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The University of Texas at Dallas has proposed 24 top journals (UTD24) covering all areas related to management. UTD24 are currently the most authoritative management journals. Institutions or research scholars who have published papers in these journals are considered to have a high academic level. This study uses the paper quality published by an institution in the UTD24 journals to indicate the research quality of this institution and takes the papers published by Chinese Business School in the UTD24 journals from 2000 to 2018 as the research object. By analyzing the staged evolution process and the research hotspot of international research collaboration network (IRC network) of Chinese Business School, this paper summarizes and analyzes the factors that influence the quality of papers published by Chinese Business School in UTD24 journals: degree centrality of an institution, betweenness centrality of an institution, the degree of attention of an institution, the degree of novelty of an institution, and the number of countries cooperating with the institution. This paper divides paper quality into two parts: the total number of papers and citations per paper of an institution. Among them, degree centrality and betweenness centrality of the institution have a significant positive impact on the total number of papers of the institution. The degree of attention and the number of countries cooperating with the institution have a significant positive impact on citations per paper, and the degree of novelty has a significant negative impact on citations per paper. [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]

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]

This article presents the hardware and software architectures used to implement the Modbus Extension (ModbusE) IIoT gateway, the performance of the acquisition cycle at the PRU real-time programmable core level, the acquisition cycle communication flow—dispatcher—OPC UA server (Linux)—OPC UA client (Windows) as well as the performance analysis of data communications between the IIoT ModbusE gateway and the OPC UA client (Windows). In order to be able to implement both the ModbusE acquisition cycle and the OPC UA server, the BeagleBone Black Board was chosen as the hardware platform. This board uses the Sitara AM335x processor (Texas Instruments (TI), Dallas, TX, USA) from Texas Instruments. Thus, the acquisition cycle was implemented on the PRU0 real-time core, and the OPC UA server, running under the Linux operating system, was implemented on the ARM Cortex A8 processor. From the analysis of the communication speed of the messages between the OPC UA client and the ModbusE servers, it was found that the ModbusE acquisition cycle speed was higher than the acquisition speed of the OPC UA client. [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]

The COVID-19 pandemic forced many educators and students around the world to shift abruptly from a face-to-face environment to an online learning management system (LMS). This change of environment proved especially difficult for English language learners (ELLs) in the United States. Some of the challenges for ELLs include technology issues, lack of facility with the LMS, limited comprehension of written instructions, time management difficulties, social isolation, and low motivation. This paper discusses those challenges and examines the benefits and shortcomings of using an LMS for lessons, assessments, and communication among ELLs. This qualitative study investigates the experiences of ELL students enrolled in a Dallas, Texas area high school during the COVID-19 pandemic and their attitudes towards completing coursework through an LMS platform. [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]

We propose a macrofinance model that rationalizes robust features in equity index option markets. When rare disasters are followed by economic recoveries, the slope of the implied volatility term structure is positive in good times but turns negative in bad times. Additionally, implied volatility decreases with moneyness in bad times (volatility skew), whereas the shape becomes a smile in good times in the presence of rare economic booms. Our theory contributes to understanding the dynamics of the implied volatility surface yet keeping standard asset-pricing moments realistic. This paper was accepted by Gustavo Manso, finance. Funding: The authors are grateful to HEC Montreal, the University of Texas at Dallas, and particularly to the Canadian Derivatives Institute for generous financial support. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4587. [ABSTRACT FROM AUTHOR]

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

Are we contributing positively to the society at large by research that we conduct in the field of Operations Management? Currently, the answer is probably closer to "no" than to "yes." We often do not realize it, but there is very real cost of conducting our research nonresponsibly. In this invited OM Forum contribution, which is based on my Manufacturing and Service Operations Management Distinguished Fellow lecture given at the University of Texas at Dallas in 2018, I discuss what I believe it means to conduct research responsibly, I offer some specific steps to improve the relevance of what we do, and I argue that this approach gives our field a new opportunity to make broader impact by expanding the horizon of our work. History: This paper has been accepted for the Manufacturing & Service Operations Management Special Section on Responsible Research in Operations Management. [ABSTRACT FROM AUTHOR]

As a point of departure for this special issue of the journal, we turned to Clive Dilnot's seminal two-part essay, ‘The State of Design History’, published in Design Issues. In these essays, Dilnot declares the imperative to place ‘socio-historical understanding’ at the centre of our ‘attempts to understand design activity’. Twenty-five years on the prescience of this call is underlined by the fact that scholarship has become more interdisciplinary, and the geographical foci of global discourses have been reassessed, certainly beyond Euro-American concerns. This development is evident in the themes and content of more recent Design History Society conferences, such as the 2009 conference on design writing. To bring the debate both closer to home for us and into another forum, we convened and co-chaired a panel entitled ‘The Current State of Design History’ for the Design Studies Forum, held at the 2008 College Art Association (CAA) annual conference in Dallas, Texas. From the submissions, received from scholars working in the UK, Europe, Australia and the USA., we chose papers which together would present a diversity of perspectives and provide directions for the future. The essays contained in this issue are revised versions of some of the papers presented in that session. We also asked Clive Dilnot to reflect on the essays and on what he saw as the potential futures for design history. This introduction serves to place these contributions within the larger context of design history. [ABSTRACT FROM PUBLISHER]

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]

Magnum Hunter Resources Corporation (MHRC) was an oil and gas company headquartered near Dallas, TX. Although the company grew rapidly through acquisitions, the accounting department did not keep pace with the company's growing size and sophistication. Management identified this as an internal control deficiency (ICD) prior to issuing the 2011 financial statements but did not disclose it because management underestimated its severity. The company later disclosed multiple material weaknesses when it restated its financial statements. This case study is designed for use in the undergraduate or graduate audit classroom to examine the classification and disclosure requirements for ICDs. After completing this case study, students will be able to apply professional standards to classify ICDs; critique the decision-making process of management, consultants, and auditors tasked with evaluating ICDs; and consider the impact of material weakness disclosure on investors. JEL Classifications: M41; M42. [ABSTRACT FROM AUTHOR]

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

A major concern in the ongoing debate over school choice is whether private schools help to increase their students' levels of tolerance necessary for a functioning democracy in the United States. Over 40 years ago, scholars at the University of Minnesota created a survey which measured political knowledge, political tolerance, perceived threats from opposing groups, and support for democratic norms anchored in each respondent's view of the political group they find most distasteful. In 1997, researchers at various universities used a similar survey instrument to derive responses from students in eighth-grade social studies classes who were enrolled in seven public and twenty-four private schools in New York City and Dallas/Fort Worth, Texas. Those original data remained archived and unexamined for decades. We analyze those data using Ordinary Least Squares (OLS) and rigorous Nearest Neighbor Matching (NNM) methods based on propensity scores. We find that students who attended private schools demonstrate higher levels of political knowledge and stronger support for democratic norms when compared to observationally similar students who attended public schools. [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]

The article presents a recording of the minutes from the American Risk and Insurance Association (ARIA) midyear board of directors meeting on February 22, 1985 that was held at the Dallas/Fort Worth Airport Hilton Hotel. Among the topics included were the 1985-86 budget, an update on the number of papers submitted for the annual meeting, the announcement that an educational speaker for the annual meeting will no longer be funded by the Insurance Information Institute, a report form the Membership Committee, a site for the 1989 annual Meeting was announced as a resort-type location in Denver, and David Klock was announced as the New Executive Director.

This paper examines the determinants of industrial property value. We use the factor-analytic linear structural relations (LISREL) model to confront measurement problems associated with related work. A simultaneous test of the effects on property value of factors summarizing physical property, national market, focal market, interest rate and location variables is performed. Findings indicate that the value of industrial buildings during 1987-1991 in the Dallas/Fort Worth area is primarily related to local market effects and to physical characteristics and location of the property. [ABSTRACT FROM AUTHOR]

Background: In the United States, cardiovascular diseases (CVD) are the leading cause of death and disability in women. CVD-modifiable risk factors, including poor diet quality and inadequate physical activity, can be addressed through evidence-based interventions (EBIs). Strong Hearts Healthy Communities (SHHC) is an EBI that has demonstrated effectiveness in reducing CVD risk and improving health outcomes among rural white women. The aims of this study were to understand the general health, diet, and physical activity-related needs and goals of women living in an urban community, to inform the tailoring and adaptation of the SHHC EBI to an urban setting and more diverse population. Methods: Focus groups (FGs) were conducted with African American/Black and Hispanic/Latinx women in the Dallas metropolitan area who had a BMI ≥ 25 kg/m2 and engaged in ≤ 150 min per week of moderate physical activity. The data were coded using a team-based, deductive, and thematic analysis approach, that included multiple coders and in-depth discussions. Results: Four FGs with a total of 18 participants (79% Black and 21% Latinx) were conducted, and three themes were developed: (1) participants had adequate knowledge and positive attitudes towards healthy living but faced many barriers to practicing healthy behaviors; (2) culturally-based beliefs and community practices exerted a strong influence on behaviors related to food and stress, revealing barriers to healthy eating and generational differences in stress and stress management; (3) participants desired a more individualized approach to nutrition and physical activity interventions that included familiar and enjoyable activities and social support centered around shared health goals. Conclusions: The SHHC intervention and similar health programs for Black/African American and Hispanic/Latinx women in urban settings should emphasize individualized nutrition and practical skills for healthy eating with accessible, familiar, and enjoyable exercises. Additionally, stress management strategies should be culturally and generationally sensitive and social support, whether through family, friends, or other program participants, should be based on shared health goals. [ABSTRACT FROM AUTHOR]

A pentatomid bug Bathycoelia indica Dallas, 1851 is reported as a pest of pomegranate plantation in Maharashtra (India). Brief re-description of the species, including that of male and female genitalia, eggs, some nymphal stages and live adults, with many digital illustrations, is provided. [ABSTRACT FROM AUTHOR]

Background: Food pantry clients have high rates of food insecurity and greater risk for and prevalence of diet-related diseases. Many clients face time, resource, and physical constraints that limit their ability to prepare healthy meals using foods typically provided by pantries. We compared two novel approaches to alleviate those barriers and encourage healthier eating: meal kits, which bundle ingredients with a recipe on how to prepare a healthy meal, and nutritious no-prep meals, which can be eaten after thawing or microwaving. Methods: Participants were adult pantry clients from a large food pantry in the Southern sector of Dallas, Texas. We conducted a repeated measures between-subjects study with 70 clients randomized to receive 14-days of meal kits (n = 35) or no-prep meals (n = 35). Participants completed questionnaires at baseline and two-week follow-up on demographics, hedonic liking of study meals, perceived dietary quality, and food security. Two-way repeated measures analysis of variance was used to examine group and time effects, and group by time interactions. We also describe feasibility and satisfaction outcomes to inform future implementation. Results: Sixty-six participants completed the study (94%). Participants were predominantly Hispanic or Latino(a) (63%) and African American or Black (31%) women (90%). There was a significant interaction on hedonic liking of study meals (ηp²=0.16, F(1,64) = 11.78, p <.001), such that participants that received meal kits had greater improvements in hedonic liking over time than participants in the no-prep group. We observed significant improvements in perceived dietary quality (ηp²=0.36, F(1,64) = 36.38, p <.001) and food security (ηp²=0.36, F(1,64) = 36.38, p <.001) across both groups over time, but no between group differences or significant interactions indicating one intervention was more effective than the other. Program satisfaction was high across both groups, but higher among the meal kit group (ηp²=0.09, F(1,64) = 6.28, p =.015). Conclusions: Results suggest nutritious meal kits and no-prep meals may be desirable nutrition intervention strategies for pantry clients and have potential to increase food security and perceived dietary quality in the short-term. Our findings are limited by a small sample and short follow-up. Future studies should continue to test both interventions, and include longer follow-up, objective measures of dietary quality, and relevant clinical outcomes. Trial registration: This trial was registered on 25/10/2022 on ClinicalTrials.gov, identifier: NCT05593510. [ABSTRACT FROM AUTHOR]

Extreme precipitation has become more frequent and intense with time and space. Infrastructure design tools such as Intensity-Duration-Frequency (IDF) curves still rely on historical precipitation and stationary assumptions, risking current and future urban infrastructure. This study developed IDF curves by incorporating non-stationarity trends in precipitation annual maximum series (AMS) for Dallas–Fort Worth, the fourth-largest metropolitan region in the United States. A Pro-NEVA tool was used to develop non-stationary IDF curves, taking historical precipitation AMS for seven stations that showed a non-stationary trend with time as a covariate. Four statistical indices—the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Square Error (RMSE), and Nash–Sutcliffe Efficiency (NSE)—were used as the model goodness of fit evaluation. The lower AIC, BIC, and RMSE values and higher NSE values for non-stationary models indicated a better performance compared to the stationary models. Compared to the traditional stationary assumption, the non-stationary IDF curves showed an increase (up to 75%) in the 24 h precipitation intensity for the 100-year return period. Using the climate change adaptive non-stationary IDF tool for the DFW metroplex and similar urban regions could enable decision makers to make climate-informed choices about infrastructure investments, emergency preparedness measures, and long-term urban development and water resource management planning. [ABSTRACT FROM AUTHOR]

The neotropical Menenotus Laporte, 1832 includes M. lunatus (Laporte, 1832) and M. diminutus Walker, 1871. The genus has never been reviewed, and only the brief original descriptions were available so far. In this paper, we review Menenotus and describe, for the first time, genital traits of both sexes. Menenotus lunatus and M. diminutus are distinguishable by the shape of pronotum, the color pattern of connexivum, the extension of the cuplike sclerite, and the shape of the parameres, among other traits. In addition, Menenotus is compared with Euagona Dallas, 1852, which shares the prominent and curved humeri. These genera can be distinguished by the broader abdomen and the apparent connexivum in Menenotus. Their distribution pattern is different, with Euagona showing a more northern distribution in South America than Menenotus. We also updated the distribution records in Brazil, providing a map to the species of Menenotus. [ABSTRACT FROM AUTHOR]

The author reflects on the issues about preventive dentistry modalities such as dental flossing and brushing discussed during the meeting of the American Public Health Association in 1983 in Dallas, Texas. According to the author, engaging in such dental modalities does not contribute in reducing the amount of dental decay. The findings have been an important implication for the public health despite the fact that no abstract or manuscript was submitted.

Down payment or closing cost assistance is an effective program in addressing the wealth constraints of low‐and moderate‐income homebuyers. However, the spillover effect of such programs on the neighborhood is unknown. This paper estimates the impact of the City of Dallas Mortgage Assistance Program (MAP) on nearby home values using a hedonic model of home sales from 1990 to 2006. We define neighborhoods of 1,000 feet around each sale and estimate the average differences in sales prices between neighborhoods with various numbers of MAP properties before and after their appearance. We find that MAP properties tend to locate in neighborhoods with lower property values; however, unless a concentration of MAP properties forms, the infusion of MAP properties has little detrimental impact on neighboring property values. Moreover, low concentration of MAP properties has a modest positive impact on surrounding property values. © 2010 by the Association for Public Policy Analysis and Management. [ABSTRACT FROM AUTHOR]

In this study, we develop a method that assigns acoustic signals with Automatic Dependent Surveillance-Broadcast (ADS-B) data to build a labeled dataset of acoustic signals from aircraft without expensive ground-truth experiments. An exploration of the resultant labeled dataset enables an assessment of the acoustic characteristics from three types of aircraft. The fusion framework is evaluated using data from an acoustic sensor and collocated ADS-B receiver in the middle of a large urban area at Southern Methodist University in Dallas, Texas. Our results demonstrate the benefit of combining multiple types of data to generate a labeled dataset leveraging open-source aircraft surveillance data. By studying three classes of aircraft, we find that the smaller fixed wing single engine (FWSE) class is mostly detected within approximately 5000 m, while the larger fixed wing multi-engine (FWME) class is commonly detected out to greater distances above 7500 m. The FWSE class has a median source frequency at 100 Hz, compared to FWME class with median source frequency at 80 Hz, while rotorcraft has a source frequency falling into a lower range of 30–100 Hz. [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]

Information about several papers discussed at the National Simulation Conference held in Dallas, Texas on January 19-21, 1956 is presented. The thirty-five papers from nationwide sources presented largely on the design of special physical-simulation devices. There are also papers which discuss simulation in real time on digital computers.

This paper reports on a study of the prices paid by blacks and whites for housing in Dallas in 1960. The technique used to compare the price of housing with different dimensions of characteristics was to estimate implicit prices of characteristics bought by blacks and whites. Two comparisons were made. The first was based on a unit with the average of all black characteristics. The second was based on a unit with the average of all white characteristics. No statistically significant differences were found. This study represents an effort to identify a difference in the prices paid by blacks and whites for housing by identifying differences in the price paid for common characteristics. The estimation of implicit prices resulted in the prices of some characteristics being higher in the white sample, some higher in the black sample. Two indexes were created, one using black housing characteristics as a base, one using white housing characteristics as a base. For the former, we found the price of white housing to be 4 percent higher. For the latter, we found the price of black housing to be 0.3 percent higher. Neither difference was statistically significant. The results obtained are, of course, peculiar to Dallas. It may be of interest to compare the population characteristics of Dallas with other cities. The nonwhite population of Dallas in 1960 was 19 percent of the total population. This may be compared with a 14 percent nonwhite population of New York and 23.6 nonwhite population for Chicago. The nonwhite population of the Dallas SMSA grew by 56 percent (as compared with 44 percent for the white population) during the period from 1950 to 1960. (Figures for the city lack some meaning because of the incorporation of new areas into the city.) This increase was greater than that for Saint Louis (36 percent) or Washington D.C. (44 percent) but less than that for Chicago (66 percent). While it is difficult to draw conclusions about housing demand from popula... [ABSTRACT FROM AUTHOR]

Water ponding and pluvial flash flooding (PFF) on roadways can pose a significant risk to drivers. Furthermore, climate change, growing urbanization, increasing imperviousness, and aging stormwater infrastructure have increased the frequency of these events. Using physics-based models to predict pluvial flooding at the road segment scale requires notable terrain simplifications and detailed information that is often not available at fine scales (e.g., blockage of stormwater inlets). This brings uncertainty into the results, especially in highly urbanized areas where micro-topographic features typically govern the actual flow dynamics. This study evaluates the potential for flood observations collected from Waze – a community-based navigation app – to estimate the likelihood of PFF at the road segment scale. We investigated the correlation of the Waze flood reports with well-known flood observations and maps, including the National Flood Hazard Layer (NFHL), high watermarks, and low water crossings data inventories. In addition, highly localized surface depressions and their catchments are derived from a 1 m resolution bare-earth digital elevation model (BE-DEM) to investigate the spatial association of Waze flood reports. This analysis showed that the highest correlation of Waze flood reports exists with local surface depressions rather than river flooding, indicating that they are potentially useful indicators of PFF. Accordingly, two data-driven models, empirical Bayes (EB) and random forest (RF) regression, were developed to predict the frequency of flooding, a proxy for flood susceptibility, for three classes of historical storm events (light, moderate, and severe) in every road segment with surface depressions. Applying the models to Waze data from 150 storms in the city of Dallas showed that depression catchment drainage area and imperviousness are the most important predictive features. The EB model performed with reasonable precision in estimating the number of PFF events out of 92 light, 41 moderate, and 17 severe storms with 0.84, 0.85, and 1.09 mean absolute errors, respectively. This study shows that Waze data provide useful information for highly localized PFF prediction. The superior performance of EB compared to the RF model shows that the historical observations included in the EB approach are important for more accurate PFF prediction. [ABSTRACT FROM AUTHOR]

As part of an effort to observe and study ionospheric disturbances and their effects on radio signals used by Global Navigation Satellite Systems (GNSS), alternative low-cost GNSS-based ionospheric scintillation and total electron content (TEC) monitors have been deployed over the American sector. During an inspection of the observations made on 28 August 2022, we found increases in the amplitude scintillation index (S4) reported by the monitors for the period between approximately 17:45 UT and 18:20 UT. The distributed, dual-frequency observations made by the sensors allowed us to determine that the increases in S4 were not caused by ionospheric irregularities. Instead, they resulted from Carrier-to-Noise (C/No) variations caused by a solar radio burst (SRB) event that followed the occurrence of two M-class X-ray solar flares and a Halo coronal mass ejection. The measurements also allowed us to quantify the impact of the SRB on GNSS signals. The observations show that the SRB caused maximum C/No fadings of about 8 dB-Hz (12 dB-Hz) on L1 ~ 1.6 GHz (L2 ~ 1.2 GHz) for signals observed by the monitor in Dallas for which the solar zenith angle was minimum (~24.4°) during the SRB. Calculations using observations made by the distributed monitors also show excellent agreement for estimates of the maximum (vertical equivalent) C/No fadings in both L1 and L2. The calculations show maximum fadings of 9 dB-Hz for L1 and of 13 dB-Hz for L2. Finally, the results exemplify the usefulness of low-cost monitors for studies beyond those associated with ionospheric irregularities and scintillation. [ABSTRACT FROM AUTHOR]

Distributed arrays of ground-based instruments can help advance observations and improve understanding of space weather. The implementation of an array of sensors can be constrained, however, by the high cost of commercial instruments and the availability of Internet and power. Additionally, distributed observations require sensors that can be easily deployed and maintained. As part of an effort to expand the breath of skills of physics students while increasing literacy about space weather, a team of undergraduates was formed and tasked with designing, building, and testing an autonomous platform for ionospheric observations using ScintPi 3.0. ScintPi 3.0 is a low-cost ionospheric scintillation and total electron content (TEC) monitor. The design led to a platform that employs cellular-based Internet connectivity as well as solar and battery power. A fully functional prototype was built and deployed near Dallas, USA (32.9° N, 96.4° W). Results show that the platform can run for 232 hours using battery only or indefinitely when connected to the selected solar photovoltaic panel. For system monitoring, LTE functionality enables near real-time updates of the systems' health and remote shell access. Examples of observations made by the prototype are presented, including the detection of ionospheric effects caused by a space weather event. Additionally, the potential of the system for research, education, and citizen science initiatives are discussed. [ABSTRACT FROM AUTHOR]

Continuous and discrete streamflow data were combined with waterborne self-potential, surface-water temperature, and surface-water conductivity surveys obtained along an approximately 43-kilometer (26.7 mile) surveyed reach of the Elm Fork Trinity River (hereinafter referred to as "Elm Fork") upstream from Dallas, Texas, to investigate areas of gaining and losing streamflow under various streamflow and seasonal climatic conditions. Discrete streamflow measurements were made at 17 locations on October 12, 2021, and January 25, 2022, at 19 locations on May 17, 2022, and at 18 locations on August 9, 2022. Waterborne self-potential data were measured from a kayak in January 2022 during a period of base flow along three individually surveyed reaches between the Lake Lewisville Dam and Frasier Dam on the Elm Fork. Together, these data indicated different parts of the Elm Fork functioned as either a gaining or losing stream depending on streamflow and seasonal climatic conditions. Overall, there were estimated net gains in streamflow during the first two discrete-measurement events of about 107 and 2 cubic feet per second in October 2021 and January 2022, respectively, and estimated net losses in streamflow in May 2022 and August 2022 of about 24 and 18 cubic feet per second, respectively. [ABSTRACT FROM AUTHOR]

Introduction: Texas Health Resources (THR), a large, nonprofit health care system based in the Dallas‐Fort Worth area, has collaborated with the University of Texas Southwestern Medical Center (UTSW) to develop and operate a unique, integrated approach for Learning Health System (LHS) workforce development. This training model centers on academic health system faculty members conducting later‐stage translational research within a partnering regional care delivery organization. Methods: The THR Clinical Scholars Program engages early career UTSW faculty members to conduct studies that are likely to have an impact on care delivery at the health system level. Interested candidates submit formal applications to the program. A joint committee comprised of senior research faculty from UTSW and THR clinical leadership reviews proposals with a focus on the shared LHS needs of both institutions—developing high quality research output that can be applied to enhance care delivery. A key prioritization criterion for funding is the degree to which the research addresses a question relevant to THR as a high‐volume network with multiple channels for consumers to access care. The program emphasis is on supporting embedded research initiatives using health system data to generate knowledge that will improve the quality and efficiency of care for the patient populations served by the participant organizations. Results: We discuss specific strategic and tactical components of the THR Clinical Scholars Program including an overview of the academic affiliation agreement between the collaborating organizations, criteria for successful program applications, data sharing, and funding. We also share project summaries from selected clinical scholars as examples of the LHS research done in the program to date. Conclusion: This experience report provides an implementation framework for other academic health systems interested in adopting similar LHS workforce training models with community partners. [ABSTRACT FROM AUTHOR]

Presented are phencyclidine (PCP)-positive cases received by the Toxicology Laboratory at the Southwestern Institute of Forensic Sciences from local law enforcement agencies and the Office of the Medical Examiner (OME) between 1 January 2015 and 31 December 2020. Of the 43,940 requests for testing received during that time, 898 (2.04%) were positive for PCP. These cases were evaluated for PCP concentration, additional/concurrently reported drug concentrations and demographics. For ME cases, the cause and manner of death were also evaluated. Although the number of requests received by the Toxicology Laboratory increased each year, the percentage positive for PCP remained consistent. Subjects ranged from 18 to 71 years old (median 48 years) and were predominantly black (94.19%) and male (78.49%). PCP concentrations for all case types ranged from 0.02 to 2.33 mg/L (median 0.05 mg/L); driving while intoxicated (DWI) cases ranged from 0.02 to 0.14 mg/L (median 0.04 mg/L) and ME cases ranged from 0.02 to 2.33 mg/L (median 0.13 mg/L). In addition to PCP, one or more drug(s) or metabolite(s) was identified concurrently in 69.49% of cases. Cannabinoids were the most frequently detected (39.8%), followed by cocaine and its metabolites (22.0%) and ethanol (18.5%). Results were similar when comparing the additional drugs reported in ME and DWI cases. PCP concentrations in ME samples were generally higher, especially for stimulant drugs. Of the 264 ME cases positive for PCP, the manner of death was determined to be an accident for the majority of cases (62.54%), and the most common cause of death was drug toxicity (35.61%). The results from this study facilitate comparison of laboratory- or region-specific data sets, help determine whether laboratory scopes meet testing needs, contribute to reference ranges and provide the foundation for well-informed policy decisions. [ABSTRACT FROM AUTHOR]

Editorial. Comments on the Second Annual Meeting of the Association of Managerial Economists in Dallas, Texas. Themes of the meeting; Venue of the meeting; Involvement of the editors and association office-holders.

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]

Winter–spring greenhouse vegetable production is limited by low-level natural light, resulting in decreased growth and quality. To investigate whether short-term pre-harvest supplemental lighting (SL) with light emitting diodes (LEDs) can address this issue, a study was conducted in a greenhouse in Dallas, Texas. Red leaf lettuce (Lactuca sativa L. 'Red Mist') plants grown in a hydroponic system were treated with daytime or nighttime SL with red (R) and blue (B) LEDs (RB-LED), blue and UVA LEDs (B/UVA-LED), or white LEDs (W-LED) for three days before harvest and compared to those without SL (control). All SL treatments provided a photon flux density of 167 μmol·m−2·s−1 for 12 h daily. Compared with the control, SL treatments increased leaf thickness and greenness, antioxidant capacity, and concentrations of phytonutrients such as anthocyanins, carotenoids, and total phenolics; however, shoot fresh biomass and total leaf area were generally not affected by SL. There were no differences in all of the above traits among W-LED, RB-LED and B/UVA-LED. Compared with daytime SL, nighttime SL increased leaf greenness and carotenoid concentration. In summary, all three LEDs with different spectra were effective in improving lettuce quality as short-term pre-harvest SL sources and nighttime SL was more effective than daytime SL; however, plant fresh weight and total leaf area were not affected. [ABSTRACT FROM AUTHOR]

Maintaining an adequate water supply is one of the key challenges faced by the Dallas-Fort Worth Metroplex, where increasing population and rising water demand have elevated the vulnerability of the communities to water shortages. We conducted a preliminary study exploring the possibility of converting flood storage in the Joe Pool Lake to improve water supply reliability and achieve better cost efficiency. This study employs a mixed integer linear programming approach that considers the costs of using flood storage conversion to meet water needs over the northern portion of the Trinity River Basin. It includes tradeoffs between capturing and storing runoff versus return flow from the wastewater treatment facilities of the Trinity River Authority. A set of hypothetical prices and demand figures with the period of record of 1940-1996 was considered to test the mixed integer linear programming model. Results from the mixed integer linear programming produce an optimal strategy that increases the firm yield of Joe Pool Lake and associated storage-diversion on an annual basis. Also, the outcomes of the analyses of the results suggest that while the conversion would have a positive impact on water availability, a lower expansion cost of $20 per acre-foot per year would be required to produce sufficient cost savings. [ABSTRACT FROM AUTHOR]

The given article considers results of experimental measurements, productivity comparison and master controller executive system of flat-plate solar collector with thermosiphon circulation and flat solar collector with special chemical coating. There has been developed master controllers control module, which receives data from temperature and lighting sensors, obtained in operation process. The aim of the research is getting the solar collectors' optimal parameters, representing maximal usage performance index, controllability, as well as, construction type, allowing energy saving. In the recent years flat-plate solar collectors with chemical coating are characterized with higher efficiency in real conditions usage. The developed master controllers' executive system is used for monitoring the installation 's main parameters, as well, it permits to compare characteristics of solar collector with thermosiphon circulation those of flat-plate solar collector with chemical coating. The obtained experimental data has shown, that flat solar collectors, using chemical coating as a transfer medium in solar heat supply system, have an advantage in the context of usage effectiveness. The heat output and water heating in a flat solar collector are calculated, which vary depending on the intensity of solar radiation. The thermal efficiency of a flat solar collector with a thermosiphon tank based on the Mojo V3 platform using Dallas sensors is calculated. [ABSTRACT FROM AUTHOR]

Phenomenology has remained a sheltering place for those who would seek to understand not only their own "first person" experiences but also the first person experiences of others. Recent publications by renowned scholars within the field have clarified and extended our possibilities of access to "first person" experience by means of perception (Lingis, 2007) and reflection (Zahavi, 2005). Teaching phenomenology remains a challenge, however, because one must find ways of communicating to the student how to embody it as a process rather than simply to learn about it as a content area. Another challenge issues from the fact that most writings on applied phenomenology emphasize individual subjectivity as the central focus, while offering only indirect access to the subjectivity of others (for example, by way of analyzing written descriptions provided by the individual under study). While one finds in the literature of psychotherapy plentiful elucidations of the "we-experience" within which therapists form impressions of their clients' experience, there is still need for a more thoughtful clarification of our rather special personal modes of access to the experience of others in everyday life. This paper will present "second person perspectivity" as a mode of resonating with the expressions of others and will describe class activities that can bring students closer to a lived understanding of what it means to be doing phenomenology in the face of the other. [ABSTRACT FROM AUTHOR]

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]

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:

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.

Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30 minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement. Traffic demand is not the only factor that contributes to terminal congestion, because temporary changes to the road network, such as a lane closure, can make benign traffic demand highly congested. Combining a demand forecast with a traffic microsimulation framework provides a complete picture of traffic and its consequences. The result is an operational intelligence platform for exploring policy changes, as well as infrastructure expansion and disruption scenarios. To demonstrate the value of this approach, we present results from a case study at DFW Airport assessing the impact of a policy change for vehicle routing in high demand scenarios. This framework can assist airports like DFW as they tackle daily operational challenges, as well as explore the integration of emerging technology and expansion of their services into long term plans. • Introduce and evaluate methods for airport traffic demand forecasting. • Create a microsimulation of the Dallas Fort-Worth International Airport. • Combine the demand forecast with the microsimulation in order to provide a complete picture of traffic and its consequences. • The result is an operational intelligence tool for exploring policy changes and infrastructure expansion scenarios. [ABSTRACT FROM AUTHOR]

• 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]