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221 results for “multi-scale”
Dataset: Multi-scale mosaics in top-down pest control by ants from natural coffee forests to plantations
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Long-term monitoring in endangered woodlands shows effects of multi-scale drivers on bird occupancy
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Multi-scale drivers of soil resistance predict vulnerability of seasonally wet meadows to trampling by pack stock animals in the Sierra Nevada, USA
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Multi-scale optical coherence tomography imaging and visualization of Vermeer's Girl with a Pearl Earring
<p>The data sets, software, and figures accompany the publication:</p> <p>"Multi-scale optical coherence tomography imaging and visualization of Vermeer's Girl with a Pearl Earring", Optics Express 28, 26239 (2020) <a href="https://doi.org/10.1364/OE.390703">https://doi.org/10.1364/OE.390703</a></p> <ul> <li>Fig4_largescaleOCT.pdf, high resolution image of figure 4 of the manuscript</li> <li>Fig5_mediumscaleOCT.pdf, high resolution image of figure 5 of the manuscript</li> <li>Fig6_smallscaleOCT.pdf, high resolution image of figure 6 of the manuscript</li> <li>GWPE_DEMO_V5.zip<br> Zip file of a Windows executable of the virtual rendering of the Girl with the Pearl Earring. The readme file describes the operation of the virtual rendering.</li> <li>Stitching_README.txt Describes the stitching software and the accompanying data sets</li> <li>MS-OCT surface data: <ul> <li>SurfaceStitchedKwadrant11.npy</li> <li>SurfaceStitchedKwadrant12.npy</li> <li>SurfaceStitchedKwadrant21.npy</li> <li>SurfaceStitchedKwadrant22.npy</li> <li>UpperInterfaceMatrixRawdataKwadrant11.npy</li> </ul> </li> <li>MS-OCT thickness data <ul> <li>FullResGlazeStratigraphyThicknessKwadrant11.npy</li> <li>FullResGlazeStratigraphyThicknessKwadrant12.npy</li> <li>FullResGlazeStratigraphyThicknessKwadrant21.npy</li> <li>FullResGlazeStratigraphyThicknessKwadrant22.npy</li> </ul> </li> <li>MS-OCT Scattering strength data <ul> <li>FullResScatteringStrengthKwadrant11.npy</li> <li>FullResScatteringStrengthKwadrant12.npy</li> <li>FullResScatteringStrengthKwadrant21.npy</li> </ul> </li> <li>Main.py, DataAnalysisFunctionsRepository.py, and ReadAndCombineKwadrantData.py are Python files for stitching the four quadrants of data together. Runs in Python >3.5. Full stitching image takes more than an hourFullResScatteringStrengthKwadrant22.npy</li> <li>Plot_measure.py and plot_fit.py<br> Analysis of the BRDF measurements of the black underlayer background (RU1) and glaze layer (RU5). Runs in Python > 3.5</li> <li>Visualization1.ave<br> Video of the multi-scale multi-parameter OCT data set of the Girl</li> <li>Visualization2.mp4<br> Video showing an impression of the interactive demo of the Girl <ul> </ul> </li> </ul>
Predictive multi-scale occupancy models at range-wide extents: effects of habitat and human disturbance on distributions of wetland birds
<p><span><i>Aim:</i> Predicting distributions is fundamental to ecology, yet hindered by spatially-restricted sampling, scale-dependent relationships, and detection error associated with field surveys. Predictive species distribution models (SDMs) are nonetheless vital for conservation of many species. We developed a framework for building predictive SDMs with multi-scale data, and used it to develop range-wide breeding-season SDMs for 14 marsh bird species of concern.</span></p> <p><span><i>Location: </i>USA.</span></p> <p><span><i>Methods: </i>We built SDMs using data from range-wide surveys conducted over 14 years, and habitat and disturbance covariates measured at multiple spatial scales. We built hierarchical occupancy models that included heterogeneity in detectability during sampling, and used Bayesian model selection to regulate model complexity (covariates and scales) based explicitly on spatial predictive abilities. We thus integrated model selection for optimizing out-of-sample prediction, range-wide sampling over broad conditions, multi-scale analyses and scale-optimization, and species-specific detectability for a suite of wide-ranging species. </span></p> <p><span><i>Results: </i>Distributions of marsh birds were affected by local wetland conditions, but also by agricultural, urban, and hydrologic disturbances operating from local scales (100 – 500 m) to the watershed level. Variables measuring human disturbances improved prediction for most species, and every species was affected by attributes at > 1 scale. Five species showed evidence for continental-scale range contraction during the study.</span></p> <p><span><i>Main conclusions: </i>We demonstrate how hierarchical occupancy models can be optimized for prediction across a species' range at the extent of a continent while also accounting for imperfect detection, and thus describe a generalizable approach that can be used for any species. We provide the first data-driven, empirical SDMs built at the range-wide extent for most of our 14 study species and demonstrate that previous studies focused on local distributions and the effects of fine-scale wetland vegetation missed important broad-scale drivers of occupancy for marsh birds. </span></p>
Data from: A theoretical foundation for multi-scale regular vegetation patterns
Self-organized regular vegetation patterns are widespread1 and thought to mediate ecosystem functions such as productivity and robustness, but the mechanisms underlying their origin and maintenance remain disputed. Particularly controversial are landscapes of overdispersed (evenly spaced) elements, such as North American Mima mounds, Brazilian murundus, South African heuweltjies, and, famously, Namibian fairy circles. Two competing hypotheses are currently debated. On the one hand, models of scale-dependent feedbacks, whereby plants facilitate neighbours while competing with distant individuals, can reproduce various regular patterns identified in satellite imagery. Owing to deep theoretical roots and apparent generality, scale-dependent feedbacks are widely viewed as a unifying and near-universal principle of regular-pattern formation, despite scant empirical evidence. On the other hand, many overdispersed vegetation patterns worldwide have been attributed to subterranean ecosystem engineers such as termites, ants, and rodents. Although potentially consistent with territorial competition, this interpretation has been challenged theoretically and empirically and (unlike scale-dependent feedbacks) lacks a unifying dynamical theory, fuelling scepticism about its plausibility and generality. Here we provide a general theoretical foundation for self-organization of social-insect colonies, validated using data from four continents, which demonstrates that intraspecific competition between territorial animals can generate the large-scale hexagonal regularity of these patterns. However, this mechanism is not mutually exclusive with scale-dependent feedbacks. Using Namib Desert fairy circles as a case study, we present field data showing that these landscapes exhibit multi-scale patterning—previously undocumented in this system—that cannot be explained by either mechanism in isolation. These multi-scale patterns and other emergent properties, such as enhanced resistance to and recovery from drought, instead arise from dynamic interactions in our theoretical framework, which couples both mechanisms. The potentially global extent of animal-induced regularity in vegetation—which can modulate other patterning processes in functionally important ways—emphasizes the need to integrate multiple mechanisms of ecological self-organization.
Data from: Research on the mechanical behavior of shale based on multi-scale analysis
In view of the difficulty in obtaining the mechanical properties of shale, the multi-scale analysis of shale was performed on a shale outcrop from the Silurian Longmaxi Formation in the Changning area, Sichuan Basin, China. The nano/micro indentation test is an effective method for multi-scale mechanical analysis. In this paper, effective criteria for the shale indentation test were evaluated. The elastic modulus was evaluated at a multi-scale and the engineering validation of drilling cuttings was performed. The porosity tests showed that the pore distribution of shale from the nano-scale to macro-pore could be better displayed by the nuclear magnetic resonance test. The micro-scale elastic modulus and hardness increased nonlinearly with the increase in the clay packing density. It was observed that the size effect of the micro-hardness was based on porosity and composition. The partial spalling of shale at the micro-scale could lead to irregular bulges or steps in a load–displacement curve. The elastic modulus of pure clay minerals was 24.2 GPa on the parallel bedding plane, and 15.8 GPa on the vertical bedding plane. The contact hardness (pure clay minerals) was 0.51 GPa. The indentation results showed that the micro elastic modulus of shale obeyed the normal distribution, and the statistical average could predict the macro mechanical properties effectively. The present work provides a novel idea regarding the cognitive mechanics state of shale in the formation.
Data from: Multi-scale model of CRISPR-induced coevolutionary dynamics: diversification at the interface of Lamarck and Darwin
The CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) system is a recently discovered type of adaptive immune defense in bacteria and archaea that functions via directed incorporation of viral and plasmid DNA into host genomes. Here, we introduce a multi-scale model of dynamic coevolution between hosts and viruses in an ecological context that incorporates CRISPR immunity principles. We analyze the model to test whether and how CRISPR immunity induces host and viral diversification and the maintenance of many coexisting strains. We show that hosts and viruses coevolve to form highly diverse communities. We observe the punctuated replacement of extant strains, so that populations have very low similarity compared over the long term. However in the short term, we observe evolutionary dynamics consistent with both incomplete selective sweeps of novel strains and the recurrence of previously rare strains. Coalitions of multiple dominant host strains are predicted to arise because host strains can have nearly identical immune phenotypes mediated by CRISPR defense albeit with different genotypes. We close by discussing how our explicit eco-evolutionary model of CRISPR immunity can help guide efforts to understand the drivers of diversity seen in microbial communities where CRISPR systems are active.
Data from: A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture
A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness.
Identifying relationships between multi-scale social-ecological factors to explore ungulate health in a Western Kazakhstan rangeland
<p>1. Rangelands are multi-use landscapes which are socially and ecologically important in different ways. Among other interactions, shared use of rangelands by wildlife and livestock can lead to disease transmission. Understanding wildlife and livestock health and managing disease transmission in rangelands requires an integration of social and ecological knowledge.</p> <p>2. Using the example of Western Kazakhstan, home to two types of ungulate hosts, the critically-endangered saiga antelopes, <i>Saiga tatarica</i>, and livestock, we conducted a cross-scale analysis of social-economic, ecological and climatic factors that contribute to transmission of diseases. We focused on Gastro-intestinal Nematodes (GINs) because they are transmitted between hosts that share pasture and they affect ungulate fitness. We used an interdisciplinary social-ecological methods approach which included conducting fecal egg counts of GINs in saigas and livestock, semi-structured interviews and focus group discussions with livestock owners and herders in the region, and triangulation of information through secondary sources.</p> <p>3. Livestock rearing was done in two ways a) village-based livestock and b) outlying farms. The latter overlapped more with saigas. Village-based livestock had significantly higher worm burdens than those on outlying farms, which had comparable burdens to saigas. Various factors exacerbate GIN prevalence and transmission: Veterinary services are minimal; both saiga and livestock numbers are increasing; and changing climate is increasing farmers' dependence on shared pastures for hay production. It will be crucial for saiga conservationists to engage in multi-pronged conservation interventions, which are evaluated and adapted through the lens of rural livelihoods and the livestock health on which they depend.</p> <p>4. <em>Synthesis and Application: </em>Our work provides researchers and practitioners with an avenue to better understand complex inter-relationships and plan interventions within rangelands, while viewing host health from an interdisciplinary perspective - ultimately working towards wildlife conservation whilst safeguarding livelihoods across the world's rangelands.</p>
Supplementary material to "Food and habitats requirements of the Scops Owl (Otus scops) in Switzerland revealed by very high-resolution multi-scale models"
<p><strong>Abstract</strong></p> <p>In Europe, agricultural practices have progressively evolved towards high productivity leading either to the intensification of productive and accessible areas or to the abandonment of less profitable sites. Both processes have led to the degradation of semi-natural habitats like extensive grasslands, threatening species such as the Eurasian Scops Owl <em>Otus scops</em> that rely on extensively managed agricultural landscapes. In this work, we aimed to assess the habitat preferences of the Scops Owl using habitat suitability models combined with a multi-scale approach. We generated a set of multi-scale predictors, considering both biotic and abiotic variables, built on two newly developed vegetation management and orthopteran abundance models. To select the variables to incorporate in a ‘best multi-scale model’, we chose the best spatial scale for each variable using univariate models and by calculating their relative importance through multi-model inference. Next, we built ensembles of small models (ESMs) at 10 different scales from 50 to 1000 m, and an additional model with each variable at its best scale (‘best multi-scale model’). The latter performed better than most of the other ESMs and allowed the creation of a high-resolution habitat suitability map for the species. Scops Owls showed a preference for dry sites with extensive and well-structured habitats with 30–40% bush cover, and relied strongly on semi-extensive grasslands covering at least 30% of the surface within 300 m of the territory centre and with high orthopteran availability near the centre (50-m radius), revealing a need for good foraging grounds near the nest. At a larger spatial scale within a radius of 1000 m, the habitat suitability of Scops Owls was negatively related to forest cover. The resulting ESM predictions provide valuable tools for conservation planning, highlighting sites in need of particular conservation efforts together with offering estimates of the percentage of habitat types and necessary prey abundance that could be used as targets in future management plans to ensure the persistence of the population.</p>
Identification of Plant Pests Using Multi-scale SE-Xception Model
<p>The pest dataset of plant pest recognition.</p>
Multi-scale plasticity homogenization of Sn–3Ag-0.5Cu: From β-Sn micropillars to polycrystals with intermetallics
<p>Data bundle for "Multi-scale plasticity homogenization of Sn–3Ag-0.5Cu: From β-Sn micropillars to polycrystals with intermetallics" <a href="https://doi.org/10.1016/j.msea.2022.143876">6</a> <a href="https://doi.org/10.1016/j.msea.2022.143876">https://doi.org/10.1016/j.msea.2022.143876</a> / <a href="https://doi.org/10.48550/arXiv.2208.11453">https://doi.org/10.48550/arXiv.2208.11453</a> </p> <table summary="Additional metadata"> <tbody> <tr> <td> </td> </tr> </tbody> </table> <p> </p> <p> </p>
A Multi-Scale Neuron Morphometry Dataset from Peta-voxel Mouse Whole-Brain Images
<p><span>Neuron morphology and sub-neuronal patterns offer vital insights into cell typing and the structural organization of brain networks. The community-collaborative BRAIN Initiative Cell Census Network (BICCN) project has yielded a vast amount of whole-brain imaging data. However, reconstructing multi-scale neuron morphometry at a whole-brain scale requires not only the integration of diverse hardware devices, tools, and algorithms but also a dedicated production workflow. To address these challenges, we developed a cloud-based, collaborative platform capable of handling peta-scale imaging data. Using this platform, we generated the largest multi-scale morphometry dataset from hundreds of sparsely labeled mouse brains. The morphometry dataset comprises 182,497 annotated cell bodies, 15,441 locally traced morphologies, and 1,876 fully reconstructed morphologies. We also identified sub-neuronal arborizations for both axons and dendrites, along with the primary axonal tracts connecting them. In addition, we identified 2.63 million putative boutons. All morphometric data were registered to the Allen Common Coordinate Framework (CCF) atlas. The morphometry dataset has proven to be an invaluable resource for whole-brain cross-scale morphological studies in mouse.</span></p>
Data of the article "Predicting the 2023/24 El Niño from a multi-scale and global perspective" that published in Communications Earth & Environment
<p>MATLAB data of the article "Predicting the 2023/24 El Niño from a multi-scale and global perspective" that published in Communications Earth & Environment.</p> <p>The article is available on the Communications Earth & Environment at <a title="Predicting the 2023/24 El Niño from a multi-scale and global perspective" href="https://www.nature.com/articles/s43247-024-01867-w">https://www.nature.com/articles/s43247-024-01867-w</a>.</p> <p>These data include ocean temperature, current, atmosphere wind, pressure, precipitation, heat flux, and more, that from reanalysis data and coupled model outputs. Additionaly, there are four figures of the article.</p> <p>The related MATLAB codes can be accessed from <a href="https://github.com/HRKsince1993/COMMSENV-24-1347.git">https://github.com/HRKsince1993/COMMSENV-24-1347.git</a></p> <p>If these data are helpful to you, please cite our article or acknowledge us in your publication, e. g.</p> <p>Hu, R. <em>et al.</em> Predicting the 2023/24 El Niño from a multi-scale and global perspective. <em>Commun. Earth Environ.</em> <strong>5</strong>, 675 (2024). </p> <p>If you have any questions, please contact Tao Lian (<a href="mailto:liantao@sio.org.cn">liantao@sio.org.cn</a>) and/or Dake Chen (<a href="mailto:dchen@sio.org.cn">dchen@sio.org.cn</a>) and/or me.</p> <p> </p> <p>Best wishes</p> <p>Ruikun Hu</p> <p>Ph.D of physical oceanography</p> <p>State Key Laboratory of Satellite Ocean Environment Dynamics,</p> <p>Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China</p> <p><a href="mailto:ruikunhu@sio.org.cn">ruikunhu@sio.org.cn</a></p> <p>October 18, 2024</p> <p>Updated on November 8, 2024</p>
MEASUREMENT AND MULTI-SCALE MODELLING OF CYSTEINE AND GLUTATHIONE OXIDATION RATES.
<p>MEASUREMENT AND MULTI-SCALE MODELLING OF CYSTEINE AND GLUTATHIONE OXIDATION RATES.</p>
Rectangles detected with the discrete Central multi-scale Radon transform
<p>A screen recording of a demonstration mobile phone application that uses the discrete Central Radon transfom to detect, in real-time, the most prominent rectangle seen by the device's camera.</p>
Data and software for "Multi-scale variability of turbulent mixing during a Monsoon Intraseasonal Oscillation in the Bay of Bengal: an LES study"
<p>LES data outputs</p>
Predictive multi-scale occupancy models at range-wide extents: effects of habitat and human disturbance on distributions of wetland birds
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Identifying relationships between multi-scale social-ecological factors to explore ungulate health in a Western Kazakhstan rangeland
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.