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Due to the mixed distribution of buildings and vegetation, wildland-urban interface (WUI) areas are characterized by complex fuel distributions and geographical environments. The behavior of wildfires occurring in the WUI often leads to severe hazards and significant damage to man-made structures. Therefore, WUI areas warrant more attention during the wildfire season. Due to the ever-changing dynamic nature of California's population and housing, the update frequency and resolution of WUI maps that are currently used can no longer meet the needs and challenges of wildfire management and resource allocation for suppression and mitigation efforts. Recent developments in remote sensing technology and data analysis algorithms pose new opportunities for improving WUI mapping methods. WUI areas in California were directly mapped using building footprints extracted from remote sensing data by Microsoft along with the fuel vegetation cover from the LANDFIRE dataset in this study. To accommodate the new type of datasets, we developed a threshold criteria for mapping WUI based on statistical analysis, as opposed to using more ad-hoc criteria as used in previous mapping approaches. This method removes the reliance on census data in WUI mapping, and does not require the calculation of housing density. Moreover, this approach designates the adjacent areas of each building with large and dense parcels of vegetation as WUI, which can not only refine the scope and resolution of the WUI areas to individual buildings, but also avoids zoning issues and uncertainties in housing density calculation. Besides, the new method has the capability of updating the WUI map in real-time according to the operational needs. Therefore, this method is suitable for local governments to map local WUI areas, as well as formulating detailed wildfire emergency plans, evacuation routes, and management measures.

Fully distributed hydrologic models are often used to simulate hydrologic states at fine spatio-temporal resolutions. However, simulations based on these models may become computationally expensive, constraining their applications to smaller domains. This study demonstrates that a nested-discretization based modeling strategy can be used to improve the efficiency of distributed hydrologic simulations, especially for applications where fine resolution estimates of hydrologic states are of the focus only within a part of a watershed. To this end, we consider two applications where the goal is to capture the groundwater dynamics within a defined target area. Our results show that at the target locations, a nested simulation is able to competently replicate the estimates of groundwater table as obtained from the fine simulation, while yielding significant computational savings. The results highlight the potential of using nested discretization for a detailed yet computationally efficient estimation of hydrologic states in part of the model domain.

Fabrication of heterojunction between 2D molybdenum disulfide (MoS2) and gallium nitride (GaN) and its photodetection properties have been reported in the present work. Surface potential mapping at the MoS2/GaN heterojunction is done using Kelvin Probe Force Microscopy to measure the conduction band offset. Current-voltage measurements show a diode like behavior of the heterojunction. The origin of diode like behavior is attributed to unique type II band alignment of the heterojunction. The photocurrent, photoresponsivity and detectivity of the heterojunction are found to be dependent on power density of the light. Photoresponse investigations reveal that the heterojunction is highly sensitive to 405 nm laser with very high responsivity up to 105 A/W. The heterojunction also shows very high detectivity of the order of 1014 Jones. Moreover, the device shows photoresponse in UV region also. These observations suggest that MoS2/GaN heterojunction can have great potential for photodetection applications. [ABSTRACT FROM AUTHOR]

Emerging outbreaks of newly found, highly pathogenic avian influenza (HPAI) A(H5N8) viruses have been reported globally. Previous studies have indicated that H5N8 pathogenicity in mice is relatively moderate compared with H5N1 pathogenicity. However, detailed mechanisms underlying avian influenza pathogenicity are still undetermined. We used a high-throughput RNA-seq method to analyse host and pathogen transcriptomes in the lungs of mice infected with A/MD/Korea/W452/2014 (H5N8) and A/EM/Korea/W149/2006 (H5N1) viruses. Sequenced numbers of viral transcripts and expression levels of host immune-related genes at 1 day post infection (dpi) were higher in H5N8-infected than H5N1-infected mice. Dual sequencing of viral transcripts revealed that in contrast to the observations at 1 dpi, higher number of H5N1 genes than H5N8 genes was sequenced at 3 and 7 dpi, which is consistent with higher viral titres and virulence observed in infected lungs in vivo. Ingenuity pathway analysis revealed a more significant upregulation of death receptor signalling, driven by H5N1 than with H5N8 infection at 3 and 7 dpi. Early induction of immune response-related genes may elicit protection in H5N8-infected mice, which correlates with moderate pathogenicity in vivo. Collectively, our data provide new insight into the underlying mechanisms of the differential pathogenicity of avian influenza viruses. [ABSTRACT FROM AUTHOR]