Find research datasets worth reusing

opencc-by-4.0Apr 2023View details →

Data for figures and tables in: "Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument"

Supplementary material to DESI's publication 'Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument' to comply with the data management plan.

Statistical Analysis of Overlapping Double Ion Energy Dispersion Events in the Northern Cusp (Paper Data and Code)

This data and code accompanies the paper Statistical Analysis of Overlapping Double Ion Energy Dispersion Events in the Northern Cusp, published in Frontiers in Astronomy and Space Sciences in 2023. This upload includes a CSV list of the selected events, a human-readable table of the selected events (see below), plots of each selected event, and the code used to select the events.The code in this repository is a fork of <a href="https://github.com/ddasilva/dmsp-dispersion-detection">https://github.com/ddasilva/dmsp-dispersion-detection</a> at the time of publication. Future updates may exist on GitHub.

opencc-by-4.0Oct 2023View details →

Transferability of atomic energies from alchemical decomposition - additional data

Additional data to the paper "Transferability of atomic energies from alchemical decomposition"<a href="https://doi.org/10.48550/arXiv.2311.04784">https://doi.org/10.48550/arXiv.2311.04784</a>Atomic energies of selected QM9 compounds calculated with different decomposition schemes (alchemy, IQA and IBO/IAO).Code to generate the input-file and the rescaled pseudopotential files for DFT calculations with fractional core charges with the CPMD program and to calculate alchemical atomic energies from the CPMD output.

Carbon, water and energy fluxes at the subtropical forest in Kaziranga National Park in India

This dataset contains measured and modeled records of gross primary productivity (GPP), sensible heat flux and latent heat flux from 2016 to 2018 at the Kaziranga National Park, India. The measured fluxes are obtained from eddy covariance technique at the flux tower established by the Indian Institute of Tropical Meteorology (IITM) Pune as part of the MetFlux India network funded by the Ministry of Earth Sciences (MoES), the Government of India, whereas the Integrated Science Assessment Model (ISAM) at the Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Illinois, USA is used to simulate these fluxes. Additionally, the leaf area index (LAI) and meteorological measurements used as the model input are also included in this dataset.

Energy management strategies for ectothermic vertebrates: temperature and heart rate as independent proxies

Filtered data used for analysis of energy management strategies in three different species. R script provides an example of the across- and within-individual analysis.

Dynamic energy landscapes of predators and the implications for modifying prey risk

Landscapes of fear describe a spatial representation of an animal's perceived risk of predation and the associated foraging costs, while energy landscapes describe the spatial representation of their energetic cost of moving and foraging. Fear landscapes are often dynamic and change based on predator presence and behavior, and variation in abiotic conditions that modify risk. Energy landscapes are also dynamic and can change across diel, seasonal, and climatic timescales based on variability in temperature, snowfall, wind/current speeds etc. Recently, it was suggested that fear and energy landscapes should be integrated. In this paradigm, the interaction between the landscapes relates to prey being forced into areas of the energy landscape they would avoid if risk were not a factor. However, dynamic energy landscapes experienced by predators must also be considered since they can affect their ability to forage, irrespective of variation in prey behavior. We propose an additional component to the fear and dynamic energy landscape paradigm that integrates landscapes of both prey and predators, where predator foraging behavior is modulated by changes in their energyscape. Specifically, we integrate the predators' energy landscape into foraging theory that predicts prey patch-leaving decisions under the threat of predation. We predict that as a predator's energetic cost of foraging increases in a habitat, then the prey's foraging costs of predation and patch quitting harvest rate will decrease. Prey may also decrease their vigilance in response to increased energetic foraging cost for predators, which will lower prey-giving-up densities. We then provide examples in terrestrial, aerial and marine ecosystems where we might expect to see these effects. These include birds, sharks which use updrafts that vary based on wind and current speeds, tidal state, or temperature and terrestrial predators (e.g. wolves) whose landscapes vary seasonally with snow depth or ice cover which may influence their foraging success and even diet selection. A predator perspective is critical to considering the combination of these landscapes and their ecological consequences. Dynamic predator energy landscapes could add a spatiotemporal component to risk effects which may cascade through food webs.

EfficientBioAI: Making Bioimaging AI Models Efficient in Energy and Latency

This dataset contains trained deep learning models, dataset and experiment files for the manuscript "EfficientBioAI: Making Bioimaging AI Models Efficient in Energy and Latency". Please find the software and more information including tutorials here: <a href="https://github.com/MMV-Lab/EfficientBioAI">MMV-Lab/EfficientBioAI (github.com)</a>.

Energy simulation outputs for different mitigation scenarios

Advanced urban heat mitigation technologies that involve the use of super cool materials combined with properly designed green infrastructure, lower the urban ambient and land surface temperatures and reduce the cooling consumption at the city scale. We present the results of the world's largest heat mitigation project in Riyadh, KSA. Daytime radiative coolers as well as cool materials combined with irrigated or non-irrigated greenery, have been used to design eight holistic heat mitigation scenarios. We assessed the climatic impact of the scenarios as well as the corresponding energy benefits of 3,323 urban buildings. An impressive decrease of the peak ambient temperature, up to 4.5°C, is calculated, consisting of the highest reported urban ambient temperature reduction, while the annual sum of the differences of the ambient temperature against a standard temperature base, (cooling degree hours), in the city decrease by up to 26%. We found that innovative urban heat mitigation strategies contribute to remarkable cooling energy conservation by up to 16%, while the combined implementation of heat mitigation and energy adaptation technologies decreases the cooling demand by up to 35%. It is the first article investigating the large-scale energy benefits of modern heat mitigation technologies when they are implemented in cities.

Data from: Timing of conceptions in Phayre's leaf monkeys: energy and phytochemical intake

Raising offspring imposes energetic costs, especially for female mammals. Consequently, seasons favoring high energy intake and sustained positive energy balance often result in a conception peak. Factors that may weaken this coordinated effect include premature offspring loss and adolescent subfertility. Furthermore, seasonal ingestion of phytochemicals may facilitate conception peaks. We examined these factors and potential benefits of a conception peak (infant survival, interbirth interval) in Phayre's leaf monkeys (Trachypithecus phayrei crepusculus). Data were collected at Phu Khieo Wildlife Sanctuary, Thailand (78 conceptions). We estimated periods of high energy intake based on fruit and young leaf feeding and via monthly energy intake rates. Phytochemical intake was based on fecal progestin. We examined seasonality (circular statistics, cox proportional hazard models) and compared consequences of timing (infant survival and interbirth intervals, t-test, Fisher exact test). Conceptions occurred in all months but peaked from May to August. This peak coincided with high fecal progestin rather than presumed positive energy balance. Primipara conceived significantly later than multipara. Neither infant survival nor interbirth intervals were related to the timing of conception. Periods of high energy intake may not exist and would not explain the conception peak in this population. However, the presumed high intake of phytochemicals was tightly linked to the conception peak. Timing conceptions to the peak season did not provide benefits, suggesting that the clustering of conceptions may be a mere by-product of phytochemical intake. To confirm this conclusion, seasonal changes in phytochemical intake and hormone levels need to be studied more directly.

Wind energy development can lead to guild-specific habitat loss in boreal forest bats

Forest management rarely considers protecting bats in Fennoscandian regions although all species rely on forest habitat at some point in their annual cycle. This issue is especially evident as wind parks have increasingly been developed inside Fennoscandian forests, against the advice of international bat conservation guidelines. In this study, we aimed to describe and explain bat community dynamics at a Norwegian wind park located in a boreal forest, especially to understand potential avoidance or attraction effects. The bat community was sampled acoustically and described using foraging guilds (short, medium, and long-range echolocators; SRE, MRE, LRE) as well as behavior (commuting, feeding and social calls). Sampling was undertaken at two locations per turbine: (i) the turbine pad and (ii) a paired natural habitat at ground level, as well as from a meteorological tower. We used a recently developed method for camera trapping nocturnal flying insects synchronously with bat acoustic activity. Our results reveal trends in feeding and general bat activity across foraging guilds in relation to insect availability, habitat type, wind, temperature, and seasonality. We show how seasonal patterns in behavior across guilds were affected by habitat type, temperature, and wind. We found that SRE commuting and especially feeding activity was highest in natural habitats, whereas LRE overall activity at habitats more season dependent. We found that nocturnal insect availability was positively correlated with total bat feeding activity throughout the night. Our results provide evidence for both direct and indirect risks to bat communities by wind parks: SRE bat habitat is lost to wind energy infrastructure and LRE bat may have an increased risk of fatality. Our findings provide important insights on seasonal and spatial variability in bat activity, which can inform standardizing monitoring of bats acoustically in boreal forests, at wind parks, and in combination with non-invasive insect monitoring.

Supplement of "Algorithm for continual monitoring of fog life cycles based on geostationary satellite imagery as a basis for solar energy forecasting"

The file uploaded here is an animation that visually illustrates the outputs of the a newly developed machine learning based FLS (Fog and Low Stratus) detection algorithm for the SEVIRI (Spinning Enhanced Visible and InfraRed Imager) instrument onboard the MSG (Meteosat Second Generation) geo-stationary satellites over the 24hr cycle of the day for the day of 02/March/2021 and compares them with the corresponding raw channel values observed by SEVIRI. The proposed algorithm classifies each SEVIRI pixel as "clear-sky", "FLS", or "non-FLS-cloud" (identified with Khaki, Red, and Blue in the animation) based on the SEVIRI pixel values of BT12.0, BT8.7 - BT12.0, BT10.8 - BT12.0, and BT12.0 - BT13.4 plus the standard deviation of each of these variables in a spatial window sized 3x3 pixels with the central pixel being the target pixel.  In this animation, the left-hand panel shows a false-color RGB image constructed based on the SEVIRI raw channel data with the red, green, and blue channels being BT12.0- BT13.4, BT8.7 - BT12.0, and BT10.8 - BT12.0, respectively. In this panel, the green color represents the high clouds, and the light and dark red colors represent the clear-sky and FLS, respectively. The right-hand panel of this animation also shows the outputs of the ML FLS detection algorithm developed in the present study.

opencc-zeroDec 2023View details →

Coordinates of the low-lying energy Agn isomers and the Agn-Tyr complexes

Noble metal clusters with a size around the Fermi wavelength of electrons display quantum confinement effects and properties such as photoluminescence, two-photon absorption, and second and third-harmonic generation. As a result of these unique features, noble metal clusters are increasingly gaining popularity in optics and catalysis. Being highly reactive, it is standard practice to use capping agents to stabilize them. This dataset contains the structural parameters for the low-lying energy Agn isomers and the Agn-Tyr complexes from n = 3–12, all fully optimized at the B3PW91 functional combined with the def2-TZVP basis set. The structural parameters were obtained using a global search strategy combined with DFT calculations to explore the potential energy surface of clusters of atoms and molecules.

Blockchain Topics in energy sector from CoinDesk

This dataset includes articles related to blockchain technology used in energy application. The dataset includes section, title, timestamp, author, and corpus. This dataset is used to spot relevant topics discussed on CoinDesk. Please consider that this dataset will be extended with more information from other forum.

MP2 potential energy surface of HeH2p

MP2 potential energy surface of HeH2p Authors: L.I. Vazquez-Salazar and M. Meuwly This repository contains the data to construct the potential energy surface at MP2 level with the basis set aug-cc-pVTZ for the HeH_{2}^{+} system obtained with the MOLPRO software. Inside the folder, detailed instructions are available.Contact For any questions, please contact  Markus Meuwly (m.meuwly@unibas.ch) or Luis Vazquez-Salazar (luisitza.vazquezsalazar@unibas.ch)  Reference Horn, K. P., Vazquez-Salazar, L. I., Koch, C. P., & Meuwly, M. (2023). Improving Potential Energy Surfaces Using Experimental Feshbach Resonance Tomography. arXiv preprint arXiv:2309.16491.

PyPSA-PL: Sectorally-integrated modelling of the Polish energy system until 2040

This record contains all the scripts and data from the PyPSA-PL modelling exercise that supported the report:<ul><li>Kubiczek, P., Smoleń, M., Żelisko, W. (2023). Polska prawie bezemisyjna. Cztery scenariusze transformacji energetycznej do 2040 r. Instrat Policy Paper 06/2023. <a href="https://www.instrat.pl/polska-2040">https://www.instrat.pl/polska-2040</a></li></ul>The record structure is based on the PyPSA-PL repository <a href="https://github.com/instrat-pl/pypsa-pl">https://github.com/instrat-pl/pypsa-pl</a> (v2.1).

Large-Scale Traveling Ionospheric Disturbances over the European sector during the geomagnetic storm on March 23-24, 2023: energy deposition in the source regions and the propagation characteristics

IMAGE 2D Ionospheric Equivalent Currents for 23 and 24 March 2023 (https://space.fmi.fi/image/).  We thank the institutes who maintain the IMAGE Magnetometer Array (<a href="https://space.fmi.fi/image/">https://space.fmi.fi/image/</a>): Tromsø Geophysical Observatory of UiT the Arctic University of Norway (Norway), Finnish Meteorological Institute (Finland), Institute of Geophysics Polish Academy of Sciences (Poland), GFZ German Research Centre for Geosciences (Germany), Geological Survey of Sweden (Sweden), Swedish Institute of Space Physics (Sweden), Sodankylä Geophysical Observatory of the University of Oulu (Finland), DTU Technical University of Denmark (Denmark), and Science Institute of the University of Iceland (Iceland). The provisioning of data from AAL, GOT, HAS, NRA, VXJ, FKP, ROE, BFE, BOR, HOV, SCO, KUL, and NAQ is supported by the ESA contracts number 4000128139/19/D/CT as well as 4000138064/22/D/KS. The authors would like to thank Dr. Liisa Juusola for providing the IMAGE 2D Ionospheric Equivalent Currents data.

openDec 2023View details →

Model America - Summer 2020 Arizona Building Energy Simulation Results from ORNL's AutoBEM

Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (<a href="https://bit.ly/AutoBEM">bit.ly/AutoBEM</a>). Data is provided for 2,555,152 buildings located within the boundary of Arizona in the United States: Data (1.48GB *.csv) - Arizona 2,555,152 building information data with simulation results separated by county. (Simulation results are for June 1st-August 31st, 2020) Building Information Data Fields: <ul> <li>ID</li> <li>CZ</li> <li>Centroid</li> <li>State_Abbr</li> <li>Footprint2D</li> <li>Height,Area2D</li> <li>BuildingType</li> <li>NumFloors</li> <li>Area</li> <li>Standard</li> <li>NumWalls</li> <li>WWR_surfaces</li> </ul> Energy Simulation Data Fields: <ul> <li>Electricity_Facility[kBTU]</li> <li>NaturalGas_Facility[kBTU]</li> <li>Heating_Electricity[kBTU]</li> <li>Cooling_Electricity[kBTU]</li> <li>Heating_NaturalGas[kBTU]</li> <li>Heating_Total[kBTU]</li> <li>WaterSystems_Electricity[kBTU]</li> <li>Lighting_Electricity[kBTU]</li> <li>Equipment_Electricity[kBTU]</li> <li>Fans_Electricity[kBTU]</li> <li>Pumps_Electricity[kBTU]</li> <li>HeatRejection_Electricity[kBTU]</li> <li>HeatRecovery_Electricity[kBTU]</li> <li>Surface_Outside_Face_Heat_Emission[GJ]</li> <li>Zone_Exfiltration_Heat_Loss[GJ]</li> <li>Zone_Exhaust_Air_Heat_Loss[GJ]</li> <li>Heat_Rejection_Energy[GJ]</li> <li>Anthropogenic_Emissions[GJ]</li> </ul> This data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), and Biological and Environmental Research (BER).

[Data] Real-time monitoring and quality assurance for laser-based directed energy deposition: integrating co-axial imaging and self-supervised deep learning framework

The experimental setup utilized a co-axial color Charged Couple Device (CCD) camera, integrated into the laser deposition head. This camera operates at a frame rate of 30 frames per second and captures the morphology of the process area. The captured images consist of three RGB channels with a 640 × 480 pixels resolution. To enable the camera to capture the radiation from the process zone, a beam splitter is installed on Precitec's laser applicator head. An optical notch filter within the 650–675 nm range also blocks the laser wavelengths. The dataset consists of four categories that covers the process map of DED process [.rar file]. The dataset consist of around 48,000 images that are labelled into 4 categories [P1-P2-P3-P4]. The images correspond to DED process zone captured co-axially The categories are function of linear laser energy deposited. The folder is already split into Train and Test.

Research Landscape of Energy Transition and Green Finance: A Bibliometric Analysis

Dataset for article title "Research Landscape of Energy Transition and Green Finance: A Bibliometric Analysis".

Energy cascades in surface semi-geostrophic turbulence

This dataset contains the Matlab figures, scripts, and .mat data files used in the paper "Energy cascades in surface semi-geostrophic turbulence" to be submitted to JGR-Oceans. "Figures?.fig" are the matlab figures, where "?" is a integer varying from 1-9. "Figures?.m" is the matlab script which loads the "Figure?.mat" data to create "Figure?.fig" figure.