This study explores flood-related environmental injustices by deconstructing racial, ethnic, and socio-demographic disparities and spatial heterogeneity in the areal extent of fluvial, pluvial, and coastal flooding across Canada. The study integrates JBA Risk Management's 100-year Canada Flood Map with the 2016 national census-based socioeconomic data to investigate whether traditionally recognized vulnerable groups and communities are exposed inequitably to inland (e.g., fluvial and pluvial) and coastal flood hazards. Social vulnerability was represented by neighbourhood-level socioeconomic deprivation, including economic insecurity and instability indices. Statistical analyses include bivariate correlation and a series of non-spatial and spatial regression techniques, including ordinary least squares, binary logistic regression, and simultaneous autoregressive models. The study emphasizes the quest for the most appropriate methodological framework to analyze flood-related socioeconomic inequities in Canada. Strong evidence of spatial effects has motivated the study to test for the spatial heterogeneity of covariates by employing geographically weighted regression (GWR) on continuous outcome variables (e.g., percent of residential properties in a census tract exposed to flood hazards) and geographically weighted logistic regression on dichotomous outcome variables (e.g., a census tract in or out of flood hazard zone). GWR results show that the direction and statistical significance of relationships between inland flood exposure and all explanatory variables under consideration are spatially non-stationary. We find certain vulnerable groups, such as females, lone-parent households, Indigenous peoples, South Asians, the elderly, other visible minorities, and economically insecure residents, are at a higher risk of flooding in Canadian neighbourhoods. Spatial and social disparities in flood exposure have critical policy implications for effective emergency management and disaster risk reduction. The study findings are a foundation for a more detailed investigation of the disproportionate impacts of flood risk in Canada.
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http://dx.doi.org/10.1016/j.envres.2022.112982 | DOI Listing |
J Clin Med
December 2024
Degenerative and Chronic Diseases of the Faculty of Health Sciences (FGW), University Potsdam, 14469 Potsdam, Germany.
: About 65 million people worldwide are affected by epilepsy, with temporal lobe epilepsy being the most common type resistant to drugs and often requiring surgical treatment. Although open surgical approaches, such as temporal lobectomy, have been the method of choice for decades, minimally invasive MRgLITT has demonstrated promising results. However, it remains unknown whether patients who underwent one of these two approaches would show better performance on vestibulo-spatial tasks.
View Article and Find Full Text PDFCancers (Basel)
December 2024
Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis School of Medicine, University of California Davis Comprehensive Cancer Center, Sacramento, CA 95817, USA.
Patient-centered precision oncology strives to deliver individualized cancer care. In lung cancer, preclinical models and technological innovations have become critical in advancing this approach. Preclinical models enable deeper insights into tumor biology and enhance the selection of appropriate systemic therapies across chemotherapy, targeted therapies, immunotherapies, antibody-drug conjugates, and emerging investigational treatments.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Petrovsky National Research Centre of Surgery, Abrikosovsky per. 2, 119991 Moscow, Russia.
Bilio-biliary anastomosis (BBA) is a critical surgical procedure that is performed with the objective of restoring bile duct continuity. This procedure is often required in cases where there has been an injury to the extrahepatic bile ducts or during liver transplantation. Despite advances in surgical techniques, the healing of BBA remains a significant challenge, with complications such as stricture formation and leakage affecting patient outcomes.
View Article and Find Full Text PDFMaterials (Basel)
December 2024
School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth PL4 8AA, UK.
Geopolymer concrete is a sustainable construction material and is considered as a promising alternative to traditional Portland cement concrete. However, there is still not much research on the effective properties and damage behavior of geopolymer concrete with consideration of its heterogeneous characteristics by means of mesoscale models combined with the regularized microplane damage model. Here, in this research, an easy and simpler approach for generating concrete mesoscale models and characterizing the angular characteristics of aggregate particles is presented.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
The Institute of Cancer Research, London, United Kingdom.
Background: Deep learning (DL) has set new standards in cancer diagnosis, significantly enhancing the accuracy of automated classification of whole slide images (WSIs) derived from biopsied tissue samples. To enable DL models to process these large images, WSIs are typically divided into thousands of smaller tiles, each containing 10-50 cells. Multiple Instance Learning (MIL) is a commonly used approach, where WSIs are treated as bags comprising numerous tiles (instances) and only bag-level labels are provided during training.
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