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31 results for “Vulnerability analysis”
Assessment of the Vulnerability of Permafrost Carbon to Climate Change: A Sensitivity Analysis among Models
This activity is a comparison of how large-scale models represent permafrost carbon dynamics into the future (2010-2299). Model responses were evaluated at several temporal scales. To the extent possible, we standardized driver data and simulation procedures among the models. However, the protocol has been set up so that each model can build upon the procedures used to produce the outputs for historical analysis (1960- 2009) that was published in McGuire et al. 2016 (Global Biogeochemical Cycles 30:1015-1037, doi:10.1002/2016GB005405). Note that this comparison is an offline model comparison in which we assessed the sensitivity of the responses of the models to somewhat standardized forcing data. The activity compared among the models: Carbon dynamics: Predictions of average annual C fluxes (GPP, NPP, RH, CH4 fluxes, disturbance-related emissions, dissolved organic carbon export, lateral land used fluxes, etc.) and major pools for the northern permafrost region for the 2010-2299 period. Soil thermal dynamics: Predictions of annual soil thermal and hydrological dynamics at prescribed depths and the maximum annual active layer depth (in permafrost locations) for the 2010-2299 time period. The spatial simulation data for this project are are available through the National Snow and Ice Data Center (doi: 10.5067/ZRL5WJKN01XM).
Adaptive Behavior of Farmers Under Consecutive Droughts Results In More Vulnerable Farmers: A Large-Scale Agent-Based Modeling Analysis in the Bhima Basin, India
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Assessment of risk and vulnerability to disasters by field protocols and classification trees: an analysis of the Municipal Risk Reduction Plans (MRRP) of São Bernardo do Campo and Franco da Rocha (2020-2021), in Brazil
<p><span>Most disaster risk assessment methodologies were developed by natural science professionals. The UN Sendai Framework confirms the need to include these methods as interweaving complex networks of socially vulnerable financial processes, especially in developing countries. This work aimed to analyze the experience of including social vulnerability information in field protocols of the Municipal Risk Reduction Plans (MRRP) of São Bernardo do Campo and Franco da Rocha (2020-2021). A georeferenced database was structured with data from field protocols on risk sectors and then the relationship between vulnerability and risk was analyzed using the classification tree method. The results show that the geotechnical and social vulnerability variables relevant to risk attribution are largely overlapping over the sectors, but that the integrated analysis of the two dimensions allows a better interpretation of the risk level. However, the models with information from field protocols cannot replace a broader holistic assessment by the specialist in the field. Finally, qualitative reflections are made on the limitations and potential of including aspects of vulnerability in the specific case study.</span></p>
MADFORWATER: WP1: Water and water-related vulnerabilities in Egypt, Morocco and Tunisia: Task1.2: Analysis and mapping of water stress, water vulnerability and potential for water reuse in Egypt, Morocco and Tunisia: Subtask1.2.b: Data collection on water stress and vulnerability: Souss-Massa Region Subset
<p>This folder contains the dataset that I used to write my conference paper "Groundwater Resources Scarcity in Souss-Massa Region and Alternative Solutions for Sustainable Agricultural Development"</p>
Bahamas National Hazard Analysis. Data Inputs and Outputs for the InVEST Coastal Vulnerability Model.
<p>The following folders contain the model inputs and outputs for the InVEST Coastal Vulnerability model that were used in the analysis discussed in:</p> <p>Silver JM, Arkema KK, Griffin RM, Lashley B, Lemay M, Maldonado S,<br> Moultrie SH, Ruckelshaus M, Schill S, Thomas A, Wyatt K and Verutes G<br> (2019) Advancing Coastal Risk Reduction Science and Implementation by<br> Accounting for Climate, Ecosystems, and People. Front. Mar. Sci. 6:556.<br> doi: 10.3389/fmars.2019.00556</p> <p>The readme.txt file contains information about data layers.</p>
Dataset for "Towards Centrality and Causality based Vulnerability Propagation Analysis"
<ul> <li> <p><strong><code>aggregated_data.json</code></strong>: This file contains the processed data generated after loading the Goblin Weaver tool. It includes all CVEs, CWEs, and other relevant attributes. Statistical analyses, particularly vulnerability analyses, are performed on this dataset.</p> </li> <li> <p><strong><code>graph_nodes_edges.pkl</code></strong>: This file stores the parsed GraphML-format graph, divided into chunks of nodes and edges to optimize memory usage during computations. All centrality-based measurements are conducted using this file.</p> </li> <li> <p><strong><code>cve_data.csv</code></strong>: This file captures features of nodes along with their one-hop neighbors. It includes attributes such as <code>whether_cve_exists</code>, <code>cve_exists</code>, and <code>cve_num</code>, as well as the source and target nodes involved.</p> </li> <li> <p><strong><code>cve_2_siblings_data.csv</code></strong>: This file documents features of nodes with their two-hop neighbors. It includes attributes like <code>whether_cve_exists</code>, <code>cve_exists</code>, and <code>cve_num</code>, along with details of source nodes and their two-hop neighbor nodes.</p> </li> <li><code><strong>fea_matrix.csv</strong>:</code><code>This file records the matrix of every node based on transformed five types of attributes, including missrelease (freshness missrelease), outdays(freshness outdatedTimeinMs), popularity, speed, and severity. It has been used for correlation analysis. </code></li> </ul>
VCF datasets and analysis scripts for: The combination of genomic offset and niche modelling provides insights into climate change-driven vulnerability
<p>Global warming is increasingly exacerbating biodiversity loss. Populations locally adapted to spatially heterogeneous environments may respond differentially to climate change, but this intraspecific variation has only recently been considered when modelling vulnerability under climate change. Here, we incorporate intraspecific variation in genomic offset and ecological niche modelling to estimate climate change-driven vulnerability in two bird species in the Sino-Himalayan Mountains. We found that the cold-tolerant populations show higher genomic offset but risk less challenge for niche suitability decline under future climate than the warm-tolerant populations. Based on a genome-niche index estimated by combining genomic offset and niche suitability change, we identified the populations with the least genome-niche interruption as potential donors for evolutionary rescue, i.e., the populations tolerant to climate change. We evaluated potential rescue routes via a landscape genetic analysis. Overall, we demonstrate that the integration of genomic offset, niche suitability modelling, and landscape connectivity can improve climate change-driven vulnerability assessments and facilitate effective conservation management.</p>
Analysis of intelligent vehicle technologies to improve vulnerable road users safety at signalized intersections
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Mammals with large home ranges, low reproductive rates, and small body sizes are most vulnerable to roads: A meta-analysis
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VCF datasets and analysis scripts for: The combination of genomic offset and niche modelling provides insights into climate change-driven vulnerability
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Data from: Assessing the vulnerability of Africa's freshwater fishes to climate change: a continent-wide trait-based analysis
Climate change is a key driver of biodiversity loss across the globe, and freshwater fishes are predicted to be among the most vulnerable taxa. African freshwater ecosystems are home to one of the most unique and diverse ichthyo-faunas on the planet, and freshwater fish species provide essential livelihoods for millions of people living in riparian communities across the continent. Although nearly one sixth of African freshwater fishes have been designated as endangered or vulnerable to extinction by the IUCN Red List assessment, the effects of climate change on these species have not been explored on a continent-wide scale. In this study, we present the first trait-based climate change vulnerability assessment (CCVA) comprising the majority (85%) of Africa's currently described freshwater fishes. We assembled data relating to three dimensions of vulnerability including sensitivity, adaptive capacity, and exposure. In addition, we developed an index of 'conservation value' based on traditional conservation metrics including extinction risk, endemism, and provision of ecosystem services. We found that almost 40% of African freshwater fishes are vulnerable to climate change, mostly owing to the many species with highly specialized habitat and life-history requirements, and because of the numerous anthropogenic stressors they face. High proportions of species within the Nothobranchiidae and Cichlidae families were found to be vulnerable. Regions with high frequencies of vulnerable species included the African rift valley lakes, the Congo River drainage, and the coastal rivers of West Africa. Several important data deficiencies were identified relating to species' population sizes, genetic variability, and life history traits, and constitute priority research areas for the future. In addition, we highlighted some cases where traditional conservation approaches overlook species and regions that are predicted to be threatened by climate change.
Empirical Analysis of Security Vulnerabilities in Python Packages
<p>This dataset contains the data files used to analyze our RQs in the manuscript "Empirical Analysis of Security Vulnerabilities in Python Packages".</p> <p>For more information on how to understand the folder structure and dataset, please read the README.md.</p>
Data analysis of article research tittle "Online GIS and Remote Sensing-Based Mapping of Flood Vulnerability in Samarinda Seberang Subdistrict"
<p>This dataset contains an explanation of data analysis for creating a flood vulnerability map of Samarinda Seberang District. The dataset contains sub-criteria for each flood parameter and its score value. In addition, this dataset contains the weight value of each parameter, flood vulnerability level and its coloring, and the results of calculating the area of each vulnerability level.</p>
Data from: Assessing the vulnerability of Africa's freshwater fishes to climate change: a continent-wide trait-based analysis
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Data from: Climate-niche factor analysis: a spatial approach to quantifying species vulnerability to climate change
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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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Mutational analysis of Rap1 reveals specific vulnerability for long telomeres fusions
GEO Series GSE190759. Schizosaccharomyces pombe; Escherichia coli. 17 samples. Type: Other.
Transcriptomic analysis to identify genes associated with hypothalamus vulnerability in aging mice with cognitive decline
GEO Series GSE240365. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Single-cell parallel analysis of DNA damage and transcriptome reveals selective genome vulnerability
GEO Series GSE268567. Mus musculus; Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing; Other; Genome binding/occupancy profiling by high throughput sequencing.
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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.