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21 results for “Resilience analysis”
Computational Artifacts for the Paper "Are Noise-resilient Logical Timers useful for Performance Analysis?"
<p>This repository contains computational artifacts for the paper "Are Noise-resilient Logical Timers useful for Performance Analysis?" to be submitted to <a href="https://sc-protools-workshop.github.io/protools24/">ProTools@SC24.</a></p> <p>See also the <a href="https://sc24.supercomputing.org/program/papers/reproducibility-initiative/">SC24 reproducibility initiative.</a></p> <p> </p> <p>Contains</p> <ul> <li>Source code of <a href="https://doi.org/10.5281/zenodo.10822140">Score-P </a>, including implementation of the logical clock algorithm from the paper</li> <li>Software to post-process the Cube files generated by measurements</li> <li>Benchmarks <ul> <li>Source code</li> <li>Configuration skripts</li> <li>Measurement results, including output logs, Cube files</li> <li>Post-processing skripts and results</li> </ul> </li> </ul> <p> </p>
Climate Change Adaptive Resilience Analysis Dataset
<p><span>Greenhouse gas escalation and severely deteriorated environment with global warming and climate change impose substantial difficulties in energy resilience for adaption and mitigation of climate change and zero-carbon transitions. However, uncertainties in supply-demand from climate change and climate-adaptive resilience for electrified and integrative PV-battery-building systems remain unclear. In this research, following </span><span>zero-energy building design principles and innovative U-value/M-value battery sizing methods</span><span>, a </span><span>tailored</span><span> </span><span>‘kWp-kWh-m<sup>2</sup>’ design approach is proposed with </span><span>intrinsic relationships of prosumer-storage</span><span> to achieve renewable self-sufficiency and avoid battery oversizing</span><span> in both centralized and distributed forms.<a name="OLE_LINK1"></a> Comprehensive analysis is conducted by assessing economic-environmental indicators, such as levelized costs of storage, net present values, decarbonization potentials, and policy incentives, followed by the evaluation of provincial system configurations considering energy system variations across diverse climate change conditions and geographic areas. </span><span>Results reveal significant regional variations induced by climatic conditions, resource availability, local grid energy structure, and electricity prices. Notably, the long-term economic-ecological viability of the proposed PV-battery-building system is highlighted, especially with optimal battery integrations. As climate change progresses, the research provides invaluable guidelines for zero-energy transitions from optimal system design, provincial-level system configurations, and performance evaluation, guiding the strategic investment and targeted policy interventions towards sustainability transformations.</span></p> <p><span>The comprehensive dataset encompasses 25-year time series of instantaneous photovoltaic (PV) generation, building electricity demand, PV-battery system performance, and battery capacity sizing procedures across five distinct climatic regions in China. This data accounts for the impacts of different climate change scenarios, including the typical year as well as the Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 for the years 2020, 2030, 2060, and 2100. </span></p>
Data from: Resilience of an integrated crop-livestock system to climate change: a simulation analysis of cover crop grazing in southern Brazil
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Comparative analysis of RNN versus IIR digital filtering to optimize resilience to dynamic perturbations in pH sensing for vertical farming
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Measuring resilience and resistance in aging and Alzheimer disease using residual methods: A systematic review and meta-analysis
<p>Objective: There is currently a lack of consensus on how to optimally define and measure resistance and resilience in brain and cognitive aging. Residual methods use residuals from regression analysis to quantify the capacity to avoid (resistance) or cope (resilience) "better or worse than expected" given a certain level of risk or cerebral damage. We reviewed the rapidly-growing literature on residual methods in the context of aging and Alzheimer's disease (AD), and performed meta-analyses to investigate associations of residual-method based resilience and resistance measures with longitudinal cognitive and clinical outcomes.</p> <p>Methods: A systematic literature search of PubMed and Web-of-Science databases (consulted until March 2020) and subsequent screening led to 54 studies fulfilling eligibility criteria, including 10 studies suitable for the meta-analyses.</p> <p>Results: We identified articles using residual methods aimed at quantifying resistance (n=33), cognitive resilience (n=23) and brain resilience (n=2). Critical examination of the literature revealed that there is considerable methodological variability in how the residual measures were derived and validated. Despite methodological differences across studies, meta-analytic assessments showed significant associations of levels of resistance (HR[95%CI]=1.12[1.07-1.17], p<0.0001) and levels of resilience (HR[95%CI]=0.46[0.32-0.68], p<0.001) with risk of progression to dementia/AD. Resilience was also associated with rate of cognitive decline (β[95%CI]=0.05[0.01-0.08], p<0.01).</p> <p>Conclusion: This review and meta-analysis supports the usefulness of residual methods as appropriate measures of resilience and resistance, as they capture clinically meaningful information in aging and AD. More rigorous methodological standardization is needed, however, to increase comparability across studies and, ultimately, application in clinical practice.</p>
Interactive Elicitation of Resilience Scenarios based on Hazard Analysis Techniques: Supplementary Material
<p>Supplementary material for:</p> <p>Sebastian Frank, Alireza Hakamian, Lion Wagner, Dominik Kesim, Christoph Zorn, Jóakim von Kistowski, and André van Hoorn: <em>Interactive Elicitation of Resilience Scenarios based on Hazard Analysis Techniques. Springer, 2022.</em></p> <p>This artifact includes the details of the scenarios and the chatbot-based elicitation tool and study described in the paper.</p> <p>Additional software artifacts are provided in a separate Code Ocean capsule: <a href="https://doi.org/10.24433/CO.0520280.v1">https://doi.org/10.24433/CO.0520280.v1</a></p>
Monitoring resistance and resilience using carbon trajectories: analysis of forest management-disturbance interactions
<p>A changing climate is altering ecosystem carbon dynamics with consequences for natural systems and human economies, but there are few tools available for land managers to meaningfully incorporate carbon trajectories into planning efforts. To address uncertainties wrought by rapidly changing conditions, many practitioners adopt resistance and resilience as ecosystem management goals, but these concepts have proven difficult to monitor across landscapes. Here, we address the growing need to understand and plan for ecosystem carbon with concepts of resistance and resilience. Using time series of carbon fixation (n=103), we evaluate forest management treatments and their relative impacts on resistance and resilience in the context of an expansive and severe natural disturbance. Using subalpine spruce-fir forest with a known management history as a study system, we match metrics of ecosystem productivity (net primary production, g·C·m<sup>2</sup>·y<sup>-1</sup>) with site-level forest structural measurements to evaluate (1) whether past management efforts impacted forest resistance and resilience during a spruce beetle (<em>Dendroctonus rufipennis</em>) outbreak, and (2) how forest structure and physiography contribute to anomalies in carbon trajectories. Our analyses have several important implications. First, we show that the framework we applied was robust for detecting forest treatment impacts on carbon trajectories, closely tracked changes in site-level biomass, and was supported by multiple evaluation methods converging on similar management effects on resistance and resilience. Second, we found that stand species composition, site productivity, and elevation predicted resistance, but resilience was only related to elevation and aspect. Our analyses demonstrate application of a practical approach for comparing forest treatments and isolating specific site and physiographic factors associated with resistance and resilience to biotic disturbance in a forest system, which can be used by managers to monitor and plan for both outcomes. More broadly, the approach we take here can be applied to many scenarios, which can facilitate integrated management and monitoring efforts.</p>
Favoring recruitment as a conservation strategy to improve the resilience of long-lived reptile populations: insights from a population viability analysis
<p>In long-lived species, although adult survival typically has the highest elasticity, temporal variations in less canalized demographic parameters are the main drivers of population dynamics. Targeting recruitment rates may thus be the most effective strategy to manage these species. We analyzed 1136 capture–recapture histories collected over 9 years in an isolated population of the critically endangered Lesser Antillean iguana, using a robust-design Pradel model to estimate adult survival and recruitment rates. From an adult population size estimated at 928 in 2013, we found a yearly decline of 4% over the 8-year period. As expected under the canalization hypothesis for a long-lived species, adult survival was high and constant, with little possibility for improvement, whereas the recruitment rate varied over time and likely drove the observed population decline. We then used a prospective perturbation analysis to explore whether managing the species' immature cohorts would at least slow the population decline. The prospective perturbation analysis suggested that a significant and sustained conservation effort would be needed to achieve a recruitment rate high enough to slow the population decline. We posit that the high recruitment rate achieved in 2014 – likely due to the maintenance in 2012 of the main nesting sites used by this population – would be sufficient to slow this population's decline if it was sustained each year. Based on the results of diverse pilot studies we conducted, we identified the most likely threats targeting the eggs and immature cohorts, stressing the need to improve reproductive success and survival of immature iguanas. The threats we identified are also involved in the decline of several reptile species, and species from other taxa such as ground-nesting birds. These findings on a little-studied taxon provide further evidence that focusing on the immature life stages of long-lived species can be key to their conservation.</p>
The data for "Noise-Resilient Forward Transient Analysis for Pipe Burst Localization in Complex Pipe Networks: Theoretical Framework"
<p>The data is for supporting our research paper titled "Noise-Resilient Forward Transient Analysis for Pipe Burst Localization in Complex Pipe Networks: Theoretical Framework".</p>
Sweden Cancerome Analysis Network - Breast (SCAN-B) Coupled to Psychological Resilience
ClinicalTrials.gov study NCT03430492. IPD Sharing: UNDECIDED. Countries: 1. Publications: 5.
Favoring recruitment as a conservation strategy to improve the resilience of long-lived reptile populations: insights from a population viability analysis
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Monitoring resistance and resilience using carbon trajectories: analysis of forest management-disturbance interactions
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Data from: Resilience of tropical dry forests – a meta-analysis of changes in species diversity and composition during secondary succession
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Measuring resilience and resistance in aging and Alzheimer disease using residual methods: A systematic review and meta-analysis
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Development of public dynamic spatio-temporal monitoring and analysis tool of supply chain vulnerability, resilience, and sustainability
<p>Supply chains play a pivotal role in driving economic growth and societal well-being, facilitating the efficient movement of goods from producers to consumers. However, the increasing frequency of disruptions caused by geopolitical events, pandemics, natural disasters, and shifts in commerce poses significant challenges to supply chain resilience. This draft update report discusses the development of a dynamic spatio-temporal monitoring and analysis tool to assess supply chain vulnerability, resilience, and sustainability. Leveraging news data, macroeconomic metrics, inbound cargo data (for sectors in California), and operational conditions of California's highways, the tool employs Natural Language Processing (NLP) and empirical regression analyses to identify emerging trends and extract valuable information about disruptions to inform decision-making. Key features of the tool include sentiment analysis of news articles, topic classification, visualization of geographic locations, and tracking of macroeconomic indicators. By integrating diverse and dynamic data sources (e.g., news articles) and using empirical and analytical techniques, the tool offers a comprehensive framework to enhance our understanding of supply chain vulnerabilities and resilience, ultimately contributing to more effective strategies for decision-making in supply chain management. The dynamic nature of this tool enables continuous monitoring and adaptation to evolving conditions, thereby enhancing the analysis of resilience and sustainability in global supply chains.</p>
Development of public dynamic spatio-temporal monitoring and analysis tool of supply chain vulnerability, resilience, and sustainability
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Parallel in vivo analysis of large-effect autism genes implicates cortical neurogenesis and estrogen in risk and resilience [Xenopus]
GEO Series GSE155553. Xenopus tropicalis. 27 samples. Type: Expression profiling by high throughput sequencing.
Parallel in vivo analysis of large-effect autism genes implicates cortical neurogenesis and estrogen in risk and resilience [human]
GEO Series GSE155552. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic Analysis of the Host Response and Innate Resilience to Enterotoxigenic Escherichia coli Infection in Humans
GEO Series GSE95104. Homo sapiens. 72 samples. Type: Expression profiling by array.
Parallel in vivo analysis of large-effect autism genes implicates cortical neurogenesis and estrogen in risk and resilience
GEO Series GSE155554. Xenopus tropicalis; Homo sapiens. 39 samples. Type: Expression profiling by high throughput sequencing.
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.