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Impact of Organic Management Practices on Soil Greenhouse Gas Emissions from Cotton-Winter Cover Crop Systems in East-Central Texas
No full textConventional cotton production practices demand extensive management involving high pesticides, fertilizers, and tillage inputs, contributing significantly to environmental impacts. To address these concerns, we explored the potential of organic cotton systems employing diverse cover crops, manure, and biochar to mitigate soil greenhouse gas (GHG) emissions while preserving soil carbon and nitrogen. Our field experiment, conducted in the humid subtropical climate of East-Central Texas, assessed various cover crops such as oats (Avena sativa), Austrian winter pea (Pisum sativum), purple top turnip (Brassica rapa subsp. rapa), and mixed species cover crops compared against a control (no cover crop) over three consecutive years. We monitored soil GHG emissions, moisture, and temperature dynamics throughout the cover crop and cotton seasons.
Simultaneously, we conducted multiple laboratory incubations to assess the carbon and nitrogen mineralization of these cover crops in combination with poultry litter manure, examining associated GHG emissions. Our laboratory simulations also considered the impact of tillage practices on residue mineralization. Additionally, we investigated the potential of cotton residue biochar to mitigate GHG emissions during cover crop and manure decomposition.
Our findings revealed that cover crops with a lower C:N ratio, especially legume and mixed species, exhibited higher GHG emissions. However, incorporating biochar alongside cover crops demonstrated significant emission reduction. Furthermore, we observed that cover crops led to reduced soil moisture during their growth phase but contributed to increased water retention during cotton seasons
Consumer Food Waste While Dining Out: An Examination of Theory of Planned Behavior, Habits, Empathy, and Mindfulness
No full textThis dissertation explores behavioral intentions behind consumer food waste in the dining-out context, leveraging the Theory of Planned Behavior (TPB). It incorporates habits and empathy as preliminary factors influencing consumers��� intentions. Additionally, it examines the moderating role of mindfulness on food waste tolerance, thereby extending the traditional model. The sample consisted of 633 participants who have dined outside of their home at least once in the past 6 months. By employing Structural Equation Modeling (SEM) and path regression analysis, the study examines four distinct models, highlighting the interplay between subjective norms, attitudes, perceived behavioral control, and external factors such as empathy and mindfulness on food waste intentions.
Significant findings emerged from the models, indicating that empathy significantly impacts food waste intentions through attitudes, perceived behavioral control, and habits, while mindfulness moderates the empathy-intentions relationship, particularly influencing how empathy affects subjective norms and attitudes. These findings aim to offer deeper insights into the psychological underpinnings of food waste, providing a nuanced understanding of how individual differences and cognitive processes contribute to diners' propensity for food waste.
Implications of this research stretch beyond theoretical contributions, offering actionable insights for the hospitality industry and other sectors to enhance operational efficiencies, promote environmental sustainability, and foster corporate social responsibility. The study underscores the importance of targeted interventions and the potential of mindfulness and empathy in shaping consumer behavior towards food waste.
The research contributes to the literature by extending the TPB framework, introducing novel moderators, and underlining the significance of psychological factors in understanding and mitigating consumer food waste. Future research directions are proposed to further explore these dynamics and their practical applications across different contexts and cultures
Neoconservatives and Taiwan: Adherents of Conservative Precedent or Advocates for Liberal Interventionism?
No full textDuring the 1990s neoconservatives grew concerned over a burgeoning People���s Republic of China (PRC) threatening the newly democratic government of Taiwan. They wanted the United States to bolster Taiwan���s standing in the international community, commit to defend Taiwan, end strategic ambiguity, prevent further entrenchment of the PRC in international organizations, and push for closer if not official relations between the United States and Taiwan. Neoconservatives frequently employed Wilsonian rhetoric to shore up support for Taiwan. Despite this liberal notion, their foreign policy positions and thinking built on the likes of the China Lobby and New Right. By analyzing neoconservative viewpoints on U.S. policy towards Taiwan one can see how evolved earlier conservative positions despite accusations that they carried on liberal tenets in foreign policy
Teacher Motivations for Field Trips to Small Museums
No full textThis study explored what components are most valued by teachers during the planning phase of field trips to small museums. It identified teachers' motivations and constraints when planning a field trip to a small museum. In addition, it examined the influence of motivations and constraints on the likelihood of teachers taking a field trip and teachers��� willingness to put in effort to take a field trip after the planning phase. Past research on teacher motivations for field trips, however, reveals a need to improve in the area of small museums. Small museums are significant contributors to society by providing local access to education, creating job opportunities, promoting sustainability, and more. This study sought to find teachers' motives and constraints during field trip planning and the intention of taking a field trip after planning through survey data collected from teachers ranging from kindergarten to twelfth grade. The data analyzed were grouped into motives, constraints, likelihood, and willingness. The findings offer insight to small museums to make the necessary investments in school field trips that may increase revenue, enhance community engagement, and create better educational experiences
Raman Spectroscopy as a Diagnostic Tool for the Detection of Tomato Brown Rugose Fruit Virus
No full textTomatoes and peppers together constitute a billion-dollar industry in the United States alone, which speaks highly of their importance to growers and the United States Department of Agriculture (USDA) alike. These crops, however, are host to a destructive virus, tomato brown rugose fruit virus (ToBRFV). Due to its ability to overcome all tobomovirus resistance genes, including Tm-2��, there are no known resistant varieties for ToBRFV. Therefore, many regulations are in place in hopes of controlling its spread, yet it continues to spread to many areas around the world, constituting a global epidemic. Raman spectroscopy (RS) is a noninvasive tool that scans a sample and uses the interaction of light and molecules to give a resulting spectrum of scattered light that can be used for analysis. This tool for detecting chemical compounds is already popular in many fields and has recently even been a growing research endeavor for disease diagnostics in plant pathology, where it has shown great promise with a wide variety of diseases. In this study, we examine ToBRFV as well as tobacco mosaic virus (TMV) and aim to determine if RS can be used as a diagnostic method to aid in management practices. We hypothesize that we will be able to observe differences in spectral peaks between healthy and infected plant/seed tissue with control, TMV, and ToBRFV groups. After inoculation, scanning, and Matlab analysis, it was demonstrated that there were spectral differences between healthy and infected plants, as well as differences between TMV and ToBRFV-infected plants. Additionally, this experiment was done on pepper seeds and preliminary data was obtained which displayed spectral differences between pepper seeds infected with ToBRFV and control seeds, showing potential support for this notion on seed tissue as well. Results suggest that RS does show promise to be incorporated as a diagnostic method and may provide useful insight into virus distribution throughout plants. Based on the results obtained in this study, there is potential for future work to take place on the basis of this data
Prototype of a Bi-Directional Digital Twin of an Industry 4.0 Smart Manufacturing Facility
No full textThis thesis presents a pioneering exploration into the development and practical application of a bi-directional digital twin prototype within the context of Industry 4.0 smart manufacturing. Bridging the gap between the physical and digital realms, this research addresses the emerging need for advanced digital replication and interaction mechanisms capable of enhancing operational efficiency and educational processes in modern manufacturing environments. By integrating technologies like Siemens TIA Portal, NetToPLCSIM, and OPC UA Server, with a sophisticated communication framework, the study establishes a seamless, real-time bi-directional communication between a physical model and its digital counterpart. The results demonstrate the system's capability to accurately mirror actions and movements across the physical and digital domains, highlighting its potential to revolutionize manufacturing processes, predictive maintenance, and training methodologies. This work not only contributes to the theoretical understanding of digital twin technologies but also showcases a tangible implementation, paving the way for future research and the broadening of digital twin applications across various sectors of the industrial domain
Electric Powertrain Models for Small UAS Conceptual Design
No full textSmall, battery powered unmanned aerial systems (SUAS) have become indispensable tools for researchers, civilians, and warfighters. However, conceptual designers do not have rigorous tools to design and analyze their electric powertrains which consist of brushless DC motors; therefore, lid-state motor controllers, and lithium polymer batteries. Literature models to analyze the components��� efficiencies rely on detailed information that a vehicle designer cannot practically acquire at the early design stage, such as empirical test data. Therefore, engineers must rely on inaccurate constant powertrain efficiency assumptions which lead to subpar designs. Moreover, existing models ignore the influence of a component���s thermal dynamics on size and performance; therefore, these models could lead to designs that are significantly over or undersized depending on the thermal conditions in which the existing models��� underlying data was collected. Consequently, the resulting designs can overheat or add too much weight penalty in the final vehicle. We have developed a set of efficiency, thermal, and sizing models to address this literature gap in the design and analysis of electric powertrains. We validated these models using wind tunnel tests, motor teardowns, and flight tests. Individually, the models can predict a motor���s efficiency, heat transfer, mass, and electrical constants given high-level inputs which a user can easily find at the conceptual design stage. The models capture the coupled dynamics of a motor���s size, performance, and thermal response. The nuanced results enable users to size the optimal motor for a desired application and given thermal conditions. We also developed efficiency models for the motor controller and battery which rely on fewer inputs than similar literature models, and we validated them with parametric experimental tests. Finally, we developed an instrumentation system that measured and recorded a quadcopter���s propeller torque, propeller speed, and electrical power during flight. We used the flight data to validate an integrated powertrain model that combined the motor, motor controller, and battery efficiency models. The integrated model predicted the vehicle���s battery discharge within 5% of flight data for a six-minute flight. The integrated model enables a user to evaluate different powertrain configurations for an entire mission using readily available inputs
Remote and Proximal Imaging Methods for Cotton Nitrogen Status Estimation
No full textNitrogen (N) is an essential plant nutrient and also a major environmental pollutant. Plants require N for amino acid synthesis, chlorophyll health, canopy growth, and yield. In cotton, both N deficiency and excessive N applications affect plant growth and yield. Studies showed that the growth period between squaring and peak flowering corresponded to peak N uptake in cotton plants. Here we explored remote and proximal imaging methods to quantitatively estimate N status in cotton.
A multi-year N management field experiment was conducted to observe cotton development between vegetative growth and early flowering stages. Extraction of precise spatiotemporal features and robust modeling were the topics emphasized in this dissertation. Objective 1 determined the effect of exposure settings on image radiometric accuracy. The results favored the use of fixed exposure settings for UAV flights and the ideal exposure time and gain were empirically determined for the camera. The object-based empirical line calibration method was proposed for images acquired with fixed exposure settings. Objective 2 explored the systematic integration of the downwelling light sensor (DLS) to compensate for changing illumination conditions. The proposed DLS-based methods effectively removed radiometric errors due to illumination changes in fixed and auto-exposure images.
Objective 3 assimilated results from Objectives 1 and 2 to extract calibrated spectral and morphological cotton canopy features to quantify canopy N and predict stress levels. Plant biological parameters ��� plant N concentration, plant N uptake, dry biomass weight ��� were best estimated when spectral and morphological features were combined through random forest regression and gradient boosting regression models. Model estimated parameters were used to derive nitrogen nutrition index to predict stress levels with good precision and recall (F1 = 0.75). Objective 4 explored extracting spectral and morphological features from oblique ground-based images. The goal was to see if cotton had differences in spectral vegetation indices in the top and bottom canopy layers due to N stress. An algorithm was developed to correct perspective distortion in oblique images. The results showed scope for further exploration of oblique images for early detection of N stress
The Effectiveness of a Newly Developed Fluoride-Releasing O-Ring for Prevention of White Spot Lesions: An In-Vitro Study
No full textPreventing white spot lesions (WSLs) in orthodontic patients remains a challenge. An effective method for incorporating calcium fluoride (Ca-F) into polycaprolactone (PCL), widely used for drug delivery, has been established. With this method, an elastomeric ligature (O-ring) is transformed into a Ca-F O-ring capable of consistently releasing therapeutic levels of fluoride ion over a span of seven weeks. The aim of this study is to assess the effectiveness of Ca-F O-ring in preventing WSL in vitro.
A Ca-F solution was combined with 10% PCL to create a mixture of 5% PCL with Ca-F. O-rings were briefly immersed in this mixture to generate the Ca-F O-rings. 60 premolars with sound enamel were bonded and randomly allocated into three groups for pH cycling: 1) ordinary O-ring with topical over-the-counter fluoridated toothpaste application (O-F); 2) ordinary O-ring (O-R); 3) Ca-F O-ring (O-CaF). Acid-resistant nail polish was applied to surrounding tooth surface, leaving a 4x2 mm2 treatment window of exposed enamel adjacent to cervical aspect of the bracket. All specimens underwent a 9-day pH cycling process. Lightness (L*) value within the treatment window of each sample was evaluated using spectrophotometer at baseline (T0) and after (T1) pH cycling. Mineral densities were determined after pH cycling for the treatment window, adjacent surface enamel layer, and deep enamel layer.
No significant differences in L* values were found between groups at T0 and T1. At T1, L* in group O-CaF was lower than other groups, but not significantly. Group O-CaF had significantly lower mineral densities in treatment window regions than the other groups at T1. For all groups, mineral density increased in the treatment window after pH cycling when compared to adjacent surface enamel control regions.
Use of Ca-F O-rings for prevention of WSLs in orthodontic patients is promising. When compared to controls with and without topical fluoride, the group O-CaF exhibited potentially more effective remineralization after pH cycling and less of a hypermineralized surface seen with WSLs. Future studies with SEM analysis and with increased pH cycling time are needed to confirm the ability of these Ca-F O-rings to effectively remineralize enamel after pH cycling
Reliability and Economics of Distribution Systems with Edge-Level Distributed Energy Resources
No full textElectrical power distribution systems are experiencing a pivotal transformation due to the increasing integration of edge-level behind-the-meter (BTM) distributed energy resources (DERs). This transformation introduces challenges in the planning and operation of distribution systems. Primary challenges include reliable delivery of electricity to the end user while maintaining the utility���s financial viability. This dissertation introduces a multi-level hierarchical framework that bridges the gap in the current distribution system reliability assessment by incorporating the complexities and stochastic nature of end-user DERs. This framework is adaptable to distribution systems with varying levels of DER penetration and addresses the technological diversity and unpredictability inherent in DERs, making it a significant advancement over existing methodologies. This work developed a modular general-purpose end-user reliability model that forms the basis for developing reliability assessment methods and revenue impact analysis. A bottom-up probabilistic approach is presented that integrates the end-user with BTM DER into the reliability assessment. A notable innovation in this work is the application of probabilistic distributions to quantify the end-user BTM DER penetration and integrate them into the probabilistic approach to assess distribution system reliability in various DER penetration scenarios. Economic impact assessment forms another crucial dimension of this dissertation, encompassing a comprehensive exploration of the implications of end-user BTM DER integration for utility revenue, customer costs, and overall system economics. The dissertation examines the cost-benefit dynamics of DERs and the influence of regulatory policies such as Net Energy Metering (NEM), quantifying the economic impacts under various DER adoption scenarios. The dissertation employs reliability test cases and simulation analyses to study the effectiveness of the developed framework and assessment methodologies. This dissertation contributes to the field of power systems by providing methods and tools for managing the challenges and opportunities presented by end-user BTM DER in system planning and integration