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This paper provides empirical evidence using two studies to explain the primary factors facilitating electronic health record (EHR) systems adoption through the lens of the resource advantage theory. We aim to address the following research questions: What are the main organizational antecedents of EHR implementation? What is the role of monitoring in EHR system implementation? What are the current themes and people's attitudes toward EHR systems? This paper includes two empirical studies. Study 1 presents a research model based on data collected from four different archival datasets. Drawing upon the resource advantage theory, this paper uses archival data from 200 Texas hospitals, thus mitigating potential response bias and enhancing the validity of the findings. Study 2 includes a text analysis of 5154 textual data, sentiment analysis, and topic modeling. Study 1's findings reveal that joint ventures and ownership are the two main enablers of adopting EHR systems in 200 Texas hospitals. Moreover, the results offer a moderating role of monitoring in strengthening the relationship between joint-venture capability and the implementation of EHR systems. Study 2's results indicate a positive attitude toward EHR systems. The U.S. was unique in the sample due to its slower adoption of EHR systems than other developed countries. Physician burnout also emerged as a significant concern in the context of EHR adoption. Topic modeling identified three themes: training, healthcare interoperability, and organizational barriers. In a multimethod design, this paper contributes to prior work by offering two new EHR antecedents: hospital ownership and joint-venture capability. Moreover, this paper suggests that the monitoring mechanism moderates the adoption of EHR systems in Texas hospitals. Moreover, this paper contributes to prior EHR works by performing text analysis of textual data to carry out sentiment analysis and topic modeling. [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]

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]

OBJECTIVES: Our aim was to report the first known incidence of U.S. butter contamination with extremely high levels of polybrominated diphenyl ethers (PBDEs). METHODS: Ten butter samples were individually analyzed for PBDEs. One of the samples and its paper wrapper contained very high levels of higher-brominated PBDEs. Dietary estimates were calculated using the 2007 U.S. Department of Agriculture Loss-Adjusted Food Availability data, excluding the elevated sample. RESULTS: The highly contaminated butter sample had a total upper bound PBDE level of 42,252 pg/g wet weight (ww). Levels of brominated diphenyl ether (BDE)-206, -207, and -209 were 2,000, 2,290, and 37,600 pg/g ww, respectively. Its wrapping paper contained a total upper-bound PBDE concentration of 804,751 pg/g ww, with levels of BDE-206, -207, and -209 of 51,000, 11,700, and 614,000 pg/g, respectively. Total PBDE levels in the remaining nine butter samples ranged from 180 to 1,212 pg/g, with geometric mean of 483 and median of 284 pg/g. Excluding the outlier, total PBDE daily intake from all food was 22,764 pg/day, lower than some previous U.S. dietary intake estimates. CONCLUSION: Higher-brominated PBDE congeners were likely transferred from contaminated wrapping paper to butter. A larger representative survey may help determine how frequently PBDE contamination occurs. Sampling at various stages in food production may identify contamination sources and reduce risk. [ABSTRACT FROM AUTHOR]

Focuses on the effect of United States Food Administration (FA) papers on the state welfare in Texas. Historical overview of the FA activities; Reaction of the people to food conservation; Refusal of some people to honor pledge card campaigns.

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]

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]

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]

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]

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]

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]

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: 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]

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]

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]

Although hydraulic groundwater (GW) theory has been recognized as a promising tool for understanding the role of the aquifer(s) in the surface‐subsurface hydrologic cycle, the integrated modeling community still lacks a proper hydrologic structure to apply the well‐studied theory to large‐scale hydrologic predictions. This study aims to present a novel hydrologic structure that enables the Boussinesq equation‐based depiction of the bidirectional stream‐hillslope processes for applying hydraulic GW theory to large‐scale model configurations. We integrated the BE3S's (Hong et al., 2020, https://doi.org/10.1029/2020wr027571) representation scheme of the catchment‐scale stream‐hillslope continuum into the National Water Model (NWM) and applied the modified NWM (i.e., the NWM‐BE3S) to three major basins in Texas (i.e., the Trinity, Brazos, and Colorado River basins). Since the NWM currently relies on a single reservoir model for baseflow simulation, we used the Boussinesq aquifer as an alternative subsurface hydrology routine and evaluated its predictive skill and efficacy. We identified that the implemented Boussinesq aquifer(s) in the NWM‐BE3S yielded noticeable improvements in predicting streamflow for aquifers that exhibited higher nonlinearities in the observed recessions. The varying degree of improvements in streamflow predictions per the recession nonlinearities demonstrated not only (a) the algorithmic enhancement of subsurface hydrology (physics) but also (b) the applicability of the Boussinesq theory‐based depiction of the stream‐hillslope two‐way continuum. We diagnosed each stream's state based on the bidirectional stream‐hillslope exchanges and identified the dominant processes (i.e., river infiltration or baseflow) that were represented spatially in the NWM‐BE3S. Plain Language Summary: Streamflow is a critical land hydrologic component to manage water resources and the health of the associated ecosystem. While the water cycle between the stream and hillslope is the key process to accurately simulating streamflow, most currently used hydrologic/land surface models lack a theoretical basis to characterize the catchment‐scale groundwater to depict the stream‐hillslope water cycle. In this paper, we presented a new structure NWM‐BE3S that enables the Boussinesq approximation‐based characterization of the catchment(s) for improving the predictability of streamflow. The NWM‐BE3S was developed by integrating a recent numerical scheme BE3S (Hong et al., 2020, https://doi.org/10.1029/2020wr027571) into the WRF‐Hydro National Water Model (NWM) configuration as an alternative subsurface routing routine. The NWM‐BE3S was tested against streamflow observations from three major basins in Texas (i.e., the Trinity, Brazos, and Colorado River basins) to ensure the applicability of the Boussinesq‐based stream‐hillslope continuum scheme. We identified theory‐consistent improvements in the streamflow predictions from the NWM‐BE3S framework compared to the original NWM. Based on the two‐way fluxes modeled from the hydraulically continuous catchment(s) in the NWM‐BE3S, moreover, about 10% of the river reaches in the three basins were identified as losing streams during the evaluation period. Key Points: The Boussinesq theory‐based stream‐hillslope two‐way hydrologic interactions were newly introduced in the National Water Model (NWM)The Boussinesq aquifer yielded improved streamflow predictions than the single bucket model as the nonlinearity of recession increasesGaining or losing reaches in three Texas major basins showed improved predictions using the modified NWM [ABSTRACT FROM AUTHOR]

Rapid disaster assessment is critical for public security and rescue. As a secondary disaster of large-scale meteorological disasters, power outages cause severe outcomes and thus need to be monitored efficiently and without being costly. Power outage detection from space-borne remote sensing imagery offers a broader coverage and is more temporally sensitive than ground-based surveys are. However, it is challenging to determine the affected area accurately and quantitatively evaluate its severity. Therefore, a new method is proposed to solve the above problems by building a power outage detection model (PODM) and drawing a power outage spatial distribution map (POSDM). This paper takes the winter storm Uri, of 2021, as the meteorological disaster background and Harris County, Texas, which was seriously affected, as the research object. The proposed method utilises the cloud-free VIIRS DNB nadir and close nadir images (<60 degrees) collected during the 3 months before and 15 days after Uri. The core idea beneath the proposed method is to compare the radiance difference in the affected area before and after the disaster, and a large difference in radiance indicates the happening of power outages. The raw radiance of night light measurement is first corrected to remove lunar and atmospheric effects to improve accuracy. Then, the maximum and minimum pixels in the target area of the image are considered outliers and iteratively eliminated until the standard deviation change before and after elimination is less than 1% to finalize the outlier removals. The case study results in Harris show that the PODM detects 28% of outages (including traffic area) compared to 17% of outages (living area only) reported by ground truth data, indicating general agreement with the proposed method. [ABSTRACT FROM AUTHOR]

Blockchain technology, with its peer-to-peer trading feature, influences the management of energy consumption by offering the potential to transform transparency, efficiency, and sustainability within the energy sector. Nonetheless, there is a need to develop analytical decision-making models tailored for managing peer-to-peer energy transactions to improve energy resilience. Therefore, the purpose of this paper is to address the research question: How can energy distribution systems be protected via blockchain technology to enhance energy resilience and mitigate vulnerabilities to disruptions ? This paper employs a conceptual research model design and a mathematical decision-making model to address the research question by capturing the peer-to-peer trading capability of blockchain technology. The theory of planned behavior provides theoretical explanations for the proposed model. The sample includes longitudinal energy consumption data from 2015 to 2023 in Texas. The findings indicate a significant improvement in energy efficiency along with a considerable decrease in total electricity consumption. Post hoc analysis results reveal that the seasonal autoregressive integrated moving average algorithm is effective as a reliable input for the proposed mathematical model. The significant implications are to implement blockchain-based smart grids in which energy systems become more resilient to disruptions, as the peer-to-peer capability enables users to trade energy. The proposed model suggests that energy will be used more efficiently and effectively. This paper contributes to prior works by introducing a mathematical model that captures the trading behavior of energy consumers. Moreover, this paper proposes the SARIMA algorithm to predict energy demand. • A mathematical peer-to-peer trading model is presented to improve resilience. • A blockchain-based smart grid is presented for consumer energy consumption. • Five machine learning algorithms are presented in energy demand management. • Longitudinal energy consumption data of Texas is used in the model. • Theoretical support is provided using the theory of planned behavior. [ABSTRACT FROM AUTHOR]

Background: Organizational readiness is a key factor for successful implementation of evidence-based interventions (EBIs), but a valid and reliable measure to assess readiness across contexts and settings is needed. The R = MC2 heuristic posits that organizational readiness stems from an organization's motivation, capacity to implement a specific innovation, and its general capacity. This paper describes a process used to examine the face and content validity of items in a readiness survey developed to assess organizational readiness (based on R = MC2) among federally qualified health centers (FQHC) implementing colorectal cancer screening (CRCS) EBIs. Methods: We conducted 20 cognitive interviews with FQHC staff (clinical and non-clinical) in South Carolina and Texas. Participants were provided a subset of items from the readiness survey to review. A semi-structured interview guide was developed to elicit feedback from participants using "think aloud" and probing techniques. Participants were recruited using a purposive sampling approach and interviews were conducted virtually using Zoom and WebEx. Participants were asked 1) about the relevancy of items, 2) how they interpreted the meaning of items or specific terms, 3) to identify items that were difficult to understand, and 4) how items could be improved. Interviews were transcribed verbatim and coded in ATLAS.ti. Findings were used to revise the readiness survey. Results: Key recommendations included reducing the survey length and removing redundant or difficult to understand items. Additionally, participants recommended using consistent terms throughout (e.g., other units/teams vs. departments) the survey and changing pronouns (e.g., people, we) to be more specific (e.g., leadership, staff). Moreover, participants recommended specifying ambiguous terms (e.g., define what "better" means). Conclusion: Use of cognitive interviews allowed for an engaged process to refine an existing measure of readiness. The improved and finalized readiness survey can be used to support and improve implementation of CRCS EBIs in the clinic setting and thus reduce the cancer burden and cancer-related health disparities. [ABSTRACT FROM AUTHOR]

Harris County, TX, is the third most populous county in the USA and upon detection of arboviruses Harris County Public Health applies insecticides (e.g., pyrethroid-based Permanone 31–66) against adults of Culex quinquefasciatus to prevent disease transmission. Populations of Aedes aegypti, while not yet a target of public health control, are likely affected by pyrethroid exposure. As this species is a vector of emerging arboviruses, its resistance status to Permanone and the kdr mutations in the voltage-gated sodium channel (VGSC) associated with pyrethroid resistance were investigated. We examined females of known genotype at the V1016I and F1534C sites (N = 716) for their genotype at the 410 amino acid position in the VGSC, and for the influence of their kdr genotype on survival to Permanone at three different distances from the insecticide source in field tests. Most females (81.8%) had at least one resistant L allele at the 410 position, being the first report of the V410L mutation in Ae. aegypti for Texas. When only genotypes at the 410 position were analyzed, the LL genotype exhibited higher survivorship than VL or VV. Out of 27 possible tri-locus kdr genotypes only 23 were found. Analyses of the probability of survival of tri-locus genotypes and for the V410L genotype using a multivariate logistic regression model including area, distance, and genotype found significant interactions between distance and genotype. When only the most common tri-locus genotypes were analyzed (LL/II/CC, 48.2%; VL/II/CC, 19.1%; and VV/II/CC, 10.1%) genotype had no effect on survival, but significant interactions of distance and genotype were found. This indicated that the V410L kdr allele increased survival probability at certain distances. Genotypes did not differ in survivorship at 7.62-m, but LL/II/CC had higher survivorship than VL/II/CC at 15.24- and 22.86-m. The model also identified differences in survivorship among the operational areas investigated. Author summary: Preventing Aedes aegypti populations from spreading arboviruses in highly populated areas primarily relies upon chemical control with insecticides, such as pyrethroids, applied by public health agencies to target the female mosquito vector. However, the development of insecticide resistance in mosquito populations jeopardizes these vector control strategies. The impact of the different kdr mutations conferring resistance to pyrethroids on the survival of Ae. aegypti in the field is not fully understood. We previously found that two knockdown resistance (kdr) mutations in the voltage gated sodium channel (VGSC) did not increase survivorship in field cage tests despite their widespread presence and high frequency. In this paper, we report the first detection of the V410L kdr mutation in combination with the V1016I and F1534C genotypes. Most females were detected with kdr mutations at one, two or three of these sites in the VGSC. Genotyping females after insecticide application in field cage tests showed that the V410L mutations were associated with higher survivorship only at the 15.24- and 22.86-meter distances from the source of the spray application, as we observed that the LL/II/CC genotype had higher survivorship than the VL/II/CC genotype at these distances. [ABSTRACT FROM AUTHOR]

Motivated by the relatively infrequent but very large price spikes in the day-ahead and real-time energy markets operated by the Electric Reliability Council of Texas, this paper proposes an insurance that a small and risk-averse retailer in Texas (i.e., a retail electric provider (REP)) may buy to prevent financial insolvency caused by inadequate risk management. It also demonstrates the insurance's practical design, pricing, and implementation. As participation in the REP's procurement auction is voluntary, the insurance is mutually beneficial for the REP and the insurance seller. Hence, the proposed insurance is a newly developed wholesale market product that deserves consideration by REPs in Texas and competitive retailers elsewhere. [ABSTRACT FROM AUTHOR]

Background: This paper performs a detailed ordinal logistic regression study in an evaluation of a survey at a university in South Texas, USA. We show that, for categorical data in our case, ordinal logistic regression works well. Methods: The survey was designed according to the guidelines in diet and lifestyle from the American Heart Association and the United States Department of Agriculture and was sent out to all registered students at Texas A&M International University in Laredo, Texas. Data analysis included 601 students' results from the survey. Data analysis was conducted in Rstudio. Results: The results showed that, compared with students who do not have enough whole grain food and exercise, those who have enough in both tend to have normal BMIs. As age increases, BMI tends to be out of the normal range. Conclusions: Because BMI in this research has three categories, applying an ordinal logistic regression model to describe the relationship between an ordered categorical response variable and more explanatory variables has several advantages compared with other models, such as the linear regression model. [ABSTRACT FROM AUTHOR]

Automatically detecting the wet/dry shoreline from remote sensing imagery has many benefits for beach management in coastal areas by enabling managers to take measures to protect wildlife during high water events. This paper proposes the use of a modified HED (Holistically-Nested Edge Detection) architecture to create a model for automatic feature identification of the wet/dry shoreline and to compute its elevation from the associated DSM (Digital Surface Model). The model is generalizable to several beaches in Texas and Florida. The data from the multiple beaches was collected using UAS (Uncrewed Aircraft Systems). UAS allow for the collection of high-resolution imagery and the creation of the DSMs that are essential for computing the elevations of the wet/dry shorelines. Another advantage of using UAS is the flexibility to choose locations and metocean conditions, allowing to collect a varied dataset necessary to calibrate a general model. To evaluate the performance and the generalization of the AI model, we trained the model on data from eight flights over four locations, tested it on the data from a ninth flight, and repeated it for all possible combinations. The AP and F1-Scores obtained show the success of the model's prediction for the majority of cases, but the limitations of a pure computer vision assessment are discussed in the context of this coastal application. The method was also assessed more directly, where the average elevations of the labeled and AI predicted wet/dry shorelines were compared. The absolute differences between the two elevations were, on average, 2.1 cm, while the absolute difference of the elevations' standard deviations for each wet/dry shoreline was 2.2 cm. The proposed method results in a generalizable model able to delineate the wet/dry shoreline in beach imagery for multiple flights at several locations in Texas and Florida and for a range of metocean conditions. [ABSTRACT FROM AUTHOR]

Scientific studies have provided evidence that there is a relationship between violent and aggressive behaviors and addictions. Genes involved with the reward system, specifically the brain reward cascade (BRC), appear to be associated with various addictions and impulsive, aggressive, and violent behaviors. In our previous research, we examined the Taq A1 allele (variant D2 dopamine receptor gene) and the DAT-40 base repeat (a variant of the dopamine transporter gene) in 11 Caucasian boys at the Brown School in San Marcus, Texas, diagnosed with intermittent explosive disorder. Thirty supernormal controls were screened to exclude several reward–deficit behaviors, including pathological violence, and genotyped for the DRD2 gene. Additionally, 91 controls were screened to exclude ADHD, pathological violence, alcoholism, drug dependence, and tobacco abuse, and their results were compared with DAT1 genotype results. In the schoolboys vs. supercontrols, there was a significant association with the D2 variant and a trend with the dopamine transporter variant. Results support our hypothesis and the involvement of at least two gene risk alleles with adolescent violent/aggressive behaviors. This study and the research presented in this paper suggest that violent/aggressive behaviors are associated with a greater risk of addiction, mediated via various genes linked to the BRC. This review provides a contributory analysis of how gene polymorphisms, especially those related to the brain reward circuitry, are associated with violent behaviors. [ABSTRACT FROM AUTHOR]

This paper demonstrates that false data injection (FDI) attacks are extremely limited in their ability to cause physical consequences on $N-1$ reliable power systems operating with real-time contingency analysis (RTCA) and security constrained economic dispatch (SCED). Prior work has shown that FDI attacks can be designed via an attacker-defender bi-level linear program (ADBLP) to cause physical overflows after re-dispatch using DCOPF. In this paper, it is shown that attacks designed using DCOPF fail to cause overflows on $N-1$ reliable systems because the system response modeled is inaccurate. An ADBLP that accurately models the system response is proposed to find the worst-case physical consequences, thereby modeling a strong attacker with system level knowledge. Simulation results on the synthetic Texas system with 2000 buses show that even with the new enhanced attacks, for systems operated conservatively due to $N-1$ constraints, the designed attacks only lead to post-contingency overflows. Moreover, the attacker must control a large portion of measurements and physically create a contingency in the system to cause consequences. Therefore, it is conceivable but requires an extremely sophisticated attacker to cause physical consequences on $N-1$ reliable power systems operated with RTCA and SCED. [ABSTRACT FROM AUTHOR]

To prevent climate change, Europe and the world must shift to low-carbon and renewable energies. Hydrogen, as an energy vector, provides viable solutions for replacing polluting and carbon-emitting fossil fuels. Gaseous hydrogen can be stored underground and coupled with existing natural gas pipe networks. Salt cavern storage is the best suited technology to meet the challenges of new energy systems. Hydrogen storage caverns are currently operated in the UK and Texas. A preliminary risk analysis dedicated to underground hydrogen salt caverns highlighted the importance of containment losses (leaks) and the formation of gas clouds following blowouts, whose ignition may generate dangerous phenomena such as jet fires, unconfined vapor cloud explosions (UVCEs), or flashfires. A blowout is not a frequent accident in gas storage caverns. A safety valve is often set at a 30 m depth below ground level; it is automatically triggered following a pressure drop at the wellhead. Nevertheless, a blowout remains to be one of the significant accidental scenarios likely to occur during hydrogen underground storage in salt caverns. In this paper, we present modelling the subterraneous and aerial parts of a blowout on an EZ53 salt cavern fully filled with hydrogen. [ABSTRACT FROM AUTHOR]

This paper illustrates the scope and contribution that the discipline of geomorphology can offer in environmental litigation. The case in question was filed by two plaintiffs who contended that the construction of a storage facility on an adjacent property had caused significant disturbance of the topsoil, and that runoff from the impermeable surfaces (e.g., roofs, driveways) had exacerbated the problem by eroding and transporting soil and fill material from the facility directly into three ponds owned by them. They sued for $1.6 million to cover dredging, restoration of the ponds, and disposal of the sediment. Utilizing a range of geomorphological techniques, I was able to determine the most likely source area(s) of eroded sediment within the basin and quantify the extent to which the defendant's property contributed runoff and sediment to the ponds. The lawsuit was dismissed before ever going to trial. In the paper, I discuss the steps involved in the process of being an expert witness and also share some of the advice I have received from attorneys with whom I have worked. I emphasize the importance of setting any case study within a larger spatial context and encourage my fellow geomorphologists to become involved as experts in litigation because, in most instances, we can contribute to an appropriate outcome. [ABSTRACT FROM AUTHOR]

Purpose: Providing timely access is an important measure of patient satisfaction in specialty care clinics such as cancer centers. Excessive patient wait time to see an oncologist is very critical for cancer patients as they often benefit from starting the treatment process as soon as possible. This paper addresses capacity planning for both new and returning patients in cancer clinics. This research is motivated by a cancer center in Texas that seeks to improve its clinical performance to decrease new patient wait time to see an oncologist.//Design/methodology/approach: A simulation model is proposed to assess new patient access to oncologists when employing several tactical and operational policies such as resource flexibility, specialization flexibility, and reserving slots for new patients. The model utilizes two years of data collected from a cancer center in Texas. Findings: The results suggest the best combination of operating policies in order to allocate patient demand to providers. This study also determines the required capacity level to provide timely access for new patients. Originality/value: Although the literature in outpatient scheduling and capacity planning is rich, new patient access in oncology clinics has received limited attention. The few existing studies do not consider patient no-shows and cancellations, and to the best of our knowledge, no study addresses individual oncologist clinic flexibility and the idea of reserving slots for new patients. [ABSTRACT FROM AUTHOR]

This paper focuses on deriving and validating the fractional-order form of rectified linear unit activation function and its linear and nonlinear variants. The linear variants include the leaky and parametric, whereas the nonlinear variants include the exponential, sigmoid-weighted, and Gaussian error functions. Besides, a standard formula has been created and used while developing the fractional form of linear variants. Moreover, different expansion series such as Maclaurin and Taylor have been used while designing the fractional version of nonlinear variants. A simulation study has been conducted to validate the performance of all the developed fractional activation functions utilizing a single and multilayer neural network model and to compare them with their conventional counterparts. In this simulation study, a neural network model has been created to predict the system-generated power of a Texas wind turbine. The performance has been evaluated by varying the activation function in the hidden and output layers with the developed functions for single and multilayer networks. [ABSTRACT FROM AUTHOR]

Geoenvironmental models were formulated by the U.S. Geological Survey in the 1990s to describe potential environmental effects of extracting different types of ore deposits in different geologic and climatic regions. This paper presents a geoenvironmental model for roll-front (roll-type) uranium deposits in the Texas Coastal Plain. The model reviews descriptive and quantitative information derived from environmental studies and existing databases to depict existing conditions and potential environmental concerns associated with mining this deposit type. This geoenvironmental model describes how features of the deposits including host rock; ore and gangue mineralogy; geologic, hydrologic, and climatic settings; and mining methods (legacy open-pit and in situ recovery [ISR]) influence potential environmental effects from mining. Element concentrations in soil and water are compared to regulatory thresholds to depict ambient surface water and groundwater conditions. Although most open-pit operations in this region have been reclaimed, concerns remain about groundwater quality at three of the four former mills that supported former open-pit mines and are undergoing closure activities. The primary environmental concerns with ISR mining are (1) radon gas at active ISR operations, (2) radiation or contaminant leakage during production and transport of ISR resin or yellowcake, (3) uranium excursions into groundwater surrounding active ISR operations, and (4) contamination of groundwater after ISR mining. Although existing regulations attempt to address these concerns, some problems remain. Researchers suggest that reactive transport modeling and a better understanding of geology, stratigraphy, and geochemistry of ISR production areas could minimize excursions into surrounding aquifers and improve results of groundwater restoration. [ABSTRACT FROM AUTHOR]

Stochastic optimization can be used to model predictable but uncertain element failures, in an attempt to enhance system reliability in power system operation and planning. In practical applications, such as preventive operation during severe weather, the uncertainty set is often very large. This will lead to two challenges: (i) every possible scenario cannot be practically identified; and (ii) the computational demands of stochastic optimization with a large scenario set cannot be met. To address these challenges, this paper develops a multidimensional scenario selection method, which creates a rather small but representative set of scenarios. The developed method makes use of failure features as well as network features of the elements that may fail, to achieve a superior performance. The simulations studies on a synthetic large-scale Texas system, show the dominant performance of the method compared to existing algorithms in the literature, as well as common industry practices. Due to its effectiveness, the method presented in this paper enables computationally efficient implementation of stochastic power system operation and planning software tools. Such stochastic tools will improve system reliability and efficiency through enhanced use of the existing resources, without requiring any expensive system upgrade. [ABSTRACT FROM AUTHOR]

A previously completed mineral resources assessment of the Texas Coastal Plain indicated the potential for the future discovery of uranium resources. Geoenvironmental assessments that include the hydrogeologic framework can be used as a tool to understand the potential effects of mining operations. The hydrogeologic framework for this study focused on the composite hydrogeologic unit of the tract permissive for the occurrence of uranium consisting of the upper part of the Miocene-age Fleming Formation/Lagarto Clay, Pliocene-age Goliad and Pleistocene-age Willis Sands, Pleistocene-age Lissie and Beaumont Formations, and Holocene-age alluvial sediments (fluvial alluvium and eolian sand deposits). This composite hydrogeologic unit, which contains the Chicot and Evangeline aquifers of the Gulf Coast aquifer system, is intended for inclusion in a regional-scale geoenvironmental assessment of as yet undiscovered uranium resources. This article provides (1) a brief literature review describing the geologic and hydrogeologic settings, (2) the methodology used to develop a composite hydrogeologic framework, and (3) descriptions and maps of the land-surface altitude, composite hydrogeologic unit base and midpoint depth, water-level altitude, depth of water, unsaturated and saturated zone thickness, and transmissivity and hydraulic conductivity. A composite hydrogeologic unit, created by combining geologic and hydrogeologic data and maps for individual geologic and hydrogeologic units, is intended for use as a tool in a geoenvironmental assessment to evaluate potential contaminant migration through various avenues. Potential applications include using the hydrogeologic framework as an input into a geoenvironmental assessment to help estimate the potential for (1) runoff of contaminants into surface water, (2) infiltration of contaminants into the groundwater (aquifers), or (3) movement of contaminants from the mining area through wind, groundwater-flow, or streamflow in a given permissive tract. The procedures outlined in this paper also provide a method for developing hydrogeologic frameworks that can be applied in other areas where mining may occur. [ABSTRACT FROM AUTHOR]

We describe the instrumentation, calibration, and uncertainty of the network of ground-based, in situ, cavity ring down spectroscopy (CRDS) greenhouse gas (GHG) measurements deployed in the Permian basin. The primary goal of the network is to be used in conjunction with atmospheric transport modeling to determine methane emissions of the Delaware sub-basin of the Permian Basin oil and natural gas extraction area in Texas and New Mexico. Four of the measurements are based on tall communications towers, while one is on a building on a mountain ridge, with the recent addition of a small tower at that site. Although methane (CH4) is the primary specie of interest, carbon dioxide (CO2), hydrogen sulfide (H2S), and the isotopic ratio of methane (δ13CH4) are also reported for a subset of the sites. Measurements were reported following WMO X2004A scale for CH4, and the WMO X2019 scale for CO2. CRDS instruments were calibrated for CH4 and CO2 in laboratory prior deployment. For H2S, data was offset-corrected using the minimum 40-min running mean value of the day, and for δ13CH4, calibrations were based on laboratory data. We describe the characteristics of the data set with a set of illustrative analyses. Methane and carbon dioxide showed strong seasonality, with a well-defined diurnal cycle during the summer, which was opposed to the winter, when a diurnal cycle was absent. CH4 enhancements to the background, during the winter, are up to twice the summer values, which is attributed to the changes in boundary layer depth and wind speed. The largest CH4 enhancements occurred when winds blow from the center of the Delaware sub-basin, where most of the methane emissions come from. The magnitude of enhancements of CO2 did not present seasonality. H2S enhancements indicated a potential source northeast of the tower where the inlet is installed. Isotopic ratios of methane indicated that oil and natural gas extraction is the source of local methane in the region. The hourly-averaged data, starting on 1 March 2020 and described in this paper, are archived at The Pennsylvania State University Data Commons at https://doi.org/10.26208/98y5-t941 (Monteiro et al., 2021). [ABSTRACT FROM AUTHOR]

Extreme temperature outages can lead to not just economic losses but also various non-energy impacts (NEI), such as increased mortality rates, property damage, and reduced productivity, due to significant degradation of indoor operating conditions caused by service disruptions. However, existing resilience assessment approaches lack specificity for extreme temperature conditions. They often overlook temperature-related mortality and neglect the customer characteristics and grid response in the calculation, despite the significant influence of these factors on NEI-related economic losses. This paper aims to address these gaps by introducing a comprehensive framework to estimate the impact of resilience enhancement not only on the direct economic losses incurred by customers but also on potential NEI, including mortality and the value of statistical life during extreme temperature-related outages. The proposed resilience valuation integrates customer characteristics and grid response variables based on a scalable grid simulation environment. This study adopts a holistic approach to quantify customer-oriented economic impacts, utilizing probabilistic loss scenarios that incorporate health-related factors and damage/loss models as a function of exposure for valuation. The proposed methodology is demonstrated through comparative resilient outage planning, using grid response models emulating a Texas weather zone during the 2021 winter storm Uri. The case study results show that enhanced outage planning with hardened infrastructure can improve the system resilience and thereby reduce the relative risk of mortality by 16% and save the total costs related to non-energy impacts by 74%. These findings underscore the efficacy of the framework by assessing the financial implications of each case, providing valuable insights for decision-makers and stakeholders involved in extreme-weather related resilience planning for risk management and mitigation strategies. • Framework for the value of customer resilience by extreme temperature-related outages • Resilience valuation using customer characteristics and grid variables in simulations • Loss scenarios using customer factors and temperature-based damage models • Applying resilience valuation to 2021 Winter Storm Uri use-case [ABSTRACT FROM AUTHOR]

• An unprecedented very large-scale T&D dataset covering Texas is made publicly available. • The sheer size of this dataset is intended to provide a challenge for the scientific community. • This lays the foundation for demonstrating the coordination of T&D. • It can help foster the improvement of algorithms and tools for years to come. Distributed energy resources, such as rooftop solar, have rapidly expanded in recent years, given declining costs and the desire to reduce carbon emissions. With more energy resources located in the lower-voltage distribution system, it is increasingly helpful to utilize combined transmission and distribution (T&D) system models to analyze interactions between these normally-distinct subsystems. This paper proposes a methodology for creating very large-scale, highly detailed, combined T&D systems that are synthetic—that is, free from non-public data—yet still realistic. The methodology creates very large-scale combined T&D systems by merging the most up-to-date techniques for creating synthetic distribution feeder networks with the latest methods for building synthetic, meshed bulk-power transmission networks. This methodology is demonstrated on a T&D system geolocated in Texas, and benchmarked with co-simulation results. Validation demonstrates that the resulting syn -texas-TDgrid synthetic test system realistically represents characteristics found in actual networks, addressing the lack of available T&D test systems. With over 15,000 feeders and 46 million electrical nodes, this T&D dataset has applications for research in optimal power flow algorithms, voltage control, reconfiguration, and T&D coordination schemes under high adoption of distributed energy resources. [ABSTRACT FROM AUTHOR]

There are multiple common methods for collecting fossil material in the field for paleoecological analyses, so it is important to determine if and how different methods may affect the similarities and differences among taxonomic samples. Here, we evaluate the influence of two fossil collection field methods (stratigraphically in-place bulk-sediment versus picking up weathered-out fossils from the ground surface) on paleoecological results, using the Pennsylvanian marine invertebrate assemblages of the Finis Shale in Texas. Based on an informal review of recent paleoecology papers, we observed that the lithology of the study material and the nature of the research question correspond to choice of field collection protocols; however, collection protocols are not always clearly explained or justified in the text of the papers. For the present case study, we collected stratigraphically equivalent samples from three outcrops using both the surface pick-up and in-place bulk sediment methods. We found a difference in the abundance and composition of paleocommunities between these two collection methods. Evidence to support this includes the significant differences between samples using PERMANOVA (p < 0.001), the clear separation in ordination space of samples clustered by sampling method, the significantly higher richness in the surface samples (p < 0.001), and the considerable variation in relative abundances of various taxa and taxonomic groups. Richness and evenness were higher among the surface-collected samples, possibly due to collector bias, weathering artifacts, or spatial and temporal variability. Paleontologists strive to do the best science possible with the material available. Often, paleoecological research methods are limited by time, funding, or the nature of the material. In such cases, we recommend examining both collection methods, even if for only a fraction of the sampling. If only one method is possible, we recommend the use in-place, bulk-collected samples. [ABSTRACT FROM AUTHOR]

This paper proposes and tests a multilayer framework for simulating the network dynamics of inter-organizational coordination among interdependent infrastructure systems (IISs) in resilience planning. Inter-organizational coordination among IISs (such as transportation, flood control, and emergency management) would greatly affect the effectiveness of resilience planning. Hence, it is important to examine and understand the dynamics of coordination in networks of organizations within and across various systems in resilience planning. To capture the dynamic nature of coordination frequency and the heterogeneity of organizations, this paper proposes a multilayer network simulation framework enabling the characterization of inter-organizational coordination dynamics within and across IISs. In the proposed framework, coordination probabilities are utilized to approximate the varying levels of collaboration among organizations. Based on these derived collaborations, the simulation process perturbs intra-layer or inter-layer links and unveils the level of inter-organizational coordination within and across IISs. To test the proposed framework, the study examined a multilayer collaboration network of 35 organizations from five infrastructure systems within Harris County, Texas, based on the data gathered from a survey in the aftermath of Hurricane Harvey. The results indicate that prior to Hurricane Harvey: (1) coordination among organizations across different infrastructure systems is less than the coordination within the individual systems; (2) organizations from the community development system had a low level of coordination for hazard mitigation with organizations in flood control and transportation systems; (3) achieving a greater level of coordination among organizations across infrastructure systems is more difficult and would require a greater frequency of interaction (compared to within-system coordination). The results show the capability of the proposed multilayer network simulation framework to examine inter-organizational coordination dynamics at the system level (e.g., within and across IISs). The assessment of inter-organizational coordination within and across IISs sheds light on important organizational interdependencies in IISs and leads to recommendations for improving the resilience planning process. [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]

The adoption rate for Leadership in Energy and Environmental Design – Neighborhood Development (LEED-ND) projects has varied considerably across the United States. Local governments and developers face variation in the incentives and barriers while implementing LEED-ND projects across four key dimensions – economic, policy, public awareness, and organizational. This paper investigated the drivers of variation using a mixed-methods approach including a two-stage Heckman model, a survey of Texas subdivision developers and interviews with local planning officials. Results indicate that initial public funding may lead to more LEED-ND projects being completed, but with a diminishing return as these projects become established within the region. Support for local programs including tax abatement, public-private partnerships, and other incentives were also demonstrated to help facilitate LEED-ND project adoption. Overall this paper underscored the important role, especially early on, the public sector and local governments play in initiating local LEED-ND projects to inform and motivate the land development industry. • U.S. LEED-ND projects face variation in adoption rates, barriers, and incentives. • 4 key dimensions identified – economic, policy, public awareness, and organizational. • Initial public funding may lead to more LEED-ND projects being completed. • Local interviews find support for local programs to incentivize further projects. [ABSTRACT FROM AUTHOR]

Cracks that develop during galvanization of High Mast Illumination Poles (HMIPs), often at the pole-to-base plate connection, are an important concern to US fabricators and highway officials. If they are not detected during fabrication and are allowed to propagate during service, these cracks can pose a significant risk to the public due to the ubiquitous presence of HMIPs in close proximity to roads and highways. Economic losses caused by these cracks include the cost of detailed inspections to ascertain their presence and direct losses associated with discarded poles or repair of cracks that manifest while in service. Modifications to the design of HMIPs and/or the galvanization process to reduce the likelihood of galvanization cracks reduce economic loses, decrease fabrication costs, and improve public safety. This paper presents a parametric study evaluating the effects of geometric configuration and galvanization practices on thermally-induced stress/strain demands during the galvanization of HMIPs. Simulations were performed for poles with standard pole-to-base plate connection details adopted by the Texas DOT. Geometric parameters evaluated in the study included base plate-to-pole thickness ratio, pole shaft geometric shape, and bend radius. Galvanizing practice variables included dwell time, speed and angle of dipping, and cross-section orientation. Simulations were conducted using the commercial software Abaqus, following the methodology validated in a companion paper. In models having the same pole thickness, thermally-induced stresses and strains at critical locations increased with base plate-to-pole thickness ratio. In models with the same base plate thickness, stress and strain demands varied inversely proportional to pole thickness. Stress and strain demands were found to be lower for poles having circular shape than for multi-sided poles, and increases in bend radius led to reductions in localized strain demands. Dwell time was found to have a negligible effect on stress and strain demands, while increased dipping speed and dipping angle resulted in decreased stress and strain demands during galvanizing. • A numerical parametric study was conducted to study galvanization cracks in HMIPs. • The contribution of shape and galvanizing parameters to weld-toe cracks was evaluated. • Base plate-to pole thickness ratio was found to play a key role on crack formation. • Circular poles exhibited the lowest stress/strain demands during galvanizing. • Reducing dipping time and increasing dipping angles reduced plastic deformations. [ABSTRACT FROM AUTHOR]

This conceptual paper analyzes persistent challenges to racially diversify higher education in Texas, paying special attention to trends at this Southern state's most selective flagship--University of Texas at Austin. We apply critical race theorist Kimberlè Crenshaw's frame of race liberalism and her view of equality as either expansive or restrictive to analyze race-neutral approaches intended to remedy longstanding issues of racial diversity. Specifically, we focus on the Texas Top Ten Percent Policy, tracing its trajectory from affirmative action through the recent Abigail Fisher case. This examination clarifies the race-evasive basis of policies designed to improve enduring issues of racial exclusion in higher education. [ABSTRACT FROM AUTHOR]