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apidly changing wildfire regimes across the Western United States have driven more frequent and severe wildfires, resulting in wide-ranging societal threats from wildfires and wildfire-generated smoke. However, common measures of fire severity focus on what is burned, disregarding the societal impacts of smoke generated from each fire. We combine satellite-derived fire scars, air parcel trajectories from individual fires, and predicted smoke PM2.5 to link source fires to resulting smoke PM2.5 and health impacts experienced by populations in the contiguous United States from April 2006 to 2020. We quantify fire-specific accumulated smoke exposure based on the cumulative population exposed to smoke PM2.5 over the duration of a fire and estimate excess asthma-related emergency department (ED) visits as a result of this exposure. We find that excess asthma visits attributable to each fire are only moderately correlated with common measures of wildfire severity, including burned area, structures destroyed, and suppression cost. Additionally, while recent California fires contributed nearly half of the country’s smoke-related excess asthma ED visits during our study period, the most severe individual fire was the 2007 Bugaboo fire in the Southeast. We estimate that a majority of smoke PM2.5 comes from sources outside the local jurisdictions where the smoke is experienced, with 87% coming from fires in other counties and 60% from fires in other states. Our approach could enable broad-scale assessment of whether specific fire characteristics affect smoke toxicity or impact, inform cost-effectiveness assessments for allocation of suppression resources, and help clarify the growing transboundary nature of local air quality. [ABSTRACT FROM AUTHOR]

Federal school finance policy over the past 30 years has focused on resource allocation within school districts. Regulations require equal staffing across schools, particularly Title I schools, which are designated based on the percent of low-income students enrolled. The requirement to equalize staffing levels creates a loophole where, even with equal staffing levels, differences in staff experience and salary levels across schools lead to differences in actual spending across schools. In response, recent regulatory reforms have shifted from an emphasis on equal staffing to an emphasis on equal spending. Under the federal comprehensive support and improvement (CSI) system, states are required to periodically review within-district spending gaps for any district with a significant number of identified schools. We analyze spending gaps within districts in California and assess the extent to which the CSI system targets districts with inequitable spending patterns. We find that racial and income-based spending gaps across-schools are not substantially different for districts with CSI schools and districts with no CSI schools. Importantly, many districts with large spending gaps are not included in the policy and thus do not face federal regulations to measure and address resource disparities across schools. We discuss implications for school finance research and policy moving forward, particularly as schools respond to the global pandemic and reopening process. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A severe outbreak of wildfire across the US Pacific Coast during August 2020 led to persistent fire activity through the end of summer. In late September, Fire Weather Outlooks predicted higher than usual fire activity into the winter in parts of California, with concomitant elevated fire danger in the Southeastern US. To help inform the regional and national allocation of firefighting personnel and equipment, we developed visualizations of resource use during recent late season, high-demand analogs. Our visualizations provided an overview of the crew, engine, dozer, aerial resource, and incident management team usage by geographic area. While these visualizations afforded information that managers needed to support their decisions regarding resource allocation, they also revealed a potentially significant gap between resource demand and late-season availability that is only likely to increase over time due to lengthening fire seasons. This gap highlights the need for the increased assessment of suppression resource acquisition and allocation systems that, to date, have been poorly studied. [ABSTRACT FROM AUTHOR]

Channel allocation has a direct and profound impact on the performance of vehicle-to-everything (V2X) networks. Considering the dynamic nature of vehicular environments, it is appealing to devise a blended strategy to perform effective resource sharing. In this paper, we exploit deep learning techniques predict vehicles’ mobility patterns. Then we propose an architecture consisting of centralized decision making and distributed channel allocation to maximize the spectrum efficiency of all vehicles involved. To achieve this, we leverage two deep reinforcement learning techniques, namely deep Q-network (DQN) and advantage actor-critic (A2C) techniques. In addition, given the time varying nature of the user mobility, we further incorporate the long short-term memory (LSTM) into DQN and A2C techniques. The combined system tracks user mobility, varying demands and channel conditions and adapt resource allocation dynamically. We verify the performance of the proposed methods through extensive simulations and prove the effectiveness of the proposed LSTM-DQN and LSTM-A2C algorithms using real data obtained from California state transportation department. [ABSTRACT FROM AUTHOR]

During the Covid‐19 pandemic, the University of California convened the University of California Critical Care Bioethics Working Group, a team of twenty individuals tasked with developing a set of triage procedures. This article highlights several crucial components of the UC procedures and describes the reasoning behind them. The recommendations and the reasoning in the UC protocol are distinctive because of the emphasis the working group placed on grounding its decisions on the public's preferences for triage protocols. To highlight the distinctiveness of the recommendations and reasoning, this article contrasts the UC procedures with the triage procedures known as the "Pittsburgh framework." Among the specific topics discussed are age discrimination, disability discrimination, the prioritization of critical workers for scarce resources, and triage priority for pregnant patients. [ABSTRACT FROM AUTHOR]

There is interest in stock enhancement to support fisheries for California halibut Paralichthys californicus , a regionally important yet depleted species in the Southern California Bight (SCB), U.S. A quantitative model was developed to assess the cost of increasing harvestable California halibut in the SCB via releases of cultured juveniles. Reduced post-release survival of cultured juveniles was incorporated into the model, as was sex-specific lifetime survival, growth, and maturity. Simulations examined how adult California halibut population metrics were influenced by key release-strategy variables (i.e., size, number, survival, and sex ratio of released juveniles). A target increase in abundance of harvestable (≥ 559 mm total length; TL) California halibut by 5% in the entire SCB could likely be achieved by releasing large numbers (0.1–1.6 million per year) of larger-sized juveniles (40–200 mm TL). However, this was strongly mediated by their survival and sex ratio; fewer and smaller juveniles were required when releases comprised better surviving and / or more female individuals. Depending on the survival and sex ratio of released juveniles, increasing harvestable abundance in the SCB to achieve this 5% target was estimated to cost US$ 0.2–2.9 million annually, or US$ 14–219 per additional harvestable California halibut in the wild. This exploratory modeling study demonstrates that releasing juvenile California halibut could be a feasible management tool in the SCB, and provides a theoretical basis for field experiments. More broadly, it suggests that the allocation of resources to the production of larger and / or better surviving juveniles, in addition to optimizing release sex ratios, should be explored in stock enhancement programs. • Stock enhancement of California halibut was simulated by quantitative modeling. • Pre-defined target was achieved by releasing 0.1–1.6 million larger-sized (40–200 mm) juveniles. • Outcomes were strongly mediated by survival and sex ratio of released fish. • Annual costs to achieve the target were US$ 0.2–2.9 million. • Provides guidance for the allocation of resources in stock enhancement programs. [ABSTRACT FROM AUTHOR]