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• A two-stage method is proposed for electricity price forecasting. • The method diversifies the data resources improve the forecasting accuracy. • The method is tested using the real-world data of Texas electricity market. • Causal relationship combined with physical models guarantee better results. • Deep neural networks show a great performance in electricity price forecasting. Over the years, the growing penetration of renewable energy into the electricity market has resulted in a significant change in the electricity market price. This change makes the existing forecasting method prone to error, decreasing the economic benefits. Hence, more precise forecasting methods need to be developed. This paper starts with a survey and benchmark of existing machine learning approaches for forecasting the real-time market (RTM) price. While these methods provide sufficient modeling capability via supervised learning, their accuracy is still limited due to the single data source, e.g., historical price information only. In this paper, a novel two-stage supervised learning approach is proposed by diversifying the data sources such as highly correlated power data. This idea is inspired by the recent load forecasting methods that have shown extremely well performances. Specifically, the proposed two-stage method, namely the rerouted method, learns two types of mapping rules. The first one is the mapping between the historical wind power and the historical price. The second is the forecasting rule for wind generation. Based on the two rules, we forecast the price via the forecasted generation and the first learned mapping between power and price. Additionally, we observed that it is not the more training data the better, leading to our validation steps to quantify the best training intervals for different datasets. We conduct comparisons of numerical results between existing methods and the proposed methods based on datasets from the Electric Reliability Council of Texas (ERCOT). For each machine learning step, we examine different learning methods, such as polynomial regression, support vector regression, neural network, and deep neural network. The results show that the proposed method is significantly better than existing approaches when renewables are involved. [ABSTRACT FROM AUTHOR]

[Display omitted] • The fire gel, Barricade® reduced mortality of entomopathogenic nematodes from UV and desiccation. • First evaluation of Barricade and entomopathogenic nematodes for ticks infesting livestock. • Potential for use of Barricade to enhance nematode activity against questing tick larvae on pasture grasses. Entomopathogenic nematodes (EPNs), Steinernema riobrave and Heterorhabditis floridensis are under evaluation for eradication of the southern cattle fever tick, Rhipicephalus microplus infesting nilgai antelope, in South Texas. Cattle fever ticks are a significant threat to the U.S. livestock industry. Although they have been eradicated in the U.S. they frequently re-invade along the Texas-Mexico border. Remotely operated field sprayers have been developed to directly treat nilgai antelope with EPNs as they transit fence crossings and as they contact wetted foliage and soil from the surrounding area. EPNs are known to be susceptible to mortality from ultraviolet light (UV) and desiccation. A sprayable fire gel, Barricade®, has been reported to protect EPNs from UV and desiccation but has not been tested on animal hides. Barricade® at 1 and 2 percent rates was mixed with the water solution of S. riobrave and H. floridensi s and applied to cowhides (to mimic direct treatment of nilgai) and filter paper and then these substrates were placed out of doors in 0, 30, 60 or 120 min of sunlight. Wax moth larvae, Galleria mellonella , were exposed to the cowhides and filter paper to determine efficacy of the EPNs. Efficacy of S. riobrave with 1 and 2% Barricade® gel applied to cowhides was significantly improved at 30 and 60 min as compared to the control. At 120 min mortality of the wax moth larvae was near zero for both the control and the treatments. Similar results were found with the filter paper test. In contrast, efficacy of H. floridensis with Barricade® applied to cowhides or filter paper was not significantly improved at 30, 60 or 120 min as compared to the water only control. Barricade® has the potential to improve the efficacy of S. riobrave and other EPNs by reducing mortality and desiccation, especially when used in the remotely operated sprayer developed for treatment of cattle fever tick infested nilgai. [ABSTRACT FROM AUTHOR]

In order for a diabetic patient to maintain a healthy life, careful attention of an endocrinologist is required. A diabetic's reliance on the availability and accessibility of an endocrinologist can prove to be precarious when there are very few or none in his/her spatial proximity. Previous studies suggest certain socioeconomic variables (race, sex, and rurality) substantially impact an individual's susceptibility to diabetes. In this paper, we used the most cited socioeconomic variables in the extant literature to designate whether or not a county should be labeled 'at-risk.' 'At-risk' counties were denoted as such based on the relationship between the variable examined and the diabetic prevalence rate for the state of Texas. Additionally, we examined diabetes prevalence among 'at-risk' counties and the location of endocrinologist offices to assess the spatial accessibility for diabetic patients in potentially accessing the appropriate health care for the disease. Analyses revealed that using a combination of population density and median income criteria produced more counties in Texas labeled 'at-risk' than when using a more restrictive combination of several previously-cited socioeconomic variables, or when identifying 'at-risk' counties using race alone (proportion of African-American or Hispanic residents). Moreover, results show that rural counties labeled 'at-risk' are often the least likely to have an endocrinologist office in the county or in surrounding counties. Additionally, many counties with higher than the state prevalence for diabetes do not have endocrinologist offices; rather, endocrinologists are more likely to be located in densely populated counties. We conclude that there is a discrepancy in diabetic patients in counties defined as 'atrisk' having accessibility to appropriate care for their disease. [ABSTRACT FROM AUTHOR]

Post‐disaster business return is key to restoring the local economy. This paper applies a duration model to analyse factors that explain the delay in reopening a business in south Texas, United States, after Hurricane Harvey struck the region in August 2017. Other than property damage, the duration of business closure depended on the type of business and the various characteristics of its owner. Reflecting the vital role that social capital plays in disaster resilience, local chamber of commerce members tended to reopen their businesses sooner than their non‐member counterparts. Yet, there is evidence in support of the vulnerability of female chamber members. In addition to social networks, the finding of spatial interdependence implies that the decision of business owners to resume operations in the wake of a disaster is influenced by the decisions of their neighbours. Spatial interdependence also highlights the importance of providing disaster relief to businesses in a timely manner. [ABSTRACT FROM AUTHOR]

Cancer is the second leading cause of death in the U.S. Utilizing family health history in cancer prevention holds promise in lessening the burden of cancer. Nevertheless, family health history is underutilized in public health and preventive medicine. Community health workers, also known as lay health educators, are ideal candidates to offer basic cancer family history-based education and services to the general public. The authors developed the first cancer family history-based genomics training program in cancer prevention tailored for community health workers. This paper details the development and pilot testing findings of the training. Specifically, a multidisciplinary research team of geneticists, genetic counselors, health educators, community health workers, and community health worker instructors developed a 7-module, 6-hour, bilingual (English and Spanish) cancer family history-based training focusing on cancer family history-based risk assessment, lifestyle recommendations, and genetic evaluation and testing. The curriculum was based on an integrated theoretical framework, the National Comprehensive Cancer Network guidelines, the community health worker core competencies, and the 4MAT instructional model. The Texas Department of State Health Services approved and certified the curriculum with 2 delivery formats: in-person/face-to-face workshops and online training. A total of 34 community health workers completed the pilot training in person (n=17) and online (n=17) in 2018 and 2019. Participating community health workers' knowledge, attitudes, self-efficacy, and intention in delivering basic cancer family history-based genomics education and services significantly increased on the immediate post-test measures compared with their pretest data. Positive ratings and feedback were also reported by the community health workers. Findings from this pilot study suggest that wider training is warranted for educating more community health workers in the U.S. [ABSTRACT FROM AUTHOR]

This paper presents findings from a side-by-side operational comparison of granular road salt (RS) and MeltDown 20 (MD) deicing chemicals for snow and ice control from the perspective of "the maintenance worker in the truck." The field test site, near Canyon, Texas, was divided into sixteen 305 m (1,000 ft) sections that were either untreated controls or received treatment with RS or MD at nominal Texas Department of Transportation (TxDOT) application rates of 85 kg/lane km (300 lb/lane mile) and 42 kg/lane km (150 lb/lane mile), respectively. Three storms met pre-established criteria for snow accumulation, and field test sections were subject to cycles of plowing, deicing treatment, and slushing. Video and still-image data facilitated estimation of visible pavement, and vehicle-based decelerometer tests measured pavement friction. Overall results showed that granular RS outperformed MD in 5/20 data events (25%) and RS outperformed untreated control in 9/20 data events (45%). In contrast, MD never outperformed RS and outperformed control in only 5/20 data events (25%). Further, TxDOT maintenance management data indicate the operational cost to apply MD (corrosion-inhibited) is 3.5× higher than RS (noninhibited), raising questions about cost-effectiveness given the road, climate, and temperature conditions characteristic of the north Texas latitude. [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]

As climate change impacts become increasingly severe, it is critical to have a comprehensive understanding of interactions between climate, energy, and water. Previous energy-water nexus studies have focused primarily on specific dependencies, such as water for thermoelectric cooling, rather than the potential for cascading impacts of supply disruptions at broader scales. This paper explores relative energy-water interdependencies across multiple sectors at the scale of the three primary electricity interconnections within the United States. Our results indicate the need for and potential benefits of integrated policy, planning, and management of energy and water resources based on an interdependent systems perspective. • Interconnection-level Sankeys provide insights into potential vulnerabilities • Electricity generation in the Eastern US is susceptible to water disruptions • Energy intensities of public water supply and agriculture are highest in the West • Electricity and industry sectors in Texas grid have the highest fuel dependence [ABSTRACT FROM AUTHOR]

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

Reports on the acceptance by Association for Gerontology in Higher Education of papers to be presented at the 21st Annual Meeting on February 23 to 26, 1994 in Fort Worth, Texas. Deadline; Theme of the meeting; Contact.

Citizen science (CS) programs often question what motivates their volunteers and how volunteer participation can be sustained. Using a case study of citizen scientist volunteers (CSVs) who monitor water quality in Texas, I apply here a novel approach--the Dispositional-Organizational Interactions Framework (DOIF)--that provides a nuanced understanding of CSVs. The DOIF allows for consideration of how dispositional variables, such as sociodemographic characteristics and motivations for participation, may relate to organizational variables (e.g., program efficacy, results, and recognition); both overarching variables relate to indicators of commitment. The purpose of this study is to examine interactions among different aspects of a CS program and CSVs--observations that can improve CSV satisfaction and possibly retention. In a community geography partnership, volunteers of a statewide CS program were surveyed (n = 327). Results of exploratory factor analyses and a series of nonparametric tests indicate the DOIF offers insights into five major motivational factors; it uncovers between-group differences in how CSVs value organizational variables and indicate a commitment to volunteerism. This study contributes to the broader literature by incorporating the role of the organization in assessments of motivations through the creation of a novel framework and through empirical findings. The paper considers implications of results for CS programs and practice, then concludes with suggestions for future research. [ABSTRACT FROM AUTHOR]

This paper presents a seismic slope stability assessment study of an inherently heterogeneous hydraulic fill dam in Texas. Extensive cone penetration soundings conducted at the dam site were interpreted to estimate different dam material properties. Eight sections distributed along the length of the dam were considered for the slope stability assessment to incorporate the effect of variations in material properties on the hydraulic fill dam. The conventional pseudostatic analysis method was modified to account for the differences in the behavior of the dam materials during static and seismic loading conditions. The current state of practice considers the same critical slip surface for both static and pseudostatic analyses. A modified pseudostatic slope stability analysis was performed to identify other possible critical slip surfaces with lower factors of safety values than the critical slip surface obtained from the static stability analysis. A reliability-based approach was then adopted to incorporate the effect of uncertainty on the estimation of shear-strength parameters of the dam materials, and the expected performance during different seismic events was evaluated. Two hypothetical earthquake events were also considered for the postearthquake deformation and serviceability assessment studies. The approach adopted in this research study facilitates identifying the critical sections of a dam that the conventional analysis method may not consider. Hence, this new approach would be integral toward developing guidelines for evaluating the seismic resilience of earthen dams. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to review common natural disasters in Texas, along with their health effects on affected populations, in order to understand the benefit of integrating disaster research efforts into emergency response systems. The topic of natural disasters is important to address because many types of disasters in Texas are becoming more common or more intense. When disasters strike, all populations within the geographic area of impact feel the effects. Of the consequences following a disaster, the multitude of health effects are one of the most pressing to address. Immediate impacts include physical injuries, such as drownings and burns. Intermediate impacts include communicable diseases and starvation. Long-term impacts include chronic diseases and mental health disorders. To fully investigate these health effects, there needs to be a robust method of integrating disaster epidemiological studies into the immediate disaster emergency response. Disaster emergency response encompasses the actions of government and independent entities to provide immediate relief, such as provision of health services and allocation of resources, to groups and individuals impacted by natural disasters. Integration of disaster epidemiological research into the disaster emergency response could help fill in current gaps in knowledge, such as the long-term health effects of natural disasters on chronic disease and child development. [ABSTRACT FROM AUTHOR]

Environmental Stewardship (ES) is voluntary action on behalf of the environment. ES is typically practiced at environmental nonprofit organizations that offer stewardship programs. Because these programs are managed by individual organizations, relatively little external research exists on their impacts, for example, diffusing norms and behaviors of ES more broadly across society. Responding to that research gap, this paper studies change in the environmental outlooks and behaviors of participants at two partner nonprofits in Texas using surveys (n=407) and interviews (n=5). Three categories of changes in environmental behavior are assessed: Natural Areas, Environmental Activism, and Water Awareness. Findings demonstrate that participation was linked to pro-environmental changes in all categories for the survey respondents. Follow-up interviews allowed the authors to capture additional aspects of ES not addressed in the survey. Ultimately, ES can lead to greater uptake in selected pro-environment actions, higher awareness of environmental issues, and greater appreciation for natural amenities. [ABSTRACT FROM AUTHOR]

Safety studies have indicated that low skid resistance increases crash risk. Because of this reason, transportation agencies have considered managing pavement skid resistance as one of the important means to reduce crashes. This management includes understanding the skid resistance deterioration process. The objective of this paper is to model the deterioration of pavement skid resistance at the network level using a Markov Chain process. The proposed methodology is composed of three steps: (a) pre-processing the pavement skid resistance data, (b) developing the Markov Chain deterioration model, and (c) validating the developed deterioration model. To demonstrate the applicability of the proposed methodology, a numerical case study was conducted using a sample of highway sections that comprise 564 lane-miles in Texas. Findings from the numerical analysis show that the Markov Chain process can be effectively used to model the deterioration of pavement skid resistance at the network level. The developed methodology process can be used by state and local agencies to predict deterioration rates of pavement skid resistance and estimate skid resistance budget needs. [ABSTRACT FROM AUTHOR]

The paper uses data from 68 United Way of Texas chapters with web presence to create three indicators for web-based accountability — (1) disclosure of performance information (2) responsiveness to stakeholders and (3) fiscal transparency— and to estimate their determinants using OLS regression. Among others, the study finds that web-based accountability determined by online disclosure of performance information is influenced by board size, whereas fiscal transparency is affected by paid staff. The study contributes to nonprofit accountability literature by showing the connectedness of web-based accountability indicators and the need for enhanced fiscal transparency in the nonprofit sector. [ABSTRACT FROM AUTHOR]

The Curie point-depth, frequently related to the depth to the bottom of the magnetic source, is widely employed as an estimator of temperature at depth when borehole temperature data are not available. The Curie point-depth is calculated using the spectral analysis of the magnetic data derived from aeromagnetic or satellite surveys. In this paper, MATLAB user-friendly GUI are constructed to calculate the Curie Point Depth using the inversion of aeromagnetic data assuming 2D fractal magnetization and modeling the temperature at depth assuming a 1D steady-state conductive heat transfer model. The program, tested in synthetic and aeromagnetic data, is running under MATLAB 2020a or standalone application with these input parameters: Aeromagnetic data, fractal parameter, Curie temperature, surface temperature, thermal conductivity, surface radiogenic heat production and scaling length of surface radiogenic heat production. The radially averaged amplitude spectrum, scaled spectrum, modeled spectrum, Curie point-depth, and temperature profile at depth are the output parameters of the program. Finally, the program is tested with Texas aeromagnetic data, and the results of the Curie point-depth were compared with borehole data. [ABSTRACT FROM AUTHOR]

As the world's reinforced concrete (RC) civil infrastructure continues to age and exhibit visual signs of distress (e.g., cracking), the challenge of how to process this visual information is becoming increasingly important. While research is ongoing in this field, limited work has been done involving structures that are truly representative of real‐world, aged civil infrastructure requiring assessment. Thus, this paper presents the results of an experimental program and subsequent numerical investigation into the performance of a diagonally cracked, RC bent cap that was removed from a 60‐year‐old bridge in Texas. Extensive work was done to document the cracking behavior and characterize the mechanical properties of the bent cap prior to ultimate load testing. The numerical investigation included both "conventional" methods and nonlinear finite element analysis (with and without consideration of existing damage). Ultimately, the results of the experimental and numerical investigations suggest that, while the bent cap was exhibiting large‐width shear cracks in service, the damage was not indicative of an impending shear failure. [ABSTRACT FROM AUTHOR]

This paper documents the first occurrence in Texas of a wild population of Marsilea mutica Mett., (Marsileaceae), an exotic species of waterclover fern. The colony’s life history and potential for invasive behavior are discussed. [ABSTRACT FROM AUTHOR]

Mobile-source emissions are pivotal in quantifying the negative externalities of surface transportation, such as environmental pollution and climate-change, and in evaluating low-carbon traffic strategies. In such assessments, it is important to avoid prospective policy shortcomings. Hence, a wide range of sensitivities of mobile-source emissions must be understood, particularly from a traffic modeling standpoint. This paper takes a step in that direction and explores the effects of certain supply-side network attributes on emissions. Three key elements are investigated: level-of-detail of traffic activity, link speeds in the network, and link lengths. Both aggregated (hourly) and fine-grained (per-second) traffic activities are modeled using a simulation-based dynamic traffic assignment tool. Emissions are modeled using US Environmental Protection Agency's Motor Vehicle Emissions Simulator (MOVES). System-wide estimates of five criteria pollutants (CO, NO2, PM10, PM2.5, and SO2) and greenhouse-gases (CO2) are developed for a weekday morning peak-hour modeling period. Numerical experiments on a rapidly growing county in Central Texas, US, indicate that emission estimates are sensitive to all the aforementioned supply-side variables. Most notably, median network-wide estimates are found to increase in magnitude with aggregation of traffic activity and speeds. Effects of link lengths appear to be more prominent in high-speed traffic corridors, such as restricted-access highways, than low-speed unrestricted-access arterials. The latter, however, witness more traffic dynamics and subsequently contribute more to deviation in emission estimates across levels-of-detail. The findings highlight the need to be mindful of such physical sensitivities of emissions while enacting policy decisions, which frequently rely on network-based regional emissions inventories. • Microsimulation emissions models are computationally prohibitive for large networks. • We improve geographical coverage and applicability of mobile-source emissions models. • Hourly and per-second traffic activity are simulated using dynamic traffic assignment. • Median emissions estimates increase with aggregation of network-wide traffic activity data. • Criteria pollutants are sensitive to physical supply-side features and network composition. [ABSTRACT FROM AUTHOR]

Grassland environments face a number of threats including land use change, changing climate and encroachment of woody plants. In the Southern Plains of the United States, woody plant encroachment threatens traditional agricultural grazing economies in addition to grassland dependent wildlife species. Numerous studies have examined the physical drivers of conversion from grassland to woodland but social drivers may be equally important to understanding the causes of and prescriptions for environmental degradation. In this paper, we report the results of a survey of landowners in the Southern Plains of Texas and Oklahoma in which we asked participants to estimate the current amount of woody plant cover on their land, their preferred amount of woody plant cover and about their perspectives regarding the use of prescribed fire for managing woody plants. Prescribed fire is ecologically and economically one of the most effective tools for maintaining grasslands but many landowners do not use this tool due to lack of knowledge, lack of resources and concerns over safety and legal liability. We found that while most of our respondents did express a desire for less woody plant cover on their land, woody plant preference did not affect landowner's use of prescribed fire. However, belonging to a prescribed burn association and owning larger properties were correlated with increased use of prescribed fire. Woody plant cover preference was significantly influenced by landownership motivations, with hunters and other recreational motivated landowners preferring more trees and ranchers preferring fewer. This is important because throughout most of our study area, there has been a steady shift from agricultural production to amenity or recreational landownership, a trend that may undermine efforts to restore or maintain open grasslands. Future outreach efforts to promote prescribed fire to maintain grasslands should more actively support prescribed burn associations, which is an effective vehicle for increasing prescribed fire use by private landowners. [ABSTRACT FROM AUTHOR]

This paper proposes a data-driven algorithm for locating the source of forced oscillations and suggests a physical interpretation for the method. By leveraging the sparsity of forced oscillations along with the low-rank nature of synchrophasor data, the problem of source localization under resonance conditions is cast as computing the sparse and low-rank components using Robust Principal Component Analysis (RPCA), which can be efficiently solved by the exact Augmented Lagrange Multiplier method. Based on this problem formulation, an efficient and practically implementable algorithm is proposed to pinpoint the forced oscillation source during real-time operation. Furthermore, theoretical insights are provided for the efficacy of the proposed approach, by use of physical model-based analysis, specifically by highlighting the low-rank nature of the resonance component matrix. Without the availability of system topology information, the proposed method can achieve high localization accuracy in synthetic cases based on benchmark systems and real-world forced oscillations in the power grid of Texas. [ABSTRACT FROM AUTHOR]

There is a strand of the economics literature that considers the regionalized economic effects of natural resource endowments. The so-called Natural Resource Curse suggests that natural resource endowments are associated with lower longterm growth rates in the areas in which the resources are located. Lower growth arises because these areas tend to specialize in the development and exploitation of the natural resources at the expense of other dynamic economic activities that offer higher long-term growth potential. Empirical evidence has, however, not reached consistent conclusions. In this paper, we take advantage of the rapid growth in oil and gas development and production in Texas over the course of a decade to consider the localized effects on inter-industry county-level employment at the NAICS-2, county-level mean and median income, and key public finance measures at both the county and school district levels. Considering the effects within a single, large and economically diverse state enables us to control for important state-level variables that influence local public finances. We find little evidence of short term effects necessary to generate the circumstance of a resource curse over the longer term. [ABSTRACT FROM AUTHOR]

Detailed morphological documentation is provided for established Proschkinia taxa, including the generitype, P. bulnheimii, and P. complanata, P. complanatula, P. complanatoides and P. hyalosirella, and six new species. All established taxa are characterized from original material from historical collections. The new species described in this paper (P. luticola, P. staurospeciosa, P. impar, P. modesta, P. fistulispectabilis, and P. rosowskii) were isolated from the Western Pacific (Yellow Sea coast of Korea) and the Atlantic (Scottish and Texas coasts). Thorough documentation of the frustule, valve and protoplast architecture revealed the combination of characters diagnostic of the genus Proschkinia: a single‐lobed chloroplast; a broad girdle composed of U‐shaped, perforated bands; the position of the conopeate raphe‐sternum relative to the external and internal valve surface; and the presence of an occluded process through the valve, termed the "fistula". Seven strains of Proschkinia were grown in culture and five of these were sequenced for nuclear ribosomal SSU and plastid‐encoded rbcL. Phylogenetic analysis recovered a clade of Proschkinia with Fistulifera, another fistula‐bearing diatom genus, and together these were sister to a clade formed of the Stauroneidaceae; in turn, all of these were sister to a clade composed of Parlibellus and two monoraphid genera Astartiella and Schizostauron. Despite morphological similarities between Proschkinia and the Naviculaceae, these two taxa are distant in our analysis. We document the variation in the morphology of Proschkinia, including significant variability in the fistula, suggesting that fistula ultrastructure might be one of the key features for species identification within the genus. [ABSTRACT FROM AUTHOR]

We examined teachers' pedagogical reasoning for and the technological knowledge underlying their most‐valued technology‐supported activities for teaching and learning. Data from 140 preservice and 100 inservice teachers included open‐ended, narrative responses to survey questions. Qualitative research methods guided analysis of the data that identified (a) the technology‐supported activities and (b) the technical tools, target users, types of uses, rationales for use, and the TPACK underlying each activity. Preservice teachers described mostly teacher‐focused and fewer student‐focused techno‐activities, and their reasoning for use focused on the technology's presentational and engagement effects. A majority of inservice teachers' techno‐activities were student‐focused, and their reasoning highlighted the technology's support for knowledge acquisition of higher‐order cognitive skills and collaborative learning. The knowledge underlying all teachers' techno‐activities was predominantly technological pedagogical knowledge (TPK), but inservice teachers also evidenced technological content knowledge (TCK). These results may reveal differences in the teachers' respective learning experiences in teacher education and professional development or reflect a professional maturation process in that it takes teachers time in the field as professionals to broaden their techno‐activity repertoires to prioritize student‐focus. Sharing the reasoning patterns in this study with teachers may assist them in developing deeper justifications for their technological work in the classroom. Lay Description: What is already known about this topic: The instructional use of technology in PK‐12 education is predominantly teacher‐focused and transmissive in nature.Teachers' perceived technological pedagogical content knowledge may not aptly reflect their behavioural intentions or smoothly translate into enacted, aligned actions in the classroom.Little is known about teachers' pedagogical reasoning underlying their choices of instructional technology use and its relationship to technological pedagogical content knowledge. What this paper adds: Pre‐service teachers described mostly teacher‐focused techno‐activities, and in‐service teachers described more student‐focused techno‐activities.Pre‐service and in‐service teachers used different pedagogical reasoning for the same categories of technology‐supported activities; thus they valued different technological features.Pre‐service teachers applied less content‐specific knowledge in their pedagogical reasoning as compared with in‐service teachers, but both groups relied predominantly on technological pedagogical knowledge. Implications for practice and/or policy: Pre‐service teachers' prominent use of and value for presentational technologies may indicate that modelling student‐ and/or content‐focused techno‐activities is needed within teacher preparation.Cultivating and sharing teachers' pedagogical reasoning for technology‐integrated lessons may increase teachers' awareness and support deeper justifications within their technological decision‐making. [ABSTRACT FROM AUTHOR]

This study focuses on coastal counties in Texas, United States, affected by Hurricane Harvey in 2017 to gauge the influence of individual and contextual characteristics on people's ability to return to normalcy in the short term. Data from a survey conducted by the Kaiser Family Foundation and the Episcopal Health Foundation between October and November 2017 were utilised in the analysis. The paper observes, based on the results of an ordered logistic regression, and contrary to previous work, that age, gender, levels of poverty, and social capital are not significant predictors of a return to normalcy. However, indicators such as whether a person evacuated, if he/she identified as Hispanic/Latino, the extent of damage sustained to one's home, and if one's automobile was damaged or destroyed are shown to affect recovery. A discussion of the potential reasons for these findings is provided as a means of informing future research on disaster recovery. [ABSTRACT FROM AUTHOR]

In a 1989 position paper, the National Strength and Conditioning Association (NSCA) recommended that male and female athletes be trained in a similar manner with regard to modalities and program design. To determine whether that recommendation is being followed, this study examined training practices of coaches of male and female athletes at the interscholastic level. Electronic surveys regarding strength training practices were distributed to head coaches of boys' football, basketball, soccer, and baseball and girls' volleyball, basketball, soccer, and softball in the states of Texas and Wisconsin. Overall, 85% of coaches (n = 85) reported that they require their athletes to strength train. There was no difference in whether strength training was required based on athlete sex (X²=0.16, df51, p50.69) or the sex of the coach (X²= 0.63, df=1, p=0.43). The majority (67%) of teams strength trained once weekly during the season and 21% trained twice weekly. In the off-season, only 12% of teams trained once weekly, whereas 44% of teams strength trained 2 times per week and 29% 3 times weekly. The most common types of lift performed for both sexes were "bodyweight exercises," followed by "dumbbell presses," bench press, back squats, and front squats. Both female and male athletes trained most commonly at 4-8 repetition and 9-12 repetition ranges. In contrast to previous studies and in accordance with the NSCA recommendation, it seems that the high school coaches surveyed in this work largely train male and female athletes in a similar fashion with regard to training frequency, intensity, and modalities. [ABSTRACT FROM AUTHOR]

This paper presents a Bayesian network model to assess the vulnerability of the flood control infrastructure and to simulate failure cascade based on the topological structure of flood control networks along with hydrological information gathered from sensors. Two measures are proposed to characterize the flood control network vulnerability and failure cascade: (a) node failure probability (NFP), which determines the failure likelihood of each network component under each scenario of rainfall event, and (b) failure cascade susceptibility, which captures the susceptibility of a network component to failure due to failure of other links. The proposed model was tested in both single watershed and multiple watershed scenarios in Harris County, Texas using historical data from three different flooding events, including Hurricane Harvey in 2017. The proposed model was able to identify the most vulnerable flood control network segments prone to flooding in the face of extreme rainfall. The framework and results furnish a new tool and insights to help decision‐makers to prioritize infrastructure enhancement investments and actions. The proposed Bayesian network modeling framework also enables simulation of failure cascades in flood control infrastructures, and thus could be used for scenario planning as well as near‐real‐time inundation forecasting to inform emergency response planning and operation, and hence improve the flood resilience of urban areas. [ABSTRACT FROM AUTHOR]

Given the role opioid overprescribing has played in the current overdose crisis, reducing the supply of prescription opioids available for misuse has gained widespread support. Prescription monitoring programs (PMPs) have been identified as a tool for achieving this goal, but little is known about how to promote PMP use to prescribers. This paper describes the process of developing a health communication campaign to support the adoption of the Texas PMP. After formative research, message development and concept testing, a range of campaign concepts and messages were tested and final recommendations determined. The messages and lessons learned have utility beyond Texas. [ABSTRACT FROM AUTHOR]

Food preparation interventions are an increasingly popular target for hands-on nutrition education for adults, children, and families, but assessment tools are lacking. Objective data on home cooking practices, and how they are interpreted through different data collection methods, are needed. The goal of this study was to explore the utility of the Healthy Cooking Index in coding multiple types of home food preparation data and elucidating healthy cooking behavior patterns. Parent–child dyads were recruited between October 2017 and June 2018 in Houston and Austin, Texas for this observational study. Food preparation events were observed and video recorded. Participants also wore a body camera (eButton) and completed a questionnaire during the same event. Parents with a school-aged child were recruited as dyads (n=40). Data collection procedures took place in participant homes during evening meal preparation events. Food preparation data were collected from parents through direct observation during preparation as well as eButton and paper questionnaires completed immediately after the event. All data sets were analyzed using the Healthy Cooking Index coding system and compared for concordance. A paired sample t test was used to examine significant differences between the scores. Cronbach's α and principal components analysis were conducted on the observed Healthy Cooking Index items to examine patterns of cooking practices. Two main components of cooking practices emerged from the principal components analysis: one focused on meat products and another on health and taste enhancing practices. The eButton was more accurate in collecting Healthy Cooking Index practices than the self-report questionnaire. Significant differences were found between participant reported and observed summative Healthy Cooking Index scores (P <0.001), with no significant differences between scores computed from eButton images and observations (P =0.187). This is the first study to examine nutrition optimizing home cooking practices by observational, wearable camera and self-report data collection methods. By strengthening cooking behavior assessment tools, future research will be able to elucidate the transmission of cooking education through interventions and the relationships between cooking practices, disease prevention, and health. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease 2019 (COVID-19) has caused a rapid and massive transition to online education. We describe the response of our Office of Faculty Development at Texas Tech University Health Sciences Center El Paso (TTUHSC EP) to this unprecedented challenge during and after this post-pandemic crisis. The initiatives for emergency transition to eLearning and faculty development described in this paper may serve as a model for other academic health centers, schools, colleges and universities. [ABSTRACT FROM AUTHOR]

The natural complexity, heterogeneity, and extent of transboundary aquifers around the world, have led to controversy over which method or criteria should be used to identify and delineate their boundaries. Currently, there is no standard methodology that aquifer‐sharing countries can use to delineate the area of a transboundary aquifer. In the case of Mexico and Texas, Mexico uses administrative boundaries, whereas Texas uses geological boundaries. This paper proposes a method for delineation and prioritization of aquifers (or aquifer areas) called effective transboundary aquifer areas (ETAAs), which uses a combination of physical criteria (geological boundaries, topography, and hydrography) and the location and density of active water wells in the borderland between Mexico and Texas. This method identifies the area of priority (productivity area) in the aquifer using pumping patterns or hot spots regardless of the aquifer's surficial geological limits, therefore offering a more effective, local and practical management option at the transboundary level. Different geological features or pumping patterns will have different sizes and locations of ETAAs within the same aquifer. In West Texas, which is dominated by bolsons, the method produces limited options for ETAAs, whereas in South Texas in the easternmost border the identified ETAAs are more significant. Research Impact Statement: The effective transboundary aquifer areas approach is an alternative way to identify the priority area of an aquifer using pumping hot spots for a simpler and local‐based transboundary groundwater management scenario. [ABSTRACT FROM AUTHOR]

This paper discusses the historical archaeology of migration in the American Southwest. I raise three points for consideration. First, the archaeology of migration in the Southwest following Spanish colonialism has been relatively absent, but is a rich area of inquiry for historical archaeologists. Second, migration has shaped the regional consciousness, landscape, and myth-making of the historic Southwest in significant ways that merit archaeological attention. Finally, drawing on the example of Alsatian migration to Texas, I propose that an attention to scale – how migrations occur alongside and within other movements – can add nuance to historical narratives of the West by highlighting the great diversity that characterizes the region throughout the historic period. [ABSTRACT FROM AUTHOR]

Failure behaviors can strongly influence deformation-related changes in volume, which are critical in the formation of fault and fracture porosity and conduit development in low-permeability rocks. This paper explores the failure modes and deformation behavior of faults within the mechanically layered Eagle Ford Formation, an ultra-low permeability self-sourced oil and gas reservoir and aquitard exposed in natural outcrop in southwest Texas, USA. Particular emphasis is placed on analysis of the relationship between slip versus opening along fault segments and the associated variation in dilation tendency versus slip tendency. Results show that the failure mode and deformation behavior (dilation versus slip) relate in predictable ways to the mechanical stratigraphy, stress field, and specifically the dilation tendency and slip tendency. We conclude that dilation tendency versus slip tendency patterns on faults and other fractures can be analyzed using detailed orientation or structural geometry data and stress information and employed predictively to interpret deformation modes and infer volume change and fluid conduit versus barrier behavior of structures. [ABSTRACT FROM AUTHOR]

We use the magnitude and centroid period of Rayleigh wave along with the amplitude of fluctuations of water level in a well to calculate effective porosity of a karst aquifer at the site scale. The radial and vertical displacements of Rayleigh wave are first related to the confining pressure of rock, which is then related to fluid pressure via the Gassmann equation. Three seismograms recorded at station 633A of the USARRAY and the induced responses of Well J-17 in the Edwards Aquifer (Texas) allow the calculation of an effective porosity between 17.0 and 24.4 percent, the average of which is close to the total porosity of core samples determined by geophysical well logs. This paper provides an innovative method to measure effective porosity in aquifers. Because of the long wavelengths of Rayleigh wave, the interdisciplinary approach is advantageous in that the resulting effective porosity is at the site scale which includes large conduits or voids. [ABSTRACT FROM AUTHOR]

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

This paper suggests evolving linear models as a powerful alternative for online forecasting of synchronous time series. First, using a priori knowledge of an expert, all known possible features are clustered in some categories so that each category includes homogeneous features. Then, a novel evolving correlation-based forward subset selection technique is used to determine relevant features from each category. Next, based on the selected features, an estimation of the output of the system is modeled through an evolving adaptive linear regression model. In evolving systems, selected features and their associated weights could vary over time based on new incoming data samples which contain new information. Finally, a soft combination of output estimations of all categories, in a new sense of Takagi–Sugeno fuzzy system, gives the prediction of the output of the system at each sampling time. The approach offers a certain new view at the enhancement of evolving forecasting models. The proposed approach embodies recursive learning and one-step-ahead incremental algorithms that progressively modify the model to ensure continuous learning, and self-organization of the model structure and its parameters. Two real-world problems, forecasting electricity load of the Electric Reliability Council of Texas region and stock price forecasting of technology sector of Standard & Poor’s 500 index, are provided to validate the developed method. Pros and cons of the proposed approach are comprehensively discussed and shown through simulation results and comparisons with other state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Transition-age youth (TAY, ages 14–26) diagnosed with serious mental health conditions are at high risk for vocational struggles. This paper examines the implementation and process evaluation of Individual Placement and Support (IPS) and Supported Employment enhanced to better meet developmental needs of TAY. Enhancements include the integration of a TAY development focus, engagement best-practices, Supported Education and Peer Support. Community mental health providers participated in a process evaluation to explore the feasibility of a larger scale implementation. Common organizational barriers were encountered across provider sites including: leadership support, agency structures and funding mechanisms; compounded by the complexity of bridging child and adult systems. Findings have implications for both child and adult community mental health providers as they adapt and integrate programming for TAY. [ABSTRACT FROM AUTHOR]

Gender, although gaining attention, remains under‐researched in disaster risk reduction protocols and response and recovery efforts. This study examines women's experiences of two disasters in small towns in the United States, utilising qualitative interviews with residents of Granbury and West, Texas, during the first year of disaster recovery. Granbury was struck by an EF‐4 tornado on 15 May 2013, whereas an explosion occurred at a local fertiliser facility in West on 17 April 2013. The paper explores how women's experiences of inter‐gender power dynamics in decision‐making, the prioritisation of childcare, and women's participation in the community affect their post‐disaster recovery. Previous research highlights different forms of human response and recovery vis‐à‐vis 'natural' and technological disasters, with less attention paid to gender differences. The results point to the persistent, and similar, effect of gender stratification on women's experiences across different types of disasters in the US and the continued importance of gender‐sensitive disaster policies and programmes. [ABSTRACT FROM AUTHOR]

In a post-graduate class, 33 American elementary and secondary teachers from five different school districts in southwest Texas provided their personal reflections on how their administrators responded to the coronavirus pandemic from March to May, 2020. Ten of the teachers, supervised by their professor, analysed these responses. The paper describes the administrative actions in each category that teachers thought were effective, as well as those that were not, across three broad categories: communication, accountability, and interpersonal relationships. Four recommendations for improving administrators' effectiveness in unexpected crises are provided. [ABSTRACT FROM AUTHOR]

The article focuses on the impact of political science courses on presidential and gubernatorial elections in Texas. Topics discussed include examines the impact of political science courses on the political information learned by students in order to deepen current understanding of the link between education and elections; and paper particularly analyzes the impact of the several courses on students' knowledge of the 2020 U.S. Presidential Election and 2018 gubernatorial elections in Texas.

This paper develops models for hurricane exposure, fragility curve-based damage to electrical transmission grid components and power generating stations using Monte-Carlo simulation, and restoration cost to predict resiliency factors including power generation capacity lost and the restoration cost for electrical transmission grid and power generation system damages. Synthetic grid data are used to model the Energy Reliability Council of Texas (ERCOT) electrical grid. A case study is developed based on Hurricane Harvey. This work is extended to evaluate the changes to resiliency as the percentage of renewable sources is increased from 2017 levels to levels corresponding to the NREL Futures Study 2050 Texas scenarios for 50% and 80% renewable energy. [ABSTRACT FROM AUTHOR]

Using adherence to diabetes management guidelines as a case study, this paper applied a novel geospatial hot-spot and cold-spot methodology to identify priority counties to target interventions. Data for this study were obtained from the Dartmouth Atlas of Healthcare, the United States Census Bureau's American Community Survey and the University of Wisconsin County Health Rankings. A geospatial approach was used to identify four tiers of priority counties for diabetes preventive and management services: diabetes management cold-spots, clusters of counties with low rates of adherence to diabetes preventive and management services (Tier D); Medicare spending hot-spots, clusters of counties with high rates of spending and were diabetes management cold-spots (Tier C); preventable hospitalisation hot-spots, clusters of counties with high rates of spending and are diabetes management cold-spots (Tier B); and counties that were located in a diabetes management cold-spot cluster, preventable hospitalisation hot-spot cluster and Medicare spending hot-spot cluster (Tier A). The four tiers of priority counties were geographically concentrated in Texas and Oklahoma, the Southeast and central Appalachia. Of these tiers, there were 62 Tier A counties. Rates of preventable hospitalisations and Medicare spending were higher in Tier A counties compared with national averages. These same counties had much lower rates of adherence to diabetes preventive and management services. The novel geospatial mapping approach used in this study may allow practitioners and policy makers to target interventions in areas that have the highest need. Further refinement of this approach is necessary before making policy recommendations. [ABSTRACT FROM AUTHOR]

Failure behaviour can strongly influence deformation-related changes in volume, which is critical in the formation of fault and fracture porosity and conduit development in low permeability rocks. This paper explores the failure modes and deformation behaviour of faults within the mechanically layered Eagle Ford Formation, an ultra-low permeability self-sourced oil and gas reservoir and aquitard exposed in natural outcrop in southwest Texas, USA. Particular emphasis is placed on analysis of the relationship between slip versus opening along fault segments, and the associated variation in dilation tendency versus slip tendency. Results show that the failure mode and deformation behaviour (dilation versus slip) relate in predictable ways to the mechanical stratigraphy, stress field, and specifically the dilation tendency and slip tendency. We conclude that dilation tendency versus slip tendency patterns on faults and other fractures can be analysed using detailed orientation or structural geometry data and stress information, and employed predictively to interpret deformation modes and infer volume change and fluid conduit versus barrier behaviour of structures. [ABSTRACT FROM AUTHOR]

The goal of our ongoing research is to identify strengths and weaknesses of high school level science fair and improvements that can help science educators make science fair a more effective, inclusive and equitable learning experience. In this paper, we confirm and extend our previous findings in several important ways. We added new questions to our anonymous and voluntary surveys to learn the extent to which students had an interest in science or engineering careers and if science fair participation increased their interest in science or engineering. And we surveyed a national rather than regional high school student group by incorporating our survey into the Scienteer online portal now used by Texas and some other states for science fair registration, parental consent, and project management. We learned that about ~60% of the more than 300 students in the national cohorts completing surveys in 2017 and 2018 said that they were interested in a career in science or engineering, and ~60% said that participating in science fair increased their interest in science or engineering. About two-thirds of the students were required to participate in science fair, and that requirement reduced the frequency of students who said that science fair increased their interest. In the worst case, ~10% of the students who said that they were not interested in a career in science or engineering and who were required to participate in science fair engaged in research misconduct (i.e., plagiarism and making up their results). Students' positive comments about competition in science fair focused on the competition incentive, whereas their positive comments about science fair that was non-competitive focused on learning about the scientific process and learning in general. We discuss the findings in the context of National Science Teaching Association guidance about voluntary science fair participation and begin to identify features of science fair practice consistent with increased student interest in the sciences or engineering. [ABSTRACT FROM AUTHOR]

Power grids have recently become more susceptible to sub-synchronous control interactions (SSCI) due to the increasing penetration of renewable resources and series-compensated lines. SSCI is a purely electrical and fast-growing phenomenon. Therefore, without an expeditious detection and mitigation solution, it can cause serious damage to renewable and transmission facilities, consequently leading to cascading outages. This paper proposes an effective algorithm to detect SSCI within 45 ms and reliably send a trip signal within 95 ms. First, a comprehensive SSCI analysis is suggested to improve the preprocessing of the measured signal. Then, the proposed algorithm utilizes mode identification approaches in conjunction with a moving fast fourier transform (FFT) to capture and process the frequency and magnitude of oscillations to issue a reliable trip command in the case of an SSCI event. To evaluate the algorithm, a portion of the Electric Reliability Council of Texas (ERCOT) grid with relatively high penetration of renewable generation resources is utilized. The proposed detection algorithm is implemented on a real-time target device and is tested with an SSCI signal from the ERCOT grid under real-time operating conditions. The results indicate the efficiency and accuracy of the method with successful detection within the acceptable time frame. [ABSTRACT FROM AUTHOR]

In 2017, three sub-synchronous resonance (SSR) events were reported in the transmission system of Electric Reliability Council of Texas (ERCOT). These three events with different consequences are due to the same cause, i.e., Type-3 wind farms radially connected to a series compensated transmission line. The objectives of this paper are: 1) to build a testbed to replicate these real-world events and investigate what causes the different consequences; 2) to find out the impact of wind penetration level and wind speed on SSR; and 3) to investigate how to mitigate SSR. The replication testbed is built in MATLAB/Simpowersystems with each wind farm represented by a single aggregated wind turbine with full dynamics. The challenge of replication is the limited information about those three events, the ERCOT system, and the wind farms. Nevertheless, relying on simplification and assumptions, we are able to replicate the three events. Our contributions include the configured testbed for Type-3 wind farm SSR studies, diagnosis of impacting factors on SSR, and the confirmation of an SSR mitigation strategy through grid-side converter ac voltage command signal modulation. [ABSTRACT FROM AUTHOR]

Although hydraulic fracturing has been massively studied and applied as a key technique to enhance the gas production from tight formations, some problems and uncertainties exist to accurately predict and analyze the fracture behavior in complex reservoirs, especially in the naturally fractured reservoirs like shale reservoirs. This paper presents a full 3D numerical model (FLAC3D) to study hydraulic fracturing behavior under the impact of preexisting orthogonal natural fractures. In this numerical model, the hydraulic fracture propagation direction is assumed perpendicular to the minimum principal stress and activated only by tensile failure, whereas the preexisting natural fractures can be activated by tensile or shear failure or a combination of them, and only tensile failure can open the natural fracture as well. The newly developed model was used to study the impact of preexisting orthogonal natural fractures on hydraulic fracturing behavior, based on a multistage hydraulic fracturing operation in a naturally fractured reservoir from the Barnett Shale formation, northwest of Texas in USA. In this multistage operation, two more representative stages, i.e., stage 1 with a relatively large horizontal stress anisotropy of 3.3 MPa and stage 4 with a comparatively small one of 1.3 MPa, were selected to conduct the simulation. Based on the numerical results, one can observe that the interaction between hydraulic and natural fracture is driven mainly by induced stress around fracture tip. Besides, the horizontal stress anisotropy plays a key role in opening the natural fracture. Thus, no significant opened fracture is activated on natural fracture in stage 1, while in stage 4 an opened fracture invades to about 90 m into the first natural fracture. Conversely, the hydraulic fracture length in stage 1 is much longer than in stage 4, as some fluid volume is stored in the opened natural fracture in stage 4. In this work, the shear failure on natural fractures is treated as the main factor for inducing the seismic events. And the simulated seismic events, i.e., shear failure on natural fractures, are very comparable with the measured seismic events. [ABSTRACT FROM AUTHOR]

Oscillations have been observed in wind farms with weak grid interconnections. While Texas observes 4 Hz low-frequency oscillations, the west region in China observes subsynchronous oscillations at 30 Hz. Furthermore, this oscillation mode caused torsional interactions with a remote synchronous generator and led to shutdown of the power plant. Inspired by those real-world events, this paper aims to present an analytical model of type-4 wind in weak grids that can demonstrate both low-frequency and subsynchronous frequency oscillations. Critical factors, e.g., the parameters of the phase-locked loop (PLL), are examined using small-signal analysis. The analysis results are validated using a testbed built in MATLAB/SimPowerSystems. Except power electronic switching sequences, the testbed has controls (e.g., wind turbine pitch control, maximum power point control, converter controls), machine dynamics and power system dynamics modeled. This testbed includes a 100 MW Type-4 wind farm, a 600 MW synchronous generator, a long transmission line and a grid. The testbed successfully demonstrates two types of dominant oscillations under different PLLs. In addition, the testbed demonstrates torsional interactions due to the proximity of the subsynchronous mode and one of the torsional modes. [ABSTRACT FROM AUTHOR]