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619 results for “configuration”
Plant response to habitat amount and configuration in Swedish forests
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Data from: Planning for climate change through additions to a national protected area network: implications for cost and configuration
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Data for: Ecosystem connectivity and configuration can mediate instability at a distance in metaecosystems
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Configurational crop heterogeneity increases within-field plant diversity
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Cooperative O-atom binding produces the active configuration for OH formation in high-temperature catalytic hydrogen oxidation
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Data from: Indirect effects of habitat amount mediated by habitat configuration determine bat diversity at the landscape-scale in Peninsular Malaysia
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Easy-to-configure zero-dimensional valley-chiral modes in a graphene point junction
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Namelists required to run sea ice and physics configuration of MITgcm for the West Antarctic Peninsula
<p>This dataset contains the namelists that describe the initial conditions, forcing files and specific package configurations used to run a sea ice and ocean physics configuration of the MITgcm (general circulation model) for the West Antarctic Peninsula (WAP). </p>
Artifacts of Paper "Understanding and Discovering Software Configuration Dependencies in Cloud and Datacenter Systems"
<p>This package contains all the artifacts (i.e. codes & datasets) we use in our paper "Understanding and Discovering Software Configuration Dependencies in Cloud and Datacenter Systems" accepted to FSE 2020.</p>
[CTD-ES][Larissa_Rocha] Feature Interactions in Highly Configurable Systems
<p>Video da minha apresentação do CTD-ES, SBES 2020. </p> <p>Título: "Feature Interactions in Highly Configurable Systems: A Dynamic Analysis Approach With VarXplorer"</p> <p>Autora: Larissa Rocha Soares (UFBA)<br> Advisor(s): Eduardo Almeida (UFBA), Ivan Machado (UFBA), Christian Kästner (Carnegie Mellon University)</p>
Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study
<p><strong>Slightly processed raw data for the paper 'Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study'</strong></p> <ul> <li>The processing include a spike removal to allow an interpolation to a common wavenumber axis.</li> <li>Always three files belong to each other: wavenumber axis file (wx_XYZ), spectral intensity file (spec_XYZ) and metadata file (meta_XYZ). The ‘XYZ’ refers to the samples measured (see the publication and its SI for details).</li> </ul>
Cluster configurations of the Hegselmann-Krause model on network ensembles
<p>This is the raw data underlying the results of the preprint [arxiv:2102.10910](https://arxiv.org/abs/2102.10910).</p> <p> </p> <p>## Data</p> <p>For each measured combination of the confidence and system size, there is one gzipped<br> file. For different ensembles, we collected data in different ranges and quality.<br> The paramters are:</p> <p>* Number of samples `m` per parameter combination<br> * Range `r` of confidences epsilon<br> * Distances `d` between values of epsilon (basically the resolution of the data)<br> * Largest size `N_max`</p> <p>The single files follow a naming scheme of `n{N}_e{epsilon}.cluster.dat.gz`, where<br> `{N}` signals the system size of the simulation and `{epsilon}` is the confidence<br> value of the simulation (without a decimal point, i.e., `0050` corresponds to `epsilon = 0.050`).<br> The sizes `N` are usually powers of two (or for the lattices, perfect squares close to powers of two).</p> <p>We present the data for each ensemble in one archive.</p> <p><br> * Fully connected `full.tar`<br> * `m = 1000`, `r = [0.0, 0.6]`, `d = 0.001`, `N_max = 262144`<br> * Barabasi Albert with a mean degree of 4 `BA4.tar`<br> * `m = 1000`, `r = [0.0, 0.6]`, `d = 0.002`, `N_max = 32768`<br> * Barabasi Albert with a mean degree of 10 `BA10.tar`<br> * `m = 1000`, `r = [0.0, 0.6]`, `d = 0.001`, `N_max = 65536`<br> * Square lattice with first nearest neighbors `lat1.tar`<br> * `m = 1000`, `r = [0.0, 0.6]`, `d = 0.001`, `N_max = 16384`<br> * Square lattice with second nearest neighbors `lat2.tar`<br> * `m = 1000`, `r = [0.0, 0.6]`, `d = 0.001`, `N_max = 16384`<br> * Square lattice with third nearest neighbors `lat3.tar`<br> * `m = 1000`, `r = [0.0, 0.6]`, `d = 0.001`, `N_max = 65536`<br> * Square lattice with fourth nearest neighbors `lat4.tar`<br> * `m = 1000`, `r = [0.0, 0.6]`, `d = 0.001`, `N_max = 65536`<br> * Square lattice with third nearest neighbors and 1% rewired edges `lat3_ws.tar`<br> * `m = 1000`, `r = [0.0, 0.3]`, `d = 0.001`, `N_max = 16384`<br> * connected Erdos Renyi with mean degree of 10 `ER10.tar`<br> * `m = 1000`, `r = [0.0, 0.3]`, `d = 0.002`, `N_max = 32768`</p> <p> </p> <p>## Data format</p> <p>Each final state is encoded as three lines:</p> <p>* The convergence time is a single integer with a line prefix '# sweeps: '<br> * The positions of all clusters in opinion space with a line prefix '# ' (unsorted)<br> * The number of agents in each of the clusters without a line prefix</p> <p> </p> <p>## Python example for reading the format</p> <p>An example script, which visualizes the S vs eps graph for the largest size of the fully connected<br> case, with a function to read this format is given in `example.py`.</p>
Using Code Reviews to Automatically Configure Static Analysis Tools
<p>Working dataset (check traceability oracle) used in the paper</p>
Molecular configuration data for the reactions between radicals of formamide and vinyl cyanide
<p>The files in the folder /datafile in SuppMater.zip contain optimized atomistic configurations of the reactant (RC), the intermediate (IM), the transition state (TS) and the product (PD) of the reactions between partially dehydrogenated radicals of formamide (H2NCHO) and vinyl cyanide (H2CCHCN) for producing 1H-pyrimidin-2-one (C4H4N2O). The data are obtained by using density functional theory calculations with the M06 functional with 6-31+G(d,p)/6-311++G(d,p) basis sets as implemented in Gaussian 16 B.01. The name of these file consists of two parts separated by "_" including the ID of the reaction (defined in the manuscript), and the molecular state name. For instance, "C4-TS2.data" stands for the 2nd transition state in the reaction C4. Each file may contain one or two molecules/radicals.</p> <p>The total number of the atoms in the first molecule will be read on the first line; the corresponding Gibbs free energy (G, in a.u., with thermal free energy correction at 100 K) on the second, and the atomic type and three atomic Cartesian coordinates on the following lines. The second molecule will be read after the first one in the same format, except for that G is already given with the first molecule for the entire state (of multiple molecules). The filenames started by "Cytosine", "Uracil" and "Thymine" correspond to the reactions between C4H4N2O and amino, methyl or hydroxyl to produce cytosine, thymine or uracil, respectively.</p> <p>The file "RateCoefficient.pdf" contains the rate coefficients as a function of the temperature for the most favourable pathways for the reactions between dehydrogenated formamide and vinyl cyanide.</p>
Data from: Landscape configuration alters spatial arrangement of terrestrial-aquatic subsidies in headwater streams
Context: Freshwater ecosystems depend on surrounding terrestrial landscape for resources. Most important are terrestrial leaf litter subsidies, which differ depending on land use. We lack a good understanding of the variation of these inputs across spatial scales. Objectives: We sought to determine: (1) the relative importance of local versus catchment-level forestation for benthic leaf litter biomass in streams, (2) how landscape configuration alters these relationships, and (3) how land use affects the quality and diversity of leaf litter subsidies. Methods: We measured biomass and identity of benthic leaf litter in 121 reaches in 10 independent catchments seasonally over the course of a year. We assessed direct and indirect effects of forestation, reach position, and seasonality on leaf litter biomass using structural equation models, and assessed how leaf litter diversity varied with land use. Results: In catchments with forested headwaters, the degree of forestation and reach position in the catchment influenced benthic leaf litter biomass indirectly through local reach-scale forestation. In catchments where forest was only located downstream, or with minimal forest, none of these factors influenced reach-level benthic leaf litter. Leaf litter diversity peaked in fall in all land use types, but was generally lowest in forested reaches. Conclusions: Not only habitat amount, but its location relative to other habitats is important for ecosystem function in the context of cross-ecosystem material flows. Here, lack of upstream forest altered spatial patterns of leaf litter storage. Studies with high spatiotemporal resolution may further reveal effects of landscape configuration on other ecosystems.
Data from: Local coastal configuration rather than latitudinal gradient shape clonal diversity and genetic structure of Phymatolithon calcareum maerl beds in North European Atlantic
Maerl beds are one of the world's key coastal ecosystems and are threatened by human activities and global change. In this study, the genetic diversity and structure of one of the major European maerl-forming species, Phymatolithon calcareum, was studied using eight microsatellite markers. Two sampling scales (global: North East Atlantic and regional: Galicia) were investigated and fifteen maerl beds from Atlantic Europe were sampled. At the regional-scale the location of sites outside and within four estuaries allowed to test for the influence of coastal configuration on population connectivity and genetic diversity. Results suggested that clonal reproduction plays an important role in the population dynamics of P. calcareum maerl beds. Clonality was variable among populations, even within the same region. At the European scale, these differences in clonality cannot be explained by the geographic or latitudinal distribution of the populations studied. A significant genetic differentiation was found among almost all population pairs and a positive correlation between geographic and genetic distances showed the limited dispersal capacity of P. calcareum. Moreover, a very clear pattern of genetic structure was revealed at the regional scale between populations located within and at the mouth of the estuaries. Genetic differentiation among estuaries was less marked for the sites located in outer-zones compared to those located in the inner-zones. In addition, variation in level of clonality linked to seascape was also observed: populations situated in the outer-zones of the estuaries were less clonal than those in the inner-zones. Finally, populations from the same estuary generally shared one or several mutilocus genotypes.
Data from: Configurational landscape heterogeneity shapes functional community composition of grassland butterflies
1. Landscape heterogeneity represents two aspects of landscape simplification: (i) compositional heterogeneity (diversity of habitat types) and (ii) configurational heterogeneity (number, size and arrangement of habitat patches); both with different ecological implications for community composition. 2. We examined how independent gradients of compositional and configurational landscape heterogeneity, at eight spatial scales, shape taxonomic and functional composition of butterfly communities in 91 managed grasslands across Germany. We used landscape metrics that were calculated from functional maps based on habitat preferences of individual species during different life stages. The relative effects of compositional and configurational landscape heterogeneity were compared with those of local land use intensity on butterfly taxonomic diversity, community composition and functional diversity of traits related to body size, feeding breadth and migratory tendency. 3. As expected, compositional heterogeneity had strong positive effects on taxonomic diversity while configurational heterogeneity had strong positive effects on trait dominance within the community. When landscapes had smaller mean patch size and greater boundary area, communities were dominated by species with more specialized larval feeding, decreased forewing length and limited migratory tendency. 4. The positive effects of increased configurational landscape heterogeneity outweighed the negative effects of local land use intensity on larval feeding specialization, at all spatial scales, highlighting its importance for specialists of all dispersal capabilities. 5. Synthesis and applications. We show that landscapes with high compositional heterogeneity support communities with greater taxonomic diversity, while landscapes with high configurational heterogeneity support communities that include vulnerable species (feeding specialists with larger body size, sedentary nature and more negatively affected by local management intensity). A decline in functional community composition can lead to functional homogenization, affecting the viability of the ecosystems by decreasing the variability in their responses to disturbance and altering their functioning. A landscape management for grasslands that promotes the maintenance of small patch sizes and a diversity of land-uses in the surrounding landscape (within 250–1000 m) is recommended for the conservation of diverse butterfly communities. These strategies could also benefit Government programs such as the EU 2020 Biodiversity Strategy in their efforts to reduce the loss of biodiversity in agricultural landscapes.
Data from: Temperature drives abundance fluctuations, but spatial dynamics is constrained by landscape configuration: implications for climate-driven range shift in a butterfly
1. Prediction of species distributions in an altered climate requires knowledge on how global- and local-scale factors interact to limit their current distributions. Such knowledge can be gained through studies of spatial population dynamics at climatic range margins. 2. Here, using a butterfly (Pyrgus armoricanus) as model species, we first predicted based on species distribution modelling that its climatically suitable habitats currently extend north of its realized range. Projecting the model into scenarios of future climate, we showed that the distribution of climatically suitable habitats may shift northward by an additional 400 km in the future. 3. Second, we used a 13-year monitoring data set including the majority of all habitat patches at the species' northern range margin to assess the synergetic impact of temperature fluctuations and spatial distribution of habitat, microclimatic conditions and habitat quality, on abundance and colonisation-extinction dynamics. 4. The fluctuation in abundance between years was almost entirely determined by the variation in temperature during the species' larval development. In contrast, colonisation and extinction dynamics were better explained by patch area, between-patch connectivity, and host plant density. This suggests that the response of the species to future climate change may be limited by future land-use and how its host plants respond to climate change. It is thus probable that dispersal limitation will prevent P. armoricanus from reaching its potential future distribution. 5. We argue that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate. It includes factors acting at the scale of habitat patches such as habitat quality and microclimate, and landscape-scale factors such as the spatial configuration of potentially suitable patches. Knowledge of population dynamics under various environmental conditions, and the incorporation of realistic scenarios of future land-use, appear thus essential to provide predictions useful for actions mitigating the negative effects of climate change.
Data from: Response of non-grassland avian guilds to adjacent herbaceous field buffers: testing hypotheses about configuration of targeted conservation practices in agricultural landscapes
1. A substantial part of the world's land base is dominated by agriculture, and forest habitat often consists of discrete patches of forest and linear woody corridors. These natural components provide habitat for some forest birds, but make conservation of these species difficult. In-field practices applied outside forest patches, such as specific juxtapositions of herbaceous field buffers adjacent to forest habitat, could increase avian diversity contributions of existing forest without creation of additional forest habitat. Our prediction was that herbaceous field buffers would increase bird richness in adjacent forest, and we evaluated four potential mechanisms. 2. We used bird count data from a conservation buffer monitoring program and hierarchical community models to estimate species richness of forest generalist, forest interior, and shrubland (edge) species near forest edges with and without adjacent herbaceous field buffers. We accounted for heterogeneity in detection probabilities and forest cover in surrounding landscapes when estimating species- and guild-level responses. 3. Consistent with the drift fence hypothesis, adjacent herbaceous buffers were associated with a modest increase in richness of forest interior birds in woody corridors, but not in forest blocks. Consistent with resource complementation, adjacent herbaceous buffers were associated with modest increases in richness of shrubland (edge) birds in both woody corridors and forest blocks. 4. Across all species and guilds, adjacent buffers generally associated with greater abundance (e.g. 28 of 39 species), but these increases were also relatively small and highly variable (i.e. overlapping 95% credible intervals). Corroborating existing research, effects of adjacent herbaceous buffers are likely real, but neither pervasive nor strong. 5. Synthesis and applications. Conservation practices targeted to grassland species often produce measurable conservation benefits for target species. However, biodiversity return for investment would be further increased if targeted practices could be deployed in ways that also produce benefits for non-target species in adjacent habitats. Our results suggest that additional benefits for non-target species using adjacent forest habitat are likely to be modest, so conservation planning should focus on species targeted by the conservation practices and avoidance of potential negative impacts on those species when positive benefits to adjacent habitat are weak or lacking.
Data from: Territory configuration moderates the frequency of extra-group mating in superb fairy-wrens
The frequency of extra-pair paternity (EPP) in socially monogamous birds varies substantially between and within species, but ecological drivers of this variation remain poorly understood. Habitat configuration could influence EPP by moderating access to extra-pair mates, because species occupying territories in a clustered 'honeycomb' configuration have a larger pool of potential extra-group mates in their immediate neighbourhood than those living in linearly arranged territories (e.g. along narrow strips of riparian or fragmented habitat). We exploited variation in the spatial arrangement of territories due to anthropogenic modification of habitat of the cooperatively breeding superb fairy-wren Malurus cyaneus to test whether habitat configuration influenced the frequency of EPP. In this species, most paternity is obtained by males outside the social group (extra-group paternity, EGP). We found that the frequency of EGP among groups living in linear strips of roadside vegetation (41% of 44 offspring) was lower than it was for groups living in clustered territories within continuous habitat (59% of 70 offspring). Differences in group size and pair relatedness did not explain differences in EGP associated with territory configuration, though the frequency of EGP was negatively correlated with pair relatedness. Our finding suggests that territory configuration can influence rates of EGP and that anthropogenic habitat fragmentation has the potential to limit access to extra-pair mates, affecting mating systems and ultimately fitness.
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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.