Physical Sciences and Mathematics Commons^™

Deepsec: A Deep Learning Framework For Secreted Protein Discovery In Human Body Fluids, Dan Shao, Lan Huang, Yan Wang, Kai He, Xueteng Cui, Yao Wang, Qin Ma, Juan Cui

School of Computing: Faculty Publications

Motivation: Human proteins that are secreted into different body fluids from various cells and tissues can be promising disease indicators. Modern proteomics research empowered by both qualitative and quantitative profiling techniques has made great progress in protein discovery in various human fluids. However, due to the large number of proteins and diverse modifications present in the fluids, as well as the existing technical limits of major proteomics platforms (e.g. mass spectrometry), large discrepancies are often generated from different experimental studies. As a result, a comprehensive proteomics landscape across major human fluids are not well determined.

Results: To bridge …

Performance Of The Beta-Binomial Model For Clustered Binary Responses: Comparison With Generalized Estimating Equations, Seongah Im

Journal of Modern Applied Statistical Methods

This study examined performance of the beta-binomial model in comparison with GEE using clustered binary responses resulting in non-normal outcomes. Monte Carlo simulations were performed under varying intracluster correlations and sample sizes. The results showed that the beta-binomial model performed better for small sample, while GEE performed well under large sample.

Utilizing Patient-Derived Epithelial Ovarian Cancer Tumor Organoids To Predict Carboplatin Resistance, Justin W. Gorski, Zhuwei Zhang, J. Robert Mccorkle, Jodi M. Dejohn, Chi Wang, Rachel W. Miller, Holly H. Gallion, Charles S. Dietrich Iii, Frederick R. Ueland, Jill M. Kolesar

Obstetrics and Gynecology Faculty Publications

The development of patient-derived tumor organoids (TOs) from an epithelial ovarian cancer tumor obtained at the time of primary or interval debulking surgery has the potential to play an important role in precision medicine. Here, we utilized TOs to test front-line chemotherapy sensitivity and to investigate genomic drivers of carboplatin resistance. We developed six high-grade, serous epithelial ovarian cancer tumor organoid lines from tissue obtained during debulking surgery (two neoadjuvant-carboplatin-exposed and four chemo-naïve). Each organoid line was screened for sensitivity to carboplatin at four different doses (100, 10, 1, and 0.1 µM). Cell viability curves and resultant EC₅₀ values …

Automated Statistical Structural Testing Techniques And Applications, Yang Shi

Dissertations and Theses

Statistical structural testing(SST) is an effective testing technique that produces random test inputs from probability distributions. SST shows superiority in fault-revealing power over random testing and deterministic approaches since it heritages the merits from both of them. SST ensures testing thoroughness by setting up a probability lower-bound criterion for each structural cover element and test inputs that exercise a structural cover element sampled from the probability distribution, ensuring testing randomness. Despite the advantages, SST is not a widely used approach in practice. There are two major limitations. First, to construct probability distributions, a tester must understand the underlying software's structure, …

Space Science And Social Media: Automating Science Communication On Twitter, Maia Williams

Honors Projects

This project analyzes how social media is used to engage general audiences in astronomy and space science, as well as ways to improve engagement through automation. Tweets from five space science organizations were sampled. The engagement rate for each tweet was calculated from the number of interactions it received. Accounts that tweet more per day had more followers, and accounts with more followers received more interactions. This project also investigated how to build a Twitter bot to automate science communication. Using NASA Application Programming Interfaces, a Twitter bot was written in Python to tweet images taken by the NASA Mars …

Turn Of Phrase: Contrastive Pre-Training For Discourse-Aware Conversation Models, Roland Laboulaye

Theses and Dissertations

Understanding long conversations requires recognizing a discourse flow unique to conversation. Recent advances in unsupervised representation learning of text have been attained primarily through language modeling, which models discourse only implicitly and within a small window. These representations are in turn evaluated chiefly on sentence pair or paragraph-question pair benchmarks, which measure only local discourse coherence. In order to improve performance on discourse-reliant, long conversation tasks, we propose Turn-of-Phrase pre-training, an objective designed to encode long conversation discourse flow. We leverage tree-structured Reddit conversations in English to, relative to a chosen conversation path through the tree, select paths of varying …

Chagas Disease In Hiv-Infected Patients: It’S Time To Consider The Diagnosis, Melissa Nolan Ph.D., Mph, Natasha S. Hochberg

Faculty Publications

No abstract provided.

Bpsou Final Reclaimed Areas Maintenance And Monitoring Qapp - 2021, Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Extended Search For Supernovalike Neutrinos In Nova Coincident With Ligo/Virgo Detections, M. A. Acero, P. Adamson, L. Aliaga, N. Anfimov, A. Antoshkin, E. Arrieta-Diaz, L. Asquith, A. Aurisano, A. Back, C. Backhouse, M. Baird, N. Balashov, P. Baldi, B. A. Bambah, S. Bashar, K. Bays, R. Bernstein, V. Bhatnagar, B. Bhuyan, J. Bian, Roberto Petti, Et. Al.

Faculty Publications

A search is performed for supernovalike neutrino interactions coincident with 76 gravitational wave events detected by the LIGO/Virgo Collaboration. For 40 of these events, full readout of the time around the gravitational wave is available from the NOvA Far Detector. For these events, we set limits on the fluence of the sum of all neutrino flavors of F < 7(4) × 10¹⁰ cm⁻² at 90% C.L. assuming energy and time distributions corresponding to the Garching supernova models with masses 9.6ð27Þ M_^⊙. Under the hypothesis that any given gravitational wave event was caused by a supernova, this corresponds to a distance …

The Eco‐Integrity And Grassland Management — The Lessons From Biodiversity Conservation & Community Development In Imar, China, Weijie Deng

IGC Proceedings (1993-2023)

No abstract provided.

Rangeland Day As A Tool For Monitoring Propagation, M. Azimi, Mehdi Farahpour, M. Borhani, Hossein Arzani

IGC Proceedings (1993-2023)

No abstract provided.

Farmers' Perspectives On Local Feedstuffs And Introduced Forages: Case Study Of Four Villages In Northern Nigeria, G.-E. Akouègnon, Volker Hoffmann, R. Schultze‐Kraft

IGC Proceedings (1993-2023)

No abstract provided.

Nitrogen And Rainfall Effects On Crop Growth—Experimental Results And Scenario Analyses, Saadi Sattar Shahadha, Ole O. Wendroth, Dianyuan Ding

Plant and Soil Sciences Faculty Publications

Nitrogen (N) fertilization is critical for crop growth; however, its effect on crop growth and evapotranspiration (ETc) behaviors under different amounts of rainfall is not well understood. As such, there is a need for studying the impact of nitrogen application rates and rainfall amounts on crop growth and ETc components. Agricultural system models help to fill this knowledge gap, e.g., the Root Zone Water Quality Model (RZWQM2), which integrates crop growth-related processes. The objective of this study is to investigate the effect of the nitrogen application rate on crop growth, soil water dynamics, and ETc behavior under different rainfall amounts …

Providing Improved Livelihoods For Muskoka’S Stakeholders In The Time Of Two Global Crises, Andrew Court '22

Student Scholarship

Climate change and the coronavirus pandemic have drastically impacted the livelihoods of Muskoka’s stakeholders. Climate change has led to altered weather patterns and environments in Muskoka, which have negatively impacted stakeholders' (defined as permanent residents, seasonal residents and tourists) built infrastructure, mental and physical health, and these effects are only expected to worsen in the coming decades. Similarly, the coronavirus pandemic has caused many physical and mental health problems for Muskoka's stakeholders and has also led to tensions and anxieties regarding opinions about whether or not every stakeholder should be able to access the region during the pandemic. Although coronavirus …

Modeling Hyperpolarized Nmr Phenomena In Optically Pumped Semiconductors, Michael Eric West

Arts & Sciences Electronic Theses and Dissertations

Nuclear magnetic resonance (NMR) is a widely-used technique that measures the local environments of nuclei. It is able to detect small differences in energy, making it a highly-valued tool. However, the technique is challenged by inherently low sensitivities, requiring either large sample volumes or long periods of time to overcome this. In semiconductors, optical pumping (OP) can overcome this low sensitivity by creating incredibly large and dynamic nuclear spin polarizations (``hyperpolarization''), which is detectable as a large NMR signal. The combined technique of optically-pumped NMR (OPNMR) is a valuable tool that can explore electronic and nuclear phenomena within semiconductors. In …

Smooth Ica Under Time Pattern Assumptions, Jiayi Fu

Arts & Sciences Electronic Theses and Dissertations

Independent component analysis (ICA) is wildly used in differently areas. As traditional ICA models make no assumptions on time pattern, they do not take time domain information into consideration. In this thesis, we introduced new assumptions that allow local dependence over time, and we built smooth ICA models to utilize the smoothness information for sources signals. Based on the local dependence assumptions, constrained optimization problems with smoothing penalty were discussed. Then we introduced smooth ICA estimators and estimating equations. Under local dependence assumptions, we gave proofs about the consistency and asymptotic normality of these estimators. We derived the Newton iterative …

Method Development For Enhancing Sensitivity Of Dynamic Nuclear Polarization Nuclear Magnetic Resonance Spectroscopy For Structural Studies Of Pkc-Drug Interactions, Patrick Terrence Judge

Arts & Sciences Electronic Theses and Dissertations

To perform the most relevant structural studies on biological systems, experiments need to be carried out when the target proteins are in their endogenous cellular environment. Nuclear magnetic resonance (NMR) is well-suited to probe the structure and dynamics of a wide variety of systems, including biologically relevant proteins. However, NMR suffers from an inherent lack of sensitivity. Dynamic nuclear polarization (DNP) NMR is a powerful technique that is used to enhance NMR sensitivity by transferring the greater polarization of exogenously doped electron spins to nuclear spins of interest though the use of a high-power microwave source. Solid effect radicals offer …

Stratigraphic Evidence Of Two Historical Tsunamis On The Semi-Arid Coast Of North-Central Chile, Jessica M. Depaolis, Tina Dura, Breanyn Macinnes, Lisa L. Ely, Marco Cisternas, Matías Carvajal, Hui Tang, Hermann M. Fritz, Cyntia Mizobe, Robert L. Wesson, Gino Figueroa, Nicole Brennan, Benjamin P. Horton, Jessica E. Pilarczyk, D. Reide Corbett, Benjamin C. Gill, Robert Weiss

Geological Sciences Faculty Scholarship

On September 16, 2015, a M_w 8.3 earthquake struck the north-central Chile coast, triggering a tsunami observed along 500 km of coastline, between Huasco (28.5°S) and San Antonio (33.5°S). This tsunami provided a unique opportunity to examine the nature of tsunami deposits in a semi-arid, siliciclastic environment where stratigraphic and sedimentological records of past tsunamis are difficult to distinguish. To improve our ability to identify such evidence, we targeted one of the few low-energy, organic-rich depositional environments in north-central Chile: Pachingo marsh in Tongoy Bay (30.3°S).

We found sedimentary evidence of the 2015 and one previous tsunami as tabular …

Community Detection In Complex Networks, Zhenqi Lu

McKelvey School of Engineering Theses & Dissertations

Network science plays a central role in understanding and modeling complex systems in many disciplines, including physics, sociology, biology, computer science, economics, politics, and neuroscience. By studying networks, we can gain a deep understanding of the behavior of the systems they represent. Many networks exhibit community structure, i.e., they have clusters of nodes that are locally densely interconnected. These communities manifest the hierarchical organization of the objects in systems, and detecting communities greatly facilitates the study of the organization and structure of complex systems.

Most existing community-detection methods consider low-order connection patterns, at the level of individual links. But high-order …

Non-Hermitian Physics And Engineering In Whispering Gallery Mode Microresonators, Changqing Wang

McKelvey School of Engineering Theses & Dissertations

Non-Hermitian physics describes the behaviors of open systems which have interactions with the environment. It can be applied to a wide range of classical and quantum systems. Exotic physical phenomena are unveiled in such non-Hermitian systems, especially around a singular point in the parameter space, i.e., the exceptional point (EP), where the eigenvalues and the associated eigenvectors are degenerate. A plethora of demonstrations have been found in optics and photonics, where the non-Hermitian effects are ubiquitous due to the existence of optical dissipation or amplification. In particular, whispering gallery mode (WGM) resonators are ideal candidates for studying light-matter interactions in …

Neural Representation In The Primary Visual Cortex Amid High Neural Variability, Ji Xia

Arts & Sciences Electronic Theses and Dissertations

Animals process high-dimensional sensory information constantly. How does neural activityin sensory cortices represent this information? Recent advances in large-scale recordings allow us to monitor activity of hundreds or thousands of neurons simultaneously across a long period of time. Population recordings showed that cortical neuronal responses to repeated sensory stimulation is highly variable from trial to trial. However, how neurons in neocortex represent sensory information amid high neural variability is not well understood. To answer this question, we used two-photon calcium imaging to record from hundreds of excitatory neurons simultaneously from mouse primary visual cortex. We analyzed neural responses to repeated …

Photoacoustic Imaging, Feature Extraction, And Machine Learning Implementation For Ovarian And Colorectal Cancer Diagnosis, Eghbal Amidi

McKelvey School of Engineering Theses & Dissertations

Among all cancers related to women’s reproductive systems, ovarian cancer has the highest mortality rate. Pelvic examination, transvaginal ultrasound (TVUS), and blood testing for cancer antigen 125 (CA-125), are the conventional screening tools for ovarian cancer, but they offer very low specificity. Other tools, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), also have limitations in detecting small lesions. In the USA, considering men and women separately, colorectal cancer is the third most common cause of death related to cancer; for men and women combined, it is the second leading cause of cancer deaths. …

Continuous-Time And Complex Growth Transforms For Analog Computing And Optimization, Oindrila Chatterjee

McKelvey School of Engineering Theses & Dissertations

Analog computing is a promising and practical candidate for solving complex computational problems involving algebraic and differential equations. At the fundamental level, an analog computing framework can be viewed as a dynamical system that evolves following fundamental physical principles, like energy minimization, to solve a computing task. Additionally, conservation laws, such as conservation of charge, energy, or mass, provide a natural way to couple and constrain spatially separated variables. Taking a cue from these observations, in this dissertation, I have explored a novel dynamical system-based computing framework that exploits naturally occurring analog conservation constraints to solve a variety of optimization …

A Neuromorphic Machine Learning Framework Based On The Growth Transform Dynamical System, Ahana Gangopadhyay

McKelvey School of Engineering Theses & Dissertations

As computation increasingly moves from the cloud to the source of data collection, there is a growing demand for specialized machine learning algorithms that can perform learning and inference at the edge in energy and resource-constrained environments. In this regard, we can take inspiration from small biological systems like insect brains that exhibit high energy-efficiency within a small form-factor, and show superior cognitive performance using fewer, coarser neural operations (action potentials or spikes) than the high-precision floating-point operations used in deep learning platforms. Attempts at bridging this gap using neuromorphic hardware has produced silicon brains that are orders of magnitude …

Algebraic, Computational, And Data-Driven Methods For Control-Theoretic Analysis And Learning Of Ensemble Systems, Wei Miao

McKelvey School of Engineering Theses & Dissertations

In this thesis, we study a class of problems involving a population of dynamical systems under a common control signal, namely, ensemble systems, through both control-theoretic and data-driven perspectives. These problems are stemmed from the growing need to understand and manipulate large collections of dynamical systems in emerging scientific areas such as quantum control, neuroscience, and magnetic resonance imaging. We examine fundamental control-theoretic properties such as ensemble controllability of ensemble systems and ensemble reachability of ensemble states, and propose ensemble control design approaches to devise control signals that steer ensemble systems to desired profiles. We show that these control-theoretic properties …

Association Of Structural Variation (Sv) With Cardiometabolic Traits In Finns, Lei Chen

Arts & Sciences Electronic Theses and Dissertations

Cardiovascular diseases (CVDs) are known to be associated with a variety of quantitative risk factors such as cholesterol, metabolites, and insulin. Understanding the genetic basis of these quantitative traits can shed light on the etiology, prevention, diagnosis, and treatment of disease. However most prior trait-mapping studies have focused on single nucleotide variants (SNVs) and Indels, with the contribution of structural variation (SV) remaining unknown. In this thesis, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. In the first chapter, we used sensitive methods to identify and genotype 129,166 high-confidence …

Computational Approaches For Screening Drugs For Bioactivation, Reactive Metabolite Formation, And Toxicity, Noah Flynn

Arts & Sciences Electronic Theses and Dissertations

Cytochrome P450 enzymes aid in the elimination of a preponderance of small molecule drugs, but can generate reactive metabolites that may adversely conjugate to protein and DNA, in a process known as bioactivation, and prompt adverse reaction, drug candidate attrition, or market withdrawal. Experimental assays are low-throughput and expensive to perform, so they are often reserved until later stages of the drug development pipeline when the drug candidate pools are already significantly narrowed. Reactive metabolites also elude in vivo detection, as they are transitory and generally do not circulate. In contrast, computational methods are high-throughput and cheap to screen millions …

Electronic, Optical, And Magnetic Properties Of Novel Two-Dimensional Materials, Xiaobo Lu

Arts & Sciences Electronic Theses and Dissertations

The field of two-dimensional(2D) materials is experiencing rapid growth and attracting tremendous research interests within the condensed matter community due to its ultimate thickness dimension and unique physical properties. The consistently emerging novel 2D materials not only provide extraordinary intrinsic properties of their single layer and multi- layer structures but also exhibit fascinating responses to the tunable external conditions. The fertile contents and boundless possibilities of novel 2D materials make it one of the pivots of modern nanotechnology towards deepening the physics understanding and promising practical applications.

In the first part of the thesis, we reveal the distinct Stark effects …

Market Making In A Limit Order Book: Classical Optimal Control And Reinforcement Learning Approaches, Chuyi Yu

Arts & Sciences Electronic Theses and Dissertations

Since the last decade, algorithmic trading has become one of the most significant developments in electronic security markets. Several types of problems and practices have been studied such as optimal execution, market making, statistical arbitrage, latency arbitrage, and so on. Among these, high-frequency market making plays a crucial role since it provides large liquidity to the market, which makes trading and investing cheaper for other market participants, and also creates sizable profits for high-frequency market makers (HFM) from the large quantity of round-trip executions involved in such practices. In this thesis, we discuss two approaches to solve the high-frequency market …

Enantioselective Synthesis Of Β-Amino Acid Derivatives Using Amidine-Based And Bifunctional Organocatalysts, Matthew Robert Straub

Arts & Sciences Electronic Theses and Dissertations

Two new enantioselective methodologies have been developed that have important implications for the asymmetric synthesis of β-amino acids and their derivatives. First, chiral amidine-based catalyst (ABC) HBTM-2 catalyzed an asymmetric cyclocondensation between in situ activated fluoroacetic acid and N-sulfonyl aldimines to give α-fluoro-β-lactams in highly enantioenriched form, achieving modest to excellent diastereoselectivities. These reactive lactams can then be quenched with various alcohols and amines to deliver the α-fluoro-β-amino acid derivatives in moderate isolated yields. Secondly, bifunctional double hydrogen bond donor-amine organocatalysts enable the catalytic alcoholysis of various racemic N-carbalkoxy-3-substituted isoxazolidin-5-ones, resulting in their kinetic resolution. The enantioenriched unreacted isoxazolidinone and …