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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]

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]

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]

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]

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]

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]

Carbon capture and sequestration from a stationary source comprises four distinct engineering processes: separation of CO2 from the other flue gases, compression, transportation, and injection into the chosen storage site. An analysis of the thermodynamic and transport properties of CO2 shows that dissolving this gas in seawater at depths more than 600 m is, most likely, an optimal long-term storage method; and that for transportation, the CO2 must be in the denser supercritical state at pressures higher than 7.377 MPa. The separation, compression, transportation, and injection processes require significant energy expenditures, which are determined in this paper using realistic equipment efficiencies, for the cases of two currently in operation coal power plants in Texas. The computations show that the total energy requirements for carbon removal and sequestration are substantial, close to one-third of the energy currently generated by the two power plants. The cost analysis shows that two parameters - the unit cost of the pipeline and the discount factor of the corporation - have a very significant effect on the annualized cost of the CCS process. Doubling the unit cost of the pipeline increases the total annualized cost of the entire CCS project by 36% and increasing the discount rate from 5% to 15% increases this annualized cost by 32%. [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]

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]

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]

This paper investigates the strategic pricing behavior of a leader in a two-person, noncooperative game when profits depend on the purchasing response of a follower who not only reacts to changing prices instantaneously, but also builds long-lived consumption infrastructure that affects future demand. As an application of such a system, we formulate the relationship between these players in the natural gas and electricity generation industries as a bilevel problem. The leader is a natural gas producer whose objective is to maximize profit; the follower is an electric utility who solves a capacity expansion and dispatch problem with the objective of minimizing the cost of electricity generation and long-run investments. To find solutions, the bilevel problem is reformulated as a mixed-integer linear program by replacing the lower-level player's model with its Karush–Kuhn–Tucker conditions, which are necessary and sufficient for optimality here, and linearizing the upper-level player's objective function using the strong duality conditions of the lower-level problem. After parameterizing the model with publicly available data for Texas, we conduct scenario analyses through 2040, evaluating strategies of the natural gas producer under different policies regarding carbon taxes and incentives for carbon capture and storage (CCS). We then observe how the lower-level player responds to these strategies in terms of the evolution of the generation mix, added capacity, and CO 2 emissions. We also quantify the effects of strategic pricing by running scenarios where natural gas prices are fixed. Key findings include: (1) different levels of carbon tax and CCS incentive can have non-monotonic effects on the optimal natural gas price and producer profit, (2) effects of CCS incentives can spill over to technologies without CCS, and (3) omission of strategic pricing from the model not only decreases the profit for the producer but also can increase the costs for the electricity sector. • Bilevel model for interaction between natural gas producer and electric utility. • Carbon policy effects on electricity capacity mix, generation mix, and CO 2 emissions. • Effectiveness of different reformulations of bilevel programming problems. • Demonstration of how strategic natural gas pricing affects carbon policy outcomes. [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]

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]

Fuzzy neural network systems (FNNSs) can incorporate the merits of fuzzy logic systems (FLSs) and neural networks (NN). This paper designs a type of non-singleton FNNSs for forecasting issues. The proposed hybrid backpropagation (BP) algorithms and recursive least square (RLS) algorithms are used for optimizing the parameters of antecedents, input measurements, and consequents simultaneously. Two computer simulation examples based on the data of European Network on Intelligent Technology (EUNITE) and data of west Texas intermediate (WTI) crude oil price are used for testing. Convergence analysis shows that the hybrid optimized FNNSs have very high generalization ability. [ABSTRACT FROM AUTHOR]

• Integrated techno-economic assessment of the hydrogen value chain in the Permian Basin, spanning production, storage, and transportation. • Identified cost benefits in feedstock and tax credits for Permian-based hydrogen, balanced by transport expenses to Houston. • Scaling up to 412,000 metric tons/year can counterbalance transportation costs, positioning the Permian Basin competitively in the hydrogen market. This paper investigates the untapped potential of the Permian Basin, a multifaceted energy axis in Texas and adjoining states, in the emerging era of decarbonization. Aligned with current policy directives on regional hydrogen hubs, this study explores the viability of developing a hydrogen energy hub in the Permian Basin, thereby producing low-carbon intensity hydrogen from natural gas in the Basin and transporting it to the Greater Houston area. Diverging from existing literature, this study provides an integrated techno-economic evaluation of the entire hydrogen value chain in the Permian Basin, encompassing production, storage, and transportation. Furthermore, it comparatively analyzes the scenario of interest against an optimized base scenario, thereby underlining comparative advantages and disadvantages. The paper concludes that the delivered cost of Permian-based low-carbon intensity hydrogen to the Greater Houston area is $1.85/kg, benchmarked to the scenario, with hydrogen produced close to the Greater Houston area and delivered at $1.42/kg. Our findings reveal that Permian-based low-carbon intensity hydrogen production can achieve cost savings in feedstock ($0.25/kg) and potentially accrue a higher production tax credit due to a shorter gas supply chain to production ($0.33/kg). Nevertheless, a significant cost barrier is the expense of long-haul pipeline transport ($0.90/kg) from the Permian Basin to Houston as opposed to local production. Despite the obstacles, the study identifies a potential breakeven solution where increasing the production scale to at least 412,000 metric ton per year (about 3 steam-reforming plants) in the Permian Basin can effectively lower costs in the transport sector. Hence a scaled-up production can mitigate the cost difference and establish the Permian Basin as a competitive player in the hydrogen market. In conclusion, a SWOT analysis presents Strengths, Weaknesses, Opportunities, and Threats associated with Permian-based hydrogen production. [ABSTRACT FROM AUTHOR]

As our environment becomes increasingly urban, the governance of urban regions faces multifaceted challenges. There is growing recognition that studying the governance of urban regions requires looking beyond individual plans and examining networks of plans. Existing work on plan networks focuses on documents, neglecting the agency of the people and governments who create and implement the plans. To help fill this gap, we develop and test an analytical framework for assessing urban governance within a network of plans, focusing on the alignment of plan content, interactions, and the relative efficacy of the plans. We apply this framework in metropolitan Austin, Texas (USA), studying five strategic plans that address the region's built environments, transportation systems, and natural areas over a 20 year-period. The analysis reveals how voluntary regional scenario-planning conducted decades earlier continues to shape city and regional development goals; how alignment between plans on paper can belie poor cross-jurisdictional coordination in practice; and how plans addressing transportation and natural areas are more efficacious for implementation than plans for the built environment. In addition to making plan dynamics visible, the framework thus allows for rigorous, empirical assessment of regional governance through a network of plans. • A framework is proposed to analyze urban-region governance with a network of plans. • The framework is tested with five strategic plans in Austin, Texas (USA). • Evidence is found of a network consisting of documents and agency. • Network-of-plan research benefits from the framework. [ABSTRACT FROM AUTHOR]

Using computer vision techniques such as stereo vision systems for sea state measurement or for offshore structures monitoring can improve the measurement fidelity and accuracy with no significant additional cost. In this paper, two experiments (in-lab/open-sea) are conducted to study the performance of stereo vision system to measure the water wave surface elevation and rigid body heaving motion. For the in-lab experiment, regular water waves are generated in a wave tank for different frequencies and wave heights, where the water surface is scanned by the stereo vision camera installed on the top of the tank. Surface elevation inferred by the stereo vision is verified by an installed stationary side camera that records the water surface through the tank transparent side window, water surface elevation measured by the side camera recordings is extracted using edge detection algorithm. During the in-lab experiment a heaving buoy is installed to test the performance of Visual Simultaneous Localization and Mapping (VSLAM) algorithm to monitor the buoy heave motion. The VSLAM algorithm fuses a buoy onboard stereo vision recordings with an embedded Inertial Measurement Unit (IMU) to estimate the 6-DOF of a rigid body. The Buoy motion VSLAM measurements are verified by a KLT tracking algorithm implemented on the video recordings of the stationary side camera. The open-sea experiment is implemented in Lake Somerville, Texas. The stereo vision system is installed to measure the water surface elevation and directional spectrum of the wind generated irregular waves. The open-sea wave measurements by the stereo vision are verified by a Sofar commercial wave buoys deployed in the testing location. • Edge detection is adequate for wave height measurement in wave tanks. • Stereo vision is effective for in-tank/open-sea wave height measurement. • Stereo vision is effective directional wave spectrum measurement. • KLT algorithm is accurate in planar rigid structure motion measurement. • VSLAM shows better accuracy when measuring small amplitudes than accelerometers. [ABSTRACT FROM AUTHOR]

VNIR-SWIR (400–2500 nm) reflectance measurements were made on the surfaces of various cores, cuttings and sample splits of sedimentary rocks from the Tertiary Jackson Group, and Catahoula, Oakville and Goliad Formations. These rocks vary in composition and texture from mudstone and claystone to sandstone and are known host rocks for roll front uranium occurrences in Karnes and Live Oak Counties, Texas. Spectral reflectance profiles, 569 in total, were reduced to 125 representative spectral signatures, which were analyzed using the U.S. Geological Survey's (USGS) Material Identification and Characterization Algorithm (MICA). MICA uses an automated continuum-removal procedure together with a least-squares linear regression to determine the fit of observed sample spectral absorption features to those of reference mineral standards in a spectral library. The reference minerals include various clay, mica, carbonate, ferric and ferrous iron minerals and their mixtures. In addition, absorption feature band-depth analysis was done to identify rock surfaces exhibiting absorption features related to uranium and zeolite minerals, which were not included in the command files used to execute MICA. Rocks from each of the four geologic units produced broadly similar spectral signatures as a result of comparable mineral compositions, but there were some notable differences. For example, Ca- and Na-montmorillonite was matched most frequently to the spectral absorption features in 2-μm (∼2000–2500 nm) wavelengths, while goethite occurred often at 1-μm (∼400–1000 nm) wavelengths. The latter is related to limonitic iron-staining in and around oxidized zones of the uranium roll front as described in previous papers. Rocks of the Jackson Group differed from those of the Catahoula, Oakville and Goliad units in that the former exhibited spectral features we interpret as being due to the presence of lignite-bearing mudstone layers. Goliad rocks exhibit spectral features related to dolomite, gypsum, anhydrite, and an unidentified green clay mineral that is possibly glauconite. Jackson Group rocks also exhibit weak but well-resolved absorption features at 964 and 1157 nm related to either or both zeolite minerals clinoptilolite and heulandite. These zeolite minerals and a few spectra exhibiting hydrous silica absorption features are indicative of alteration of volcanic glass in tuffaceous mudstone and claystone layers. A few sample spectra exhibited strong absorption features at around 1135 nm related to the uranium mineral coffinite. Both the 1135 nm coffinite and 1157 nm zeolite absorption features overlap somewhat, potentially making them difficult to distinguish without additional hyperspectral field, laboratory or remote sensing data. The results of this study were compared to mixtures of minerals described for ore, gangue and alteration minerals in deposit models for sandstone-hosted uranium, sedimentary bentonite and sedimentary zeolite. Use of these spectra can help facilitate mapping of both waste materials from the legacy mining of the above commodities, as well as future exploration and resource assessment activities. • Visible to infrared reflectance spectra were analyzed of uranium-hosting rocks. • These include the Jackson Group, Catahoula, Oakville, and Goliad Formations. • Compositional variability in ferric‑iron, clay, and carbonate minerals was determined. • Some rocks contain detectable zeolite and uranium industrial/critical minerals. • The data and methods in this work will be useful for future remote sensing studies. [ABSTRACT FROM AUTHOR]

Activation functions play an important role in deep learning models by introducing non-linearity to the output of a neuron, enabling the network to learn complex patterns and non-linear relationships in data and make predictions on more complex tasks. Deep learning models' most commonly used activation functions are Purelin, Sigmoid, Tansig, Rectified Linear Unit (ReLU), and Exponential Linear Unit (ELU), which exhibit limitations such as non-differentiability, vanishing gradients, and neuron inactivity with negative values. These functions are typically defined over a finite range, and their outputs are integers or real numbers. Using fractional calculus in designing activation functions for neural networks has shown promise in improving the performance of deep learning models in specific applications. These activation functions can capture more complex non-linearities than traditional integer-order activation functions, improving performance on tasks such as image classification and time series prediction. This paper focuses on deriving and testing linear and non-linear fractional-order forms of activation functions and their variants. The linear activation function includes Purelin. In contrast, the non-linear activation functions are Binary Step, Sigmoid, Tansig, ReLU, ELU, Gaussian Error Linear Unit (GELU), Hexpo, and their variants. Besides, the standard formula has been implemented and used in developing the fractional-order linear activation function. Furthermore, various expansion series, such as Euler and Maclaurin, have been used to design non-linear fractional-order activation functions and their variants. The single- and multi-layer fractional-order neural network models have been developed using the designed fractional-order activation functions. The simulation study uses developed fractional-order neural network models for predicting the Texas wind turbine systems' generated power. The performance of single and multi-layer fractional-order neural network models has been evaluated by changing the activation functions in the hidden layer while keeping the Purelin function constant at the output layer. Experiments on neural network models demonstrate that the designed fractional-order activation functions outperform traditional functions like Sigmoid, Tansig, ReLU, ELU, and their variants, effectively addressing limitations. • Activation functions are derived into fractional functions using fractional calculus. • The fractional neural network models have been made by adopting derived functions. • A Case study has been done on the Texas wind turbine with the models to predict the power. • The models' performance has been evaluated using the fractional functions. [ABSTRACT FROM AUTHOR]