Find research datasets worth reusing

Dataset for Learning in Continuous Action Space for Developing High Dimensional Potential Energy Models

The NN potentials developed in this study and the other available MLIP methods such as GAP, SNAP, qSNAP, and MEGNET used for benchmarking.

Development of strategy for combined smart ventilated window and PCM energy storage control for residential building energy saving

The dataset includes the published data in the article Development of strategy for combined smart ventilated window and PCM energy storage control for residential building energy saving. For the details of the data description please refer to the paper.

Large-eddy simulation of airborne wind energy farms: AWES virtual flight data

Large-eddy simulation of airborne wind energy farms: AWES virtual flight data. This dataset contains virtual flight data collected from individual systems in airborne wind energy parks obtained by means of large-eddy simulations. All data are stored as Python dictionary objects in the Pickle format. Additional Python scripts are provided to visualize the data.

Supplementary Materials for publication in Energies

This archive contains four video animation of high-speed OH* chemiluminescence imaging of methane flame and syngas flames in a model gas-turbine combustor at normal and elevated conditions

Dataset for analysis of the value of energy for wave, wind and solar power

Data and code for: Vrana, Til Kristian, & Svendsen, Harald G. (2021). Quantifying the Market Value of Wave Power compared to Wind&Solar - a case study. The 9th Renewable Power Generation Conference - RPG Dublin Online 2021 (RPG 2021),  (https://doi.org/10.1049/icp.2021.1383)

Energy Scenarios Tool - JRC - data behind the tool

This dataset includes the data behind the JRC Energy Scenarios Tool that is available online on <a href="https://visitors-centre.jrc.ec.europa.eu/en/media/tools/energy-scenarios-explore-future-european-energy">https://visitors-centre.jrc.ec.europa.eu/en/media/tools/energy-scenarios-explore-future-european-energy</a>  The aim of this tool is to explain how energy is produced and used in the EU, today and in the future. The tool helps to understand the magnitude and speed of the projected changes, in other words, to understand the energy transition.

Data for "Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa"

This is the data used for "Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa using the improved SSiB4/TRIFFID-Fire model". The data includes two folders: fireon and fireoff representing the scenarios with the fire model turned on and off. Each folder includes 14 years of data from 2000-2013.

opencc-by-4.0Jan 2022View details →

Datasets for: Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy

The datasets and supplementary materials for the manuscript "Group Contribution and Machine Learning Approaches to Predict Abraham Solute Parameters, Solvation Free Energy, and Solvation Enthalpy". Citations should refer directly to the manuscript (refer to the DOI <a href="https://doi.org/10.1021/acs.jcim.1c01103">10.1021/acs.jcim.1c01103</a>). The preprint version of of the manuscript is also available at: <a href="https://doi.org/10.33774/chemrxiv-2021-djd3d-v2">10.33774/chemrxiv-2021-djd3d-v2</a>   Regarding "Solvation_data-1.0.0.zip": The datasets include the curated data for: (1) Abraham solute parameters, (2) solvation free energy, (3) solvation enthalpy, (4) gas-water partition coefficient (logKw), (5) water-1-octanol partition coefficient (logPow). The fitted Abraham and Mintz solvent parameters are also included. Detailed information can be found in the "README.txt" file of the zip file.   Regarding "ML_model_files.zip": This contains the machine learning model files for SoluteML and DirectML. For the instruction on how to use it, please refer to the chemprop_solvation git repository (<a href="https://github.com/fhvermei/chemprop_solvation">https://github.com/fhvermei/chemprop_solvation</a>)

opencc-zeroDec 2021View details →

Data from: The active mouse rests within: Energy management among and within individuals

1. The relationship between daily energy expenditure (DEE) and resting metabolic rate (RMR) provides insight into how organisms allocate energy to maintenance versus energetically expensive activities such as locomotor activity. 2. Three models have been devised to describe energy management: the allocation, independent, and performance models, which respectively predict a DEE-RMR slope of b<1, b=1, and b>1. 3. Here, we took paired repeated metabolic and behavioural measurements in 51 female white-footed mice to 1) evaluate which energy management models apply at the among- and within-individual levels, and to 2) quantify the relationship between metabolic traits and two energetically expensive behaviours. 4. The DEE-RMR slope was different at the among- versus within-individual levels, with values supporting the performance and allocation models at the among- and within-individual levels, respectively. Accordingly, the relationship between voluntary wheel running and RMR was positive at the among-individual level (r = 0.40±0.21), but negative at the within-individual level (r = -0.23±0.10). 5. To our knowledge, this is the first study to simultaneously partition the relationship between RMR and behaviour at the among- versus within-individuals levels while determining which energy management models apply at each of these levels. In doing so, we have identified a mechanism through which compensation occurs at the within-individual level.

Case studies used in the test of the MCDA-MSS for energy systems analysis, described according to its 156 features

Case studies used in the test of the MCDA-MSS, described according to its 156 features.

opencc-zeroJan 2022View details →

Effects of embryo energy, egg size and larval food supply on the development of asteroid echinoderms

Organisms have limited resources available to invest in reproduction, causing a tradeoff between the number and size of offspring. One consequence of this tradeoff is the evolution of disparate egg sizes and, by extension, developmental modes. In particular, echinoid echinoderms (sea urchins and sand dollars) have been widely used to experimentally manipulate how changes in egg size affect development. Here we test the generality of the echinoid results by 1) using laser ablations of blastomeres to experimentally reduce embryo energy in the asteroid echinoderms (sea stars), Pisaster ochraceus and Asterias forbesi and 2) comparing naturally produced, variably-sized eggs (1.7 fold volume difference between large and small eggs) in A. forbesi. In P. ochraceus and A. forbesi there were no significant differences between juveniles from both experimentally reduced embryos and naturally produced eggs of variable size. However, in both embryo reduction and egg size variation experiments, simultaneous reductions in larval food had a significant and large effect on larval and juvenile development. These results indicate that 1) food levels are more important than embryo energy or egg size in determining larval and juvenile quality in sea stars and 2) the relative importance of embryo energy or egg size to fundamental life history parameters (time-to and size-at metamorphosis), does not appear to be consistent within echinoderms.

opencc-by-4.0Jan 2022View details →

Data for Structure of Energy Precipitation Induced by Superbolt-Lightning Generated Whistler Waves

This is the dataset for the publication Structure of Energy Precipitation Induced by Superbolt-Lightning Generated Whistler Waves. Detailed instruction attached within.

opencc-by-4.0Jan 2022View details →

An Artificial Intelligence Dataset for Solar Energy Locations in India

To expedite development of solar energy, land use planners will need access to up-to-date and accurate geo-spatial information of PV infrastructure. In this work, we develop a machine learning model to map utility-scale solar projects across India using freely available satellite imagery. Model predictions were validated by human experts to obtain a total of 1438 solar farms. We also estimate the solar footprint across India and quantified the degree of land modification associated with land cover types that may cause conflicts. Our analysis indicates that over 74% of solar development in India was built on landcover types that have natural ecosystem preservation, and agricultural values. Our work increases the feasibility of long-term monitoring of renewable energy deployment targets.

opencc-zeroJan 2022View details →

Brain size, gut size and cognitive abilities: the energy trade-offs tested in artificial selection experiment

The enlarged brains of homeotherms bring behavioural advantages, but also incur high energy expenditures. The 'Expensive Brain' (EB) hypothesis posits that the energetic costs of the enlarged brain and the resulting increased cognitive abilities (CA) were met either by increased energy turnover or reduced allocation to other expensive organs, such as the gut. We tested the EB hypothesis by analyzing correlated responses to selection in an experimental evolution model system, which comprises line types of laboratory mice selected for high or low basal (BMR), or high maximum (VO2max) metabolic rates. The traits are implicated in the evolution of homeothermy, having been pre-requisites for the encephalisation and exceptional CA of mammals, including humans. High-BMR mice had bigger guts, but not brains, than mice of other line types. Yet, they were superior to the other line types in the cognitive tasks carried out in both reward and avoidance learning contexts. Furthermore, the high-BMR mice had higher neuronal plasticity (indexed as the long-term potentiation, LTP) than their counterparts. Our data indicate that the evolutionary increase of CA in mammals was initially associated with increased BMR and brain plasticity. It was also fueled by an enlarged gut, which was not traded off for brain size.

opencc-by-4.0Feb 2022View details →

Non-local eddy-mean Kinetic Energy transfers

Animation of eddy-mean Kinetic Energy transfers during the decorrelation phase of 120-day long, 20-member ensemble simulations of the Western Mediterranean basin. The three terms are associated with the kinetic energy equation of the ensemble mean flow (left), that of the turbulent flow (center) and that of the ensemble mean of the full flow (right). The latter is associated with non-local eddy-mean KE transfers.

opencc-by-4.0Feb 2022View details →

Acoustic propulsion of nano- and microcones: dependence on particle size, acoustic energy density, and sound frequency

Supplementary data for the following manuscript: Johannes Voß, Raphael Wittkowski, "Acoustic propulsion of nano- and microcones: dependence on particle size, acoustic energy density, and sound frequency".

Proximate and evolutionary sources of variation in offspring energy expenditure in songbirds

Aim: Understanding variation in offspring energy expenditure is important because energy is critical for growth and development. Weather may exert proximate effects on offspring energy expenditure, but in altricial species these might be masked by parental care and huddling with siblings. Such effects are particularly important to understand given changing global weather patterns, yet studies of wild offspring in the presence of parental care are lacking. Offspring energy expenditure may also vary among species due to evolved responses to environmental selection pressures, requiring studies at both proximate and ultimate levels. Location: USA, South Africa, Malaysia. Time period: 2016-2019. Major taxa studied: Songbirds. Methods: We used the doubly-labeled water technique to estimate nestling daily energy expenditure of 54 songbird species across three continents. We used Bayesian phylogenetic mixed models to test proximate and evolutionary causes of variation in offspring energy expenditure while accounting for phylogeny and phylogenetic uncertainty. Results: Offspring energy expenditure increased with more rainfall and colder air temperatures, but decreased among offspring in broods with more siblings. Across species, nestling and adult mortality, but not growth rate, were positively associated with offspring energy use. Main conclusions: Weather had clear proximate effects on offspring energy expenditure and parents were either unable or unwilling to fully offset these effects. However, the decrease in offspring energy use when huddling with more siblings demonstrated a modulating effect of life history traits. For example, high nest predation rates favor reduced parental care and can force offspring to spend more energy coping with environmental conditions. Furthermore, reduced energy expenditure is thought to facilitate increased longevity, which is increasingly realized with lower extrinsic mortality rates, providing an explanation for the positive association between adult mortality and offspring energy expenditure. Ultimately, both proximate and evolutionary influences need to be considered to better understand causes of offspring energetics.

Energy expenditure does not explain step length-width choices during walking

Healthy young adults have a most preferred walking speed, step length, and step width that are close to energetically optimal. However, people can choose to walk with a multitude of different step lengths and widths, which can vary in both energy expenditure and preference. Here we further investigate step length-width preferences and their relationship to energy expenditure. In line with a growing body of research, we hypothesized that people's preferred stepping patterns would not be fully explained by metabolic energy expenditure. To test this hypothesis we used a two-alternative forced-choice paradigm. Fifteen participants walked on an oversized treadmill. Each trial participants experienced two stepping patterns and then chose the pattern they preferred. Over time, we adapted the choices such that there was 50% chance of choosing one pattern over another (equally preferred). If people's preferences are based solely on metabolic energy expenditure, then these equally preferred stepping patterns should have equal energy expenditure. We found that energy expenditure differed across equally preferred step length-width patterns (p < 0.001). On average, longer steps with higher energy expenditures were preferred over shorter and wider steps with lower energy expenditures (p < 0.001). We also asked participants to rank a set of shorter, wider, and longer steps from most preferred to least preferred, and from most energy expended to least energy expended. Only 7/15 participants had the same rankings for their preferences and perceived energy expenditure. Our results suggest that energy expenditure is not the only factor influencing a person's conscious gait choices. --

Short term grass bud response to high and low energy fires

Increasingly, land managers have attempted to use extreme prescribed fire as a method to address woody plant encroachment in savanna ecosystems. The effect that these fires have on herbaceous vegetation is poorly understood. We experimentally examined immediate (<24hr) bud response of two dominant graminoids, a C3 caespitose grass, Nassella leucotricha, and a C4 stoloniferous grass, Hilaria belangeri, following fires of varying energy (J/m2) in a semi-arid savanna in the Edwards Plateau ecoregion of Texas. Treatments included high- and low-energy fires determined by contrasting fuel loading and a no burn (control) treatment. Belowground axillary buds were counted and their activities classified to determine immediate effects of fire energy on bud activity, dormancy, and mortality. High-energy burns resulted in immediate mortality of N. leucotricha and H. belangeri buds (P < 0.05). Active buds decreased following high-energy and low-energy burns for both species (P < 0.05). In contrast, bud activity, dormancy, and mortality remained constant in the control. In the high-energy treatment, 100% (n=24) of N. leucotricha individuals resprouted while only 25% (n=24) of H. belangeri individuals resprouted (P < 0.0001) three weeks following treatment application. Bud depths differed between species and may account for this divergence, with average bud depths for N. leucotricha 1.3 cm deeper than H. belangeri (P < 0.0001). Synthesis and applications: Our results suggest that fire energy directly affects bud activity and mortality through soil heating for these two species. It is imperative to understand how fire energy impacts the bud banks of grasses to better predict grass response to increased use of extreme prescribed fire in land management.

Data from: Energy and physiological tolerance explain multi-trophic soil diversity in temperate mountains

Aim – Although soil biodiversity is extremely rich and spatially variable, both in terms of species and trophic groups, we still know little about its main drivers. Here, we contrast four long-standing hypotheses to explain the spatial variation of soil multi-trophic diversity: energy, physiological tolerance, habitat heterogeneity, and resource heterogeneity. Location – French Alps Methods – We built on a large-scale observatory across the French Alps (Orchamp) made of seventeen elevational gradients (~90 plots) ranging from low to very high altitude (280 - 3160 m), and encompassing large variations in climate, vegetation and pedological conditions. Biodiversity measurements of 36 soil trophic groups were obtained through environmental DNA metabarcoding. Using a machine learning approach, we assessed 1) the relative importance of predictors linked to different ecological hypotheses in explaining overall multi-trophic soil biodiversity, and 2) the consistency of the response curves across trophic groups. Results – We showed that predictors associated with the four hypotheses had a statistically significant influence on soil multi-trophic diversity, with the strongest support for the energy and physiological tolerance hypotheses. Physiological tolerance explained spatial variation in soil diversity consistently across trophic groups, and was an especially strong predictor for bacteria, protists and microfauna. The effect of energy was more group-specific, with energy input through soil organic matter strongly affecting groups related to the detritus channel. Habitat and resource heterogeneity had overall weaker and more specific impacts on biodiversity with habitat heterogeneity affecting mostly autotrophs, and resource heterogeneity affecting bacterivores, phytophagous insects, enchytraeids and saprotrophic fungi. Main Conclusions – Despite the variability of responses to the environmental drivers found across soil trophic groups, major commonalities on the ecological processes structuring soil biodiversity emerged. We conclude that among the major ecological hypotheses traditionally applied to aboveground organisms, some are particularly relevant to predict the spatial variation in soil biodiversity across the major soil trophic groups.