Physical Sciences and Mathematics Commons^™

Statistical Inference On Lung Cancer Screening Using The National Lung Screening Trial Data., Farhin Rahman

Electronic Theses and Dissertations

This dissertation consists of three research projects on cancer screening probability modeling. In these projects, the three key modeling parameters (sensitivity, sojourn time, transition density) for cancer screening were estimated, along with the long-term outcomes (including overdiagnosis as one outcome), the optimal screening time/age, the lead time distribution, and the probability of overdiagnosis at the future screening time were simulated to provide a statistical perspective on the effectiveness of cancer screening programs. In the first part of this dissertation, a statistical inference was conducted for male and female smokers using the National Lung Screening Trial (NLST) chest X-ray data. A …

Urban Vulnerability Analysis Based On Micro-Geographic Unit With Multi-Source Data—Case Study In Urumqi, Xinjiang, China, Jianghua Zheng, Danlin Yu, Chuqiao Han, Zhe Wang

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

This study introduces a novel approach to urban public safety analysis inspired by a streetscape analysis commonly applied in urban criminology, leveraging the concept of micro-geographical units to account for urban spatial heterogeneity. Recognizing the intrinsic uniformity within these smaller, distinct environments of a city, the methodology represents a shift from large-scale regional studies to a more localized and precise exploration of urban vulnerability. The research objectives focus on three key aspects: first, establishing a framework for identifying and dividing cities into micro-geographical units; second, determining the type and nature of data that effectively illustrate the potential vulnerability of these …

Iowa Waste Reduction Center Newsletter, August 2023, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Contents:

--- STAR4D at the Iowa State Fair
--- Farewell to Our Interns
--- Reminder: Iowa Recycling and Solid Waste Management Conference
--- Free Energy Assessments
--- Industry News

Causal Inference And Machine Learning Methods In Parkinson's Disease Data Analysis, Albert Pierce

Computational and Data Sciences (PhD) Dissertations

This dissertation documents an investigation into Parkinson’s Disease utilizing machine learning and causal inference methods. I will cover a descriptive analysis of Parkinson’s Disease (PD) in a vast, high-quality database and present costs associated with Parkinson’s Disease medications. I also researched a causal inference method assessing the Carbidopa-Levodopa effect on two-year survival and a causal survival analysis on a one-to-five-year survival comparing no drug use and Carbidopa-Levodopa in Parkinson’s Disease patients.

For my classification with Parkinson’s gait, patients were monitored with a smartphone and an additional 6 Inertial Measurement Unit (IMU) sensors to collect clinical gait measures. I used classical …

Application Of Machine Learning Algorithms For Elucidation Of Biological Networks From Time Series Gene Expression Data, Krupa Nagori

Computational and Data Sciences (PhD) Dissertations

This dissertation provides a deep dive into understanding gene expression, interaction, regulation, and the intricate mechanisms behind heliotropism and phototropism. Additionally, the research accentuates the significance of machine learning techniques, specifically for gene regulatory networks (GRNs).

Chapter 1 offers an exhaustive benchmarking of GRN methodologies, furthering our comprehension of machine-learning models relevant to GRNs. The evaluation revealed that GRNTE, SWING, and BiXGBoost emerged as top-performing methods in GRN inference. The suitability of these models varies depending on specific research criteria such as computational needs, dataset dimensions, and performance metric emphasis. An innovation of this chapter was the introduction of Colab …

Optimal Control Frameworks For Modeling Dynamics And Androgen Deprivation Therapies In Prostate Cancer, Hussein Ed Duweh

Mathematics Dissertations - Archive

In this work, we present an optimal control approach for the assessment of treatments in prostate cancer. For this purpose, we use two different approaches, based on differential equations, to model the dynamics of prostate cancer. For the first approach, we use a system of ordinary differential equations (ODE) that model androgen-dependent and independent prostate cancer cell mechanisms. Given some synthetic patient data, we then performed a parameter estimation process by formulating an optimization problem to obtain the coefficients in this model. A second optimal control problem was formulated to obtain optimal androgen suppression therapies. A theoretical analysis of both …

Understanding The Role Of Interactivity And Explanation In Adaptive Experiences, Lijie Guo

All Dissertations

Adaptive experiences have been an active area of research in the past few decades, accompanied by advances in technology such as machine learning and artificial intelligence. Whether the currently ongoing research on adaptive experiences has focused on personalization algorithms, explainability, user engagement, or privacy and security, there is growing interest and resources in developing and improving these research focuses. Even though the research on adaptive experiences has been dynamic and rapidly evolving, achieving a high level of user engagement in adaptive experiences remains a challenge. %????? This dissertation aims to uncover ways to engage users in adaptive experiences by incorporating …

Hybridly Integrated Semiconductor Lasers And Amplifiers On Iii-V/Si3n4 Platform For Beam Combining And Other Advanced Applications, Siwei Zeng

All Dissertations

Photonic integrated circuits (PICs) are devices that integrate multiple photonic functions on a small chip and allow for accurate dimension control and massive production. Similar to electronic integrated circuits, PICs can significantly reduce the system cost, size, weight, and operation power (CSWaP). Recently, the PIC technology has transformed many optical technologies which traditionally rely on tabletop systems and bulky components, such as optical interconnects, nonlinear optics, and quantum photonics, into a chip-scale platform. This device and system miniaturization has successfully led to a wide range of practical applications in computing, sensing, spectroscopy, and communication. However, the traditional passive PIC platform …

Liquid Flow And Gas Diffusion In Natural Rocks: Experimental And Simulation Studies, Xuewei Ning

Earth & Environmental Sciences Dissertations - Archive

Natural rocks, as key components in energy and environmental geosciences, play crucial roles in groundwater extraction, geological storage of high-level nuclear waste, geothermal energy mining, and petroleum exploration in both conventional and unconventional reservoirs. Unconventional reservoirs, specifically the tight shale formations, have seen a significant usage in petroleum production in recent decades, largely due to advances in fracturing stimulation techniques which counter the inherently low permeability and connectivity of shale reservoirs by expanding natural fractures and creating artificial ones for an enhanced petroleum production. However, the low mobility (liquid flow and gas diffusion) of stored fluids in naturally fractured formations …

Identification Of Acidic Residues In Proteins By Selective Chemical Labeling And Tandem Mass Spectrometry, Fnu Ashima

Chemistry & Biochemistry Theses - Archive

Proteins play important role in carrying out a wide range of cellular activities. They are subjected to various post-translational modifications (PTMs) by the addition of functional groups such as acetyl, phosphoryl, and methyl which leads to changes in their biological functions, localization, activity, and structure. The growth of MS technology has immensely facilitated the identification of PTMs comprehensively. This dissertation focuses on mapping these changes using covalent labeling techniques by tagging carboxylic acid residues, which undergo various kinds of PTMs. The second chapter focuses on the methods designed for Affinity Purification Mass Spectrometry (AP-MS) chemical cross-linking (CXL) of protein complexes. …

Modelling Galaxy Cluster Triaxiality In Stacked Cluster Weak Lensing Analyses, Hao-Yi Wu

Physics Faculty Publications and Presentations

Counts of galaxy clusters offer a high-precision probe of cosmology, but control of systematic errors will determine the accuracy of this measurement. Using Buzzard simulations, we quantify one such systematic, the triaxiality distribution of clusters identified with the redMaPPer optical cluster finding algorithm, which was used in the Dark Energy Survey Year-1 (DES Y1) cluster cosmology analysis. We test whether redMaPPer selection biases the clusters’ shape and orientation and find that it only biases orientation, preferentially selecting clusters with their major axes oriented along the line of sight. Modelling the richness–mass relation as log-linear, we find that the log-richness amplitude …

Modulation Of Voltage-Gating And Hysteresis Of Lysenin Channels By Cu2+ Ions, Andrew Bogard, Pangaea W. Finn, Aviana R. Smith, Ilinca M. Flacau, Rose Whiting, Daniel Fologea

Physics Faculty Publications and Presentations

The intricate voltage regulation presented by lysenin channels reconstituted in artificial lipid membranes leads to a strong hysteresis in conductance, bistability, and memory. Prior investigations on lysenin channels indicate that the hysteresis is modulated by multivalent cations which are also capable of eliciting single-step conformational changes and transitions to stable closed or sub-conducting states. However, the influence on voltage regulation of Cu²⁺ ions, capable of completely closing the lysenin channels in a two-step process, was not sufficiently addressed. In this respect, we employed electrophysiology approaches to investigate the response of lysenin channels to variable voltage stimuli in the presence …

Towards Nuclei Segmentation With Limited Annotations, Mohammad Minhazul Haq

Computer Science and Engineering Dissertations - Archive

Nuclei segmentation is a fundamental but challenging task in histopathology image analysis. For semantic segmentation of nuclei, Convolutional Neural Network (CNN), and Vision Transformer (VT) models give very promising results. However, to successfully train fully-supervised CNN and VT models we need significant amount of annotated data which is highly rare in biomedical domain. Also, collecting an unannotated histopathology dataset first, and then manually doing pixel-level labeling is expensive, time-consuming and tedious process. Therefore, we require to discover a way for training nuclei segmentation models with unlabeled datasets. In this thesis, I present my work towards solving this critical problem by …

Investigating The Effect Of Peephole Optimizations On Binary Code Differences, Xiaolei Ren

Computer Science and Engineering Dissertations - Archive

ABSTRACT: Binary diffing is a technique used to compare and identify differences or similarities in executable files without access to source code. The potential applications of binary diffing in various software security tasks, such as vulnerability search, code clone detection, and malware analysis, have generated a vast body of literature in recent years. One of the recurring themes in binary diffing research is the evaluation of its resilience against the impact of compiler optimization, which is the most common source of syntactic differences in binary code. Despite that most binary diffing tools claim that they are immune to compiler optimization, …

On-Line Environment Adaptation For User Performance Optimization, Subharag Sarkar

Computer Science and Engineering Dissertations - Archive

In today’s fast-paced and globally connected world, businesses are creating products with more significance to user personalization and customization. This has amplified the importance of capturing and learning user preferences as more information from users can lead to the designing and development of products that will improve user engagement and performance. Numerous algorithms based on collaborative filtering and recommender systems have been used to learn user preferences, but almost all of them require big datasets to train on. This creates a dependency on collecting more and more user information which might lead to ethical considerations and privacy concerns. To solve …

Self-Calibrating Optical Galaxy Cluster Selection Bias Using Cluster, Galaxy, And Shear Cross-Correlations, Chenxiao Zeng, Andrés N. Salcedo, Hao-Yi Wu, Christopher M. Hirata

Physics Faculty Publications and Presentations

The clustering signals of galaxy clusters are powerful tools for self-calibrating the mass–observable relation and are complementary to cluster abundance and lensing. In this work, we explore the possibility of combining three correlation functions – cluster lensing, the cluster–galaxy cross-correlation function, and the galaxy autocorrelation function – to self-calibrate optical cluster selection bias, the boosted clustering and lensing signals in a richness-selected sample mainly caused by projection effects. We develop mock catalogues of redMaGiC-like galaxies and redMaPPer-like clusters by applying halo occupation distribution models to N-body simulations and using counts-in-cylinders around massive haloes as a richness proxy. In addition …

The Temporal Evolution Of Subduction Initiation In The Samail Ophiolite: High-Precision U–Pb Zircon Petrochronology Of The Metamorphic Sole, Matthew Rioux, Joshua M. Garber, Michael Searle, James L. Crowley, Sally Stevens, Mark Schmitz, Andrew Kylander-Clark, Kayla Leal, Tyler Ambrose, Andrew J. Smye

Geosciences Faculty Publications and Presentations

High-precision dating of the metamorphic sole of ophiolites can provide insight into the tectonic evolution of ophiolites and subduction zone processes. To understand subduction initiation beneath a young, well-preserved and well-characterized ophiolite, we performed coupled zircon laser-ablation inductively coupled mass spectrometry trace element analyses and high-precision isotope dilution-thermal ionization mass spectrometry U–Pb dating on 25 samples from the metamorphic sole of the Samail ophiolite (Oman-United Arab Emirates). Zircon grains from amphibolite- to granulite-facies (0.8–1.3 GPa, ~700–900°C), garnet- and clinopyroxene-bearing amphibolite samples (n = 18) show systematic trends of decreasing heavy rare earth element slope (HREE; Yb/Dy) with decreasing Yb …

Uav-Based Quantification Of Dynamic Lahar Channel Morphology At Volcán De Fuego, Guatemala, Jerry C. Mock, Jeffrey B. Johnson, Armando Pineda, Gustavo Bejar, Amilcar Roca

Geosciences Faculty Publications and Presentations

This study quantified erosional and depositional processes for secondary lahars in Las Lajas drainage at Volcán de Fuego, Guatemala, during the rainy season from May to October 2021. Abundant pyroclastic material from ongoing eruptive activity is remobilized seasonally during heavy precipitation, which can impact infrastructure and populations living near Fuego. Our region of focus was in an agricultural zone 6 to 10 km from the summit, surveyed with an unoccupied aerial vehicle (UAV) quadcopter at monthly intervals. Imagery was processed into overlapping time-lapse structure from motion digital elevation models (DEMs). DEMs were differenced to find volumetric changes as a function …

Spectroscopy Of Highly Charged Ions For Astrophysical And Laboratory Plasma Diagnostics, Yang Yang

All Dissertations

Electron beam ion traps (EBITs) are small-scale laboratory devices that create and trap highly charged ions (HCI) for spectroscopic studies. These devices create plasma conditions resembling astrophysical environments like stellar winds and supernova remnants, providing valuable insights into astrophysical plasma. Theoretical models for such systems require incorporating relativistic and quantum electrodynamics effects, making experimental studies of HCIs essential for benchmarking these theories.

Spectral analysis of astrophysical and laboratory plasma requires understanding the ionization balance. Accurate atomic data, including excitation, ionization, and recombination cross sections, along with precise knowledge of operating conditions such as electron beam density, electron beam energy, and …

Inkjet-Printed Electrochemical Sensors For Lead Detection, Annatoma Arif

Open Access Theses & Dissertations

This PhD dissertation research has developed a simple, miniaturized, sensitive, selective, reproducible, and disposable 3D (inkjet printed – additive manufacturing technology) gold (Au) plated electrochemical sensor (ECS) on shape memory polymer (SMP) for aqueous lead detection. This technology has shown promising performance in the application of electrochemical sensing (lead (II) detection) due to increased effective electrode surface area (7.25 mm^2 ± 0.15 mm^2) despite miniaturizing lateral surface area (4.19 mm^2). The design, fabrication processes, optimization including bismuth functionalization, evaluation, uncertainty analysis, and cost analysis of the novel SMP based inkjet printed Au plated sensor have been delineated in this manuscript …

Interdisciplinary Approach To Understanding Stakeholder Reasoning And Decision-Making For Water, Katalina Salas

Open Access Theses & Dissertations

On a global scale, humanity is compelled to address complex or â??wickedâ?? resource-related issues in the face of accelerating environmental change. In our work, we use the term wicked problem to refer to an issue that has multiple potential solutions and involves various stakeholders. The paths to reach resource sustainability under environmental uncertainty are difficult to identify, plausible outcomes remain uncertain, and tradeoffs required by any path chosen are challenging to understand. Environmental sustainability issues may involve perspectives from multiple stakeholders (i.e., scientists, policymakers, community members, and industry), often leading to conflicting interests and cultural misalignments that trigger the need …

Geospatial Wildfire Risk Prediction Using Deep Learning, Abner Alberto Benavides

Electronic Theses, Projects, and Dissertations

This report introduces a thorough analysis of wildfire prediction using satellite imagery by applying deep learning techniques. To find wildfire-prone geographical data, we use U-Net, a convolutional neural network known for its effectiveness in biomedical image segmentation. The input to the model is the Sentinel-2 multispectral images to supply a complete view of the terrain features.

We evaluated the wildfire risk prediction model’s performance using several metrics. The model showed high accuracy, with a weighted average F1 score of 0.91 and an AUC-ROC score of 0.972. These results suggest that the model is exceptionally good at predicting the location of …

Age And Paleontology Of The Turin Pit Locality, Monona County, Iowa, Samantha Wright

Electronic Theses and Dissertations

The Turin Pit locality (Monona county, Iowa) has been known to paleontologists since 1908, yet the age of the fauna has been unclear. Early paleontologists considered Turin Pit to date to a pre-Illinoian interglacial (the “Aftonian).” Subsequent researchers suggested it dated to the last glaciation. This study provides a partial list of mammals in the Turin Pit fauna, and together with stratigraphic information, uses the known age ranges of taxa to estimate an age for the assemblage. The presence of Mammuthus, Aenocyon, and Castoroides combined with a magnetically-reversed till located stratigraphically above fossil-bearing deposits, suggest the Turin Pit …

2023 August - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Innovations In Geospatial Technologies For Water And Environmental Resource Protection, Madeleine Bolick

All Dissertations

New technologies and applications of technologies are critical to protecting environmental and water resources. Students need to be aware of these new technologies so they can be prepared to utilize them in their future careers. One such technology is using Unmanned Aerial Vehicles (UAVs) because it can be applied to a wide variety of fields such as engineering, construction, wildlife biology, agriculture, and many more. Chapter two discusses the creation of an online teaching module to introduce students to using UAVs in natural resource research and evaluates how well students respond to the education module. Overall, student familiarity with UAVs …

High-Energy Storm Events And Their Impacts On Carbon Storage In Tidal Wetlands Of South Carolina, Gavin Gleasman

All Dissertations

Atmospheric carbon dioxide (CO₂) concentrations have been increasing at an accelerating rate for the past two centuries, profoundly impacting global climate change. Atmospheric CO₂ concentrations are influenced by the global carbon cycle through physical and biogeochemical pathways. Tidal wetland environments play a vital role in the global carbon cycle by offsetting atmospheric CO₂ concentrations through their natural physiochemical processes of high autotrophic productivity, allochthonous organic matter deposition, anoxic soils, and continuous accretion which promotes carbon sequestration with long-term storage at the land-ocean margin. The Intergovernmental Panel on Climate Change (IPCC) and United States Global Change Research …

Cosmic Diffuse Neutrino And Gamma-Ray Backgrounds In The Mev Regime, Ilukpitiye Samalka Anandagoda

All Dissertations

Cosmic Multi-Messenger backgrounds include relic diffuse components created in the early Universe and contributions from individual sources. In this dissertation, I present the work done in Anandagoda (2019); Anandagoda et al. (2020, 2023) where type Ia (SNe Ia) and core-collapse supernovae (CCSNe) contributions to the diffuse neutrino and gamma-ray backgrounds in the MeV regime are studied. These backgrounds are referred to as DSNB and DSGB respectively. Based on this work, the diffuse SN Ia background is ~10⁶ times lower (for electron antineutrinos) than the CCSN background making it negligible. The predicted DSNB electron antineutrino flux at earth in the …

Computational Analysis Of Antibody Binding Mechanisms To The Omicron Rbd Of Sars-Cov-2 Spike Protein: Identification Of Epitopes And Hotspots For Developing Effective Therapeutic Strategies, Mohammed Alshahrani

Computational and Data Sciences (PhD) Dissertations

The advent of the Omicron strain of SARS-CoV-2 has elicited apprehension regarding its potential influence on the effectiveness of current vaccines and antibody treatments. The present investigation involved the implementation of mutational scanning analyses to examine the impact of Omicron mutations on the binding affinity of four categories of antibodies that target the Omicron receptor binding domain (RBD) of the Spike protein. The study demonstrates that the Omicron variant harbors 23 unique mutations across the RBD regions I, II, III, and IV. Of these mutations, seven are shared between RBD regions I and II, while three are shared among RBD …

Ocean Wave-Coherent Temperature And Humidity Near-Surface Vertical Distributions And Their Effect On Radar Performance Over The Ocean, Mathew James Stanek

Electronic Theses and Dissertations

Large knowledge gaps concerning the effect of ocean surface waves on near-surface vertical distributions of temperature and humidity in the marine atmospheric surface layer exist due to practical limitations and sensor fidelity challenges of direct measurements. Wave effects on these distributions between the wave trough and crest are least studied within the literature. These scalar distributions influence atmospheric refractivity, which can lead to anomalous propagation of electromagnetic energy. Measurements of temperature and humidity are classically made using rocket- or radiosondes and fixed weather stations, and can utilize tethered profiling systems. However, these measurement systems have limitations when obtaining measurements near …

Functional Nanocomposite Coatings For Use In Food Packaging, Camden N. Webb

Master's Theses

Plastics are a class of materials known for their cost and property advantages, increasing significantly in their usage worldwide. Unfortunately, these benefits come with an increasingly concerning environmental impact. A combination of inadequate disposal options and combinations of materials have led to environmental disasters that will impact generations. One of the worst areas for plastic waste is food packaging. Plastic as a material generally excels at durability and longevity, but as food packaging, it outlives its intended purpose by several orders of magnitude. This leads to plastic food packaging materials sitting in landfill or leading to the environment for hundreds …