Physical Sciences and Mathematics Commons^™

Stereospecific Cross-Coupling Reactions Of Vinyl Triflates And An Investigation Of The Synthesis And Reactivity Of Activated Alkyltricyclohexylstannanes, Pejman Ghaemimohammadi

Dissertations, Theses, and Capstone Projects

Organic chemistry exists in all aspects of everyday life from polymers to pharmaceutics. Formation of carbon-carbon bonds is essential for the synthesis of complex organic compounds. This goal can be achieved by using transition metal catalysts. Second-row transition metals such as Pd, Pt, Rh, and Ir have shown remarkable efficacy in these reactions. Metal-catalyzed cross-coupling reactions form carbon-carbon bonds between electrophiles and nucleophiles using transition metal catalysts. Pd is mainly used in this reaction.

Transition metal-catalyzed cross-coupling reactions that form a bond between two C(sp²) carbons have been widely studied over the past decades. C(sp²)-C(sp^{3 …}

Low Elevation Coastal Zone (Lecz) Population Social Vulnerability And Risk: A Spatial Analysis Based On The 2015-16 National Family Health Survey (Nfhs-4) Of India, Paradorn Wongchanapai

Dissertations, Theses, and Capstone Projects

Background & Problem Statement:

This study assessed social vulnerability and risk to hydroclimate hazards of Indian urban and rural populations in the Low Elevation Coastal Zone (LECZ), a contiguous coastal area with elevations less than 10 meters. The LECZ is considered an at-risk area as hydroclimate hazards tend to be heightened. Moreover, being the most populous country in the world, any hydroclimate hazards that hit the LECZ would disproportionately impact a large number of Indian populations. Understanding the social vulnerability and risk of the LECZ populations can help mitigate and prevent potential adverse outcomes for the populations.

Importantly, this study …

Clustering Of Patients With Heart Disease, Mukadder Cinar

Dissertations, Theses, and Capstone Projects

Heart disease, a leading cause of mortality worldwide, presents complex challenges in public health due to its varied manifestations. Accurate diagnosis and patient stratification are essential for effective management and improved outcomes. In response, this study employed machine learning techniques to analyze heart disease data obtained from UCI Machine Learning Repository, aiming to enhance patient care through advanced data analysis.

The study began with the application of K-Nearest Neighbors (KNN) classification, which categorized patients into 'Disease' and 'No Disease' groups. This preliminary step provided initial insights into the structure of the dataset. Subsequently, K-means clustering was applied in two rounds, …

Studies Of Oxidopyrylium Ylide Dimers And Their Utility In The Synthesis Of Densely Functionalized Troponoids, Daniel V. Schiavone

Dissertations, Theses, and Capstone Projects

Herein, we describe our efforts to investigate mechanistic considerations of oxidopyrylium ylides and their use in cycloadditions to form complex bicyclic structures and the advancement of these cycloadducts to the synthesis of densely functionalized tropolones. This work also describes applications of tropolones as biologically relevant structures and dynamic fluorophores.

In Chapter 1, we expand upon previous studies done in the Murelli Lab describing the ability of 3-hydroxy-4-pyrone derived oxidopyrylium dimers to revert back to ylides in situ and as result can be used as a clean oxidopyrylium ylide source in accessing oxabicyclic compounds. Intermolecular cycloadditions of these ylides can be …

Containerization Of Seafarers In The International Shipping Industry: Contemporary Seamanship, Maritime Social Infrastructures, And Mobility Politics Of Global Logistics, Liang Wu

Dissertations, Theses, and Capstone Projects

This dissertation discusses the mobility politics of container shipping and argues that technological development, political-economic order, and social infrastructure co-produce one another. Containerization, the use of standardized containers to carry cargo across modes of transportation that is said to have revolutionized and globalized international trade since the late 1950s, has served to expand and extend the power of international coalitions of states and corporations to control the movements of commodities (shipments) and labor (seafarers). The advent and development of containerization was driven by a sociotechnical imaginary and international social contract of seamless shipping and cargo flows. In practice, this liberal, …

Deep Learning-Based Human Action Understanding In Videos, Elahe Vahdani

Dissertations, Theses, and Capstone Projects

The understanding of human actions in videos holds immense potential for technological advancement and societal betterment. This thesis explores fundamental aspects of this field, including action recognition in trimmed clips and action localization in untrimmed videos. Trimmed videos contain only one action instance, with moments before or after the action excluded from the video. However, the majority of videos captured in unconstrained environments, often referred to as untrimmed videos, are naturally unsegmented. Untrimmed videos are typically lengthy and may encompass multiple action instances, along with the moments preceding or following each action, as well as transitions between actions. In the …

Rational Design Of Peptide-Based Materials Informed By Multiscale Molecular Dynamics Simulations, Dhwanit Rahul Dave

Dissertations, Theses, and Capstone Projects

The challenge of establishing a sustainable and circular economy for materials in medicine and technology necessitates bioinspired design. Nature's intricate machinery, forged through evolution, relies on a finite set of biomolecular building blocks with through-bond and through-space interactions. Repurposing these molecular building blocks requires a seamless integration of computational modeling, design, and experimental validation. The tools and concepts developed in this thesis pioneer new directions in peptide-materials design, grounded in fundamental principles of physical chemistry. We present a synergistic approach that integrates experimental designs and computational methods, specifically molecular dynamics simulations, to gain in-depth molecular insights crucial for advancing the …

Complex Ball Quotients And New Symplectic 4-Manifolds With Nonnegative Signatures, Anar Akhmedov, Sümeyra Sakalli, Sai-Kee Yeung

Mathematical Sciences Faculty Publications and Presentations

We construct new symplectic 4-manifolds with non-negative signatures and with the smallest Euler characteristics, using fake projective planes, Cartwright– Steger surfaces and their normal covers and product symplectic 4-manifolds Σ_g × Σ_h, where g ≥ 1 and h ≥ 0, along with exotic symplectic 4-manifolds constructed in [7, 12]. In particular, our constructions yield to (1) infinitely many irreducible symplectic and infinitely many non-symplectic 4-manifolds that are homeomorphic but not diffeomorphic to (2n−1)CP²#(2n−1)CP² for each integer n ≥ 9, (2) infinite families of simply connected irreducible nonspin symplectic and such …

Low Shear In Short-Term Impacts Endothelial Cell Traction And Alignment In Long-Term, Mohanish Chandurkar, Nikhil Mittal, Shaina P. Royer-Weeden, Steven D. Lehmann, Yeonwoo Rho, Sangyoon J. Han

Michigan Tech Publications, Part 2

Within the vascular system, endothelial cells (ECs) are exposed to fluid shear stress (FSS), a mechanical force exerted by blood flow that is critical for regulating cellular tension and maintaining vascular homeostasis. The way ECs react to FSS varies significantly; while high, laminar FSS supports vasodilation and suppresses inflammation, low or disturbed FSS can lead to endothelial dysfunction and increase the risk of cardiovascular diseases. Yet, the adaptation of ECs to dynamically varying FSS remains poorly understood. This study focuses on the dynamic responses of ECs to brief periods of low FSS, examining its impact on endothelial traction-a measure of …

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 …

Evaluating The Reliability And Accuracy Of Alchemical Binding Free Energy Methods And Calculations, Fnu Sheenam

Dissertations, Theses, and Capstone Projects

Molecular recognition plays a crucial role in various biological processes, such as enzymatic reactions, signal transduction, and genetic information processing. Investigating how proteins selectively bind to their partners is an active research area, but there is a lack of experimental details on protein structures and interactions in molecular complexes. Computational techniques based on macromolecular structures offer a way to predict protein-ligand interactions and explore their recognition mechanisms. Estimating binding affinities, particularly through alchemical binding free energy calculations, has become valuable in supporting drug discovery. This work introduces new methodologies, utilizing the Alchemical Transfer Method, to address issues like poor convergence …

A Causal Inference Approach For Spike Train Interactions, Zach Saccomano

Dissertations, Theses, and Capstone Projects

Since the 1960s, neuroscientists have worked on the problem of estimating synaptic properties, such as connectivity and strength, from simultaneously recorded spike trains. Recent years have seen renewed interest in the problem coinciding with rapid advances in experimental technologies, including an approximate exponential increase in the number of neurons that can be recorded in parallel and perturbation techniques such as optogenetics that can be used to calibrate and validate causal hypotheses about functional connectivity. This thesis presents a mathematical examination of synaptic inference from two perspectives: (1) using in vivo data and biophysical models, we ask in what cases the …

Examining The Health Risks Of Particulate Matter 2.5 In New York City: How It Affects Marginalized Groups And The Steps Needed To Reduce Air Pollution, Freddy Castro

Dissertations, Theses, and Capstone Projects

The following examines the impact of particulate matter 2.5 (PM2.5) on public health, focusing on its sources and effects on vulnerable populations in New York City. PM2.5 is a particle that is 2.5 micrometers or less in diameter and, because of its size, can enter the bloodstream affecting the respiratory and cardiovascular systems and further complicating the health of the immunocompromised. Recent studies have shown that PM2.5 can come from various sources, including transportation and industrial emissions, as well as indoor sources like cigarettes and gas-operated stoves. Despite reduced levels of PM2.5 due to recent policy changes and initiatives taken …

Making Sense Of Making Parole In New York, Alexandra Mcglinchy

Dissertations, Theses, and Capstone Projects

For many individuals incarcerated in New York, the initial step toward freedom begins with an interview with the Board of Parole. This process, however, is frequently a complex and challenging one, characterized by repeated denials and extended incarcerations. The disparity in outcomes – where one individual may receive over 20 denials and another is granted parole on their first attempt – highlights the ambiguity and inconsistency in the parole decision-making process. This project aims to clarify the factors that influence parole decisions by concentrating on measurable variables. These include age, race, duration of sentence served, proportion of sentence served, type …

The Early Late Miocene Cessation Of Deep And Intermediate Water Circulation Through The Central American Seaway, Benjamin Stanley Kwiatkowski

Dissertations, Theses, and Capstone Projects

The state of the middle late Miocene global ocean circulations which regulated climate and affected deep ocean chemical environments were impacted by geographic changes. During the Miocene, cirum-equatorial circulations slowly decreased, which included through the seaway between the Americas called the Central American Seaway (CAS). Its shoaling and ultimate closing led to the onset of modern day oceanic circulation as characterized by the global thermohaline circulation. However, this seaway has a long hotly debated history concerning the timing of its restriction and shallowing owing in part to the shifting of tectonic plates.

The goal of this research focuses on investigating …

Artificial Intelligence Model Predicts Sudden Cardiac Arrest Manifesting With Pulseless Electric Activity Versus Ventricular Fibrillation, Lauri Holmstrom, Bryan Bednarski, Harpriya Chugh, Habiba Aziz, Hoang Nhat Pham, Arayik Sargsyan, Audrey Uy-Evanado, Damini Dey, Angelo Salvucci, Jonathan Jui, Kyndaron Reinier, Piotr J Slomka, Sumeet S Chugh

Student and Faculty Publications

BACKGROUND: There is no specific treatment for sudden cardiac arrest (SCA) manifesting as pulseless electric activity (PEA) and survival rates are low; unlike ventricular fibrillation (VF), which is treatable by defibrillation. Development of novel treatments requires fundamental clinical studies, but access to the true initial rhythm has been a limiting factor.

METHODS: Using demographics and detailed clinical variables, we trained and tested an AI model (extreme gradient boosting) to differentiate PEA-SCA versus VF-SCA in a novel setting that provided the true initial rhythm. A subgroup of SCAs are witnessed by emergency medical services personnel, and because the response time is …

Brief Communication: Recent Estimates Of Glacier Mass Loss For Western North America From Laser Altimetry, Brian Menounos, Caitlyn Forentine, Alex A. Gardner, Andrew G. Fountain

Geology Faculty Publications and Presentations

Glaciers in western North American outside of Alaska are often overlooked in global studies because their potential to contribute to changes in sea level is small. Nonetheless, these glaciers represent important sources of freshwater, especially during times of drought. Differencing recent ICESat-2 data from a digital elevation model derived from a combination of synthetic aperture radar data (TerraSAR-X/TanDEM-X), we find that over the period 2013–2020, glaciers in western North America lost mass at a rate of 12:3+3:5 Gt yr^-1. This rate is comparable to the rate of mass loss (11:71:0 Gt yr1) for the period 2018– 2022 calculated …

Learning From Machines: How Negative Feedback From Machines Improves Learning Between Humans, Tengjian Zou, Gokhan Ertug, Thomas Roulet

Research Collection Lee Kong Chian School Of Business

Prior studies on learning from failure primarily focus on how individuals learn from failure feedback given by other individuals. It is unclear whether and how the advent of machine feedback may influence individuals’ learning from failures. We suggest that failure feedback provided by machines facilitates learning in two ways. First, it focuses individuals’ attention on their failures, leading them to learn from these failures. Second, it serves as a catalyzer, motivating individuals to learn more from failure feedback given to them by other individuals as well. In addition, this catalyzing effect is stronger if the failure feedback from machines and …

Machine Learning For Refining Knowledge Graphs: A Survey, Budhitama Subagdja, D. Shanthoshigaa, Zhaoxia Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Knowledge graph (KG) refinement refers to the process of filling in missing information, removing redundancies, and resolving inconsistencies in knowledge graphs. With the growing popularity of KG in various domains, many techniques involving machine learning have been applied, but there is no survey dedicated to machine learning-based KG refinement yet. Based on a novel framework following the KG refinement process, this paper presents a survey of machine learning approaches to KG refinement according to the kind of operations in KG refinement, the training datasets, mode of learning, and process multiplicity. Furthermore, the survey aims to provide broad practical insights into …

Handling Long And Richly Constrained Tasks Through Constrained Hierarchical Reinforcement Learning, Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Safety in goal directed Reinforcement Learning (RL) settings has typically been handled through constraints over trajectories and have demonstrated good performance in primarily short horizon tasks. In this paper, we are specifically interested in the problem of solving temporally extended decision making problems such as robots cleaning different areas in a house while avoiding slippery and unsafe areas (e.g., stairs) and retaining enough charge to move to a charging dock; in the presence of complex safety constraints. Our key contribution is a (safety) Constrained Search with Hierarchical Reinforcement Learning (CoSHRL) mechanism that combines an upper level constrained search agent (which …

Public Acceptance Of Using Artificial Intelligence-Assisted Weight Management Apps In High-Income Southeast Asian Adults With Overweight And Obesity: A Cross-Sectional Study, Han Shi Jocelyn Chew, Palakorn Achananuparp, Palakorn Achananuparp, Nicholas W. S. Chew, Yip Han Chin, Yujia Gao, Bok Yan Jimmy So, Asim Shabbir, Ee-Peng Lim, Kee Yuan Ngiam

Research Collection School Of Computing and Information Systems

Introduction: With in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity. Methods: 280 participants were recruited between May and November 2022. Participants completed a questionnaire on sociodemographic profiles, Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and Self-Regulation of Eating Behavior Questionnaire. Structural equation modeling was performed using R. Model fit was tested using maximum-likelihood generalized unweighted least squares. Associations between influencing factors were analyzed using correlation and linear regression. Results: 271 participant responses were …

Vibmilk: Non-Intrusive Milk Spoilage Detection Via Smartphone Vibration, Yuezhong Wu, Wei Song, Yanxiang Wang, Dong Ma, Weitao Xu, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

Quantifying the chemical process of milk spoilage is challenging due to the need for bulky, expensive equipment that is not user-friendly for milk producers or customers. This lack of a convenient and accurate milk spoilage detection system can cause two significant issues. First, people who consume spoiled milk may experience serious health problems. Secondly, milk manufacturers typically provide a “best before” date to indicate freshness, but this date only shows the highest quality of the milk, not the last day it can be safely consumed, leading to significant milk waste. A practical and efficient solution to this problem is proposed …

M3sa: Multimodal Sentiment Analysis Based On Multi-Scale Feature Extraction And Multi-Task Learning, Changkai Lin, Hongju Cheng, Qiang Rao, Yang Yang

Research Collection School Of Computing and Information Systems

Sentiment analysis plays an indispensable part in human-computer interaction. Multimodal sentiment analysis can overcome the shortcomings of unimodal sentiment analysis by fusing multimodal data. However, how to extracte improved feature representations and how to execute effective modality fusion are two crucial problems in multimodal sentiment analysis. Traditional work uses simple sub-models for feature extraction, and they ignore features of different scales and fuse different modalities of data equally, making it easier to incorporate extraneous information and affect analysis accuracy. In this paper, we propose a Multimodal Sentiment Analysis model based on Multi-scale feature extraction and Multi-task learning (M 3 SA). …

Improving Conversational Recommender System Via Contextual And Time-Aware Modeling With Less Domain-Specific Knowledge, Lingzhi Wang, Shafiq Joty, Wei Gao, Xingshan Zeng, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Conversational Recommender Systems (CRS) has become an emerging research topic seeking to perform recommendations through interactive conversations, which generally consist of generation and recommendation modules. Prior work on CRS tends to incorporate more external and domain-specific knowledge like item reviews to enhance performance. Despite the fact that the collection and annotation of the external domain-specific information needs much human effort and degenerates the generalizability, too much extra knowledge introduces more difficulty to balance among them. Therefore, we propose to fully discover and extract the internal knowledge from the context. We capture both entity-level and contextual-level representations to jointly model user …

Market-Gan: Adding Control To Financial Market Data Generation With Semantic Context, Haochong Xia, Shuo Sun, Xinrun Wang, Bo An

Research Collection School Of Computing and Information Systems

Financial simulators play an important role in enhancing forecasting accuracy, managing risks, and fostering strategic financial decision-making. Despite the development of financial market simulation methodologies, existing frameworks often struggle with adapting to specialized simulation context. We pinpoint the challenges as i) current financial datasets do not contain context labels; ii) current techniques are not designed to generate financial data with context as control, which demands greater precision compared to other modalities; iii) the inherent difficulties in generating context-aligned, high-fidelity data given the non-stationary, noisy nature of financial data. To address these challenges, our contributions are: i) we proposed the Contextual …

Pathway To Bakken Eor, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet on the enhanced oil recovery (EOR) potential of the Bakken Formation.

Cognitive Load Scale In Learning Formal Definition Of Limit: A Rasch Model Approach, Rina Oktaviyanthi, Ria Noviana Agus, Mark Lester B. Garcia, Kornkanok Lertdechapat

Mathematics Faculty Publications

Constructing proofs for the limit using the formal definition induces a high cognitive load. Common assessment tools, like cognitive load scales, lack specificity for the concept of limits. This research aims to validate an instrument tailored to assess cognitive load in students focused on the formal definition of limits, addressing the need for diverse strategies in education. The research employs a quantitative survey design with a Rasch model approach, utilizing a data collection instrument in the form of a questionnaire. Subsequently, the data are analyzed by focusing on three aspects: (1) item fit to the Rasch model, (2) unidimensionality, and …

Exploring Perceptions Of Algorithmic Bias In Video Interviewing Software: The Importance Of Ai Hiring Education, Theresa Fister, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Many employers across various fields are incorporating artificial intelligence into their hiring processes. Existing research suggests that although artificial intelligence is often perceived as neutral by its advocates, it can inadvertently perpetuate both implicit and explicit biases present in the engineers and designers responsible for its development through the machine learning process. To delve deeper into this issue, we conducted a research study involving 25 recent graduates from 12 different industries. Our aim was to gain insights into the workings of AI video interviewing software and to understand the reactions of recent graduates who have used this technology. Considering the …

Trends In Catch Rates Of Sawfish On The Australian North West Shelf, C. Wakefield, S. J. Newman, M. Braccini, A. Harry

Fisheries Research Articles

Northwestern Australia is thought to have some of the world’s last remaining viable sawfish populations, although little quantitative data exists on their status or trends. This study examined 17 years of logbook bycatch records (n = 815) for green sawfish Pristis zijsron and narrow sawfish Anoxypristis cuspidata from a trawl fishery operating on the Australian North West Shelf. Incidental sawfish captures by the fishery are rare, occurring approximately once every 75 trawls (~199 trawl hours). To standardize catch rates and account for excess zeros in the data, we employed generalized additive models for location, scale, and shape (GAMLSSs) using a …

Examination Of Traditional Botnet Detection On Iot-Based Bots, Ashley Woodiss-Field, Michael N. Johnstone, Paul Haskell-Dowland

Research outputs 2022 to 2026

A botnet is a collection of Internet-connected computers that have been suborned and are controlled externally for malicious purposes. Concomitant with the growth of the Internet of Things (IoT), botnets have been expanding to use IoT devices as their attack vectors. IoT devices utilise specific protocols and network topologies distinct from conventional computers that may render detection techniques ineffective on compromised IoT devices. This paper describes experiments involving the acquisition of several traditional botnet detection techniques, BotMiner, BotProbe, and BotHunter, to evaluate their capabilities when applied to IoT-based botnets. Multiple simulation environments, using internally developed network traffic generation software, were …