The aim of this study is to analyse the didactic potential found in the novel Beartown (Backman, 2016) in relation to sex education as a part of literature studies in Swedish upper secondary school. Focusing on the three central terms of Swedish sex education, the study analyses the depiction of sexuality, consent, and relationships found within the novel from a gender and ideological perspective using the method of explicit and implicit ideology read as presented by an implied author. The results of the analysis show that Beartown depicts an environment that constructs and reinforces a heteronormative ideal and male-centric perspective as it relates to these terms. While the novel´s implied author is critical of said depiction and the negative consequences for the characters affected, the novel does not provide a preferred alternative to the problematic environment depicted. However, this criticism does help to provide a promising foundation for discussing sex education and sexuality, consent, and relationships within a classroom context.

Vibrio vulnificus, an emergent human pathogen, causes septicemia with a mortality rate over 50%. Additionally, symptom onset occurs rapidly, with the incubation time for ingestion cases being around 26 hours. This, combined with the severity of symptoms has led to V. vulnificus being considered the deadliest seafood-associated pathogen, claiming responsibility for 95% of seafood-related deaths. Currently, the molecular mechanisms through which some strains of this bacteria emerge to become pathogens are unknown. The main focus of this study is to expand upon the base of knowledge surrounding this question through comparing virulence phenotypes in environmentally collected strains of V. vulnificus. Specifically, this study will evaluate the pathogenic potential of environmental isolates collected from water and oyster sources in Lee County, Florida, in lieu of the outbreak that occurred in October 2022. To test this, a variety of assays were performed. First, a phylogenetic tree was built to establish the relationships between strains. Next, to study in vitro responses, serum resistance assays and sialic acid growth curves were performed. Then, to further classify the pathogenic potential of these environmental strains, they were tested against THP-1 monocytes differentiated into macrophages for their ability to resist phagocytosis and induce apoptosis. This study found differential responses amongst the environmental isolates, with some exhibiting significant pathogenic potential and others being sensitive to all tested assays. Understanding which strains emerge as pathogens will help determine the prevalence of key virulence factors within natural populations of bacteria and provide critical data on the phenotypic outcomes of differing genotypes.

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A novel approach for modeling anthropogenically-initiated wildfire ignition was developed that significantly advances the theoretical knowledge of human-wildfire interactions. Gravity interaction models that are commonly used for economic analyses associated with business competition were combined with fluid dynamics models that mimic human movement patterns to predict the probability of anthropogenically-initiated wildfire. Herein, a combined gravity interaction and fluid dynamics models is developed and validated for wildfire potential prediction against historic and current wildfire data. The study identified population centers and transportation corridors, in particular: proximity to railroads and roads; traffic volume; and density of the corridors as the most influential factors for wildfire ignition. The population centers are identified as global influencing factors, and are modeled as the gravity term. The transportation corridors are identified as local influencing factors, and are modeled using fluid flow analogy as diffusion and convection terms. An analytic convection diffusion model (CDM) model is derived and the model coefficients calibrated using historic wildfire data. The model is implemented in GIS, and applied for the prediction of wildfire potential prediction in southeastern Mississippi. The model shows a correlation of R2=0.87 against winter historic data, whereas the Gravity model with a fuel component shows only R2=0.75 correlations. The improved predictions using the proposed CDM model is due to its capability to predict both the global and the local measure of incendiary activity patterns within a single dynamic equation. The CDM model can be used as a standalone model that can predict the wildfire potential in a region. It can also be combined with the fuel layer and meteorological conditions to obtain spatio-temporal variation of wildfire risks, which would provide a decision support system for wildfire mitigation and land use planning and development. The CDM model will help fire managers better plan wildfire mitigation (fuel reduction) strategies and effectively stage equipment and personnel geographically in areas of drought that are coincident with high ignition probability. Land use and transportation managers will gain better understanding of the changes in wildfire risk pattern due to urban fringe development.