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Computational Biomechanics for a Standing Human Body: Modal Analysis and Simulation
No full textWe develop computational mechanical modeling and methods for the analysis and simulation of the motions of a human body. This type of work is crucial in many aspects of human life, ranging from comfort in riding, the motion of aged persons, sports performance and injuries, and many ergonomic issues.
A prevailing approach for human motion studies is through lumped parameter models containing discrete masses for the parts of the human body with empirically determined spring, mass, damping coefficients. Such models have been effective to some extent; however, a much higher-fidelity modeling method is to model the human body as it is, namely, as a continuum.
We present this approach, and for comparison, we choose two digital CAD models of mannequins for a standing human body, one from the versatile software package LS-DYNA and another from open resources with some of our own adaptations. Our basic view in this paper is to regard human motion as a perturbation and vibration from an equilibrium position which is upright standing. A linear elastodynamic model is chosen for modal analysis, but a full nonlinear viscoelastoplastic extension is possible for full-body simulation.
The motion and vibration of these two mannequin models is analyzed by modal analysis, where the normal modes of motion are determined. LS-DYNA is used as the supercomputing and simulation platform. Four sets of low-frequency modes are tabulated, discussed, visualized, and compared. Higher frequency modes are also selectively displayed. We have found that these modes of motion and vibration form intrinsic basic modes of biomechanical motion of the human body. This view is supported by our finding of the upright walking motion as a low-frequency mode in modal analysis. Dynamic motions of CAD mannequins are also simulated by drop tests for comparisons and the validity of the models is discussed through Fourier frequency analysis. In the low-frequency range, our numerical results have provided a satisfactory self-consistent match as validation. All computed modes of motion are collected in several sets of video animations for ease of visualization. Samples of LSDYNA computer codes are also included for possible use by other researchers
Electrokinetic Convection-Enhanced Delivery of Macromolecules to the Brain
No full textElectrokinetic convection-enhanced delivery (ECED) utilizes an external electric field to drive the delivery of molecules and bioactive substances to local regions of the brain through electroosmosis and electrophoresis, without the need for an applied pressure. We studied the implementation of ECED to direct a neutrally charged fluorophore (3 kDa) from a doped biocompatible acrylic acid/acrylamide hydrogel placed on the cortical surface. Ex vivo (N = 18) and in vivo (N = 12) experiments were conducted to compare fluorophore infusion using ECED (time = 30 min, current = 50 ��A) and diffusion-only control trials. The linear intensity profile of infusion was significantly higher in ECED compared to control trials, both for in vivo and ex vivo. The linear distance of infusion, area of infusion, and the displacement of peak fluorescence intensity along the direction of infusion in ECED trials compared to control trials were significantly larger for in vivo trials, but not for ex vivo trials. These results demonstrate the effectiveness of ECED to direct a solute from a surface hydrogel towards inside the brain parenchyma based predominantly on the electroosmotic vector
Multi-Tiered Systems of Support: Implementation Experiences of High School Principals
No full textThis study aimed to explore the Multi-Tiered Systems of Support (MTSS) implementation experiences of three high school principals and their assistant principals in one North Texas public school district. The study utilized qualitative methods and case study design to better understand the principals��� overall impression of MTSS implementation and their suggestions for improving the conditions that may have hindered the implementation of MTSS on their campuses. The findings presented in this study are the analysis of data acquired through the Self-Assessment of MTSS Implementation (SAM) survey, the principal interviews, and document analysis. The analysis was guided by implementation science as proposed by Fixsen and Blas�� (2008). This analysis of the data showed that the three high schools in the study have stalled in their MTSS implementation efforts after five years, mostly during the program installation phase, despite their best efforts. To move the high schools forward from the program installation stage to the full operation stage on the implementation science continuum, I proposed recommendations that address the three main drivers of successful implementation: leadership drivers, organization drivers, and competency drivers. By systematically addressing these drivers, the high schools in the study can progress toward full implementation of MTSS
San Giacomo di Galizia: The Digital Reconstruction of a Galleon of the Anglo-Spanish War of 1585 ��� 1604
No full textThe San Giacomo di Galizia was a late-16th century galleon employed by Spain during the Anglo-Spanish War that took place between 1585 and 1604. After a failed attempt to capture the English port of Falmouth, the ship returned to Ribadeo on the north coast of Spain, where it sunk due to the damage received in foul weather. The purpose of the thesis was to digitally reconstruct the vessel based on the archaeological evidence, primary historical sources, and contemporary naval treatises in order to analyze the hydrostatic features of the galleon to comprehend the seagoing performance of similar ships of this period. Likewise, the project aimed to determine the efficiency of this new methodology as a digital tool for nautical archaeology and historical research
The Role of the Science Teacher: Examination of Science Education Research and Science Teacher Education
No full textScience education has repeatedly identified the teacher as the greatest classroom level factor on student learning. Given the known variance in instructor ability and quality, a failure to consider how an instructor effect may be impacting study results draws into question the validity of study analyses and conclusions that fail to adequately conduct meaningful comparisons. The first investigation of this dissertation examined 79 studies from three leading science education journals to determine the frequency and quality of attention towards instructor differences in sampling efforts. Our findings indicate that instructor difference is rarely considered to a sufficient level within science education research, even in studies with exceedingly small sample sizes. These results are concerning for research practitioners who may be neglecting a key factor in research outcomes.
Though literature surrounding science teacher preparation programs is limited, current evidence suggests that methods courses frequently foreground instructional strategies and activities rather than a more comprehensive framework for science teaching. Potential consequences for this emphasis for preservice educators include a rejection of research-based instructional strategies, weakened instructional effectiveness, and an inability to conduct effective classroom decision-making. Study two in this dissertation analyzed 30 science methods syllabi from varying institutions and education programs to provide preliminary insight into science methods emphases. Our findings support prior claims that science methods courses are highlighting instructional strategies while neglecting the crucial role of the science teacher and teacher behaviors.
The science teacher must clearly understand their role in scaffolding student thinking away from misconceptions and towards accurate understanding of scientific ideas. The final study of this dissertation sought to triangulate findings from study two by interviewing methods instructors to understand their conceptualizations of effective science teaching, the instructional role of the science teacher, and the function of teacher behaviors within that role. Our findings suggest that methods instructors often employ vague metaphorical language when describing the instructional role of the science teacher and rarely address teacher behaviors. Syllabi were found to effectively reflect methods instructors��� conceptualizations of effective science teaching and the function of teacher behaviors but were less effective in representing methods instructors��� conceptualizations of the role of the science teacher
Geometric Deep Learning for Molecular Discoveries
No full textWith the rapid advancement of artificial intelligence (AI), its applications in scientific research have grown significantly, giving rise to the research area of AI for science (AI4Science). In this dissertation, we focus on AI for molecular science, such as small molecules and proteins, aiming to build efficient and effective methods to accelerate molecular discovery. we particularly focus on two fundamental tasks, molecular representation learning and molecule generation. Specifically, we model molecules as graphs and design geometric deep learning methods for molecules.
We first consider representation learning of 3D molecular graphs, where each node has its 3D coordinates. With an accurate representation learning model, we can reduce the computation time required for predicting molecular properties. In this dissertation, we provide an analysis in the spherical Coordinate System (SCS) for the complete identification of 3D graph structures and propose our SphereNet. SphereNet can distinguish similar molecular structures, such as two enantiomers that are mirror images of each other and reduce complexity from O(nk��) to O(nk��),
enabling it to perform efficiently on large-scale molecules. Here n and k denote the number of nodes and the average degree in the 3D graph, respectively.
While SphereNet presents advancements in accuracy and efficiency, it still can not incorporate 3D information completely. Furthermore, its complexity remains higher than some existing methods. We then propose ComENet to address these issues and incorporate 3D information completely and efficiently. Our method guarantees full completeness of 3D information on 3D graphs by achieving global and local completeness with a complexity of O(nk).
SphereNet and ComENet are tailored for small molecules. Extending their application to proteins is challenging due to the large number of atoms in proteins and their inherent multi-level nature. Therefore, we further design our method ProNet specifically for proteins. ProNet completely captures three levels of protein structures, e.g., the amino acid, backbone, or all-atom levels and is more efficient than existing methods. ProNet can be applied on various downstream tasks, including protein fold and function prediction, protein-ligand binding affinity prediction, and protein-protein interaction prediction.
Lastly, we consider 3D molecule generation. The generation of novel molecules with desired properties is an important step in drug discovery. In this dissertation, we apply language models (LMs) for 3D molecule generation by introducing our canonical and SE(3)-invariant tokenizer, Geo2Seq. Experiments show that our new method can achieve promising results
John Bickham field notebook: AK9001-AK9500.pdf
No full textBound book, each page corresponds to a karyotype slide data.Data pages for AK9501-AK10000 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
Investigating Fifth Grade Teachers��� Implementation of ESL Instructional Strategies in Literacy-Infused Science Instruction
No full textThe purpose of this study was to investigate whether there is a significant difference in the time allocation of ESL instructional strategies between the treatment teachers who received literacy-infused science (LIS) curriculum accompanied virtual professional development (VPD) on such strategies as an intervention and control group of teachers who did not receive the VPD intervention. I further explored teachers��� perceptions of the impact and challenges of English as a Second Language (ESL) instructional strategy implementation in their science teaching practices and their students��� responses to the strategies.
To examine the differences in fifth-grade science teachers��� time allocation in their use of ESL instructional strategies between treatment and control groups, a low-inference observational instrument, Pedagogical Observation Protocol (POP), was used. Treatment teachers received bi-weekly VPD sessions provided through Project LISTO (Literacy-Infused Science Using Technology Innovation Opportunity, Grant Award No. U411B16001; Lara-Alecio et al., 2013), including a series of scaffolding strategies that benefit teachers��� professional growth as well as their students��� learning outcomes. A total of 14,332 rounds of observation clips were collected from 98 in-service science teachers who were randomly assigned to treatment and control conditions across Texas during the 2018-2019 academic year. Results revealed a statistically significant difference in 7 out of 9 strategies between treatment and control group teachers in utilizing ESL instructional strategies in science classrooms. Treatment teachers significantly used more strategies learned in VPDs than the control group of teachers. To further explore the perceived impact of ESL instructional strategy implementation, semi-structured focus group interviews were conducted for treatment teachers at the end of the school year. The results of the thematic analysis indicated a positive perception of using ESL strategies in science classrooms in terms of enhancing teachers��� quality of instruction and self-confidence as well as students��� science learning interest and literacy development. Therefore, this evidence supported that teachers��� instructional practice and student support were positively impacted by allocating a variety of instructional time toward ESL strategies. However, teachers encountered the challenges such as time constraints and technological issues while implementing ESL strategies might potentially lead to less time allocation in certain strategies
Essays on the Causal Effects of Retailer Strategic Actions on Sales, Omnichannel Shopping, and Mobile App Engagement
No full textRetailers engage in strategic actions such as store closure and the introduction of new features in mobile apps. Each action has the potential to change shoppers��� omnichannel shopping behavior and engagement. Empirical analysis of the causal effects of these strategic actions is challenging because field experiments are often expensive and infeasible. In the two essays of my dissertation, I focus on the strategic actions of a large U.S. retailer of video games and consumer electronics and analyze the causal effects of these actions. I use the difference-in-differences (DID) framework, controlling for potential endogeneity, to causally estimate the effects of the strategic actions. I apply machine learning algorithms to explore treatment effect heterogeneity and analyze unstructured app clickstream data.
In Essay 1, I study the impact of store closure on the retail chain���s aggregate sales, customers��� omnichannel shopping, and mobile app usage. The results show that store closures led to a significant loss of $209,317 in net monthly sales per county, surpassing the average sales of the closed stores. Both offline and online sales dropped after the closure of a store. These results highlight that retailers should re-examine their closure plans and account for the negative spillover effect.
Essay 2 examines the causal effect of in-app payment introduction on omnichannel shopping and mobile app usage behavior, uncovers individual-level treatment effect heterogeneity, and investigates the underlying mechanisms. I find that adopting in-app payment significantly boosts overall purchases. As a result, overall spending net of returns is 25.3% (33.6%) higher for Apple Pay (PayPal) adopters than nonadopters. Mechanisms driving these results include increased spending both offline and online, reduced friction, lower mobile cart abandonment rate, increased Buy-Online-and-Pickup-In-Store (BOPIS) orders, heightened app usage near stores, greater store visits due to increased product returns and trade-ins, and more impulse purchases
Selective Aryl Hydrocarbon Receptor Modulators as a Potential Treatment for Major Depressive Disorder
No full textMajor depressive disorder (MDD) is a worldwide public health concern, and although treatments exist, many people still suffer from treatment resistant depression. The projects in this dissertation aimed to evaluate the feasibility of using selective aryl hydrocarbon modulators (SAhRMs) as a treatment for MDD. The aryl hydrocarbon receptor (AhR) is a ligand-activated intracellular transcription factor that is involved in numerous biological processes which are linked to potential causes of MDD. Two SAhRMs, 3,3���-diindolylmethane (DIM) and 1,4-dihydroxy-2-napthoic acid (DHNA) were tested for their ability to prevent and treat MDD-like behavior in female mice using unpredictable chronic mild stress (UCMS). Depression- and anxiety-like behaviors were examined using a battery of behavioral tests. In the first project, both SAhRMs prevented and reversed depression-like behavior but had little effect on anxiety like behavior. An isomer of DHNA, which is inactive at the AhR, did not prevent depression-like behavior, hinting at a role for AhR activity in the antidepressant action of DHNA. In the second project, male mice were examined, and SAhRMs did not act as antidepressants but had some effects on anxiety-like behavior in males. There was no effect of SAhRMs on spatial learning or on weight gain in stressed or unstressed male or female mice. The third project tested mice which do not express the AhR in the internal epithelium (AhR��IEC). AhR��IEC mice were resilient to the effects of stress on depression-like behavior, suggesting a role for intestinal AhR in maintaining depression- like states. Additionally, SAhRMs prevented depression-like behavior in these mice, effectively eliminating the intestinal epithelium as a potential site of action for SAhRMs. Limitations, possible mechanisms, and applications are discussed. The results of these studies indicate a potential for SAhRMs to be developed as a treatment for MDD and highlight the need to further investigate the role of AhR in MDD