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858 results for “Energy Data”
Data from: Use of a microfluidic platform to uncover basic features of energy and environmental stress responses in individual cells of Bacillus subtilis
Bacteria use a variety of stress-sensing systems to sense and respond to diverse stressors and to ensure their survival under adverse conditions. The gram-positive bacterium Bacillus subtilis responds to energy stress (ATP depletion) and to environmental stressors using two distinct stress-sensing pathways that converge on the alternative sigma factor σB to provoke a general stress response. Past efforts to study the σB stress response in bulk culture and on agarose pads were unable to visualize the responses of individual cells under tightly controlled conditions for extended periods of time. Here we use a microfluidics-based strategy to discern the basic features of σB activation in single cells in response to energy and environmental stress, both immediately upon stressor exposure and for tens of generations thereafter. Upon energy stress at various levels of stressor, cells exhibited fast, transient, and amplitude-modulated responses but not frequency modulation as previously reported. Upon environmental stress, which is mediated by the stressosome complex, wild-type cells primarily exhibited a transient and amplitude-modulated response. However, mutant cells producing only one of the four paralogous RsbR stressosome proteins showed striking and previously unseen differences. Whereas RsbRA-only cells mimicked the wild type, RsbRC-only cells displayed a slower but sustained overall response composed of repeated activation events in single cells.
Data for "Non-reciprocal energy transfer through the Casimir effect"
<p>Raw data for the project "Non-reciprocal energy transfer through the Casimir effect".</p>
(re)Use Indications of High Energy Physics related Research Data and Software in CERN Open Data Portal
<p>This dataset contains High Energy Physics related research data and software (re)use indications (formal citations, informal mentions) in scholarly works. All research data and software resources were identified and extracted from CERN Open Data Portal. The (re)use indications were identified by a mix of approaches: use of citation discovery services and multiple search approaches in Google Scholar. All identified research data and software (re)use indications were classified according to their purpose, location, and elements.</p> <p>The data was collected in 2018 for a PhD thesis on research data and software (re)use indications in scholarly works.</p>
(re)Use Indications of High Energy Physics related Research Data and Software in INSPIRE-HEP
<p>This dataset contains High Energy Physics related research data and software (re)use indications (formal citations, informal mentions) in scholarly works. All research data and software resources were identified and extracted from INSPIRE-HEP. The (re)use indications were identified by a mix of approaches: use of citation discovery services and multiple search approaches in Google Scholar. All identified research data and software (re)use indications were classified according to their purpose, location, and elements.</p> <p>The data was collected in 2018 for a PhD thesis on research data and software (re)use indications in scholarly works.</p>
Transcription of Physical Properties Data Compilations Relevant to Energy Storage: I. Molten Salts: Eutectic Data
<p>Transcription of Physical Properties Data Compilations Relevant to Energy Storage: I. Molten Salts: Eutectic Data. This is a large dataset of eutectic mixtures originally compiled and published in 1978. There was not previously a machine-readable version of this dataset. We have transcribed the 2-component mixtures into csv format. We have also included 6 basic features that are widely available on Pubchem for the individual components in the mixtures, and a list of components that were not available via Pubchem.</p>
Ocean eddy kinetic energy at 1000 m depth estimated from Argo drift data from July 1997 to December 2015
<p><strong>Eddy kinetic energy at 1000 dbar depth estimated from Argo drift data from July 1997 to December 2015</strong><br><br>These are the data used to draw Fig.1 of Katsumata (2017b).<br>Argo drift data from YoMaHa (Lebedev et al. 2017) is averaged<br>in a quasi-circle with a radius of 300 km, deformed to follow<br>bathymetry, and deviation from the average is our eddy here.<br><br>Detail of the method is found in Katsumata (2017a).<br><br><a href="https://doi.org/10.1175/JPO-D-16-0150.1">Katsumata (2017a)</a><br><a href="https://doi.org/10.1175/JPO-D-16-0150.1">Katsumata (2017b)</a><br>Lebedev, K., H. Yoshinari, N. A. Maximenko, and P. W. Hacker,<br> (2007) YoMaHa’07: Velocity data assessed from trajectories of<br> Argo floats at parking level and at the sea surface. IPRC Tech.<br> Note 4, 16 pp.<br> <a href="https://doi.org/10.1175/JPO-D-16-0150.1">http://apdrc.soest.hawaii.edu/projects/yomaha/</a></p> <p> </p>
Energy Profiler Raw Data Results
<p>Energy profiler data collected for the Masters' thesis of Linus Jungemann.</p>
Data Anomaly Detection in Cyber-Physical Energy Systems
<p>The data is created in an agent-system, used for controlling distributed energy systems. The agents follow the Lightweight Power Exchange Protocol to negotiate whenever an agent detects a planning problem. The protocol is explained in "A lightweight distributed software agent for automatic demand—supply calculation in smart grids" by Veith, Steinbach and Windeln. Different kinds of anomalies were created by manipulating an agent accordingly: anomalies in the values of the exchanged messages and anomalies in the communication behavior. The implementation of the power exchange used for the data generation can be found here: https://gitlab.com/mango-agents/mango-library/-/tags/Integration_of_the_LPEP.</p> <p>Anomalies in the values are manipulated by 500 % of the original value (dataset 500_p.csv).</p> <p>Anomalies in the communication behavior are anomalously started every minute for 8996 seconds in the future (dataset 1m_8996_50p.csv) and every 15 minutes for 2012 seconds in the future (15m_2012_50p.csv).</p> <p>For anomalies in the communication topology, an agent was chosen to which selected agent does not send any messages, although the agent is part of the neighborhood (Topology anomalies/agent_removed.csv). Furthermore, an agent was manipulated to send messages to an agent which is normally not part of its neighborhood (Topologie anomalies/agent_added.csv).</p> <p>Normal data is also given.</p>
Data included in "Sea surface energy fluxes' response to the Quasi-Biweekly Oscillation: A case study in the South China Sea"
<p>Underway observed sea surface energy fluxes data in 2019 and 2021 over the summer South China Sea.</p>
Interfacial Cherenkov radiation from ultralow-energy electrons - Data set
<p>Data set for "Interfacial Cherenkov Radiation from Ultralow-Energy Electrons"</p>
Data Repository - Impact of competing energy scales on the shell-filling sequence in elliptic bilayer graphene quantum dots
<p>Data Repository for the Publication: Impact of competing energy scales on the shell-filling sequence in elliptic bilayer graphene quantum dots</p> <p>Abstract:</p> <p>We report on a detailed investigation of the shell-filling sequence in electrostatically defined elliptic bilayer graphene quantum dots (QDs) in the regime of low charge carrier occupation, N < 12, by means of magnetotransport spectroscopy and numerical calculations. We show the necessity of including both short-range electron-electron interaction and wavefunction-dependent valley g-factors for understanding the overall fourfold shell-filling sequence. These factors lead to an additional energy splitting at half-filling of each orbital state and different energy shifts in out-of-plane magnetic fields. Analysis of 31 different BLG QDs reveals that both valley g-factor and electron-electron interaction induced energy splitting increase with decreasing QD size, validating theory. However, we find that the electrostatic charging energy of such gate-defined QDs does not correlate consistently with their size, indicating complex electrostatics. These findings offer significant insights for future BLG QD devices and circuit designs.</p>
Data from: Economic uncertainty, geopolitical risk and U.S. energy price risk spillover: An empirical study based on the risk spillover model
<p>This data is mainly used to analyze the risk correlation among economic uncertainly,geopolitical risk and energy price,and can also be applied to the TVP-VAR model to analyze the correlation between different variables using the time-varying parameter model,which has great potential for reuse. The risk relationship between economic uncertainly.At the same time,since it is macroeconomic data,it does not involve any moral and ethical issues.</p>
Data for "Unraveling the Atmospheric Energy Input and Ionization due to EMIC-Driven Electron Precipitation from ELFIN's Observations"
<p>Dataset relative to the paper "Unraveling the Atmospheric Energy Input and Ionization due to EMIC-Driven Electron Precipitation from ELFIN's Observations"</p><ol><li>case_study.zip: ELFIN&POES conjunction<ol><li>POES flux is in #/s/cm2/sr/keV</li><li>ELFIN flux is in #/s/cm2/sr/MeV</li></ol></li><li>EMICdriven_events_atmospheres_temps: background atmosphere density & temperature for all 144 events<ol><li>Density is in g/cm3</li></ol></li><li>EMICdriven_events_nflux_PA_en: ELFIN events number flux 0°-90°<ol><li>ELFIN flux is in #/s/cm2/sr/MeV (...nflux.csv files)</li><li>ELFIN pitch-angle is in degrees (...nflux_PA.csv files)</li></ol></li><li>EMICdriven_events_nflux_PA_en: ELFIN events number flux 0°-180°<ol><li>ELFIN flux is in #/s/cm2/sr/MeV (...nflux.csv files)</li><li>ELFIN pitch-angle is in degrees (...nflux_PA.csv files)</li></ol></li><li>energy_deposition.csv: energy deposition vs altitude</li><li>ionization_rates.csv: ionization rate vs altitude</li><li>lat_lon_ionization.csv: time of EMIC-driven events with lat/lon, ionization&altitude peak and energy flux</li><li>avg_atm_density.csv: average background density</li><li>mean_PAD: mean PAD in #/s/cm2/sr/eV</li><li>median_PAD: median PAD in #/s/cm2/sr/eV</li></ol>
Data from: Life-history strategy and behavioral type: risk-tolerance reflects growth rate and energy allocation in ant colonies
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Data from: Trajectory energy minimisation for cell growth tracking and genealogy analysis
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Data from two dimensional electronic spectroscopy showing that photosynthesis tunes quantum-mechanical mixing of electronic and vibrational states to steer exciton energy transfer
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Data from: A metabolic and body-size scaling framework for parasite within-host abundance, biomass, and energy flux
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Data from: The metabolic cost of changing walking speeds is significant, implies lower optimal speeds for shorter distances, and increases daily energy estimates
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Data from: Travelling Wave Pulse Coupled Oscillator (TWPCO) Using a Self-Organizing Scheme for Energy-efficient Wireless Sensor Networks
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Data from: International Atomic Energy Agency survey study with referring physicians on patient radiation exposure and its tracking: A prospective survey using a web based questionnaire
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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.