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294 results for “ISS”
ISS Mouse brain embryo - MIPPED images , all rounds all channels
<p>Repository containing the stitched, mipped and aligned images of all the cycles and channels used in the Mouse embryo ISS characterization from La Manno et al 2020 The repository contains:</p> <ul> <li>Stitched aligned and mipped images of all round and cycles for different samples (2A,2D, 6B,10B)</li> <li>A codebook with the code of every expected gene detecoded is included</li> <li>A preliminary decoding of the 4 samples included in the folder "decoded_spots"</li> <li>Information about channel order in a .txt</li> </ul>
Lightning Potential Index Using ICON Simulation at the km-scale over the Third Pole Region: ISS-LIS events and ICON-CLM simulated LPI
<p>This dataset contains records of lightning events recorded by the International Space Station (ISS) Lightning Imaging Sensor (LIS) from October 2019 to September 2022 in the Third Pole region. Furthermore, the Icosahedral Nonhydrostatic Weather and Climate Model in Climate Limited-Area Mode (ICON-CLM) was utilized to simulate the hourly Lightning Potential Index (LPI) over the Third Pole region for the same duration. The aforementioned dataset was utilized in the creation of the research article titled "Modeling Lightning Activity in the Third Pole Region: Performance of a km-scale ICON-CLM Simulation" authored by Prashant Singh and Bodo Ahrens. The paper has been submitted to the journal Atmosphere. In CORDEX-FPS-CPTP contribution no. 17 (GUF), you can find more data from ICON-CLM, such as precipitation, CAPE, wind vectors, and more.</p>
Oregon Wolfe Barley (Hordeum vulgare) Informative & Spectacular Subset (ISS) vegetative stage growth data
<p>Oregon Wolfe Barley Informative & Spectacular Subset (ISS) was raised at the Ag Alumni Seed Phenotyping Facility (AAPF) at Purdue University (West Lafayette, Indiana, USA) for 42 days. There were 18 genotypes, with two replicates for each genotype (total plants: 36). AAPF is a controlled environment high-throughput phenotyping facility with automated imaging and irrigation systems. A virtual tour of AAPF can be found at <a href="https://ag.purdue.edu/aapf/virtual-tour.html">https://ag.purdue.edu/aapf/virtual-tour.html</a>.</p> <p>Seeds were sown in a 6 L pot with 2.8 L of Profile Porous Ceramic Greens Grade and Berger BM6 each with 10g of Osmocote. Five hundred ml of Turface was laid on top of each pot to avoid effect of algae for RGB data derivation. The growth temperature in the chamber was 72/68 degrees Fahrenheit day/night. Relative humidity was set at 60%. Lighting was 16 h day/8 h night.</p> <p>Plants were imaged with RGB camera from one top and 12 side views three times a week, ranging between 10 days from planting (equivalent to sowing, Dfp) to 42 Dfp. Ground reference data of plant height and tiller count were measured twice a week. </p> <p> </p> <p>RGB imaging data were stored in “OWB_RGB.xlsx”. Datasheet “Information” describes the variables in datasheets for top view, side average view and every side view.</p> <p> </p> <p>Ground reference data for plant height and tiller count were stored in “OWB_ground_reference.xlsx”. Datasheet “Information” describes the variables in datasheet “Data”.</p>
EDEN ISS 2020 Telemetry Dataset
<h2>Overview</h2> <p>The EDEN ISS 2020 Telemetry Dataset (edeniss2020) is a time series dataset. It consists of equidistant sensor readings stemming from 97 sensors in the [EDEN ISS](https://eden-iss.net/) research greenhouse.</p> <p>EDEN ISS was a (almost) closed loop research greenhouse build under the lead of the German Aerospace Center to study Controlled Environment Agriculture (CEA) techniques and plant growth for future long-term space missions. EDEN ISS was deployed in Antarctica in 2018 next to the german Neumayer III polar station and has been in operation for four years. </p> <p>The data contained in the edeniss2020 dataset was recorded during the third mission year in 2020 between 2020/01/01 and 2020/12/30. Every sensor within the dataset is related to one of the following Subsystems</p> <p> </p> <table> <tbody> <tr> <td><strong>Acronym</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>AMS‑FEG</td> <td>Atmosphere Management System (AMS) of the Future Exploration Greenhouse (FEG)</td> </tr> <tr> <td>AMS‑SES</td> <td>Atmosphere Management System AMS of the Service Section (SES)</td> </tr> <tr> <td>ICS</td> <td>Illumination Control System</td> </tr> <tr> <td>NDS</td> <td>Nutrient Delivery System</td> </tr> <tr> <td>TCS</td> <td>Thermal Control System</td> </tr> </tbody> </table> <p> </p> <h2>Specification</h2> <table> <tbody> <tr> <td><strong>Item</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>Number of Files</td> <td>97</td> </tr> <tr> <td>Start Date</td> <td>2020/01/01 00:00:05</td> </tr> <tr> <td>End Date</td> <td>2020/12/30 23:55:00</td> </tr> <tr> <td>Sampling Rate</td> <td>1/300 Hz (5min)</td> </tr> <tr> <td>Datapoints (per file)</td> <td>105119</td> </tr> </tbody> </table> <p> </p> <h2>Contents</h2> <p>The dataset includes the following files:</p> <div> <ul> <li><code>ams-feg/*.csv</code>: Sensor readings related to the AMS-FEG</li> <li><code>ams-ses/*.csv</code>: Sensor readings related to the AMS-SES</li> <li><code>ics/*.csv</code>: Temperature readings related to the ICS</li> <li><code>nds/*.csv</code>: Sensor readings related to the NDS</li> <li><code>tcs/*.csv</code>: Sensor readings related to the</li> <li><code>edeniss2020.csv</code>: Description and Units of the measurements.</li> <li><code>README.md</code>: This file.</li> </ul> <table> <tbody> <tr> <th>Subsystem</th> <th>Sensor</th> <th>#sensors</th> <th>Note</th> </tr> </tbody> <tbody> <tr> <td>AMS-FEG</td> <td>CO2</td> <td>2</td> <td> </td> </tr> <tr> <td> </td> <td>Photosynthetic Active Radiation (PAR)</td> <td>2</td> <td> </td> </tr> <tr> <td> </td> <td>Relative Humidity (RH)</td> <td>2</td> <td> </td> </tr> <tr> <td> </td> <td>Temperature (T)</td> <td>3</td> <td> </td> </tr> <tr> <td>AMS-SES</td> <td>CO2</td> <td>2</td> <td> </td> </tr> <tr> <td> </td> <td>Photosynthetic Active Radiation (PAR)</td> <td>1</td> <td> </td> </tr> <tr> <td> </td> <td>Relative Humidity (RH)</td> <td>1</td> <td> </td> </tr> <tr> <td> </td> <td>Temperature (T)</td> <td>3</td> <td> </td> </tr> <tr> <td> </td> <td>Vapor Pressure Deficit (VPD)</td> <td>1</td> <td> </td> </tr> <tr> <td>ICS</td> <td>Temperature (T)</td> <td>38</td> <td>Measured at the LED lamp above each growth tray</td> </tr> <tr> <td>NDS</td> <td>Electrical Conductivity (EC)</td> <td>4</td> <td>EC of the nutrient solutions</td> </tr> <tr> <td> </td> <td>Level (H)</td> <td>2</td> <td>Level of the solution in the nutrient solution tanks</td> </tr> <tr> <td> </td> <td>PH-Value (PH)</td> <td>4</td> <td>PH Value of the nutrient solutions</td> </tr> <tr> <td> </td> <td>Pressure (P)</td> <td>8</td> <td>Pressure in the piping from the tanks to the growth racks in the FEG</td> </tr> <tr> <td> </td> <td>Temperature (T)</td> <td>4</td> <td>Temperature of the nutrient solutions.</td> </tr> <tr> <td> </td> <td>Volume (V)</td> <td>2</td> <td>Volume up to the level sensor</td> </tr> <tr> <td>TCS</td> <td>Pressure (P)</td> <td>3</td> <td> </td> </tr> <tr> <td> </td> <td>Relative Humidity (RH)</td> <td>2</td> <td> </td> </tr> <tr> <td> </td> <td>Temperature (T)</td> <td>12</td> <td> </td> </tr> <tr> <td> </td> <td>Valve (VALVE)</td> <td>3</td> <td> </td> </tr> </tbody> </table> </div> <p> </p> <h2>Usage</h2> <p>For usage information please refer to the README.md file.</p> <p> </p> <p> </p>
ISS images of Kiev during and before the Ucrania war
<p>Calibrated RGB images of Kiev at Night taken from the International Space Station.</p> <p>Early access upon request (alejasan@ucm.es)</p> <p>Data source of this app: https://pmisson.users.earthengine.app/view/kiev</p> <p> </p> <p>The data will be disembarked, as soon as the first article is sudmited or a year. What happens first.</p>
Dark Skies ISS - Community Health
Results of the community health analysis of the Dark Skies ISS project (January 2016 - December 2018)
VNMPF-LIS: Validation Network Multiplatform Precipitation Feature (VNMPF) Dataset with International Space Station Lightning Imaging Sensor (ISS LIS) Data
<p>The Multiplatform Precipitation Feature (MPF) database combines ground- and space-based precipitation observations and retrievals from the Global Precipitation Measurement (GPM) mission Validation Network (VN) with space-based lightning measurements from the Lightning Imaging Sensor on board the International Space Station (ISS LIS). The data are synthesized in a thunderstorm-like, feature-based framework that encapsulates the microphysical, kinematic, and electrical properties of the observed storm.<br> <br> A VNMPF includes:</p> <p>- Radar information, GPM orbit, and ISS orbit <br> - Time/date information<br> - Geographical information<br> - Radar reflectivity characteristics<br> - Lightning energetic and identification information (where there is lightning)<br> - 3-dimensional wind information (where radars in dual-Doppler configuration are available)<br> <br> Version 1: 2017-2020</p> <p>Version 2: 2017-2022, updated VN winds </p>
Dataset for P. Ripka, M. Mirzaei, J. Maier: Flat Magnetic X-Y Alignment sensor, IEEE Sensors Letters Vol. 8, Iss. 7, 2024, pp. 1-4 10.1109/LSENS.2024.3414375
Open the record for dataset details and reuse information.
RF recording from the QB50-ISS cubesats from 2017-05-29
<p>This dataset contains an IQ recording of the telemetry signals of many of the QB50 project cubesats. The recording was done on 2017-05-29 18:25:29 UTC, shortly after several cubesats were released from the ISS. The recording was done from 40.5962º N, 3.6964º W, 700 m ASL, near Madrid (Spain). A 7 element yagi antenna built by Arrow and a LimeSDR were used to record. The antenna was handheld in vertical polarization and connected to the SDR with a short (~1 metre) piece of coaxial cable.</p> <p>The recording is 3 Msps IQ and uses a centre frequency of 436.5 MHz and WAV format.</p> <p>More information about this recording can be found in the post "<a href="https://destevez.net/2017/05/a-tour-of-qb50/">A tour of QB50</a>" by the author.</p>
Czech Rep. ISS night time images
<p>A subsample of Sources of Environmental risks from artificial nighttime lighting widespread and increasing across Europe </p> <p>Please use the main source. </p> <pre>https://doi.org/10.5281/zenodo.6468940</pre>
Barcelona light impact impact maps using ISS images
<p>Environmental impact maps of Barcelona based on the ISS image ISS035-e-023385 from https://eol.jsc.nasa.gov.</p> <p>Includes:</p> <p>Estimations of the corrections to all Lucas et al. 2013 pigments using the ratios BG and GR. Also, Aubé et al 2013 index.</p> <p>These files have been produced calibrating procedure Sánchez de Miguel 2015 and updated procedures and Sánchez de Miguel et al 2019a and early stages of Sánchez de Miguel et. al 2019b.</p>
Dark Skies Clasification of ISS images.
<p>The Dark Skies Citizen Science Project is indeed related to Cities at Night, a program that uses images taken from the International Space Station (ISS) to catalog and monitor light pollution in cities around the world. The project is a collaboration between the Complutense University of Madrid and other institutions.</p> <p>Citizen scientists can participate in the project by using the Cities at Night website to classify and identify the different sources of light in the images, such as streetlights, buildings, and illuminated signs. This information helps researchers create more accurate maps of light pollution and track changes in urban lighting over time.</p> <p>The Dark Skies Citizen Science Project is a great way for people to get involved in scientific research and contribute to a better understanding of the impact of light pollution on our cities and the environment.</p>
A Phase 3 Study to Evaluate the Safety and Efficacy of Saizen® in Children With Idiopathic Short Stature (ISS)
ClinicalTrials.gov study NCT01746862. IPD Sharing: Not stated. Countries: 1. Publications: 1.
On following pages: 473. Senegal Striped Grass Mouse (Lemniscomys linulus); 474. Mittendorf's Striped Grass Mouse (Lemniscomys mittendorfi); 475. Hoogstraal's Striped Grass Mouse (Lemniscomys hoogstraali), 476. Buffoon Striped Grass Mouse (Lemniscomys macculus); 477. Griselda Striped Grass Mouse (Lemniscomys griselda); 478. Single-striped Grass Mouse (Lemniscomys rosalia); 479. Rosevear's Striped Grass Mouse (Lemniscomys roseveari); 480. West African Rufous-nosed Rat (Oenomys ornatus); 481. Common Rufous-nosed Rat (Oenomys hypoxanthus); 482. East African Groove-toothed Swamp Rat (Pelomys fallax); 483. Hopkins's Groove-toothed Swamp Rat (Pelomys hopkinsi); 484. Lake Victoria Groove-toothed Swamp Rat (Pelomys isseli); 485. Angolan Groove-toothed Swamp Rat (Pelomys campanae); 486. Least Groove-toothed Swamp Rat (Pelomys minor); 487. Target Rat (Stochomys longicaudatus); 488. Kemp's Thicket Rat (Thamnomys kempi); 489. Hatt's Thicket Rat (Thamnomys majon; 490. Schouteden's Thicket Rat (Thamnomys schoutedeni); 491. Thomas's Thicket Rat (Thamnomys venustus); 492. Namaqua Rock Rat (Micaelamys namaquensis); 493. Grant's Rock Rat (Micaelamys granti); 494. Mesic Four-striped Grass Rat (Rhabdomys dilectus); 495. West-Central South African Fourstriped Grass Rat (Rhabdomys bechuanae); 496. KwaZulu Natal Four-striped Grass Rat (Rhabdomys chakae); 497. Karoo Four-striped Grass Rat (Rhabdomys intermedius); 498. Xeric Four-striped Grass Rat (Rhabdomys pumilio), 499. Loring's Thallomys (Thallomys loringi); 500. Black-tailed Thallomys (Thallomys nigricauda); 501. Sundevall's Thallomys (Thallomys paedulcus); 502. Shortridge's Thallomys (Thallomys shortridgei). in Muridae
On following pages: 473. Senegal Striped Grass Mouse (Lemniscomys linulus); 474. Mittendorf's Striped Grass Mouse (Lemniscomys mittendorfi); 475. Hoogstraal's Striped Grass Mouse (Lemniscomys hoogstraali), 476. Buffoon Striped Grass Mouse (Lemniscomys macculus); 477. Griselda Striped Grass Mouse (Lemniscomys griselda); 478. Single-striped Grass Mouse (Lemniscomys rosalia); 479. Rosevear's Striped Grass Mouse (Lemniscomys roseveari); 480. West African Rufous-nosed Rat (Oenomys ornatus); 481. Common Rufous-nosed Rat (Oenomys hypoxanthus); 482. East African Groove-toothed Swamp Rat (Pelomys fallax); 483. Hopkins's Groove-toothed Swamp Rat (Pelomys hopkinsi); 484. Lake Victoria Groove-toothed Swamp Rat (Pelomys isseli); 485. Angolan Groove-toothed Swamp Rat (Pelomys campanae); 486. Least Groove-toothed Swamp Rat (Pelomys minor); 487. Target Rat (Stochomys longicaudatus); 488. Kemp's Thicket Rat (Thamnomys kempi); 489. Hatt's Thicket Rat (Thamnomys majon; 490. Schouteden's Thicket Rat (Thamnomys schoutedeni); 491. Thomas's Thicket Rat (Thamnomys venustus); 492. Namaqua Rock Rat (Micaelamys namaquensis); 493. Grant's Rock Rat (Micaelamys granti); 494. Mesic Four-striped Grass Rat (Rhabdomys dilectus); 495. West-Central South African Fourstriped Grass Rat (Rhabdomys bechuanae); 496. KwaZulu Natal Four-striped Grass Rat (Rhabdomys chakae); 497. Karoo Four-striped Grass Rat (Rhabdomys intermedius); 498. Xeric Four-striped Grass Rat (Rhabdomys pumilio), 499. Loring's Thallomys (Thallomys loringi); 500. Black-tailed Thallomys (Thallomys nigricauda); 501. Sundevall's Thallomys (Thallomys paedulcus); 502. Shortridge's Thallomys (Thallomys shortridgei).
FIGURE 5. A, B. Gibbula isseli Monterosato, 1889 in Catalogue of the primary types of marine molluscan taxa described by Tommaso Allery Di Maria, Marquis of Monterosato, deposited in the Museo Civico di Zoologia, Roma
FIGURE 5. A, B. Gibbula isseli Monterosato, 1889, Costantinopoli (Turkey), H. 4.9 mm, with original label (MCZR–M– 11304); C–E. Trochus latior Monterosato, 1880, Sfax (Tunisia), H. 17.5 mm, with original labels (MCZR–M–11306); F, G. Zizyphinus linnaei Monterosato, 1884, Palermo (Sicily), H. 23.2 mm, with original label (MCZR–M–11543); H, I. Zizyphinus lissus Monterosato, 1889, Yorkshire (U. K.), H. 22.2 mm, with original label (MCZR–M–11578).
Madrid light impact impact maps using ISS images
<p>Environmental impact maps of Madrid based on the ISS image ISS030-e-082052 from https://eol.jsc.nasa.gov.</p> <p>Includes:</p> <p>Estimations of the corrections to all Lucas et al. 2013 pigments using the ratios BG and GR. Also, Aubé et al 2013 index.</p> <p>These files have been produced calibrating procedure Sánchez de Miguel 2015 and updated procedures and Sánchez de Miguel et al 2019a and early stages of Sánchez de Miguel et. al 2019b.</p>
Anomaly Detection dataset for the ISS Panel mockup
<p>If you use the dataset, please cite:</p> <p><em>Siddhant Shete, Dennis Mronga</em></p> <p><strong>"Adaptive Online Anomaly Detection using Transfer Learning"</strong></p> <p>About the dataset: The dataset is basically used for anomaly detection in the ISS(International Space Station) panel. This dataset was captured from the mockup used for experiments at the institute. The panel replicates the curcuit and control boards at ISS. The dataset is segregated in two parts Normal data and Anomalous data.</p> <p>Contents of <em><strong> ISSPanelDataset.zip </strong></em></p> <ol> <li>Nomal</li> <li>Anomaly</li> </ol> <p>The Anomaly folder has data with different scenarios where the led lights are on, the fan panel cover is missing or some parts are missaligned.</p> <p> </p> <p><em>This dataset is provided by the Robotics Innivation Center, DFKI GmbH.</em></p> <p><em>The grant was provided by Federal Ministry for Economic Affairs and Climate Action </em></p> <p><em>Grant number: 20W1922F</em></p>
Safety and Effectiveness Evaluation of the ISS System in Treatment of Acute Ischemic Stroke
ClinicalTrials.gov study NCT03733236. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Phase I Safety and Immunogenicity Preventive Vaccine Trial Based on the HIV-1 Tat and V2-deleted Env Proteins (ISS P-002)
ClinicalTrials.gov study NCT01441193. IPD Sharing: Not stated. Countries: 1. Publications: 13.
Efficacy and Safety of rhGH (Jintropin®) in Pediatric Participants With ISS
ClinicalTrials.gov study NCT03635580. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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)
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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.