Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires

We apply the Physics Informed Neural Network (PINN) to the problem of wildfire fire-front modelling. We use the PINN to solve the level-set equation, which is a partial differential equation that models a fire-front through the zero-level-set of a level-set function. The result is a PINN that simulates a fire-front as it propagates through the spatio-temporal domain. We show that popular optimisation cost functions used in the literature can result in PINNs that fail to maintain temporal continuity in modelled fire-fronts when there are extreme changes in exogenous forcing variables such as wind direction. We thus propose novel additions to the optimisation cost function that improves temporal continuity under these extreme changes. Furthermore, we develop an approach to perform data assimilation within the PINN such that the PINN predictions are drawn towards observations of the fire-front. Finally, we incorporate our novel approaches into a Bayesian PINN (B-PINN) to provide uncertainty quantification in the fire-front predictions. This is significant as the standard solver, the level-set method, does not naturally offer the capability for data assimilation and uncertainty quantification. Our results show that, with our novel approaches, the B-PINN can produce accurate predictions with high quality uncertainty quantification on real-world data.Comment: Accepted for publication in Spatial Statistic

Gender-Role Cognition in Three-Year-Old Boys and Girls

Although the multidimensionality of gender roles has been well established, few researchers have investigated male and female roles separately. Because of the substantial differences in the ways male and female roles are portrayed in our culture, boys and girls may think and learn about these roles differently. The male role is more clearly defined, more highly valued, and more salient than the female role; thus, children's cognitions about these two roles may be expected to differ. The present study addressed the question of whether there is sex-typical variation in gender labeling, gender-role knowledge, and schematicity. Participants were 120 families; 15% were from minority ethnic groups, and 17% were single-parent families; 25% of the parents had a high school education or less. Results indicated that at 36 months of age, boys were less able to label gender and less knowledgeable about gender roles than were girls. Boys' knew more about male stereotypes than female stereotypes, whereas girls knew considerably more than boys about the female role and as much as boys about the male role. Boys and girls were found to be similar in gender schematicity. Traditionality of parental attitudes regarding child-rearing and maternal employment were not strongly related to children's gender cognition.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45617/1/11199_2004_Article_226122.pd

Advancing the public health applications of Chlamydia trachomatis serology.

Genital Chlamydia trachomatis infection is the most commonly diagnosed sexually transmitted infection. Trachoma is caused by ocular infection with C trachomatis and is the leading infectious cause of blindness worldwide. New serological assays for C trachomatis could facilitate improved understanding of C trachomatis epidemiology and prevention. C trachomatis serology offers a means of investigating the incidence of chlamydia infection and might be developed as a biomarker of scarring sequelae, such as pelvic inflammatory disease. Therefore, serological assays have potential as epidemiological tools to quantify unmet need, inform service planning, evaluate interventions including screening and treatment, and to assess new vaccine candidates. However, questions about the performance characteristics and interpretation of C trachomatis serological assays remain, which must be addressed to advance development within this field. In this Personal View, we explore the available information about C trachomatis serology and propose several priority actions. These actions involve development of target product profiles to guide assay selection and assessment across multiple applications and populations, establishment of a serum bank to facilitate assay development and evaluation, and development of technical and statistical methods for assay evaluation and analysis of serological findings. The field of C trachomatis serology will benefit from collaboration across the public health community to align technological developments with their potential applications

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements