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Background: Active commuting to school can be a meaningful contributor to overall physical activity in children. To inform better micro-level urban design near schools that can support active commuting to school, there is a need for measures that capture these elements. This paper describes the adaptation of an observational instrument for use in assessing micro-scale environments around urban elementary schools in the United States. Methods: The Micro-scale Audit of Pedestrian Streetscapes for Safe Routes to School (MAPS-SRTS) was developed from existing audit instruments not designed for school travel environments and modifications for the MAPS-SRTS instrument include the structure of the audit tool sections, the content, the observation route, and addition of new subscales. Subscales were analyzed for inter-rater reliability in a sample of 36 schools in Austin, TX. To assess reliability for each subscale, one-way random effects single-measure intraclass correlation coefficients (ICC) were used. Results: Compared to the 30 original subscales, the adapted MAPS-SRTS included 26 (86.6%) subscales with revised scoring algorithms. Most MAPS-SRTS subscales had acceptable inter-rater reliability, with an ICC of 0.97 for the revised audit tool. Conclusions: The MAPS-SRTS audit tool is a reliable instrument for measuring the school travel environment for research and evaluation purposes, such as assessing human-scale determinants of active commuting to school behavior and documenting built environment changes from infrastructure interventions. [ABSTRACT FROM AUTHOR]

Fifty years ago, animal models studied in the lab were highly diverse, and biological insights were derived from experiments in many species. However, the pursuit of mechanistic explanations in organismal biology led to a shift in the species most commonly studied. The advent of genetic manipulations and economies of scale promoted the consolidation of research into fewer species (eg, Drosophila melanogaster, Mus musculus, Danio rerio, Caenorhabditis elegans). As a result, the tremendous variety of evolutionary adaptations across species provided insights into ultimate causes of evolution, but their proximate mechanisms have been understudied in recent decades. Within the last decade, developments in genome modifications have enabled functional genetic studies in a wide variety of species. This special issue combines papers derived from a symposium organized at the Society for Integrative and Comparative Biology conference in January 2023 in Austin, Texas. The symposium entitled "Neuroethology in the age of gene editing: New tools and novel insights into the molecular and neural basis of behavior" was convened to catalyze the transfer of knowledge and skills from researchers who have applied genome modification technologies in new model organisms to scientists who would like to bring these approaches to their own research programs. We highlight this work here, and suggest how the future of biological knowledge will be informed by these powerful experiments. [ABSTRACT FROM AUTHOR]

Traffic accidents directly influence public safety and economic development; thus, the prevention of traffic accidents is of great importance in urban transportation. The accurate prediction of traffic accidents can assist traffic departments to better control and prevent accidents. Thus, this paper proposes a deep learning method named attention-based residual dilated network (ARDN), to extract essential information from multi-source datasets and enhance accident prediction accuracy. The method utilizes bidirectional long short-term memory to model sequential information and incorporates an attention mechanism to recalibrate weights. Furthermore, a dilated residual layer is adopted to capture long term information effectively. Feature encoding is also employed to incorporate natural language descriptions and point-of-interest data. Experimental evaluations of datasets collected from Austin and Houston demonstrate that ARDN outperforms a range of machine learning methods, such as logistic regression, gradient boosting, Xgboost, and deep learning methods. The ablation experiments further confirm the indispensability of each component in the proposed method. [ABSTRACT FROM AUTHOR]

Computer simulation models are a useful tool in planning, enabling reliable yet affordable what-if scenario analysis. Many simulation models have been proposed and used for urban planning and management. Still, there are a few modeling options available for the purpose of evaluating the effects of various stormwater control measures (SCM), including LID (low-impact development) controls (green roof, rain garden, porous pavement, rainwater harvesting), upland off-line controls (sedimentation, filtration, retention–irrigation) and online controls (detention, wet pond). We explored the utility and potential of the Soil and Water Assessment Tool (SWAT) as a modeling tool for urban stormwater planning and management. This study demonstrates how the hydrologic modeling strategies of SWAT and recent enhancements could help to develop efficient measures for solving urban stormwater issues. The case studies presented in this paper focus on urban watersheds in the City of Austin (COA), TX, where rapid urbanization and population growth have put pressure on the urban stormwater system. Using the enhanced SWAT, COA developed a framework to assess the impacts on erosion, flooding, and aquatic life due to changes in runoff characteristics associated with land use changes. Five catchments in Austin were modeled to test the validity of the SWAT enhancements and the analytical framework. These case studies demonstrate the efficacy of using SWAT and the COA framework to evaluate the impacts of changes in hydrology and the effects of different regulatory schemes. [ABSTRACT FROM AUTHOR]

This paper seeks to demonstrate the impact of the gig economy on product quality in seemingly unrelated local industries through the labor market. Our empirical context is the quality of service for restaurants in the city of Austin, and we examine how they were impacted by the exogenous exit and reentry of rideshare platforms, Uber and Lyft, because of regulatory changes. We leverage these exogenous shocks and combine them with sentiment-analyzed data from Yelp reviews that capture how customers assess the quality of service at each restaurant. We show that, compared with control cities, customers in Austin become more negative about service quality when Uber and Lyft are present in the city. Additionally, we use rich data on employee turnover and wages to demonstrate that service staff turnover increases in Austin when Uber and Lyft are present compared with the control cities. We also conduct several additional studies and robustness checks that are all congruent with our hypothesis that Uber and Lyft lower the quality of service in Austin restaurants by raising their staff turnover. Together, these results suggest significant ramifications of the gig economy on the broader industries through the labor market. This paper was This paper was accepted by Matt Shum, marketing. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4481. [ABSTRACT FROM AUTHOR]

This section offers news briefs related to Southwestern history. The first Save Texas History Symposium will be held at the Texas General Land Office in Austin, Texas on November 6, 2010. A collection of papers relating to the career of Mirabeau B. Lamar has been accessioned by the Archives Division of the Texas State Library. A visual chronicle of the history of the West Texas A&M University in Canyon is presented at the Panhandle Plains Historical Museum.

Background: Respiratory diseases are the second most common cause of illnesses in horses, their etiology can be viral, bacterial, immune-mediated, or mechanical (Racklyeft and Love DN, Aust Vet J 78:549–59, 2000; Austin et al., J Am Vet Med Assoc 207:325–328, 1995; Arroyo et al., J Vet Intern Med 31:894–900, 2017). Klebsiella variicola is a Gram-negative bacterium that was initially identified as an endophyte in soil and plants such as bananas, rice, sugar cane and maize but recent studies have identified this microorganism as an emerging pathogen in humans (Rodríguez-Medina et al., Emerg Microbes Infect 8:973–988, 2019; Fontana et al., J Clin Microbiol 57:e00825–18, 2019; Rosenblueth et al., Syst Appl Microbiol 27:27–35, 2004). This paper describes, for the first time to our knowledge, the isolation of K. variicola from pleural effusion in a male adult horse. Case presentation: 17-years Italian Saddle Horse with respiratory distress and fever was admitted to the Veterinary Teaching Hospital of the Department of Veterinary Medical Sciences, University of Bologna. At home, the patient had undergone antibiotic therapy without clinical improvement. Vital signs on admission revealed an increased respiratory rate, tachycardia, pyrexia and weight loss. The animal was submitted for collateral examination including thoracic radiology and ultrasound and thoracoscopy that showed bilateral pleural effusion associated with multifocal pulmonary atelectasis. During the thoracoscopic examination, that confirmed the presence of a seropurulent pleural effusion, a sample of pleural fluid was collected and Gram-negative bacteria were isolated and subjected to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) that allowed the identification of K. variicola. The isolate was sensitive to amikacin, cefazolin, enrofloxacin, marbofloxacin, tetracycline, and trimethoprim-sulfamethoxazole;the horse was treated with Oxytetracycline and amikacin. Despite a general health improvement of the subject, the pleural effusion did not resolve after treatment. Conclusions: This paper describes, for the first time, the isolation of K. variicola in a horse with respiratory disease. The misidentification between K. variicola and K. pneumoniae has caused unawareness about significant aspects of this bacterial species. In fact, even though in animals the role of this bacterium is not clear, in humans it has been recognized as an emerging pathogen. The use of new methods for bacterial identification will probably lead to the isolation of a greater number of strains which will have to be studied to acquire knowledge that will be useful to clarify the clinical importance and relevance of K. variicola also in animals. [ABSTRACT FROM AUTHOR]

This paper illustrates the performative nature of participatory video (PV), drawing on JL Austin's well-known work on speech acts, utterances, and performative sentences, as well as Butler's reworking and application of the notion of performativity. During recent research I used PV as a method. Sub-Saharan African refugee research participants who had not known each other before the PV project negotiated issues to be filmed and made a short film together, creating a small community where none existed before, who are taking steps to organize collective action. The emergence of this new community in and through the making of the film during the fieldwork illustrates the performativity of PV, what is accomplished in and through its making. This performativity works not only through people who take part in creating a video, distributing the video, and watching the video, but also may have effects on people who have never seen the given video, as they are in a landscape and embedded in social relations affected by people who took part in it or saw it. PV is thus both a way of gathering data to learn about the world, and it also is involved in changing it, bringing forth new relationships and new ways of being. [ABSTRACT FROM AUTHOR]

Information about several papers discussed at the symposium "Stress, Condition, and Ornamentation" part of the 2014 at the Society of Integrative and Comparative Biology held from January 3-7, 2014 at Austin, Texas is presented. Topics discussed include the relationship between stressors and ornamentation where in signalling molecules such as corticosterone and cortisol has a vital role, effect of environmental stress, and the contribution of evolution and function of ornaments and armaments.

Introduction New Orleans and Austin are two cities that are quite different in many ways. While one is known for its poverty, disparity, and crime, the other is famous for its young, vibrant, and fun environment. While one is proud of its past, the other is excited about its future. However, the history of these two cities in terms of developing a learning health system information infrastructure does not follow the same narrative. Methods One important aspect of any learning health system is availability of information to allow for the learning to be systematic, ongoing, and data-driven. This requires the capability to share data across the usually fragmented health systems. This paper uses a comparative case study approach based on personal experiences and key informant interviews to trace the development of information sharing infrastructure in the two cities. The study uses examples to demonstrate learning health system activities facilitated by these information infrastructure capabilities. Results The analysis identified some key factors that may explain the differences in approach and outcomes in the two cities. New Orleans adopted a more comprehensive approach than Austin in envisioning the needs of the community. The study finds that development of a learning health system infrastructure is assisted by working with champions in the community, by not being constrained by legacy systems, and by considering data sharing as a health systems transformation effort rather than simply a technology solution. Other unique factors that particularly helped New Orleans to build a more forward-looking infrastructure were the role of a backbone organization in the community and a broader collaboration among medical, social, behavioral, and public health service providers. Conclusions Both Austin and New Orleans have many health systems innovations underway. However, like many other communities in the United States, they have a long way to go to become learning health systems, a goal that cannot be achieved without a robust, shared information infrastructure. [ABSTRACT FROM AUTHOR]

Information about the 19th International Conference on Microelectronic Test Structures (ICMTS) held in Austin, Texas in 2006 is presented. There were over 40 regular papers presented in nine sessions at the meeting. The papers feature work directed to furthering the understanding of systematic and parametric yield loss characteristics of complementary metal oxide semiconductors (CMOS) to microelectromechanical systems (MEMS).

Jose L. Walteros and Austin Buchanan This paper focuses on providing a rigorous, worst-case explanation for why the maximum clique problem is apparently so easy in naturally occurring graphs, despite its intractability in the worst case. To this day, there exist unsolved benchmark instances with just 1,000 vertices. In contrast, real-life instances appear to be much easier. Indeed, relatively simple algorithms can solve instances with millions of vertices in just a few seconds. However, these algorithms lack any worst-case guarantees on their running time. Exactly why these real-life instances are so easy has been somewhat of a puzzle. This paper shows that maximum clique can be solved in time polynomial in the size of the graph, but exponential in a graph invariant that we denote by. Typically, is very small for real-life graphs, being 0, 1 or 2 in over half of the instances coming from commonly used testbeds. In these and other cases where can be thought of as a small constant, our algorithm runs in time. To this day, the maximum clique problem remains a computationally challenging problem. Indeed, despite researchers' best efforts, there exist unsolved benchmark instances with 1,000 vertices. However, relatively simple algorithms solve real-life instances with millions of vertices in a few seconds. Why is this the case? Why is the problem apparently so easy in many naturally occurring networks? In this paper, we provide an explanation. First, we observe that the graph's clique number ω is very near to the graph's degeneracy d in most real-life instances. This observation motivates a main contribution of this paper, which is an algorithm for the maximum clique problem that runs in time polynomial in the size of the graph, but exponential in the gap g ≔ (d + 1) − ω between the clique number ω and its degeneracy-based upper bound d+1. When this gap g can be treated as a constant, as is often the case for real-life graphs, the proposed algorithm runs in time O (d m) = O (m 1.5 ) . This provides a rigorous explanation for the apparent easiness of these instances despite the intractability of the problem in the worst case. Further, our implementation of the proposed algorithm is actually practical—competitive with the best approaches from the literature. [ABSTRACT FROM AUTHOR]

The study of Buhari's statements on "jailing of more thieves," "rule of law should be subjected to national interest," and "being fair in federal appointments" seem not to have been approached from speech act perspective. As such, this paper analyses the locutionary acts, illocutionary acts, and the perlocutionary effects of Buhari's statements on the above subject matters. The data were obtained from the online version of Nigerian Dailies. Austin's speech acts theory serves as the theoretical framework for data analysis. The findings of the study reveal that Buhari's statement on "jailing of more thieves" is based on fact that he has already jailed some high-profile Nigerians since he was elected as the President of Nigeria. The findings of the study reveal the locutionary and illocutionary acts of Buhari's statements. The study also shows how Buhari's statements abided by or flouted Austinian felicity conditions. The perlocutionary effects of the statements were also identified. [ABSTRACT FROM AUTHOR]

Traditional feed composition tables have been a useful tool in the field of animal nutrition throughout the last 70 yr. The objective of this paper is to discuss the challenges and opportunities associated with creating large feed ingredient composition tables. This manuscript will focus on three topics discussed during the National Animal Nutrition Program (NANP) Symposium in ruminant and nonruminant nutrition carried out at the American Society of Animal Science Annual Meeting in Austin, TX, on July 11, 2019, namely: 1) Using large datasets in feed composition tables and the importance of standard deviation in nutrient composition as well as different methods to obtain accurate standard deviation values, 2) Discussing the importance of fiber in animal nutrition and the evaluation of different methods to estimate fiber content of feeds, and 3) Description of novel feed sources, such as insects, algae, and single-cell protein, and challenges associated with the inclusion of such feeds in feed composition tables. Development of feed composition tables presents important challenges. For instance, large datasets provided by different sources tend to have errors and misclassifications. In addition, data are in different file formats, data structures, and feed classifications. Managing such large databases requires computers with high processing power and software that are also able to run automated procedures to consolidate files, to screen out outlying observations, and to detect misclassified records. Complex algorithms are necessary to identify misclassified samples and outliers aimed to obtain accurate nutrient composition values. Fiber is an important nutrient for both monogastrics and ruminants. Currently, there are several methods available to estimate the fiber content of feeds. However, many of them do not estimate fiber accurately. Total dietary fiber should be used as the standard method to estimate fiber concentrations in feeds. Finally, novel feed sources are a viable option to replace traditional feed sources from a nutritional perspective, but the large variation in nutrient composition among batches makes it difficult to provide reliable nutrient information to be tabulated. Further communication and cooperation among different stakeholders in the animal industry are required to produce reliable data on the nutrient composition to be published in feed composition tables. [ABSTRACT FROM AUTHOR]

Copyright of Enthymema is the property of Enthymema, International Journal of Literary Criticism, Literary Theory & Philosophy of Literature 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 2012, the Austin Independent School District reported that over 60 percent of its students identified as Hispanic. However, the number of theatrical offerings for children including Latino stories or Latino/a characters on Austin stages is staggeringly disproportionate to the number of Latino children living in the community. Mariachi Girl is a new bilingual Spanish/English musical for child audiences. This paper articulates and analyzes research findings from surveys collected from children, teachers, and care givers who saw the production. The paper introduces the term culturally responsive artistry and offers new perspectives and suggestions on how arts institutions and theater educators can form lasting relationships with minority communities. [ABSTRACT FROM AUTHOR]

Accurate shared micromobility demand predictions are essential for transportation planning and management. Although deep learning methods provide robust mechanisms to tackle demand forecasting challenges, current models based on graph neural networks suffer from limited scalability and high computational cost. There is both a need and significant potential to enhance the accuracy and efficiency of existing shared micromobility demand forecasting models. To fill these research gaps, this paper proposes a deep learning model named Interactive Convolutional Network (ICN) to forecast spatiotemporal travel demand for shared micromobility. The proposed model develops a novel channel dilation method by utilizing multi-dimensional spatial information (i.e., demographics, functionality, and transportation supply) based on travel behavior knowledge for building the deep learning model. We use the convolution operation to process the dilated tensor to simultaneously capture temporal and spatial dependencies. Based on a binary-tree-structured architecture and interactive convolution, the ICN model extracts features at different temporal resolutions and then generates predictions using a fully-connected layer. We conducted two practical case studies from Chicago, IL, and Austin, TX to test the proposed model. The results show that the ICN model significantly outperforms all benchmark models. The model predictions have the potential to assist micromobility operators in developing efficient vehicle rebalancing strategies, while also providing cities with guidance on enhancing the management of their shared micromobility system. [ABSTRACT FROM AUTHOR]

The article discusses various research papers on acoustics presented at the 146th Meeting of the Acoustical Society of America held in Austin, Texas on November 10-14, 2003 including "Application of multibeam sonar in marine ecology and fisheries research: New fields and limitations," by Francois M. Gerlotto and colleagues, "In situ fish school studies enabled by multi-beam sonar," by Ole Arve Misund and "Three-dimensional acoustic backscatter measurements in the water column with hull-mounted and towed multibeam echo-sounders," by Christian de Moustier.

The present study aims to identify the impact of the tone of risk reporting narratives on company market value. The paper uses a sample of 34 Portuguese non-finance companies with shares traded at the Euronext Lisbon stock exchange market. The paper conducts an automated content analysis of the risk reporting narratives included in the risk and risk management sections of the annual reports for 2018 by using the software DICTION 7 (Digitext, Inc., Austin, TX, USA) to retrieve the speech tone. Main findings indicate that the tone category "activity" is associated negatively with the company's market value. This result shows that investors misprice risk information that incorporates traces of overconfidence, narcissistic self-confidence and heroic leadership. The present study extends prior literature by analyzing the economic incentives of the tone of risk reporting narratives, not yet studied. Findings are both relevant to investors to support their decision-making processes and managers to strategically manage their risk communication tactics and benefit from the advantages emanated from them. Limitations related to the research setting do not undermine the generalization of findings because the automated algorithm provided by DICTION assures the content analysis's reliability. The sample used corresponds to the population of the Portuguese non-finance listed companies. [ABSTRACT FROM AUTHOR]

Understanding and forecasting complex freight mode choice behavior under various industry, policy, and technology contexts is essential for freight planning and policymaking. Numerous models have been developed to provide insights into freight mode selection; most use discrete choice models such as multinomial logit (MNL) models. However, logit models often rely on linear specifications of independent variables despite potential nonlinear relationships in the data. A common challenge for researchers is the absence of a heuristic and efficient method to discern and define these complex relationships in logit model specifications. This often results in models that might be deficient in both predictive power and interpretability. To bridge this gap, we develop an MNL model for freight mode choice using the insights from machine learning (ML) models. ML models can better capture the nonlinear nature of many decision-making processes, and recent advances in "explainable AI" have greatly improved their interpretability. We showcase how interpretable ML methods help enhance the performance of MNL models and deepen our understanding of freight mode choice. Specifically, we apply SHapley Additive exPlanations (SHAP) to identify influential features and complex relationships to improve the MNL model's performance. We evaluate this approach through a case study for Austin, Texas, where SHAP results reveal multiple important nonlinear relationships. Incorporating those relationships into MNL model specifications improves the interpretability and accuracy of the MNL model. Findings from this study can be used to guide freight planning and inform policymakers about how key factors affect freight decision-making. [ABSTRACT FROM AUTHOR]

This study explores the socioeconomic disparities observed in the early adoption of Electric Vehicles (EVs) in the United States. A multiagent deep reinforcement learning-based policy simulator was developed to address the disparities. The model, tested using data from Austin, Texas, indicates that neighborhoods with higher incomes and a predominantly White demographic are leading in EV adoption. To help low-income communities keep pace, we introduced tiered subsidies and incrementally increased their amounts. In our environment, with the reward and policy design implemented, the adoption gap began to narrow when the incentive was equivalent to an increase in promotion from 20% to 30%. Our study's framework provides a new means for testing policy scenarios to promote equitable EV adoption. We encourage future studies to extend our foundational study by adding specifications. [ABSTRACT FROM AUTHOR]

Highlights the events during the annual meeting by the History of Science Society held jointly with the Philosophy of Science Association in Austin, Texas in November 2004. Number of papers submitted for presentations; Overview of the discussion by Cornell University professor Peter Dear on the history of science; Information on the facilitators for the event.

This paper adopts an Austin-based speech-act theoretical framework to examine how, and to what extent, public social network discussions can contribute to the dissemination of knowledge. We focus on the role of Verdictives, the group of illocutionary acts which consist in the issuing of a judgment, and argue that the knowledge resulting from a Verdictive depends on its bringing about its characteristic conventional effect. Against this background, and working from a corpus consisting of comments on two Facebook posts discussing the highly debated issue of vaccinations, we analyze how knowledge dissemination can take place in social network discussions through the performance of Verdictives and other moves aimed at supporting, rejecting or challenging them. Particular attention is paid to moves aimed at legitimizing or delegitimizing participants as addressers of Verdictives and their sources of information. We conclude from our analyses that Facebook users have their implicit folk-epistemology, but that certain 'bad habits' in their communicative behavior and some limitations in their attitude towards inquiry, as well as the negative influence of their search for affiliative relations, significantly limit their possibilities of exchanging and disseminating genuine knowledge. • The contribution online discussions can make to knowledge dissemination is discussed. • A corpus consisting of comments and replies on two Facebook posts is examined. • The illocutionary dynamics of Verdictives in online discussions is illustrated. • Some "bad habits" of Facebook users in online discussions are highlighted. • It is argued that Facebook users have an implicit folk-epistemology. [ABSTRACT FROM AUTHOR]

Finding new sustainable energy sources or improving the efficiencies of the existing ones represents a very important research and development direction. The hybridization approach is one solution for increasing the efficiency of the existing energy sources. In the case of photovoltaic technology, the hybridization of the photovoltaic panels (PV) with thermoelectric generators (TEGs) has become a more interesting solution for the research community in the last decade. Thus, a comprehensive review of the characterization methods and instruments used in PV-TEG hybrid system study represents the objective of this work. PV and TEG equivalent circuits are presented. The instruments and software applications used for the measurements and simulations are presented and analyzed. The analysis of the literature reveals that there are many papers that offer partial or no information about the instruments used or about the measurement quality (accuracies, uncertainties, etc.). In hybrid system modeling, the preferred software applications are MATLAB (MathWorks, Natick, MA, USA) and COMSOL Multiphysics (Comsol, Burlington, MA, USA), while for experimental studies based on computers, LabVIEW (NI, Austin, TX, USA) is preferred. This review work could be interesting for researchers and engineers who are interested in finding solutions for characterizing or monitoring hybrid system components, but it is not limited to these. [ABSTRACT FROM AUTHOR]

Shared automated vehicles (SAVs) have the potential to promote transit ridership by providing efficient first-mile last-mile (FMLM) connections through reduced operational costs to fleet providers and lower out-of-pocket costs to riders. To help plan for a future of integrated mobility, this paper investigates the impacts of SAVs serving FMLM connections, as a mode that provides flexibility in access/egress decisions and is well coordinated with train station schedules. To achieve this objective, a novel dynamic pooling algorithm was introduced to match SAVs with riders while coordinating the riders' arrival times at the light-rail station to a known train schedule. Microsimulations of SAVs and travelers throughout two central Austin neighborhoods show how larger service areas, higher levels of SAV demand, and longer arrival times between successive trains require larger SAV fleet sizes and higher SAV utilization rates to deliver close traveler wait times. Four-person SAVs appear to perform similar to 6-seat SAVs but will cost less to provide. Using a dynamic pooling algorithm tightly coordinated with train arrivals (every 15 min) delivers 87% of travelers to their stations in time to catch the next train, while uncoordinated assignments deliver just 58% of travelers in time. • This paper investigates the impacts of SAVs serving first-mile last-mile train connections in central Austin. • 90% of the trips and 30% of travel distances are shared (among strangers) on board these SAVs. • Four-seat SAVs perform similar to 6-seat SAVs but will cost less to provide. • Reductions in seat capacity increases curb congestion (particularly with 1-seater SAVs). • SAVs coordinated with train arrivals deliver almost 90% of travelers in time for the next train. [ABSTRACT FROM AUTHOR]

Abstract: Vehicular emitted air pollutant concentrations were studied near three types of roadways in Austin, Texas: (1) State Highway 71 (SH-71), a heavily traveled arterial highway dominated by passenger vehicles; (2) Interstate 35 (I-35), a limited access highway north of Austin in Georgetown; and (3) Farm to Market Road 973 (FM-973), a heavily traveled surface roadway dominated by truck traffic. Air pollutants examined include carbon monoxide (CO), oxides of nitrogen (NO x ), and carbonyl species in the gas-phase. In the particle phase, ultrafine particle (UFP) concentrations (diameter < 100 nm), fine particulate matter (PM2.5, diameter < 2.5 μm) mass and carbon content and several particle-bound organics were examined. All roadways had an upwind stationary sampling location, one or two fixed downwind sample locations and a mobile monitoring platform that characterized pollutant concentrations fall-off with increased distance from the roadways. Data reported in this paper focus on UFP while other pollutants and near-roadway chemical processes are examined in a companion paper. Traffic volume, especially heavy-duty traffic, wind speed, and proximity to the road were found to be the most important factors determining UFP concentrations near the roadways. Since wind directions were not consistent during the sampling periods, distances along wind trajectories from the roadway to the sampling points were used to study the decay characteristics of UFPs. Under perpendicular wind conditions, for all studied roadway types, particle number concentrations increased dramatically moving from the upwind side to the downwind side. The elevated particle number concentrations decay exponentially with increasing distances from the roadway with sharp concentration gradients observed within 100–150 m, similar to previously reported studies. A single exponential decay curve was found to fit the data collected from all three roadways very well under perpendicular wind conditions. No consistent pattern was observed for UFPs under parallel wind conditions. However, regardless of wind conditions, particle concentrations returned to background levels within a few hundred meters of the roadway. Within measured UFP size ranges, smaller particles (6–25 nm) decayed faster than larger ones (100–300 nm). Similar decay rates were observed among UFP number, surface, and volume. [Copyright &y& Elsevier]

This paper investigated the highway stormwater quality at two Texas cities—Austin and College Station. Two highways with high average daily traffic were monitored using passive stormwater samplers for collecting first-flush runoff during a 16-month period. Detailed traffic and weather data were collected at College Station sites, but only weather data were obtained at Austin sites. A stepwise regression analysis on College Station data identifies the antecedent dry period (ADP) as the most significant predictor of pollutant concentration. Specifically, the College Station data show an unexpected result that pollutant event mean concentrations significantly decrease with increasing ADP for all analyzed pollutants. However, the runoff concentrations observed in Austin were not significantly correlated with ADP. The result from College Station data provides a different insight to the pollutant buildup and removal process on highways. Conceptual highway pollutant buildup and removal models are proposed for generating further discussion and research interest. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to describe and assess one of the first comprehensive residential green-builder programs in the U.S. It compares trends of items used in residential construction during the past five years and reports why participating builders chose to incorporate specific items and their level of commitment to the program. This description provides a baseline of strategies to investigate the effect of this program in developing sustainable communities. The builder study population was derived from a database of registered “green” residences built during 1998-2002 in greater Austin, Texas (2,335 homes and 73 listed builders). Almost half the builders constructed just one “green” home, whereas two builders built almost 75% of the green homes during the 5-year study period. Less than 1% of the homes received a perfect 5-star rating, whereas 87% were rated 1 or 2 stars. The frequency of implementing the 122 green features were compared over time and analyzed for correlation with cost and their associated star-value. Cost was the primary factor determining item use frequency. Participating builders generally concurred that the program was successful and beneficial to homeowners but that the additional work required for participation provided little financial reward for builders. While much can be done with low-cost interventions to reduce the negative environmental impacts of residential construction, builder participation may be enhanced by promotion of some of the higher cost features. In addition, public education about the long-term benefits of green homes is needed to increase homeowner participation, and encourage builders to incorporate more environmentally friendly features in the homes they construct. [ABSTRACT FROM AUTHOR]

The preferred method of switching the very high currents and voltages present in electromagnetic launch systems is to use arrays of solid-state devices. The effort to reduce the overall switch mass and volume has generated interest in advanced high-power, high-temperature semiconductor materials such as silicon carbide (SiC). Devices produced from SiC are expected to provide significant performance improvements in very high-power switching devices over current devices based on silicon (Si) materials. The performance improvement expectations are based on SiC's superior material properties, most notably for power devices are a bandgap of 3.26 eV (three times that of Si), a breakdown field of 2-4 MV · cm-1 (order of magnitude better than Si), a thermal conductivity of 4.5 W · cm-1 K-1 (three times that of Si), and a saturated drift velocity of 2 × 107 cm · s-1 (two times that of Si). This paper describes the results of recent experiments at the Institute for Advanced Technology at The University of Texas at Austin in which SiC p-i-n diodes arranged in parallel pairs are subjected to high current density pulses. The failure modes of paralleled devices are compared to the failure modes seen in individual devices subjected to high current density pulses (maximum of 234 × 104 A · cm-2). The results show current equalization between paralleled high-voltage diodes when subjected to high current densities, which suggests that high-voltage SiC active devices will also function well in parallel arrangements. [ABSTRACT FROM AUTHOR]

The article presents information related to the American Association for Artificial Intelligence (AAAI). It reports that the 2004 Classic Paper Award was given to the author of the most influential paper from the Fourth National Conference on Artificial Intelligence, held in 1984 in Austin, Texas. The Awards Committee selected Hector J. Levesque of the University of Toronto, to receive the award for his paper, "A Logic of Implicit and Explicit Belief." The article also presents the financial statement of the AAAI as of December 31, 2003 and related statements of activities, changes in net assets and cash flow for the year that ended. The financial statements are presented on the actual basis of accounting. As required by Financial Accounting Standards No. 124 investments are stated at fair market value and realized and unrealized gains and losses are combined on the statement of activities. AAAI is exempt from income taxes on its earning from investments and its exempt function operations under Section 501(c)(3) of the Internal Revenue Code and Section 23 701(d) of the California Revenue and Taxation Code. Federal and California taxes were paid during 2003 on earnings from sales of mailing lists and advertising.

The article that the 146th Meeting of the Acoustical Society of America will be held November 10-14, 2003 at the Renaissance Austin Hotel in Austin, Texas. The technical program of the event will consist of lecture and poster sessions. Instrument and equipment exposition will be located near the registration desk and meeting rooms.

Fordist automobile production methods are regarded as having been viable only in the USA prior to the 1950s. This article examines their potential in the largest non-North American automobile market—the UK, using recently-released documentation regarding General Motors' (GM's) abortive 1925 takeover bid for Britain's second largest car manufacturer, the Austin Motor Company. GM's plans for developing Austin as the leading UK car manufacturer show that existing British mass production methods could have yielded substantially higher productivity, when combined with American systems for achieving 'economies of throughput'. This, in turn, required tacit knowledge regarding 'flow production' methods, which GM executives identified as the missing element of Austin's 'elementary mass production' system. The article also discusses GM's detailed plans for Austin—utilising economies of scale, scope, and throughput to reduce prices to levels competitors would find hard to match—and their implications for the British automobile industry. [ABSTRACT FROM AUTHOR]