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282 results for “data engineering”
Supporting Data for Human Factors in Developing Automated Vehicles:A Requirements Engineering Perspective
<p>This data set complements our manuscript in submission with the title:</p> <p>"Human Factors in Developing Automated Vehicles: A Requirements Engineering Perspective"</p> <p>We provide two files:</p> <p>a) the interview guide</p> <p>b) an overview that maps from themes to example quotes and codes derived from particular interview subjects</p>
Towards a Data-Driven Requirements Engineering Approach: Automatic Analysis of User Reviews
<p>6000 French user reviews from three applications on Google Play (Garmin Connect, Huawei Health, Samsung Health) are labelled manually. We selected four labels: rating, bug report, feature request and user experience.</p> <ul> <li><strong>Ratings</strong> are simple text which express the overall evaluation to that app, including praise, criticism, or dissuasion.</li> <li><strong>Bug reports</strong> show the problems that users have met while using the app, like loss of data, crash of app, connection error, etc.</li> <li><strong>Feature requests</strong> reflect the demande of users on new function, new content, new interface, etc.</li> <li>In <strong>user experience</strong>, users describe their experience in relation to the functionality of the app, how does certain functions be helpful.</li> </ul> <p>As we can observe from the following table, that shows examples of labelled user reviews, each review belongs to one or more categories.</p> <table> <tbody> <tr> <th>App</th> <th>Total</th> <th>Rating</th> <th>Bug report</th> <th>Feature request</th> <th>User experience</th> </tr> </tbody> <tbody> <tr> <td>Garmin Connect</td> <td>2000</td> <td>1260</td> <td>757</td> <td>170</td> <td>493</td> </tr> <tr> <td>Huawei Health</td> <td>2000</td> <td>1068</td> <td>819</td> <td>384</td> <td>289</td> </tr> <tr> <td>Samsung Health</td> <td>2000</td> <td>1324</td> <td>491</td> <td>486</td> <td>349</td> </tr> </tbody> </table> <p> </p> <h2>New Dataset</h2> <p>Based on this dataset, we developed a labeled dataset containing 6,000 English and 6,000 French reviews for classification, as well as 1,200 bilingual reviews for clustering. The new dataset has been made publicly available on Zenodo at the following link: <a href="../records/11066414">https://zenodo.org/records/11066414</a></p>
Replication package for Workshop on Software Engineering 22' - What does the pytest plugins data say?
<p>This database stores the information used to run the experiment in the article: <strong>What does the pytest plugins data say?</strong></p>
Proactive Conflict Detection for Collaborative Model-driven Software Engineering (Evaluation Data)
<p>Results of the evaluation for the paper "Proactive Conflict Detection for Collaborative Model-driven Software Engineering"</p>
Data from: Exotic megaherbivores as ecosystem engineers in Australian savannas: Do they facilitate predator movement?
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Data and R code from: Relics of beavers past: time and population density drive scale-dependent patterns of ecosystem engineering
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Data and R code from: Pollination interactions reveal direct costs and indirect benefits of plant–plant facilitation for ecosystem engineers
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Data and code from: Engineering bacteriophages through deep mining of metagenomic motifs
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Data from: A pattern-oriented simulation for forecasting species spread through time and space: A case study on an ecosystem engineer on the move
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Data for marine fungi engineered to convert D-galacturonic acid to galactaric acid
<p>Two Excel files are stored, related to the successful engineering of two marine fungi (<em>Trichoderma</em> sp. LF328 and <em>Coniochaeta sp</em>. MF729) for the production of galactaric (mucic) acid from D-galacturonic acid, which is described in Vidgren et al. 2020. One file contains the HPLC data for cultivations carried out in 24-well plates with medium containing D-galacturonic acid, poly-D-galacturonic acid or pectin as a source of D-galacturonic acid, with lactose, xylose, glucose or glycerol as co-substrates. Cultures were sampled on days 3, 4 and 6, and sometimes on days 5 and 7, as indicated in the data. Data for negative results (e.g. lack of consumption of galactaric acid by the parent strains) is also included.</p> <p>The second file contains the HPLC data for cultivations carried out in 1 (<em>Coniochaeta sp</em>. C1) or 1.5 L (<em>Trichoderma</em> sp. T2) bioreactors, with information on culture volume and product yield for <em>Trichoderma</em> sp. T2.</p>
Data from: Migrating bison engineer the green wave
<p>Newly emerging plants provide the best forage for herbivores. To exploit this fleeting resource, migrating herbivores align their movements to surf the wave of spring green-up. With new technology to track migrating animals, the Green Wave Hypothesis has steadily gained empirical support across a diversity of migratory taxa. This hypothesis assumes the green wave is controlled by variation in climate, weather, and topography, and its progression dictates the timing, pace, and extent of migrations. However, aggregate grazers that are also capable of engineering grassland ecosystems make some of the world's most impressive migrations, and it is unclear how the green wave determines their movements. Here we show that Yellowstone's bison (Bison bison) do not choreograph their migratory movements to the wave of spring green-up. Instead, bison modify the green wave as they migrate and graze. While most bison surfed during early spring, they eventually slowed and let the green wave pass them by. However, small-scale experiments indicated that feedback from grazing sustained forage quality. Most importantly, a 6-fold decadal shift in bison density revealed that intense grazing caused grasslands to green up faster, more intensely, and for a longer duration. Our finding broadens our understanding of the ways in which animal movements underpin the foraging benefit of migration. The widely accepted Green Wave Hypothesis needs to be revised to include large aggregate grazers that not only move to find forage, but also engineer plant phenology through grazing, thereby shaping their own migratory movements.</p>
Data for 'Ultrafast strain engineering and coherent structural dynamics from resonantly driven optical phonons in LaAlO3'
<p>This folder contains all the raw data required to generate the figures in the work 'Ultrafast strain engineering and coherent structural dynamics from resonantly driven optical phonons in LaAlO3'. </p> <p> </p> <p><strong>Contents</strong></p> <p><em>Figure 2:</em></p> <p>(a) Time resolved balanced reflection data for the short and long time periods: LongTimeData.txt and ShortTimeData.txt. The corresponding Fourier spectra shown in the inset: InsetFourier_LongTimeData.txt and InsetFourier_ShortTimeData.txt</p> <p>(b) Time resolved polarization rotation data for the short and long time periods: LongTimeData.txt and ShortTimeData.txt. The corresponding Fourier spectra shown in the inset: InsetFourier_LongTimeData.txt and InsetFourier_ShortTimeData.txt</p> <p><em>Figure 3:</em></p> <p>(a) Time-resolved polarization rotation data after excitation at two different pump photon energies: trace_85meV_excitation.txt and trace_124meV_excitation.txt. Amplitude as function of central pump photon energy: Inset_Wavelength_dependence.txt and the absorption of LaAlO3: Inset_absorption.txt</p> <p>(b) The raw data for different polarizations: traces_angle_dependence.txt</p> <p>(c) The experimentally obtained (AmplitudeExperiment.txt) and DFT calculated values (AmplitudeDFT.txt).</p> <p><em>Figure 4</em></p> <p>(a) Fourier spectra (and double Gaussian fit) corresponding to time-resolved measurments after excitation at different central photon energies: FourierSpectraData.txt (and FourierSpectraFits). Inset: Extracted peak amplitude (Inset_StrainvsWavelength.txt) and Gaussian fit of the TA strain (Inset_GaussianFit.txt). </p> <p>(b)The TA/LA ratio as function of pump photon energy (SoundWaveRatio.txt) and the Lorentzian fit (RatioFit.txt). And the absorption of LaAlO3 (Absorption_coefficient.txt).</p> <p> </p> <p> </p> <p> </p> <p> </p>
Data of publication: Defect engineering for Quantum Grade Rare-Earth Nanocrystals
<p>Data corresponding to the figures of the publication "Defect Engineering for Quantum Grade Rare-Earth Nanocrystals" by S. Liu et al. (hhttps://pubs.acs.org/doi/10.1021/acsnano.0c02971). A text file describes data in each compressed folder, please refer to the publication for more details. </p>
Data from: Environmental gradients determine the potential for ecosystem engineering effects
Understanding processes that determine biodiversity is a fundamental challenge in ecology. At the landscape scale, physical alteration of ecosystems by organisms, called ecosystem engineering, enhances biodiversity worldwide by increasing heterogeneity in resource conditions and enhancing species coexistence across engineered and non-engineered habitats. Engineering-diversity relationships can vary along environmental gradients due to changes in the amount of physical structuring created by ecosystem engineering, but it is unclear how this variation is influenced by the responsiveness of non-structural abiotic properties to engineering. Here we show that environmental gradients determine the capacity for engineering to alter resource availability and species diversity, independent of the magnitude of structural change produced by engineering. We created an experimental rainfall gradient in an arid grassland where rodents restructure soils by constructing large, long-lasting burrows. We found that greater rainfall increased water availability and productivity in both burrow and inter-burrow habitats, causing a decline in local (alpha) plant diversity within both of these habitats. However, increased rainfall also resulted in greater differences in soil resources between burrow and inter-burrow habitats, which increased species turnover (beta diversity) across habitats and stabilized landscape-level (gamma) diversity. These responses occurred regardless of rodent presence and without changes in the extent of physical alteration of soils by rodents. Our results suggest that environmental gradients can influence the effects of ecosystem engineering in maintaining biodiversity via resource heterogeneity and species turnover. In an era of rapid environmental change, accounting for this interaction may be critical to conservation and management.
Data from: Macro-detritivores assist resolving the dryland decomposition conundrum by engineering an underworld heaven for decomposers
<p>Litter decomposition in most terrestrial ecosystems is regulated by moisture-dependent microorganism activity, among other things. <span class="fontstyle01"><span>Decomposition models typically underestimate rates of plant litter decomposition in drylands, suggesting the existence of additional drivers of decomposition. Attempts to reveal these drivers have predominantly focused on abiotic degradation agents, alternative moisture sources,</span></span> and <span class="fontstyle01"><span>soil-litter mixing</span></span>. The role of burrowing animals in promoting decomposition has received less attention despite greatly contributing to plant litter transfer from the harsh desert surface to the moister and nutrient-rich environment belowground. Our goal was to explore how macro-detritivore burrows affect plant litter mineralization dynamics. We introduced <sup>13</sup>C-labeled litter belowground into (1) desert isopod (<i>Hemilepistus reaumuri</i>) burrows and (2) artificial burrows, and aboveground on top of (3) isopod fecal pellet mounds and (4) bare soil crust. We compared the litter mass loss between the four treatments and used cavity ring-down spectroscopy to reveal the <i>in situ</i> mineralization dynamics. No litter mineralization was evident during the dry summer months both above- and belowground. Following rain events, mineralization rates spiked in all four micro-environments, quickly diminishing aboveground while slowly waning belowground. Total litter mass loss was twofold higher below- than aboveground and was significantly higher in isopod burrows compared to artificial burrows. Our findings demonstrate that burrowing macro-detritivores promote litter decomposition in deserts by transferring organic matter to their burrows where favorable climatic conditions and a nutrient-enriched environment foster microbial activity. Thus, attempts to resolve the dryland decomposition conundrum should not be limited to exploring factors that allow decomposition under harsh desert surface climatic conditions, but focus on the role that animals play in facilitating decomposer-friendly environments to which they translocate plant litter.</p>
Data from: Leaf-cutter ants engineer large nitrous oxide hot spots in tropical forests
Though tropical forest ecosystems are among the largest natural sources of the potent greenhouse gas nitrous oxide (N2O), the spatial distribution of emissions across landscapes is often poorly resolved. Leaf-cutter ants (LCA, Atta and Acromyrmex, Myrmicinae) are dominant herbivores throughout Central and South America and influence multiple aspects of forest structure and function. In particular, their foraging creates spatial heterogeneity by concentrating large quantities of organic matter (including nitrogen, N) from the surrounding canopy into their colonies, and ultimately, into colony refuse dumps. Here, we demonstrate that refuse piles created by LCA species Atta colombica in tropical rainforests of Costa Rica provide ideal conditions for extremely high rates of N2O production (high microbial biomass, potential denitrification enzyme activity, N content, and anoxia), and may represent an unappreciated source of heterogeneity in tropical forest N2O emissions. Average instantaneous refuse pile N2O fluxes surpassed background emissions by more than three orders of magnitude (in some cases exceeding 80,000 μg N2O-N m-2 h-1) and generating fluxes comparable to or greater than those produced by engineered systems such as wastewater treatment tanks. Refuse-concentrating Atta species are ubiquitous in tropical forests, pastures and production ecosystems, and increase density strongly in response to disturbance. As such, LCA colonies may represent an unrecognised greenhouse gas point source throughout the Neotropics.
Experimental Data for: Research Perspective on Supporting Software Engineering via Physical 3D Models
<p>Experimental data for the experiment presented in the technical report 1507: "Research Perspective on Supporting Software Engineering via Physical 3D Models"</p>
Research data supporting "Raman spectroscopy reveals new insights into the zonal organization of native and tissue-engineered articular cartilage"
<p>This file contains the raw research data supporting the publication above.</p>
Experimental Data of Air Heat Engine Characteristics
<p>Air heat engine characteristic experiment is an experimental method used to study the working principle, performance, and efficiency of air heat engines. An air heat engine is a device that uses thermal energy to compress and expand gases, thereby driving mechanical motion. During the experimental process, a small piston air compressor is usually used as the experimental object.</p>
Data from: Engineering self-deliverable ribonucleoproteins for genome editing in the brain
<p>The delivery of CRISPR ribonucleoproteins (RNPs) for genome editing <em>in vitro </em>and <em>in vivo</em> has important advantages over other delivery methods, including reduced off-target and immunogenic effects. However, effective delivery of RNPs remains challenging in certain cell types due to low efficiency and cell toxicity. To address these issues, we engineered self-deliverable RNPs that can promote efficient cellular uptake and carry out robust genome editing without the need for helper materials or biomolecules. Screening of cell-penetrating peptides (CPPs) fused to CRISPR-Cas9 protein identified potent constructs capable of efficient genome editing of neural progenitor cells. Further engineering of these fusion proteins identified a C-terminal Cas9 fusion with three copies of A22p, a peptide derived from human semaphorin-3a, that exhibited substantially improved editing efficacy compared to other constructs. We found that self-deliverable Cas9 RNPs generated robust genome edits in clinically relevant genes when injected directly into the mouse striatum. Overall, self-deliverable Cas9 proteins provide a facile and effective platform for genome editing <em>in vitro</em> and <em>in vivo</em>.</p>
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)
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.