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Homeowners who originally bought when marketwide price levels were high (low) fetch high (low) sales prices and rents, even decades later. We study the propagation of reference-dependence to neighboring listings. The "spillover" reference point effect is about one-half as large as the "own" reference point effect. Neither house quality nor location appears capable of explaining the result. Using a simple model to provide empirical predictions, we find support for a competition-based mechanism. We quantify the aggregate effect of own and spillover reference point effects on aggregate prices and/or rents at the ZIP code level. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

This paper examines the empirical relationship between the Madden–Julian oscillation (MJO), the quasi‐biennial oscillation (QBO), and atmospheric river (AR) activity and precipitation in California on subseasonal time scales. We introduce an experimental forecast tool that uses observed anomaly patterns during a 38 yr period to predict the probability of above‐ and below‐normal AR activity and precipitation at lead times of 1–6 weeks based on the phase and amplitude of the MJO and QBO. The hindcast prediction skill of probabilistic AR activity and precipitation forecasts is evaluated for Northern, Central, and Southern California, as well as two sets of smaller geographical domains. These smaller domains are more relevant for water resource management and allow us to investigate the sensitivity of prediction skill to domain size. Consistent with previous studies, our results demonstrate that subseasonal AR activity and precipitation in California are strongly modulated by the MJO and QBO. The anomaly patterns of AR activity and precipitation vary considerably throughout the cool season, with a tendency toward below‐normal AR activity and precipitation during easterly QBO and above‐normal AR activity and precipitation during westerly QBO in JFM. The opposite patterns are generally observed in OND, but the anomaly signals are weaker and less coherent for AR activity. Certain combinations of MJO phase, QBO phase, lag time, and season yield notably higher skill scores, reinforcing the notion of "windows of opportunity" for skillful subseasonal‐to‐seasonal predictions. In California, these forecasts of opportunity are predominantly associated with easterly QBO in JFM and FMA. Plain Language Summary: This paper examines the relationship between the Madden–Julian oscillation (MJO), the quasi‐biennial oscillation (QBO), and atmospheric river (AR) activity and precipitation in California. We introduce an experimental forecast tool that shows the likelihood of above‐normal and below‐normal AR activity and precipitation based on the phases of the MJO and QBO. Consistent with previous studies, our results demonstrate that AR activity and precipitation in California are strongly influenced by the MJO and the QBO. There is a tendency for below‐normal AR activity and precipitation during easterly QBO conditions in January–March. The opposite pattern (above‐normal AR activity and precipitation) generally occurs during westerly QBO conditions. The results also suggest that our forecast tool has some potential to improve the prediction of AR activity and precipitation. The reliability and usefulness of this forecast tool depend on multiple factors, including the MJO phase, the QBO phase, and the time of year. In California, this forecast tool is likely to provide the most beneficial value during easterly QBO conditions in mid‐winter through early spring. Key Points: The modulation of atmospheric river (AR) activity and precipitation in California by the Madden‐Julian oscillation and quasi‐biennial oscillation is quantifiedA hindcast skill assessment of probabilistic AR activity and precipitation forecasts is presentedAn experimental subseasonal AR activity and precipitation forecast tool is introduced [ABSTRACT FROM AUTHOR]

The present paper continues the series of publications by the authors devoted to solving the problem of recognition regions with potential high seismicity. It is aimed at the development of the mathematical apparatus and the algorithmic base of the FCAZ method, designed for effective recognition of earthquake-prone areas. A detailed description of both the mathematical algorithms included in the FCAZ in its original form and those developed in this paper is given. Using California as an example, it is shown that a significantly developed algorithmic FCAZ base makes it possible to increase the reliability and accuracy of FCAZ recognition. In particular, a number of small zones located at a fairly small distance from each other but having a close "internal" connection are being connected into single large, high-seismicity areas. [ABSTRACT FROM AUTHOR]

This paper examines the relationship between daily carbon emissions for California's savanna and forest wildfires and regional meteorology over the past 18 years. For each fuel type, the associated weather [daily maximum wind, daily vapor pressure deficit (VPD), and 30-day-prior VPD] is determined for all fire days, the first day of each fire, and the day of maximum emissions of each fire at each fire location. Carbon emissions, used as a marker of wildfire existence and growth, for both savanna and forest wildfires are found to vary greatly with regional meteorology, with the relationship between emissions and meteorology varying with the amount of emissions, fire location, and fuel type. Weak emissions are associated with climatologically typical dryness and wind. For moderate emissions, increasing emissions are associated with higher VPD from increased warming and only display a weak relationship with wind speed. High emissions, which encompass ∼85% of the total emissions but only ∼4% of the fire days, are associated with strong winds and large VPDs. Using spatial meteorological composites for California subregions, we find that weak-to-moderate emissions are associated with modestly warmer-than-normal temperatures and light winds across the domain. In contrast, high emissions are associated with strong winds and substantial temperature anomalies, with colder-than-normal temperatures east of the Sierra Nevada and warmer-than-normal conditions over the coastal zone and the interior of California. Significance Statement: The purpose of this work is to better understand the influence of spatially and temporally variable meteorology and spatially variable surface fuels on California's fires. This is important because much research has focused on large climatic scales that may dilute the true influence of weather (here, high winds and dryness) on fire growth. We use a satellite-recorded fire emissions dataset to quantify daily wildfire existence and growth and to determine the relationship between regional meteorology and wildfires across varying emissions in varying fuels. The result is a novel view of the relationship between California wildfires and rapidly variable, regional meteorology. [ABSTRACT FROM AUTHOR]

Traffic crashes are one of the most severe problems that affect communities worldwide. According to the World Health Organization, the annual number of global fatalities due to traffic crashes is about 1.35 million. Many factors affect the likelihood and the severity of a crash. In this paper, different factors are studied to evaluate their impact on the frequency, the severity, and the type of crashes at intersections, in order to boost road safety. California crash data have been obtained from the Highway Safety and Information System (HSIS) database and have been analyzed statistically. The analysis has included several factors such as severity, type of intersection, and the characteristics of the driver, roadway, environment, and vehicle. A negative binomial regression has been conducted by using the Statistical Analysis System (SAS®) Software for building three models. As a result, different parameters have been considered significant factors in each model. From all the models, the type of intersection and collision, the area of the crash, the type of surface type and its condition, the number of lanes, the age, and the gender have been considered significant factors for crashes at intersections. The result of this study could help reduce the likelihood and severity of crashes. [ABSTRACT FROM AUTHOR]

To explain cognitive capture, economic sociologists often examine the structure of relationships between regulators and market participants. This paper argues that the nature of regulators' misperception should be subject to analysis as well. Different types of misperceptions develop over timelines of varying lengths. Depending on the misperception, different sets of relationships and parties may therefore be the cause of regulators' capture. The paper illustrates this point with a case study of regulators' failure to detect pervasive market power in California's electricity markets between 1998 and 2001. Existing explanations focus on sellers' short‐term attempts to distract regulators from widespread evidence of market power. Using data from three archives and in‐depth interviews, I show that the regulators did not fall prey to such "information problems." Instead, their misperception resulted from a more foundational "worldview problem." This error affects regulators' basic conception of the marketplace and can be traced to earlier and more gradual forms of influence exerted by utilities that, ironically, would become the victims of market power. [ABSTRACT FROM AUTHOR]

This article examines Francisco P. Ramírez’s editorial practice of altering reprint poems culled from periodicals, books, and anthologies from across the Hispanophone world and reprinted in Southern California. By isolating El Clamor Público’s poems, mapping their potential citational provenance and place of publication, and comparing reproductions to originals, I show how Ramírez’s reprint practices shaped authorship and genre in his paper. I propose Ramírez’s reprint practices are important examples of the print culture norm of editing reprint poems to centralize the reading public’s interests and experiences. Ramírez’s reprint practices made the poems more understandable to and relevant for a California audience while at the same time facilitating an intellectual and cultural sense of belonging that resists the reproduction of knowledge and aesthetics from a non-California epistemology. [ABSTRACT FROM AUTHOR]

California has experienced one of the most intense and prolonged droughts in its history in the last decade, prompting the state government to undertake a series of policy responses. This paper compares the impact of the 2015 urban water-use reduction mandate with respect to pre-policy voluntary conservation efforts and post-policy water consumption trends by examining utility-level water demand dynamics of the Metropolitan Water District in Southern California. The findings overall indicate that despite voluntary measures resulting in a gradual decline in urban water-use, the introduction of the regulatory stick achieved swift reduction targets that remained even after removal of the mandatory policy. [ABSTRACT FROM AUTHOR]

This paper proposes a modeling approach for characterizing the probability of wildfire ignition caused by faults on power distribution systems. The proposed model serves as a starting point in research literature to illustrate, from an analytical perspective, the many factors that influence wildfire ignitions in power distribution systems. This paper presents the series of events that leads to power-system-related wildfire ignitions, and characterizes the wildfire ignition probability as a combination of the probability that a fault occurs along a power distribution line segment, and the probability that the fault results in the sustained ignition of a vegetation fuel bed surrounding the line. The proposed model integrates a variety of data including environmental conditions, power system protection settings, and power system line flows. A case study is performed on a test 33-bus distribution system using observed historical weather data from a high-threat fire district in California. The California case study is utilized to investigate the effects of three primary factors (wind speed, line congestion, and protection settings) on wildfire ignition probability. [ABSTRACT FROM AUTHOR]

BACKGROUND Integrating unmanned aerial vehicles (UAV) as a new method of pesticide application into existing commercial crop protection systems requires extensive research and comparison to conventional, proven application technology. Pest control expressed as efficacy against target pests, and spray quality expressed as coverage and chemical residue are three key criteria. We investigated and compared these quantitative parameters between a multi‐rotor UAV and conventional piloted airplanes in two commercial alfalfa production systems. RESULTS: Effective and equivalent control of leaf‐feeding insect pests was achieved by both methods of aerial application when delivering chlorantraniliprole at the same labeled use rate in different spray volumes (46.8 and 93.5 L ha–1) on commercially grown alfalfa in California. Residue levels and spray coverage were also comparable and consistent between the UAV and airplane applications across three sampling techniques, specifically residue levels on alfalfa, insecticide recovery from filter paper, and spray coverage on water sensitive cards. Differences in droplet size and deposit characteristics were more variable for the UAV than airplanes based on analysis of deposition images. CONCLUSION: The results of this study provide confidence supporting the use of small‐scale multi‐rotor UAVs for pesticide application on agricultural crops. According to the parameters tested, UAV application quality and crop protection performance were comparable to that of the conventional fixed wing airplane application. However, the droplet spectrum and the short‐term fate of droplets from unmanned aerial spray system require further optimization for effective and efficient crop protection with minimal risk to the environment. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty. [ABSTRACT FROM AUTHOR]

Water reuse with Advanced Water Treatment (AWT) is increasingly appealing for urban areas seeking water supply reliability. In cities facing water scarcity, how can large-scale reuse support reliability and how do reuse operations affect water quality, energy use, and water conservation? This paper presents a systems analysis of metropolitan-scale water reuse and its effects on water supply and quality. For the case study of Los Angeles County, California, USA, hydroeconomic modeling is used to evaluate reuse as a contributor to water supply given urban water conservation, drought-induced water scarcity, and costs and benefits for supply and demand. Results indicate that AWT can be a viable source of supply especially when coupled with conservation. Across modeled scenarios, reuse provides as much as 30% of regional supplies. New water reuse with AWT becomes viable when imported water availability is 50% or less of historic values. Existing indirect potable reuse operations in the county remain important. Systemwide energy intensity of operations increases with greater reuse in the absence of water conservation. Modeled influent flow rates to wastewater treatment plants resemble historical values, but extreme flow events could pose risks. The paper offers a holistic framework to evaluate water reuse as a component of urban water management. [ABSTRACT FROM AUTHOR]

Parking supply is one of the most neglected elements of the built environment in travel behavior research, despite evidence linking parking with vehicle use. As transportation impacts of new development are increasingly measured by vehicle miles traveled (VMT), explicitly connecting parking characteristics with vehicle travel is necessary to better inform transportation and land use policy. In this paper, we begin to address this research gap and explore the relationship between constrained parking and household VMT. Utilizing the 2017 National Household Travel Survey (NHTS) California add-on sample, we estimate residential parking constraint for households in Los Angeles County. Then, we develop a two-level model framework. Level 1 (Cost) models estimate travel costs, represented by vehicle ownership as a function of parking constraints, the built environment, and demographics. Level 2 (Demand) models regress household-level total and homebased-work VMT on predicted vehicle ownership, controlling for temporal and environmental characteristics. To further explore the relationship between parking and VMT by place type, we applied Level 1 and Level 2 models to develop a suite of scenarios for typical households in Los Angeles County. Our findings support the hypothesis that the built environment (including parking) influences VMT through travel costs (vehicle ownership). Results from scenarios analysis reveal constrained on-site residential parking (< 1 parking space per dwelling unit), accounts for an approximate 10–23 percentage-point decrease in VMT within each place type. Finally, implications for practice and future research are presented. [ABSTRACT FROM AUTHOR]

Some financial disruptions that started in California, U.S., in March 2023, resulting in the closure of several medium-size U.S. banks, shed new light on the role of liquidity in business cycle dynamics. In the normal path of the business cycle, liquidity and output mutually interact. Small shocks generally lead to mean reversion through market forces, as a low degree of liquidity dissipation does not significantly disrupt the economic dynamics. However, larger shocks and greater liquidity dissipation arising from runs on financial institutions and contagion effects can trigger tipping points, financial disruptions, and economic downturns. The latter poses severe challenges for Central Banks, which during normal times, usually maintain a hands-off approach with soft regulation and monitoring, allowing the market to operate. However, in severe times of liquidity dissipation, they must swiftly restore liquidity flows and rebuild trust in stability to avoid further disruptions and meltdowns. In this paper, we present a nonlinear model of the liquidity–macro interaction and econometrically explore those types of dynamic features with data from the U.S. economy. Guided by a theoretical model, we use nonlinear econometric methods of a Smooth Transition Regression type to study those features, which provide and suggest further regulation and monitoring guidelines and institutional enforcement of rules. [ABSTRACT FROM AUTHOR]

Sustainable pavement is the need of the hour using the mechanistic and robust pavement design approach, eliminating empiricism in the present IRC SP 72-2015 design guidelines, if any. Giroud and Han (2004) (GH) approach has confirmed existing empiricism in IRC SP 72-2015 design guidelines and permits the use of locally available material, thus saving transportation costs and reducing air pollution. IRC SP 72 – 2015 recommends design thickness only for the unreinforced condition in gravel roads for the maximum rut of 50mm. This paper presents the comparative study of an unreinforced and geotextile-reinforced gravel road design for Indian conditions with the rut as a vital design parameter using the GH method for subgrade classes with 2% to 5% CBR and the maximum traffic count of 100,000. The proposed unique equation provides Allowable Rut Depth (ARD) based aggregate thickness for 10,000 to 100,000 traffic count apart from simplifying the complex procedure of the GH approach for IRC SP 72-2015 data. The unique equation's result reveals an increase of 22.65% in aggregate thickness is attributed to the increase in ARD of 30mm using locally available poor aggregates. This confirms the practical relevance of ARD in pavement design that may help in planning maintenance programs and road rehabilitation strategies. The results obtained from the unique equation match 85 to 100% with GH results. Saving up to 36.5% to 76.9% of costly aggregate is found in the case of geotextile-reinforced gravel roads in Indian conditions. [ABSTRACT FROM AUTHOR]

Red beds (RBs) are widely distributed in all continents of the world. With the rapid development of road and railway construction, the construction of roads and railways in RB areas is increasing. However, when RB is the filler, it will expose three aspects of serious deficiencies in compaction, mechanical bearing capacity, and water stability, which will cause fatal harm to the subgrade. Therefore, RB has to be abandoned and cannot be used as a subgrade filler. In this paper, different microwave irradiation temperatures (DMITs) from room temperature of 25°C to 700°C were used to reveal the enhancing mechanism of RB in three aspects based on the analysis results of microscopic composition and structure. The microscopic composition and structure show that RB can be divided into a low-temperature section (25°C–400°C) and a high-temperature section (500°C–700°C) under the microwave condition. The low-temperature section has some improvement in the engineering performance of RB, but the influence is limited. The engineering performance of RB is improved completely in the high-temperature section. Specifically, the coarse size of RB increases with the rise in microwave temperature, which is beneficial for improving fine size. The compaction property of RB is not largely affected by the water content and can still meet the most stringent subgrade filler requirements, even under saturated conditions or 0. The California bearing ratio (CBR) value can maintain more than 20% under the ultimate working condition, far higher than the code requirements. The increase of internal friction angle and cohesion can enhance the stability of the cut slope, which is conducive to construction in remote mountainous areas. The water resistance of RB is positively correlated with the microwave irradiation temperature, especially at 700°C; RB experiences secondary hardening after encountering water, the mechanical strength increases, and the softening coefficient reaches 107.44%. The research shows that after microwave high-temperature stabilization, the engineering characteristics of the RB are thoroughly strengthened, and it becomes a high-quality subgrade filler to eliminate the three diseases of RB subgrade completely. Compared with the traditional method of adding stabilizers, microwave in situ RB stabilization reduces the site construction's complexity, saves a lot of stabilizer use and transportation costs, and can effectively reduce carbon emissions. This study provides a positive perspective on the in situ application of the RB soft rock subgrade. It could be a starting point for understanding the microwave-based stabilization of soft rock soils subgrade filler in situ. [ABSTRACT FROM AUTHOR]

Oilfield Produced Water (OPW) has been identified as a viable solution to mitigate water scarcity in California's Central Valley. However, consumer perception on the use of OPW outside of the oil and gas industry remains unknown and poses a hurdle for large-scale adoption. This paper, based on 134 randomly selected residents of Kern County (California's largest oil-producing county and top agricultural region), examined attitudes towards OPW reuse. In the survey, more than half (52.3%) of participants said that they have heard about oilfield-produced water and other reclaimed waters. Findings also suggest that participants mostly preferred rain and stormwater, and interestingly scored OPW higher than industrial and black waters for irrigation purposes. Around 67% of the participants supported the use of oilfield-produced water for irrigating crops. Younger people (18–29 years) expressed greater concern about using OPW compared to the older residents. Given the drought conditions in Central Valley, policymakers might need to focus on a circular economy and mandate the use of OPW in Central Valley considering that this region's economy lies at the nexus of the O&G and agriculture industries. [ABSTRACT FROM AUTHOR]

Tax increment financing (TIF) is a mechanism used by municipal governments throughout the United States to fund public and private urban development projects. This paper examines the trajectories of TIF in the state of California and the City of Chicago, where the expansion of TIF as a mechanism for publicly financed development is inextricable from disinvestments in social reproduction and the transformation of public funding for K-12 education. Taking seriously the divergent paths of TIF in each case, we argue that the framework of social reproduction helps expand the scope of TIF as a "policy in place," bringing into view other path and place-dependent factors that shape the adaptation and implementation of public finance mechanisms. Bridging the literature on urban policy and feminist political economy, we suggest that scholars must investigate the place-specific entanglements of social reproduction and public finance if we are to understand how mechanisms such as TIF are adopted, expanded, or curtailed within the broader framework of neoliberal urban governance. In making such an intervention, we expand on calls to attend to the ways public finance can heighten or mitigate economic inequality. [ABSTRACT FROM AUTHOR]

Demand for food and water are increasing while the extent of arable land and accessible fresh water are decreasing. This poses global challenges as economies continue to develop and the population grows. With agriculture as the leading consumer of water, better understanding how water is used to produce food may help support the increase of Crop Water Productivity (CWP; kg/m3), the ratio of crop output per unit of water input (or crop per drop). Previous large-scale CWP studies have been useful for broad water use modeling at coarser resolutions. However, obtaining more precise CWP, especially for specific crop types in a particular area and growing season as outlined here are important for informing farm-scale water management decision making. Therefore, this study focused on California's Central Valley utilizing high-spatial resolution satellite imagery of 30 m (0.09 hectares per pixel) to generate more precise CWP for commonly grown and water-intensive irrigated crops. First, two products were modeled and mapped. 1. Landsat based Actual Evapotranspiration (ETa; mm/d) to determine Crop Water Use (CWU; m3/m2), and 2. Crop Productivity (CP; kg/m2) to estimate crop yield per growing season. Then, CWP was calculated by dividing CP by CWU and mapped. The amount of water that can be saved by increasing CWP of each crop was further calculated. For example, in the 434 million m2 study area, a 10% increase in CWP across the 9 crops analyzed had a potential water savings of 31.5 million m3 of water. An increase in CWP is widely considered the best approach for saving maximum quantities of water. This paper proposed, developed, and implemented a workflow of combined methods utilizing cloud computing based remote sensing data. The environmental implications of this work in assessing water savings for food and water security in the 21st century are expected to be significant. [ABSTRACT FROM AUTHOR]

The use of polarimetric synthetic aperture radar (PolSAR) is one of the most successful tools for solving remote sensing problems. The multidimensional speckle noise encountered in the acquisition of these images is the main challenge for PolSAR users. Therefore, tailored processing of PolSAR images is required, especially for the use of hypothesis testing in change detection. In this paper, we use McKay's bivariate gamma distribution (MBG) to describe a joint distribution resulting from two components of the total scattering power image (SPAN). We derive closed form expressions for the MBG Kullback–Leibler and Rényi divergences between SPAN-based random pairs. We provide new two-sample divergence-based hypothesis tests and evaluate their performance using Monte Carlo experiments. Finally, we apply the new tests to real PolSAR images to evaluate the changes caused by urbanization processes in the Los Angeles and California regions. The results show that our proposals are able to detect changes in PolSAR images. [ABSTRACT FROM AUTHOR]

The early 2020s diversity, equity, and inclusion movement has prompted debate about banning the use of suspect insurance pricing variables because they discriminate against protected classes, such as gender. This paper demonstrates how banning an insurance pricing variable currently used in insurance pricing models can result in regulatory adverse selection if the ban heterogeneously combines policyowners with different expected losses into the same risk class, contrary to risk‐based pricing. The paper begins by describing several recent regulatory and judicial decisions to ban insurance pricing variables. It next describes the process used by insurers to set insurance prices, followed by a discussion of applicable insurance discrimination laws. Using a simple risk aversion model, the paper next examines whether a ban on gender‐based auto insurance pricing in California in 2019 results in regulatory adverse selection. The paper concludes by describing possible alternative pricing variables available to auto insurers if gender‐based pricing is banned. [ABSTRACT FROM AUTHOR]

Calls for using marine protected areas (MPAs) to achieve goals for nature and people are increasing globally. While the conservation and fisheries impacts of MPAs have been comparatively well‐studied, impacts on other dimensions of human use have received less attention. Understanding how humans engage with MPAs and identifying traits of MPAs that promote engagement is critical to designing MPA networks that achieve multiple goals effectively, equitably and with minimal environmental impact.In this paper, we characterize human engagement in California's MPA network, the world's largest MPA network scientifically designed to function as a coherent network (124 MPAs spanning 16% of state waters and 1300 km of coastline) and identify traits associated with higher human engagement. We assemble and compare diverse indicators of human engagement that capture recreational, educational and scientific activities across California's MPAs.We find that human engagement is correlated with nearby population density and that site "charisma" can expand human engagement beyond what would be predicted based on population density alone. Charismatic MPAs tend to be located near tourist destinations, have long sandy beaches and be adjacent to state parks and associated amenities. In contrast, underutilized MPAs were often more remote and lacked both sandy beaches and parking lot access.Synthesis and applications: These results suggest that achieving MPA goals associated with human engagement can be promoted by developing land‐based amenities that increase access to coastal MPAs or by locating new MPAs near existing amenities during the design phase. Alternatively, human engagement can be limited by locating MPAs in areas far from population centres, coastal amenities or sandy beaches. Furthermore, managers may want to prioritize monitoring, enforcement, education and outreach programmes in MPAs with traits that predict high human engagement. Understanding the extent to which human engagement impacts the conservation performance of MPAs is a critical next step to designing MPAs that minimize tradeoffs among potentially competing objectives. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

This paper investigates whether shocks in oil prices affect the level of crime in Kern County, California's top oil producing county. Monthly data from 2003 to 2018 is employed using a nonlinear autoregressive distributed lag model to test the asymmetric effects of these changes. Results for Kern County indicate that in the long-run, a negative shock in oil prices increases criminal activity while short-run oil price changes have no effect on criminal activity. Results from neighboring counties indicate that positive shocks to oil prices increase criminal activity in wealthy regions. Findings from generalized impulse response functions indicate that criminal activity in Los Angeles, Kings and San Bernardino Counties respond to shocks from Kern County's crime rates. They also indicate that criminal activity in Inyo and Los Angeles Counties influence Kern County's crime rate. [ABSTRACT FROM AUTHOR]

The existing machine learning (ML) models for vibration-based damage assessments often use highly compressed features or are restricted to preprocessed signals with fixed durations and sampling rates. Additionally, the learning capacities of ML models and computational resources are limited, which restricts using raw signals as direct input. This paper studied Mel filter banks (MFBs) for seismic signal processing, inspired by speech recognition technology. It is argued that the same filter designs in audio engineering may not be appropriate for seismic records, and therefore, a customized filter bank formulation was developed. Hybrid deep learning models for rapid assessments (HyDRA) were introduced as multibranch neural network architectures that enable end-to-end training for different types of processed vibration data structures. Moreover, the performance-based earthquake engineering (PBEE) equation was adjusted to integrate ML model uncertainties for probabilistic assessments. The proposed concepts were validated in a case study based on a data set of 32,400 nonlinear time-history analyses of a highway bridge in California. Insights and guidelines are provided for optimum filter design based on 5,184 experiments. Several HyDRA architectures were compared with benchmark models. The optimized MFB feature type outperformed features obtained from continuous wavelet transform and a stacked vector of conventional earthquake engineering indexes. A Bayesian variant of HyDRA was investigated to showcase its integration in the modified PBEE equation. Adopting custom filter banks with the HyDRA architecture enables effective feature extraction from raw vibration records by diversifying feature space and preserving information in the time and frequency domains. [ABSTRACT FROM AUTHOR]

Nowcasting is a term originating from economics, finance, and meteorology. It refers to the process of determining the uncertain state of the economy, markets or the weather at the current time by indirect means. In this paper, we describe a simple two‐parameter data analysis that reveals hidden order in otherwise seemingly chaotic earthquake seismicity. One of these parameters relates to a mechanism of seismic quiescence arising from the physics of strain‐hardening of the crust prior to major events. We observe an earthquake cycle associated with major earthquakes in California, similar to what has long been postulated. An estimate of the earthquake hazard revealed by this state variable time series can be optimized by the use of machine learning in the form of the Receiver Operating Characteristic skill score. The ROC skill is used here as a loss function in a supervised learning mode. Our analysis is conducted in the region of 5° × 5° in latitude‐longitude centered on Los Angeles, a region which we used in previous papers to build similar time series using more involved methods (Rundle & Donnellan, 2020, https://doi.org/10.1029/2020EA001097; Rundle, Donnellan et al., 2021, https://doi.org/10.1029/2021EA001757; Rundle, Stein et al., 2021, https://doi.org/10.1088/1361-6633/abf893). Here we show that not only does the state variable time series have forecast skill, the associated spatial probability densities have skill as well. In addition, use of the standard ROC and Precision (PPV) metrics allow probabilities of current earthquake hazard to be defined in a simple, straightforward, and rigorous way. Plain Language Summary: Earthquake nowcasting refers to the determination of hazard for major earthquakes at the present time, the recent past, and the near future. Nowcasting is an idea borrowed from economics, markets, and meteorology, where it has been frequently used. In this paper, we show that there is order hidden within chaotic earthquake seismicity using a very simple transformation of the data. Small earthquakes appear to transition from unstable stick‐slip events that produce seismic waves, to stable sliding where no seismic waves are produced. Our hypothesis is that this transition is due to a material phenomenon called strain‐hardening, that is frequently observed in laboratory rock mechanics experiments. The result is a state variable time series, computed over the last 51 years in California, that strongly resembles the long‐anticipated cycle of stress accumulation and release. Using supervised machine learning techniques, we can optimize the two‐parameter model. From that optimized model, we can rigorously calculate the probability of current hazard from major earthquakes. Extending these methods, we can also compute spatial hazard as well. The result is a new method for assessing earthquake hazard that may be useful for a variety of applications. Key Points: "Chaotic" seismicity contains hidden structure in the form of state variable time seriesStandard data science methods can be used to convert the time series to probabilitiesBoth temporal and spatial probabilities can be computed [ABSTRACT FROM AUTHOR]

Although widely acknowledged as an important social determinant of health, until recently researchers and policymakers have primarily approached housing insecurity as an urban issue, obscuring the visibility of its impacts in rural contexts, including the ways in which housing insecurity intersects with other health and structural inequities facing rural populations. Working to address this gap in the existing literature, this paper explores the experiences of housing insecurity in a rural context by reporting on an analysis of 210 in-depth interviews with 153 adults between the ages of 18–35, living in California's rural North State, a relatively overlooked far northern region of the state comprised of 12 north central and north eastern counties. Using in-depth qualitative interview data, we conducted an exploratory pattern-level analysis of participants' narratives structured by four dimensions of housing insecurity defined in the literature (housing affordability, housing stability, housing conditions, and neighborhood context). Drawing attention to the pervasiveness of rural housing insecurity within our sample, this analysis highlights the unique ways in which rurality creates distinct experiences not currently captured in the existing literature. Further research is needed across different types of rural communities to better understand the various ways that housing insecurity affects the everyday lives and health of rural residents. By grounding research within the experiences of rural residents, we are better able to respond to the crisis of rural housing insecurity and develop solutions that are tailored to rural residents' unique needs. [ABSTRACT FROM AUTHOR]

The escalating challenges of waste management and the increasing demand for sustainable construction practices have spurred growing attention to the innovative use of waste materials in various construction applications. Past studies reveal that the incorporation of waste materials into construction processes has contributed to environmental sustainability by reducing the burden on landfills and conserving natural resources. This paper explores the diverse range of waste materials being re-purposed in construction, including, agricultural residues of rice husk called rice husk ash and industrial by-products from brick kilns called brick kiln dust (BKD). Various laboratory tests including differential free swell, Atterberg's limits, modified Proctor, unconfined compressive strength, and California bearing ratio, were performed on black cotton soil (BCS) alone and in combination with varying percentages of rice husk ash and brick kiln dust. Additionally, the thickness of the flexible pavement was evaluated for various optimum combinations based on California bearing ratio values and finally, economic feasibility associated with the use of waste materials was addressed, providing insights into the overall sustainability of such practices. Also, the laboratory test indicates an improvement in the geotechnical characteristics of black cotton soil by adding an optimum amount of RHA (20%) and BKD (15%) alone and in combination with each other. Moreover, the required thickness for the flexible pavement was found to be reduced corresponding to each million standard axels loading conditions. Furthermore, it is evident from the results that the cost of the flexible pavement was substantially reduced for all the optimum mixes and the highest economy of 65% has been achieved corresponding to BCS:RHA:BKD::65:20:15. [ABSTRACT FROM AUTHOR]

In this paper the meteorological drivers of North American Monsoon (NAM) extreme precipitation events (EPEs) are identified and analyzed. First, the NAM area and its subregions are distinguished using self‐organizing maps applied to the Climate Prediction Center global precipitation data set. This reveals distinct subregions, shaped by the inhomogeneous geographic features of the NAM area, with distinct extreme precipitation character and drivers. Next, defining EPEs as days when subregion‐mean precipitation exceeds the 95th percentile of rainy days, five synoptic features and one mesoscale feature are investigated as potential drivers of EPEs. Essentially all EPEs can be associated with at least one selected driver, with only one event remaining unclassified. This analysis shows the dominant role of Gulf of California moisture surges, mesoscale convective systems and frontal systems in generating NAM extreme precipitation. Finally, a frequency and probability analysis is conducted to contrast precipitation distributions conditioned on the associated meteorological drivers. The findings demonstrate that the co‐occurrence of multiple features does not necessarily enhance the EPE probability. Plain Language Summary: Extreme precipitation is of great importance for both geophysical and socioeconomic reasons. This study first identifies geographic subregions of the North American Monsoon within which extreme precipitation exhibits distinct characteristics. The extreme precipitation events in each subregion are then associated with at least one candidate atmospheric driver, revealing the dominant precipitation drivers among subregions. Depending on the subregions and driver, precipitation rates may increase or decrease when two candidate factors co‐occur. Several such double driver combinations are examined. Key Points: Seven subregions of the North American Monsoon with distinct precipitation characters are identifiedGulf of California moisture surges, mesoscale convective systems and frontal systems are primary drivers of extreme precipitationA probability analysis reveals the nonlinear and non‐additive characters of the interactions among extreme precipitation event drivers [ABSTRACT FROM AUTHOR]

Motivated by debates about California's net migration loss, we employ valued exponential-family random graph models to analyze the inter-county migration flow network in the United States. We introduce a protocol that visualizes the complex effects of potential underlying mechanisms and perform in silico knockout experiments to quantify their contribution to the California Exodus. We find that racial dynamics contribute to the California Exodus, urbanization ameliorates it, and political climate and housing costs have little impact. Moreover, the severity of the California Exodus depends on how one measures it, and California is not the state with the most substantial population loss. This paper demonstrates how generative statistical models can provide mechanistic insights beyond simple hypothesis-testing. [ABSTRACT FROM AUTHOR]

This paper examines whether U.S./Mexico border residence in California is related to the prevalence of DSM-5 alcohol use disorder (AUD) among Whites and Hispanics. Household survey data were obtained from 1,209 adults (59.7% female) 18 to 39 years of age resident in four counties in California: Imperial on the U.S./Mexico border; and Kern, Tulare, and Madera in California's Central Valley. Households were selected using a list assisted sample, with data collected on the phone or online. Results show that AUD rates were not different between border and non-border location and between Whites and Hispanics. AUD was negatively associated with higher income ($20,000 to $60,000: AOR=.38; 95%CI=.17–.86; p<.01—more than $60,000: AOR=.27; 95%CI:.09–.81; p<.01) and poor risk perception (AOR=.86; 95%CI=.78–.94; p<.01). AUD was positively associated with continued volume of drinking (AOR = 1.05; 95%CI = 1.01–1.09; p<.01), drinking in Mexico (AOR = 4.28; 95%CI = 1.61–11.36; p<.01), marijuana use (AOR = 4.11; 95%CI = 1.73–9.77; p<.01), and impulsivity (AOR = 1.55; 95%CI = 1.23–1.94). Efforts to prevent AUD in the population in California, and especially among those who live close to the border with Mexico, should take into consideration factors such as impulsivity, marijuana use, border crossing to drink in Mexico, all of which increased risk of AUD. [ABSTRACT FROM AUTHOR]

This paper investigates how Supplemental Nutrition Assistance Program (SNAP) eligibility affects food expenditures. A 2019 policy change in California granted SNAP eligibility to previously ineligible Supplemental Security Income (SSI) recipients. Using the Consumer Expenditure Survey, we find that after the policy change, affected SSI recipients increased their "food at home" budget share between 2.5 and 4.3 percentage points ($120 to $206 per quarter). The SNAP effect on total food expenditures is dampened by a decrease in "food away from home" which SNAP benefits cannot be spent on. [ABSTRACT FROM AUTHOR]

This second special issue of the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) further advances and expands upon the initial research findings of the first GRAPEX special issue on the measurement and remote sensing of vine water use and stress. This is a highly collaborative and interdisciplinary experiment, which involves USDA-ARS scientists, industry, and university researchers. The large scope of this research has allowed the development of new measurement and remote sensing tools and techniques to quantify vine evapotranspiration, moisture status, and stress, with the ultimate goal of improving irrigation management in California vineyards. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to provide a human ecology economics (HEE) framework for understanding and addressing homelessness, especially as it exists in California and the San Francisco Bay Area. The role of business and private "stakeholders of the homeless" is emphasized. Design/methodology/approach: The HEE approach relies on evolutionary and complex systems processes, and it incorporates interdisciplinary material from the humanities. Within HEE, an early-stage exploratory research method is used. In-depth interviews with 16 long-term residents who are also managers in various organizations help to identify private-sector perceptions including how businesses can engage with and support the homeless. Findings: In the current balance between needed supplies of "production capital," which includes affordable housing, shelter beds, food, clothing, medical supplies and so on and "transaction capital," which is an interacting mix of social capital, informational capital and financial capital, the authors find that the business community needs to pay greater attention to deficits in "transaction capital." Research limitations/implications: It is beyond the scope of this paper, and beyond the current ability of complex system modeling, to prioritize the best interventions across various types of homeless communities. However, for early-stage research, the authors have provided a useful ontology of the human ecology of homelessness that might inform further research and policy initiatives. Follow-on research might then investigate, with more rigorous methods, the narrower causalities between subcomponents of one's ontology. Originality/value: Scholars, policymakers and business community activists might appreciate the more comprehensive and accessible interdisciplinary framework for understanding the causes and possible responses to homelessness. [ABSTRACT FROM AUTHOR]

This paper studies whether and how mandatory nonfinancial disclosure affects firms' real decisions. I exploit a disclosure regulation enacted in California, which mandates that firms disclose how they conduct due diligence to address their suppliers' human rights abuses. I find that treated firms increase their supply chain due diligence, and their suppliers' human rights performance improves following the regulation. The effects are stronger when firms face greater pressure from non-governmental organizations (NGOs) and socially conscious shareholders, when customers have greater incentives to use the newly disclosed information, and when the regulation leads to a larger increase in information comparability. Collectively, the results suggest that mandatory nonfinancial disclosure can affect firms' real decisions through market mechanisms and that stakeholder responses play a key role. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G14; G18; G38; J80; K22; K31; K38; L23; M41; M48. [ABSTRACT FROM AUTHOR]

Some of the deadliest wildfires in the U.S., such as California’s 2018 wildfires, have been ignited by power systems. In an effort to prevent and minimize the ignition of wildfires, or control them if ignited, energy companies have developed wildfire mitigation plans. This paper provides energy companies and power system operators, engineers, researchers, and suppliers an overview of the state-of-the-art studies that address key topics in these wildfire mitigation plans and compares the wildfire mitigation plans of several energy companies. The key topics include grid design and system hardening, asset management and inspection, situational awareness and forecasting, operational response, vegetation management, public safety power shutoff, and risk-spend efficiency. This paper also presents a comparison of several energy companies’ decision-making criteria for initiating a public safety power shutoff. Finally, we discuss opportunities for future research studies that could help energy companies prevent wildfire ignitions. [ABSTRACT FROM AUTHOR]

Aims: This paper examines trends and correlates of alcohol‐involved motor vehicle crashes (AMVCs) in California between 2005 and 2016 among Hispanic and non‐Hispanic Whites (Whites hereafter). Together these two groups comprise 76% of the state population. The paper also examines whether alcohol outlet density, percentage of Hispanics in census tract populations, and distance to the U.S./Mexico border are related to greater risks for AMVCs. The border is of interest given the greater availability of alcohol in the area. Methods: Crash data come from Statewide Integrated Traffic Records System maintained by the California Highway Patrol. Sociodemographic and community characteristics data from the U.S. Census and alcohol outlet density were aggregated to census tracts. Total motor vehicle crashes and AMVCs were related to these characteristics using hierarchical Bayesian Poisson space–time models. Results: There were over two million injury and fatality crashes during the period of analysis, of which 11% were AMVCs. About 1.7% of these crashes had fatalities. The rate of AMVCs increased among both Whites and Hispanics until 2008. After 2008, the rate among Whites declined through 2016 while the rate among Hispanics declined for 2 years (2009 and 2010) and increased thereafter. Crash distance from the border (RR = 1.016, 95% CI = 1.010 to 1.022) and percent Hispanic population (RR = 1.006; 95% CI = 1.003 to 1.009) were well‐supported results with 95% credible intervals that did not include 1. The percentages of the following: bars/pubs, males, individuals aged 18 to 29 and 40 to 49 years, U.S. born population, individuals below the 150% poverty level, unemployed, housing vacant, and housing owner‐occupied were all positively associated with AMVCs and well supported. Conclusions: Between 2005 and 2016 the rate of AMVCs in California declined among Whites but not among Hispanics. Population‐level indicators of percent Hispanic population, distance to the U.S. Mexico border, gender, age distribution, and socioeconomic stability were positively associated with crash rates, indicating that important contextual characteristics help determine the level of AMVC rates in communities. [ABSTRACT FROM AUTHOR]

The study presented in this paper analyzed four long-term pavement performance (LTPP) test sections located in the states of New York (NY) and California (CA). Two of them are flexible pavement sections, whereas the other two are composite pavement sections. Two levels of analysis—in-state analysis and cross-state analysis—were performed for these pavement sections to determine the impacts of traffic and climate conditions. The performance of the pavement sections was evaluated in respect of thermal cracking and rutting resistance. The in-state analysis focused on comparing the pavement sections located in the same state. The two pavement sections located in CA exhibited insignificant variation in thermal cracking, although one of them had an additional 1.5" (38 mm) dense-graded asphaltic concrete (AC) layer. On the other hand, the additional 1.5" (38 mm) AC layer resulted in a significant reduction in the rutting depth in one pavement section. The in-state analysis of the two pavement sections located in NY revealed that the 0.8" (20.4 mm) chip seal layer had significantly low resistance to thermal cracking and rutting. The cross-state analysis examined pavement sections of comparable structural capacities—two with low structural capacity, and two with high structural capacity. The performance comparison of the two pavement sections with low structural capacity revealed that the chip seal layer exhibited a significantly high rutting depth, i.e., low rutting resistance under high traffic loads in a freezing climate. On the contrary, the two pavement sections with high structural capacity showed relatively high rutting resistance in both warmer and freezing climates. Furthermore, this paper presents the pavement deterioration models for rutting and thermal cracking in the LTPP test sections. These models were developed using multiple linear regression considering the pavement service life (age), traffic load (average annual daily truck traffic, AADTT), and climate impact (freezing index, FI). The deterioration models had coefficients of determination (r2) in the range of 0.82–0.99 and standard errors varying from 0.01 to 9.92, which indicate that the models are reliable. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) systems have become increasingly common and the trend will continue. Examples of AI systems include autonomous vehicles (AV), computer vision, natural language processing and AI medical experts. To allow for safe and effective deployment of AI systems, the reliability of such systems needs to be assessed. Traditionally, reliability assessment is based on reliability test data and the subsequent statistical modelling and analysis. The availability of reliability data for AI systems, however, is limited because such data are typically sensitive and proprietary. The California Department of Motor Vehicles (DMV) oversees and regulates an AV testing program, in which many AV manufacturers are conducting AV road tests. Manufacturers participating in the program are required to report recurrent disengagement events to California DMV. This information is being made available to the public. In this paper, we use recurrent disengagement events as a representation of the reliability of the AI system in AV, and propose a statistical framework for modelling and analysing the recurrent events data from AV driving tests. We use traditional parametric models in software reliability and propose a new non‐parametric model based on monotonic splines to describe the event process and to estimate the cumulative baseline intensity function of the event process. We develop inference procedures for selecting the best models, quantifying uncertainty and testing heterogeneity in the event process. We then analyse the recurrent events data from four AV manufacturers, and make inferences on the reliability of the AI systems in AV. We also describe how the proposed analysis can be applied to assess the reliability of other AI systems. This paper has online supplementary materials. [ABSTRACT FROM AUTHOR]

Roads constructed over poor ground conditions that carry high traffic volumes and axle loads may, over time, experience persisting occurrences of pavement distress. Road construction, be it a new or a rehabilitation project, is both costly and time-consuming. An appealing option that improves pavement durability, reduces construction cost and time, accelerates strength development over a short curing period, and decreases pavement thickness is to chemically stabilize local road materials. In contrast to other aggregate materials, there has been a gap in evaluating and quantifying the feasibility of chemical stabilization of sandstone aggregate that possesses marginal quality as a road construction material. Therefore, the aim of this paper is to provide an experimental investigation of relative strength development of sandstone aggregate subbase of marginal quality stabilized with combinations of Portland composite cement (PCC), ordinary Portland cement (OPC), and styrene–butadiene latex copolymer (or polymer). The samples were prepared with different gravel-to-sand (G:S) ratios of 2.1, 1.2, and 0.4 and subsequently stabilized with a polymer-cement (P/C) blend. Samples were compacted and cured under dry and wet conditions before measuring their unconfined compressive strength (UCS), indirect tensile strength (ITS), and California bearing ratio (CBR). At the same curing condition and P/C contents, it was found that the UCS and CBR of P/C-stabilized samples increased with increasing G:S ratios. At the same polymer and cement contents, the P/C-stabilized samples with the highest G:S ratio of 2.1 also demonstrated a significantly higher rate of UCS strength development compared with the samples with lower G:S ratio and unstabilized samples. Soil stabilization with a combination of 0.75% polymer and 5% cement contents yielded the highest UCS that was approximately seven times the UCS of unstabilized samples and an ITS of 0.73 MPa. Stabilization with a combination of 0.75% polymer and 3% cement contents yielded the highest CBR value that significantly exceeded 30% after only 4 days of soaking and was seven times that of unstabilized samples. This paper has thus demonstrated the potential improvement to the strength development of sandstone aggregate subbase stabilized with P/C blend under the optimal curing condition and the importance of identifying and using the optimal proportion of polymer and cement to achieve the target strength development and improvement. [ABSTRACT FROM AUTHOR]

The deployment of hydrogen refueling stations is vital to the development of fuel cell vehicles. Past studies on the hydrogen refueling stations didn't consider congestion on paths and assumed all flows are on the shortest paths of OD pairs, which is not consistent with travelers' route choice behavior. In this paper, we study flow refueling location allocation based on the user-equilibrium (UE) status, which is consistent with travelers' route choice behavior. We present a flow-capturing location allocation (FCLA) model on UE conditions. We also presented an equilibrium algorithm avoiding cannibalization to solve the model. Based on the transportation network of Anaheim city in California in the US, we compared the results of applying a non-equilibrium method to the FCLA model and applying the equilibrium method to the FCLA model on UE conditions. The results of the two algorithms and models are different. The equilibrium model and algorithm can capture more flow and has a higher flow-capturing ratio. What's more, the equilibrium model and algorithm can fully capture the expected flow in practice since the real transportation network is basically in UE status. The equilibrium model and algorithm presented in this paper is the first study of this kind to locate stations in cities and is useful in the deployment of hydrogen refueling stations. • Study flow refueling location allocation based on the user-equilibrium (UE) status. • A flow capturing location allocation (FCLA) model on UE conditions. • An equilibrium algorithm avoiding cannibalization to solve the model. • Compare between non-equilibrium method and equilibrium method in flow capturing. [ABSTRACT FROM AUTHOR]

Background: Uptake of HIV pre-exposure prophylaxis (PrEP) remains low among transgender people as compared to other subgroups, despite high rates of HIV acquisition. In California, Latinx people comprise 40% of the population and Latina transgender women experience some of the highest burden of HIV of any subgroup, indicating a critical need for appropriate services. With funding from the California HIV/AIDS Research Programs, this academic-community partnership developed, implemented, and evaluated a PrEP project that co-located HIV services with gender affirming care in a Federally Qualified Heath Center (FQHC). Trans and Latinx staff led intervention adaptation and activities. Methods: This paper engages qualitative methods to describe how a PrEP demonstration project- Triunfo- successfully engaged Spanish-speaking transgender Latinas in services. We conducted 13 in-depth interviews with project participants and five interviews with providers and clinic staff. Interviews were conducted in Spanish or English. We conducted six months of ethnographic observation of intervention activities and recorded field notes. We conducted thematic analysis. Results: Beneficial elements of the intervention centered around three intertwined themes: creating trusted space, providing comprehensive patient navigation, and offering social support "entre nosotras" ("between us women/girls"). The combination of these factors contributed to the intervention's success supporting participants to initiate and persist on PrEP, many of whom had previously never received healthcare. Participants shared past experiences with transphobia and concerns around discrimination in a healthcare setting. Developing trust proved foundational to making participants feel welcome and "en casa/ at home" in the healthcare setting, which began from the moment participants entered the clinic and continued throughout their interactions with staff and providers. A gender affirming, bilingual clinician and peer health educators (PHE) played a critical part in intervention development, participant recruitment, and patient navigation. Conclusions: Our research adds nuance to the existing literature on peer support services and navigation by profiling the multifaced roles that PHE served for participants. PHE proved instrumental to empowering participants to overcome structural and other barriers to healthcare, successfully engaging a group who previously avoided healthcare in clinical settings. [ABSTRACT FROM AUTHOR]

The objective of this study was to measure particulate matter (PM) total loss rates in three older (1940s, 1960s, and 1980s) elevators in California during two phases and three low-cost intervention modes. Tracer gas decay and <2 μm aerodynamic diameter nontoxic NaCl particles (PM2) were used to calculate PM2 loss rates. The NaCl particles were considered surrogates for smaller particles carrying SARS-CoV-2. Empirical PM2 loss rates were paired with modeled dynamic scenarios to estimate SARS-CoV-2-relevant PM2 removal. Mean loss rates (hr-1) ranged from 1.8 to 184. Compared to a closed-door, stationary elevator, the moving elevators had a fourfold increased mean loss rate (hr-1), while an air cleaner in a stationary elevator increased the mean loss rates sixfold. In a dynamic particle removal simulation of a ten-story elevator, PM was removed 1.38-fold faster with an air cleaner intervention during bottom and top floor stops only (express ride) and 1.12-fold faster with an air cleaner during every other floor stops. The increase in removal rates due to the air cleaner was modest due to the higher moving and open-door removal rates, except during stationary phase. The half-life of PM2 particles in a stationary elevator after all passengers have left can be 8-12 minutes following a single emission and 2-5 minutes with an air cleaner. The low particle removal rate in the stationary elevator requires an intervention so that the particle removal rate will be high to eliminate infectious aerosol. If codes permit, keeping the door open when the elevator is stationary is most effective; otherwise, an air cleaner in a stationary elevator should be used. While an air cleaner is commonly seen as a substantial improvement in reducing potential virus concentration in air, in the moving elevator scenarios, the effect is quite modest. This paper provides empirical particle loss rates inside elevators, the effectiveness of air cleaners in a dynamic elevator space, two approaches to control infectious agents while the elevator is stationary, and support for a precautionary approach towards elevator use amidst a pandemic. [ABSTRACT FROM AUTHOR]

The Free Application for Federal Student Aid (FAFSA) is the primary gatekeeper to secure financial aid for college. The federal government instituted two changes to the process in 2017, commonly known as "prior-prior year" FAFSA: (1) an earlier start date that lengthens the filing period and (2) the ability to use completed taxes from the prior calendar year. This paper uses descriptive statistics to examine resulting changes in application filing behavior in California. Students submitted their FAFSA substantially earlier and refiling rates increased among independent students in the policy year. Although these changes may have reduced the burden of applying, the earlier submissions did not appear to substantially alter state aid receipt or postsecondary attendance. [ABSTRACT FROM AUTHOR]

This work to articulate a geography of hope in the face of institutionalized epistemic injustice extends the emerging Indigenous political ecology approach through engagement with cultural resources law and policy. While Indigenous political ecology offers a framework to understand the context in which geographies of hope are created, geographies of hope are specific spatial processes that exemplify resilience, vision, and ingenuity in adverse circumstances. This paper focuses on such hopeful, place-based work to bring US and, specifically, California, cultural resources and repatriation law and policy into alignment with contemporary international Indigenous human rights standards. The Native and non-Native allies advocating for legal and political change are both focused on protecting particular places and their entwined epistemologies, and on altering processes of decision-making that privilege non-Indigenous epistemologies. Hope is specifically fostered in efforts to educate non-Native citizens on the continuities between past and present, in highlighting the efforts of Indigenous people working to care for and protect their heritage on/in/with the land, and in fostering legal frameworks that center justice. [ABSTRACT FROM AUTHOR]

Despite being some of the harshest environments to design for and inhabit, deserts are considered some of the most malleable in our imagination. Countless military bases, proving grounds, gunneries, and practice fields that simulate other locales prove that in military imagination, deserts are nondescript proxy spaces waiting to be filled with the character of whatever location they are to imitate. The developers' imagination is not far behind. Through a historical case study of California City, an ambitiously planned but only partially built desert development project, and unpacking of the terms "desert" and "wasteland," this essay examines the colonial gaze towards the desert that often shapes our perceptions of this unique environment and exposes the fallacies in our thinking that lead us to imagine deserts as a blank slate waiting to be transformed. The paper also highlights the dangers of overconfidence in technology to create techno-utopias and the need to acknowledge the reality of the desert's harsh environment in any planning or development. [ABSTRACT FROM AUTHOR]