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Don't Fear The Artificial Intelligence: A Systematic Review Of Machine Learning For Prostate Cancer Detection In Pathology, Aaryn Frewing, Alexander B. Gibson, Richard Robertson, Paul Urie, Dennis Della Corte Aug 2023

Don't Fear The Artificial Intelligence: A Systematic Review Of Machine Learning For Prostate Cancer Detection In Pathology, Aaryn Frewing, Alexander B. Gibson, Richard Robertson, Paul Urie, Dennis Della Corte

Faculty Publications

The adoption of whole slide image (WSI) scanners in clinical practice was accelerated by US Food and Drug Administration approval in 2017, which allowed primary pathologic diagnoses to be made on scanned images. Images in the digital domain allow the application of pathology artificial intelligence (AI), including clinical decision support with algorithms performing specific diagnoses.1,2 These algorithms, if trained properly, could go beyond the ability of human observation to detect and quantify features that are not recognizable by human perception.1,3,4

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Designed For Better Control: Using Kinematic And Dynamic Metrics To Optimize Robot Manipulator Design, John R. Morrell Aug 2023

Designed For Better Control: Using Kinematic And Dynamic Metrics To Optimize Robot Manipulator Design, John R. Morrell

Theses and Dissertations

In the field of control theory, optimal performance is generally defined as the best possible controlled performance given a static, unchangeable plant system. However, principled design of the underlying system can make designing effective controllers easier and dramatically improve the final control performance beyond what any finely tuned controller could achieve alone. This work develops performance metrics for serial robot arms which help guide the design and optimization of the structure of the arm to achieve greater final performance. First, a kinematic (motion-based) metric called the Actuator Independence Metric (AIM) measures the uniqueness of the movement capabilities of the different …

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Measuring Microparticle Adhesion Via High-Speed Rotor, Jacob C. Fearnley Aug 2023

Measuring Microparticle Adhesion Via High-Speed Rotor, Jacob C. Fearnley

Theses and Dissertations

Much is known about the atomic/molecular theories that govern adhesion as well as the macroscopic aspects and properties of adhesion. However, adhesion in the microparticle regime is poorly characterized. We report on experiments that use centrifugal force to remove polystyrene (PS) particles from the surface of a high-speed titanium rotor operated in vacuum. This unique rotor can apply forces far greater than other centrifugal force methods or related techniques using atomic force spectroscopy. The mode of attachment, whether particles were located on the windward side versus leeward side of the spinning rotor, time spent in vacuum prior to experiments, and …

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Detailed Characterization Of Material Deformation, Alexander J. Farnsworth Aug 2023

Detailed Characterization Of Material Deformation, Alexander J. Farnsworth

Theses and Dissertations

This dissertation presents a comprehensive exploration of material deformation at the atomic level, investigating key findings and contributions through three fundamental methods: Sum Frequency Generation Spectroscopy (SFG), X-ray Diffraction (XRD), and Electron Backscatter Diffraction (EBSD). The research commences by uncovering the material dependency of nonresonant responses in both SFG and Second Harmonic Generation (SHG) signals. This redefinition of the nonresonant component as an information-rich carrier, rather than mere background noise, leads to novel insights into the potential applications of SFG. The study then delves further into the influence of mechanical stress on materials, establishing a connection between dislocation density on …

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Separation Of Perrhenate And Perfluoroalkyl Substances By Ion Chromatography With Customized Stationary Phases, Wai Ning Chan Aug 2023

Separation Of Perrhenate And Perfluoroalkyl Substances By Ion Chromatography With Customized Stationary Phases, Wai Ning Chan

Theses and Dissertations

Ion exchange chromatography (IC) is an analytical technique used to separate charged molecules including ions, proteins, small nucleotides, and amino acids. It can function in anion or cation mode. In this dissertation, anion exchange chromatography was used, and column materials were made in our lab with resorcinarene-based compounds called cavitands. Cavitands create cavities to bind to molecules because of their three-dimensional structure. Two new gradient IC methods were established to identify and quantify perrhenate and perfluoroalkyl substances (PFAS) by customized resorcinarene-based column, zinc cyclen resoecinarene (ZCR) and arginine methyl ester (RUE) columns. The ZCR column accomplished outstanding separation of perrhenate …

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Rural Science Teachers Social Network Analysis Matrices, Rebecca L. Sansom, Tracy Poulsen Aug 2023

Rural Science Teachers Social Network Analysis Matrices, Rebecca L. Sansom, Tracy Poulsen

ScholarsArchive Data

These are the social network matrices for our study of rural science teachers. Each matrix is located on a separate tab on the spreadsheet.

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The Role Of Cytosolic Chaperonin Cct And Its Co-Chaperone Phlp1 In Folding And Assembly Of Signaling Complexes, Yujin Kwon Aug 2023

The Role Of Cytosolic Chaperonin Cct And Its Co-Chaperone Phlp1 In Folding And Assembly Of Signaling Complexes, Yujin Kwon

Theses and Dissertations

CCT, a large (1 MDa) protein-folding machine, is a eukaryotic group II chaperonin that is essential for folding many cellular proteins and is the most complex of all chaperonins with two rings each composed of eight paralogous subunits. CCT captures proteins in its folding chamber to assist the folding of its substrates. CCT utilizes ATP hydrolysis to open and close its chamber and fold its substrates. CCT has been shown to be important in the folding of proteins with - propeller domains which consist of seven WD40 repeat sequences that fold into -sheets that form the blades of a propeller-like …

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Terahertz From Electrons, Electronics From Terahertz, Clayton D. Moss Aug 2023

Terahertz From Electrons, Electronics From Terahertz, Clayton D. Moss

Theses and Dissertations

Time-domain terahertz spectroscopy (THz-TDS) is a valuable technique for studying collective ultrafast phenomena. Several mechanisms exist for converting ultrashort optical laser pulses into coherent THz sources. Broadband THz pulses can be obtained from electron currents in air plasma, which requires combinations of different colors of light to be most effective. I report multi-color generation schemes of THz pulses that deliver coherent THz output. Experimental and theoretical work using the photocurrent model describe ways to use non-harmonic color combinations to utilize several sources of light available in a table-top laser setup. Additionally, THz-TDS is used to study a variety of ultrafast …

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The Influence Of Political Media On Large Language Models: Impacts On Information Synthesis, Reasoning, And Demographic Representation, Alexander Glenn Shaw Aug 2023

The Influence Of Political Media On Large Language Models: Impacts On Information Synthesis, Reasoning, And Demographic Representation, Alexander Glenn Shaw

Theses and Dissertations

This thesis investigates the impact of finetuning the LLaMA 33B language model on partisan news datasets, revealing negligible changes and underscoring the enduring influence of pretraining datasets on model opinions. Training nine models across nine distinct news datasets spanning three topics and two ideologies, the study found consistent demographic representation, predominantly favoring liberal, college-educated, high-income, and non-religious demographics. Interestingly, a depolarizing effect emerged from partisan news finetuning, suggesting that intense exposure to topic-specific information might lead to depolarization, irrespective of ideological alignment. Despite the exposure to contrasting viewpoints, LLaMA 33B maintained its common sense reasoning ability, showing minimal variance on …

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Improved Endmember Mixing Analysis (Emma): Application To A Nested Catchment, Provo River, Northern Utah, Alyssa Nicole Thompson Aug 2023

Improved Endmember Mixing Analysis (Emma): Application To A Nested Catchment, Provo River, Northern Utah, Alyssa Nicole Thompson

Theses and Dissertations

An endmember mixing analysis (EMMA) is a hydrograph separation technique used to identify and quantify stream source contributions, but the error within the results of the analysis itself can be difficult to quantify. Employing EMMA to accurately quantify these contributions is particularly important for critical watersheds that supply water to large populations, such as montane watersheds. We applied EMMA to the Provo River, a nested catchment with three monitoring locations in northern Utah, to understand the limitations and potential improvements that could be made to EMMA. Four main endmembers (quartzite groundwater, soil water, snow and carbonate groundwater) were identified for …

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Continuous-Time Trajectory Estimation And Its Application To Sensor Calibration And Differentially Flat Systems, Jacob C. Johnson Aug 2023

Continuous-Time Trajectory Estimation And Its Application To Sensor Calibration And Differentially Flat Systems, Jacob C. Johnson

Theses and Dissertations

State estimation is an essential part of any robotic autonomy solution. Continuous-time trajectory estimation is an attractive method because continuous trajectories can be queried at any time, allowing for fusion of multiple asynchronous, high-frequency measurement sources. This dissertation investigates various continuous-time estimation algorithms and their application to a handful of mobile robot autonomy and sensor calibration problems. In particular, we begin by analyzing and comparing two prominent continuous-time trajectory representations from the literature: Gaussian processes and splines, both on vector spaces and Lie groups. Our comparisons show that the two methods give comparable results so long as the same measurements …

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A Polarizable Molecular Dynamics Potential For Molten Salt Property Prediction, Jared Thurgood Aug 2023

A Polarizable Molecular Dynamics Potential For Molten Salt Property Prediction, Jared Thurgood

Theses and Dissertations

The present study attempts to find an alternate computational tool to model the complex physical interactions within the molten salt FLiNaK in a way that is both efficient and accurate. Additionally, this study seeks to describe the effects of several different types of impurities on the FLiNaK salt system. This study selects two different polarizable force fields, the AMOEBA polarizable approach and the polarizable ion model, to determine the density and the structure of the impure FLiNaK salt mixtures at typical operating temperatures in molten salt reactors (between 500-900 °C). This study conducts ab initio molecular dynamics (AIMD) simulations and …

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Semantically Structured Creative Computer Systems & Automated Evaluation Of Creative Artifacts, Brad Spendlove Aug 2023

Semantically Structured Creative Computer Systems & Automated Evaluation Of Creative Artifacts, Brad Spendlove

Theses and Dissertations

Computational creativity seeks, in part, to develop autonomous agents that exhibit creativity. Language is an ideal creative domain for studying computer agents due to its rich interconnectedness and immense space of possible combinations. This dissertation explores the design, testing, and theory of creative computer systems that write microfiction and play the board game Codenames. The designs of these systems are all similarly based on building up creative artifacts from the underlying structure of the relationships between words. A critical component of the creative process is the ability to evaluate the quality of creative output. Human and automated assessment of our …

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Geochemistry Of Zircon And Apatite In Rhyolites From The Central Snake River Plain: Genetic Implications, Chesley Philip Gale Aug 2023

Geochemistry Of Zircon And Apatite In Rhyolites From The Central Snake River Plain: Genetic Implications, Chesley Philip Gale

Theses and Dissertations

Whole-rock and mineral compositions of three eruptive deposits from the Twin Falls caldera, associated with the Yellowstone hotspot, provide a window into melt generation and evolution for hot, dry, A-type rhyolites. Three rhyolitic units were sampled via the Kimberly drill-core as a part of project HOTSPOT, a study focused on mantle plume and continental lithosphere interaction. Previous work has been done to collect high resolution U-Pb zircon ages, and Hf- and O-isotopic compositions. This study examined the geochemistry of apatite and zircon along with host rock compositions in the context of this previous work. The Kimberly core sampled the Shoshone …

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Groundwater Flow Across The Coyote Wash Fault And Cedar Mesa Anticline Near St. Johns, Arizona, Stephanie Lynn Latour Aug 2023

Groundwater Flow Across The Coyote Wash Fault And Cedar Mesa Anticline Near St. Johns, Arizona, Stephanie Lynn Latour

Theses and Dissertations

As the demand for water increases across the southwestern United States, the region's utilization of and dependence on water stored in groundwater aquifers has risen in kind. The Coconino Aquifer (C-aquifer) underlies much of the southwestern Colorado Plateau and is a primary source of groundwater in northeastern Arizona. One of the largest commercial users of water from the C-aquifer in Apache County, Arizona, is Springerville Generating Station, a coal-fired power plant owned and operated by Tucson Electric Power. The area surrounding the power plant, located between the cities of Springerville and St. Johns, Arizona (the Springerville-St. Johns area), is geologically …

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The Student Becomes The Teacher: Training High-Performance Language Models More Sample-Efficiently From Small Models Via Superstilling, Chaz Allen Gundry Aug 2023

The Student Becomes The Teacher: Training High-Performance Language Models More Sample-Efficiently From Small Models Via Superstilling, Chaz Allen Gundry

Theses and Dissertations

Recent advances including the Transformer architecture have revolutionized the Natural Language Processing community by providing immense performance improvements across many tasks, including the development of Large Language Models (LLMs). LLMs show enormous promise as few-shot learners, common-sense knowledge repositories, conversational agents, writing assistants, and coding tools, and are gaining widespread traction in commercial industry. However, LLMs are expensive and time-consuming to train, requiring many passes over terabytes of data for the largest models. In this paper, we present Superstilling, a method for reducing the sample complexity of language model training by distilling the knowledge from a previously-trained model (the teacher) …

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Experimental Characterization Of Internal Wave Generation By Multiple Ridge Topographies, Natasha J. Wilson Aug 2023

Experimental Characterization Of Internal Wave Generation By Multiple Ridge Topographies, Natasha J. Wilson

Theses and Dissertations

Internal waves are three dimensional waves that occur in stratified fluids, where density increases with depth, such as the ocean and atmosphere. In the oceans, internal waves are continuously generated by tidal flow over subsea topography. The size and shape of the topography, as well as the stratification relative to the oscillation frequency influence the characteristics of the generated internal wave field. To advance the current understanding of how ridges on a subcritical topography changes the internal waves generated, four symmetric topographies are used with ridge numbers ranging from three to six. An additional single ridge topography is used, as …

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Deployable Mechanisms And Applications For Minimally Invasive Surgery, Jacob L. Sheffield Aug 2023

Deployable Mechanisms And Applications For Minimally Invasive Surgery, Jacob L. Sheffield

Theses and Dissertations

This thesis explores techniques to utilize deployable, developable, and compliant mechanism design principles while investigating applications for minimally invasive surgery. This work also examines contemporary outreach strategies to broaden awareness and expand dissemination avenues of engineering research. The outcomes of this research aim to (i) equip product designers with machine design tools, (ii) deliver background and designs to mitigate surgical frustration and procedure complications associated with obstructed laparoscope lenses during laparoscopic surgery, and (iii) provide engineering researchers with new tools to extend the impact of their research. Part one of this work (Chapter 2) introduces methods for embedding linear-motion mechanisms …

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Exploring New Horizons In Microwave-Promoted Iminyl Radical Chemistry And Synthesis Of Bulky Dehydroamino Acids, Jatinder Singh Aug 2023

Exploring New Horizons In Microwave-Promoted Iminyl Radical Chemistry And Synthesis Of Bulky Dehydroamino Acids, Jatinder Singh

Theses and Dissertations

The first project in this dissertation presents a simplified and efficient protocol for synthesizing pyrrolines through 5-exo iminyl radical cyclizations. The microwave irradiation of O-Phenyloximes tethered to alkenes causes N-O homolysis resulting in iminyl radical generation, which subsequently undergoes 5-exo-trig cyclizations furnishing pyrrolines. This eliminates the need for toxic radical initiators (AIBN, benzoyl peroxide), propagating agents (Bu3SnH, (Me3Si)3SiH), and expensive catalysts or single-electron transfer (SET) cycles. We explored the scope of diverse traps and substrates for iminyl radical cyclizations. The iminyl radical cyclizations formed versatile pyrrolines with moderate to excellent yields. The diastereoselectivity also ranged from low to high. Moreover, …

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Improving Xrd Analysis With Machine Learning, Rachel E. Drapeau Aug 2023

Improving Xrd Analysis With Machine Learning, Rachel E. Drapeau

Theses and Dissertations

X-ray diffraction analysis (XRD) is an inexpensive method to quantify the relative proportions of mineral phases in a rock or soil sample. However, the analytical software available for XRD requires extensive user input to choose phases to include in the analysis. Consequently, analysis accuracy depends greatly on the experience of the analyst, especially as the number of phases in a sample increases (Raven & Self, 2017; Omotoso, 2006). The purpose of this project is to test whether incorporating machine learning methods into XRD software can improve the accuracy of analyses by assisting in the phase-picking process. In order to provide …

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Lumbar Skin Strain Fields In The Context Of Skin Adhered Wearables, Andrew Kent Gibbons Aug 2023

Lumbar Skin Strain Fields In The Context Of Skin Adhered Wearables, Andrew Kent Gibbons

Theses and Dissertations

A comprehensive background is herein presented for lumbar skin strain and its effect on skin adhered wearable (SAW) products. A background of the development of computational models of the interaction of skin and novel SAWs being researched is also presented. These include products involving the use of high deflection strain gauges to measure skin strain during functional movements (FMs) as a method to address the complicated phenotyping of the etiological causes of low back pain (LBP). The background concludes with the mathematical calculation of the principal skin strain magnitudes and orientations using retroreflective marker coordinate data in a motion capture …

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Multilevel Mixture Irt Modeling For The Analysis Of Differential Item Functioning, Luke Dras Aug 2023

Multilevel Mixture Irt Modeling For The Analysis Of Differential Item Functioning, Luke Dras

Theses and Dissertations

A multilevel mixture IRT (MMixIRT) model for DIF analysis has been proposed as a solution to gain greater insight on the source of nuisance factors which reduce the reliability and validity of educational assessments. The purpose of this study was to investigate the efficacy of a MMix2PL model in detecting DIF across a broad set of conditions in hierarchically structured, dichotomous data. Monte Carlo simulation was performed to generate examinee response data with conditions common in the field of education. These include (a) two instrument lengths, (b) nine hierarchically structured sample sizes, (c) four latent class features, and (d) eight …

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Engagement In Secondary Mathematics Group Work: A Student Perspective, Rachel H. Jorgenson Aug 2023

Engagement In Secondary Mathematics Group Work: A Student Perspective, Rachel H. Jorgenson

Theses and Dissertations

In the realm of academic engagement research, students are valuable sources of information to learn how and why students often engage unproductively in mathematics group work. However, although secondary mathematics students are often expected to engage in meaningful mathematical discourse in a small group setting, little research has been conducted to better understand student engagement in this setting from the perspective of the students themselves. This thesis attempts to understand how one junior high student described his own engagement in mathematics small group work as well as what factors influenced this engagement. By conducting several cycles of observations and interviews …

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The Generalizability Of Proposed Theoretical Factor Models For Common Assessments For Specific Learning Disability In Reading Using A Community Sample, Sean B. Vanhille Aug 2023

The Generalizability Of Proposed Theoretical Factor Models For Common Assessments For Specific Learning Disability In Reading Using A Community Sample, Sean B. Vanhille

Theses and Dissertations

Specific learning disabilities (SLD) are among the most diagnosed developmental disorders in children, with specific learning disability in reading (SLDR) as the most common. SLDR typically occurs due to deficits in phonological processing that can negatively impact decoding and/or reading comprehension skills. Reading deficits are often diagnosed using formal assessments such as the Comprehensive Test of Phonological Processing (CTOPP-2), the Gray Oral Reading Test (GORT-5), the Wechsler Intelligence Scale for Children (WISC-V), and the Woodcock Johnson Achievement Battery (WJ-IV-A). I did not find any research in which the theoretical factor models proposed in the technical manuals of these assessments were …

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Parents' Perceptions Of The Importance Of Teaching Mathematics: A Q-Study, Ashlynn M. Holley Aug 2023

Parents' Perceptions Of The Importance Of Teaching Mathematics: A Q-Study, Ashlynn M. Holley

Theses and Dissertations

Mathematics education has gone through multiple reform efforts over the last century and continues to be the target of improvement efforts. Past changes in curriculum and goals have sometimes led to heated debates between various stakeholders. Knowing the views of different stakeholders can help determine what common ground there is between these different groups and where areas of disagreement might arise. Parents are especially important to understand because they have been influential in past reform efforts. Despite the importance of parents' opinions, little research has been conducted concerning their perspectives on the importance of mathematics teaching. Using Q-methodology, I was …

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Bidirectional Interference Between Speech And Mathematical, Language, Or Visuospatial Tasks In Younger And Older Adults, Chanelle Thomas Aug 2023

Bidirectional Interference Between Speech And Mathematical, Language, Or Visuospatial Tasks In Younger And Older Adults, Chanelle Thomas

Theses and Dissertations

This study examined interference between three non-speech tasks and concurrent speech performance. The non-speech activity consisted of computer-based mathematical, language, and visuospatial tasks. The speech tasks included a procedural discourse monologue and a conversation. Participants included 60 adults in two age groups with 30 participants each. The younger adults were aged from 18 to 30 years and older adults from 55 to 82 years. Each participant completed the non-speech tasks in isolation, the speech tasks in isolation, and then each of the speech tasks concurrently with each of the three non-speech tasks. Speech acoustic measures included the mean and standard …

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Physics-Guided Modeling Of Acoustic Environments Using Limited Spatio-Spectro-Temporal Data, Mylan Ray Cook Aug 2023

Physics-Guided Modeling Of Acoustic Environments Using Limited Spatio-Spectro-Temporal Data, Mylan Ray Cook

Theses and Dissertations

When creating data-based models it is important to include the underlying physical characteristics and constraints of the data. If physical characteristics are not properly included in the model, results may be infeasible or physically impossible. Acoustic environments are better characterized by ensuring that models include the fundamental spatial, spectral, and temporal characteristics of noise sources, or how they change based on location, frequency, and time. When model data are limited, in availability or in reliability, additional care must be taken to ensure models predict feasible results. This dissertation focuses on physics-guided modeling of acoustic environments using limited data, taking into …

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A Step Into Structural Biology: Structural Determination Of Tnk1-Uba And Computational Design Of A Radical Sam Cyclase, Yi-Jie Tseng Aug 2023

A Step Into Structural Biology: Structural Determination Of Tnk1-Uba And Computational Design Of A Radical Sam Cyclase, Yi-Jie Tseng

Theses and Dissertations

Structural biology uncovers life's secrets by studying protein structures via techniques like X-ray crystallography. This knowledge drives advancements in protein engineering for the improvement of human lives. Yet, obtaining high-quality crystals in X-ray crystallography is challenging. To overcome this, we used Translocation ETS Leukemia protein Sterile Alpha Motif domain (TELSAM), a promising polymer-forming crystallization chaperone (PFCC), to enhance protein crystallization. Human thirty-eight-negative kinase-1 (TNK1), a key player in cancer progression, possess a ubiquitin association (UBA) domain that binds polyubiquitin and regulates TNK1 activity and stability. Although sequence analysis hints at an unconventional TNK1 UBA domain architecture, its molecular structure lacks …

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Computational Modeling Of Energy Landscapes And Trajectory Studies Of Fundamental Organometallic Reactions, Joshua I. Wheeler Aug 2023

Computational Modeling Of Energy Landscapes And Trajectory Studies Of Fundamental Organometallic Reactions, Joshua I. Wheeler

Theses and Dissertations

Organometallic reactions are a fundamental class of chemical transformations. The mechanisms of organometallic reactions are routinely modeled by calculating intermediates and transition-state structures on a potential energy surface with density functional theory (DFT). The translation of these calculated structures to a reaction mechanism is typically done under the umbrella of statistical transition state theory. This dissertation reports the use of DFT calculations and quasiclassical direct dynamics trajectories to explore the possibility of nonstatistical dynamic effects in organometallic reactions. Chapter 1 provides a brief review of potential energy surfaces, transition state theory, dynamics trajectories, and a review of previous dynamics studies …

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More Is Better Than One: The Effect Of Ensembling On Deep Learning Performance In Biochemical Prediction Problems, Jacob A. Stern Aug 2023

More Is Better Than One: The Effect Of Ensembling On Deep Learning Performance In Biochemical Prediction Problems, Jacob A. Stern

Theses and Dissertations

This thesis presents two papers addressing important biochemical prediction challenges. The first paper focuses on accurate protein distance predictions and introduces updates to the ProSPr network. We evaluate its performance in the Critical Assessment of techniques for Protein Structure Prediction (CASP14) competition, investigating its accuracy dependence on sequence length and multiple sequence alignment depth. The ProSPr network, an ensemble of three convolutional neural networks (CNNs), demonstrates superior performance compared to individual networks. The second paper addresses the issue of accurate ligand ranking in virtual screening for drug discovery. We propose MILCDock, a machine learning consensus docking tool that leverages predictions …

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