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A continuous monitoring of neurological status can help in reporting the physical and mental health of a person. This can be capitalized for building a healthcare tracking system using a wearable device and a handheld mobile device. In this paper, we have used the non-EEG physiological biosignals dataset which gives practicability among subjects for acquiring data easily from wearable device sensors linearly and comfortably rather than the way of putting the subjects in a cumbersome setup laboratory. This paper proposes a custom fully convolutional-LSTM (FCN-LSTM) network to identify the neurological status of a subject using multivariate time series physiological sensor data. The proposed architecture uses parallel stacks of the convolutional layers and LSTM cells. This combination of different network types is significant for the selected problem as the fully convolutional section of the model extracts the local spatial features in the data, while the LSTM network handles the high-level features and temporal dependencies. The proposed FCN-LSTM model yielded a high accuracy of 98.6% and a precision of 98% on the non-EEG dataset from UT-Dallas. The average accuracy of single-subject results of the dataset using the proposed model was observed to be 99.26%. The results from the proposed model are significantly improved when compared with various state-of-the-art works on this problem. These results strongly suggest that this model, when put on a wearable device, can be effectively used to detect the neurological status or stress that the subject may be going through in real time. [ABSTRACT FROM AUTHOR]

Drawing on qualitative data from an exploratory study of the experiences of audit pair researchers—pairs of black, white, and Latinx field testers—in an urban nightlife study in Austin, Dallas, and Houston, Texas, this paper examines nightclub owners' use of what I identify as "exclusionary tools"—that is, "dress codes," "steering," and "fake guest lists." Using Critical Race Theory's critique of neutrality, I argue that these exclusionary tactics create a welcoming atmosphere for white patrons while maintaining limits on the participation of African Americans and other peoples of color. This paper offers empirical examples of how these exclusionary practices limit legal challenges to discrimination in the first place and concludes with a discussion of potential methodological approaches for expanding this exploratory study and further identifying systematic exclusionary practices. [ABSTRACT FROM AUTHOR]

This paper presents a new data fusion multiscale observation product (MOP) for flood emergencies. The MOP was created by integrating multiple sources of contributed open-source data with traditional spaceborne remote sensing imagery in order to provide a sequence of high spatial and temporal resolution flood inundation maps. The study focuses on the 2015 Memorial Day floods that caused up to USD 61 million dollars of damage. The Hydraulic Engineering Center River Analysis System (HEC-RAS) model was used to simulate water surfaces for the northern part of the Trinity River in Dallas, using reservoir surcharge releases and topographic data provided by the U.S. Army Corps of Engineers. A measure of fit assessment is performed on the MOP flood maps with the HEC-RAS simulated flood inundation output to quantify spatial differences. Estimating possible flood inundation using individual datasets that vary spatially and temporally allow to gain an understanding of how much each observational dataset contributes to the overall water estimation. Results show that water surfaces estimated by MOP are comparable with the simulated output for the duration of the flood event. Additionally, contributed data, such as Civil Air Patrol, although they may be geographically sparse, become an important data source when fused with other observation data. [ABSTRACT FROM AUTHOR]

Power generation using small wind turbines connected to AC grids has been gaining attention and contributions in recent years. As small wind turbines are connected to remote areas as support energy systems, there are not extensive contributions connecting those small turbines to AC grids. This paper presents the integration of a small wind generation system which is AC-grid-connected. The system is composed of a 160 W commercial small wind turbine with a permanent magnet synchronous generator and a 140 W Texas Instruments (Dallas, TX, USA) development kit devoted to connecting photovoltaic panels to AC grids. Several experimental tests were developed to characterize the devices, e.g., to obtain the power–current curves of the synchronous generator. Moreover, a mathematical model of the flyback converter is developed in detail in order to design a new converter controller. All the control capacity of the development kit is used to extract the maximum power of the synchronous generator, to reject the oscillation produced by the inverter and to connect the system to the AC grid. Experimental results show that is possible to integrate these devices to provide energy to power systems with some achievable adaptations. [ABSTRACT FROM AUTHOR]

This paper considers the problem of estimating road user costs (RUCs), such as travel time and delays, for roadway construction projects under time and data limitations. RUCs measure the mobility impacts of construction work zones on public roads. RUC metrics are typically used in construction phases to determine the project's incentives and disincentives. However, determining RUC can be challenging due to scarce traffic data availability, incomplete construction plans, and limited time to conduct analysis. In this paper, we use traffic microsimulation to estimate the RUC for each hour of a typical 24-h day using 11 construction cases in Dallas, Texas. Our primary contribution includes developing relationships between peak-hour RUC measures with respect to the total daily values. Such relationships would allow an estimation of the full day RUC based only on the analysis of the peak hour. The main results suggest that the peak-hour travel time as a fraction of the daily value is, on average, 8.2%, comparable to typical percentages of the peak-hour traffic volumes. Furthermore, the models for predictive relationships using construction scenario demand and capacity show high correlation coefficients, presenting a potential for the development of such relationships for roadway construction projects. [ABSTRACT FROM AUTHOR]

Transportation has been identified as one of the major barriers to successful reentry for prisoners released to community in the United States. We foregrounded transportation and mobility in our design consistent with the new mobilities paradigm and investigated the mobility needs of returning citizens from the perspective of service providers and employers in Dallas, Texas. We interviewed 17 participants who directly served returning citizens in their professional roles as part of a conventional content analytic design that focused specifically on transportation and mobility among their clients. The findings include five primary themes: 1) Returning citizens rely primarily on public transit; 2) Access to cars is rare, complicated, but advantageous; 3) Support lays a road to successful reentry; 4) Transportation is critical for successful reentry, and; 5) Returning citizens face a complex network of obligations. We utilized mobilities literature and assemblage thinking to interpret our findings as an expansion of the carceral mobilities literature both conceptually and geo-spatially as a reentry mobility assemblage. The paper concludes with a consideration of the possibilities for social service practice, research, and pedagogy through a mobilities lens. [ABSTRACT FROM AUTHOR]

In this paper, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers' clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles' abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%–15% of all moving vehicles in the Dallas–Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle's actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials—a common visualization of arterial signal performance for transportation planning and operations. [ABSTRACT FROM AUTHOR]

Nowadays, in researches on electric vehicle routing problems, in order to improve the delivery efficiency and reduce the routing cost, many important elements are broad discussed such as the customer time window, the routing algorithm, the electric energy consumption, etc. In these, the routing algorithm is the key element to achieve a good solution. Based on this background, the paper investigates the routing algorithm, then adopts the elitist genetic algorithm and proposes an improved neighbor routing initialization method for solving the electric vehicle routing problem. In our method, the electric vehicle energy consumption is used as the main component of the routing system. The neighbor routing initialization enables the routing system to choose the close route from a suitable first customer in the initialization, which makes the routing search faster and find the global optimal route easily. The simulations on the Solomon benchmark data and the Hiland Dairy milk delivery example in Dallas, Texas, USA verifies the good performance of the method. [ABSTRACT FROM AUTHOR]

Infrasound data contain contributions from incoherent noise, coherent noise and signals of interest. The design of an infrasound array to target sources of interest requires a quantification of array response, individual sensor response, propagation effects (topography and meteorological conditions), signal spectrum and the noise environment. The Comprehensive Nuclear-Test-Ban Treaty community has spent significant effort in quantifying the acoustic field in rural environments for frequencies up to 7 Hz. Given that the nuclear monitoring and tactical infrasound community have growing interests in monitoring sources in or near populated regions, there is an emergent need to measure and understand acoustic fields in these environments as well. This paper focuses on quantification of the acoustic field in three different urban environments: (1) arrays installed within Dallas, TX, a metropolitan area, (2) an array installed at the rural–suburban interface near San Diego, CA and (3) an array installed in Vicksburg, MS, a small city with multiple major transportation corridors. A minimum of five months of data was recorded and used for each site characterization. The analysis focuses on frequencies from 0.1 to 45 Hz. The quantification of the data from these three sites is accomplished with statistical noise models that capture the total ambient acoustic field, separation of the coherent portion of the field and trend analysis to link temporal and seasonal variations to wind speed and anthropogenic activities. The resulting physical interpretation of the data demonstrates that the total acoustic field in urban regions is overall higher and inversely related to the number of coherent detections observed by an array. Furthermore, this study presents an analysis framework for characterizing additional urban arrays and provides a basis for future array site selection and installation. [ABSTRACT FROM AUTHOR]

Machine learning (ML) is being used regularly in many different fields. This paper compares traditional econometric methods that have better explanations of data analysis to ML methods, focusing on predicting, understanding and unpacking ML methods which have higher prediction accuracies of four key transport‐planning variables: household vehicle‐miles traveled (continuous variable), household vehicle ownership (count variable), mode choice (categorical variable), and land use change (categorical variable with strong spatial interactions). Here, the results of ten ML methods are compared to methods of ordinary least squares (OLS), multinomial logit (MNL), negative binomial and spatial auto‐regressive (SAR). The U.S.'s 2017 National Household Travel Survey and land use data sets from the Dallas‐Ft. Worth region of Texas are used. Results suggest traditional econometric methods work pretty well on the more continuous responses (VMT and vehicle ownership), but the random forest (RF), gradient boosting decision trees (GBDT), and extreme gradient boosting (XGBoost) methods delivered the best results, though the RF model required 30 to almost 60 times more computing time than XGBoost and GBDT methods. The RF, GBDT, XGBoost, light gradient boosting method (lightGBM), and catboost offer better results than other methods for the two "classification" cases, with lightGBM being the most time‐efficient. Importantly, ML methods captured the plateauing effect modelers may expect when extrapolating covariate effects. [ABSTRACT FROM AUTHOR]

In this paper, we present a method (Action-Fusion) for human action recognition from depth maps and posture data using convolutional neural networks (CNNs). Two input descriptors are used for action representation. The first input is a depth motion image that accumulates consecutive depth maps of a human action, whilst the second input is a proposed moving joints descriptor which represents the motion of body joints over time. In order to maximize feature extraction for accurate action classification, three CNN channels are trained with different inputs. The first channel is trained with depth motion images (DMIs), the second channel is trained with both DMIs and moving joint descriptors together, and the third channel is trained with moving joint descriptors only. The action predictions generated from the three CNN channels are fused together for the final action classification. We propose several fusion score operations to maximize the score of the right action. The experiments show that the results of fusing the output of three channels are better than using one channel or fusing two channels only. Our proposed method was evaluated on three public datasets: 1) Microsoft action 3-D dataset (MSRAction3D); 2) University of Texas at Dallas-multimodal human action dataset; and 3) multimodal action dataset (MAD) dataset. The testing results indicate that the proposed approach outperforms most of existing state-of-the-art methods, such as histogram of oriented 4-D normals and Actionlet on MSRAction3D. Although MAD dataset contains a high number of actions (35 actions) compared to existing action RGB-D datasets, this paper surpasses a state-of-the-art method on the dataset by 6.84%. [ABSTRACT FROM AUTHOR]

Summary: With the grid's evolution, the end‐users demand becomes more vital for demand side management (DSM). Accurate load forecasting (LF) is critical for power system planning and using advanced demand response (DR) strategies. To design efficient and precise LF, information about various factors that influence end‐users demand is required. In this paper, the impact of different factors on electrical demand and capacity of climatic factors existence and their variation is discussed and analysed. The Pearson correlation coefficient (PCC) is utilized to express the degree of electric demand correlation with metrological and calendar factors. Then, the optimal‐Bayesian regularization algorithm (BRA) based on ANN for LF is presented. The effect of the number of neurons in hidden layers on output is observed to select the most appropriate option. Additionally, heating degree days (HDDs) and cooling degree days (CDDs) indices are investigated to consider the impact of air conditioners' (ACs) loads in different seasons. Case studies on data from Dallas, Texas, USA, are used to demonstrate the influence of various factors on electrical demand. The proposed algorithm's effectiveness for LF and error formulations shows that optimal‐BRA‐enabled LF presents better accuracy than state‐of‐the‐art approaches. Thus, the proposed electric demand prediction strategy could help the system operator know DR potential at different times better, leading to optimal system resources dispatching through DR actions. [ABSTRACT FROM AUTHOR]

Dallas/Fort Worth International Airport (DFW) was one of the first airports in the USA to receive Federal Aviation Administration (FAA) approval to fly small unmanned aerial system (sUAS) aircraft in highly restricted Class B airspace. To date, almost 100 public and commercial flights have been flown at DFW in support of law enforcement activities, fire safety, airport construction and private industry videography. The path to FAA issuance of sUAS certificates of authorization (COA) was paved by a concerted effort among a broad cross-section of aviation professionals with an interest in integrating UAS operations into the DFW environment. The DFW UAS Work Group worked diligently on many aspects of sUAS operations, ranging from COA application to UAS education to flight procedures development. Collaboration between airport representatives and various entities within the FAA resulted in an executed letter of agreement that supports public and commercial sUAS flights over airport property. This paper describes the methodology applied by the work group that led to successful sUAS flight operations. The paper also identifies barriers encountered and the processes applied to mitigate those issues. The author and the DFW UAS Work Group would like to share information that would hopefully assist other airports in developing a sUAS flight programme. [ABSTRACT FROM AUTHOR]

The Air Quality Index (AQI), developed by the United States Environmental Protection Agency (USEPA), has been providing the public with crucial information regarding the status of contamination of the atmosphere for the past 45 years. Prior to introduction of the AQI, only a handful of metropolitan areas reported on air quality, and each region decided on its own metric. The inception of a single AQI helped homogenize the air quality metrics across the nation and indeed served as an important future template for other governmental and regulatory agencies across the world. The formulators had the foresight to recognize that our understanding of air pollution and its effects may change over time, which are likely to change regulatory limits. They used a dynamic framework to define the AQI, such that the broad definition or principle does not need to change with every change in regulatory limits or policy, and the fundamental goal of alerting the public to deleterious air quality is not affected. The establishment of the AQI increased public awareness of the importance of clean air and has helped muster support for air quality and emission regulations. The National Ambient Air Quality Standards (NAAQS) set forth by the USEPA provides acceptable levels of criteria pollutants – namely carbon monoxide, lead, nitrogen dioxide, ozone, particulate matter, and sulfur dioxide. A comparison of the actual levels, as compared to the regulatory limits (since the cessation of leaded gasoline, lead is no longer included in the index), are used as the basis for the AQI. As the regulatory limits change, so does the exact evaluation of the AQI, making it a living index. In this paper, we provide a historical overview of the Air Quality Index, the Federal Reference Methods (FRMs) vs. Federal Equivalent Methods (FEMs) for measuring them, and as an illustrative example, we discuss the air quality for Dallas-Ft. Worth, currently the fourth most populous metropolitan region in the United States, vis-a-vis the reported AQI. [Display omitted] • Origin and formulation of the Air Quality Index. • The pollutants forming the basis of the AQI and official methods to measure them. • Accessing back trajectories and other meteorological data to assess mesoscale transport. [ABSTRACT FROM AUTHOR]

The article announces a call for papers for the Council for Exceptional Children's 57th Annual International Convention slated in April 1979 in Dallas, Texas. Individuals may submit papers, program sessions or other types of convention ideas to program chairperson, Kenneth E. Wyatt. Deadline for submission of papers and convention ideas is June 15, 1978 which could include workshops, demonstrations, and other practical application formats. Topics must have relevance to the exceptional child and other key concerns.

This paper presents a novel methodology for urban growth prediction using a machine learning approach. The methodology treats successive historical satellite images of an urban area as a video for which future frames are predicted. It adopts a time‐dependent convolutional encoder–decoder architecture. The methodology's input includes a satellite image for the base year and the prediction horizon. It constructs an image that predicts the growth of the urban area for any given target year within the specified horizon. A sensitivity analysis is performed to determine the best combination of parameters to achieve the highest prediction performance. As a case study, the methodology is applied to predict the urban growth pattern for the Dallas–Fort Worth area in Texas, with focus on two of its counties that observed significant growth over the past decade. The methodology is shown to produce results that are consistent with other growth prediction studies conducted for the areas. [ABSTRACT FROM AUTHOR]

Whether racial bias is intertwined with capital case dispositions continue to be a matter of contention. In 1972, Furman v. Georgia ruled capital punishment unconstitutional on the grounds of being capricious and arbitrary. To better understand this sociological phenomenon, the current paper examines capital punishment within a historical context. Specifically, the present study is an exploratory examination of county-level data consisting of offenders who received a death sentence between 1923 through 1972. Media accounts from a Dallas newspaper during that time period were also examined. Results indicate that Blacks were disproportionately sentenced to death compared to their White counterparts. Capital sentencing trends at the county level reflect national trends of racial bias that characterized this historical period. [ABSTRACT FROM AUTHOR]

The contrast of space and place has long been an active topic of scholarly discussions in many disciplines. While spatial analysis enjoys a multitude of quantitative methods, the study of place remains mostly conceptual and descriptive. This paper expands upon the rich concepts of place in the literature to propose a quantitative framework for placial analysis based on events. Central to the proposed framework are three assumptions: (1) human experiences transform space to place; (2) events build human experiences in space; and (3) places emerge organically and may change characters, spatial extent and location over time through the shifts in occurrences and types of events in space and time. The proposed framework consists of three elements: clustering events, decomposing event distributions, and identifying the similarity of event clusters. We applied the framework to identify criminological places in the City of Dallas in the United States and the changes of these places from 1 June 2014 to 30 May 2018. [ABSTRACT FROM AUTHOR]

Looking to transition towards health equity, the American Heart Association worked with a design strategy consultancy, verynice, on the development of a toolkit for human-centered innovation. Professor Matthew Manos of the USC Iovine and Young Academy led a group of students on a residential experience in Dallas that leveraged the toolkit to better understand the social determinants of health. Since then, the toolkit has since been applied to several residential experiences in the school. This paper explores the application of this toolkit in an educational environment for teaching students how to listen to community needs, and suspend their bias. [ABSTRACT FROM AUTHOR]

An active stage of relativistic astrophysics started in 1963 since in this year, quasars were discovered, Kerr solution had been found and the first Texas Symposium on Relativistic Astrophysics was organized in Dallas. Five years later, in 1967–1968 pulsars were discovered and their model as rotating neutron stars (NSs) had been proposed, meanwhile Wheeler claimed that Kerr and Schwarzschild vacuum solutions of Einstein equations provide an efficient approach for astronomical objects with different masses. Wheeler suggested to call these objects black holes. NSs were observed in different spectral band of electromagnetic radiation. In addition, a neutrino signal had been found for SN1987A. Therefore, multi-messenger astronomy demonstrated its efficiency for decades even before observations of the first gravitational radiation sources. However, usually, one has only manifestations of black holes in a weak gravitational field limit and sometimes a model with a black hole could be substituted with an alternative approach which very often looks much less natural, however, it is necessary to find observational evidences to reject such an alternative model. At the moment, only few astronomical signatures for strong gravitational field are found, including a shape of relativistic iron K α line, size and shape of shadows near black holes at the Galactic Center (GC) and M87, trajectories of bright stars near the GC. After two observational runs, the LIGO–Virgo collaboration provided a confirmation for a presence of mergers for 10 binary black holes and one binary NS system where gravitational wave signals were found. In addition, in the last years, a remarkable progress has been reached in a development of observational facilities to investigate a gravitational potential, for instance, the number of telescopes operating in the Event Horizon Telescope network is increasing and accuracy of a shadow reconstruction near the GC is improving, meanwhile largest VLT, Keck telescopes with adaptive optics and especially GRAVITY facilities observe bright IR stars at the GC with perfect accuracy. More options for precision observations of bright stars will be available with creating extremely large telescopes Thirty Meter Telescope (TMT) and E-ELT. It is clear that the GC (Sgr A ∗ ) is a specific object for observations. Our solar system is located at a distance around 8 kpc from the GC. Earlier, theorists proposed a number of different models including exotic ones for GC such as boson star, fermion ball, neutrino ball, a cluster of NSs. Later, some of these models were ruled out or essentially constrained with consequent observations and theoretical considerations. Currently, a supermassive black hole with mass around 4 × 1 0 6 M ⊙ is the most natural model for GC. Using results of observations for trajectories of bright stars in paper [A. F. Zakharov, P. Jovanović, D. Borka and V. B. Jovanović, J. Cosmol. Astropart. Phys.05 (2016) 045] the authors got a graviton mass constraint which is comparable and consistent with constraints obtained recently by the LIGO–Virgo collaboration. Later, we consider opportunities to improve current graviton mass constraints with future observations of bright stars [A. F. Zakharov, P. Jovanović, D. Borka and V. B. Jovanović, J. Cosmol. Astropart. Phys.04 (2018) 050]. Similarly, from an analysis of bright star trajectories, one could constrain a tidal charge which was predicted by a gravity theory with an additional dimension [A. F. Zakharov, Eur. Phys. J. C78 (2018) 689]. [ABSTRACT FROM AUTHOR]

Neighborhood infrastructure, such as sidewalks, medical facilities, public transit, community gathering places, and tree canopy, provides essential support for safe, healthy, and resilient communities. This paper examines the presence and condition of neighborhood infrastructure and shows that "infrastructure deserts" exist, which are low-income neighborhoods with significantly more deficient infrastructure. A generalized data-driven framework is developed and implemented at the street-level for 12 types of neighborhood infrastructure in Dallas, Texas. The results show significant infrastructure inequities across income levels for most types of infrastructure. Statistical inference predicts (with 95 % confidence) that low-income neighborhoods are 2.0 to 3.5 times more likely to have highly deficient infrastructure (8 or more deficient infrastructure types) than high-income areas and 1.4 to 2.4 times more likely to have highly deficient infrastructure than middle-income neighborhoods. This paper addresses the methodological challenge of considering multiple infrastructure types and provides a guide for infrastructure investment prioritization. • A generalized data-driven framework that assesses 12 neighborhood infrastructure types and identifies"infrastructure deserts" • Infrastructure inequities across income levels for most types of infrastructure discovered in Dallas, Texas, USA • Low-income neighborhoods are 2 to 3.5 times likelier to have highly deficient infrastructure than high-income neighborhoods [ABSTRACT FROM AUTHOR]

Translating changes in land surface conditions and climate into changes in precipitation, runoff and flood frequencies over a range of catchment scales is a pressing challenge for hydrologic design and flood risk management today. In this paper, we describe a novel approach for modeling areal runoff frequency from heavy-to-extreme precipitation in large urban areas using a simple but general stochastic model for runoff at point scale and bi- and univariate parametric probability distributions for positive point precipitation and areal runoff, respectively. We apply the approach to the Dallas–Fort Worth area using a 22-year historical multisensor precipitation dataset from the National Weather Service to characterize how the different factors that specify the second-order statistics of precipitation, imperviousness and soil water holding capacity at point scale may shape areal runoff frequency, and to assess how changes in precipitation climatology and land surface conditions may change areal runoff frequency as a function of catchment scale and magnitude of precipitation. The results indicate that areal runoff frequency is impacted most significantly by changes in climatological mean and coefficient of variation of positive point precipitation, water holding capacity of soil, imperviousness, and spatial correlation scale of positive point precipitation given the probability of occurrence of heavy-to-extreme precipitation, and that a very small number of low-order statistics of point precipitation may describe areal runoff frequency given the conditional probability distribution models for point precipitation and areal runoff. The approach presented hence offers a parsimonious physically-based alternative to purely numerical approaches based on integrated modeling, or empirical approaches based solely on statistical modeling toward predictive modeling of areal precipitation and runoff frequencies under changing hydroclimatological conditions. [ABSTRACT FROM AUTHOR]

Local-scale government ordinances that attempt to delay or displace oil and gas drilling in their territories are common in regions with hydrocarbon extraction activities. Drawing on literature from policy mobilities and resource and energy governance, this paper analyzes policymaking processes that resulted in a December 2013 ordinance in Dallas, Texas, which established a 1500 foot (457.2 meter) setback between gas wells and residences, making drilling (with hydraulic fracturing) nearly impossible. Dallas was not the first city in the region to adopt an oil and gas drilling ordinance; indeed, many regulatory provisions were copied from other regional cities. This paper explains policy mobility in the Dallas policymaking process in terms of anti-political practices and hydrocarbon institutions that, overall, determine neoliberal hydrocarbon governance. City governments cede some of the political process to gas drilling task forces that work to render setbacks technical. Legal classification of subsurface hydrocarbons as the mineral estate creates a legal gray area that confounds municipal regulatory authority and gives discursive power to mineral owners to threaten municipal officials with lawsuits. Both of these anti-political strategies encouraged selective copying and morphing of other policy provisions by the Dallas city government. Adopting longer municipal setback distance regulations represents a type of contestation of neoliberalism situated between complete deregulation and overt opposition. [ABSTRACT FROM AUTHOR]

This paper proposes a novel analytical framework that integrates spatial statistics and machine learning techniques to identify relationships between e-commerce and distribution facilities. The framework includes centrographic analysis, global and local spatial association measurements, and a recently popularized interpretable machine learning approach – gradient boosting decision trees (GBDT) – to analyze warehousing location choices. We apply this framework to ZIP Codes Business Patterns data from 2003 to 2016 in three large metropolitan areas in Texas, US (i.e., Dallas-Fort Worth, Austin, and Houston). The thematic maps reveal the spatial clustering of areas with higher e-commerce activity but lower logistics facility coverage. It is worth noting that we do not observe logistics sprawl in the study region. The GBDT results show that industrial activities and transportation network accessibility are key factors influencing warehousing location choices. We also find that the relationship between warehouses and e-commerce establishments is weaker in Houston, a major maritime gateway for goods entering and leaving, as compared to Dallas-Fort Worth and Austin. Implications for local freight transportation planners and decision-makers are discussed. [ABSTRACT FROM AUTHOR]

In November 2016 researchers, clinicians, and student experts gathered in Dallas, Texas, USA for the annual meeting of the International Society for Traumatic Stress Studies (ISTSS). From the description of the meeting theme forward it was acknowledged that interdisciplinary approaches will be required to fully understand traumatic stress as a public health problem, including epidemiology, biostatistics and health services research. Further, it was recognized that knowledge translation would be of critical importance if we were to increase public awareness of - and destigmatize - posttraumatic biopsychosocial problems, including posttraumatic stress disorder (PTSD). Moreover, we recognized innovative technologies as potentially usefully applied to public health strategies, including media and internet usage might aid knowledge translation and have a direct impact on help-seeking and trauma-informed care. The present special issue of the journal brings a collection of papers from some of the most impactful and innovative ideas that were presented in Dallas. [ABSTRACT FROM AUTHOR]

Background: This paper is based on a panel discussion at the 32nd annual meeting of the International Society for Traumatic Stress Studies in Dallas, Texas, in November 2016. Objective: Paula Schnurr convened a panel of experts in the fields of public health and technology to address the topic: 'What I have changed my mind about and why.' Method: The panel included Richard Bryant, Lucy Berliner, Dean Kilpatrick, Albert ('Skip') Rizzo, and Josef Ruzek. Results: Panellists discussed innovative strategies for the dissemination of scientific knowledge and evidence-based treatment. Conclusions: Although there are effective treatments, there is a need to enhance the effectiveness of these treatments. There also is a need to develop simpler, low-cost strategies to disseminate effective treatments. However, technology approaches also offer pathways to increased dissemination. Researchers must communicate scientific findings more effectively to impact public opinion and public policy. [ABSTRACT FROM AUTHOR]

• Provides method for analyzing areas of high parking demand. • Identifies e-scooter vendor launching sites. • Compares techniques for analyzing roadway segments of high micromobility demand. • Discusses policy implications and potential environmental impacts of micromobility. • Examines the accuracy of shortest path models in predicting e-scooter paths. To enhance the effectiveness of dockless shared micromobility vehicle services, address challenges created by these services, and achieve better implementation performance, cities need efficacious strategies to tackle two major challenges: parking demand and infrastructure improvements. This paper offers two techniques for analyzing areas of high parking demand and roadway segments of high micromobility vehicle demand. The proposed processes support efforts to assign free-floating parking and reduce vehicle clutter across cities, and assist transportation planners in identifying locations for road infrastructure improvement and ordinance enforcement. An unsupervised learning approach using vendor launching site analysis is used to appropriately locate dockless vehicle parking zones. Furthermore, this paper compares three methods for identifying high-demand corridors. Two shortest path models are generated to predict trip paths for trip data without trajectories, considering rider route preferences and infrastructure types. A Simplified Matching Heuristic (SMH) that uses trip data with trajectories, is developed herein to match trip trajectory data to the network street links. These analytical processes are applied in a case study of Dallas, TX. Results show that methods using shortest path models may poorly predict the actual path taken by e-scooter users. A discussion of policy implications for micromobility planning and management and potential environmental impacts of emerging transportation technologies are also presented. [ABSTRACT FROM AUTHOR]

Drawing on notions of the symbolic economy and urban imaginary as an inherent dimension of the neoliberal public sphere, this paper examines historicized city plans and their visions, and develops a framework for understanding the role of city plans in shaping urban imaginaries and branded spaces. The paper claims that future city visions, fundamental to plan-making, help legitimize the power elites' growth agendas and ambitions to invest in both symbolic and material flagship place-making projects heavily bolstered and publicized by the media. The study examines this claim in the American context, selecting Dallas, Texas as a unique entrepreneurial city overly concerned with its public image characterized by a long-standing legacy of place promotion and plan-making. Using archival research and semi-structured interviews with key informants, this paper finds that city plans' visions, subservient to the civic elites' cultural tastes, have been instrumental in rallying public support to materialize place-making projects in accord with the city's larger preoccupation with "world-class" status showcased and widely promoted by media outlets. This study concludes by reflecting on the subtle yet tangible link between plan-making and urban imaginaries, an overt tendency of ever more commodified urban spaces, and the paradox it poses to city planning. • Urban imaginaries are embedded in textual narratives, conceptual symbols, and visual renditions. • Plan making and city plans are fundamental to legitimizing the power elites' pro-growth urban imaginaries. • Planners and architects, as urban imagineers, play a key role in mobilizing the public to approve of place-making projects. • Media heavily brands and disseminates elites' growth-oriented urban imaginaries in the public sphere. • Elites' imposing urban imaginaries are often at odds with more pressing urban imaginaries based on social justice. [ABSTRACT FROM AUTHOR]

In this paper, a finite-element-based model is being introduced and developed, using the Cast3m (CEA, Paris, France) simulation tool, to evaluate the thermo-mechanical behavior of a small-scale test bed. In fact, many studies on thermal behavior of cavities have been carried out in literature. However, none of them took into account the co-existence of all thermal phenomena (conduction, convection, internal/external radiation). The work presented in this paper presents a thermo-mechanical model, which aims to combine, in a holistic way, these phenomena. An experimental validation of the thermal model has been first carried out using an infrared camera and DS18B20 (Maxim Integrated Products, Dallas, TX, USA) numerical sensors. Results are reported and show the accuracy of the proposed model since both numerical and experimental values of heat transmittance fit together. The main objective is to evaluate heat losses through the walls, by means of heat transmittance calculation, and proposing new functional materials that will help in energy harvesting, as a perspective of this work. As for the mechanical study, it was meant to investigate the distribution of the mechanical stress towards the building envelope submitted to its own weight. Results showed that the stress is uniformly distributed on the lateral walls of the structure as well as on the floor. [ABSTRACT FROM AUTHOR]

First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Victor Palacios is first author on 'Importin-9 regulates chromosome segregation and packaging in Drosophila germ cells', published in JCS. Victor conducted his PhD research in the lab of Michael Buszczak at the University of Texas Southwestern Medical Center, Dallas, TX, where he investigated the essential role of Importin-9 in Drosophila fertility. [ABSTRACT FROM AUTHOR]

Disruption management during the airline scheduling process can be compartmentalized into proactive and reactive processes depending upon the time of schedule execution. The state of the art for decision-making in airline disruption management involves a heuristic human-centric approach that does not categorically study uncertainty in proactive and reactive processes for managing airline schedule disruptions. Hence, this paper introduces an uncertainty transfer function model (UTFM) framework that characterizes uncertainty for proactive airline disruption management before schedule execution, reactive airline disruption management during schedule execution, and proactive airline disruption management after schedule execution to enable the construction of quantitative tools that can allow an intelligent agent to rationalize complex interactions and procedures for robust airline disruption management. Specifically, we use historical scheduling and operations data from a major U.S. airline to facilitate the development and assessment of the UTFM, defined by hidden Markov models (a special class of probabilistic graphical models) that can efficiently perform pattern learning and inference on portions of large data sets. We employ the UTFM to assess two independent and separately disrupted flight legs from the airline route network. Assessment of a flight leg from Dallas to Houston, disrupted by air traffic control hold for bad weather at Dallas, revealed that proactive disruption management for turnaround in Dallas before schedule execution is impractical because of zero transition probability between turnaround and taxi-out. Assessment of another flight leg from Chicago to Boston, disrupted by air traffic control hold for bad weather at Boston, showed that proactive disruption management before schedule execution is possible because of non-zero state transition probabilities at all phases of flight operation. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a detailed estimation of fuel consumption and emissions during taxi operations using aircraft position data from actual operations at Dallas/Fort Worth International Airport. Making assumptions of the thrust level during each state, fuel flow and emission index values from International Civil Aviation Organization’s databank are extrapolated. This provides a relative comparison of all the taxi phases and their contribution to the total effect. Analysis reveals that stop-and-go situations, resulting primarily from congestion on airport’s taxiway system, account for approximately 18% of fuel consumed. The states of idling and taxiing at constant speed or braking were found to be the two largest sources of fuel burn and emissions, and the model estimates are sensitive to the thrust level assumptions for these states. [Copyright &y& Elsevier]

Abstract: Models assessing exposure to air pollution often focus on macro-scale estimates of exposure to all types of sources for a particular pollutant across an urban study area. While results based on these models may aid policy makers in identifying larger areas of elevated exposure risk, they often do not differentiate the proportion of population exposure attributable to different polluting sources (e.g. traffic or industrial). In this paper, we introduce a population exposure modeling system that integrates air dispersion modeling, Geographic Information Systems (GIS), and population exposure techniques to spatially characterize a source-specific exposure to ambient air pollution for an entire urban population at a fine geographical scale. By area, total population exposure in Dallas County in 2000 was more attributable to vehicle polluting sources than industrial polluting sources at all levels of exposure. Population exposure was moderately correlated with vehicle sources (r = 0.440, p < 0.001) and weakly with industrial sources (r = 0.069, p = 0.004). Population density was strongly correlated with total exposure (r = 0.896, p < 0.001) but was not significantly correlated with individual or combined sources. The results of this study indicate that air quality assessments must incorporate more than industrial or vehicle polluting sources-based population exposure values alone, but should consider multiple sources. The population exposure modeling system proposed in this study shows promise for use by municipal authorities, policy makers, and epidemiologists in evaluating and controlling the quality of the air in the process of urban planning and mitigation measures. [Copyright &y& Elsevier]

• Noise complaints aggravate transportation inequality. • Minorities may not be reluctant to report noise complaints. • Transportation-related matters dominate self-reported noise complaints. As a self-reporting data source, the 311 non-emergency service reflects the residents' concerns on various environmental complaints, including noise. This study explores the nexus between noise complaints extracted from this data source and the transportation-related inequality that reflects a wide range of socio-demographic cohorts associated with it in Dallas, Texas. Noise constitutes an inevitable fact of life—especially in denser urban areas, that as this paper reports, reflects social injustice. Drawing from multiple socio-demographic and transportation indicators, this study conducts multiple statistical and spatial analyses in the selected case studies. The findings further identify the explanatory variables relative to noise complaints and their inequality implications. The results confirm that transportation-related factors affect inequality while also operating within specific socio-demographic patterns. The study gleans lessons for transportation and urban planners, policymakers, and local authorities. [ABSTRACT FROM AUTHOR]

The article discusses how the processing of medication orders are influenced by a remote order scanning system (ROSS) at Baylor University Medical Center (BUMC) in Dallas, Texas. Digital scanning technology is used by ROSS for converting paper based prescription orders into electronic documents. A randomized comparison of efficiencies was done to analyze implementation of a ROSS to oversee physician orders handled at BUMC. The ROSS helped reduce time consumption in medication order processing.

Mail Processing and Distribution Centers (P&DCs) run 24 hours a day, 7 days a week and are staffed by a skilled complement of full-time, part-time, and temporary employees. A recurrent problem faced by facility managers involves the development of daily schedules for the automation equipment used to process the mail. The ultimate goal is to minimize the labor costs associated with running the facility while ensuring that all service standards are met. The focus of this paper is on the equipment scheduling aspect of the problem. In particular, we seek a weekly schedule that satisfies all operational, technological, and legal constraints of the system at a minimum cost. The problem is modeled as a large-scale mixed-integer linear program and solved sequentially using a three-stage methodology. In each stage, a separate criterion is optimized and the corresponding objective function value is used as a constraint in subsequent stages. To ease the computational burden, two major enhancements are developed. The first is a pre-processor designed to reduce the number of integer variables; the second is a heuristic that uses the linear programming solution as a target and attempts to find a feasible integer point as close to it as possible. The methodology is demonstrated with data obtained from the Dallas P&DC. The computations indicate that for letter operations alone the annual savings will be on the order of $1.6 million per facility when the system is implemented nationwide over the next 3 years. [ABSTRACT FROM AUTHOR]

Presents an answer sheet in relation to selected papers from the 27th Annual Symposium of the American Breast Disease held in Dallas, Texas.

Public education campaigns, to be successful, must repeat simple, consistent messages over time, using various sources and media. During the 2000, 2001, and 2002 ozone seasons, the North Central Texas Council of Governments (NCTCOG) employed a four-pronged, multimedia approach to educate the public about air quality in the Dallas/Fort Worth (DFW) region. The four-pronged approach included several varied information sources:

This article presents abstracts of the papers discussed in the 25th Annual Carrell-Krusen Symposium held at the Texas Scottish Rite Hospital for Children in Dallas, Texas from February 27-March 1, 2003. A case featuring the limb-girdle weakness in a young girl was studied. It was found that glycogenosis type III is an autosomal recessive disorder. A 13-year old boy with progressive spinobulbar paralysis was studied.

Asian Americans have often been perceived as the "model minority" that is relatively immune to the problem of illegal drug use. This paper examines the patterns and determinants of illegal drug use among first and second-generation Asian American youths in Dallas—an area with rapid Asian population growth. Through a targeted survey, we have found a very high rate of cumulative drug use and a significant rate of current drug use. We have also detected some intra-Asian differences in drug abuse among major Asian groups. The results of our statistical analysis identify several possible correlates of current Asian drug abuse, including gender, differential association, parental warning, GPA, type of neighborhood, and high-school quality. [ABSTRACT FROM AUTHOR]

Abstract This paper profiles the cost and the profitability potential associated with recycling and reuse of ultrapure rinse waters left over from semiconductor wafer-rinsing processes. An environmental health and safety financial software tool was used to a) account for costs, b) estimate their financial impact, and c) compare the profitability potential of recycling and nonrecycling options. The financial analysis was designed to help environmental health and safety specialists enhance the ways they present the economic soundness of spent-rinse-water recycling to fabrication managers. It was found that the financial software tool provided a flexible, low-maintenance, decision-oriented approach to understanding the full cost of owning water-recycling systems. A financial-analysis case study looked at a typical fabrication facility that processed 480,000 200-millimeter wafers annually, used 500 gallons per minute of ultrapure water, and recycled at 50 percent. Both direct and indirect costs were calculated. The financial analysis showed that the annual incremental cost difference between recycling ($2.03 million) and not recycling ($2.85 million) is approximately $823,878. This annual cost reduction, taken over the 15-year estimated productive/economic life of the system and discounted at 15 percent, with a combined tax rate of 40 percent and a five-year depreciation, results in a net present value of $2,577,212. [ABSTRACT FROM AUTHOR]

Provides information on the 101st Annual Meeting of the Archaeological Institute of America which was held in Dallas, Texas from December 27 to 30, 2000. Awardees at the event; Officers who were elected to the Institute's Governing Board; Abstracts of the research papers at the meeting.

• Novel home appliance scheduling is presented incorporating DERs for demand response. • Risk aversion is applied and compared with the risk-neutral approach by adding CVAR. • GT unified ENNC method is applied for solving multi-objective optimization. • Overall energy cost and gaseous emissions are optimized by the fuzzy compromising method. Due to environmental issues and smart grid development, distributed energy resources, energy storage systems, and demand response (DR) are gaining attention to reduce the pollution and fossil fuel usage. This paper presents a customer's preferences based innovative home appliances scheduling framework considering numerous constraints and DR for scheduling household appliances incorporating local energy grid and energy storage systems, including electrical and thermal energy storage. First, the models of household appliances and air conditioning load are built as the shiftable and non-schedulable loads and a flexible thermal load, respectively. Second, an enhanced normalized normal constraint (ENNC) strategy based on game theory (GT) is presented for a novel home appliance scheduling (HAS) framework with the objectives to optimize consumption cost, end-users comfort, and peak to average ratio. Then, the fuzzy compromising (FCP) method is proposed to optimize overall energy cost and gaseous emissions for the novel HAS framework with a residential local energy grid. In addition to this, conditional value at risk (CVaR) has also been incorporated in the objective function to resolve the sudden absence of distributed energy resources and power failures. Finally, case studies on data from Dallas, Texas, USA are performed, and the simulation results show that the proposed strategy is computationally inexpensive and outperforms other approaches in terms of electricity cost, gaseous emissions, and customer's comfort. The proposed approach gives a significantly lower cost of 104.30 cents and gaseous emissions of about 18.753 kg for an entire day of novel HAS with DR adoption. Thus, it can provide help for DR accomplishment and precise prediction of electricity consumption. [ABSTRACT FROM AUTHOR]

This paper shows how federal resources and mandates concerning the HIV epidemic combined with the political economy and political culture of Dallas, Texas to create a distinctive local HIV/AIDS service system. The infusion of federal funds allowed nonprofit organizations to expand their services, especially in the areas of economic assistance and social services. In additions, funding to minority agencies and services to minority clients were expanded. While the fund administration structure imposed on the nonprofit providers necessitated greater administrative efforts on their part and enhanced the power of local government, it also greatly improved coordination. [ABSTRACT FROM AUTHOR]

Two studies were conducted to explore the following questions: (i) does intimacy, within the context of a couple relationship, contribute to individual need fulfillment?; (ii) does self-disclosure have beneficial effects on need fulfillment without being accompanied by intimacy's others dimensions: positive affective tone and partner listening and understanding?; and (iii) does intimacy's impact on need fulfillment mediate its relationship with physical and psychological well-being? For the first study, 154 commuter university students completed questionnaire measures of well-being and the Need Fulfillment Inventory (NFI), a new paper-and-pencil test that assesses the agentic and communal dimensions of need fulfillment. Results from study 1 showed positive correlations between both agentic and communal need fulfillment and well-being. For the second study, 133 cohabiting couples were asked to complete the NFI, two measures of relational intimacy, five measures of well-being, and to keep a daily record of their interactions for a week. Factor analyses of the daily record data revealed three dimensions of verbally intimate interaction: positive affective tone, daily self-disclosure, and listening and understanding. Results supported the notion that relational intimacy, assessed globally and as a characteristic of the couples’ daily interactions, is positively associated with individual need fulfillment. Self-disclosure's impact on need fulfillment was found to vary as a function of the other dimensions of intimacy present in the interactions. The pattern of moderation between self-disclosure and other dimensions of intimacy was not exactly as predicted, however; sometimes, self-disclosure may soften the detrimental effects of negative interactions on need fulfillment. Finally, the mediational hypothesis was mostly supported, which indicates that intimacy's relationship to psychological well-being is most likely accounted for by its effects on individua... [ABSTRACT FROM AUTHOR]

The article provides information about the twenty-second Annual Meeting of the Southwestern Social Science Association held on April 11 and 12, 1941 at Dallas, Texas. On Friday, April 11, Accounting Luncheon Meeting was held in Room 3. Earl A. Sailers of Louisiana State University was the Chairman. Round-Table Discussion was held on the Present Status of "Principles of Accounting." In sociology section, meeting on "Social Standards in a Changing Society" was held in Room 428. Fred C. Watts of the Oklahoma Baptist University acted as the Chairman. William T. Chambers of Stephen F. Austin College was the chairman for the Geography Section. General discussion on "Industrialization in the Southwest," was presented by Elmer Johnson from the University of Texas and "The Paper and Pulp Industry of Texas," by Victor Schoffelmayer, The Dallas Morning News. In psychology section, meetings were held on "The Relation of Dominance Scores to Level of Aspiration in Mental Test Performance," and "The Influence of Number of Lists to be Learned upon Learning and Retention."

This article presents information on convention program of the Southwestern Social Science Association and the American Business Writing Association joint conference, held in April 1955, in Dallas, Texas. Some of papers presented in the meetings on various topics like accounting, agricultural economics, business administration, sociology, government, geography are: "A Well-Informed and Better-Guided Student," by William P. Carr; "Recent Developments in Accounting Research," by Charles T. Zlatkovich; "Course Content and Conduct," by Emerson O. Henke; "The Southern Farmer and Foreign Trade," by M.D. Woodin; "The Southern Farmer and Current Agricultural Legislation and Regulation," by William A. Faught; "A Comparison of Riparian and Appropriated Water Rights," by Wells A. Hutchins; "A Comparison of Land-Value Theories and the Everyday Operation of the Land Market," by Robert L. Tontz; "Geography of the Rainforest of Western Pichincha and Esmeraldas, Ecuador," by Luis Freile; and others.

Over the last decades, Transit-Oriented Developments (TODs) have stimulated various debates in several contexts including environmental and transportation planning. Scholars have explored the TODs' broad spatial and socioeconomic characteristics; however, very few studies (if at all) have conducted their attributes including mixedland use in regards to noise, particularly when they require such examination. This paper aims to explain and explore TODs' implications associated with noise by comparing them with non-TODs in the Dallas-Fort Worth metroplex area. The data include sound pressure levels (SPLs) and various built environment features through TOD stations and surrounding areas compared with non-TOD stations by performing the grid sampling method. Using a unique two-level hierarchical linear model (HLM), the study examines the impacts of TODs on noise both at micro and macro levels. The findings show that with their features TODs generate higher sound levels with almost 9.0 dB(A) difference. The study provides insights into the relationship between noise, land use, and transportation by discussing their practice and policy implications. • TODs (68.4 dBA) are substantially noisier than non-TODs (56.7 dBA). • The characteristics of TODs significantly affect noise levels, particularly mixed-land use. • Increasing transportation and related facilities of TODs intensify environmental, social, and public health impacts. • TODs result in environmental noise impacts at both micro and macro levels as hierarchical linear model (HLM) computed. [ABSTRACT FROM AUTHOR]

The article focuses on the critical testing of a new apoptosis drug in the U.S. A startup company Joyant Pharmaceuticals in Dallas, Texas, licensed some anticancer compounds from the University of Texas-Southwestern (UTSW). In a September 2004 paper in the journal "Science", UTSW investigators described how one of them killed cancer cell lines (in combination with another compound) by inducing apoptosis, or programmed cell death, at spectacularly low concentrations. Embryologists, over a hundred years ago, were the first to recognize cell death as a necessary process, but the critical importance of apoptosis in eliminating unwanted adult cells only became accepted with the isolation of its molecular components beginning in the 1980s.