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In 2015, The Learning Center, a consumer health library at MD Anderson Cancer Center, embarked on a project to translate paper pathfinders into online Recommended Resources in Springshare’s LibGuides platform. This project was successfully undertaken by a small staff of librarians and health education specialists with a range of technical skills and allowed online access to resources available both online and in The Learning Center. This article briefly addresses the activities and decisions leading up to the adoption of LibGuides, outlines the process of creating more than 40 online Recommended Resources, and describes the outcomes to date. [ABSTRACT FROM AUTHOR]

Background: Human papillomavirus (HPV) infections can cause cancers of the cervix, vagina, vulva, penis, anus, and oropharynx. The most recently approved HPV vaccine, Gardasil-9, protects against HPV infection and can prevent HPV-associated invasive cancers. However, Gardasil-9 is one of the most underused vaccines in the US today. Young adults are at risk for HPV infection, but many are not vaccinated. This study uses a randomized controlled trial (RCT) to test an innovative multilevel intervention to increase HPV vaccination rates among young adults. In this paper, we describe the research protocol. Methods: The study uses a two by three factorial design. A total of 1200 young adults in Texas, age 18–26 years, who have not been previously fully vaccinated against HPV will be randomly assigned to one of six conditions to receive: (1) standard CDC information about HPV vaccination (control); (2) video narratives about HPV vaccination; (3) written narratives about HPV vaccination; or (4–6) enhanced access to HPV vaccine combined with (4) standard CDC information, (5) video narratives, or (6) written narratives. The two primary outcomes are the rate of HPV vaccination initiation by 3-month follow-up and rate of HPV vaccination completion by 9-month follow-ups. We will determine the impact of the individual level intervention (i.e., persuasive narratives through video or written format), the systemic level intervention (i.e., enhanced access to HPV vaccines), and the combination of both levels, on HPV vaccination initiation and completion. We will also use purposive sampling to select participants to take part in semi-structured interviews/focus groups to better understand the mechanisms of the intervention. Discussion: Recruitment and data collection began in March 2022. We expect to complete data collection by March 2026. We expect that narratives, enhanced access, and the combination of both will improve HPV vaccination initiation and completion rates among young adults. If proven successful, these individual- and system-level interventions can be easily disseminated in regions with low HPV vaccination rates to improve HPV vaccination, and ultimately decrease HPV-related cancer burden. Trial Registration: NCT05057312. [ABSTRACT FROM AUTHOR]

In 2020, Texas was overrepresented in food insecure households. One avenue many food insecure households take to subsidize their food intake is the use of food pantries. Previous literature has identified many efforts to incorporate nutritional information and foods at pantry sites. However, few have considered how religious affiliation can impact organizational structure and agents in regards to nutritional focus. The purpose of this paper is to investigate perceptions of nutritional information, behaviors, and policies of the volunteers at our research sites and the how pantry operations impact the deployment of that information to clients. Our research question asks how do the religious elements of our research sites impact nutritional policy and concerns of food pantries? Using analysis of field notes generated from participant observation at 5 of the religiously-affiliated food pantries in Brazos County, TX, and a verbal survey on organizational nutrition policy administered to food pantry volunteers, we find that religious cultures at these food pantries create barriers to nutrition complementary to hegemonic nutrition. Our findings suggest that interventions targeting the improvement of organizational nutrition policy at local food pantries must consider organizational culture more critically, particularly religious elements. [ABSTRACT FROM AUTHOR]

The goal for the next generation of terrestrial reference frames (TRF) is to achieve a 1-mm- and 0.1-mm/yr-accurate frame realization through the combination of reference station solutions by multi-technique geodetic observatories. A potentially significant source of error in TRF realizations is the inter-system ties between the instruments at multi-technique stations, usually independently determined through ground-based local surveying. The quality of local tie surveys is varied and inconsistent, largely due to differences in measurement techniques, surveying instruments, site conditions/geometries, and processing methods. The Global Geodetic Observing System (GGOS) has tried to address these problems by issuing guidelines for the construction and layout of future multi-technique observatories, promoting uniformity and quality while minimizing existing problems with local surveying that are exacerbated over longer baseline distances. However, not every observatory is going to be able to completely satisfy these guidelines, and in this work, a successful endeavor to satisfy the accuracy goals while exceeding the GGOS baseline guideline is detailed for the McDonald Geodetic Observatory (MGO) in the Davis Mountains of Texas, USA. MGO consists of a VLBI Geodetic Observing System (VGOS), infrastructure in place for a Space Geodesy Satellite Laser Ranging (SGSLR) telescope, and several Global Navigation Satellite Systems (GNSS) stations spanning a 900 m baseline and a 120 m elevation change. The results of the local ties between the GNSS stations across the near-kilometer baseline, as measured from their antenna reference points, show sub-mm precision and 1 mm accuracy validated through repeatability across several surveys conducted in 2021as well as 1 mm consistency with the monthly averaged daily solutions of the GNSS-based positioning. In this paper, we report these results as well as the framework of the surveys with sufficient detail and rigor in order to give confidence to the quality claims and to present the novel design and techniques employed in the procedure, processing, and error-budget analysis, which were determined through iterative research methods across repeated survey campaigns. [ABSTRACT FROM AUTHOR]

Financial exploitation (FE) is one of the most common reports to Adult Protective Services (APS) and the cases are often complex. Consequently, APS caseworkers report FE investigations to be among the most difficult while simultaneously reporting low confidence in productive outcomes for these investigations. This necessitates finding ways to support APS FE investigations. This paper describes the structure, process, and formative findings of a collaboration between forensic accounting examiners and APS workers to investigate complex cases of FE. Among the 77 FE cases completed, forensic examiners reviewed multiple years of financial records which included over 101,000 transactions, totaling over $213,000,000.00 in finances, and identified over $8,000,000 in questionable activity. Scores on the 8-item Client Satisfaction Questionnaire were high indicating high program satisfaction by APS workers, subject matter experts, and forensic examiners. These findings support the feasibility and acceptability of forensic accounting and APS collaborations to investigate complex cases of FE. [ABSTRACT FROM AUTHOR]

A sewer system is a principal element of infrastructure in modern cities, accounting for massive amounts of public investments. Corrosion of manholes in the sewer system is a global issue, and millions of dollars are being spent on the maintenance, restoration, and replacement of deteriorated sewer networks. Concrete manholes in the sewer system are deteriorating due to the attack of sulfuric acid produced by microorganisms in a process termed microbial induced concrete corrosion (MICC), which reduces the lifespan of concrete sewer elements. The objective of this paper is to investigate the correlation between the gas- and liquid-phase sewer environmental factors and hydrogen sulfide concentration in the gas phase. The production, emission, and build-up of hydrogen sulfide gas in manholes is identified as a major cause of MICC in manhole shafts. The field study was conducted in more than 200 manholes in the City of Arlington (Texas, US). The data was collected every minute for 48 h to understand the trends of liquid- and gas-phase parameters such as hydrogen sulfide (H2S concentration), liquid and gas temperature, pH, DO, and relative humidity. The study also examines how gas-phase H2S concentrations vary with season; manhole design, including manholes' depth, slope, and presence of drop; and sewer flow conditions such as velocity and turbulence. Although no strong linear correlation was found between liquid-/gas-phase parameters, the manhole categories were found to play a significant role in H2S generation. The manholes with hydraulic jump generated the highest average H2S concentrations, followed by manholes with drops. High turbulence zones were observed in manholes of both categories, leading to H2S stripping from liquid to gas phase. The highest H2S concentration was recorded in summer, suggesting that higher liquid temperature resulted in increased bacterial activity, which generated greater liquid-phase sulfide. Greater Henry's law constants in summer, due to high temperatures, would have favored transfer of liquid-phase sulfide to the gas phase. [ABSTRACT FROM AUTHOR]

States have adopted a variety of policies to encourage universities to expand research production, with the hope of supporting economic growth and competitiveness. This paper considers whether a state-level initiative succeeded in influencing university-based research outputs among regional public universities. We test whether the Texas Research Incentive Program increased research production at a set of state universities as measured by total research spending, federally-funded research spending, the number of scholarly publications, and the share of publications published in high impact factor journals. Using a novel dataset and difference-in-differences analytic strategy, we found that TRIP adoption was associated with a 19%-25% increase in research expenditures at emerging research universities in Texas relative to a matched set of comparable universities. However, TRIP did not influence federally-funded research expenditures or journal publication outputs. We also show that federally-funded research expenditures influence publication outputs — both in amount and quality — and that number of full-time faculty influences both federal research expenditures and publication outputs. We discuss contributions to the literature on regional public universities, loose coupling, and research production, as well as implications for policy. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D), depth-averaged shallow water equation (SWE) models are routinely used to simulate flooding in coastal areas – areas that often include vast networks of channels and flood-control topographic features and/or structures, such as barrier islands and levees. Adequately resolving these features within the confines of a 2D model can be computationally expensive, which has led to coupling 2D simulation tools to less expensive one-dimensional (1D) models. Under certain 1D–2D coupling approaches, this introduces internal constraints that must be considered in the generation of the 2D computational mesh used. In this paper, we further develop an existing automatic unstructured mesh generation tool for SWE models, ADMESH+, to sequentially (i) identify 1D constraints from the raw input data used in the mesh generation process, namely the digital elevation model (DEM) and land–water delineation data; (ii) distribute grid points along these internal constraints, according to feature curvature and user-prescribed minimum grid spacing; and (iii) integrate these internal constraints into the 2D mesh size function and mesh generation processes. The developed techniques, which include a novel approach for determining the so-called medial axis of a polygon, are described in detail and demonstrated on three test cases, including two inland watersheds with vast networks of channels and a complex estuarine system on the Texas, USA, coast. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of meeting increasing energy needs by assessing the potential of bioenergy as a sustainable resource option in South Central Texas. Available agricultural crop residues suitable for bioenergy production are evaluated from the 21 counties in South Central Texas Regional Water Planning Area (Region L). The residues produced and available for bioenergy are quantified according to the production areas for each field crop and tree area. Residue-to-product ratios of field crops are determined according to crop type and production quantity. Biomass potential of trees is calculated based on tree density and biomass production per tree. The results demonstrate that the potential productions of utilizable agricultural wastes are in the range of 898.7 t kt–1421.39 kt for Region L. The average annual energy potential is estimated at 19.27 PJ, and ranges between 14.36 and 24.18 PJ. The average potential biomass-based electricity production could compensate significant amount of coal-based electricity generated in the Texas and when agricultural wastes are available. [ABSTRACT FROM AUTHOR]

There is a concerted effort to build intelligent sea and numerous artificial intelligence technologies have been explored. At present, more and more people are engaged in the research of deep reinforcement learning algorithm, and its mainstream application is in the field of games. Reinforcement learning has conquered chess belonging to complete information game, and Texas poker belonging to incomplete information games. And it reached or even surpassed the highest player level of mankind in E-sports games with huge state space and complex action space. However, reinforcement learning algorithm still has great challenges in fields such as automatic driving. The main reason is that the training of reinforcement learning needs to build an environment for interacting with agents. However, it is very difficult to construct realistic simulation scenes, and there is no guarantee that we will not encounter the state that the agent has not seen. Therefore, it is necessary to explore the simulation scene first. Based on this, this paper mainly studies reinforcement learning in simulation scenario. There are huge challenges in migrating them to real scenario applications, especially in sea missions. Aiming at the heterogeneous multi-agent game confrontation scenario, this paper proposes a sea battlefield game confrontation decision algorithm based on multi-agent deep deterministic policy gradient. The algorithm combines long short-term memory and actor-critic, which not only realizes the convergence of the algorithm in huge state space and action space, but also solves the problem of sparse real rewards. At the same time, imitation learning is integrated into the decision algorithm, which not only improves the convergence speed of the algorithm, but also greatly improves the effectiveness of the algorithm. The results show that the algorithm can deal with a variety of different tactical sea battlefield scenarios, make flexible decisions according to the changes of the enemy, and the average winning rate is close to 90%. [ABSTRACT FROM AUTHOR]

Rural and urban America have becoming increasingly divided, both politically and economically. Entrepreneurship can help rural communities catch back up by jumpstarting economic growth, creating jobs, and building resilience to economic shocks. However, less is known about firm creation in rural areas compared to urban areas. To that end, in this paper we ask: What factors predict firm creation in rural America? Our analysis, based on a comparative framework involving multiple machine learning modeling techniques, helps addresses three gaps in academic literature on rural firm creation. First, entrepreneurship research stretches across disciplines, often using econometric methods to identify the effect of a specific variable, rather than comparing the predictive importance of multiple variables. Second, research on firm creation centers on high-tech, urban firms. Third, modern machine learning techniques have not yet been applied in an integrated way to address rural entrepreneurship, a complex economic and policy problem that defies simple, monocausal claims. In this paper, we apply four machine learning methods (subset selection, lasso, random forest, and extreme gradient boosting) to a novel dataset to examine what social and economic factors are predictive of firm growth in rural Texas counties from 2008–2018. Our results suggest that some factors commonly discussed as promoting entrepreneurship (e.g., access to broadband and patents) may not be as predictive as socioeconomic ones (age distribution, ethnic diversity, social capital, and immigration). We also find that the strength of specific industries (oil, wind, healthcare, and elder/childcare) predicts firm growth, as does the number of local banks. Most factors predictive of firm growth in rural counties are distinct from those in urban counties, supporting the argument that rural entrepreneurship is a distinct phenomenon worthy of distinct focus. More broadly, this multi-model approach can offer initial, focusing guidance to policymakers seeking to address similarly complex policy problems. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to evaluate the Dual Use (DU) Option – a crop insurance policy created by the 2018 Farm Bill – relative to other policies available to dual-purpose annual forage producers. The new policy combines existing rainfall-based policies for annual forage crops and multi-peril policies for grain, allowing coverage for multiple crop uses on the same acres during the same growing season. Design/methodology/approach: The paper uses a simulation model to examine crop insurance choices for a typical Texas dual-purpose wheat farm. The certainty equivalent (CE) of wealth is used to rank choices within and between three insurance plans and to analyze the effects of those choices over a range of producer risk aversion levels and for three cases of yield expectations. Findings: The DU Option is more preferred as risk aversion increases, but it is not universally preferred. Therefore, while the policy can be a viable risk management tool, certain restrictions may be limiting its effectiveness. Practical implications: The findings of this paper can help explain farm-level decision making related to dual-purpose annual forage crop insurance program choices. Originality/value: This paper contributes to the literature by documenting a new crop insurance program made available in the 2018 Farm Bill and provides insights into producers' possible choices by evaluating extensive scenarios. [ABSTRACT FROM AUTHOR]

Accurate spatial estimation of extremes is an increasingly important topic in environmental research and risk assessment. Conditional bias (CB)-penalized kriging (CBPK) improves such estimation by minimizing linearly weighted sum of error variance and variance of Type-II error. However, CBPK requires skillful prescription of the weight for the CB penalty which is a significant challenge in practice. In this paper, we describe an extension of CBPK, referred to herein as adaptive conditional bias-penalized kriging (ACBPK), which objectively prescribes the weight for improved estimation of extremes without deteriorating performance in the unconditional mean squared error sense. For comparative evaluation in the real world, cross validation experiments were carried out for precipitation estimation using hourly rain gauge data in the Arkansas-Red River Basin (AB), central Texas (TX) and southeastern US (SE) areas. The results show that CB is detected for about 26, 24 and 25% of all data points in the AB, TX and SE cases, respectively, and that, given detection of CB, ACBPK reduces root mean square error of hourly precipitation exceeding 12.7 mm by 15, 21 and 9% and hourly precipitation exceeding 25.4 mm by 14, 26 and 10% relative to ordinary kriging (OK) for the AB, TX and SE cases, respectively. The overall findings indicate that, if accurate spatial estimation in the tails of the distribution is important or accurate modeling of spatiotemporally-varying correlation structure is a challenge, ACBPK should be favored over OK. [ABSTRACT FROM AUTHOR]

This paper discusses Texas Examinations of Educator Standards Program Languages Other Than English – Spanish exam (TExES LOTE – Spanish) and its potential bias, particularly against teacher candidates with Spanish as a heritage language (HL) background. In Texas, most teacher candidates, or college students of Spanish preparing for secondary teacher certification, are heritage speakers of Spanish. However, while they are competent Spanish speakers, many fail their TExES LOTE – Spanish exam. In light of recent demographic trends and a growing body of research on HL learners, Spanish teaching in higher education and, to a lesser extent, in secondary schools has begun to move away from teaching so-called prestigious varieties of Spanish (e.g., Spain) toward inclusion of other varieties of Spanish, especially those spoken in the U.S. and those that reflect students' heritage. Despite this pedagogical shift, we posit that TExES LOTE – Spanish exam does not reflect current Spanish curricular content, which negatively affects these students' performance. We provide examples and available exam statistics to support our claim. Through this conversation about the mismatch between student background and TExES LOTE – Spanish content, we hope to start a dialogue about a much-needed revision of this exam in the near future. [ABSTRACT FROM AUTHOR]

The research team developed a community-based, intergenerational intervention, the Spanish-language Healthy Buddy Program to alleviate transportation barriers experienced by Latinx older adults. College students were paired with Latinx older adults and helped them identify transportation- and health-related resources in their communities. During COVID-19, the program was implemented in Hillsborough County, Florida, and Dallas-Fort Worth Metroplex and San Antonio, Texas. This paper reports the study process and outcomes using quantitative and qualitative data collected in Texas (n = 25). Individual interviews indicated older adult participants were receptive to the program model and appreciated the roles student buddies played to help improve their mobility. [ABSTRACT FROM AUTHOR]

Paris' power law is commonly used to describe transverse thermal cracking propagation in asphalt concrete (AC) pavements. In its most common format, it relates the rate of change in the crack length per cycle to changes in either the stress intensity factor K or the energy release. The parameters defining this relationship for ACs can be obtained using the Texas cyclic Overlay Test (OTR). This paper describes two numerical approaches for simulating the OTR using the extended finite element method (XFEM). The first uses the direct low-cyclic fatigue (LCF) approach and the second uses the virtual crack closure technique (VCCT). Comparisons of the model predictions to laboratory OTR measurements for six mixtures suggest that the XFEM model coupled with VCCT is better suited for simulating the OTR. The model output includes the crack length and the energy release rate ERR (i.e. ${\rm \Delta }J_R$ Δ J R ) as cracks propagate. This data was used to fit the modified Paris' law parameters ${A}^{\prime}$ A ′ and ${n}^{\prime}$ n ′ as a function ${\rm \Delta }J_R$ Δ J R . Subsequently, the traditional A and n Paris' power law parameters were fitted by estimating the corresponding ΔK. Using this model, it was possible to efficiently estimate the AC cracking parameters using as input only the tensile modulus and the critical ERR. [ABSTRACT FROM AUTHOR]

This paper describes a human-centered design approach to investigate unmet adolescent sexual health wants and needs among youth of color in low-income and rural communities in Texas, North Carolina, and Connecticut (n = 149). The approach involved gathering qualitative data through in-depth interviews and other human-centered design activities between April 2016 and August 2016. Data were analyzed using thematic content analysis after each round of data collection. Themes were triangulated across multiple data sources to identify key insights. Results highlighted several important unmet wants and needs. Participants shared that schools were not the preferred place to learn about sexual health and healthy relationships, due to uncomfortable and sometimes even hostile environments. When discussing the potential to use internet- and technology-based sexual health resources, participants expressed concerns over privacy, safety, and credibility of information available. Similarly, participants preferred mobile apps over websites due to the privacy of the experience. Most importantly, key emotions impacting adolescents' access to and use of sexual health resources were identified. Results indicated a preference for consuming story-based information in a text message format that described diverse experiences related to sexual health topics. Together, these findings led to the development of an innovative, mobile health intervention for adolescents, the Real Talk mobile app. This human-centered approach can support researchers and practitioners in strengthening intervention development efforts to improve the reach, adoption, and implementation of sexual health interventions. [ABSTRACT FROM AUTHOR]

The article is a report from the President of the Society for the Advancement of Scandinavian Studies (SASS) about their 2-year term and the recent annual conference held at the University of Texas, Austin. The report highlights the success of the conference, including the keynote lecture and the presentation of papers by Society members. The report also announces the winners of various awards and discusses the challenges and opportunities facing the field of Scandinavian Studies, such as hiring and membership. The report concludes with an invitation to the next conference in Seattle and emphasizes the importance of financial support for the Society's mission. [Extracted from the article]

In this paper, we present formal and informal volunteers' perceived experiences of a mass vaccination clinic for COVID‐19 in central Texas. Volunteers at one or more of our team's vaccination events responded to an anonymous survey to share perceptions of their preparedness, training experiences, communication effectiveness and satisfaction, to help us identify opportunities to improve volunteer training and engagement for responses to pandemics. Overall, the volunteers perceived their work to be meaningful, felt prepared and were satisfied with their experiences as volunteers. A dedicated team that communicates well and emphasizes a team approach is key to success, especially in unprecedented situations such as the COVID‐19 pandemic. Implications for future volunteer training and involvement in disaster responses are discussed. [ABSTRACT FROM AUTHOR]

Accurate, timely, and accessible meteorological and soil moisture measurements are essential for a number of applications including weather forecasting, agricultural decision-making, and flood and drought prediction. Such data are becoming increasingly available globally, but the large number of networks and various data reporting formats often make utilization of such data difficult. The TexMesonet is a "network of networks" developed within the state of Texas to collect, process, and make public data collected from more than 1700 monitoring stations throughout the state. This paper describes the TexMesonet, with special attention paid to monitoring sites installed and managed by the Texas Water Development Board. It also provides a case study exemplifying how these data may be used and gives recommendations for future data applications. [ABSTRACT FROM AUTHOR]

Connected vehicle (CV) data in this paper refer to the in-vehicle telematic data, including trajectories and driving events (e.g., hard braking) collected by vehicle manufacturers when vehicles are moving. Recently manufactured vehicles are equipped with cellular modems and Internet of Things (IoT) devices to collect vehicle data. Such data, after removing personal information, are being redistributed to third-party organizations. Compared to other probe vehicle data, the CV data has a higher penetration rate, ubiquitous coverage, and almost lane-level positioning accuracy. These features pave the road for novel transportation applications in transportation planning and traffic operations. In this paper, we represent a novel framework to estimate the regional link volumes based on the CV data and a deep neural network (DNN) model. The training data are generated according to the link volumes (targeted model output) and the corresponding CV counts (input features) at the same locations. The DNN model's performance was compared with other estimation methods like linear regression and random forest and showed superior performance. The trained DNN model takes ubiquitous CV counts from other locations to estimate the corresponding link volumes. As a case study, the proposed DNN model was trained with a large training data set derived from CV data and time-dependent link counts collected at over 1,200 locations on freeways in the Dallas FortWorth, Texas, area. The results reveal good accuracy and robustness. [ABSTRACT FROM AUTHOR]

Industrial and energy-related industries are major sources of carbon dioxide emissions, and their interdependence, as reflected in the financial field, has attracted the attention of scholars. For the purpose of exploring the evolutionary characteristics of the short-term dynamic correlation coefficient between the EU carbon futures price and the industrial and energy-related indices, this paper selected the settlement price of EU carbon emission quota futures, the MSCI energy I index on three dimensions, and the Dow Jones industrial index and West Texas crude oil futures price, as sample data. Using the time-varying t-copula model to measure the dynamic correlation coefficient between variables, the time-sliding window idea and coarse-grained method were combined to establish the correlation fluctuation mode, and a complex network theory and analysis methods were used to study the evolutionary traits of the time-varying network structure between the EU carbon price and the industrial and energy-related index. The results show that the transmission objects of the key correlation fluctuation modes in the network are stable and maintain their own state with a high probability. Second, the clustering effect exists in the transmission process. Some nodes with high mediating abilities are also the key correlation wave modes in the dynamic correlation evolution network. This study provides ideas for the study of the correlations between multiple variables and is also a useful reference for international investors. [ABSTRACT FROM AUTHOR]

Background: Our purpose in this study was to explore perceived problematic issues of local communities in rural areas and to test the hypothesis that increased perceptions of problematic issues in the community are negatively associated with respondents' general self-rated health (GSRH). Methods: Data used for this paper were drawn from two surveys of persons living in small towns and rural places in Texas. The association of each of the 33 perceived problematic issues with GSRH was assessed using bivariate and multivariate correlation analyses. Results: Results indicated that 88% of the potentially problematic community issues included in this study were negatively and significantly associated with respondents' GSRH at the bivariate level. The overall pattern of associations changed only slightly when the individual-level characteristic variables were controlled. Certain sociodemographic variables (i.e., age, household income, educational attainment, and race) were verified to be significant predictors of GSRH. Conclusions: Similar to results from previous studies conducted in urban settings, our findings from rural and smalltown Texas demonstrate the importance of incorporating individuals' perceptions of problematic community issues in health disparities research. [ABSTRACT FROM AUTHOR]

Fast and rigorous well performance evaluation is made possible by new solutions of the pressure diffusion equation. The derived Gaussian pressure transient (GPT) solutions can be practically formulated as a decline curve analysis (DCA) equation for history matching of historic well rates to then forecast the future well performance and estimate the remaining reserves. Application in rate transient analysis (RTA) mode is also possible to estimate fracture half-lengths. Because GPT solutions are physics-based, these can be used for production forecasting as well as in reservoir simulation mode (by computing the spatial and temporal pressure gradients everywhere in the reservoir section drained by either an existing or a planned well). The present paper focuses on the physics-based production forecasting of so-called "unruly" wells, which at first seem to have production behavior noncompliant with any DCA curve. Four shale wells (one from the Utica, Ohio; one from the Eagle Ford Formation, East Texas; and two from the Wolfcamp Formation, West Texas) are analyzed in detail. Physics-based adjustments are made to the Gaussian DCA history matching process, showing how the production rate of these wells is fully compliant with the rate implied by the hydraulic diffusivity of the reservoir sections where these wells drain from. [ABSTRACT FROM AUTHOR]

A relevant, well-crafted emergency plan can help schools most optimally return to normal following a disaster. During this time, educators find themselves facing unintended responsibilities like operating on the front lines of providing social-emotional support for their students. Researchers conducted 115 interviews with educators impacted by Hurricanes Harvey and Matthew in Texas and North Carolina to assess their mental health and their school's role in returning to normal. Findings suggest that emergency plans often did not take into account the social-emotional factors of recovery. This paper seeks to provide insight into the experiences of educators following a disaster and propose elements to consider in revising school emergency plans. [ABSTRACT FROM AUTHOR]

This paper compares the educational achievement and growth of Latinx third through eighth-grade students attending school along the U.S.-Mexico Border and in the interior of the four Border states. The theories of structural and legal violence predict that powerful Anglos have created systems of social reproduction, concentrated disadvantage, and immigration law that reduce Latinx education close to the U.S.-Mexico Border. We test these theories with data from the Stanford Education Data Archive (SEDA), which contains information on Latinx achievement and growth in all public school districts in the four Border states. We find that Latinx achievement and growth are similar along the Border and in the interior except in Texas, where concentrated disadvantage dramatically lowers Latinx achievement and growth. We also find that social reproduction is more beneficial for Latinx youth along the Border because, surprisingly, Latinx adults tend to be more educated near the border than in the interior. We find no evidence that immigration laws reduce education more near the Border than in the interior. We discuss the implications of our findings for theory and policy. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the impact of the GreenLeaders designation on hotel performance under the joint theoretical framework of environmental corporate social responsibility and social identity theory. We focus on 1,198 individual hotel properties from five major cities in Texas between 2010 and 2019. A two-way fixed-effects model is applied to model monthly revenue per available room (RevPAR) and TripAdvisor ratings for each hotel. Results show that GreenLeaders certification leads to a 6.00% increase in hotels' monthly RevPAR and a 4.25% increase in hotels' monthly average TripAdvisor rating. This impact grew over time during the research period. The findings also unveil a set of moderating variables, such as hotel class and chain affiliation. More specifically, the effect of GreenLeaders certification is larger for upscale and independent hotels. The major results are also confirmed through a robustness analysis using propensity-score-based weighting and placebo tests. Lastly, implications are provided for hoteliers and investors. [ABSTRACT FROM AUTHOR]

Formation fracturing is the method of choice for developing shale oil and gas reservoirs that constitute a gigantic resource in the U.S.A. and many other countries but are characterized by a low permeability in the nano-Darcy range. The oil production of Texas has increased by about 5 million B/D in 15 years as a result of shale exploitation by massive multistage hydraulic fracturing. The mathematical modeling of this fracturing process is complex and can be approached in several ways. This paper first gives a concise description of the fracturing process as carried out in Texas. Included are the ranges of the key reservoir properties, as well as the injection fluid volumes and pressure, the composition of the injected fluid, proppant type, and volume, and other relevant data. Also included are the number of fracture stages, methods of zonal isolation, and diagnostic techniques used. An important variable considered is flowback, in particular, fluid retention and oil and gas production. High-salinity water production is discussed. Given the above variables, the currently used fracture simulators are briefly considered and compared, both the geomechanics-based and fracture-propagation-based. No single simulator can model the complete process. The directions currently being followed are briefly described. Also discussed is the simulation of the re-fracturing process and its range of success in increasing oil recovery from about the original ~5% to ~8%. Future processes such as plasma fracturing are mentioned, and their future applicability is discussed for further increasing oil recovery. [ABSTRACT FROM AUTHOR]

Distributed acoustic sensing (DAS) is a new seismic monitoring technology. DAS generates a large amount of data, necessitating the development of new technologies to allow for cost-effective processing and handling. The raw seismic data is noisy and must be processed. The curvelet transform is an excellent choice for processing seismic data due to its localized nature, as well as its frequency and dip characteristics. However, its capabilities are limited in case of noise other than white. This paper proposes a denoising method based on a combination of the curvelet transform and a whitening filter, as well as a procedure for estimating noise variance. The whitening filter is included to improve the performance of the curvelet transform in both coherent and incoherent noise cases, as well as to simplify the noise variance estimation method and make it easier to use standard threshold methodology without delving into the curvelet domain. Two data sets are used to validate the suggested technique. Pseudo-synthetic data set created by adding noise to the actual noise-free data collection from the Netherlands offshore F3 block and the on-site data set (with ground roll noise) from east Texas, USA. Experimental results demonstrate that the proposed algorithm achieves the best results under various types of noise. [ABSTRACT FROM AUTHOR]

The utilization of wind energy has become increasingly popular in the United States and many European countries due to its abundant nature and optimized design. While existing wind turbines are predominantly large-scale and not suitable for standalone or distributed power production, Lubbock County in West Texas offers a diverse range of renewable energy options to meet its energy needs. The region relies heavily on utility-scale wind energy sources to supply power to the Texas Grid, replacing conventional fossil fuel-based systems. Currently, standalone solar PV systems are the preferred choice for renewable energy generation. However, West Texas possesses an ample supply of wind energy that can be harnessed to establish a microgrid and provide standalone power to rural communities. Distributed wind energy offers localized power generation, reducing transmission losses and grid strain, while conventional wind farms require long-distance transmission, leading to efficiency gains. By employing the latest technology and optimizing efficiency, even in low-scale generation, a 6-kilowatt permanent magnet alternator-based distributed wind turbine has been designed. This paper focuses on analyzing the techno-economic aspects of implementing this wind turbine in a real-world scenario, taking into account wind attributes, such as velocity and available power, at the specific location. [ABSTRACT FROM AUTHOR]

The main challenges of the input current control in synchronous DC-DC buck converters are the nonlinear model of the system, changes of the operating point in a wide range, and the need to use an input LC filter for current smoothing, which may result in the instability of the closed-loop system. In this paper, a step-by-step approach is developed for the design and improvement of a PI-feedforward closed-loop controller. It is shown that a linear PI controller cannot stabilize the closed-loop system properly during wide changes in model parameters, e.g., an equivalent series resistance of the input filter. To cope with the stability issues, a fixed-frequency sliding mode controller (SMC) has been developed in this paper for the implementation of an electro-mechanical actuator (EMA) emulator. Moreover, a systematic approach is proposed for controller tuning and the selection of the SMC's gains. To achieve high power efficiency, high-frequency GaN switches are used for the practical implementation of the DC-DC converter. Despite large changes in the load current, the designed nonlinear controller can track the input current reference satisfactorily. Steady-state and dynamic responses of the proposed SMC are compared with conventional linear controllers. Considering the Lyapunov stability theorem, it is proved that the designed SMC can stabilize the closed-loop system in the entire utilizable domain. The proposed nonlinear SMC controller enjoys a very simple control law. Hence, despite having very high switching and sampling frequencies, it can be easily implemented. The experimental response of the designed synchronous DC-DC buck converter is evaluated experimentally by implementing the control strategy in a TMS320F28335PGFA DSP from Texas Instrument. Moreover, the comprehensive comparison of the proposed SMC controller and a PI-feedforward controller proved the superior performance of the developed closed-loop system, in terms of the transient time response, robustness, and stability of the EMA emulator. [ABSTRACT FROM AUTHOR]

In February 2021, Texas was hit by a severe winter storm. The extreme cold weather triggered an unprecedented increase of electricity demand and simultaneous failure of multiple electricity grid components. The dual effect caused a widespread power outage that left millions of Texans without power for days. This paper estimates the indirect economy-wide cascading impact of that power outage. It utilized historical make and use tables between 1997 and 2019 in an inoperability input-output analysis–based economic impact assessment model to quantify the expected indirect cost of the power outage in terms of the loss of gross domestic product of Texas. This research found that expected loss to be approximately $664 million in 2019 values. It also found that in Texas industries such as oil and gas extraction, petroleum, coal products, and so on are particularly vulnerable to such weather-related prolonged power outages. The outcomes of this paper can be used in planning for strategies to make the grid robust, reliable, and resilient to severe weather events. The identification of vulnerable industries can also help in planning for auxiliary capacities so the cascading economic impacts of the weather-related power outages can be reduced. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue on topics including hearing loss prevention, hearing health, and noise-induced hearing loss (NIHL).

Benevolence is often a way for the church to engage with the local community, however, churches often struggle with how to do so most effectively. This paper provides a description of five church models from Baptist congregations in Central Texas. This paper will summarize each church’s approach and synthesize the approaches to form recommendations for congregational social work, including roles of the social worker in the congregation and suggestions for how churches might work with social workers to enhance and better articulate policies and practices around benevolence ministries. A highlight of the literature surrounding congregational community ministries will also be included. This article aims to advance the role of social workers in congregations and give tangible tools for both social work and congregational engagement with benevolence funds. [ABSTRACT FROM AUTHOR]

The COVID-19 (SARS-CoV-2 virus) pandemic has led to a substantial loss of human life worldwide by providing an unparalleled challenge to the public health system. The economic, psychological, and social disarray generated by the COVID-19 pandemic is devastating. Public health experts and epidemiologists worldwide are struggling to formulate policies on how to control this pandemic as there is no effective vaccine or treatment available which provide long-term immunity against different variants of COVID-19 and to eradicate this virus completely. As the new cases and fatalities are recorded daily or weekly, the responses are likely to be repeated or longitudinally correlated. Thus, studying the impact of available covariates and new cases on deaths from COVID-19 repeatedly would provide significant insights into this pandemic's dynamics. For a better understanding of the dynamics of spread, in this paper, we study the impact of various risk factors on the new cases and deaths over time. To do that, we propose a marginal-conditional based joint modelling approach to predict trajectories, which is crucial to the health policy planners for taking necessary measures. The conditional model is a natural choice to study the underlying property of dependence in consecutive new cases and deaths. Using this model, one can examine the relationship between outcomes and predictors, and it is possible to calculate risks of the sequence of events repeatedly. The advantage of repeated measures is that one can see how individual responses change over time. The predictive accuracy of the proposed model is also compared with various machine learning techniques. The machine learning algorithms used in this paper are extended to accommodate repeated responses. The performance of the proposed model is illustrated using COVID-19 data collected from the Texas Health and Human Services. [ABSTRACT FROM AUTHOR]

Parkland dedication is receiving increasing attention from cities because it provides capital funding without raising taxes on existing residents. Its parameters are dependent on interpretation of court rulings and in the past decade these have changed in ways that substantially enhance the potential of these revenues for local governments. The changes invariably become the focus of controversies between developers who resist paying the dedication fees and elected officials who are charged with safeguarding the interest of taxpayers. This paper addresses two central areas of controversy: Changes in interpretations of what constitutes a "nexus"; and the magnitude and characteristics of credits given to developers who provide park amenities in their projects. The "essential nexus" principle requires there to be a reasonably proximate connection between facilities developed with the resources derived from a dedication and the residents who will reside in the development providing those resources. A recent census of the 73 cities in Texas that have parkland dedication ordinances was analyzed and the relative merits of five different approaches they have used for defining service areas is discussed: a single city-wide zone, pre-determined zones; reasonable proximity; specified distance; and a hybrid model of distance/pre-established zones. Among the 73 ordinances reviewed, approximately half believed the most equitable ratio for crediting developers for park amenities they provided within subdivisions was 50%. Among the others, maximum credit varied from 0% to 100%. The relative merits are evaluated, together with the extent to which floodplain land and retention ponds are acceptable to meet a dedication requirement. [ABSTRACT FROM AUTHOR]

This paper analyzes the problem of a principal (she) designing a contract for an agent (he) to form a short-lived partnership to exploit an asset before reselling, as in asset flipping. The agent possesses higher expertise than the principal in the sense that he can form a more-accurate assessment of the resale value of the asset before negotiating the dissolution of the partnership. By dissolving the partnership through a Texas shootout with the agent as proposer, the principal can "neutralize" her partner's informational advantage and have him disclose the resale value for free. Thus, in the optimal contract, the agent's superior expertise does not distort the structure of the partnership (i.e., the allocation of shares). The partners attain a higher aggregate surplus ex-ante if the principal commits to giving the asset away to the agent upon dissolving the partnership: She earns a lower revenue but lets all types of the agent enjoy a higher surplus. Thus, at the ex-ante stage, the agent could "bribe" the principal to implement this alternative. However, the additional surplus for lower types is insufficient to compensate the principal, so this higher ex-ante aggregate surplus is unattainable at the interim stage. [ABSTRACT FROM AUTHOR]

The increase in the concentration of geological gas emissions in the atmosphere and particularly the increase of methane is considered by the majority of the scientific community as the main cause of global climate change. The main reasons that place methane at the center of interest, lie in its high global warming potential (GWP) and its lifetime in the atmosphere. Anthropogenic processes, like engineering geology ones, highly affect the daily profile of gasses in the atmosphere. Should direct measures be taken to reduce emissions of methane, immediate global warming mitigation could be achieved. Due to its significance, methane has been monitored by many space missions over the years and as of 2017 by the Sentinel-5P mission. Considering the above, we conclude that monitoring and predicting future methane concentration based on past data is of vital importance for the course of climate change over the next decades. To that end, we introduce a method exploiting state-of-the-art recurrent neural networks (RNNs), which have been proven particularly effective in regression problems, such as time-series forecasting. Aligned with the green artificial intelligence (AI) initiative, the paper at hand investigates the ability of different RNN architectures to predict future methane concentration in the most active regions of Texas, Pennsylvania and West Virginia, by using Sentinel-5P methane data and focusing on computational and complexity efficiency. We conduct several empirical studies and utilize the obtained results to conclude the most effective architecture for the specific use case, establishing a competitive prediction performance that reaches up to a 0.7578 mean squared error on the evaluation set. Yet, taking into consideration the overall efficiency of the investigated models, we conclude that the exploitation of RNN architectures with less number of layers and a restricted number of units, i.e., one recurrent layer with 8 neurons, is able to better compensate for competitive prediction performance, meanwhile sustaining lower computational complexity and execution time. Finally, we compare RNN models against deep neural networks along with the well-established support vector regression, clearly highlighting the supremacy of the recurrent ones, as well as discuss future extensions of the introduced work. [ABSTRACT FROM AUTHOR]

Library services in the US were reduced during the COVID-19 lockdowns in 2020, and rural residents were particularly impacted. To understand the impact of the pandemic on library services in rural areas, this paper analyzed the 2020 Texas Public Library Statistics and a portion of the 2019 and 2018 data. It examined various services from libraries located in the areas with a population of less than 5,000. Although libraries opened only 76% of hours in 2020 compared to 2019 and 2018, their public computer usage dropped around 50% compared to previous years. Paired sample t-tests suggested statistically significant differences in annual library visits, opening hours, and computer use, indicating much-needed support for computing resources in rural areas because of the pandemic. This study suggested that rural libraries are crucial candidates for a public-private partnership to build rural broadband and enhance public computing services. [ABSTRACT FROM AUTHOR]

Within medical education, feedback is an invaluable tool to facilitate learning and growth throughout a physician’s training and beyond. Despite the importance of feedback, variations in practice indicate the need for evidence-based guidelines to inform best practices. Additionally, time constraints, variable acuity, and workflow in the emergency department (ED) pose unique challenges to providing effective feedback. This paper outlines expert guidelines for feedback in the ED setting from members of the Council of Residency Directors in Emergency Medicine Best Practices Subcommittee, based on the best evidence available through a critical review of the literature. We provide guidance on the use of feedback in medical education, with a focus on instructor strategies for giving feedback and learner strategies for receiving feedback, and we offer suggestions for fostering a culture of feedback. [ABSTRACT FROM AUTHOR]

In our title, "chaos" means there is a positive Lyapunov exponent that causes the tornado to move. We are asserting that a positive Lyapunov exponent is not always needed to have a butterfly effect. Lorenz's butterfly effect initially appeared in meteorology and has captured the imaginations of people for applications to all kinds of fields. We feel it is important to understand simpler non-meteorological models to understand the additional aspects of the butterfly effect. This paper presents simple linear map models that lack "chaos" but exhibit a butterfly effect: our simplest model does not have any positive Lyapunov exponents but still exhibits a butterfly effect, that is, temporary exponential growth from a tiny perturbation such as one infected mosquito setting off an epidemic outbreak. We focus on a 24-dimensional version of the map where a significant butterfly effect is observed even though the only Lyapunov exponent is 0. We introduce a linear "infected mosquito" model that shows how off-diagonal matrix entries can cause a finite-time growth rate. We argue that the degree of instability in our systems can be better measured by its finite-time growth rate. Our findings suggest that even in linear systems, off-diagonal matrix entries can significantly impact the system's behavior and be more important than the Lyapunov exponents in higher-dimensional systems. A focus on finite-time growth rates can yield valuable insights into the system's dynamics. [ABSTRACT FROM AUTHOR]

Background: Drug overdose deaths in Texas have been accelerating in recent years with an increase of 33% in the 12 months leading up to December 2020. Accurate counts of nonfatal overdoses – including associated aspects of overdose, such as substances involved, demographic information, and reversal agents administered is critical to increase timely and adequate response to individuals and communities in need. Methods: Twenty semi-structured interviews were conducted with harm reduction workers across four Texas counties to understand existing methods of reporting overdoses, naloxone dissemination/administration, and recommendations for improving overdose surveillance. Interviews were transcribed and emergent themes were identified based on the a priori research goals. Results: Findings highlighted a variety of overdose data collection methods and tools among harm reduction organizations including Excel spreadsheet, web-based TONI application, notes on personal cell phones, and paper notes. Types of overdose data collected varied widely. Participants noted existing methods are suboptimal and that there is a need for a unified, statewide reporting system to improve overdose data capture. Participants also highlighted that overdose surveillance should include "hidden populations" of people who use drugs that are not currently counted in surveillance methods as a result of not interacting with the healthcare system. Conclusions: Texas lacks a unified overdose reporting system to capture critical data to inform overdose response and prevention efforts. Nontraditional reporters may be critical toward improving overdose syndromic efforts and capturing data among hard-to-reach populations. Harm reduction organizations are uniquely positioned to facilitate reporting among community gatekeepers and people who use drugs. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) is a neurodevelopmental disability affecting 1 in 44 children nationally. Timely referral to intervention and support services for ASD has consistently demonstrated significant long‐term positive effects on symptoms and subsequent skills and family outcomes. This paper highlights a novel and innovative approach of short‐term consultations for best practices to ultimately increase access to timely ASD evaluations and support through a state‐wide school telehealth initiative. The goal of the initiative was to facilitate rapid access to ASD evaluation and support (within 2 weeks of referral in school‐age youth) among under‐resourced school systems in Central Texas. First, this paper provides background relative to current disparities that many children face when attempting to obtain ASD evaluations and support. Second, a statewide legislative response is described that created a mental health consortium targeting increased access to broad‐based mental health services and supports, particularly in underserved areas. Next, the Texas Child Health Access Through Telemedicine (TCHATT) program is outlined with a particular focus on day‐to‐day operationality and concentrated efforts to increase mental health literacy among school teams relative to ASD symptoms and co‐occurring behavioral health concerns. Year 1 utilization data metrics (September 2020–May 2021) and representative case examples are presented. Finally, early "lessons learned" and future directions are discussed. Highlights: In 2020, the Texas Child Health Access Through Telemedicine (TCHATT) program was implemented state‐wide as a partnership between local school districts, community mental health agencies, and developmental specialists at the 12 academic medical centers across Texas to increase access to services for youth with behavioral or developmental referral concerns.The model aims to provides timely access (within 1 week) to a telehealth visit with a developmental specialist for short‐term evaluation and support as well as pairing families with a system navigator to facilitate referral follow‐through to community resources.The TCHATT model offers school districts a potentially viable option for increasing access to timely autism evaluation and supports via telehealth. [ABSTRACT FROM AUTHOR]

Background: Visibility of the transgender community has increased, particularly in the media. Trans teachers face a challenge, as their professional roles are both public and private. In an effort to seek personal and professional support, trans teachers have turned to social media outlets. Additionally, current research does not always encompass intersectional experiences of trans BIPOC teachers. Aim: This paper presents an autohistoria-teoría, or autoethnographical case study account of the author's experience coming out in the workplace as a trans teacher in Texas. Methods: Guided by Slavin et al. multicultural model of the stress process coupled with intersectionality, this paper attempts to describe how a trans teacher of color navigates the workplace. The data for this study are a collection of all of the author's social media posts from 2005 to 2015. Results: Findings reveal that allies provided some support, and that this trans teacher used deflection as a coping strategy in posts. Conclusion: The results suggest that administrative and peer support can impact transgender workers' mental well-being. In this paper, autohistoria-teoría is used as a powerful way for a trans BIPOC teacher's narrative to be told, which contributed to cultural healing. [ABSTRACT FROM AUTHOR]

Introduction: Atrial Fibrillation (AF) is a common tachyarrhythmia affecting 33 million people worldwide. Hybrid AF ablation utilises a surgical (epicardial) ablation followed by an endocardial catheter-based ablation. The aim of this systematic review and meta-analysis is to summarize the literature reporting mid-term freedom from AF following hybrid ablation. Methods: An electronic search of databases was performed to identify all relevant studies providing mid-term (2 year) outcomes following hybrid ablation for AF. The primary study outcome was to assess the mid-term freedom from AF following hybrid ablation, utilising the metaprop function on Stata® (Version 17.0, StataCorp, Texas, USA). Subgroup analysis was performed to assess the impact of various operative characteristics on mid-term freedom from AF. The secondary outcomes assessed mortality and procedural complication rate. Results: The search strategy identified 16 studies qualifying for inclusion in this meta-analysis, with 1242 patients in total. The majority of papers were retrospective cohort studies (15) and one study was a randomized control trial (RCT). The mean follow up was 31.5 ± 8.4 months. Following hybrid ablation, the overall mid-term freedom from AF was 74.6% and 65.4% for patients off antiarrhythmic drugs (AAD). Actuarial freedom from AF was 78.2%, 74.2% and 73.6% at 1, 2 and 3 years respectively. No significant differences in mid-term freedom from AF based epicardial lesion set (box vs pulmonary vein isolation) or Left atrial appendage/Ganglionated Plexus/Ligament of Marshall ablation or staged vs concomitant procedures. There were 12 deaths overall following the hybrid procedure with a pooled complication rate of 5.53%. Conclusion: Hybrid AF ablation offers promising mid-term freedom from AF reported at a mean follow-up of 31.5 months. The overall complication rate remains low. Further analysis of high-quality studies with randomized data and long-term follow up will help verify these results. [ABSTRACT FROM AUTHOR]

Here it might be helpful to pose a pair of questions: Absent aggressive moves by the Mexican government and military toward centralization in Coahuila and Texas, would Texians have rebelled in late 1835 over the status of slavery? 31 Randolph B. Campbell, I An Empire for Slavery: The Peculiar Institution in Texas, 1821-1865 i (Baton Rouge: Louisiana State University Press, 1989), 48. 32 Declaration, Martin Perfecto de Cós, July 5, 1835, John W. Smith Papers, 1822-1934, Col 917, Daughters of the Republic of Texas Library, San Antonio, Texas. And absent any threats to the status of slavery in Texas at that time, would Texians have rebelled over aggressive moves of the Mexican government and military toward centralization in Texas? It is not clear that Lack included Texas-born combatants in his tables.[76] Alamo defenders are included in the overall total of 3,685.) The presence of thirty-seven volunteers from Gonzales who died at the Alamo is another factor. [Extracted from the article]

Simple Summary: People with substance use disorders have extremely elevated rates of smoking and, therefore, are a priority population for lung cancer screening. This paper examines the lung cancer screening practices—determining patients' eligibility for lung cancer screening and making referrals to screening—of Texas healthcare organizations that provide services to people with substance use disorders. This work demonstrated that few organizations are determining patients' eligibility and even fewer are making referrals. While not all organizations have the capability to make referrals (i.e., no on-site prescriber), they each have a vital role to play in eligibility determination and patient education. There is a need for researchers to focus intervention and implementation efforts within these organizations to increase capacity and ensure that patients are being navigated to lung cancer screening at multiple touch points across the healthcare continuum. For people at elevated risk for lung cancer, lung cancer screening (LCS) reduces lung cancer mortality. People with non-nicotine substance use disorders (SUDs) have elevated rates of smoking compared with the general population, highlighting them as a priority population for LCS consideration. Although research has shown LCS is underutilized, there is little literature to inform whether organizations that serve individuals with SUDs have existing clinical protocols surrounding LCS. In the current study, we examine the LCS eligibility and referral practices among these organizations. We conducted a statewide needs assessment survey in 2021 to discern how tobacco use was being addressed at Texas organizations that provide treatment or services to individuals with SUDs. Respondents were asked to report on their center's LCS eligibility and referral practices. The analytic sample consists of 125 respondents who represented 23 federally qualified health centers, 29 global local mental health authorities (LMHAs), 12 substance use treatment programs in LMHAs, and 61 standalone substance use treatment centers. Very few respondents indicated that healthcare providers at their center made referrals to LCS for patients (8.8%); a few respondents indicated that their healthcare providers assessed patients' eligibility for LCS but did not make referrals (3.2%). Intervention and implementation efforts are needed in these and other SUD healthcare settings to bolster organizational capacity and ensure that patients are being navigated to lung cancer screening at multiple touch points across the care continuum. [ABSTRACT FROM AUTHOR]

Approximately one-third of the veteran population suffers from post-traumatic stress disorder, a mental illness that is often co-morbid with social anxiety disorder. Student veterans are especially vulnerable as they struggle to adapt to a new, less structured lifestyle with few peers who understand their difficulties. To support mental health experts in the treatment of social anxiety disorder, this study utilized machine learning to detect anxiety in text transcribed from interviews with patients and applied topic modeling to highlight common stress factors for student veterans. We approach our anxiety detection task by exploring both deep learning and traditional machine learning strategies such as transformers, transfer learning, and support vector classifiers. Our models provide a tool to support psychologists and social workers in treating social anxiety. The results detailed in this paper could also have broader impacts in fields such as pedagogy and public health.1 [ABSTRACT FROM AUTHOR]