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We present the results of a search for deeply eclipsing white dwarfs in the Zwicky Transient Facility (ZTF) Data Release 4 (DR4). We identify nine deeply eclipsing white dwarf candidates, four of which we followed up with high-cadence photometry and spectroscopy. Three of these systems show total eclipses in the ZTF data and our follow-up Apache Point Observatory 3.5 m telescope observations. Even though the eclipse duration is consistent with sub-stellar companions, our analysis shows that all four systems contain a white dwarf with low-mass stellar companions of ∼0.1 M⊙. We provide mass and radius constraints for both stars in each system based on our photometric and spectroscopic fitting. Finally, we present a list of 41 additional eclipsing WD+M candidates identified in a preliminary search of ZTF DR7, including 12 previously studied systems. We identify two new candidate short-period, eclipsing, white dwarf–brown dwarf binaries within our sample of 41 WD+M candidates based on Pan-STARRS colours.

 

Background Since 1999, West Nile virus (WNV) has moved rapidly across the United States, resulting in tens of thousands of human cases. Both the number of human cases and the minimum infection rate (MIR) in vector mosquitoes vary across time and space and are driven by numerous abiotic and biotic forces, ranging from differences in microclimates to socio-demographic factors. Because the interactions among these multiple factors affect the locally variable risk of WNV illness, it has been especially difficult to model human disease risk across varying spatial and temporal scales. Cook and DuPage Counties, comprising the city of Chicago and surrounding suburbs, experience some of the highest numbers of human neuroinvasive cases of WNV in the United States. Despite active mosquito control efforts, there is consistent annual WNV presence, resulting in more than 285 confirmed WNV human cases and 20 deaths from the years 2014–2018 in Cook County alone. Methods A previous Chicago-area WNV model identified the fifty-five most high and low risk locations in the Northwest Mosquito Abatement District (NWMAD), an enclave ¼ the size of the combined Cook and DuPage county area. In these locations, human WNV risk was stratified by model performance, as indicated by differences in studentized residuals. Within these areas, an additional two-years of field collections and data processing was added to a 12-year WNV dataset that includes human cases, MIR, vector abundance, and land-use, historical climate, and socio-economic and demographic variables, and was assessed by an ultra-fine-scale (1 km spatial x 1 week temporal resolution) multivariate logistic regression model. Results Multivariate statistical methods applied to the ultra-fine-scale model identified fewer explanatory variables while improving upon the fit of the previous model. Beyond MIR and climatic factors, efforts to acquire additional covariates only slightly improved model predictive performance. Conclusions These results suggest human WNV illness in the Chicago area may be associated with fewer, but increasingly critical, key variables at finer scales. Given limited resources, these findings suggest large variations in model performance occur, depending on covariate availability, and provide guidance in variable selection for optimal WNV human illness modeling. 

For many students, trigonometry is a difficult subject because it requires strong spatial visualization abilities. A team at Jackson State University makes the teaching and learning process easer with a new learning tool for mobile phones developed using augmented reality (AR). The results indicated that AR incorporated learning tool has great potential for learning trigonometry.