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The Effects of Culturally Tailored Agricultural Literacy Curriculum Among Latino Youth Behavior
No full textAgriculture and nutrition are tightly intertwined as each relies heavily on the other to support the Nation���s food system and the consumers it feeds. Unfortunately, the urbanization of our communities has triggered a divide between farmers and their consumers. This is made evident by the general population lacking an inadequate level of agricultural literacy. Partnered with this decline, an insidious health problem, childhood obesity, has increased in America���s youth. It is important to recognize that there is a higher prevalence of this health disparity among the Hispanic population. Through the lens of the social cognitive theory, the researchers aimed to assess the impact of culturally relevant agricultural literacy lessons have on Latino youths��� agricultural literacy levels and nutrition attitudes and behavior scores. The objectives of this study were achieved by implementing two interventions, the comparison and treatment, to youth after-school and summer programs located in Central and South Texas. The comparison group received the standardized agricultural literacy curriculum from the National Agricultural Literacy Matrix. The treatment group received the culturally tailored version of the curriculum. The pre and posttest data were analyzed by t-tests and repeated measures ANOVA. Regardless of intervention, the agricultural literacy levels of youth increased from pre to posttest which provides researchers with evidence of the positive impact of youth engaging with nutrition based, agricultural literacy curriculum. The youth who engaged with the culturally relevant agricultural literacy curriculum had a positive gain in their nutrition attitudes and behavior scores. Conversely, the comparison group did not have significant change in their nutrition scores. The novelty of this research provides valuable insight to scholars in the agricultural literacy field as it underscores the importance of providing a space for youth to connect their cultural background and experiences while interacting with lessons that highlight the relationship of the agricultural industry and nutrition
Bayesian Optimization of Coupled Systems
No full textThe field of multidisciplinary design optimization (MDO) addresses the complex challenge of optimizing systems characterized by interconnections or couplings, which significantly increases the computational burden for ensuring reliability in optimization outcomes. Particularly, design challenges involving feedback-coupled systems are notorious for their substantial demands on computational resources. In response to this issue, substantial efforts have been directed towards developing surrogate models that accurately replicate the intricate interconnected nature of these systems. Such models promise to drastically reduce computational expenses while maintaining effectiveness. Although Bayesian Optimization (BO) is traditionally celebrated for its efficiency in querying surrogate models, it encounters significant limitations when applied to constructing surrogate models for interconnected systems. Specifically, the black-box nature of BO struggles to capture the complexities of these systems, often necessitating frequent queries to the actual functions for training set updates. This approach, while potentially reliable, results in prohibitive computational costs.
To address these challenges and enhance the efficiency and reliability of optimization in the context of interconnected systems, we propose a novel methodology. This methodology focuses on the construction and querying of interconnected surrogate models, designed to more effectively and efficiently replicate the behavior of the target systems. By overcoming the limitations of traditional black-box models, our approach aims to provide a viable solution to the computational and practical challenges inherent in multidisciplinary design optimization of feedback-coupled systems. This advancement represents a significant leap forward in the pursuit of computationally efficient and reliable optimization techniques for complex, interconnected systems
Self-Healing of Bulk Vitrimers as a Function of Thermomechanical Boundary Conditions
No full textThe subject of this study is vitrimers, a class of thermoset polymers with exchangeable covalent bonds, with a focus on their ability to improve material durability in the aerospace, civil infrastructure, and elastomer technology industries while requiring minimal intervention. The material used in this study was procured from ATSP Innovations, provided as a bulk block with the specified dimensions to meet our testing requirements. The selected material, a variant of ATSP characterized as CBAB, was chosen strategically owing to its unique availability in bulk form from the manufacturer at this juncture. This characteristic of CBAB was pivotal for our study as it is allowed for a consistent and uniform sample preparation, an essential factor for the integrity of our fracture mechanics analysis.
To evaluate the bulk fracture, compact tension (CT) tests were done on samples cut out of a panel. The samples were then mended by putting the two halves of the sample together and applying heat and mechanical pressures to study the kinetics of bond formation and their selfrepair mechanisms. Pre- and post-healing fracture toughness measurements were methodically performed, demonstrating a significant restoration of mechanical strength, confirming the effectiveness of the repair procedure. Furthermore, the study investigated the interplay between time and temperature influencing vitrimers ability to self-heal, offering light on the best circumstances for maximal healing efficiency. The time and temperature dependence of the healing mechanism was explained quantitatively by means of an Arrhenius relationship, and the activation energy of the bond reformation was assessed. Furthermore, by revealing the intricate link between stress levels and the healing process, this study sheds light on the fundamental mechanisms governing vitrimer self-repair, paving the path for improved material design and application. A comparison was made between the healing performance of bulk samples and ATSPcarbon fiber reinforced composites, obtained from other studies, to shed light on the effect of confinement (in the composite) on the healing performance of the vitrimers. Crucially, this study emphasizes the critical roles that temperature, time, and stress levels play in shaping the dynamics of self-healing, providing invaluable insights for both advancing our understanding of vitrimers and facilitating their wider adoption in the field of self-repairing materials
Effect of Overnight Storage Conditions on Dimensional Stability of Conventional Injection Molded, 3D Printed and Milled Complete Dentures
No full textStatement of problem: In modern prosthodontics the fabrication method of complete dentures has become more diverse than ever with the introduction of 3D printing and milling manufacturing. Despite the variety of manufacturing methods developed, the storage recommendations have remained virtually unchanged and untested for new manufacturing methods. Water storage has traditionally been advised at nighttime to prevent denture base distortion through the loss of moisture in the acrylic resin matrix. With the advent of CAD/CAM 3D printed denture bases and Milled denture bases from solid pucks of preprocessed acrylic the necessity to store dentures in liquid when not in use to the authors knowledge has remained untested.
Purpose: The aim of this study was to evaluate whether there is any typical deformation pattern of Injection molded, 3D printed and milled complete dentures stored in different overnight storage conditions for 14 days.
Materials & Methods: One edentulous maxillary typodont model was used as reference for fabrication of n=60 samples of identical digitally designed denture bases. Each denture base was approximately 2 mm thick and n= 20 samples were fabricated from each respective material; Ivobase injection molded pink hybrid denture base resin, Sprintray denture base EU 3D printed resin and Avadent Milled denture bases PMMA Puck LIGHT ��� Universal Shoulder. n=10 samples from each material group were randomly assigned to either a wet or dry storage group. All denture bases were submerged in 37 ��C Water bath for 12 hrs. and alternated for 14 days between their respective storage conditions and heated water bath simulating the oral cavity. Samples were scanned at 3-time intervals time ���0��� (T0), on the 7th day (T1), on the 14th day (T2). Scans were measured for deviations from the reference scan. Statistical analysis performed using Kruskal-Wallis with Bonferroni corrections (����=0.05) for between group differences and Related Samples Friedmans Two-way analysis of variance by ranks for within group differences.
Results: The Group 2 denture bases fabricated from the Ivobase and placed in the dry storage conditions demonstrated greater dimensional change with statistically significant differences in RMS value compared to the Group 1 Ivobase wet storage conditions (p< 0.003). In addition, the Group 3 & 4 Sprintray (wet/dry) demonstrated lower RMS values (p<0.007 & p<0.015) and better stability over time compared to the Group 2 Ivobase dry storage at time points T0-T2. The Avadent milled dentures demonstrated greater RMS value and distortion than the Group 1 Ivobase wet (p<.001), Group 3 Sprint ray wet (p<.001) and Group 4 Sprintray dry (p<.001). There was no significant difference in RMS value between the dry storage and wet storage of the Avadent denture bases.
Conclusions: Statistically greater dimensional changes were found in the dry storage group of Ivobase denture bases compared to the wet denture bases. Sprintray 3D printed denture bases exhibited no statistically significant dimensional changes in 14 days when stored in wet or dry conditions. Avadent milled denture bases exhibited no statistically significant dimensional changes in 14 days when stored in wet or dry conditions, but experienced greater dimensional change compared to Ivobase wet and Sprintray wet/dry storage conditions. All groups regardless of timepoint or storage conditions experience dimensional changes less than <1mm
John Bickham field notebook: AK23501-AK24000.pdf
No full textBound book, each page corresponds to a karyotype slide data.Data pages for AK24001-AK24500 corresponding to unique identifiers of specimens/samples examined for biological research. Specimens are primarily housed at Texas A&M University; Biodiverstiy Research and Teaching Collection
Probabilistic Clustering Methods for Complex Data and Related Topics
No full textProbabilistic clustering involves identifying mutually exclusive subsets of data in a probabilistic manner by characterizing the probability distribution on the space of partitions, enabling uncertainty quantification. Random partition models serve as prior probability models for probabilistic clustering, which are closely connected to Bayesian nonparametric models involving discrete random structures. This dissertation aims to contribute to the existing literature on probabilistic clustering and related topics by introducing new key concepts and novel methodologies.
First, we offer new perspectives on exchangeable random partition models based on the concept of balancedness and risk equilibrium/penalization priors with respect to a loss function. The balancedness property provides a better understanding of what probabilistic clustering model works better and what does not for different applications. The notion of risk equilibrium and penalization priors, which are not limited to clustering problems, provide the development of objective and regularized prior model probabilities in light of the effect of loss functions.
Next, we suggest Bayesian hierarchical models with non-exchangeable random partition models associated with a graph that represents complex dependence structures. We start by introducing the low-rank horseshoe prior based on random spanning trees, which simultaneously detects structured sparsity and smoothness of high-dimensional parameters associated with the graph. Also, we introduce the graph product partition model where a probability of partition is defined as a product of cohesion functions capturing internal and external connectivity. This formulation does not rely on graph generative assumptions and can be used as a robust alternative for the probabilistic clustering of graphs with node attributes.
Finally, we propose the logistic-beta process, whose logistic transformation yields a stochastic process with common beta marginals that have significant computational benefits. It has great potential in applications to dependent Bayesian nonparametric models involving beta distributions, related to probabilistic clustering of non-exchangeable data. We illustrate with a Bayesian density regression problem based on the newly proposed logistic-beta dependent Dirichlet process
System-Level Rotordynamic Analysis of Centrifugal Compressors Using Computational Fluid Dynamics (CFD), Design and Optimization of Novel Swirl Brakes
No full textThe accurate characterization of compressor rotordynamic coefficients during the design phase reduces the risk of subsynchronous vibration (SSV) problems occurring in the field. Although rotordynamists extensively investigate discrete compressor components (such as seals and front shrouds) to tackle instability issues, integrated or system-level analysis of compressor rotordynamics is very scarce. In reality, the impeller, eye labyrinth seal, and the front shroud heavily influence one another; and the collective dynamic behavior of the system differs from the sum of the dynamic behavior of isolated components. Furthermore, American Petroleum Institute (API) level II vibration stability analysis requires inclusion of all possible destabilizing forces including those that stem from seals and the front shroud cavity.
A CFD-based approach is taken to evaluate the dynamic behavior of the system as a whole. The geometry and operating conditions in this work are based on a recently published experimental study on centrifugal compressor. The commercial CFD code CFX 19.0 is used to resolve Reynolds Averaged Navier-Stokes (RANS) equations to quantify the eye labyrinth seal and front cavity stiffness, damping, and added mass. The entire compressor stage is modeled to uncover the coupled behavior of the components and assess the stability of the whole system instead of just discrete components. In the current work, three CFD approaches, namely quasi-steady, transient static eccentricity, and transient mesh deformation techniques are studied and benchmarked against analytical and experimental results from the literature. Having established the efficacy of the proposed approach, 4 types of swirl brakes are proposed and analyzed for stability. The novel swirl brakes create negative swirls at the brake cavities and stabilize both the front shroud and the eye-labyrinth seal simultaneously. The designed swirl brakes are further investigated to identify contribution of each geometric feature of the brakes to the rotordynamic stability of the whole system/stage. The geometric parameters chosen for the parametric study are the height of the slot cavity, the number of slots, the length of slots, the slot angle and the direction of slot curvature
Effect of Feedstock Chemistry and Melt Pool Dynamics on Realizing Superior Strength and Surface Quality in Additively Manufactured Ultra-High Strength Steels
No full textAdditive manufacturing (AM) methods generally utilize a layer-by-layer process, fabricating parts from the bottom up which differs from conventional subtractive manufacturing methods. The current focus of AM development involves the production of complex, functional parts. Due to an increase in demand from industries such as aerospace, biomedical and automotive, metal AM has become increasingly popular. Laser powder bed fusion (L-PBF) is widely regarded as the most versatile metal AM process, utilizing high energy density laser to selectively melt powder particles into highly intricate designs.
Laser powder bed fusion (L-PBF) of a newly developed high strength steel known as AF96 has received notable attention due to its unique microstructure and superior mechanical properties. The current study investigates the influence of initial alloy carbon content and decarburization on the mechanical properties of AF96 fabricated via L-PBF. A process parameter development study was first performed to determine optimal processing parameters that result in near defect-free as-printed parts. Test specimens were then fabricated using optimized parameter combinations for mechanical and microstructural characterization. This process was completed for three compositions of AF96 powder containing varying amounts of initial carbon content. Preliminary results show a significant increase in both yield strength and ultimate tensile strength with increasing initial carbon content.
Spatter, an inherent by-product of conventional laser welding, DED, and L-PBF (Laser Powder Bed Fusion), significantly impacts part quality. This research investigates spatter's mechanisms, effects, and in-situ monitoring techniques within the context of L-PBF. Spatter, classified into droplet (hot) and powder (cold) types, originates from vapor-driven entrainment and recoil pressure, impacting surface quality and creating internal flaws. Spatter redeposition during printing leads to recoater impediment, defect formation, and porosity, affecting mechanical properties and surface roughness. In-situ monitoring techniques encompass visible-light high-speed camera imaging, Schlieren video imaging, X-ray video imaging, and infrared video imaging, each revealing various aspects of spatter behavior. A specialized visible-light high-speed camera system for EOS M290 L-PBF, developed for this study, provides insights into spatter ejection behavior. Technical challenges in camera operation and video acquisition were addressed, achieving successful high-speed video imaging capturing spatter movement. Optical microscopy analysis of L-PBF-fabricated AF96-29 cubes reveals varied surface qualities, correlating with spatter distribution in different printability map regions. This study underscores the complexities of spatter behavior, its detrimental effects, and the significance of tailored in-situ monitoring techniques for understanding and mitigating spatter-related issues in L-PBF
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
Enhancing Control Assessments and Risk Analysis in Batch Chemical Processes: A Focus on Safer Design Methodologies
No full textBatch and semi-batch processes involving critical chemical reactions pose significant risks to industrial safety and require rigorous control assessment and risk analysis. This study aims to survey current industry practices and methodologies for testing and assessing the controls in batch reactions. It identifies strengths and limitations in existing procedures and propose safer design methods to mitigate reactive hazards. In batch reactions, a diverse range of chemicals operates at dynamic parameters such as temperature and pressure. Assuming the worst case scenarios and improper evaluation of controls could lead to events with dire consequences. The study examines the typical tests conducted for batch reactions and identifies opportunities for optimization based on the outcomes. Layer of Protection Analysis is used to evaluate various preventive controls such as Inherently Safer Designs (ISDs), automated systems and relief sizing. Recognizing the pivotal role of critical controls such as quenching and relief sizing as the last line of safeguards in the batch processes, here we determine what are the different ways of performing quenching process to halt the reaction and the effective way of doing this operation. We also develop a model and calculate for effective quenching during worst-case scenarios, demonstrating how this proposed safer design method maximizes control functionality and minimizes risk. As relief is also considered in many cases where quenching is not practical, the relief sizing of reactive systems is quite complex and here we compare how drastic the change in relief size would be for a reactive system when compared to relief sizing performed in a conventional way. Another concern highlighted is relying solely on automated systems, which can lead to catastrophic consequences in case of process deviation. This research scrutinizes the conditions which are considered over conservatively by many of the process Industries, arriving at conclusion of adequacy in the Safety Systems and its impact on the availability of the Safety System on demand (PFD) using exSILentia tools. Overall, this study comprehensively explores industry practices in testing, standard controls and alternate safer designs along with conservative safety system settings