>Other data related to the campaign can be obtained from the corresponding author upon reasonable request.<br> juha.kangasluoma@helsinki.fi</p> <p>References:</p> <p>Stolzenburg, Laurila et al. "Improved counting statistics of an ultrafine differential mobility particle size spectrometer system",<br> Atmos. Meas. Techn., in press, 2023</p> <p>Aalto et al., "Physical characterization of aerosol particles during nucleation events",<br> Tellus B, vol. 53, pp. 344-358, 2001</p> <p>Kangasluoma et al., "Sub-3 nm Particle Detection with Commercial TSI 3772 and Airmodus A20 Fine Condensation Particle Counters",<br> Aerosol Sci. Techn., vol. 49, pp. 674-681, 2015</p>
In vivo rat brain for Ultrasound Localization Microscopy: raw and beamformed data.
<p><strong>Datasets provided for Open Platform for Ultrasound Localization Microscopy: Performance Assessment of Localization Algorithms.</strong></p> <p><strong>Abstract:</strong></p> <p>Ultrasound Localization Microscopy (<strong>ULM</strong>) is an ultrasound imaging technique that relies on the acoustic response of sub-wavelength ultrasound scatterers to map the microcirculation with an order of magnitude increase in resolution. Initially demonstrated <em>in vitro</em>, this technique has matured and sees implementation<em> in vivo</em> for vascular imaging of organs, and tumors in both animal models and humans. The performance of the localization algorithm greatly defines the quality of vascular mapping. We compiled and implemented a collection of ultrasound localization algorithms and devised three datasets<em> in silico</em> and<em> in vivo</em> to compare their performance through 18 metrics. We also present two novel algorithms designed to increase speed and performance. By openly providing a complete package to perform ULM with the algorithms, the datasets used, and the metrics, we aim to give researchers a tool to identify the optimal localization algorithm for their usage, benchmark their software and enhance the overall image quality in the field while uncovering its limits.</p> <p>This article provides all materials and post-processing scripts and functions.</p> <p><strong>Methods:</strong></p> <p>200.000 ultrasound images have been acquired <em>in vivo </em>on a rat brain with skull removal at 1000 Hz with a 15 MHz linear probe.</p> <p>This dataset contains raw radiofrequency data (<strong>RF</strong>) and beamformed images (<strong>IQ</strong>) of the brain vascularization with flowing microbubbles (ultrasound contrast agent).</p> <p><strong>Article to be cited:</strong> Heiles, Chavignon, Hingot, Lopez, Teston and Couture.<br> <a href="http://doi.org/10.1038/s41551-021-00824-8"><em>Performance benchmarking of microbubble-localization algorithms for ultrasound localization microscopy</em>, Nature Biomedical Engineering, 2022, (doi.org/10.1038/s41551-021-00824-8)</a>.</p> <p><strong>Related processing scripts and codes:</strong> <a href="https://github.com/AChavignon/PALA">github.com/AChavignon/PALA</a></p> <p><strong>Related datasets:</strong> <a href="https://doi.org/10.5281/zenodo.4343435">doi.org/10.5281/zenodo.4343435</a></p> <p><strong>Acknowledgments:</strong></p> <p>We thank Cyrille Orset (INSERM UMR-S U1237, Physiopathology and Imaging of Neurological Disorders, GIP Cyceron, BB@C, Caen, France) for animals’ preparation and perfusion of contrast agent and the biomedical imaging platform CYCERON (UMS 3408 Unicaen/CNRS, Caen, France).</p>
Raw data to accompany the manuscript 'Data for Engineering Lipid Metabolism of Chinese Hamster Ovary (CHO) Cells for Enhanced Recombinant Protein Production' published in the Journal Data in Brief
<p>This repository consists of the raw western blot, microscopy and mass spectrometry data to accompany the manuscript 'Data for Engineering Lipid Metabolism of Chinese Hamster Ovary (CHO) Cells for Enhanced Recombinant Protein Production' published in the Journal Data in Brief and associated with the article '<a href="https://www.ncbi.nlm.nih.gov/pubmed/31805379">Engineering of Chinese hamster ovary cell lipid metabolism results in an expanded ER and enhanced recombinant biotherapeutic protein production</a>' published in the journal Metabolic Engineering (see DOI: 10.1016/j.ymben.2019.11.007). </p> <p>The western blot raw file is associated with Figure 1a and 1b of the Data in Brief manuscript.</p> <p>The confocal microscopy raw image files (x3) are associated with Figure 1c of the Data in Brief manuscript.</p> <p>The mass spectrometry files are the raw data that refers to the samples presented in Figure 5 of the Data in Brief manuscript. Files are labelled as in the Data in Brief and Metabolic Engineering manuscripts. The file name structures is as follows;</p> <p>CHO-Controlpoolai</p> <p>Where 'a' represents replicate 'a' of three biological replicates and 'i' refers to mass spectrometry technical analysis 1 of 3 technical analyses of each replicate (thus for each cell pool or line there are three biological replicates that are each analysed in triplicate such that there are 9 raw mass spectrometry files for each cell pool or line).</p> <p>All the mass spectrometry files are found in the compressed (zip) file named mass_spectrometry_raw_files_archive.zip</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.