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177 results for “multi-level”
Multi-level in vivo selection of the biocontrol agent Akanthomyces muscarius, virulence, growth, sporulation, and variant data
<p>Changes in parasite virulence are commonly expected to lead to trade-offs in other life history traits that can affect fitness. Understanding these trade-offs is particularly important if we want to manipulate the virulence of microbial biological control agents. Theoretically, selection across different spatial scales, i.e. between- and within-hosts, shapes these trade-offs. However, trade-offs are also dependent on parasite biology. Despite their applied importance the evolution of virulence in fungal parasites is poorly understood: virulence can be unstable in culture and commonly fails to increase in simple passage experiments. We hypothesized that manipulating selection intensity at different scales would reveal virulence trade-offs in a fungal pathogen of aphids, <em>Akanthomyces muscarius</em>. Starting with a genetically diverse stock we selected for speed of kill, parasite yield, or infectivity by manipulating competition within and between hosts and between populations of hosts over 7 rounds of infection. We characterized ancestral and evolved lineages by whole genome sequencing and by measuring virulence, growth rate, sporulation, and fitness. While several lineages showed increases in virulence, we saw none of the trade-offs commonly found in obligately-killing parasites. Phenotypically similar lineages within treatments often shared multiple single-nucleotide variants, indicating strong convergent evolution. The most dramatic phenotypic changes were in the timing of sporulation and spore production <em>in vitro. </em>We found that early sporulation led to reduced competitive fitness but could increase the yield of spores on media, a trade-off characteristic of social conflict. Notably, the selection regime with the strongest between-population competition and lowest genetic diversity produced the most consistent shift to early sporulation, as predicted by social evolution theory. Multi-level selection therefore revealed social interactions novel to fungi and showed that these biocontrol agents have the genomic flexibility to improve multiple traits - virulence and spore production - that are often in conflict in other parasites.</p>
Loss of multi-level 3D genome organization during breast cancer progression - FISH dataset
<p>This entry contains the raw and processed FISH images produced by the following study:<br><strong>Loss of multi-level 3D genome organization during breast cancer progression</strong></p> <p>The raw images contained in file 2022-mcf10a-cancer-progression-fish-db.tar.gz were processed using fish data analysis workflow (<a href="https://github.com/paulsengroup/2022-mcf10a-cancer-progression/blob/main/run_fish.sh" target="_blank" rel="noopener">link</a>) hosted at <a href="https://github.com/paulsengroup/2022-mcf10a-cancer-progression" target="_blank" rel="noopener">paulsengroup/2022-mcf10a-cancer-progression</a>.<br>The resulting files have been archived in file 2022-mcf10a-cancer-progression-fish-processed-data.tar.gz.</p>
Data: Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD
<p>This archive contains all scripts, resource data and results, including intermediate results to reproduce the results for "Metabolic modeling reveals a multi-level deregulation of host-microbiome metabolic networks in IBD". </p>
Development of a Multi-Level Dynamic Model to Measure the Resilience Level of Transportation Infrastructure Networks
<p>The recent increase in disasters is making the largest critical infrastructure system namely the transportation infrastructure system susceptible to unexpected damage. Discontinuation of services provided by transportation infrastructures will create significant societal, economic, and collateral damages. Therefore, this study aims to identify dimensions to measure the resilience of the transportation infrastructures. This study also aims to develop a model to measure the resilience of the transportation infrastructures resilience. To fulfill the aims of this study, a questionnaire was developed which was supported by a comprehensive literature review. 92 valid responses were received and analyzed qualitatively and quantitatively. Statistically significant variables were used to develop a resilience measurement tool. The developed tool will provide relative resilience measures for multiple projects which will help in identifying the most vulnerable segment of the transportation infrastructure network. Exploratory factor analysis (EFA) was performed to identify the constructs and structural equation modeling (SEM) was used to develop the model. Without previous experience in reconstruction works, handling integrated assets becomes very critical. Also, such inexperience makes it difficult to handle emergency resources properly. However, such issues regarding integrated assets can be resolved by investing in locating integrated assets away from the roadways, so if a break in a railroad crossing or utility line occurs or emergency repairs are needed, the impact on the roadway operations can be minimized. To avoid issues related to access to previous disaster data for the roadway this study suggess investing in preparing an interactive online platform for recording and reviewing data related to disasters as well as previous resilience enhancing activities for the roadway with easy access credentials. The findings of this study will support practitioners and decision-makers in investing in the appropriate resilience enhancement activity project for funding and investment.</p>
Multi-Level Monte Carlo Models for Flood Inundation Uncertainty Quantification - Dataset
<p>Dataset used for the analysis of Multi-level Monte Carlo methods for flood inundation uncertainty quantification. This includes:</p> <ol> <li>Flood model simulations for Dyce, Glasgow and Inverurie across three resolutions (5m/10m/20m).</li> <li>Data for violin plot figures with code.</li> </ol>
Data from: The Effects of Multi-Level Identity Dynamics in New Venture Creation
<p>Anonymized interview data from SNF project<strong> The Effects of Multi-Level Identity Dynamics in New Venture Creation </strong>(in the context of collective entrepreneurial ventures) that has been used for publications (as stated in Data Management Plan). Additional data available upon request.</p>
Data and code: Bayesian Multi-level model calibration of the SPASS phenology model for silage maize
<p>Data and code supporting the research article: Bayesian Multi-level model calibration of the SPASS phenology model for silage maize - M. Viswanathan, A. Scheidegger, T. Streck, S. Gayler, T.K.D. Weber. This includes R code for the implementation of the SPASS phenology maize model; Jags in R to implement the Bayesian multi-level models .</p>
Wearable Network for Multi-Level Physical Fatigue Prediction in Manufacturing Workers - Dataset
<p>This dataset contains data from 43 subjects following two authentic manufacturing protocols and their self-reported fatigue score. The system employs 6 wearable sensors to continuously track vital and locomotive signs from multiple body locations.</p> <p> </p> <p>The goal of the experiment is to predict fatigue trends in a subject, while they are asked to perform pre-defined manual tasks simulating a manufacturing environment, using data from soft, flexible, wearable sensors and a vision system. The tasks in this study are repetitive and physically exerting involving intricate steps taken in real manufacturing settings. The iterative nature of the tasks facilitates comparative analyses of distinct temporal segments to characterize fatigue. The two manufacturing tasks are (1) Task Composite: Composite Sheet Layup, and (2) Task Harnessing: Wire Harnessing. The task protocol requires the subject to wear sensors to monitor vital and locomotive signs continuously. Additionally, we incorporate a weighted vest to exaggerate the induced fatigue in a reasonable duration for the study to mimic a full shift for a manufacturing worker. Each task consists of two rest periods of 5 minutes each at the start and end, as well as five segments of physical tasks. On average, each task takes a total of 1 hour. Before each data segment, the subject fills out a survey form to indicate their current fatigues as per the Borg scale. </p>
A Multi-level Dataset of Linux Kernel Patchwork
<p>The dataset, source code, application and document of a MSR 2018 data showcase paper.</p> <p>Yulin Xu and Minghui Zhou. 2018. A Multi-level Dataset of Linux Kernel Patchwork. In MSR '18: MSR '18: 15th International Conference on Mining Software Repositories , May 28–29, 2018, Gothenburg, Sweden. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3196398.3196475</p> <p>Description of each files:</p> <p>The level-0 data is stored in the file `level-0.zip'.</p> <p>The level-1 and level-2 data are stored in the file `level-1 and level-2.7z'.</p> <p>The tool is the file `application.7z'.</p> <p>The source code of the tool is the file `source code.7z'.</p> <p>The document of the tool is the file `Usage of Application.pdf'.</p> <p>The document of the dataset is the file `Description of Tables.pdf'.</p>
Biodiversity scale-dependence and opposing multi-level correlations underlie differences among taxonomic, phylogenetic, and functional diversity
<p><b>Aim:</b> Biodiversity is a multi-dimensional property of biological communities that represents different information depending on how it is measured, but how dimensions relate to one another and under what conditions is not well understood. We explore how taxonomic, phylogenetic, and functional diversity can differ in scale-of-effect dependence and habitat-biodiversity relationships, and subsequently how spatial differences among biodiversity dimensions may arise.</p> <p><b>Location:</b> Nebraska, United States</p> <p><b>Time period:</b> May-July 2016, 2017</p> <p><b>Major taxa studied:</b> Birds</p> <p><b>Methods:</b> Across 2016 and 2017, we conducted 2,641 point counts at 781 sites. We modeled the occupancy of 141 species using Bayesian Bernoulli-Bernoulli hierarchical logistic regressions. We calculated species richness (SR), phylogenetic diversity (PD), and functional diversity (FD) for each site and year based on predicted occupancy, accounting for imperfect detection. Using Bayesian latent indicator scale selection and multivariate modeling, we quantified the spatial scales-of-effect that best explained the relationships between environmental characteristics and SR, PD, and FD. Additionally, we decomposed the residual between- and within-site biodiversity correlations using our repeated measures design.</p> <p><b>Results:</b> We demonstrate spatial differences among biodiversity predictions, arising from scale-dependence in habitat-biodiversity relationships and variation in correlation structure among biodiversity dimensions. Although relationships between specific land cover types and SR, PD and FD were qualitatively similar, the spatial scales at which these variables were important in explaining biodiversity differed among dimensions. Between-site residual biodiversity correlations were negative, yet within-site biodiversity residual correlations were positive.</p> <p><b>Main conclusions:</b> Our results demonstrate how spatial differences among biodiversity dimensions may arise from biodiversity-specific scale-dependent habitat relationships, low shared environmental correlations and opposing residual correlations between dimensions, which suggest that single-scale and single-dimension analyses are not entirely appropriate for quantifying habitat-biodiversity relationships. After accounting for shared habitat relationships, we found positive within-site residual correlations between taxonomic, phylogenetic, and functional diversity, suggesting that habitat change over time influenced all biodiversity dimensions relatively similarly. However, negative between-site residual correlation among biodiversity dimensions may indicate trade-offs in achieving maximum biodiversity across multiple biodiversity dimensions at any given location. Although habitat management can to a limited degree improve biodiversity relatively across all metrics, other environmental effects may ensure that not all facets of biodiversity can be maximized at once. If maximizing a specific biodiversity dimension is the goal, then care should be taken to consider these within-site residual correlations.</p>
Antelope space-use and behaviour indicate multi-level responses to varying anthropogenic influences in a highly human-dominated landscape
<p><span></span></p> <p>A primary means of conserving a species or a habitat in a human-dominated landscape is through promoting coexistence with humans while minimizing conflict. For this, we should understand how wildlife are impacted by direct and indirect human activities. Such information is rare from areas with high human densities. To investigate how animals respond to altered ecological conditions in human-dominated landscapes, we focussed on a wild herbivore of conservation concern in Krishnasaar Conservation Area (KrCA) in Nepal. Here, blackbuck, <em>Antilope cervicapra</em>, a generalist grazer, lives in refugia located in a growing human population. We studied the impacts of humans on habitat use and behaviour of blackbuck. We laid 250 x 250 m grid cells in the entire KrCA and carried out indirect sign surveys with three replications for habitat use assessment. We observed herds of blackbuck for 89 hours in different habitat types using scan sampling methods. Our habitat-use survey showed that habitats under intensive human use were hardly used by blackbuck, even when high-quality forage was available. Habitat openness was the major predictor of habitat-use inside the core area, where levels of human activities were low. We also found a positive correlation between habitat use by blackbuck and livestock. Blackbuck were substantially more vigilant when they were in forest than in grassland, again indicating an influence of risk. Overall, blackbuck appear to be sensitive to risk associated with both natural and anthropogenic factors. Our findings have direct implications for managing human-wildlife interactions in this landscape, specifically regarding strategies for livestock grazing in habitats highly used by blackbuck and concerning predictions of how changing land use will impact long-term persistence of blackbuck. Our work suggests that wild herbivores may be able to persist in landscapes with high human densities so long as there are refuges where human activities are relatively low.</p>
Data from: Multi-level thresholds of residential and agricultural land use for elk avoidance across the Greater Yellowstone Ecosystem
<p>1. Conversion of land for settlements and agriculture is increasing globally and can influence wildlife space use. However, there is limited research to identify the thresholds of land use change that incur wildlife avoidance, and how these thresholds might vary across levels of selection.</p> <p>2. We evaluated multi-level avoidance thresholds of elk (<em>Cervus canadensis</em>) impacted by residential development and irrigated agriculture across the Greater Yellowstone Ecosystem in Idaho, Montana, and Wyoming. Using GPS data from 765 elk in 21 herds, we estimated habitat selection in relation to development and agriculture at 3 levels (home range selection, within home range selection, and movement path selection). Next, using individual selection covariates and associated measures of land use availability, we used functional-response models to evaluate how selection varied based on availability, and in turn, to estimate avoidance thresholds.</p> <p>3. We found individual and level-specific variation in elk responses to environmental factors. Elk exhibited stronger responses (either selection or avoidance) when selecting home range locations (i.e. second-order selection) than when selecting areas within home ranges (i.e. third-order selection) or selecting movement paths (i.e. fourth order selection). Importantly, elk avoidance of development and agriculture changed as the amount of land in these categories changed. Across all levels of selection, elk exhibited neutral selection for human development at low levels of availability (<1.1–2.2% developed) but avoided areas that were >1.1–2.2% developed. Conversely, elk selected positively for irrigated agriculture at low to moderate levels of availability (<52.0–66.2% agriculture) but exhibited neutral selection in areas that were > 52.0–66.2% agriculture.</p> <p>4. Synthesis and Applications: Elk avoidance of low levels of human development suggests conservation efforts such as restrictions on future development or conservation easements could focus on areas that are still below 2% developed. Additionally, because elk selection was strongest at the landscape scale, conservation actions that are based on information about the overall landscape structure may be most impactful. Our results highlight the importance of understanding variability in wildlife habitat selection at multiple levels, particularly in relation to land use change and highlight how functional response modelling can help inform landscape conservation.</p>
A scoping review of multi-level governance of forests in the Philippines
<p>This review scopes the landscape of multi-level forest governance in the Philippines, providing a clearer picture of potential gaps and opportunities for further development in the field. </p>
Hyper PUF with multi-level operation: Challenge-Response Pair Library
<p>An optical PUF with multi level operation (that we named as Hyper PUF) is interrogated with a set of 100 Random Probing Challenges producing in the far field an optical response, the speckle pattern.</p> <p>The multi-level operation is induced by modifying the scattering properties of the PUF with a second light pattern, the Transforming Level.</p> <p>Per each Transforming Level, we acquired the Responses to the 100 Random Probing Challenges.</p> <p>In this repository, we collect the Random Probing Challenges, the ten Transforming Levels and the relative Responses to the Probing Challenges per each Transforming Level.</p>
Efficacy Testing of a Multi-Level Family Planning Intervention
ClinicalTrials.gov study NCT06923189. IPD Sharing: YES. Countries: 1. Publications: 1.
Approach-Avoidance Conflict-a Multi-level Predictor for Therapy Response
ClinicalTrials.gov study NCT02807480. IPD Sharing: YES. Countries: 1. Publications: 9.
Multi-level Supermarket Discount Study
ClinicalTrials.gov study NCT04178824. IPD Sharing: YES. Countries: 1. Publications: 4.
Modeling Multi-level Dyadic Behavior to Transform the Science and Practice of Psychotherapy Process and Outcome.
ClinicalTrials.gov study NCT03594773. IPD Sharing: NO. Countries: 1. Publications: 2.
TissueLink Study During Multi-Level Spine Surgery
ClinicalTrials.gov study NCT01300559. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Multi-level Intervention to Increase Access and Use of the Patient Portal
ClinicalTrials.gov study NCT05180721. IPD Sharing: Not stated. Countries: 1. Publications: 2.
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.