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Articles 1 - 11 of 11
Full-Text Articles in Physical Sciences and Mathematics
Multifunctional And Moisture Tolerant Zinc-Based Mono- And Bi-Metallic Metal-Organic Framework (Mof) Thin Films, Emmanuel Agbata
Multifunctional And Moisture Tolerant Zinc-Based Mono- And Bi-Metallic Metal-Organic Framework (Mof) Thin Films, Emmanuel Agbata
Theses and Dissertations
Many applications of metal-organic frameworks (MOFs) are highly dependent on their structures. The type and consistency of structure inform their properties. Zinc-based MOFs are applicable in different fields because of the low toxicity of zinc materials and are therefore also useful for catalysis. While MOF-5, a zinc-based MOF with carboxylate linkers is moisture intolerant, a variant of this is moisture tolerant. The introduction of a nitrogen-based linker in the zinc MOF which renders the structure moisture-tolerant. This material has not been explored as much, despite its multifunctional properties. Furthermore, the growth of Zn-based bimetallics of this MOF has not yet …
The Generation Of Terahertz Light And Its Applications In The Study Of Vibrational Motion, Aldair Alejandro
The Generation Of Terahertz Light And Its Applications In The Study Of Vibrational Motion, Aldair Alejandro
Theses and Dissertations
Terahertz (THz) spectroscopy is a powerful tool that uses ultrashort pulses of light to study the properties of materials on picosecond time scales. THz light can be generated through a variety of methods. In our lab, we generate THz through the process of optical rectification in nonlinear optical (NLO) organic crystals. THz light can be used to study several phenomena in materials, such as spin precession, electron acceleration, vibrational and rotational motion. The work presented in this dissertation is divided into two parts: (1) the generation of THz light and (2) applications of THz light. The first portion of this …
Applying Mathematical Modeling To The Study Of Family Systems, Dahlia Maxwell
Applying Mathematical Modeling To The Study Of Family Systems, Dahlia Maxwell
Theses and Dissertations
Mathematical modeling provides a powerful framework for insight into current scientific theories as well as hypothesis generation for further research. Despite its undeniable potential to enrich scientific advancement, the application of mathematical modeling remains conspicuously scarce in the field of family science. The complexity inherent in family dynamics, coupled with the intricate interplay of emotions in the individual, underscores the necessity of a robust analytical approach. Addressing this critical gap in the literature, this thesis introduces a sophisticated mathematical model of family dynamics integrating essential elements from family systems theory, emotion dynamics, and appraisal theory. The model is implemented as …
Advancing Single-Cell Proteomics Through Innovations In Liquid Chromatography And Mass Spectrometry, Kei Grant Isaac Webber
Advancing Single-Cell Proteomics Through Innovations In Liquid Chromatography And Mass Spectrometry, Kei Grant Isaac Webber
Theses and Dissertations
Traditional proteomics studies can measure many protein biomarkers simultaneously from a single patient-derived sample, promising the possibility of syndromic diagnoses of multiple diseases sharing common symptoms. However, precious cellular-level information is lost in conventional bulk-scale studies that measure tissues comprising many types of cells. As single cells are the building blocks of organisms and are easier to biopsy than traditional bulk samples, performing proteomics on a single-cell level would benefit clinicians and patients. Single-cell proteomics, combined with mass spectrometry imaging, can be used to analyze cells in their microenvironment, preserving spatial information. We have previously used laser-capture microdissection to isolate …
Robot Proficiency Self-Assessment Using Assumption-Alignment Tracking, Xuan Cao
Robot Proficiency Self-Assessment Using Assumption-Alignment Tracking, Xuan Cao
Theses and Dissertations
A robot is proficient if its performance for its task(s) satisfies a specific standard. While the design of autonomous robots often emphasizes such proficiency, another important attribute of autonomous robot systems is their ability to evaluate their own proficiency. A robot should be able to conduct proficiency self-assessment (PSA), i.e. assess how well it can perform a task before, during, and after it has attempted the task. We propose the assumption-alignment tracking (AAT) method, which provides time-indexed assessments of the veracity of robot generators' assumptions, for designing autonomous robots that can effectively evaluate their own performance. AAT can be considered …
N-H Nhc Palladium Catalysts Derived From Unique 2-Phosphinoimidazole Precursors For C-C Cross Coupling Reactions And Application Of Slow Releasing Polymers Impregnated With Gibberellic Acid To Overcome Seed Dormancy For Land Reclamation, Alexandra Jean Setelin Larson
N-H Nhc Palladium Catalysts Derived From Unique 2-Phosphinoimidazole Precursors For C-C Cross Coupling Reactions And Application Of Slow Releasing Polymers Impregnated With Gibberellic Acid To Overcome Seed Dormancy For Land Reclamation, Alexandra Jean Setelin Larson
Theses and Dissertations
Organometallic chemistry is highly dependent upon the ligands which are employed on a metal's surface. These ligands control steric bulk and electronics of the metal center which can change the reactivity of the organometallic complex. Ligands that are standard in organometallic chemistry include phosphine ligands. These phosphine ligands have been utilized in the field since the 1960's and have shaped the development of many key organometallic catalysts. Phosphine ligands are easily functionalized and highly reactive. This increased reactivity, however, causes severe limitations as phosphine ligands are often unstable under standard benchtop conditions and must be handled both air and moisture …
Gt-Ches And Dycon: Improved Classification For Human Evolutionary Systems, Joseph S. Johnson
Gt-Ches And Dycon: Improved Classification For Human Evolutionary Systems, Joseph S. Johnson
Theses and Dissertations
The purpose of this work is to rethink the process of learning in human evolutionary systems. We take a sober look at how game theory, network theory, and chaos theory pertain specifically to the modeling, data, and training components of generalization in human systems. The value of our research is three-fold. First, our work is a direct approach to align machine learning generalization with core behavioral theories. We made our best effort to directly reconcile the axioms of these heretofore incompatible disciplines -- rather than moving from AI/ML towards the behavioral theories while building exclusively on AI/ML intuition. Second, this …
Development Of Bifunctional Peptides As Scaffolds For Bifunctional Catalysis And A Novel Method Of Peptide Stapling Using Squaric Esters, Adam X. Wayment
Development Of Bifunctional Peptides As Scaffolds For Bifunctional Catalysis And A Novel Method Of Peptide Stapling Using Squaric Esters, Adam X. Wayment
Theses and Dissertations
Enzymes are some of nature's most powerful tools in chemical processes. However, their molecular complexity makes them difficult to synthesize and complicates their application in traditional organic synthesis. Peptides, a building block of enzymes, can be rapidly synthesized and have been used as a possible alternative in achieving enzyme-like catalysis. However, most peptide-based catalysts are limited in reaction-scope and are unable to incorporate traditional organic catalysts. We have designed a helical peptide scaffold capable of being functionalized with a wide variety of organocatalysts as well as transition-metal based catalysts. In order to understand how the peptide structure effects reactivity and …
New Mathematics Teachers' Goals, Orientations, And Resources That Influence Implementation Of Principles Learned In Brigham Young University's Teacher Preparation Program, Caroline S. Gneiting
New Mathematics Teachers' Goals, Orientations, And Resources That Influence Implementation Of Principles Learned In Brigham Young University's Teacher Preparation Program, Caroline S. Gneiting
Theses and Dissertations
Research in mathematics education shows that new mathematics teachers struggle to implement reform teaching practices that they learned in their teacher preparation programs. In this study, the researcher observed and interviewed three new mathematics teachers (within five years of graduation) to further explore the question of why new teachers use or do not use what they learned in their teacher preparation program. The study uses an expanded version of Schoenfeld's decision-making theory of Orientations, Goals, and Resources. This theory proved useful in the analysis of the research data, providing a framework to incorporate and organize the numerous reasons suggested by …
Usability-Driven Security Enhancements In Person-To-Person Communication, Tarun Kumar Yadav
Usability-Driven Security Enhancements In Person-To-Person Communication, Tarun Kumar Yadav
Theses and Dissertations
In the contemporary digital landscape, ensuring secure communication amid widespread data exchange is imperative. This dissertation focuses on enhancing the security and privacy of end-to-end encryption (E2EE) applications while maintaining or improving usability. The dissertation first investigates and proposes improvements in two areas of existing E2EE applications: countering man-in-the-middle and impersonation attacks through automated key verification and studying user perceptions of cryptographic deniability. Insights from privacy-conscious users reveal concerns about the lack of E2EE support, app siloing, and data accessibility by client apps. To address these issues, we propose an innovative user-controlled encryption system, enabling encryption before data reaches the …
Open System Neural Networks, Bradley Hatch
Open System Neural Networks, Bradley Hatch
Theses and Dissertations
Recent advances in self-supervised learning have made it possible to reuse information-rich models that have been generally pre-trained on massive amounts of data for other downstream tasks. But the pre-training process can be drastically different from the fine-tuning training process, which can lead to inefficient learning. We address this disconnect in training dynamics by structuring the learning process like an open system in thermodynamics. Open systems can achieve a steady state when low-entropy inputs are converted to high-entropy outputs. We modify the the model and the learning process to mimic this behavior, and attend more to elements of the input …