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This paper focuses on the development of a virtual training system by applying simulation techniques such as: Full Simulation and Hardware-in-the-Loop (HIL). This virtual reality system is intended to be a teaching and learning tool focused on the area of industrial robotics. For this purpose, mathematical models (kinematic and dynamic) have been considered. These models determine the characteristics and restrictions of the movements of a Scara SR-800 robot. The robot is then virtualized to simulate position and trajectory tasks within virtual environments. The Unity 3D graphic engine (Unity Software Inc., San Francisco, CA, USA), allows the design and development of the training system which is composed of a laboratory environment and an industrial environment. The same that contribute to the visualization and evaluation of the movements of the robot through the proposed control algorithm using the mathematical software (MatLab, manufactured by MathWorks, USA), through shared memories. This software in turn can be linked to an electronic board (Raspberry Pi) for data acquisition through a wireless connection. Finally, the stability and robustness of the implemented controllers are analyzed, as well as the correct operation of the virtual training system. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for prioritising bridge retrofits within a regional road network subject to uncertain seismic hazard, using a technique that accounts for network performance while avoiding the combinatoric computational costs of exhaustive searches. Using global variance-based sensitivity analysis, a probabilistic ranking of bridges is determined according to how much their retrofit statuses influence the expected cost of the road network disruption. Bridges' total-order sensitivity (Sobol') indices are estimated with respect to the expected cost using the hybrid-point Monte Carlo approximation method. A bridge's total-order Sobol' index measures how much its retrofit status influences the variance of the expected cost of the road network performance and accounts for the effect of its interactions with other bridges' retrofit states. For 71 highway bridges in San Francisco, a retrofit strategy based on bridges' total-order Sobol' indices outperforms other heuristic strategies. The proposed method remains computationally tractable while accounting for the probabilistic nature of the seismic hazard, the uniqueness of individual bridges, network effects, and decision-makers' priorities. Because this method leverages existing risk assessment tools and models without imposing further assumptions, it should be extensible to other types of networks under different types of hazards and to other decision variables. [ABSTRACT FROM AUTHOR]

Substantial increases in non-native aquatic vegetation have occurred in the upper San Francisco Estuary over the last 2 decades, largely from the explosive growth of a few submerged and floating aquatic plant species. Some of these species act as ecosystem engineers by creating conditions that favor their further growth and expansion as well as by modifying habitat for other organisms. Over the last decade, numerous studies have investigated patterns of expansion and turn-over of aquatic vegetation species; effects of vegetation on ecosystem health, water quality, and habitat; and effects of particular species or communities on physical processes such as carbon and sediment dynamics. Taking a synthetic approach to evaluate what has been learned over the last few years has shed light on just how significant aquatic plant species and communities are to ecosystems in the Sacramento-San Joaquin Delta. Aquatic vegetation affects every aspect of the physical and biotic environment, acting as ecosystem engineers on the landscape. Furthermore, their effects are constantly changing across space and time, leaving many unanswered questions about the full effects of aquatic vegetation on Delta ecosystems and what future effects may result, as species shift in distribution and new species are introduced. Remaining knowledge gaps underlie our understanding of aquatic macrophyte effects on Delta ecosystems, including their roles and relationships with respect to nutrients and nutrient cycling, evapotranspiration and water budgets, carbon and sediment, and emerging effects on fish species and their habitats. This paper explores our current understanding of submerged and floating aquatic vegetation (SAV and FAV) ecology with respect to major aquatic plant communities, observed patterns of change, interactions between aquatic vegetation and the physical environment, and how these factors affect ecosystem services and disservices within the upper San Francisco Estuary. [ABSTRACT FROM AUTHOR]

Women make up an extraordinary proportion of the individuals in murals worldwide, which can be viewed as a great base for communicating undivided, visual messages of female empowerment, mutual tolerance, and social justice in a world that is unjust, phallogocentric, (still) misogynistic, and strongly prejudicial against women. At the same time, it can be seen as politically opportune and fitting to stress even further the female perspective and send a clear political statement regarding women's rights and issues. In this respect, this paper focuses on the visualization of the politics of tolerance and liberation expressed in the Maestrapeace mural of the renowned education community center building called "Edificio de Mujeres" or the Women's Building in San Francisco, California, which pays tribute to a number of feminist icons from history and fiction, and the names of more than 600 women written in calligraphy, which is a vivid, undivided, and written presentation of the visual politics of female empowerment and tolerance, at the same time advocating for independence, self-determination, gender equality, and social justice. The building's spectacular mural, painted exclusively by seven women artists is a broad-based work of art that presents a culmination of a multicultural, multiethnic, and diverse female world that is built, or more precisely painted on the principles of inclusion, acceptance, and open-mindedness. [ABSTRACT FROM AUTHOR]

In the face of the ever-increasing pressure on climate change, recent decades witnessed booming interests in the integrated energy systems (IES) consisting of intermittent renewable energy and dispatchable power sources, such as reformed gas-fed solid oxide fuel cells (SOFC). However, optimization of system design and operation is challenging due to the system complexity, inevitable couplings, and various constraints. To this end, this paper proposes a comprehensive model to describe integrated energy systems with combined cooling, heating, and power (CCHP). Optimal economic performance is formulated as the objective function. Constraints are derived based on the safety and operation requirements. The problem is solved by developing a two-stage stochastic programming framework to achieve the optimized results in terms of both design and operation. The second stage concerns the operation scheduling given the operation plan and stochastic characteristics, based on which the first stage concerns the design planning to realize the prescribed CCHP capacity. Considering the computation complexity of the second stage, the stochastic characteristics are represented by selected scenarios. And to present the mutual influence of energy demands and climate conditions, the time sequence correlation among energy demands and renewable energy availability is considered in the clustering-based scenario selection technique. To solve the proposed two-stage framework, the real-coded genetic algorithm and mixed integer linear programming method are applied in the first and second stages, respectively. A case study in San Francisco is carried out to verify the effectiveness of the proposed method, providing some intuitive guidance for future IES operation and system planning. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ingeniería de Construcción is the property of Revista Ingenieria de Construccion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Urban Studies (Sage Publications, Ltd.) is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recent studies on international networks have investigated the role of global cities as catalysts of knowledge flows. In this paper, we examine global cities in transnational networks of innovators. To assess the likelihood of scientists and inventors from different cities to take part in international teams, we propose a measure based on 3-hyperedges in the collaboration network constructed from scientific publications and patents. This measure is used to identify the most competitive global cities in the international network of innovators. To this end, we construct a null model based on the hypergeometric ensembles of random graphs. We find that five US cities play a leading role in transnational networks of innovators. Among them, San Francisco stands out as the most globalized city. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Analytical Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we present a simple yet effective rotation averaging pipeline, termed Incremental Rotation Averaging (IRA), which is inspired by the well-developed incremental Structure from Motion (SfM) techniques. Unlike the traditional rotation averaging methods which estimate all the absolute rotations simultaneously and focus on designing either robust loss function or outlier filtering strategy, here the absolute rotations are estimated in an incremental way. Similar to the incremental SfM, our IRA is robust to relative rotation outliers and could achieve accurate rotation averaging results. In addition, we propose several key techniques, such as initial triplet and Next-Best-View selection, Weighted Local/Global Optimization, and Re-Rotation Averaging, to push the rotation averaging results one step further. Ablation studies and comparison experiments on the 1DSfM, Campus, and San Francisco datasets demonstrate the effectiveness of our IRA and its advantages over the state-of-the-art rotation averaging methods in accuracy and robustness. [ABSTRACT FROM AUTHOR]

Bears are a large global community of big and hairy gay, bisexual and queer (GBQ) men. Little sustained empirical scholarship has investigated Bears' lives and communities, and none from within geography. Three geographic lenses are used to demonstrate the significance of a geographic approach to Bears. First, rural and urban imaginaries are entwined with Bear masculinities and ideals of 'real men'. However a geographically specific North American working class rural imaginary is particularly important. Second, the global trajectory of Bear begins in 1980s San Francisco and has since spread worldwide. The idea that Bear is fundamentally an American phenomenon is challenged by evidence of global variation in Bear identities, communities, and spaces. Third, the material and aesthetic production of Bear spaces relates to Bear masculinities and bodies, particularly fat bodies. Regarding more ephemeral Bear events, the 'Bearing' of space (including queer space) may provide a means of understanding these. The paper argues first that geography is crucial for understanding Bears and second that geographers of masculinities, sexualities, and fatness/bodies could productively engage with Bear identities, communities, and spaces. [ABSTRACT FROM AUTHOR]

Following a disaster, residents of a community may be displaced from their damaged homes, leading to expensive and lengthy disruption, with many choosing to move away permanently. Population losses may hinder recovery and exacerbate inequalities across neighborhoods. This study considered household place attachment and identified groups with low place attachment along with expensive and slow postdisaster recovery. We developed a framework to integrate place attachment considerations into housing recovery simulations. We used data from the American Housing Survey to develop housing and neighborhood satisfaction models and identify the neighborhoods with the least-attached residents. A computational simulation framework was used to simulate postearthquake housing recovery for a community and assess expected costs and time frames. We used the triad of low place attachment, high cost, and slow recovery to identify households prone to permanently moving away from their communities. A case study of housing recovery after a hypothetical earthquake near San Francisco demonstrated the application of the methodology. We found that about 10% of the population in some neighborhoods are prone to moving away after a large earthquake. Households with low income, renters, and those in older buildings are most likely to have low place attachment and experience costly and slow recovery. Whereas existing approaches rely on heuristics, the approach and results in this paper provide quantitative means to assess potential population losses and inform efforts to reduce them. The framework to integrate place attachment into housing recovery simulations is versatile and employs publicly available information making it transferable to other communities. [ABSTRACT FROM AUTHOR]

As a special dual-polarization technique, compact polarimetric (CP) synthetic aperture radar (SAR) has already been widely studied and installed on some spaceborne systems due to its superiority to quad-polarization; moreover, quad-pol information can be explored and reconstructed from the CP SAR data. In this paper, a refined model is proposed to estimate the quad-pol information for the CP mode. This model involves CP decomposition, wherein the polarization degree is introduced as the volume scattering model parameter. Moreover, a power-weighted model for the co-polarized coherence coefficient is proposed to avoid the iterative approach in pseudo-quad-pol information reconstruction. Experiments were implemented on the simulated Gaofen-3 and ALOS-2 data collected over San Francisco. Compared with typical reconstruction models, the proposed refined model shows its superiority in estimating the quad-pol information. Furthermore, terrain classification experiments using a complex-value convolutional neural network (CV-CNN) were performed on AIRSAR Flevoland data to validate the reconstruction effectiveness for classification applications. [ABSTRACT FROM AUTHOR]

Most criminal defendants cannot afford to hire an attorney. To provide constitutionally mandated legal services, states commonly use either private court-appointed attorneys or a public defender organization. This paper investigates the relative efficacy of these two modes of indigent defense by comparing outcomes of codefendants assigned to different types of attorneys within the same case. Using data from San Francisco, I show that in multiple defendant cases, public defender assignment is plausibly as good as random. I find that public defenders reduce the probability of any prison sentence by 22% and the length of prison sentences by 10%. [ABSTRACT FROM AUTHOR]

This paper shows the research developed in order to evaluate two resilience indicators, PHRI and Rsys, in the San Francisco de Cunuguachay pressurized irrigation network, specifically in the Yulchirón 2 branch. In this context, the irrigation branch was designed to operate on an on-demand basis and in shifts in order to evaluate the indicators in both operation modes, subjecting the network to unfavourable events. The resilience at the level of pressures and demands of the branch is estimated to remain operational in the different disruptive events, meeting the minimum conditions of the initial design. In this regard, with the implementation of resilience indicators in irrigation networks, it is possible to diagnose the response of the network to changes in its operation. Therefore, the use of indicators allows for obtaining a more reliable and adaptable network to changes in its operation. Consequently, the use of indicators allows for obtaining more reliable and adaptable networks to changes, since the engineer can make the right decisions in the project, improving the planning and management of irrigation networks. [ABSTRACT FROM AUTHOR]

It seems intuitively obvious that firms in supply chains may have more to gain than to lose from learning to cooperate; but it is now more than two decades since Poirier [1999.Advanced Supply Chain Management. San Francisco, CA: Barrett-Koehler] and others called for cooperation in order to capture mutual gains in supply networks and even now ‘cooperation is neither common nor easy’. The simple fact is that not only are supply chains exceptionally complex but so too is the ‘process of cooperating’ – often in the context of antitrust legislation and competition policy. This paper argues that there is a critical need to rethink the principles and processes of cooperation within the broader framework of the competitive behaviour of firms and business strategy. Particularly, it suggests that the relatively recent thinking of Greenwald and Kahn [2005.Competition Demystified A Radically Simplified Approach to Business Strategy. New York, NY: Portfolio, The Penguin Group] in their ‘radically simplified approach to business strategy’ offers sound conceptual insights into cooperation and cooperative strategies for firms not only in markets but also in chains. Furthermore, it notes that the analytical framework for cooperation and cooperative strategies which the authors develop is far removed from the notion of cooperation as ‘commitment and trust and shared thinking’ and from ‘buyer/seller reciprocity’ and ‘collaborative attitudes’ which tend to underwrite much contemporary thinking and research. The paper also argues that the Greenwald and Kahn framework – its single intelligence model of cooperation and cooperative strategies – resonates with real-world relevance, at least for particular supply chains. The paper focuses attention on research into globally significant export coal chains from major east coast Australian ports and in brief case studies finds substantial alignment between concept and practice. [ABSTRACT FROM PUBLISHER]

In this paper, a supervised manifold-learning method is proposed for PolSAR feature extraction and classification. Based on the tensor algebra, the proposed method characterizes each pixel with a local neighbourhood centered at it, thereby combining the spatial and polarimetric information within the image. The inherent spatial information is beneficial to alleviate the influence of speckle noise and improve the stability of the extracted features. In addition, the label information of training samples is utilized in feature extraction, therefore the discriminability of different classes can be well preserved. The tensor discriminative locality alignment (TDLA) method is applied to find the multilinear transformation from the original feature space to the low-dimensional feature space. Based on the extracted features in the low-dimensional space, the SVM classifier is applied to achieve the final classification result. A real PolSAR data set acquired over San Francisco is adopted for performance evaluation. The experimental results show that the proposed method can not only improve the classification accuracy, but also alleviate the influence of speckle noise. In addition, the spatial details can be well preserved, demonstrating the superior performance of the proposed method. [ABSTRACT FROM AUTHOR]

Seventy-five years ago (1945), the United Nations (UN) was founded in San Francisco by 50 nations. There, a small archives unit served to assemble the first records of the organization; this was the first iteration of today's Archives and Records Management Section (ARMS). Throughout its history, the fortunes of the UN Archives have waxed and waned, while its role has continuously evolved. Trying to carve out a place for itself within the largest international organization in the world, its physical and administrative structures have undergone profound changes, as has its mission, number of staff, the type of records it holds and its users. This paper examines significant events in the development of the UN Archives, the challenges it has faced and what may be learned from them. [ABSTRACT FROM AUTHOR]

Ridesourcing services such as Uber are nowadays a common feature within available transport options of many cities around the world (E.g. London & San Francisco). There has been much publicity about the potential impacts of ridesourcing services and how (or if) they should be managed or regulated without an objective understanding of who uses these services and why, as well as its current and future implications for public transport (PT). Ridesourcing is part of a broader tech-driven, mobile app-based sharing phenomenon – the 'sharing economy' – which has disrupted traditional market models and industries, for example, the transport industry, where new players such as Uber have emerged and have quickly become part of the urban transport landscape. Uber has been at the forefront in disrupting the transport sector since its first launch in 2010 (San Francisco, USA). Since its launch, Uber has generated extensive media coverage and debate among policymakers, transport planners and transport authorities on how these services are affecting traditional transport modes such as buses and taxis. However, without objective empirical data – in terms of impacts on trip making characteristics, PT ridership and congestion – policymakers and transport regulators are yet to fully understand the real impacts ridesourcing services are having on the transport network. This paper is part of broader research that aims to provide insights and empirical-based evidence on how Uber services are used (UberX and Uberpool) in London. A comprehensive survey was undertaken using a detailed questionnaire, issued to UberX and Uberpool users in London to gather detailed data on who uses the Uber services, why they use it and what are the trip purposes, in order to understand Uber user demographics and what effects (if any) Uber services are having on PT usage and trip making characteristics in London. The final findings provide important insights on Uber user demographics, trip purposes, types of trips replaced, impact on car ownership and why travellers use Uber services. [ABSTRACT FROM AUTHOR]

Purpose: San Francisco started regulating short-term vacation rentals on rooms/apartments/houses located within city limits in September 2019. The objectives of this conceptual-scenario and regression study are to calculate the present value of the net earnings for a short-term residential rental property located in San Francisco pre-regulation and post-regulation, and consider a financial reason motivating households to list properties as short-term rentals. Design/methodology/approach: A present value approach is used to estimate the value of rental space to tourists prior to the passage of San Francisco's short-term rental regulations compared to post-rental rules. Table 2 shows pre- and post-income scenarios. Price increases of +20, +40 and +60 percent over the initial base rate failed to restore host earnings to pre-registration levels. The present value model calculates the net revenue less net cost associated with listing a property. The regression model uses the number of listings as the dependent variable, and housing prices divided by weekly wages as independent variables. Findings: The short-term rental regulations significantly reduce the profitability associated with short-term tourist stays offered by hosts and listed by online platforms. A host earns pre-regulation income when average daily rents increase by approximately 71.5 percent. It will likely limit income earned by hosts and Airbnb and other shared housing website platforms due to the reduced number of rental days allowed for shared housing caused by ordinances and host enrollment restrictions. The regression model results suggest that homeowners were listing properties for rent to help cover higher priced property purchases. Research limitations/implications: Airbnb, VRBO, Booking.com, and HomeAway are all private companies; this means that financial information is not publicly available. HomeAway, VRBO, and Booking.com are companies owned by Expedia. FlipKey is owned by TripAdvisor. Due to limited public information regarding income statements and property listing trends, regression analysis and descriptive statistics cannot be generated using audited financial statements. Practical implications: Rent control restriction frequently sets the maximum price below the market-clearing price, which results in limited supply but increase in demand for housing. The San Francisco regulations outlaw second-home rentals and seriously limit the availability of other rentals to tourists. FlipKey and HomeAway tend to rent second homes, which San Francisco now bars from being rented for short-term. Social implications: The San Francisco restrictions were enacted with the goal of increasing the supply of rental housing available to permanent residents by restricting short-term rentals. This may have limited short-term benefits to permanent residents, but in the long term lowers income associated with single-family housing which will encourage housing arrangements that would avoid leasing restrictions and lower the number of new houses built. Other cities also have a history of rent controls, and are experiencing housing shortages and at the same time attracting large numbers of tourists. These cities may be motivated to enact similar rental restrictions as those approved in San Francisco. Originality/value: These short-term rental restrictions just started being implemented and enforced. A court decision upheld them. There were media reports outlining the restrictions, but enforcement has just started, so no research papers have been written about San Francisco. Prior research studies have not used net present value analysis to calculate the loss to the host by enacted ordinances restricting tourists' length of stay and have neither tried to explain why homeowners are listing properties for short-term rentals. [ABSTRACT FROM AUTHOR]

Background: Symptom checkers have been widely used during the COVID-19 pandemic to alleviate strain on health systems and offer patients a 24-7 self-service triage option. Although studies suggest that users may positively perceive web-based symptom checkers, no studies have quantified user feedback after use of an electronic health record–integrated COVID-19 symptom checker with self-scheduling functionality. Objective: In this paper, we aimed to understand user experience, user satisfaction, and user-reported alternatives to the use of a COVID-19 symptom checker with self-triage and self-scheduling functionality. Methods: We launched a patient-portal–based self-triage and self-scheduling tool in March 2020 for patients with COVID-19 symptoms, exposures, or questions. We made an optional, anonymous Qualtrics survey available to patients immediately after they completed the symptom checker. Results: Between December 16, 2021, and March 28, 2022, there were 395 unique responses to the survey. Overall, the respondents reported high satisfaction across all demographics, with a median rating of 8 out of 10 and 288/395 (47.6%) of the respondents giving a rating of 9 or 10 out of 10. User satisfaction scores were not associated with any demographic factors. The most common user-reported alternatives had the web-based tool not been available were calling the COVID-19 telephone hotline and sending a patient-portal message to their physician for advice. The ability to schedule a test online was the most important symptom checker feature for the respondents. The most common categories of user feedback were regarding other COVID-19 services (eg, telephone hotline), policies, or procedures, and requesting additional features or functionality. Conclusions: This analysis suggests that COVID-19 symptom checkers with self-triage and self-scheduling functionality may have high overall user satisfaction, regardless of user demographics. By allowing users to self-triage and self-schedule tests and visits, tools such as this may prevent unnecessary calls and messages to clinicians. Individual feedback suggested that the user experience for this type of tool is highly dependent on the organization's operational workflows for COVID-19 testing and care. This study provides insight for the implementation and improvement of COVID-19 symptom checkers to ensure high user satisfaction. [ABSTRACT FROM AUTHOR]

This paper examines the materiality of digitally mapping eviction and landlord geographies, focusing on struggles and contradictions that critical GIS and counter-mapping collectives encounter in attempting to produce data, maps, and tools useful for housing justice organizing. I look at how public restrictions of parcel ownership and eviction data, along with limited accessibility of free and open source mapping software, often instantiate increased reliance upon technocapitalist data and infrastructure. Many of these systems are precipitative of gentrification geographies, thereby at odds with the politics of antidisplacement mapping. Meanwhile, there are a growing number of cartographic labs and companies that produce geospatial data related to evictions and property ownership, but that prioritize data accumulation and scalability over grounded housing justice. By exploring paradoxes within this space, I theorize the conjuncture of datafied property and propertied data landscapes. Homing in on San Francisco landscapes of the Tech Boom 2.0., I draw upon my own experience working with the Anti-Eviction Mapping Project and partner groups. I conclude by looking to housing justice and land rematriation practices based upon grounded relationalities - models that offer emancipatory trajectories for digitally mapping property and dispossession. [ABSTRACT FROM AUTHOR]

In the traditional criminal justice system, an arrest is followed by multiple decision points determining detention, prosecution, guilt, and sentence. Many jurisdictions across the U.S. are exploring alternative programs and approaches that consider individual needs and assessed risks at each decision point. San Francisco County, California, uses post‐filing pretrial diversion programs as alternatives to the traditional criminal justice system for defendants based on factors including social and behavioral needs. In this paper, we estimate the impact of a referral to felony pretrial diversion programs on case outcomes and subsequent criminal justice contact. To address selection bias associated with nonrandom assignment into diversion programs, we exploit the random assignment of felony cases to arraignment judges and use variation among judicial diversion referral rates as an instrument for the diversion referral. We find that a referral to diversion increases the time to disposition in the current case and decreases the probability of a subsequent conviction up to five years following case arraignment. Subgroup analyses find that the benefits of diversion are concentrated among females, those who are under the age of 25, and those facing drug sales charges. [ABSTRACT FROM AUTHOR]

The article offers information on the Jewish communities in California where some are historical, holding a remnant of the Jewish population that resided there decades or a century ago. It discusses a paper titled "The Marine Heritage Project," written in the late 1800s including inspirational references to Judaism at that time in San Francisco and discusses the contribution of Levi Strauss to Judaism in San Francisco.

When facing multiple, competing, objectives such as those encountered in resilience-based design of buildings (e.g., cost reduction versus functionality preservation), there is no single design that can be declared objectively better than the rest. Multiobjective optimization (MOO) methods can instead be used to identify a group of design alternatives that represent the optimal trade-offs between competing objectives. In doing so, however, MOO relies on performance evaluation for a large number of design alternatives, representing a problem for performance-based building seismic design, which typically involves computationally intensive and time-consuming nonlinear analyses of building models subjected to suites of ground motion records. Furthermore, only minimal guidance exists for the post-MOO selection of a final design from the optimal set, further impeding its adoption in design of buildings. This paper addresses these issues through use of simplified structural models and methods applied within a MOO methodology, coupled with a newly adapted post-Pareto pruning approach to narrow down the optimal design set to a manageable-sized group of final design alternatives. The methodology was applied to optimize the design of a 7-story reinforced concrete moment frame office building in San Francisco. [ABSTRACT FROM AUTHOR]

Street attributes are thought to play an important role in influencing pedestrian route choices. Faced with alternatives, pedestrians have been observed to choose faster, safer, more comfortable, more interesting, or more beautiful routes. Literature on pedestrian route choice has provided methods for assessing the likelihood of such options using discrete choice models. However, route choice estimation, which is data intensive and computationally challenging, remains infrequently deployed in planning mobility analysis practice. Even when coefficients from previous studies are available, operationalizing them in foot-traffic predictions has been rare due to uncertainty involved in the transferability of behavioral effects from one context to another, as well as computational challenges of predicting route choice with custom attributes. This paper explores a simpler method of route choice prediction, implemented in the Urban Network Analysis toolbox, which assigns probabilities to available route options based on distance alone. We compare the accuracy of distance-weighted approaches to the more detailed utility-weighted approach using a large dataset of observed GPS pedestrian traces that include numerous trips between same intersections pairs in downtown San Francisco as a benchmark. Even though a utility-weighted model matches observed pedestrian flows most accurately, a distance-weighted model is only marginally inferior, on average. However, shortest-distance and highest-utility route predictions are both significantly inferior to the utility-weighted and distance-weighted sample-enumeration methods. Our findings suggest that simplified assumptions can be used to predict pedestrian flow in practice with existing software, opening pedestrian flow predictions to a wider range of planning and transportation applications. [ABSTRACT FROM AUTHOR]

Classical epidemiological models assume mass action. However, this assumption is violated when interactions are not random. With the recent COVID-19 pandemic, and resulting shelter in place social distancing directives, mass action models must be modified to account for limited social interactions. In this paper we apply a pairwise network model with moment closure to study the early transmission of COVID-19 in New York and San Francisco and to investigate the factors determining the severity and duration of outbreak in these two cities. In particular, we consider the role of population density, transmission rates and social distancing on the disease dynamics and outcomes. Sensitivity analysis shows that there is a strongly negative correlation between the clustering coefficient in the pairwise model and the basic reproduction number and the effective reproduction number. The shelter in place policy makes the clustering coefficient increase thereby reducing the basic reproduction number and the effective reproduction number. By switching population densities in New York and San Francisco we demonstrate how the outbreak would progress if New York had the same density as San Francisco and vice-versa. The results underscore the crucial role that population density has in the epidemic outcomes. We also show that under the assumption of no further changes in policy or transmission dynamics not lifting the shelter in place policy would have little effect on final outbreak size in New York, but would reduce the final size in San Francisco by 97%. [ABSTRACT FROM AUTHOR]

In 2017, San Francisco (SF) implemented Law Enforcement Assisted Diversion (LEAD), a program Beckett described as harm reduction policing. Through a process and outcome evaluation of LEAD SF, this paper demonstrates the positive impacts of harm reduction policing, on those who use drugs and/or engage in sex work. When law enforcement officers used their discretion to divert individuals into LEAD rather than arrest, those individuals had significantly fewer felony and misdemeanor arrests and felony cases, in comparison to a propensity score matched group. The focus group and interview data describe that the collaboration, the warm handoff, and LEAD's harm reduction principles were mechanisms of success. However, obtaining officer buy-in was a key challenge. Despite that obstacle, LEAD SF's harm reduction policing reduces offending, improves the wellbeing of people who use drugs and engage in sex work, and allows the police to carry out their mandate to protect and serve. [ABSTRACT FROM AUTHOR]

The provision of mass urban transit is frequently tied to agendas of social justice and equity. Yet there are persistent challenges to locating justice within urban mobility regimes. Drawing on two cases of transit activism – Free Transit Toronto and Black Lives Matter in the San Francisco Bay Area – this paper identifies three limitations to transport justice scholarship and practice, namely the theorization of mobility, space, and justice. These activist struggles demonstrate that justice cannot be adequately defined through an abstract accounting of how harms and benefits are distributed, but also concerns the contextual and conflictual processes of producing space and subjects. [ABSTRACT FROM AUTHOR]

The use of SF6 gas decomposition components for the fault diagnosis of gas-insulated equipment (GIE) has received widespread attention and been extensively adopted by the power industry. However, the present focus is mainly on the use of a component type or absolute content for generating qualitative judgments on the existence of a fault, and the practical diagnosis method for field diagnosis is extremely lacking. In this paper, ten-year fault data were collected and analyzed. Decomposition components were extracted and combined, based on the decomposition characteristics of SF6, and enhancement factors were given to three component characteristic quantities using fuzzy C-means clustering algorithm. The component characteristic quantities that characterized the high-energy discharge fault, partial discharge, and partial over-thermal fault of the device were extracted: % (SOF2+SO2), % (9SO2F2), and % (5CO2). With adoption of these characteristic quantities as the coordinate axes of the triangle coordinate system, a triangle fault diagnosis method for field diagnosis of SF6 GIE was constructed. The diagnosis method was validated by a large number of experimental data and field failure data, and 128 of the 150 experimental samples were correctly recognized. Moreover, the test conditions did not considerably affect the diagnostic results of the method. This technique can provide a simple and effective field diagnostics technology for the power industry. [ABSTRACT FROM AUTHOR]

Surface charging of spacers is one of the main factors restricting the industrialization of DC gas insulated lines (GILs). The effects of ion mobility, gas pressure and temperature on surface charge behavior are important issues to be clarified. In this paper, a selection method of ion mobility is reviewed and reconsidered. A multiphysics-coupled model considering ion mobility, species of ions, temperature, and gas pressure is investigated. A mathematical model of ion mobility under low and high electric fields is presented and the critical electric field strengths are calculated, based on the current density vs electric field strength. The results show that the two critical electric field strength have different characteristics with gas pressure and temperature. The ion mobility in SF 6 gas has a completely different calculation model in high electric field and low electric field, and these two ion mobilities are equal only at a specific temperature and gas pressure. This paper can provide a reference for the selection of ion mobility in DC GILs under conditions of temperature and pressure. [ABSTRACT FROM AUTHOR]

To model the responses of electromagnetic surveys for geophysical subsurface sensing, a mixed total field/scattered field-based discontinuous Galerkin frequency-domain (TF/SF DGFD) method is proposed in this paper. The proposed TF/SF DGFD method is implemented at a subdomain level based on the domain decomposition technique. Different subdomains can employ either the TF DGFD framework or the SF DGFD framework, which are then coupled through the Riemann transmission condition. To balance the computation efficiency and accuracy for practical applications, the proposed method prefers to using the SF DGFD framework for subdomains with sources and using the TF DGFD framework for the remaining subdomains. At the interfaces between total field and scattered field subdomains, the Riemann transmission condition is slightly modified by incorporating the background fields due to the physically imposed sources in the background media. In this way, the proposed method only requires surface integrals of the background fields as extra overhead instead of elementwise integration of the scattering objects for the purely scattered field-based method, which can improve the computational efficiency. Also, it is more accurate than the purely TF DGFD method given the same mesh. Numerical examples are studied to examine the performance of the proposed method, which is proven to have better accuracy than the TF DGFD method. The TF/SF DGFD method will facilitate modeling of electromagnetic surveys under complicated geophysical environments for subsurface sensing. [ABSTRACT FROM AUTHOR]

In this paper additive models with p-order autoregressive conditional symmetric errors based on penalized regression splines are proposed for modeling trend and seasonality in time series. The aim with this kind of approach is try to model the autocorrelation and seasonality properly to assess the existence of a significant trend. A backfitting iterative process jointly with a quasi-Newton algorithm are developed for estimating the additive components, the dispersion parameter and the autocorrelation coefficients. The effective degrees of freedom concerning the fitting are derived from an appropriate smoother. Inferential results and selection model procedures are proposed as well as some diagnostic methods, such as residual analysis based on the conditional quantile residual and sensitivity studies based on the local influence approach. Simulations studies are performed to assess the large sample behavior of the maximum penalized likelihood estimators. Finally, the methodology is applied for modeling the daily average temperature of San Francisco city from January 1995 to April 2020. [ABSTRACT FROM AUTHOR]

For a new corporate headquarters in San Francisco's Mission Bay district, SHoP Architects designed a semi‐conditioned atrium space inside the external glazed envelope known as "the commons." To ventilate this space, the facade contractor developed a transparent, steel‐framed glazing system featuring motorized bi‐fold units. These operable window units, 3.0 m wide by 4.4 m tall, are computer‐controlled in conjunction with operable skylights to maintain comfortable temperatures in the atrium and significantly reduce the need for mechanical ventilation. This paper describes the engineering and design development of this dynamic facade. A number of kinematic options were studied, resulting in the final configuration whereby window operation is guided in the visible upper and lower rails. In the upper rails, the self‐weight is resolved via newly developed double vertical hybrid rollers. The necessary lateral stability is provided by scissor arms mounted on both sides at the top and bottom, which prevent the window from moving sideways on one side over the entire opening stroke. The windows are operated via two of the currently largest chain drives on the market (lift/pull force 1500 N). In addition, a linear locking drive moves a push rod with three double claws, which additionally keep the window in the "closed" position. The chain drives are synchronized and internally controlled with the linear locking drive. All components are integrated and concealed in the central mullion. A complete opening takes approximately 155 seconds. Safety strips integrated circumferentially in the frame protect the device, while closing, from objects that are accidentally left in the window rebate and will switch off the device automatically. The units are constructed according to the European Machinery Directive 2006/42/EG, and a risk analysis was carried out in advance. The drive technology and all electrical components are UL‐certified. [ABSTRACT FROM AUTHOR]

This paper explores the material and representational politics that are catalyzed by Anti-Mass , an installation made by Cornelia Parker from the remains of a burned Black church located in the deYoung Museum in San Francisco, California. Applying an attention to religious materiality (the interpretive circuit between words, bodies, and things), semiotic ideology (an approach that explores competing and ascendant meanings), and an ethnographic sensibility, I argue that three hermeneutic fields coalesced around Anti-Mass in the museum. The first interpretation is a Killmonger hermeneutic that read Anti-Mass as a profaning of Black sacred matter. The second is an Anti- hermeneutic , which sought to preserve representational openness prized by abstract expressionism. The third is a resurrection hermeneutic , which reflected popular notions of US multicultural transcendence and a more melancholic meditation on anti-Black religious violence expressed by adjacent artwork and embodied by the ethnographer herself via a lump corpothetics. [ABSTRACT FROM AUTHOR]

Provides information on the annual meeting of pediatric radiology society to be held at San Francisco Fairmont Hotel on May 5-10, 2005. Format changes for the presentation of papers and workshop; Theme of the conference; List of schedule of activities.

During the early Gold Rush period, San Francisco’s seaport was hastily constructed on a site that was ill-fit for its purpose. Challenges included firstly the need for incoming vessels to be unloaded by hand onto smaller vessels in order to bring goods ashore and, secondly, a series of six great fires over eighteen months, from December 1849 to mid-1851. The fires, which repeatedly burned San Francisco’s seaport to the ground, staggered the confidence of the business community and gave rise to a “moody conviction” that the city was doomed. These developmental challenges provide the context within which seaport workers living in San Francisco from Sydney were constituted as a problem. These migrants were attacked on account of the important roles they assumed in the operation of the seaport and were accused of starting San Francisco’s fires to create opportunities for theft and plunder. A strategic series of attacks orchestrated by the Committee of Vigilance saw these migrants pushed out of the valuable waterfront real estate they had occupied. These attacks also formed part of a broader postfire redevelopment project. This attempt to tease out the social history of San Francisco’s built environment contributes to a spatial turn in historical studies that emphasizes the need to regard space as well as time as a critical dimension of social life. [ABSTRACT FROM AUTHOR]

Crime detection is one of the most important research applications in machine learning. Identifying and reducing crime rates is crucial to developing a healthy society. Big Data techniques are applied to collect and analyse data: determine the required features and prime attributes that cause the emergence of crime hotspots. The traditional crime detection and machine learning-based algorithms lack the ability to generate key prime attributes from the crime dataset, hence most often fail to predict crime patterns successfully. This paper is aimed at extracting the prime attributes such as time zones, crime probability, and crime hotspots and performing vulnerability analysis to increase the accuracy of the subject machine learning algorithm. We implemented our proposed methodology using two standard datasets. Results show that the proposed feature generation method increased the performance of machine learning models. The highest accuracy of 97.5% was obtained when the proposed methodology was applied to the Naïve Bayes algorithm while analysing the San Francisco dataset. [ABSTRACT FROM AUTHOR]