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This paper introduces the Watermark Imaging System (WImSy) which can be used to photograph, document, and study sheets of paper. The WImSy provides surface images, raking light images, and transmitted light images of the paper, all in perfect alignment. We develop algorithms that exploit this alignment by combining several images together in a process that mimics both the "surface image removal" technique and the method of "high dynamic range" photographs. An improved optimization criterion and an automatic parameter selection procedure streamline the process and make it practical for art historians and conservators to extract the relevant information to study watermarks. The effectiveness of the method is demonstrated in several experiments on images taken with the WImSy at the Metropolitan Museum of Art in New York and at the Getty Museum in Los Angeles, and the results are compared with manually optimized images. [ABSTRACT FROM AUTHOR]

This paper focuses on crime status prediction through an ensemble methodology applied to extensive datasets obtained from catalog.data.gov, specifically targeting Los Angeles crime incidents since 2020. The research methodology comprises meticulous data collection, rigorous preprocessing, exploratory data analysis, model selection, and comprehensive model evaluation. Initial challenges included data inaccuracies and privacy-preserving measures in location data, necessitating thorough cleaning and transformation processes. Exploratory data analysis revealed crucial insights, including the 'Status' attribute's limited correlation, crime code distributions, areawise crime counts, and temporal patterns. To address class imbalance within 'Status', the Synthetic Minority Oversampling Technique (SMOTE) was applied to balance the dataset. Model evaluation highlighted the superiority of random forest models employing 10 and 20 decision trees, alongside KNN, which demonstrated consistent high accuracy, balanced precision-recall trade-offs, and notable F1 scores in crime status prediction. [ABSTRACT FROM AUTHOR]

Runtime verification (RV) refers to methods for formal reasoning about all aspects of the dynamic execution of systems, including hardware, software, and cyber-physical systems. RV includes techniques to assess and enforce correctness of a system against systemic bugs or extrinsic uncertainties. These methods are typically considered lightweight as they may not involve exhaustive verification or proofs, but they provide a higher level of rigor and versatility compared to conventional testing methods. This article introduces the extended versions of selected papers from the peer-reviewed proceedings of the 20th International Conference on Runtime Verification (RV 2020). RV 2020 was supposed to be held in Los Angeles, California, USA in July 2020, but was instead held virtually due to the global Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

Traffic congestion occurs when there is a mismatch between the demand for road use and the available capacity. The volume-delay function (VDF) can quantify the relationship between travel time and the volume of traffic on a particular link, and also provide insight into the state of a traffic system, such as whether it is congested or uncongested. In this paper, we present a VDF model that is based on the fundamental diagram and has two main components: (1) an improved VDF with fewer parameters that can handle both congested and uncongested traffic conditions, based on a fundamental diagram, and (2) a model-based VDF practical calibration framework for practical traffic applications that can determine key parameters for a link in a corridor. Our experiments using corridors in Los Angeles and Beijing demonstrate that our proposed analytical methods effectively calculate road impedance under congested conditions. The results indicate that the proposed model is superior to other existing models in terms of the root mean squared error (RMSE) and mean absolute error (MAE). In addition, our calibrated results indicate that the travel time index (TTI) in Los Angeles is 2.12, in Beijing is 1.74. The model proposed in this paper provides a useful calibration tool for enhancing model performance and improving the accuracy of travel time and speed estimates in traffic assignment. [ABSTRACT FROM AUTHOR]

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]

As the world becomes increasingly "smaller," global governance too shifts beyond states and formal agreements to include norms and actors at all levels of government and society. Cities, in particular, are emergent actors in global affairs. This paper examines a new type of experiential learning model for this burgeoning local–global governance: academic partnerships with city governments for undergraduate international relations courses. Occidental College and Pomona College have partnered with the Los Angeles Mayor's Office to localize and adopt the United Nations Sustainable Development Goals (SDGs). This study focuses on two Spring 2021 Task Force courses, where students worked in consultation with the Mayor's Office to conduct policy research on local implementation of SDG 5 on gender equality. It analyzes the pedagogical value of the Task Force courses with a focus on student learning outcomes and challenges. Through qualitative content analysis of student reflection papers, we find that the courses generate substantial student learning, particularly in higher forms of learning, including development of research and professional skills and metacognitive reflection on "doing theory," or praxis, within the international relations discipline. Further, these partnerships also benefit the city, as they generate valuable data that inform policymaking. [ABSTRACT FROM AUTHOR]

The aggregates are essential materials in civil engineering, they are used for railway and road constructions, for hydraulic engineering but they are also the base material of concrete. The crushed stones are exposed to several effects during their lifespan. Therefore, several tests were developed to evaluate their performance. One of the most important aspects is the resistance to degradation. However, degradation tests require special types of equipment and usually take longer than common strength tests which are more likely to be available for rock materials. Therefore, the empirical connections between strength and degradation values can be extremely useful in practice. The paper aimed to collect all available relationships and datasets from the literature that presents the relations between these different parameters - such as Aggregate Impact Value (AIV), Aggregate Crushing Value (ACV), Ten Percent Fines Value (TFV), Los Angeles Abrasion Value (LAAV), and micro-Deval Coefficient (MDE) - and rock strength parameters - such as Uniaxial Compressive Strength (UCS) and Point Load Strength Index (IS(50)) - and to provide the best-fit formula for different rock types. The paper also highlights the difficulties and limitations of the compared relationships. [ABSTRACT FROM AUTHOR]

While the co-production of knowledge through community-engaged research is intended to be a reciprocally beneficial process, academic institutions have often devalued community expertise by treating community organizations as subjects rather than co-creators of knowledge. Drawing from Black Feminist Epistemology, this ethnographic study examines how one community-based organization, Los Angeles Community Action Network (LA CAN), partners with academic researchers, including their discourse around partnerships and how they challenged power dynamics between community and their university partners. This paper discusses key themes from their partnerships, including centering community members' expertise through their lived experience and forming long-term mutual relationships rooted in abolition and the Black Radical Tradition. Drawing on an analysis of LA CAN's organizing and research processes with academic partners, we discuss how the centering of community expertise and forming relationships with academics aligned on these values can help to challenge the traditional power dynamics in community-university partnerships, resulting in different ways of knowing or what LA CAN referred to as "the real data set.". [ABSTRACT FROM AUTHOR]

Philip K. Dick takes the highly computerized but ruined Los Angeles of the United States after the post-apocalyptic war as the background and brings the cyberspace struggle between androids and humans as the novel's theme, sketching a cyberpunk society in which humans and androids fight against each other. The novel Do Androids Dream of Electric Sheep? invites people to think about cyberspace and human-androids subjectivity. Inspired by Slavoj Zizek's critical theory of cyberspace, this paper uses this science-fiction force as a text to explore how contemporary American science fiction reconstructs a revolutionary human-androids subject in cyberspace, challenging human subjectivity in the urban space. Faced with human-android coexistence, Dick affirms the coexistence of multiple subjects using equal dialogue, fully exploits the advantages of androids and humans, and constructs the subject with human-androids. Through an in-depth study of androids, this paper concludes that in a human-androids coexistence space, humans and androids should not be in a master-slave relationship; instead, they are each other's constitutive Other. Humans should try to break the boundary between self and others to accept a pluralistic and open subject. [ABSTRACT FROM AUTHOR]

Runtime verification (RV) refers to methods for formal reasoning about all aspects of the dynamic execution of systems, including hardware, software, and cyber-physical systems. RV includes techniques to assess and enforce correctness of a system against systemic bugs or extrinsic uncertainties. These methods are typically considered lightweight as they may not involve exhaustive verification or proofs, but they provide a higher level of rigor and versatility compared to conventional testing methods. This article introduces the extended versions of selected papers from the peer-reviewed proceedings of the 21st International Conference on Runtime Verification (RV 2021). RV 2021 was supposed to be held in Los Angeles, California, USA in November 2021, but was instead held virtually due to the global Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

Background: According to the 5th edition of the Japanese Guidelines for the Treatment of Gastric Cancer, proximal gastrectomy is recommended for patients with early upper gastric cancer who can retain the distal half of the residual stomach after R0 resection. However, a large number of recent clinical studies suggest that surgical indications for proximal gastrectomy in the guidelines may be too narrow. Therefore, this meta-analysis included patients with early and advanced gastric cancer and compared short- and long-term postoperative outcomes between the two groups. At the same time, we only had high-quality clinical studies such as propensity score-matched studies and randomized controlled trials, which made our research more authentic and credible. Methods: Data were retrieved from PubMed, EMBASE, Medline, and Cochrane Library up to June 2023, and included treatment outcomes after proximal gastrectomy with double-tract reconstruction and total gastrectomy with Roux-en-Y reconstruction. The primary results were Early-phase complications(Anastomotic leakage, Anastomotic bleeding, Abdominal abscess, Abdominal infection, Pulmonary infection, Incision infection, Intestinal obstruction, Dumping syndrome, Pancreatic fistula), Late-phase complications(Intestinal obstruction, Anastomosis stricture, Dumping syndrome, Reoperation, Internal hernia, Incidence of endoscopic gastroesophageal reflux), Serious complications (≥ Grade III C-D score), Quality of life[Gastroesophageal reflux symptom evaluation (Visick score)(≥ III), Los Angeles classification(C or D)], Nutritional status(Hemoglobin, Receipt of vitamin B12 supplementation), Oncologic Outcomes(The 5-year overall survival rates). Secondary outcomes were surgical outcomes (Operative time, Estimated blood loss, Postoperative hospital stay, Number of harvested lymph nodes, Gas-passing, Postoperative mortality).The Cochrane risk-of-bias tool and Newcastle‒Ottawa scale were used to assess the quality of the included studies. Results: After screening, 11 studies were finally included, including 1154 patients. Results from the combined literature showed that total gastrectomy had a significant advantage over proximal gastrectomy with double-tract reconstruction in mean operating time (MD = 4.92, 95% CI: 0.22∼9.61 P = 0.04). However, meta-analysis results showed that Hemoglobin (MD = 7.12, 95% CI:2.40∼11.84, P = 0.003) and Receipt of vitamin B12 supplementation (OR = 0.12, 95% CI:0.05∼0.26, P < 0.00001) in the proximal gastrectomy with double-tract reconstruction group were better than those in the total gastrectomy with Roux-en-Y reconstruction group. There is no significant difference between the proximal gastrectomy with double-tract reconstruction and the total gastrectomy with Roux-en-Y reconstruction group in Early-phase complications(OR = 1.14,95% CI:0.79∼1.64, P = 0.50), Late-phase complications(OR = 1.37,95% CI:0.78∼2.39, P = 0.27), Gastroesophageal reflux symptom evaluation (Visick score)(≥ III)(OR = 0.94,95% CI:0.14∼1.07 P = 0.07), Los Angeles classification(C or D)(OR = 0.33,95% CI:0.01∼8.21, P = 0.50), the 5-year overall survival rates (HR = 1.01, 95% CI: 0.83 ~ 1.23, P = 0.89). Conclusion: Proximal gastrectomy with double-tract anastomosis is a safe and feasible treatment for upper gastric carcinoma. However, the operating time was slightly longer in the proximal gastrectomy with double-tract group compared to the total gastrectomy with Roux-en-Y group. The two groups were comparable to the total gastrectomy with Roux-en-Y group in terms of serious complications (≥ Grade III C-D score), early-phase complications, late-phase complications, and quality of life. Although the scope of proximal gastrectomy is smaller than that of total gastrectomy, it does not affect the 5-year survival rate, indicating good tumor outcomes for patients. Compared to total gastrectomy with Roux-en-Y group, proximal gastrectomy with double-tract reconstruction had higher hemoglobin levels, lower probability of vitamin B12 supplementation, and better long-term efficacy. In conclusion, proximal gastrectomy with double-tract reconstruction is considered one of the more rational surgical approaches for upper gastric cancer. [ABSTRACT FROM AUTHOR]

While infill development is widely accepted by cities as an alternative to urban sprawl, a very dearth of research has attempted to measure infill development and identify contributing factors to infill development. Filling this research gap, this paper models residential infill development in the City of Los Angeles by employing five machine learning (ML) algorithms. This paper attempts to identify the best-performing ML algorithms by comparing the performance of the ML algorithms. Of the five ML algorithms tested, the random forest (RF) and k-nearest neighbor (kNN) algorithms are selected as the best-performing algorithms. The RF algorithm ranks independent variables from most to least important. Overall, the ranks suggested that residential infill development in the City of Los Angeles is significantly influenced by the physical conditions of property and neighborhood rather than socioeconomic characteristics. Diverse land uses, good housing mixes, and rail transit accessibility also, importantly, contributed to the infill development. This finding suggests that the city's planning efforts, such as the promotion of accessory dwelling unit (ADU) development and the expansion of rail transit, can create a virtuous circle for sustainable urban development. [ABSTRACT FROM AUTHOR]

Self-melting ice asphalt pavement materials inhibit pavement freezing and improve driving safety. This paper aims to study the long-term salt release characteristics of self-melting ice asphalt mixtures and the impact on pavement after complete salt release. Firstly, a method to accelerate the rapid release of salt based on the Los Angeles abrasion tester. Then, long-term salt release patterns were elucidated under the influence of deicing agent dosage, type of asphalt, and type of gradation. Finally, a quantitative analysis of the pavement performance after complete salt release is conducted. The results indicate that the release efficiency of the Los Angeles abrasion tester method has increased by 91 times compared to the magnetic stirrer immersion flushing method and by 114 times compared to the natural soaking method. The SBS-modified self-melting ice asphalt mixture possesses a longer duration of salt release, but the uniformity of salt release is inferior. Salt release duration is directly proportional to the dosage of deicing agents. SMA-13 self-melting ice asphalt mixture exhibits poorer uniformity in salt release. After complete salt release, high-temperature stability of self-melting ice asphalt mixtures decreased by 31.6%, low-temperature performance decreased by 15.4%, water stability decreased by 26.7%, and fatigue life decreased by 35.9%. [ABSTRACT FROM AUTHOR]

This paper presents an extensive numerical study on the seismic performance of steel eccentrically braced frames (EBFs) designed according to the ASCE 7-16 standard. A series of EBF building structures ranging from 2 to 12 stories located in downtown Los Angeles are designed with different yielding links, including conventional and replaceable links. The performance of the structures is investigated through nonlinear time-history analyses (NLTHAs) under a suite of 40 ground motions, selected and scaled to match the target uniform hazard spectrum. The peak deformations are first examined to assess the performance of the buildings as well as the design procedure. Residual deformations are also evaluated and critically compared with acceptable limits, to provide insight into the downtime and recovery time of EBFs after major earthquakes. Previous studies have demonstrated that the response of stable yielding systems to major earthquakes is often accompanied by significant residual deformations, and that residual drifts exceeding 0.5% can cause hindrance to the buildings occupants. In EBFs, in addition to residual drifts, residual link rotations are also relevant and expected to be more severe due to the localization of inelastic deformations in the yielding link. For replaceable modular yielding links, significant residual link rotations after major earthquakes will hinder repairs and the link replacement process, which is one of the important design objectives. The performance of EBFs is also compared with what was observed in previous studies for buckling restrained braced frames and special moment resisting frames. In the end, the results from the extensive NLTHAs are used to establish a relationship between peak drifts and peak link rotations in EBFs. [ABSTRACT FROM AUTHOR]

The 2020 census reports that 61.2 million Latinxs live in the US, totaling around 19% of all residents, forming the country's largest minority population. With the growing number of Latinxs, there has been a higher level of contact between Spanish and English leading to language mixing or code-switching (CS) in mainstream American culture. This paper examines the Spanish/English CS in radio advertisements on Los Angeles's 96.3 La Mega, a bilingual radio station geared towards today's youth. Using Derrick' 2015 sentential framework for the linguistic analysis of multilingual sentences, I carry out a sentence-by-sentence analysis of the linguistic nature of the on-air bilingual advertisements. I explore both national advertisements, as well as DJ-endorsed advertisements, to discern whether they follow the patterns previously pointed out in the literature for positive consumer evaluations of Spanish/English bilingual advertisements. Furthermore, I am interested in if these advertisements are in line with the ethos of 96.3 La Mega, which prides itself on being fully bilingual. This research will shed light on the linguistic nature of contemporary strategies being used in bilingual advertisements for the US Latinx community and marketing tactics designed to encourage their consumerism. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive modeling framework for large-scale agent-based multimodal transportation simulation tailored to the complex urban environments of megacities, with a specific focus on the Greater Los Angeles (LA) area. The framework leverages the Multi-Agent Transport Simulation (MATSim) toolkit, which addresses the evolving challenges posed by urbanization and technology-driven shifts in human mobility patterns. The framework enables the generation of explicit travel trajectories for a representative 10% sample population of LA County, comprising over one million individuals. To ensure the model's validity, an efficient network calibration algorithm is proposed with rigorous validation using publicly available traffic count data. This paper underscores the development and configuration of the agent-based simulation model for LA, providing a robust foundation for large-scale urban mobility simulations and advancing our understanding of the intricacies of megacities. [ABSTRACT FROM AUTHOR]

Chile, recognized as one of the world's most earthquake-prone nations, has gained valuable insights from significant earthquakes, such as those in 1985 and 2010, which have influenced updates to the nation's design codes. Although Chile's seismic design approach has been largely effective in recent earthquakes and demonstrated an "operational" performance level in most structures, performance-based design (PBD) methods have not yet been officially incorporated as valid approaches in the Chilean seismic design codes for buildings. However, in 2017, the Chilean Association on Seismology and Earthquake Engineering (ACHISINA) introduced a PBD approach, primarily for verification purposes, based on the Los Angeles Tall Buildings Structural Design Council (LATBSDC) framework. In this work, firstly, we provide an overview of Chile's PBD methodology, focusing on the thresholds for various performance levels. These levels are established through experimental and numerical analysis, correlating performance with permissible damage levels. The second part of the paper examines the seismic performance of a residential building, designed before the 2010 Maule earthquake and subsequently damaged, using Chile's PBD guidelines. This case study highlights the implementation and effectiveness of PBD for assessing seismic resilience in Chilean structures. [ABSTRACT FROM AUTHOR]

This study aims to forecast New York and Los Angeles gasoline spot prices on a daily frequency. The dataset includes gasoline prices and a big set of 128 other relevant variables spanning the period from 17 February 2004 to 26 March 2022. These variables were fed to three tree-based machine learning algorithms: decision trees, random forest, and XGBoost. Furthermore, a variable importance measure (VIM) technique was applied to identify and rank the most important explanatory variables. The optimal model, a trained random forest, achieves a mean absolute percent error (MAPE) in the out-of-sample of 3.23% for the New York and 3.78% for the Los Angeles gasoline spot prices. The first lag, AR (1), of gasoline is the most important variable in both markets; the top five variables are all energy-related. This paper can strengthen the understanding of price determinants and has the potential to inform strategic decisions and policy directions within the energy sector, making it a valuable asset for both industry practitioners and policymakers. [ABSTRACT FROM AUTHOR]

Objectives: The objective of this paper is to improve understanding of the spatial relationship of the built environment (BE) with urban gun crime and how the influence of environmental features varies across geographic location and socioeconomic context. Specifically, we analyze associations between incidents of reported firearms violence and distance to built environment features, accounting for neighborhood socio-economic status. Methods: This study compares reported crime data with the outputs from a Monte Carlo Simulation using the Network Cross-K Function for Stochastic Spatial Events on street networks. Where data is available, we examine ten features—transit stations, universities/colleges, convenience stores, gas stations, liquor licenses, alcohol outlets, tobacco retailers, lodging, restaurants, and schools—across diverse metropolitan areas to uncover features that exert "attractive" or "repellent" influence on firearms violence. We present results from four U.S. cities and examine how results vary by socio-economic status of census tracts. Results: Attractive features include tobacco retailers in Pittsburgh, hotels/motels, alcohol outlets, and restaurants in New Orleans, and rail transit stations in Los Angeles. We uncover localized attractive and repellent relationships within the lowest and highest socio-economic areas. We also identify several firearms crime repellents, including universities/colleges and public/private schools. Conclusions: We find that attractors vary by city and socio-economic status, indicating that the unique underlying environmental context of each city facilitates firearms crime differently. [ABSTRACT FROM AUTHOR]

This paper examines communicating about complex challenges facing populations experiencing homelessness and examining alternative ways to communicate with these populations in times of crisis. Utilizing a case study approach, the researchers focused on cities in New York and California due to the high numbers of unhoused populations and individuals experiencing homelessness within these states. Experts in crisis and emergency management have provided invaluable recommendations on the general protection of life and property; however, individuals identifying as homeless or unhoused share characteristics that heighten their risk and vulnerability, such as lower socioeconomic status, unstable resilience levels prior to a crisis, and geographic disparities. The intersection of these attributes presents unique challenges for emergency managers and relevant public administrators when implementing crisis response and communication strategies, such as one-way written and oral messaging over media and social networks, along with enacting any new protocols needed in relation to the crisis itself, like targeted outreach. This paper discusses the evolution of crisis communication for homeless and unhoused populations, national statistics, along with analysis of case studies for Los Angeles, California, and New York City, New York. The paper concludes with eight major themes related to communicating with homeless and unhoused populations during times of crises and practical recommendations for emergency managers and relevant public administrators. It is critical that representatives and advocates for populations experiencing homelessness, or are unhoused, are involved in the dialogue and planning efforts. Stable investment in communication infrastructure and crisis communication programs and services is vital to assist homeless and unhoused populations in gaining access to the Internet and cell phone providers, outreach campaigns for printed messaging, alternative locations for media reporting, and receiving critical information during crisis and noncrisis periods. In terms of messaging, crisis-related alerts (oral and written) must be reviewed to ensure clarity in tone to avoid ambiguity and identify and remove any stigmatization language to open a two-way dialogue. Emergency managers and related public administrators must use a diverse array of communication avenues and strategies, such as social media and electronic messages (i.e., cell phones, media statements, and business signage) and traditional methods (i.e., leaflets at social service providers and shelters) with a focus on creating dialogue and empowering individuals to engage and seek out services. In addition, a crisis team dedicated to communicating with homeless and unhoused populations in times of crisis is needed along with dedicated resources for staffing, communication infrastructure, programs, and services. [ABSTRACT FROM AUTHOR]

Introduction: The COVID-19 pandemic disproportionately affected older adults, particularly those with pre-existing chronic health conditions. To address the health disparity and challenges faced by under-resourced African American older adults in South Los Angeles during this period, we implemented a hybrid (virtual/in-person), pre-post, community-based participatory intervention research project utilizing a faith-based lay health advisor model (COVID-19 Health Ambassador Program (CHAP)). We recruited COVID-19 Health Ambassadors (CHAs) and African American older adults (participants) from faith-based organizations who partook in CHA-led meetings and follow-ups that educated and supported the participants. This paper seeks to evaluate this intervention's implementation using the Consolidated Framework for Implementation Research (CFIR) as a reporting tool with an emphasis on fidelity, challenges, and adaptations based on data collected via stakeholder interviews and surveys. Results: CHAP was delivered to 152 participants by 19 CHAs from 17 faith-based organizations. CHAs assisted with chronic disease management, resolved medication-related challenges, encouraged COVID-19 vaccination, reduced psychological stress and addressed healthcare avoidance behaviors such as COVID-19 vaccine hesitancy among the participants. Challenges encountered include ensuring participant engagement and retention in the virtual format and addressing technological barriers for CHAs and participants. Adaptations made to better suit the needs of participants included providing communication tools and additional training to CHAs to improve their proficiency in using virtual platforms in addition to adapting scientific/educational materials to suit our participants' diverse cultural and linguistic needs. Conclusion: The community-centered hybrid approach in addition to our partnership with faith-based organizations and their respective COVID-19 health ambassadors proved to be essential in assisting underserved African American older adults manage chronic health conditions and address community-wide health disparities during the COVID-19 pandemic. Adaptability, cultural sensitivity, and teamwork are key to implementing health interventions especially in underserved populations. [ABSTRACT FROM AUTHOR]

Mega-events like the Olympics and the Football World Cup routinely harm host cities and societies, largely due to their linkages with ambitious urban development agendas. Concurrently, resident protest has had only limited success in mitigating mega-event-related damages, notwithstanding the growth of resistance networks at local, national, and transnational scales. Contextualised within the broader processes of the Agenda 2020 and New Norm Olympic reforms, this paper explores the tactics of protest against the Summer Olympics in Paris 2024 and Los Angeles 2028. In so doing, the paper demonstrates how the reforms have moderated some of the more egregious aspects of mega-event harm, while nevertheless preserving some fundamental problems with hosting, albeit in more diffuse or disguised forms. The paper makes sense of these processes through the notion of Potemkinism, conceptualised as a dynamic between the superficial and the substantive, and predicated on obfuscation or concealment. The paper also presents a taxonomy of tactics adopted by host city residents to counter the problems that persist in these processes of Potemkin reform. [ABSTRACT FROM AUTHOR]

Atmospheric delay correction remains a major challenge for interferometric synthetic aperture radar (InSAR) technology. In this paper, we first reviewed several commonly used methods for tropospheric delay correction in InSAR. Subsequently, considering the large volume and high temporal resolution of global navigation satellite system (GNSS) station measurement data, we proposed a method for spatial prediction of the InSAR tropospheric delay phase based on the backpropagation (BP) neural network and GNSS zenith total delay (ZTD). Using 42 Sentinel-1 interferograms over the Los Angeles area in 2021 as an example, we validated the accuracy of the BP + GNSS method in spatially predicting ZTD and compared the correction effects of BP + GNSS and five other methods on interferograms using the standard deviation (StaD) and structural similarity (SSIM). The results demonstrated that the BP + GNSS method reduced the root-mean-square error (RMSE) in spatial prediction by approximately 95.50% compared to the conventional interpolation method. After correction using the BP + GNSS method, StaD decreased in 92.86% of interferograms, with an average decrease of 52.03%, indicating significantly better correction effects than other methods. The SSIM of the BP + GNSS method was lower in mountainous and high-altitude areas with obvious terrain changes in the east and north, exhibiting excellent and stable correction performance in different seasons, particularly outperforming the GACOS method in autumn and winter. The BP + GNSS method can be employed to generate InSAR tropospheric delay maps with high temporal and spatial resolution, effectively addressing the challenge of removing InSAR tropospheric delay signals in areas with significant terrain variations. [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]

This paper offers a theoretical investigation about the notion of "skills" within a geographical approach. For spatial practices, the challenge is probably less about understanding what individuals do than their ways of doing. Building on an empirical survey about the tourists practices in Los Angeles, the paper first supports the idea that each spatial configuration is an issue for every individual, a gathering of spatial stakes that everyone must address. Then, it argues that the ways in which individuals deal with these stakes depend on their skills. Defining skills as "the mastery of techniques", the article engages a critical discussion with French pragmatic sociology (Boltanski and Thévenot) and geography (Lussault) as well as upon works in anthropology (Ingold). [ABSTRACT FROM AUTHOR]

Cellular vehicle-to-everything (C-V2X) is a communication technology that supports various safety, mobility, and environmental applications, given its higher reliability properties compared to other communication technologies. The performance of these C-V2X-enabled intelligent transportation system (ITS) applications is affected by the performance of the C-V2X communication technology (mainly packet loss). Similarly, the performance of the C-V2X communication is dependent on the vehicular traffic density which is affected by the traffic mobility patterns and vehicle routing strategies. Consequently, it is critical to develop a tool that can simulate, analyze, and evaluate the mutual interactions of the transportation and communication systems at the application level to quantify the benefits of C-V2X-enabled ITS applications realistically. In this paper, we demonstrate the benefits gained when using C-V2X Vehicle-to-Infrastructure (V2I) communication technology in an energy-efficient dynamic routing application. Specifically, we develop a Connected Energy-Efficient Dynamic Routing (C-EEDR) application using C-V2X as a communication medium in an integrated vehicular traffic and communication simulator (INTEGRATION). The results demonstrate that the C-EEDR application achieves fuel savings of up to 16.6% and 14.7% in the IDEAL and C-V2X communication cases, respectively, for a peak hour demand on the downtown Los Angeles network considering a 50% level of market penetration of connected vehicles. The results demonstrate that the fuel savings increase with increasing levels of market penetration at lower traffic demand levels (25% and 50% the peak demand). At higher traffic demand levels (75% and 100%), the fuel savings increase with increasing levels of market penetration with maximum benefits at a 50% market penetration rate. Although the communication system is affected by the high density of vehicles at the high traffic demand levels (75% and 100% the peak demand), the C-EEDR application manages to perform reliably, producing system-wide fuel consumption savings.The C-EEDR application achieves fuel savings of 15.2% and 11.7% for the IDEAL communication and 14% and 9% for the C-V2X communication at the 75% and 100% market penetration rates, respectively. Finally, the paper demonstrates that the C-V2X communication constraints only affect the performance of the C-EEDR application at the full demand level when the market penetration of the connected vehicles exceeds 25%. This degradation, however, is minimal (less than a 2.5% reduction in fuel savings). [ABSTRACT FROM AUTHOR]

With the continuous enrichment of traffic Internet-of-Things data acquisition methods, more and more spatiotemporal data on road networks is collected in real time by various sensors and multimedia devices. The data-driven deep learning approach can make full use of real-time data from a road network to predict future traffic status. By mining the spatiotemporal relationships between road units, the ability to predict network evolutionary behaviors is improved, which provides a new method of traffic management. There are strong semantic relations between road intersections or road sections in terms of traffic evolution. Modeling the network only from a shallow spatial topological perspective ignores the important intrinsic association of the dynamic network. In this paper, we propose a semantic associative neural network (SANN) for traffic evolution analysis by modeling the propagation effects and similarity patterns between road units. Considering the inadequacy of the fixed adjacent matrix, graph convolution is used to encode the semantic features of a road network and embed them in a bidirectional recurrent neural network for sequence prediction. Finally, the experiments are conducted based on speed data sets to prove the effectiveness of the proposed method. The model achieved a well-predicted accuracy of 95.33% and 84.08% on Pems-Bay and Los Angeles data sets. [ABSTRACT FROM AUTHOR]

Dynamic charging has the potential to overcome the barriers to electric vehicle (EV) adoption by converting road segments into powered lanes (electric roadways or ERs). This paper focuses on examining public acceptance by determining the factors that affect the short-term and long-term intention to purchase an EV and drive on ERs; identifying the clusters of the technology acceptance; and assessing the value of travel time savings (VTTS) for driving on ERs, in general, and for different clusters. A survey was conducted in Los Angeles, California and distributed online, gathering 600 responses. The results showed that respondents' innovativeness, lifestyle and environmental consciousness significantly affect the intention to drive on ERs in the short- and long-run. Public acceptance, in general, seems to be related to charging patterns, safety of commute route, and safety concerns for ERs, among other factors, and depends on the implementation time of the technology. Higher VTTS were found for electrified lanes exclusive for EVs on interstate and arterial roads. People who were classified as positive toward ERs had higher VTTS for ERs followed by those who were neutral and those who were concerned about ERs. This paper can help policymakers and transport operators devise strategies to accelerate EV adoption by appropriately implementing the ER technology. [ABSTRACT FROM AUTHOR]

In February 2021, a winter storm brought snow, ice, and freezing temperatures, which caused severe interruptions in the electric power and water supply systems in Texas and surrounding areas. In this paper, we use survey data to investigate the ways that households adapted and reacted to those outages. The analysis aimed to determine (1) how common different household adaptations were, (2) how adaptations varied with outage and household characteristics, (3) how adaptations tended to occur together, (4) how unhappy households were as a result, (5) how household unhappiness varied with outage and household characteristics, and (6) what concerns influenced the unhappiness level. Results are compared with findings from a study that used an almost identical survey instrument but was based on a larger data set from Los Angeles. Findings from both studies suggest that almost everyone implemented at least one adaptation; most implemented several. They also agreed the most common adaptations were using candles, a flashlight, and/or a lantern; charging the cell phone in the car; purchasing bottled water; and delaying or reducing consumption. Both studies indicate that households experienced varied levels of unhappiness, which were similar for electric power and water interruptions. The reported levels of unhappiness were notably higher in Texas than Los Angeles, however, possibly because the outages had relatively long durations and were recent. Financial, time/effort, health, and stress concerns all were found to have a substantial influence on the extent of unhappiness, in both the Texas and Los Angeles analyses, suggesting that it is critical to consider all of them. Analysis of the Texas study introduced the new finding that repeated service outages during an event is associated with both increased adaptation implementation and greater unhappiness. Analyzing larger data sets from additional events in different locations would be helpful to further understanding of household experiences in service outages. Several practical applications emerge from this work. First, by knowing how people are likely to adapt, officials can better prepare to support their constituents during a crisis. Anticipating the distribution of unhappiness could point infrastructure operators to consider other measures for service quality besides downtime alone, as important as that is. Knowing the differential effects of outages on different populations can improve officials' understanding of social vulnerabilities in their communities, which is needed for planning, education, and outreach. Electric and water outages accompany many kinds of hazard events; the extent to which a local population can adapt, and how officials and infrastructure operators can enhance those adaptations, will be important elements of local community resilience. [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]

Sedimentary phosphate extraction in open-pit operations generates large volumes of waste rock (WR), which are mainly overburdens and interburdens. Traditionally, the WR is mixed and stored on the surface in waste rock piles (WRPs). This paper presents a case study of the Benguerir mine site in Morocco. It investigates the potential valorization of each WR lithology based on the geological and geomechanical properties to reduce their environmental footprint and create added value to "waste." The WR samples (soils and rocks) were collected from drill cores and mining trenches in the Benguerir mine. The geological characterization results using petrographic descriptions indicate the presence of nine phosphate layers and, in addition to the overburdens, eight interburdens. Four types of WR are identified: carbonate, siliceous, marly clay, and phosphate. The geomechanical characterization of soil-like samples showed an average plasticity index (PI) of 50% according to the methylene blue value (MBV) of 7.1, classifying them in the A3–A4 categories as plastic and clayey marl soils. The hard rock samples have excellent mechanical properties in terms of their uniaxial compressive strength (UCS), Los Angeles abrasion value (LA), and micro-Deval value (MD). The average compressive strength is 104 MPa for the flint, 35 MPa for the phosphate flint, 32 MPa for the silexite, 26 MPa for the limestone, 11 MPa for the indurated phosphate, and 8 MPa for the marly limestone. Based on the obtained results, these WRs can be considered as an excellent alternative secondary raw material for use in civil engineering applications, ceramics, and cement industries. [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]

Since the accessory dwelling unit (ADU) has emerged as a policy alternative to increase housing stock and provide affordable options for areas impacted by housing shortages, many local governments recently adopted ADU policies that promote the construction of ADUs. Taking the City of Los Angeles as the study area, this paper examines how the city's ADU ordinance impacts the relationship of the characteristics of the properties and neighborhoods with ADU development by constructing multilevel logistic regression models. The outputs of the models suggest that the ordinance contributes to diversifying the types and locations of the properties and neighborhoods where ADUs are built. The influence of the property characteristics associated with ADU development before the implementation of the ordinance significantly diminished after the ordinance. The outputs also indicate that the ordinance probably attracted ADU developments in the areas with higher accessibility to bus transit. These findings will help planners take appropriate actions and policies that support ADU developments. [ABSTRACT FROM AUTHOR]

Traffic state estimation (TSE), which reconstructs the traffic variables (e.g., speed, flow) on road segments using partially observed data, plays an essential role in intelligent transportation systems. Generally, traffic estimation problems can be divided into two categories: model-driven approaches and data-driven approaches. The model-driven method is commonly used to solve TSE efficiently and calibrate the parameters of these models. The data-driven method requires a large amount of historical observed traffic data in order to improve performance accurately. In order to combine the advantages of model-driven and data-driven methods, this paper proposed a hybrid framework incorporating the traffic flow model into deep learning (TFMDL) modeling that contains both model-driven and data-driven components. This paper focuses on highway TSE with observed data from loop detectors. We build a hybrid cost function to adjust the weights of model-driven and data-driven proportions. We then evaluate the proposed framework using the open-access performance measurement system (PMS) dataset on a corridor of US I-405 in Los Angeles, California. The experimental results show the advantages of the proposed TFMDL approach in performing better than several benchmark models in terms of estimation accuracy and data efficiency. [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]

Random forests are a popular type of machine learning model, which are relatively robust to overfitting, unlike some other machine learning models, and adequately capture non-linear relationships between an outcome of interest and multiple independent variables. There are relatively few adjustable hyperparameters in the standard random forest models, among them the minimum size of the terminal nodes on each tree. The usual stopping rule, as proposed by Breiman, stops tree expansion by limiting the size of the parent nodes, so that a node cannot be split if it has less than a specified number of observations. Recently an alternative stopping criterion has been proposed, stopping tree expansion so that all terminal nodes have at least a minimum number of observations. The present paper proposes three generalisations of this idea, limiting the growth in regression random forests, based on the variance, range, or inter-centile range. The new approaches are applied to diabetes data obtained from the National Health and Nutrition Examination Survey and four other datasets (Tasmanian Abalone data, Boston Housing crime rate data, Los Angeles ozone concentration data, MIT servo data). Empirical analysis presented herein demonstrate that the new stopping rules yield competitive mean square prediction error to standard random forest models. In general, use of the intercentile range statistic to control tree expansion yields much less variation in mean square prediction error, and mean square prediction error is also closer to the optimal. The Fortran code developed is provided in the Supplementary Material. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive framework for life‐cycle carbon emission assessment of steel frame structures in seismic zones, with a particular focus on emerging self‐centering steel structures with reduced residual deformation and enhanced seismic resilience. The proposed framework is illustrated through a life‐cycle embodied carbon (EC) emission study on an office building located at Los Angeles, USA. Different structural bracing systems are considered for comparison, namely, conventional concentrically braced frame (CBF), bucking‐restrained braced frame (BRBF), and self‐centering braced frames (SCBFs). The life cycle assessment (LCA) of EC emissions mainly involves four phases: (1) components manufacturing phase, (2) construction phase, (3) operation and maintenance phase, and (4) EC emissions related to seismic hazard. For the last stage, the engineering demand parameter (EDP) is obtained through incremental dynamic analysis (IDA), and combined with the fragility function and the seismic risk curve to obtain the expected EC emissions related to seismic hazard over the life cycle. Among other findings, the results show that: (1) In the manufacturing process, the EC emissions of the emerging SCBFs are slightly increased (by up to 1.4%) compared with the two other conventional steel frames. (2) During the construction, operation, and maintenance phases, there is no difference in the EC emissions for the different structural systems. (3) The EC emissions related to potential seismic risk are reduced by up to 65.3% when the proposed self‐centering structural system (P‐SCBF) is used. (4) Compared with the CBF, the total EC emission over a 100‐year lifespan can be reduced by up to 14.6% when the P‐SCBF is used. Due to the limited deformation capacity of braces, the EC emissions of CBF and BRBF are more sensitive to increases in the intensity measure (IM). Since a building becomes difficult to repair when the maximum residual inter‐story drift exceeds 0.5%, BRBF and CBF are more susceptible to demolition due to unacceptable residual deformation, leading to higher EC emissions. The EC reduction efficiency of the emerging steel frames become more remarkable with increasing life span. [ABSTRACT FROM AUTHOR]

Background: Community-partnered participatory research (CPPR) is a research approach that supports equitable collaboration of community and academic co-leaders in research and policy. Despite CPPR's 25-year history, infrastructure supporting community members in bidirectional learning has not been formalized. Objective: This paper describes processes and procedures using CPPR to plan conferences to develop community leadership training infrastructure. Methods: We utilized rapid ethnographic analysis to examine conference planning processes for community leadership in CPPR. Community and academic leaders in Los Angeles, New Orleans, and Chicago met weekly over two months to plan, given COVID-19, three Zoom conferences on a leadership training institute for CPPR, with planning for (1) community co-leadership in research and policy; (2) local and national CPPR programs; and (3) models for bidirectional training. Results: The planning process emphasized bidirectional learning for community and academic members for research and services/policy to benefit communities, within a Community Leadership Institute for Equity (C-LIFE) to promote equity and power sharing for community leaders. The planning process identified major themes of framing of C-LIFE conference planning goals, developing the conference structure, promoting equity and diversity, envisioning the future of CPPR, challenges, collaborations, future curriculum ideas for C-LIFE, evaluation and next-steps for Zoom conferences in November 2020. Conclusions: It was feasible to use CPPR to plan Zoom conferences to promote community leadership training across multiple sites. Key planning themes included promoting equity, addressing structural racism, bidirectional learning and integrating community, academic, and policy priorities with community co-leaders as change agents. [ABSTRACT FROM AUTHOR]

With the transportation sector being the largest contributor of greenhouse gas emissions in the United States, states are actively planning the deployment of plug-in electric vehicles (PEVs). Mass adoption of PEVs requires attracting potential buyers living in multi-unit dwellings (MUDs). Given the current low adoption rate of PEVs in MUDs and MUD residents' reliance on public charging, this paper studies whether there is a positive correlation between the number of public Level 2 (L2) chargers and MUD density (measured by total square footage of MUD per capita) across census block groups (CBGs) in LA County. The results show that high MUD-density CBGs and low MUD-density CBGs do not differ much in terms of the number of chargers. The charger-to-PEV-ratio range for MUD residents derived in this paper is below the ideal charger-to-PEV-ratio range in the literature. A direct policy implication is that more charging infrastructure should be made available to MUD residents. This includes public L2 chargers near MUDs, which are discussed in this paper, and onsite MUD charging, which is still at an early stage. • Correlation between EV charger quantity and MUD density in LA County is estimated. • Findings suggest insufficient public Level 2 chargers for the use of MUD EV owners. • MUD charger-to-EV-ratios are computed across census block groups (CBGs). • An MUD charger sufficiency map for LA County is created at CBG level. • This paper concludes that more chargers should be made available to MUD residents. [ABSTRACT FROM AUTHOR]

In this hybrid ethnographic case study, I explore how a cadre of Israeli-American parents in Los Angeles navigate the local Hebrew education landscape to seek linguistic resources for their children. I examine how participants envision Hebrew learning and determine the roles of Jewish, Israeli-serving, and public schools in transmitting Hebrew language, Judaism, and Israeli identity. Participants' perspectives on the vitality and utility of American Jewish institutions mediate their interest in various Hebrew learning offerings, surfacing cues that signal an institution's trustworthiness. This paper expands discourse on Hebrew education by foregrounding Israeli-heritage individuals' concerns regarding diasporic Hebrew learning. [ABSTRACT FROM AUTHOR]

Neoliberal tenets have colored the past half-century of education reform, marked by top-down accountability, market competition, and regimented learning aims. Federal drift and post-pandemic recovery, along with economic uncertainty, will blur policy priorities going forward. Less noticed, local networks of pro-equity activists have come to challenge urban bureaucracies, while advancing fairness, diverse forms of schooling, respectful and rigorous social relations inside schools. This paper examines the case of Los Angeles, where a coalition of Black and Latina leaders, civil rights attorneys, social-justice nonprofits, and pedagogical reformers succeeded to progressively fund schools, extend college-prep courses, and decriminalize discipline. Student achievement, in turn, climbed steadily upward for nearly two decades, 2002 to 2019. This pluralist network of advocates carved-out a third civic terrain, challenging corporate elites and traditional labor leaders. Rooted in humanist ideals, these colorful activists countered the individualistic and competitive values of neoliberal advocates, while motivating lasting institutional change. [ABSTRACT FROM AUTHOR]

The national demand for social justice, racial equality, and criminal justice reform rightfully and painfully continues to sweep the consciousness of this nation. Community colleges were founded on educational excellence, opportunity, and access and should reflect principles of equity, justice, and community. This mission calls upon us, the most egalitarian institutions, to lead by example by making structural and permanent changes to root out the ill effects of racism and bias from our classrooms, curriculum, and workplace. In this paper, we examined equity‐minded leadership, culture, and climate at the Los Angeles Community College District, the nation's largest, and their efforts to transform their institutions, guided by their Framework for Racial Equity and Social Justice. The Framework speaks to the values of the District and directs specific action steps and commitments that will allow the colleges and District to actively build anti‐racist organizational capacity and resilience and move forward towards a more socially and racially‐just academic community. [ABSTRACT FROM AUTHOR]

Urban mobility has been a priority for many cities worldwide due to the high population volume that moves around to meet personal and professional needs. However, transportation modes show inefficiencies that cannot be faced by adopting an approach to maximizing performance. In other words, it is necessary to recognize and measure the disutilities (drawbacks) of the transportation system to create effective public policies to deal with the problem. Therefore, this paper aims to develop a methodology to measure the Total Disutilities of modes of transportation. Mathematical modeling is developed using transport literature, and an application is conducted using data from the 10 most populated American cities. The results show that Dallas, Houston, Chicago, Los Angeles, New York, San Antonio, and Philadelphia presented the lowest Total Disutilities costs (USD) per kilometer. Moreover, the higher disutilities costs occurred in Automobiles in New York and in Bus, Motorcycle, Bicycles or Scooters, and Walking in San Antonio. On the other hand, the lower disutilities costs were established in Automobile in Dallas and in Bus or Train, Motorcycle, Bicycle or Scooter, and Walking in Los Angeles. [ABSTRACT FROM AUTHOR]

The fifth-generation (5G) network is the current emerging technology that meets the increasing need for higher throughputs and greater system capacities. It is expected that 5G technology will enable many new applications and services. Vehicle-to-everything (V2X) communication is an example of an application that is supported by 5G technology and beyond. A V2X communication system allows a vehicle to be connected to an entity, such as a pedestrian, another vehicle, infrastructure, and a network, to provide a robust transportation solution. It uses many models and strategies that are usually based on machine learning (ML) techniques, which require the use of a vehicle dataset. In this paper, a real vehicle dataset is proposed that was generated in the city of Los Angeles (LA). It is called the Vehicle dataset in the city of LA (VehDS-LA). It has 74,170 samples that are located on 15 LA streets and each sample has 4 features. The LA dataset has been opened to allow researchers in V2X and ML fields to use it for academic purposes. The main uses of the VehDS-LA dataset are studies related to 5G networks, vehicle automation, or ML-Based vehicle mobility applications. The proposed dataset overcomes limitations experienced by previous related works. [ABSTRACT FROM AUTHOR]

Recent advances in quantitative tools for examining urban morphology enable the development of morphometrics that can characterize the size, shape, and placement of buildings; the relationships between them; and their association with broader patterns of development. Although these methods have the potential to provide substantial insight into the ways in which neighborhood morphology shapes the socioeconomic and demographic characteristics of neighborhoods and communities, this question is largely unexplored. Using building footprints in five of the ten largest U.S. metropolitan areas (Atlanta, Boston, Chicago, Houston, and Los Angeles) and the open-source R package, foot, we examine how neighborhood morphology differs across U.S. metropolitan areas and across the urban-exurban landscape. Principal components analysis, unsupervised classification (K-means), and Ordinary Least Squares regression analysis are used to develop a morphological typology of neighborhoods and to examine its association with the spatial, socioeconomic, and demographic characteristics of census tracts. Our findings illustrate substantial variation in the morphology of neighborhoods, both across the five metropolitan areas as well as between central cities, suburbs, and the urban fringe within each metropolitan area. We identify five different types of neighborhoods indicative of different stages of development and distributed unevenly across the urban landscape: these include low-density neighborhoods on the urban fringe; mixed use and high-density residential areas in central cities; and uniform residential neighborhoods in suburban cities. Results from regression analysis illustrate that the prevalence of each of these forms is closely associated with variation in socioeconomic and demographic characteristics such as population density, the prevalence of multifamily housing, and income, race/ethnicity, homeownership, and commuting by car. We conclude by discussing the implications of our findings and suggesting avenues for future research on neighborhood morphology, including ways that it might provide insight into issues such as zoning and land use, housing policy, and residential segregation. [ABSTRACT FROM AUTHOR]

An instrument of wealth accumulation and racial segregation in housing markets, the intersections between zoning and labor are often overlooked. Extending theories of space, race, and class, and drawing on historical and archival evidence, I elaborate three ways that American land-use zoning emerged to shape labor markets in the early 20th century: (1) zoning constrained households from engaging in subsistence and direct market activity, acting as a regulatory source of labor commodification; (2) zoning first emerged as a xenophobic tool for regulating labor competition; and (3) zoning introduced racialized boundaries distinguishing formal work from a sphere of economic informality. I illustrate these theoretical-historical propositions with a study of the frontier origins of American land-use zoning laws in late-19th -century Los Angeles. This first and influential approach to residential zoning emerged amid racial dynamics of western settlement and the class politics of a national "free" labor market. I demonstrate how efforts to regulate the settlement and labor practices of poor urban households and Chinese immigrants on in Los Angeles became the direct legal basis for the dichotomous categories of "residential" and "industrial" districts that the city first defended before the U.S. Supreme Court in 1915. By theorizing the intersections of land-use zoning and labor markets, this paper provides a theoretical framework and historical genealogy for future work to consider entanglements of housing and labor politics amid the concurrent flexibilization of work and land use in the present. [ABSTRACT FROM AUTHOR]

This paper shows an agricultural irrigation alternative using a low-cost Internet of Things (IoT) application. This technology allows the automation and optimization of processes by monitoring, processing, and analyzing large volumes of related data, including variables related to the soil (moisture), fertilization, and irrigation, which can be visualized through the internet to enable sustainable and efficient agriculture. The study is centered on the Los Angeles, Biobío, Chile case. The main objective of the prototype is to optimize water consumption for agricultural irrigation by using only the amount that is strictly necessary for each crop by allowing real-time visualization of irrigation status, moisture data, and irrigation times while providing a history of data that can be used for further analysis. [ABSTRACT FROM AUTHOR]

Although earlier research has shown that individual differences on the spectrum of attention deficit hyperactivity disorder (ADHD) are highly heritable, emerging evidence suggests that symptoms are associated with complex interactions between genes and environmental influences. This study investigated whether a genetic predisposition [Note that the term 'genetic predisposition' was used in this manuscript to refer to an estimate based on twin modeling (an individual's score on the latent trait that resembles additive genetic influences) in the particular population being examined.] for the symptom dimensions hyperactivity and inattention determines the extent to which unique-environmental influences explain variability in these symptoms. To this purpose, we analysed a sample drawn from the Twins Early Development Study (TEDS) that consisted of item-level scores of 2168 16-year-old twin pairs who completed both the Strengths and Difficulties Questionnaire (SDQ; Goodman, in J Child Psychol Psychiatry 38:581–586, 1997) and the Strength and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN; Swanson, in Paper presented at the meeting of the American Psychological Association, Los Angeles, 1981) questionnaire. To maximize the psychometric information to measure ADHD symptoms, psychometric analyses were performed to investigate whether the items from the two questionnaires could be combined to form two longer subscales. In the estimation of genotype-environment interaction, we corrected for error variance heterogeneity in the measurement of ADHD symptoms through the application of item response theory (IRT) measurement models. A positive interaction was found for both hyperactivity (e.g., β 1 = 2.20 with 95% highest posterior density interval equal to [1.79;2.65] and effect size equal to 3.00) and inattention (e.g., β 1 = 2.16 with 95% highest posterior density interval equal to [1.56;2.79] and effect size equal to 3.07). These results indicate that unique-environmental influences were more important in creating individual differences in both hyperactivity and inattention for twins with a genetic predisposition for these symptoms than for twins without such a predisposition. [ABSTRACT FROM AUTHOR]

As the amplification of seismic force demands due to higher‐mode effects on tall buildings is increasingly recognized as a design challenge, a number of high‐performance systems have been proposed to limit such effects through combined base shear‐limiting and moment‐limiting dual mechanisms. To better understand the influence of these dual base systems on the overall seismic behavior of tall buildings, this paper presents a study on the seismic response of Multi‐Degree‐of‐Freedom (MDOF) systems incorporating combined base shear‐limiting and moment‐limiting mechanisms. For an MDOF system with a given initial period and base strength level, the base shear‐limiting mechanism is defined by a shear strength factor, an inelastic stiffness parameter, and an energy‐dissipation parameter, while the base moment‐limiting mechanism is defined by a moment strength factor. To determine the influence of these parameters on the overall seismic responses of MDOF structures, a comprehensive parametric study was conducted, and the results were presented and discussed in terms of base displacement and rotation demands, seismic force demand amplification at the base and along the height, peak floor acceleration, peak roof drift, and absorbed energy. The numerical modeling methodology used in the parametric study was validated against 200 small‐scale shaking table tests of a scaled MDOF specimen with a base shear and moment dual‐mechanism system and was used to model MDOF structures that are representative of tall buildings with initial periods ranging from 1.0 to 10 s and having various base‐mechanism properties. The parametric study was then conducted using an ensemble of 20 Ground Motions (GM) scaled to three code‐specified seismic hazard levels for Los Angeles, California. The results of this study can be used to facilitate the design of base shear and moment dual‐mechanism systems for mitigating higher‐mode effects and enhancing the seismic resilience of tall buildings. [ABSTRACT FROM AUTHOR]