Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
105
datasets available to search
ShareScore release 0.9.0
Dataset results
105 results for “shuttling”
Begomovirus DNA-B Movement Protein and Nuclear Shuttle Protein Ref-Seq Datasets
<p>Multiple Sequence Alignment of proteins encoded on begomovirus DNA-B (movement protein and nuclear shuttle protein; n=131). One isolate per species based on ICTV reference list.</p> <p> </p>
Shelf–to–basin shuttle of highly fractionated chromium isotopes in the Arctic Ocean
<p>This dataset contains total dissolved chromium concentration and isotopic ratios in seawater associated with our paper "Shelf–to–basin shuttle of highly fractionated chromium isotopes in the Arctic Ocean" (submitted and accepted in Geochimica Cosmochimica Acta).</p> <p>The seawater samples were collected during the 2015 ArcticNet/Geotraces cruise aboard the CCGS Amundsen along the sections GN02 and GN03. </p> <p>All processing and measurements were done at the Saskatchewan Isotope Laboratory at the University of Saskatchewan (Canada).</p> <p>This data will also be available in the next GEOTRACES Intermediate Data Product (November 2025).</p> <p><span><strong>></strong> Cr_53_52_D_DELTA_BOTTLE_METADATA-2015CanadianArcticGEOTRACEScruise_OVERVIEW.csv : details the context of the expedition and the sampling/processing methods;</span></p> <p><span><strong>></strong> Cr_53_52_D_DELTA_BOTTLE_METADATA-2015CanadianArcticGEOTRACEScruise_DATA.csv : gives details on the data (<em>e.g.</em> units), as well as technical information associated with the measurements;</span></p> <p><span><strong>></strong> Cr_53_52_D_DELTA_BOTTLE_DATA-2015CanadianArcticGEOTRACEScruise.csv : chromium data associated with the paper.</span></p>
Electron shuttling capacity and greenhouse gas production of soils for three high-elevation wetlands at Niwot Ridge, 2024.
High-elevation wetlands are important indicators of how mountain ecosystems may respond to global climate change. These wetlands also act as locations of disproportionate biogeochemical processing on the landscape, but they remain relatively understudied compared to lowland wetlands. This study aimed to characterize redox-active organic matter (RAOM) reduction, a known key control on carbon cycling in high-latitude peatland ecosystems, to better understand biogeochemical cycling in high elevation wetlands and carbon greenhouse gas production at Niwot Ridge LTER. Soils were collected from three different types of wetlands, a subalpine wetland, a periglacial solifluction lobe, and an alpine wet meadow. Samples were incubated at a common temperature in the laboratory to measure RAOM reduction, carbon dioxide production, and methane production over 63-d. This dataset reports the electron shuttling values, a measure of RAOM reduction, and the greenhouse gas production over the incubation period.
Dataset: Shuttle Pharmaceuticals Holdings, Inc. (SHPH) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Orbiter Space Shuttle OV-103 Discovery
*Many thanks to the support generously provided by Meredith Siegfried Madden and Dr. Peter Madden. Without you this wouldn't be possible.* Smithsonian source data can be found [here](https://ids.si.edu/ids/media_view?id=3d_package:d8c636ce-4ebc-11ea-b77f-2e728ce88125) This media file is in the public domain (free of copyright restrictions). You can copy, modify, and distribute this work without contacting the Smithsonian. For more information and to review the 3D disclaimer, visit the Smithsonian's [Terms of Use](https://www.si.edu/Termsofuse) page. Orbiter, Space Shuttle, OV-103, Discovery Manufacturer: Rockwell International Corporation Materials: Airframe: aluminum alloys, titanium, Surface: silica tiles, reinforced carbon carbon RCC nose cap and wing leading edges, Interior: many materials (aluminum, fabric, beta cloth, velcro, etc.) Dimensions: Overall: 24.314m x 17.768m x 38.03m, 73176.5kg (78 ft. x 57 ft. x 122 ft., 161325lb.) EDAN-URL: edanmdm:nasm_A20120325000 Source: Objaverse 1.0 / Sketchfab
Shuttle Radar Topography Mission digital elevation models, data points, radiocarbon dates, and geochemical data for the Rub' al Khali Desert
Open the record for dataset details and reuse information.
Supporting Dataset for "A synthetic C4 shuttle via the β-hydroxyaspartate cycle in C3 plants"
<p>Plants depend on the enzyme ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) for CO<sub>2</sub> fixation. However, especially in C3 plants, photosynthetic yield is reduced by the formation of 2-phosphoglycolate, a toxic oxygenation product of Rubisco, which needs to be recycled in a high-flux–demanding metabolic process called photorespiration. Canonical photorespiration dissipates energy and causes carbon and nitrogen losses. Reducing photorespiration through carbon-concentrating mechanisms, such as C4 photosynthesis, or bypassing photorespiration through metabolic engineering is expected to improve plant growth and yield. The β-hydroxyaspartate cycle (BHAC) is a recently described microbial pathway that converts glyoxylate, a metabolite of plant photorespiration, into oxaloacetate in a highly efficient carbon-, nitrogen-, and energy-conserving manner. Here, we engineered a functional BHAC in plant peroxisomes to create a photorespiratory bypass that is independent of 3-phosphoglycerate regeneration or decarboxylation of photorespiratory precursors. While efficient oxaloacetate conversion in <em>Arabidopsis thaliana</em> still masks the full potential of the BHAC, nitrogen conservation and accumulation of signature C4 metabolites demonstrate the proof of principle, opening the door to engineering a photorespiration-dependent synthetic carbon–concentrating mechanism in C3 plants.</p> <p>Data analysis was performed in R. For analysis of gas exchange measurements, the “plantecophys” package was used (<a href="https://www.pnas.org/doi/full/10.1073/pnas.2022307118#core-r55">55</a>). The data are summarized in <a href="http://www.pnas.org/lookup/doi/10.1073/pnas.2022307118#supplementary-materials">Datasets S1–S10</a>. All other study data are included in the article and/or supporting information, available at <a href="https://doi.org/10.1073/pnas.2022307118">https://doi.org/10.1073/pnas.2022307118</a></p> <p>Dataset S1: Enzymatic activity of BHAC enzymes in Arabidopsis rosette leaves. For ISR the rate of percentual 15N label enrichment in aspartate was quantified. Shown mean and standard deviation (SD).</p> <p>Dataset S2: Metabolome of BHAC plants. Shown is mean and standard deviation (SD) of the calculated relative amount per mg fresh weight of four biological replicates per genotype for each condition.</p> <p>Dataset S3: Ammonium quantification in BHAC plants. Shown is mean and standard deviation (SD) for four biological replicates per genotype per condition measured in technical triplicates.</p> <p>Dataset S4: Phenotyping of BHAC plants. Shown is mean and standard deviation (SD) of five biological replicates per genotype per condition.</p> <p>Dataset S5: A/Ci curve measurements of BHAC plants. Shown is mean of four biological replicates per genotype.</p> <p>Dataset S6: Light response measurements of BHAC plants. Shown is mean of four biological replicates per genotype.</p> <p> Dataset S7: Metabolite levels of phosphorylated intermediates and glyoxylate in air-grown plants. Shown is mean and standard deviation of ≥ 3 replicates.</p> <p>Dataset S8: Metabolome of ggt1-1 complementation lines with AGAT. Shown is mean and standard deviation (SD) of four biological replicates.</p> <p>Dataset S9: Enzymatic activity of AGAT and GGT in Arabidopsis rosette leaves of the ggt1-1 complemention lines. Shown mean and standard deviation (SD) of three biological replicates measured in technical triplicates.</p> <p>Dataset S10: O2-Dependency of CCP was measured at 4% O2. Shown is the mean ±SD of n ≥ 3.</p>
Supporting data for 'A shuttling-based two-qubit logic gate for linking distant silicon quantum processors'
<p>Data supporting for paper 'A shuttling-based two-qubit logic gate for linking distant silicon quantum processors'.</p> <p>All the data are stored in the HDF5 format that can be conveniently loaded by the xarray Python package.</p>
ES-PT, Remote Driving, Automated shuttle remote driving across borders
<p>Use Case Category: <strong>Remote Driving</strong><br> User Story: <strong>Automated shuttle remote driving across borders</strong><br> Location: Spain-Portugal (ES-PT) cross-border corridor</p> <p>According to 3GPP TS 22.186 R16, Remote Driving “enables a remote driver or a V2X application to operate a remote vehicle for those passengers who cannot drive themselves or a remote vehicle located in dangerous environments. For a case where variation is limited, and routes are predictable, such as public transportation, driving based on cloud computing can be used. In addition, access to cloud-based back-end service platform can be considered for this use case group”.</p> <p>User Story: <strong>Automated shuttle remote driving across borders</strong></p> <p>This use case is focussed in the deployment of last mile EV Automated shuttle vehicles in different environments:</p> <p>· Cross Border environment: The shuttle will cover a route between Spain and Portugal connecting the cities of Tui and Valença through the old international bridge.</p> <p>· Urban environment: The shuttle will cover a route in the city of Vigo.</p> <p>For both environments, we will consider these two scenarios:</p> <p>· Scenario 1: Cooperative automated operation: In this scenario, the EV Autonomous shuttle is able to receive information coming from other actors (like a Vulnerable Road User) and adapt its behaviour according to specific needs.</p> <p>· Scenario 2: Remote Control: In this scenario the EV autonomous vehicle is driving following a predefined route, and suddenly an obstacle appears in its path blocking the original route. In this situation, an operator is alarmed, and he/she is able to remotely take the control of the EV autonomous vehicle or issue a set of new navigation commands in order to handle a new route.</p>
ES-PT, Advanced Driving, Automated Shuttle
<p>Use Case Category: <strong>Advanced Driving</strong><br> User Story: <strong>Automated shuttle remote driving across borders</strong><br> Location: Spain-Portugal (ES-PT) cross-border corridor</p> <p>According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency”</p> <p>User story: Automated shuttle remote driving across borders</p> <p>This use case is focussed in the deployment of last mile EV Automated shuttle vehicles in different environments:<br> - Cross Border environment: The shuttle will cover a route between Spain and Portugal connecting the cities of Tui and Valença through the old international bridge.<br> · Urban environment: The shuttle will cover a route in the city of Vigo.</p> <p>Scenario: Cooperative automated operation: In this scenario, the EV Autonomous shuttle is able to receive information coming from other actors (like a Vulnerable Road User) and adapt its behaviour according to specific needs.</p>
Spin-EPR-pair separation by conveyor-mode single electron shuttling in Si/SiGe
<p>Dataset for the paper 'Spin-EPR-pair separation by conveyor-mode single electron shuttling in Si/SiGe'</p>
Multi-shuttle crane scheduling in automated storage and retrieval systems
<p>The uploaded ".zip"-file contains 6 folders corresponding to the 6 experiments in our working paper "Multi-shuttle crane scheduling in automated storage and retrieval systems".</p> <p><br> Each of these folders contains a "results.csv" file with the data from the experiments. All but the last two columns contain information about the solved instance, the second to last column contains the objective value and the last column the runtime.</p> <p> </p> <p>Then each folder contains ".txt"-files or several folders with ".txt"-files. Each files contains one instance.</p> <p>Each instance begins with the name of the file in which it is located. Then follows an empty line, a line with the word "VEHICLE" and a new line<br> "NUMBER OF CAPACITY EMPTYING REQUIREMENTS HIGHEST SPEED LONGEST DISTANCE MAXIMUM DISTANCE". It follows a line containing the following integers: the number of vehicles, the capacity of all vehicles, the number of empty slots, the total number of requests, the speed in x dimension, the speed in y dimension, and an upper limit for the maximum distance between the I/O point and each slot.<br> Next follows a line with the text "CUSTOMER" and then a line with the text "CUSTOMER NUMBER". XCOORD. YCOORD."<br> This is followed by lines each containing a relevant slot. Each entry begins with a number that counts the entries, followed by the x-coordinate and then the y-coordinate. The first entry has the number 0 and is the I/O point. Then the customer locations follow, and then we start the restart the numbering at 1 for the following requests.</p>
To Stop or to Shuttle Halides? The Role of an Ionic Liquid inThermal Halide Mixing of Hybrid Perovskites
<p>Raw NMR data for the paper : https://doi.org/10.1021/acsenergylett.3c01878</p> <p>ACSEnergy Lett. 2023, 8,5041−5049</p>
Constellation analysis of automated local public transport shuttles in the north western development area of Berlin
<h2><strong><span>Konstellationsanalyse: Autonome ÖPNV-Shuttles im Entwicklungsband Nordwest </span></strong></h2> <p>Das Dokument beinhalten stellt eine deutschsprachige Ergebnisdokumentation einer Konstellationsanalyse aus dem Projekt „NOWEL4 – Berliner NordWestraum Level 4" dar . Die Konstellationsanalyse ist ein Brückenkonzept für inter- und transdisziplinäre Zusammenarbeit, das u.a. in der Nachhaltigkeits- und Technikforschung eingesetzt werden kann. Die Ergebnisse zeigen eine gegenwärtige Konstellation und eine Zielkonstellation der Einbindung autonomer Shuttles in den ÖPNV im Berliner Entwicklungsband NordWest. </p> <h2> </h2> <p> </p>
The SpinBus architecture: Scaling spin qubits with electron shuttling
Open the record for dataset details and reuse information.
Empowering Autonomous Shuttles with Next-Generation Infrastructure
<p>This dataset accompanies the paper: <strong>Empowering Autonomous Shuttles with Next-Generation Infrastructure </strong>presented at the European Conference on Computer Vision (ECCV) 2024 in Milan. </p> <p>We provide a dataset in the form of CSV-file recordings. The dataset was recorded during the three-day congress IT-TRANS 2024 in Karlsruhe. It contains 207 individual recordings, each recording representing one trip between the two intelligent bus stops, with a total driving duration of 7 hours and 28 minutes. We publish V2X messages, information regarding the autonomous driving of the shuttle, and recorded information from the bus stops and the intelligent traffic light.</p> <p><br>More information about the data and the setup can be read in the paper.<br><br>This work was partially funded by KAMO: Karlsruhe Mobility High Performance Center (www.kamo.one).</p>
Citizens Acceptance of Shuttles_final_pub
Open the record for dataset details and reuse information.
Data and analysis accompanying the paper "Shuttling an electron spin through a silicon quantum dot array"
<p>Raw data and analysis scripts to reproduce the analysis for the figures of the paper "Shuttling an electron spin through a silicon quantum dot array". Analysis scripts are written in python and require the package QCoDeS.</p> <p>Zwerver, A.M.J., et al. ArXiv:2209.000920v2</p>
Supplementary material: animated GIF of null space shuttle with shortening of the subducted Iberian crust.
<p>Supplementary material to the paper: </p><p>Geologically constrained geometry inversion with and null-space navigation to explore alternative geological scenarios: a case study in the Western Pyrenees. <br>Jeremie Giraud, Mary Ford, Guillaume Caumon, Lachlan Grose, Vitaliy Ogarko, Roland Martin, Paul Cupillard. </p><p>Note that the profile A-B shown here is more to the west than the profile shown in the paper. The image shows the full model inclusive of padding cells.</p>
Reliability of the Incremental Shuttle Walk Test in University Students
ClinicalTrials.gov study NCT06638281. IPD Sharing: NO. Countries: 1. Publications: 0.
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.