Physical Sciences and Mathematics Commons^™

Convolutional Neural Network For Biomarker Discovery For Triple Negative Breast Cancer With Rna Sequencing Data, Xiangning Chen, Justin M Balko, Fei Ling, Yabin Jin, Anneliese Gonzalez, Zhongming Zhao, Jingchun Chen

Faculty, Staff and Student Publications

Triple negative breast cancers (TNBCs) are tumors with a poor treatment response and prognosis. In this study, we propose a new approach, candidate extraction from convolutional neural network (CNN) elements (CECE), for discovery of biomarkers for TNBCs. We used the GSE96058 and GSE81538 datasets to build a CNN model to classify TNBCs and non-TNBCs and used the model to make TNBC predictions for two additional datasets, the cancer genome atlas (TCGA) breast cancer RNA sequencing data and the data from Fudan University Shanghai Cancer Center (FUSCC). Using correctly predicted TNBCs from the GSE96058 and TCGA datasets, we calculated saliency maps …

Artificial Intelligence In Higher Education: The State Of The Field, Helen Crompton, Diane Burke

Teaching & Learning Faculty Publications

This systematic review provides unique findings with an up-to-date examination of artificial intelligence (AI) in higher education (HE) from 2016 to 2022. Using PRISMA principles and protocol, 138 articles were identified for a full examination. Using a priori, and grounded coding, the data from the 138 articles were extracted, analyzed, and coded. The findings of this study show that in 2021 and 2022, publications rose nearly two to three times the number of previous years. With this rapid rise in the number of AIEd HE publications, new trends have emerged. The findings show that research was conducted in six of …

Extraction And Analytical Method For N-Nitrosoatrazine Using Liquid Chromatography Paired With Tandem Mass Spectrometry, Carolyn Billings

Honors Program: Senior Projects (Public)

Atrazine is an herbicide used in the United States to control weeds. When combined with nitrite, atrazine can be nitrosated to form N-nitrosoatrazine (NNAT) in vivo and in vitro under acidic conditions. Atrazine can also be metabolized to atrazine mercapturate, deethylatrazine (DEA), didealkylatrazine (DDA), and deisopropylatrazine (DIA). Atrazine is monitored in drinking water due to its possible carcinogenicity. The objective of this study was to develop extraction and analytical methods for NNAT, atrazine, and atrazine metabolites. An instrument detection limit, extraction methods comparison, and extraction method detection limit were determined. To compare methods, Fischer 344 rat tissue samples were …

Engaging Students Through Conversational Chatbots And Digital Content: A Climate Action Perspective, Thomas Menkhoff, Benjamin Gan

Research Collection Lee Kong Chian School Of Business

In this case study, we report experiences deploying a conversational chatbot as a pre-class and post-class engagement tool for undergraduate students enrolled in sustainability-related courses aimed at educating them about the severity of climate change and the importance of climate action by offsetting one’s carbon footprint (e.g, by planting trees or mangroves in SEA). The intitiative supports the university’s sustainability efforts in general and our new sustainability major in particular aimed at helping students to achieve sustainability-related learning outcomes with reference to climate change and climate action (SDG 13), one of the 17 Sustainable Development Goals established by the United …

Alfred Russel Wallace Notes 25. Wallace And The 'Physical Environment'., Charles H. Smith

Faculty/Staff Personal Papers

Alfred Russel Wallace’s natural selection essay of 1858 has been held to frame a greater role for the physical environment in forcing selection regimes than we find in Darwin’s writings, but here that verdict is challenged by a re-examination of both the essay itself, and period usage of the term ‘physical.’

Quantifying Oil And Gas Industry Related Geohazard Using Radar Interferometry And Hydro-Geomechanical Modeling, Weiyu Zheng

Earth Sciences Theses and Dissertations

The Permian Basin, containing a large amount of oil and gas, has been intensively developed for hydrocarbon production. However, the hazards related to the oil and gas industry including surface deformation and the underlying mechanisms in this region have not been well known. My PhD study aims to monitor the geohazards in the Permian Basin and better comprehend the subsurface mechanisms with the aid of high-resolution and high-accuracy Interferometric Synthetic Aperture Radar (InSAR) images. Generally, as the pore pressure is influenced by wastewater injection/hydrocarbon production, the pressure changes can propagate to other surrounding underground and overlying rock/soil layers, resulting in …

Grid Independence Studies Of Eddy-Resolving Models At The Scale Of A River Reach Along A Transect In Marble Canyon Of The Colorado River, Arizona, Rosa Elena España Urresty

Open Access Theses & Dissertations

This study presented a novel approach for evaluating the impact of changes in spatial resolution on field-scale models to identify turbulent flow patterns in hydraulic features in canyon-bound rivers. The methodological framework incorporated seven different computational domain resolutions to analyze the sensitivity of field-scale models to spatial resolution changes by employing techniques such as turbulent kinetic energy spectrum, spatiotemporal analysis of eddy structures, divergent Kullback-Leibler (KL) divergence, Nash-Sutcliffe (NS) model efficiency coefficient, wavelet power spectrum, and GCI calculation. Statistical and physical-based skill metrics are employed to quantifying information loss to evaluate a set of domain resolutions. Grid independence studies have …

Using Object Detection To Navigate A Game Playfield, Peter Kearnan Hyde-Smith

Master's Theses (2009 -)

Perhaps the crown jewel of AI is the self-navigating agent. To take many sources of data as input and use it to traverse complex and varied areas while mitigating risk and damage to the vehicle that is being controlled, visual object detection is a key part of the overall suite of this technology. While much efforts are being put towards real-world applications, for example self-driving cars, healthcare related issues and automated manufacturing, we apply object detection in a different way; the automation of movement across a video game play field. We take the TensorFlow Object Detection API and use it …

Enots Wolley Variations And Related Sequences, Nathan Myles Nichols

Master's Theses (2009 -)

The Enots Wolley sequence is a lexicographically earliest sequence (LES) that is closely related to the Yellowstone sequence. It is an open conjecture by N. J. Sloane that every number with at least two distinct prime factors appears as a term of the Enots Wolley sequence. In this thesis, this conjecture is proved for a variation of the Enots Wolley sequence that operates on the binary representation of a positive integer rather than the prime factorization. The methods used are then applied to prove some new properties of the prime factorization Enots Wolley sequence.

Nftdisk: Visual Detection Of Wash Trading In Nft Markets, Xiaolin Wen, Yong Wang, Xuanwu Yue, Feida Zhu, Min Zhu

Research Collection School Of Computing and Information Systems

With the growing popularity of Non-Fungible Tokens (NFT), a new type of digital assets, various fraudulent activities have appeared in NFT markets. Among them, wash trading has become one of the most common frauds in NFT markets, which attempts to mislead investors by creating fake trading volumes. Due to the sophisticated patterns of wash trading, only a subset of them can be detected by automatic algorithms, and manual inspection is usually required. We propose NFTDisk, a novel visualization for investors to identify wash trading activities in NFT markets, where two linked visualization modules are presented: a radial visualization module with …

Does Deep Learning Improve The Performance Of Duplicate Bug Report Detection? An Empirical Study, Yuan Jiang, Xiaohong Su, Christoph Treude, Chao Shang, Tiantian Wang

Research Collection School Of Computing and Information Systems

Do Deep Learning (DL) techniques actually help to improve the performance of duplicate bug report detection? Prior studies suggest that they do, if the duplicate bug report detection task is treated as a binary classification problem. However, in realistic scenarios, the task is often viewed as a ranking problem, which predicts potential duplicate bug reports by ranking based on similarities with existing historical bug reports. There is little empirical evidence to support that DL can be effectively applied to detect duplicate bug reports in the ranking scenario. Therefore, in this paper, we investigate whether well-known DL-based methods outperform classic information …

A Learner-Verifier Framework For Neural Network Controllers And Certificates Of Stochastic Systems, Krishnendu Chatterjee, Thomas A. Henzinger, Dorde Zikelic, Dorde Zikelic

Research Collection School Of Computing and Information Systems

Reinforcement learning has received much attention for learning controllers of deterministic systems. We consider a learner-verifer framework for stochastic control systems and survey recent methods that formally guarantee a conjunction of reachability and safety properties. Given a property and a lower bound on the probability of the property being satisfied, our framework jointly learns a control policy and a formal certificate to ensure the satisfaction of the property with a desired probability threshold. Both the control policy and the formal certificate are continuous functions from states to reals, which are learned as parameterized neural networks. While in the deterministic case, …

How To Find Actionable Static Analysis Warnings: A Case Study With Findbugs, Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies

Research Collection School Of Computing and Information Systems

Automatically generated static code warnings suffer from a large number of false alarms. Hence, developers only take action on a small percent of those warnings. To better predict which static code warnings should ot be ignored, we suggest that analysts need to look deeper into their algorithms to find choices that better improve the particulars of their specific problem. Specifically, we show here that effective predictors of such warnings can be created by methods that ocally adjust the decision boundary (between actionable warnings and others). These methods yield a new high water-mark for recognizing actionable static code warnings. For eight …

Subgraph Centralization: A Necessary Step For Graph Anomaly Detection, Zhong Zhuang, Kai Ming Ting, Guansong Pang, Shuaibin Song

Research Collection School Of Computing and Information Systems

Abstract Graph anomaly detection has attracted a lot of interest recently. Despite their successes, existing detectors have at least two of the three weaknesses: (a) high computational cost which limits them to small-scale networks only; (b) existing treatment of subgraphs produces suboptimal detection accuracy; and (c) unable to provide an explanation as to why a node is anomalous, once it is identified. We identify that the root cause of these weaknesses is a lack of a proper treatment for subgraphs. A treatment called Subgraph Centralization for graph anomaly detection is proposed to address all the above weaknesses. Its importance is …

Supporting Novices Author Audio Descriptions Via Automatic Feedback, Rosiana Natalie, Joshua Shi-Hao Tseng, Hernisa Kacorri, Kotaro Hara

Research Collection School Of Computing and Information Systems

Audio descriptions (AD) make videos accessible to those who cannot see them. But many videos lack AD and remain inaccessible as traditional approaches involve expensive professional production. We aim to lower production costs by involving novices in this process. We present an AD authoring system that supports novices to write scene descriptions (SD)—textual descriptions of video scenes—and convert them into AD via text-to-speech. The system combines video scene recognition and natural language processing to review novice-written SD and feeds back what to mention automatically. To assess the effectiveness of this automatic feedback in supporting novices, we recruited 60 participants to …

Parsing-Conditioned Anime Translation: A New Dataset And Method, Zhansheng Li, Yangyang Xu, Nanxuan Zhao, Yang Zhou, Yongtuo Liu, Dahua Lin, Shengfeng He

Research Collection School Of Computing and Information Systems

Anime is an abstract art form that is substantially different from the human portrait, leading to a challenging misaligned image translation problem that is beyond the capability of existing methods. This can be boiled down to a highly ambiguous unconstrained translation between two domains. To this end, we design a new anime translation framework by deriving the prior knowledge of a pre-Trained StyleGAN model. We introduce disentangled encoders to separately embed structure and appearance information into the same latent code, governed by four tailored losses. Moreover, we develop a FaceBank aggregation method that leverages the generated data of the StyleGAN, …

Drinking Water Contaminants: Bacteria, Bruce I. Dvorak, Becky O. Schuerman

Department of Civil and Environmental Engineering: Faculty Publications

Testing drinking water for fecal bacteria or Escherichia coli (E. coli) is commonly used as an indicator of the presence of pathogenic microorganisms. The presence of pathogenic (disease-causing) microorganisms is a concern when considering the safety of drinking water. Pathogenic microorganisms can cause flu-like systems, intestinal infections, dysentery, hepatitis, typhoid fever, cholera, and other illnesses.

Aloe Barbadensis Rinds Employ Physical And Chemical Defense Mechanisms Against Insect Herbivores With Varying Success, Zachary Johnson, Ishveen Kaur, Fernando Castillo, Rupesh R. Kariyat, Debasish Bandyopadhyay

School of Integrative Biological & Chemical Sciences Faculty Publications

Plants deter herbivory through a suite of physical and chemical defenses. While most studies have focused on understanding one or the other, efficient plant defense against herbivory is often cumulative. To examine this, we used Aloe barbadensis (Asphodelaceae) as a model, since in natural settings, the species is found to be well-defended against insect herbivores. To start with, we hypothesized that the epicuticular wax potentially plays an important role in herbivore defense as the major physical defense. To test our hypothesis, we conducted bioactivity-guided extraction and polarity-based fractionation of A. barbadensis rinds. We then mixed them into an artificial diet, …

A Diffusion Network Event History Estimator, Jeffrey J. Harden, Bruce A. Desmarais, Mark Brockway, Frederick J. Boehmke, Scott J. Lacombe, Fridolin Linder, Hanna Wallach

Government: Faculty Publications

Research on the diffusion of political decisions across jurisdictions typically accounts for units’ influence over each other with (1) observable measures or (2) by inferring latent network ties from past decisions. The former approach assumes that interdependence is static and perfectly captured by the data. The latter mitigates these issues but requires analytical tools that are separate from the main empirical methods for studying diffusion. As a solution, we introduce network event history analysis (NEHA), which incorporates latent network inference into conventional discrete-time event history models. We demonstrate NEHA’s unique methodological and substantive benefits in applications to policy adoption in …

Highly Pathogenic Avian Influenza A(H5n1) Virus Outbreak In New England Seals, United States, Wendy Puryear, Kaitlin Sawatzki, Nichola Hill, Alexa Foss, Jonathon J. Stone, Lynda Doughty, Dominique Walk, Katie Gilbert, Maureen Murray, Elena Cox, Priya Patel, Zak Mertz, Stephanie Ellis, Jennifer Taylor, Deborah Fauquier, Ainsley Smith, Robert A. Digiovanni, Adriana Van De Guchte, Ana Silvia Gonzalez-Reiche, Zain Khalil, Harm Van Bakel, Mia K. Torchetti, Kristina Lantz, Julianna B. Lenoch, Jonathan Runstadler

United States Department of Agriculture Wildlife Services: Staff Publications

We report the spillover of highly pathogenic avian influenza A(H5N1) into marine mammals in the northeastern United States, coincident with H5N1 in sympatric wild birds. Our data indicate monitoring both wild coastal birds and marine mammals will be critical to determine pandemic potential of influenza A viruses.

Viscous Thin-Film Models Of Nanoscale Self-Organization Under Ion Bombardment, Tyler Evans

Mathematics Theses and Dissertations

For decades, it has been observed that broad-beam irradiation of semiconductor surfaces can lead to spontaneous self-organization into highly regular patterns, sometimes at length scales of only a few nanometers. Initial theory was largely based on erosion and redistribution of material occurring on fast time scales, which are able to produce good agreement with certain aspects of surface evolution. However, further experimental and theoretical work eventually led to the realization that numerous effects are active in the irradiated target, including stresses associated with ion-implantation and the accumulation of damage leading to the development of a disordered, amorphous layer atop the …

Practical Implementation Of The Immersed Interface Method With Triangular Meshes For 3d Rigid Solids In A Fluid Flow, Norah Hakami

Mathematics Theses and Dissertations

When employing the immersed interface method (IIM) to simulate a fluid flow around a moving rigid object, the immersed object can be replaced by a virtual fluid enclosed by singular forces on the interface between the real and virtual fluids. These forces represent the impact of the rigid motion on the fluid flow and cause jump discontinuities across the interface in the whole flow field. Then, the IIM resolves the fluid flow on a fixed computational domain by directly incorporating the jump conditions across the interface into numerical schemes. Previous development of the method is limited to simple smooth boundaries. …

Exploring Protein Conformations And Functions Through Molecular Dynamics Simulations And Machine Learning, Hao Tian

Chemistry Theses and Dissertations

Proteins are essential biomacromolecules that perform a variety of critical functions in living organisms. The tertiary structure of a protein plays a crucial role in its biological activity as it determines how the protein interacts with other molecules. Consequently, understanding protein conformation and function is an important area of research with implications in medicine, biotechnology, and other fields.

The first part of this dissertation focuses on protein allostery, a process by which proteins transmit perturbations caused by binding at one site to a distal site, thereby regulating activity. With the development of computational methods like molecular dynamics simulations and machine …

Novel Generalizations And Algorithms For The Max-K-Coverage Problem, Luc Cote

Computer Science Senior Theses

In this thesis we consider the fundamental optimization problem known as the Max-k- Coverage problem and its generalizations. We first discuss the well-studied generalization to the problem of maximizing a monotone submodular function subject to a cardinality constraint and introduce a new primal-dual algorithm which achieves the optimal approximation factor of (1 − 1/e). While greedy algorithms have been known to achieve this approximation factor, our algorithms also provide a dual certificate which upper bounds the optimum value of an instance. This certificate may be used in practice to provide much stronger guarantees than the worst-case (1 − 1/e) approximation …

An Empirical Study Of Locality-Sensitive Hashing To Approximate The Minimum Spanning Tree, Elizabeth Crocker

Computer Science Senior Theses

The minimum spanning tree is a problem with important applications but for which there are no known efficient algorithms for large data sets. Locality-sensitive hashing has been used to solve the near-neighbor problem and further applications in clustering, which indicates its potential for approximating the minimum spanning tree as well. An algorithm by Sariel Har-Peled, Piotr Indyk, and Rajeev Motwani utilizes locality-sensitive hashing to provide a c-approximation of the minimum spanning tree in O(dn^1+1/c log² n) time. In this thesis, we implement and test this algorithm. We determine that the algorithm is suited to provide a better-than-random approximation …

Counting Elliptic Curves With A Cyclic M-Isogeny Over Q, Grant S. Molnar

Dartmouth College Ph.D Dissertations

Using methods from analytic number theory, for m > 5 and for m = 4, we obtain asymptotics with power-saving error terms for counts of elliptic curves with a cyclic m-isogeny up to quadratic twist over the rational numbers. For m > 5, we then apply a Tauberian theorem to achieve asymptotics with power saving error for counts of elliptic curves with a cyclic m-isogeny up to isomorphism over the rational numbers.

Measuring Radiation Protection: Partners From Across The Nuclear Enterprise Evaluate The Radiation Protection Of Us Army Vehicles, Andrew W. Decker, Robert Prins

Faculty Publications

Recent mounting nuclear threats and postures from adversary nation-states, such as Russia, China, North Korea, and Iran, represent a clear danger to the interests and security of the United States of America and its Allies. To meet these threats, the 2022 Nuclear Posture Review requires the Department of Defense (DoD) to design, develop, and manage a combat-credible U.S. military which, among other prioritizations, is survivable. A survivable force can generate combat power despite adversary attacks. As such, the US Army must prepare today to set the conditions for successful conventional warfare on the nuclear battlefields of tomorrow. Our Army cannot …

A Node Elimination Algorithm For Cubatures Of High-Dimensional Polytopes, Arkadijs Slobodkins

Mathematics Theses and Dissertations

Node elimination is a numerical approach for obtaining cubature rules for the approximation of multivariate integrals over domains in Rⁿ. Beginning with a known cubature, nodes are selected for elimination, and a new, more efficient rule is constructed by iteratively solving the moment equations. In this work, a new node elimination criterion is introduced that is based on linearization of the moment equations. In addition, a penalized iterative solver is introduced that ensures positivity of weights and interiority of nodes. We aim to construct a universal algorithm for convex polytopes that produces efficient cubature rules without any user …

In Situ Microwave Fixation Provides An Instantaneous Snapshot Of The Brain Metabolome, Jelena A. Juras, Madison B. Webb, Lyndsay E. A. Young, Kia H. Markussen, Tara R. Hawkinson, Michael D. Buoncristiani, Kayli E. Bolton, Peyton T. Coburn, Meredith I. Williams, Lisa P. Y. Sun, William C. Sanders, Ronald C. Bruntz, Lindsey R. Conroy, Chi Wang, Matthew S. Gentry, Bret N. Smith, Ramon C. Sun

Markey Cancer Center Faculty Publications

Brain glucose metabolism is highly heterogeneous among brain regions and continues postmortem. In particular, we demonstrate exhaustion of glycogen and glucose and an increase in lactate production during conventional rapid brain resection and preservation by liquid nitrogen. In contrast, we show that these post- mortem changes are not observed with simultaneous animal sacrifice and in situ fixation with focused, high- power microwave. We further employ microwave fixation to define brain glucose metabolism in the mouse model of streptozotocin-induced type 1 diabetes. Using both total pool and isotope tracing analyses, we identified global glucose hypometabolism in multiple brain regions, evidenced by …

Targeting Lncrna Ddit4-As1 Sensitizes Triple Negative Breast Cancer To Chemotherapy Via Suppressing Of Autophagy, Ting Jiang, Jiaojiao Zhu, Shilong Jiang, Zonglin Chen, Ping Xu, Rong Gong, Changxin Zhong, Yueying Cheng, Xinyuan Sun, Wenjun Yi, Jinming Yang, Wenhu Zhou, Yan Cheng

Markey Cancer Center Faculty Publications

In this study, it is found that the lncRNA, DNA damage inducible transcript 4 antisense RNA1 (DDIT4-AS1), is highly expressed in triple-negative breast cancer (TNBC) cell lines and tissues due to H3K27 acetylation in the promoter region, and promotes the proliferation, migration, and invasion of TNBC cells via activating autophagy. Mechanistically, it is shown that DDIT4-AS1 induces autophagy by stabilizing DDIT4 mRNA via recruiting the RNA binding protein AUF1 and promoting the interaction between DDIT4 mRNA and AUF1, thereby inhibiting mTOR signaling pathway. Furthermore, silencing of DDIT4-AS1 enhances the sensitivity of TNBC cells to chemotherapeutic agents such as paclitaxel both …