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This paper explores how the Taiwanese-Chinese religious movement Yiguandao ("Way of Pervading Unity") creates a community of non-Chinese followers by utilizing Daoism-related beliefs and practices. Drawing on ethnographic data from fieldwork conducted in California in early 2018, published Yiguandao materials, and internet resources, the paper argues that Yiguandao activists specifically invest their messages in Daoist symbols, beliefs, and practices to reach out to non-Chinese sympathizers of "Asian philosophies" and eventually to establish a global and cross-cultural community of Dao followers. By discussing a case study from Los Angeles, the paper seeks to understand the patterns of Yiguandao activists' engagement with Daoism and how their efforts blend into establishing a global Daoist field. Finally, it thereby invites us to rethink the often haphazardly drawn boundaries—both by practitioners and scholars—between Daoism and other religious phenomena, including New Age, spirituality, and Chinese popular sects. [ABSTRACT FROM AUTHOR]

Purpose This paper compares and contrasts the implementation of pharmacist-led services for 3 different sexual and gender minority populations across California, Mississippi, and Florida. Summary Implementation of pharmacist-led services tailored to sexual and gender minorities may be a potential mechanism to address health disparities in these populations. Clinical pharmacists have the potential to provide care with cultural humility and improve health outcomes by optimizing medication regimens, reducing adverse drug events, enhancing medication acquisition, and improving medication adherence. Conclusion The services provided by clinical pharmacists varied across sites and included management of gender-affirming hormone therapy, HIV antiretroviral medication adherence programming, primary care and chronic disease state management, and involvement in care related to mental health, psychiatry, and substance use as well as sexual health. Various legislative and regulatory barriers and differences in scope of practice for pharmacists were also identified. This paper advocates for the expansion of pharmacy-led services and the adoption of a culturally humble approach to patient care. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Patients are being encouraged to complete forms electronically using patient portals rather than on paper, but willingness of older adults to make this transition is uncertain. METHODS: The authors analyzed data for 4105 Kaiser Permanente Northern California 2020 Member Health Survey respondents aged 65-85 years who answered a question about willingness to complete online forms and questionnaires using a patient portal. Data weighted to the Kaiser Permanente Northern California membership were used to estimate percentages of older adults willing to complete patient portal forms and questionnaires. Chi-square tests and log-Poisson regression models that included sociodemographic, internet use, and patient portal variables were used to identify factors predictive of willingness. RESULTS: Overall, 59.6% of older adults were willing to complete patient portal forms, 17.6% were not willing, and 22.8% were not sure. Adults aged 75-85 (49.5%) vs 65-74 years (64.8%) and Black (51.9%) and Latino (46.5%) vs White (62.8%) adults were less likely to indicate willingness. In addition to racial and ethnic differences and younger age, higher educational attainment, use of the internet alone (vs internet use with help or not at all), having an internet-enabled computer or tablet, and having sent at least 1 message through the patient portal increased likelihood of being willing. CONCLUSIONS: Health care teams should assess older adults' capabilities and comfort related to completion of patient portal-based forms and support those willing to make the digital transition. Paper forms and oral collection of information should remain available for those unable or unwilling to make this digital transition. [ABSTRACT FROM AUTHOR]

Purpose: In an effort to address persistent inequities in maternal and infant health, policymakers and advocates have pushed to expand access to doula care. Several states, including California, now cover doula services through Medicaid. As coverage expands, research on the impact of doula care will likely increase. To develop best practices for research, it is critical to engage community doulas, clients, and other key stakeholders. Description: Our overarching goal was to build capacity for future doula- and client-centered research on community doula care. First, we established a Steering Committee with members from seven relevant stakeholder groups: community doulas, former or potential doula clients, clinicians, payers, advocates, researchers, and public health professionals. Second, we conducted a needs assessment to identify and understand stakeholders' needs and values for research on community doula care. Findings from the needs assessment informed our third step, conducting a research prioritization to develop a shared research agenda related to community doula care with the Steering Committee. We adapted the Research Prioritization by Affected Communities protocol to guide this process, which resulted in a final list of 21 priority research questions. Lastly, we offered a training to increase capacity among community doulas to engage in research on community doula care. Assessment: Our findings provide direction for those interested in conducting research on doula care, as well as policymakers and funders. Conclusion: The findings of our stakeholder-engaged process provide a roadmap that will lead to equity-oriented research centering clients, doulas, and their communities. Significance: What is Already Known on this Subject?: Doula care is often cited as a cost-effective intervention to improve maternal and infant health and health care experiences. However, research that focuses on the community-based model of doula care is limited. What this Study Adds?: This paper describes a stakeholder-engaged process that identified important understudied research questions about community doula care. Researchers can further refine these questions to conduct partnered research with multiple stakeholder groups, including community doulas, former or potential doula clients, clinicians, payers, advocates, and public health professionals. Further, this paper outlines best practices for research on community doula care. [ABSTRACT FROM AUTHOR]

This paper analyzes the perspectives of college students toward food insecurity and basic needs campus resources. We draw from interviews with 49 students at one university in California's Inland Empire conducted in 2019. We found that regardless of personal experience with food insecurity, participants were generally reluctant to access resources or disclose their experiences with the campus community. We propose that this food insecurity stigma operates individually, interactionally, and structurally. We also discuss it as a by-product of neoliberal discourses about students "abusing" the system and needing to pull themselves up by the bootstraps. A response from university stakeholders has been to normalize food insecurity and visibilize resource use. While an important strategy to counteract the impact of food insecurity, we argue that normalization has limits in regard to addressing the root causes of food insecurity. Finally, we also illustrate ways that students themselves resist food insecurity stigma. [ABSTRACT FROM AUTHOR]

For evaluating the resistance performance of cement-stabilized soils in cold regions, the variation of the strength of the cemented sand–gravel (CSG) mixture concerning the hydration process should be explored. This paper aims to study the effect of freeze–thaw (F–T) cycles on the strength and microstructure of a CSG mixture with 10% cement that is subjected to 12 cycles of freezing at a temperature of −23°C for 24 h and then melted at room temperature of 24°C for the next 24 h. The uniaxial compressive strength (UCS), California bearing ratio (CBR), and weight volume loss of the samples were measured after individual F–T cycles. Furthermore, the change in the microstructure of the CSG mixture in various F–T cycles was explored. The results showed a considerable reduction in the UCS up to Cycle 3, then a slight increase for Cycles 3–6, and finally a gradual decrease for further cycles. However, the CBR and weight loss slightly fluctuated up to Cycle 6, and then gradually decreased for subsequent cycles. The majority of compounds of hydrated cement were damaged in the first three cycles. In the following cycles, between Cycles 3 and 6, the portlandite compound was dissolved and recrystallized within the microvoids. Depending on the environmental conditions, carbonation may be generated from the hydrated cement fraction, which fills the microvoids and improves the strength and structure of the mixture. During further cycles after the sixth cycle, the mechanical action of the ice lenses coupled with the disintegration of the hydrate compounds imposed many new microvoids and cracks with considerable length and width, which intensified the strength reduction of the moisture and weakened the adhesion between grains. Since cement is widely used in pavement and dam engineering for stabilizing soils, the durability of cemented soils is of prime concern. This study may help improve the durability and resistance of cemented soils in cold climates. The F–T action not only influences the macrostructure of cement-stabilized soils by imposing a wide crack and ice lens but also induces a considerable change in the complexes existing in the hydrated cement paste of the mixture. Three patterns govern the change of the mixture microstructure in various F–T cycles that correspond to the observed trend in strength. The mentioned trend for the microstructure change and, consequently, the strength variation of the CSG mixture are associated with many factors such as pH, cement content, CO2 content, moisture content within the mixture, and relative humidity within the environment. Accordingly, the pattern of microstructural changes in the CSG mixture after the middle F–T cycles may vary depending on environmental conditions. [ABSTRACT FROM AUTHOR]

Strandings have been extensively documented for large mammals, however, a comprehensive survey focusing on batoids is currently lacking. To address this knowledge gap, we conducted a review of available stranding data sourced from iNaturalist, news websites, and published papers. A total of 3.148 reports encompassing 189 batoid species were recovered, revealing the vulnerability of both oceanic and coastal species to strandings. Nevertheless, limited data on life stage, sex, animal condition, and fate hinder a comprehensive understanding of this phenomenon. Putative causes were identified only for a small percentage (6%) of the reports, namely pollution, abrupt environmental alterations, predation, pathologies, and fishing activities. The earliest reported stranding dates back to 1989, with an increase in reports observed since 2019. iNaturalist accounted for the majority (75%) of records, emphasizing its significance as a platform for reporting and monitoring batoid strandings. These strandings were reported in 51 countries, with the coastal areas of California, United States, particularly notable. Among the identified species, Rhinoptera bonasus exhibited the highest number of strandings, with 392 recorded individuals. Alarmingly, more than half of the reports involved threatened species, underscoring the need for increased attention to batoid strandings. To address these issues, we propose the establishment of stranding monitoring networks and the development of a freely accessible global database. In addition, the training of volunteer citizen scientists, the development of rescue and rehabilitation protocols, and manuals of good fishing practices aimed at commercial and recreational fisheries are also recommended. [ABSTRACT FROM AUTHOR]

A large literature documents that there are significant academic and non-academic differences between the youngest and oldest students in a school cohort. This paper investigates if being the youngest in a cohort has any impact on an individual's propensity to commit crime by utilizing a data set that contains over 4 million arrest records spanning a 20-year period in California. While I find no persistent effect on the probability of arrest, the youngest students in a cohort have a higher risk of arrest for certain offenses at age 14, corresponding to the age when they would transition to high school. [ABSTRACT FROM AUTHOR]

Aim: As climate change increases the frequency and severity of droughts in many regions, conservation during drought is becoming a major challenge for ecologists. Droughts are multidimensional climate events whose impacts may be moderated by changes in temperature, water availability or food availability, or some combination of these. Simultaneously, other stressors such as extensive anthropogenic landscape modification may synergize with drought. Useful observational models for guiding conservation decision‐making during drought require multidimensional, dynamic representations to disentangle possible drought impacts, and consequently, they will require large, highly resolved data sets. In this paper, we develop a two‐stage predictive framework for assessing how drought impacts vary with species, habitats and climate pathways. Location: Central Valley, California, USA. Methods: We used a two‐stage counterfactual analysis combining predictive linear mixed models and N‐mixture models to characterize the multidimensional impacts of drought on 66 bird species. We analysed counts from the eBird participatory science data set between 2010 and 2019 and produced species‐ and habitat‐specific estimates of the impact of drought on relative abundance. Results: We found that while fewer than a quarter (16/66) of species experienced abundance declines during drought, nearly half of all species (27/66) changed their habitat associations during drought. Among species that shifted their habitat associations, the use of natural habitats declined during drought while use of developed habitat and perennial agricultural habitat increased. Main Conclusions: Our findings suggest that birds take advantage of agricultural and developed land with artificial irrigation and heat‐buffering microhabitat structure, such as in orchards or parks, to buffer drought impacts. A working lands approach that promotes biodiversity and mitigates stressors across a human‐induced water gradient will be critical for conserving birds during drought. [ABSTRACT FROM AUTHOR]

Soil bulk density (BD) is important for measuring changes in soil chemical, physical, and biological properties; however, the measurement is tedious to collect and requires specialized equipment. Database measurements for soil surface BD do not always correspond to present field conditions as field management can alter BD in time. Saturation percentage (SP) is a routine lab measurement. The objectives of this study are to (1) understand if a relationship between BD and SP can be developed and (2) build a model that predicts BD based on a routine low‐cost lab analysis. We collected 83 soil samples from different experimental sites around California's Central Valley. At each site, BD, SP, soil organic matter (OM), and soil total organic carbon were measured. A set of models were generated and compared based on their Akaike information criterion (AIC) and adjusted R2. The best two models are presented in this paper, and their accuracy and precision in estimating BD were further compared by calculating the root mean square error (RMSE) and the R2 of the predicted versus values measured in the field. We determined that a strong relationship between BD and SP exists (R2 = 0.70) and that a cubic model that includes SP and OM resulted in the best model to predict BD in California soils. Inclusion of additional data may further strengthen this model or make it applicable for other grower regions. Core Ideas: Database bulk density values may not correspond to field conditions as management can alter bulk density.Bulk density is hard to measure and requires specialized equipment, but is needed to quantify soil carbon changes.There is a significant correlation between soil bulk density, soil saturation paste, and soil organic matter.Three models to predict bulk density based on saturation paste and organic matter were developed and evaluated. [ABSTRACT FROM AUTHOR]

Policy responses to the challenges associated with environmental change, including more frequent and severe climatic events, have interlinked environmental and social impacts. Less attention has been afforded to the latter, and specifically to the question of not just whether but how such responses create or entrench inequality. This paper examines policy responses to drought events in California, United States, and the Western Cape Province, South Africa, in terms of their effects on inequality, revealed in relationships to water access networks. We use concepts of water justice and hydraulic citizenship to evaluate how and why these policy responses reproduced water injustices in the two settings. We focus particularly on two mechanisms linking responses to widened inequalities: values‐reinforcement and strategic communication. Using interviews, policy documents, and media reports, we employ process tracing methods to illustrate these mechanisms through which drought policy impacts hydraulic citizenship experiences, manifesting water injustice. We contribute to emerging examinations of environmental policy responses and maladaptation by demonstrating how concepts of hydraulic citizenship and an emphasis on mechanisms can help us better understand and identify experiences of water injustice. We note policy implications and areas for future research, highlighting droughts as consequential policy sites for advancing social and environmental justice. [ABSTRACT FROM AUTHOR]

Background: This paper describes the protocols for a randomized controlled trial using a parallel-group trial design that includes an intervention designed to address social isolation and loneliness among people experiencing homelessness known as Miracle Friends and an intervention that combines Miracles Friends with an economic poverty-reduction intervention known as Miracle Money. Miracle Friends pairs an unhoused person with a volunteer "phone buddy." Miracle Money provides guaranteed basic income of $750 per month for 1 year to Miracle Friends participants. The study will examine whether either intervention reduces social isolation or homelessness compared to a waitlist control group. Methods: Unhoused individuals who expressed interest in the Miracle Friends program were randomized to either receive the intervention or be placed on a waitlist for Miracle Friends. Among those randomized to receive the Miracle Friends intervention, randomization also determined whether they would be offered Miracle Money. The possibility of receiving basic income was only disclosed to study participants if they were randomly selected and participated in the Miracle Friends program. All study participants, regardless of assignment, were surveyed every 3 months for 15 months. Results: Of 760 unhoused individuals enrolled in the study, 256 were randomized to receive Miracle Friends, 267 were randomized to receive Miracle Money, and 237 were randomized to the waitlist control group. In the two intervention groups, 360 of 523 unhoused individuals were initially matched to a phone buddy. Of the 191 study participants in the Miracle Money group who had been initially matched to a volunteer phone buddy, 103 were deemed to be participating in the program and began receiving monthly income. Discussion: This randomized controlled trial will determine whether innovative interventions involving volunteer phone support and basic income reduce social isolation and improve housing outcomes for people experiencing homelessness. Although we enrolled unhoused individuals who initially expressed interest in the Miracle Friends program, the study team could not reach approximately 30% of individuals referred to the study. This may reflect the general lack of stability in the lives of people who are unhoused or limitations in the appeal of such a program to some portion of the unhoused population. Trial registration: ClinicalTrials.gov NCT05408884 (first submitted on May 26, 2022). [ABSTRACT FROM AUTHOR]

Morro manzanita Arctostaphyos morroensis (Ericaceae) is a long-lived, shrub endemic to San Luis Obispo County, southern California, USA. It was listed as threatened under the U.S. Endangered Species Act in 1994, with identified threats being residential and urban development, including lack of protection on private land and lack of management on public lands, competition with invasive non-native plants, and risks of extinction associated with small and isolated populations. Our goal in this paper is to summarize and supplement the current knowledge of Morro manzanita. We review the literature on the species' description, reproductive ecology, germination cues, short-term response to fire. and distribution. We conducted field surveys to report on long-term response to fire, resampling the previously studied prescribed burn site 25 yr post-fire. Finally, we summarize the current land management of sites that support Morro manzanita and threats faced by this species. We conclude with specific recommendations for management and future study towards supporting conservation of this species and its maritime chaparral community. [ABSTRACT FROM AUTHOR]

This paper presents the findings of a large‐scale experimental study that focus on assessing structural behavior of reinforced concrete (RC) cantilever slabs with carbon/epoxy fiber‐reinforced polymer (CFRP) composite strips using a near‐surface‐mounted (NSM) approach. The NSM/CFRP system evaluated in this study was implemented in strengthening the shoulders of the Slide Canyon Bridge in California, USA. The experimental phase is divided into two main parts: (i) determining the design parameters for NSM, including the bondline strength through pull‐out tests, and (ii) conducting a practical evaluation of the bending behavior of original and retrofitted RC cantilever slabs, each with varying NSM reinforcement and three different development lengths. Results of this study indicated that the use of NSM‐CFRP has a considerable benefit in that it significantly improves ductility and changes the failure mode of the unstrengthened RC slab from the typical brittle shear‐based failure mode to a more ductile flexural‐based failure mode. The large‐scale slab specimens' performances, which had different development lengths, showed little variance, except for the slab specimen with a development length of 457.0 mm that exhibited an appreciable flexural stiffness as compared to other specimens evaluated in this study. In order to simulate the serviceability and ultimate behavior of the RC slab specimens, linear and nonlinear finite element analyses were performed. A satisfactory agreement between numerical and experimental results was achieved especially at load level prior the initiation of large‐size cracks. [ABSTRACT FROM AUTHOR]

The increase in both the frequency and magnitude of natural disasters, coupled with recent advancements in artificial intelligence, has introduced prospects for investigating the potential of new technologies to facilitate disaster response processes. Preliminary Damage Assessment (PDA), a labor-intensive procedure necessitating manual examination of residential structures to ascertain post-disaster damage severity, stands to significantly benefit from the integration of computer vision-based classification algorithms, promising efficiency gains and heightened accuracy. Our paper proposes a Vision Transformer (ViT)-based model for classifying damage severity, achieving an accuracy rate of 95%. Notably, our model, trained on a repository of over 18,000 ground-level images of homes with damage severity annotated by damage assessment professionals during the 2020–2022 California wildfires, represents a novel application of ViT technology within this domain. Furthermore, we have open sourced this dataset—the first of its kind and scale—to be used by the research community. Additionally, we have developed a publicly accessible web application prototype built on this classification algorithm, which we have demonstrated to disaster management practitioners and received feedback on. Hence, our contribution to the literature encompasses the provision of a novel imagery dataset, an applied framework from field professionals, and a damage severity classification model with high accuracy. [ABSTRACT FROM AUTHOR]

For persons serving life-without-parole (LWOP) sentences in California, a commutation usually offers them the sole glimpse of hope for release from prison. While governors were reluctant to consider any sentence reductions from 1975 to 2016, commutations—including those for LWOP—have become a more frequent occurrence since. Yet, little is still known about how governors have justified reducing a sentence that initially offered no prospect of release from prison. Given the apparent change in practice, themes emerging from the content of 177 gubernatorial commutation summaries granted to persons serving LWOP sentences between 2017 and 2021 are analyzed in this paper. Through open coding, rehabilitative indicators (programming and institutional conduct) emerged as necessary preconditions for a commutation, while retributive factors (a reassessment of the nature of the crime and the prerogative to adjust excessive prison sentences or to correct sentencing errors) complemented sentence reductions. The findings expose the ethical issues that arise from an LWOP sentence and the subsequent commutation. More specifically, they shed light on the commitment offenses underlying commuted LWOP sentences and raise questions regarding the penal objectives that are supposed to be accomplished with permanent imprisonment. [ABSTRACT FROM AUTHOR]

I employ an elasticity‐based method to invert a geodetically derived surface velocity field in the western US using for present‐day surface strain rate fields with uncertainties. The method uses distributed body forces in a thin elastic sheet and allows for discontinuities in velocity across creeping faults using the solution for dislocations in a thin elastic plate. I compare the strain rate fields with previously published stress orientations and moment rates from geological slip rate data and previous geodetic studies. Geologic and geodetic moment rates are calculated using slip rate and off‐fault strain rates from the 2023 US National Seismic Hazard Model (NSHM) deformation models. I find that computed total geodetic moment rates are higher than NSHM summed moment rates on faults for all regions of the western US except the highest deforming rate regions including the Western Transverse Ranges and the northern and southern San Andreas Fault (SAF) system in California. Computed geodetic moment rates are comparable to the moment rates derived from the geodetically based NSHM deformation models in all regions. I find systematic differences in orientations of maximum horizontal shortening rate and maximum horizontal compressive stress in the Pacific Northwest region and along much of the SAF system. In the Pacific Northwest, the maximum horizontal stress orientations are rotated counterclockwise 40–90° relative to the maximum horizontal strain rate directions. Along the SAF system, the maximum horizontal stresses are rotated systematically 25–40° clockwise (closer to fault normal) relative to the strain rates. Plain Language Summary: Geodetic measurements of surface velocities can be converted to strain rate which is a measure of the distortion rate of the crust. Strain rate is an important quantity for earthquake studies because it can be related to the rate of elastic stored energy (called moment) available for future earthquakes. In this paper I employ a new method to invert the surface velocity field in the western US for present‐day surface strain rates. I convert the strain rates to crustal moment rates and compare this with moment release rates computed from previous estimates of fault slip rates from geology as well as with model moment rates from the 2023 US National Seismic Hazard Model (NSHM). I find that computed total geodetic moment rates are higher than NSHM model moment rates on faults for many regions of the western US. I also find systematic differences in present‐day strain rates and total stress in the crust indicating that the total stress in the crust is not simply the accrual of present‐day deformation. Key Points: I implement an elasticity‐based inversion of geodetic data for strain rateSystemic differences in orientation of stress and strain rate in Cascadia, San Andreas Fault, and eastern Basin‐RangeThe total geodetic moment rates are higher than geologic moment rates within most regions of the western US [ABSTRACT FROM AUTHOR]

In California, wildfires caused by electrical infrastructure have left the state's investor-owned power utilities with major and growing liabilities. But even in such an incendiary environment, the financial industry has demonstrated that it can profit from disaster. This paper uses the 2019-2020 bankruptcy of Pacific Gas & Electric to explain how. In it, I show how "risk" in California's electricity industry is legally constituted, mediated, and allocated. First, I explain how financial perceptions of wildfire risk in California's electricity industry are shaped by the state's legal and regulatory environment, and how the law is used to manage this risk. I then turn to PG&E's bankruptcy to show how litigation functions as a financial strategy. In court, risk is endogenous to legal-financial practice. I develop the concepts of "legal arbitrage" and "leverage" to explain how law mediates the relationship between risk and finance. I adapt the concept of legal arbitrage to show how financial assets (like those in a utility with unprecedented wildfire liabilities) can possess both legal and market value, which can and often do diverge in circumstances of distress. I use the term leverage to refer to a particular kind of legal-financial power which enables actors to transfer risk away from themselves and onto others. In working through these concepts, I argue that that mainstream perceptions of risk in the financial industry are inadequate, especially in an era of increasing climate insecurity. [ABSTRACT FROM AUTHOR]

An acute difficulty in wine-ratings-related research, and in calculating consensus among judges, is that each rating is one observation drawn from a latent probability distribution that is wine- and judge-specific. One observation is almost no data at all. Minimizing a weighted sum of cross entropies has been proposed as a method of estimating the shape of the latent distribution using one observation. That method was tested on 30 blind triplicate wine ratings. This article replicates that test, presents results of tests at hypothetical boundary conditions, and then presents test results for a set of 30 blind triplicate ratings published by Cicchetti [(2014, August). Blind tasting of South African wines: A tale of two methodologies (AAWE Working Paper No. 164, 15 pages)] and a set of 1599 blind triplicate ratings from the California State Fair. The test results show that the minimum cross entropy solution is substantially more accurate than the analysis of a single rating. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study of using xanthan gum (XG), sodium alginate (SA) and gelatin (G) to stabilise collapsible soil. Modified Proctor, one-dimensional collapse, unconsolidated-undrained triaxial and California bearing ratio (CBR) tests were conducted to estimate the engineering characteristics of the untreated and treated soil. Additionally, x-ray diffraction (XRD) and scanning electron microscopy (SEM) tests were utilised to demonstrate the changes in the microstructure of the treated samples. It was found that biopolymers decreased the maximum dry density and increased the optimum water content. The results also indicated that a 4% content of XG, SA and G significantly reduced the collapse index by 96, 95 and 82%, respectively. Shear tests showed that biopolymers slightly reduced the internal friction angle and significantly increased the cohesion intercept, which led to shear strength improvement. The results also indicated that 4% XG-treated, 4% SA-treated and 4% G-treated samples exhibited higher shear strengths by 145, 106 and 73%, respectively, than the untreated samples under the same conditions. The findings also indicated that when the soil was mixed with a 4% concentration of XG, SA and G, the unsoaked CBR value increased by about 185, 157 and 141%, respectively. [ABSTRACT FROM AUTHOR]

Rationale: COVID‐19 has fundamentally changed the practice of Emergency Medicine (EM). Care delivery on the front lines has historically depended upon ostensibly reliable input‐output models for staffing, supplies, policies, and therapies. Challenged by the complexity of healthcare during the pandemic, the fallibility of these reductionist models was quickly revealed. Providers and systems quickly had to reconceptualize their dependence on the wider, complex system in which healthcare operates and find adaptive solutions to rapid changes. Aims/Method: This papers seeks to review and describe how Systems Thinking and Complexity Theory (ST/CT)—concepts, principles, and tools that can be used to understand and impact our constantly evolving health system—can be applied to better understand and enact change in complex settings such as during COVID‐19. Some of these ST/CT are described through the real world example of the Alameda Health System Vaccine Taskforce. Results: ST/CT concepts such as Unintended Consequences, Interrelationships, Emergent Behavior, Feedback Loops, and Path Dependence can help EM providers and planners understand the context in which their system operates. Key principles such as Collaboration, Iterative Learning, and Transformational Leadership can help these actors respond to current and future challenges. The integration of these concepts and principles into the Learning Health System offers a model for tying these key concepts and principles together into an adaptive, cross‐sectoral organizational approach. Conclusion: By integrating ST/CT into the practice of EM, we can not only improve our ability to care for patients but also our capacity to understand and strengthen our wider systems of care. [ABSTRACT FROM AUTHOR]

Background: Barriers exist for the provision of surgery for permanent contraception in the postpartum period. Prenatal counseling has been associated with increased rates of fulfillment of desired postpartum contraception in general, although it is unclear if there is impact on permanent contraception specifically. Thus, we aimed to investigate the association between initial timing for prenatal documentation of a contraceptive plan for permanent contraception and fulfillment of postpartum contraception for those receiving counseling. Methods: This is a planned secondary analysis of a multi-site cohort study of patients with documented desire for permanent contraception at the time of delivery at four hospitals located in Alabama, California, Illinois, and Ohio over a two-year study period. Our primary exposure was initial timing of documented plan for contraception (first, second, or third trimester, or during delivery hospitalization). We used univariate and multivariable logistic regression to analyze fulfillment of permanent contraception before hospital discharge, within 42 days of delivery, and within 365 days of delivery between patients with a documented plan for permanent contraception in the first or second trimester compared to the third trimester. Covariates included insurance status, age, parity, gestational age, mode of delivery, adequacy of prenatal care, race, ethnicity, marital status, and body mass index. Results: Of the 3103 patients with a documented expressed desire for permanent contraception at the time of delivery, 2083 (69.1%) had a documented plan for postpartum permanent contraception prenatally. After adjusting for covariates, patients with initial documented plan for permanent contraception in the first or second trimester had a higher odds of fulfillment by discharge (aOR 1.57, 95% C.I 1.24–2.00), 42 days (aOR 1.51, 95% C.I 1.20–1.91), and 365 days (aOR 1.40, 95% C.I 1.11–1.75), compared to patients who had their first documented plan in the third trimester. Conclusions: Patients who had a documented prenatal plan for permanent contraception in trimester one and two experienced higher likelihood of permanent contraception fulfillment compared to those with documentation in trimester three. Given the barriers to accessing permanent contraception, it is imperative that comprehensive, patient-centered counseling and documentation regarding future reproductive goals begin early prenatally. Plain language summary: Permanent contraception is a highly desired form of postpartum contraception in the United States, however there are several barriers to accessing it. In this paper, we investigate whether the timing of when a patient has a documented plan for postpartum contraception has an impact on if they achieve postpartum contraception. This is a cohort study from four hospitals in Illinois, Ohio, California, and Alabama for patients with a desire for postpartum permanent contraception documented in their medical record. We specifically investigated the trimester (first, second, or third) where a patient had a plan for permanent contraception first documented. We then used univariate and multivariate models to determine the relationship between the timing of a plan for permanent contraception and if a patient achieved the procedure at three time-points: hospital discharge, 42-days, and 365-days. Our findings showed that of the 3103 patients in our cohort, only 69.1% of them had a documented plan for postpartum contraception at any point before going to the hospital for their delivery admission. We additionally found that patients who had a documented plan for permanent contraception in the first or second trimester had a higher odds of receiving their postpartum contraception procedure compared to people who had their first documented plan in the third trimester. This showed us the importance of earlier counseling regarding contraception for pregnant patients. There are many barriers to accessing postpartum contraception, so having patient focused counseling about future goals around reproductive health early on in pregnancy is critical. [ABSTRACT FROM AUTHOR]

This paper analyzes the stabilizing effect of stone dust, granite dust, marble dust, and calcium lignosulphonate on construction materials and natural soils during road construction. The ultimate aim was to enhance the soil's engineering properties such that the pavement constructed could correctly withstand the load applied. To achieve this, every stabilizer was amalgamated with the soil at various percentages between 5 and 50%. Measurements were made of Atterberg limit tests, moisture content, and specific gravity. The research demonstrated that a diminution in optimal moisture content was seen, with an elevation in maximum dry density and California bearing ratio (CBR). Enhancements in the unconfined compressive strength were also identified. The outcomes determined that the untreated soil's CBR was 2.27% and in the case of soil with 45% additives, the CBR attained was 5.05%. When the soil was mixed with 50% additives, performance of 30.21%, 17.42%, and 12.82% was exhibited for (a) liquid limit, (b) plastic limit, and (c) plasticity index. Moreover, via the addition of presented stabilizers, the soil's mechanical properties were elevated appreciably. [ABSTRACT FROM AUTHOR]

Stream-terrace morphostratigraphy and optically stimulated luminescence (OSL) geochronology indicate that storm-driven sedimentation has caused down-system decoupling of the uppermost reaches of McMillan Creek (southern California, USA) from the lower reaches of McMillan Creek since 1960 ± 190 yr B.P. This is significant because source-to-sink studies report high degrees of sediment transport connectivity over millennial time scales during periods of high fluvial discharge in sediment routing systems. The most recent relatively large-magnitude episode of sedimentation emplaced a sediment slug in the ephemeral channel of McMillan Creek. The sediment slug is correlated to the "California Storm of January 1862" via OSL dating. In this paper, a conceptual model of sediment slug dynamics in an ephemeral stream over 16 decades is developed based on fluvial sedimentation events that in most instances included reworking slug-derived sediment. Due to the episodic nature of streamflow in ephemeral streams and the dearth of sediment transport between streamflow events, sediment slug coherency is sustained over longer periods of time in ephemeral streams than in perennial streams having steady or variable flow regimes. The longevity of sediment-slug coherency in ephemeral streams leads to more prolonged down-system decoupling in sediment routing systems than down-system decoupling caused by ordinary fluvial sedimentation. In McMillan Creek, it is possible that up-system decoupling driven by sedimentation has been contemporaneous with down-system decoupling, but factors other than sedimentation may have a more significant role in up-system decoupling. Source-to-sink studies completed in areas having a Mediterranean climate cannot assume that sediment flux out of upland source areas includes the total amount of sediment available for transport. [ABSTRACT FROM AUTHOR]

This paper investigates the long-term impacts of the federal Home Owners' Loan Corporation (HOLC) mortgage risk assessment maps on the spatial dynamics of recent income and racial distributions in California metropolitan areas over the 1990-2010 period. We combine historical HOLC boundaries with modern Census tract data and apply recently developed methods of spatial distribution dynamics to examine if legacy impacts are reflected in recent urban dynamics. Cities with HOLC assessments are found to have higher levels of isolation segregation than the non-HOLC group, but no difference in unevenness segregation between the two groups of cities are found. We find no difference in income or racial and ethnic distributional dynamics between the two groups of cities over the period. At the intra-urban scale, we find that the intersectionality of residing in a C or D graded tract that is also a low-income tract falls predominately upon the minority populations in these eight HOLC cities. Our findings indicate that neighborhoods with poor housing markets and high minority concentrations rarely experience a dramatic change in either their racial and ethnic or socioeconomic compositions—and that negative externalities (e.g. lower home prices and greater segregation levels) emanate from these neighborhoods, with inertia spilling over into nearby zones. [ABSTRACT FROM AUTHOR]

Inside orchards, turbulent coherent structures dominate the transport of heat, momentum, and moisture between the canopy and the atmosphere. Integrated quadrant analysis is a method to visualize the trajectory of individual turbulent coherent structures using in situ data from three-dimensional anemometry. In this paper, integrated quadrant analysis is used to characterize the turbulent transport of heat and momentum from two orchard experiments: one in the interrow space (the Canopy Horizontal Array Turbulence Study from Dixon, California in May and June 2007) and one in the crown of a tree (the Vertical Array Cherry Experiment from Linden, California in November 2019). By using the integrated quadrant analysis (IQA) method, this paper demonstrates the importance of the cross-wind velocity component in maintaining the turbulent coherent structures. Results from integrated quadrant analysis in three dimensions support the idea that the microfront is collocated with the boundary of a sweep and an ejection in a convective boundary layer. Moreover, in both orchards, there are preferred planar trajectories for individual coherent structures that do not depend on wind regimes. The statistical profile of the turbulence quantities, as well as individual coherent structures, are not appreciably different in the interrow space or within the crown. • IQA provides the 3D coherent structure trajectory in two orchard experiments. • Individual coherent structures show characteristic planar trajectories. • Turbulent coherent structures have peak intensity near the top of the canopy. • The cross-stream velocity is large during the passage of coherent structures. [ABSTRACT FROM AUTHOR]

• This paper proposes a comprehensive optimization program to increase economic efficiency and improve the resiliency. • A demand response program integrated with home energy storage systems is presented to optimize energy consumption. • To modify the consumption pattern of household consumers, a real-time pricing algorithm is proposed. • A self-healing system reconfiguration program integrated with distributed energy resources is presented. • Real data of California households are considered to model the home appliances and home energy storage systems. This paper proposes a comprehensive optimization program to increase economic efficiency and improve the resiliency of the Distribution Network (DN). A Demand Response Program (DRP) integrated with Home Energy Storage Systems (HESSs) is presented to optimize the energy consumption of household consumers. Each consumer implements a Smart Home Energy Management System (SHEMS) to optimize their energy consumption according to their desired comfort and preferences. To modify the consumption pattern of household consumers, a Real-Time Pricing (RTP) algorithm is proposed to reflect the energy price of the wholesale market to the retail market and consumers. In addition, a Self-Healing System Reconfiguration (SHSR) program integrated with Distributed Energy Resources (DER), reactive power compensation equipment, and Energy Storage Systems (ESSs) is presented to manage the DN energy and restore the network loads in disruptive events. The reconfiguration operation is performed by converting the isolated part of the DN from the upstream network to several self-sufficient networked virtual microgrids without executing any switching process. Real data of California households are considered to model the home appliances and HESSs. The proposed comprehensive program is validated on the modified IEEE 123-bus feeder in normal and emergency operating conditions. [ABSTRACT FROM AUTHOR]

This paper presents the first systematic study on power control strategies for Modular-Gravity Energy Storage (M-GES), a novel, high-performance, large-scale energy storage technology with significant research and application potential. Addressing the current research gap in M-GES power control technology, we propose two corresponding compensation modes and several power control strategies for Hybrid M-GES and M-GES. The effectiveness of these strategies is validated through simulations on the MATLAB/Simulink platform, including tests using sinusoidal power and feasibility verification based on a natural California load curve. Additionally, we analyze the normal and abnormal operating conditions of M-GES. In conclusion, the characteristics of the proposed control strategies are summarized, providing a guideline for further research. [Display omitted] • Modular-gravity energy storage (M-GES) power control system studied. • Two compensation modes and four control strategies are systematically studied and validated. • The center switching method with hysteresis control (CSM-H) excels in continuous compensation mode. • The center switching method with hysteresis control and dead zone (CSM-HD) excels in overlap compensation mode. • Based on the power control system proposed in this paper, the M-GES plant performs highly in natural power systems. [ABSTRACT FROM AUTHOR]

The evaluation of communities' vulnerability to prolonged power outages offers valuable insights for prioritizing improvements in infrastructure resilience, thereby alleviating societal consequences. This study proposes a data-driven approach aiming at developing a Social Vulnerability Index (SoVI) to prolonged power outages leveraging three county-level datasets in California including (1) demographic features, (2) power outage factors, and (3) backup power factors. Furthermore, the study conducts a sensitivity analysis on three distinct datasets under two scenarios (Scenario 1: the current SoVI in 2022, Scenario 2: the prediction of SoVI in the year 2030). The results of Scenario 1 indicate that the counties with more affected customers, the number of power outages, and less education attainment tend to be more vulnerable to power outages in 2022. Scenario 1 reveals that the number of affected customers and power outages are the primary features influencing around 29% and 18% of counties, while educational attainment, public Electric Vehicles (EVs) chargers, and homes with rooftop photovoltaic (PV) substantially impact approximately 32%, 11%, and 8% of counties, respectively. However, in Scenario 2, crucial factors affecting the anticipated SoVI in 2030 include public EV chargers, houses with rooftop PV, power outages, and adults living alone. In contrast to Scenario 1, the prevalence of adults living alone has emerged as a notable factor impacting SoVI in 2030, while both scenarios underscore the pivotal role of EV chargers in influencing SoVI concerning power outages. The proposed SoVI facilitates informed policy decisions and infrastructure improvements in energy resilience, resource allocation, and disaster preparedness, contributing valuable insights for targeted interventions in these domains. • A data-driven approach was proposed to quantify the social vulnerability index (SoVI) to power outages. • This paper applies Principal Component Analysis (PCA) to identify the most correlated features from county-level datasets. • The paper conducts a sensitivity analysis to predict SoVI in2030 and evaluate how counties' dynamics change over time. • This paper provides insights into how policymakers can reduce the social vulnerability to power outages in California. [ABSTRACT FROM AUTHOR]

Forest fires cause every year damages to biodiversity, atmosphere, and economy activities. Forest fire simulation have improved significantly, but input data describing fire scenarios are subject to high levels of uncertainty. In this work the two-stage prediction scheme is used to adjust unknown parameters. This scheme relies on an input data calibration phase, which is carried over following a genetic algorithm strategy. The calibrated inputs are then pipelined into the actual prediction phase. This two-stage prediction scheme is leveraged by the cloud computing paradigm, which enables high level of parallelism on demand, elasticity, scalability and low-cost. In this paper, all the models designed to properly allocate cloud resources to the two-stage scheme in a performance-efficient and cost-effective way are described. This Cloud-based Urgent Computing (CuCo) architecture has been tested using, as study case, an extreme wildland fire that took place in California in 2018 (Camp Fire). • Data-driven calibration to deal with uncertainty in forest fire spread prediction. • Cloud-based urgent computing implementation of a two-stage prediction model. • Use of utility function to deal with the cost-performance trade-off. • Validation against a deadly and destructive wildfire with promising results. [ABSTRACT FROM AUTHOR]

Disasters have been a long-standing concern to societies at large. With growing attention being paid to resilient communities, such concern has been brought to the forefront of resilience studies. However, there is a wide variety of definitions with respect to resilience, and a precise definition has yet to emerge. Moreover, much work to date has often focused only on the immediate response to an event, thus investigating the resilience of an area over a prolonged period of time has remained largely unexplored. To overcome these issues, we propose a novel framework utilizing network analysis and concepts from disaster science (e.g., the resilience triangle) to quantify the long-term impacts of wildfires. Taking the Mendocino Complex and Camp wildfires - the largest and most deadly wildfires in California to date, respectively - as case studies, we capture the robustness and vulnerability of communities based on human mobility data from 2018 to 2019. The results show that demographic and socioeconomic characteristics alone only partially capture community resilience, however, by leveraging human mobility data and network analysis techniques, we can enhance our understanding of resilience over space and time, providing a new lens to study disasters and their long-term impacts on society. • Quantifying community resilience is an open research challenge • This paper develops a novel framework to quantify resilience after a disaster using network analysis • Using human mobility data associated with two wildfires, we measure robustness and vulnerability of communities • Results show community resilience closely tied to socio-economic and built environmental traits of the affected areas • Our approach paves a way to study disasters and their long-term impacts on society [ABSTRACT FROM AUTHOR]

• Factors affecting injury severity in rollover crashes were explored. • Random parameters logit model with unobserved heterogeneity in means and variances. • Findings reveal temporal instability of model specifications across individual years. • Aggregate-to-component shift quantified using out-of-sample prediction. • Implications for mitigating the associated driver injury severity. Single-vehicle rollover crashes have been acknowledged as a predominant highway crash type resulting in serious casualties. To investigate the heterogeneous impact of factors determining different injury severity levels in single-vehicle rollover crashes, the random parameters logit model with unobserved heterogeneity in means and variances was employed in this paper. A five-year dataset on single-vehicle rollover crashes, gathered in California from January 1, 2013, to December 31, 2017, was utilized. Driver injury severities that were determined to be outcome variables include no injury, minor injury, and severe injury. Characteristics pertaining to the crash, driver, temporal, vehicle, roadway, and environment were acknowledged as potential determinants. The results showed that the gender indicator specified to minor injury was consistently identified as a significant random parameter in four years' models and the joint five-year model, excluding the 2016 crash model where the night indicator associated with no injury was observed to produce the random effect. Additionally, two series of likelihood ratio tests were conducted to assess the year-to-year and aggregate-to-component temporal stability of model estimation results. Marginal effects of explanatory variables were also calculated and compared to analyze the temporal stability and interpret the results. The findings revealed an overall temporal instability of model specifications across individual years, while there is no significant aggregate-to-component variation. Injury severities were observed to be stably affected by several variables, including improper turn indicator, under the influence of alcohol indicator, old driver indicator, seatbelt indicator, insurance indicator, and airbag indicator. Furthermore, the year-to-year and aggregate-to-component shift was quantified and characterized by calculating the differences in probabilities between within-sample observations and out-of-sample predictions. The overall results imply that continuing to expand and refine the model to incorporate more comprehensive datasets can result in more robust and stable injury severity prediction, thus benefiting in mitigating the associated driver injury severity. [ABSTRACT FROM AUTHOR]

The quality of traffic services depends on the accuracy and completeness of the collected traffic data. However,the existing traffic data imputation methods usually only rely on the predefined road network structure to capture the spatio-temporal features and only consider the imputation effect from a single perspective, which are very limited for imputation of different missing patterns of road traffic data. In this paper, we propose a novel deep learning framework called Hierarchical Spatio-temporal Graph Convolutional Neural Networks(HSTGCN) to impute traffic data,through the macro layer and the road layer. The model constructs macro graph of the road network based on the data temporal correlation clustering, which can mine the temporal dependencies of road traffic data from a hierarchical perspective. Besides, a temporal attention mechanism and adaptive adjacency matrix are introduced in the road layer to better extract the spatio-temporal information of the road traffic data. Finally, we use graph convolution neural networks to learn the spatio-temporal feature representations of the road layer and macro layer, which are then fused to achieve data imputation. To illustrate the efficient performance of the model, experiments are conducted on traffic data collected from California and Seattle. The proposed model performs better than the comparison model for traffic data imputation. • A full dynamic graph is built based on the urban road structure. • Extracting spatio-temporal features from multiple dimensions using hierarchical thinking. • Gate-GCN perform effective feature selection. [ABSTRACT FROM AUTHOR]

• We analyzed trends and breakpoints for three streamflow signatures of drying patterns in 540 non-perennial streams over CONUS • Nonlinear changes in streamflow are more common than linear changes for all three stream intermittency signatures. • The past behavior of non-perennial streams might be a poor predictor of future drying patterns Stream drying patterns – including duration, timing, and dry-down rates – affect aquatic ecosystems and nutrient exports in non-perennial streams. Because hydrologic processes are often nonlinear, changes in drying may also be nonlinear, but analyses of historical changes in stream drying to date have not characterized the frequency or functional forms of nonlinear change. Understanding the extent of nonlinear change in non-perennial streams is essential for advancing our fundamental knowledge of hydrological processes, aquatic ecosystems, and watershed functioning under a warming climate. This paper uses a polynomial-based trend detection technique (PolyTrend) to analyze the linear and nonlinear trend behaviors of three intermittency signatures (annual no-flow days specifying longer or shorter drying duration, day of first no-flow occurrence specifying timing of stream drying, and days from peak to no-flow specifying dry-down rates) at 540 non-perennial gage stations over 38 years (1980–2017) across the continental United States (CONUS). Additionally, we carried out a breakpoint analysis to characterize the discontinuities in the time series of each intermittency signature. Analysis of annual no-flow days shows that about 37 % of the total streamflow stations are drying for longer each year, whereas about 22 % are wetter for longer than in the past. The day of first no-flow occurrence analysis shows that 10 % of the streams are drying earlier, and 19 % are drying later. On the other hand, analysis of days from peak to no-flow shows that 14 % of streams are drying faster, and 17 % are drying more slowly. For all these metrics, among the significant trends, at least half of the relationships were nonlinear. For annual no-flow days , the breakpoint analysis shows more discontinuities in the second half of the analysis period (1999 to 2017) than in the first half, with more discontinuities in the Southern Great Plains than in other regions. The other two signatures demonstrate less frequent discontinuities in the second half of the analysis period, suggesting decreased nonlinear dynamics in recent years. Nonlinear no-flow duration trends are common in Mediterranean California, and the dry-down rate has increased in recent decades. Our findings indicate that nonlinear change in stream drying is widespread and must be accounted for in watershed planning and management. [ABSTRACT FROM AUTHOR]

Machine learning methods are increasingly being used in the field of air quality research to investigate the relationship between air pollutant levels, emissions, and meteorological changes over time. This research is used for both scientific investigation, and policy assessment and development. However, there is a lack of studies that have compared the performance of different machine learning methods. To address this gap, this paper employed various machine learning techniques, including decision tree, random forest (RF), support vector machine (SVM), support vector regression (SVR), k-nearest neighbor, neural network, and Gaussian process regression, to predict daily average PM 2.5 levels and the number of days with PM 2.5 exceedance in the South Coast Air Basin of California from 2000 to 2019. The models were trained using meteorological factors, estimated emissions, and large-scale climate indices as inputs. The SVR model demonstrated the highest predictive accuracy for PM 2.5 levels and the SVM model gave the most accurate results for predicting the number of days with PM 2.5 exceedances. Conversely, the decision tree model performed the least accurately. The results also showed that emissions have a greater impact on PM 2.5 levels over time compared to meteorological factors, though meteorology is responsible for daily variability. The most important meteorological factors were identified as surface relative humidity and relative humidity at 850 mbars, which are related to partitioning, cloud cover and wet deposition. We conducted sensitivity tests on the model's response to emissions and meteorological factors. The predicted PM 2.5 from RF and SVR showed large correlations with emissions at the early period (2000–2010). However, the changes were minimal in more recent years (2011–2019), implying that there are biases in machine learning models, in which the models consistently predict the minimum PM 2.5 levels at a baseline. [Display omitted] • SVR is more accurate on daily PM 2.5 , particularly PM 2.5 exceedances predictions. • Surface RH was the most important meteorological factor for PM 2.5 prediction. • The impact of emissions on PM 2.5 was significant before 2010 but reduced thereafter. • ML models predict past better than future; all the ML models are limited at extremes. [ABSTRACT FROM AUTHOR]

How much should electric utilities pay to maintain a reliable electricity system? This paper describes an open-ended stated-preference experiment that generates estimates for how advanced notification impacts household willingness-to-pay (WTP) to avoid outages. We find positive and statistically significant WTP to avoid power outages of $10/kWh, consistent with the expectation that outages are costly to the residential sector. We find notification reduces the WTP, but the effects are not statistically significant. There is limited evidence that these results vary by income and wealth levels. Back-up power ownership is positively correlated with respondents' WTP to avoid outages. • Stated preference survey estimates WTP to avoid power outages. • Notifications reduce WTP but result is not statistically significant. • Back-up power ownership is positively correlated with WTP. • Results inform deployment of California PSPS and EPSS programs. [ABSTRACT FROM AUTHOR]

The licensed cannabis industry represents one of the top five most economically valued agricultural commodities in California, yet farming largely remains on remote, environmentally sensitive, "marginal" lands. Using mixed methods, this paper examines the determinants of this marginalization, their embedded elaboration, and their relation to historical policy regimes. We used Generalized Additive Models (GAMs) to determine the most important predictors of licensed cannabis industry development since the inception of a statewide licensing program in 2018 and to compare the distribution of licensed cannabis to other forms of rural agriculture, including vineyards and pasture, to understand landscape factors and environmental sensitivity of land uses. We found that a county's median income and the extent of traditional (non-cannabis) agriculture, as measured by the proportion of on-farm (non-cannabis) employment, were both negatively associated with its amount of licensed cannabis agriculture. Ethnographic data suggests that cannabis is often excluded from traditional agricultural areas, through formal local-level bans, restrictive zoning, high "prime" farmland values, and cultural exclusions from other powerful resource users. The resulting relegation to "marginal" lands foments conflicts with amenity land users and environmentalists, even as it partly supports "legacy" cultivators whose farms were established under prior policy regimes. Results suggest that cannabis is more likely to be grown under conditions that introduce regulatory hurdles, including farming on steeper slopes, with natural streams onsite, and without access to large groundwater aquifers for irrigation. Our findings suggest that failure to allow licensed cannabis farming in traditional agriculture regions has led to a self-fulfilling prophecy wherein cannabis cultivation is largely relegated to environmentally sensitive areas where cultivation activity has an elevated tendency for environmental impacts. • Cannabis cultivation occurs outside conventional agricultural areas on "marginal" land. • Counties with higher incomes and more traditional agriculture issue fewer licenses. • Non-cannabis land users drive cannabis licensing restrictions. • Marginalization of cannabis produces environmental conflict and marginalizes farmers. • Marginal land use is socially and geographically produced. [ABSTRACT FROM AUTHOR]

Nitrate pollution of surface water from farms and urban runoff is widespread – impairing drinking water supplies, recreation, and wildlife habitat. The scale of the problem in rivers has overwhelmed most watershed-based best management practices. A new paradigm is needed. In this paper we highlight the 119 ha (294 acres) Prado Wetlands in southern California, USA as an example of a gravity-enabled, free surface flow vegetated wetlands to treat a river – the nitrate-rich, effluent-dominated Santa Anna River. The wetland treats ∼1–2 m3/s of the 7.1 m3/s (250 cfs) flow of the river in 28 wetland cells in two parallel trains (residence time 2–4 d, hydraulic loading rate 10–20 cm/d). The cleaner water is returned to the river and infiltrated downstream into a managed groundwater basin supplying 2.4 million customers. Since 1998, ∼1200 t of nitrate-N have been permanently removed from the river and released as N 2 -gas into the air. Over 24 years, in the warm summers an average of 6.1 mg-N/L entered the wetland and 3.7 mg-N/L flowed out, a removal efficiency of 57%. In the cooler winters, an average of 6.4 mg NO 3 -N/L entered and 2.6 mg NO 3 -N/L flowed out, a removal efficiency of 45%. Individual months varied widely in concentration removal efficiency from 7% (winter) to 98% (high summer). Areal summer removal averaged 137 mg NO 3 -N/m2/d and the apparent "k" was around 46 m/y. All-year rates were 129 mg NO 3 -N/m2/d or 47 g/m2/y, a reasonable performance considering the size of the system and its configuration for both nitrate removal and duck hunting (i.e., more open water). Annual average nitrate removal efficiency increased substantially over time (45 to 72% for 1998–2004 versus 2016–22) and is attributed to an increase in hydraulic residence time, upgraded internal plumbing, and increased winter temperatures (+3C°). Prado Wetlands also removes phosphorus, though not as well as nitrate; average warm season removal efficiency was 23% (inflow 1.20 mg PO 4 -P/L, outflow 0.93 mg PO 4 -P/L). The aerial removal rate was high at 23 mg P/m2/d or 8.5 g/y, probably due to the high inflowing P-concentrations and the hard water. Wildlife was also enhanced. Least Bell's Vireo (Vireo belli pusillus) , an endangered bird in the Prado Basin, increased from 19 pairs (1998) to a recent average of 444 pairs due to habitat improvement and reduction of cowbird parasitism. Results from the Prado Wetlands show that cleaning up rivers via diversion through wetlands benefits both water quality and wildlife. [ABSTRACT FROM AUTHOR]

• Elite and non-elite members of a complex hunter-gatherer society were found to have eaten nearly identical diets. • Similarity in elite and non-elite diets was consistent over a period of major sociopolitical change. • Male and female diets were significantly different at an inland site but not on the coast, possibility indicating a higher degree of male mobility. • Elites likely chose non-subsistence venues for status signaling, such as ownership of canoes and trade in prestige goods. How different were the lives of elites and commoners in early complex societies? This paper examines this question using data from three fisher-hunter-gatherer sites in southern California. Using shell bead counts from burials as proxies for social status and previously published human stable isotope values as indicators of dietary practices, we examine the relationship between diet and status across a period of major sociopolitical change. Our results found no significant relationships between the quantity of beads and stable isotope values, indicating that differential access to foods was not a significant way in which status was manifested in these communities. Instead, we suggest that activities including ownership of sea-going canoes, access to imported goods, and the provisioning of community feasts were likely venues for elite status signaling. [ABSTRACT FROM AUTHOR]

To assess whether a measure of leadership support for worker safety, health, and well-being predicts staff turnover in nursing homes after controlling for other factors. This paper uses administrative payroll data to measure facility-level turnover and uses a survey measure of nursing home leadership commitment to workers. In addition, we use data from Medicare to measure various nursing home characteristics. Nursing homes with at least 30 beds serving adults in California, Ohio, and Massachusetts were invited to participate in the survey. The analysis sample included 495 nursing homes. We used a multivariable ordinary least squares model with turnover rate as the dependent variable. We used an indicator for nursing homes who scored above the median on the measure of leadership that supports worker safety, health, and well-being. Control variables include bed count (deciles), ownership (corporate/noncorporate × for-profit/not-for-profit), percent of residents on Medicaid, state, being in a nonmetropolitan county, and total nurse staffing per patient day in the 2 quarters before the survey. The unadjusted turnover rate was lower for those nursing homes that scored higher on leadership commitment to worker safety, health, and well-being. After controlling for additional variables, greater leadership commitment was still associated with lower turnover but with some attenuation. We find that nursing homes with leadership that communicated and demonstrated commitment to worker safety, health, and well-being had relatively fewer nurses leave during the study period, with turnover rates approximately 10% lower than homes without. These findings suggest that leadership may be a valuable tool for reducing staff turnover. [ABSTRACT FROM AUTHOR]

Inequities in the built environment have long persisted in communities around the world. Prior studies have exposed that energy retrofit programs invest inequitably in residential buildings, leaving racial minorities with disproportionately less energy inefficient homes, regardless of income level. This inequity in energy performance and retrofit investments has yet to be studied for commercial and institutional buildings. Further research has shown that tree canopy coverage and vegetation is less dense in historically disadvantaged communities, contributing to a greater urban heat island effect and corresponding higher energy consumption for cooling compared to historically advantaged communities. Moreover, there is limited albeit emerging research that utilizes granular socioeconomic data with fine temporal scale energy consumption data to help identify energy inequalities among race and income groups. This paper examines the differential impact of energy efficiency retrofit installation on energy performance between advantaged vs. disadvantaged groups using data from U.S. public school buildings. Additionally, it studies how the effect of retrofits is compounded by the presence of vegetation surrounding the building. Utilizing hourly interval smart meter data from primary and secondary school buildings in California, the impact of retrofits are quantified using three energy metrics. Then the disparities in retrofit impact for advantaged vs. disadvantaged groups (as defined by three equity metrics) are evaluated using school-level demographic data. Lastly, regression on the percent change in monthly energy consumption from the pre-retrofit to post-retrofit period is used to quantify the incremental benefits of retrofits compounded by vegetation. Findings show that energy efficiency retrofits can improve energy performance and reduce energy inequities. Specifically, retrofits significantly increase energy efficiency and reduce the energy efficiency equity gap by up to 198%. Evidence shows that vegetation surrounding a building has a synergistic effect with mechanical retrofits for reducing energy consumption in respect to reduced cooling loads, even in cases where mechanical retrofits alone resulted in significant increases in energy consumption. Dense vegetation provides around 6% energy savings, similar in magnitude to savings from mechanical retrofit installation. This validates the effectiveness of retrofits for reducing energy consumption and improving energy equity, and demonstrates the ability of vegetation to provide additional energy savings beyond mechanical interventions. [ABSTRACT FROM AUTHOR]

This study characterized nitrogen oxides (NOx) and ammonia (NH 3) emissions from five in-use goods movement vehicles, including one diesel vehicle without selective catalytic reduction (SCR), two diesel vehicles with SCR, and two ultra-low NOx natural gas vehicles equipped with three-way catalysts (TWCs). Emissions testing was performed under real-world driving conditions in typical goods movement routes in the South Coast Air Basin (SCAB) of California. NOx emissions varied depending on the vehicle and the route. The no-SCR diesel vehicle showed the highest NOx emissions over all the routes. One of the SCR-equipped vehicles showed NOx emission rates that were two times higher than the other SCR-equipped vehicle with similar engine model year and mileage, which may be attributed to catalyst deterioration. The SCR-equipped diesel vehicles were within two to three times 0.2 g/bhp-hr certification standard over the different routes. The natural gas vehicles showed average NOx emissions around or below the optional Low NOx emissions standard of 0.02 g/bhp-hr. The three-bin moving average window (MAW) method was utilized to show the NOx emissions across various modes of operation, including idle, low load, and medium/high load. The highest fraction of vehicle operation was found in either the low load or medium/high load bins, depending on the route. NOx emissions for each of the bins varied between different vehicles, and are further analyzed in this paper. NH 3 emissions formation was favored for the TWC-equipped natural gas vehicles, which produced about 20 times more NH 3 emissions than the SCR-equipped diesel vehicles. [Display omitted] • Significant NOx reductions for the natural gas vehicles compared to the SCR-equipped diesel vehicles. • NH 3 formation favored in the TWC for the natural gas vehicles and produced during acceleration events. • Low load and medium/high load conditions dominated vehicle operation and NOx emissions. [ABSTRACT FROM AUTHOR]

Vegetation structure mapping is critical for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. Repeated measurements of these data allow for the observation of deforestation or degradation of existing forests, natural forest regeneration, and the implementation of sustainable agricultural practices like agroforestry. Assessments of tree canopy height and crown projected area at a high spatial resolution are also important for monitoring carbon fluxes and assessing tree-based land uses, since forest structures can be highly spatially heterogeneous, especially in agroforestry systems. Very high resolution satellite imagery (less than one meter (1 m) Ground Sample Distance) makes it possible to extract information at the tree level while allowing monitoring at a very large scale. This paper presents the first high-resolution canopy height map concurrently produced for multiple sub-national jurisdictions. Specifically, we produce very high resolution canopy height maps for the states of California and São Paulo, a significant improvement in resolution over the ten meter (10 m) resolution of previous Sentinel / GEDI based worldwide maps of canopy height. The maps are generated by the extraction of features from a self-supervised model trained on Maxar imagery from 2017 to 2020, and the training of a dense prediction decoder against aerial lidar maps. We also introduce a post-processing step using a convolutional network trained on GEDI observations. We evaluate the proposed maps with set-aside validation lidar data as well as by comparing with other remotely sensed maps and field-collected data, and find our model produces an average Mean Absolute Error (MAE) of 2.8 m and Mean Error (ME) of 0.6 m. [Display omitted] • Very high resolution canopy height maps at jurisdictional scale are released. • Improved performance from vision transformers based on Self-Supervised Learning (SSL). • First use of SSL and vision transformers for canopy height estimation. • Low resolution GEDI and high resolution aerial lidar predictions are combined. • Model generalizes well to aerial imagery, even though trained with satellite images. [ABSTRACT FROM AUTHOR]