Physical Sciences and Mathematics Commons^™

Riding The Decarbonisation Wave: Bhp And Its Lng Dual-Fuelled Vessels, Shantanu Bhattacharya, Flocy Joseph, Mahima Rao-Kachroo

Asian Management Insights

What does it take to decarbonise charter-related shipping?

Building Urban Sustainability With Quality Elites, Havovi Joshi

Asian Management Insights

Do elites contribute to a society more than they extract from it? In many countries where populism has surged in tandem with declining trust in elites in the political and other spheres, the answer.

Oxidative Stress In Health And Disease, V. Prakash Reddy

Chemistry Faculty Research & Creative Works

Oxidative stress, resulting from the excessive intracellular accumulation of reactive oxygen species (ROS), reactive nitrogen species (RNS), and other free radical species, contributes to the onset and progression of various diseases, including diabetes, obesity, diabetic nephropathy, diabetic neuropathy, and neurological diseases, such as Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and Parkinson's disease (PD). Oxidative stress is also implicated in cardiovascular disease and cancer. Exacerbated oxidative stress leads to the accelerated formation of advanced glycation end products (AGEs), a complex mixture of crosslinked proteins and protein modifications. Relatively high levels of AGEs are generated in diabetes, obesity, AD, and other …

Motif-Cluster: A Spatial Clustering Package For Repetitive Motif Binding Patterns, Mengyuan Zhou

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Previous efforts in using genome-wide analysis of transcription factor binding sites (TFBSs) have overlooked the importance of ranking potential significant regulatory regions, especially those with repetitive binding within a local region. Identifying these homogenous binding sites is critical because they have the potential to amplify the binding affinity and regulation activity of transcription factors, impacting gene expression and cellular functions. To address this issue, we developed an open-source tool Motif-Cluster that prioritizes and visualizes transcription factor regulatory regions by incorporating the idea of local motif clusters. Motif-Cluster can rank the significant transcription factor regulatory regions without the need for experimental …

Usually, Either Left And Right Brains Are Equally Active Or Only One Of Them Is Active: First-Principles Explanation, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

It is known that in most practical situations, either both left and right brains are equally active, or only one of them is active. A recent paper showed that this empirical phenomenon can be explained by a realistic model of the brain effectiveness. In this paper, we show that this conclusion can be made without any specific assumptions about the brain, based on first principles.

How To Efficiently Propagate P-Box Uncertainty, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, to get the desired estimate or prediction, we need to process existing data. This data usually comes from measurements, and measurements are never 100% accurate. Because we only know the input values with uncertainty, the results of processing this data also comes with uncertainty. To make an appropriate decision, we need to know how accurate is the resulting estimate, i.e., how the input uncertainty "propagates" through the data processing algorithm. In the ideal case, when we know the probability distribution of each measurement error, we can, in principle, use Monte-Carlo simulations to describe the uncertainty of …

The Emirates At 2050: Balancing Development And Environmental Stewardship, John A. Burt, Noura Al-Mansoori, Ivonne Bejarano, Gary Brown, Oscar Campbell, Johannes Els, Gary R. Feulner, Guillermo Friis-Montoya, Aaron Henderson, Natural History Museum Abu Dhabi Howarth, Brigitte (Department Of Culture And Tourism, , Abu Dhabi, United Arab Emirates , Abu Dhabi, United Arab Emirates, David M. John, Jacky Judas, Daniel Mateos-Molina, Matthew Mitchell, Ada Natoli, Francesco Paparella, Fadi (Hefaiyah Mountain Conservation Centre Yaghmour, , Environment And Protected Areas Authority, Kalba, Sharjah, United Arab Emirates , Environment And Protected Areas Authority, Kalba, Sharjah, United Arab Emirates

All Works

The United Arab Emirates (UAE) faces the challenge of balancing rapid economic development with environmental preservation and conservation in the Anthropocene era. The nation’s unique ecosystems, characterized by arid desert, rugged mountains, and diverse marine habitats, are vulnerable to disturbances such as urbanization, habitat degradation, groundwater extraction and climate change. To chart a more sustainable course for the Emirates by 2050, the paper proposes policy recommendations such as adopting a national strategy for sustainable development, strengthening environmental policies, investing in urban planning and design, promoting sustainable water management, encouraging use of nature-based solutions, addressing climate change, fostering environmental education, supporting …

Leveraging Long Short-Term User Preference In Conversational Recommendation Via Multi-Agent Reinforcement Learning, Yang Deng, Yaliang Li, Bolin Ding, Wai Lam

Research Collection School Of Computing and Information Systems

Conversational recommender systems (CRS) endow traditional recommender systems with the capability of dynamically obtaining users’ short-term preferences for items and attributes through interactive dialogues. There are three core challenges for CRS, including the intelligent decisions for what attributes to ask, which items to recommend, and when to askor recommend, at each conversation turn. Previous methods mainly leverage reinforcement learning (RL) to learn conversational recommendation policies for solving one or two of these three decision-making problems in CRS with separated conversation and recommendation components. These approaches restrict the scalability and generality of CRS and fall short of preserving a stable training …

Modeling Overdraft-Driven Nitrate Transport In Shallow Wells For Mitigation And Scenario Planning, Jonathan Cronk

Department of Biological Systems Engineering: Dissertations and Theses

In Nebraska, average nitrate concentrations in groundwater have doubled since 1974, making water quality management more important than ever. As droughts, heat waves, and floods become more common climate events, understanding their impacts will be necessary to make informed management decisions. Emerging literature describes that drought correlates to an increase in the concentration of nitrate-N at domestic and irrigation wells, however the relative contributions of the mechanisms thought to be responsible is currently unknown.

This research assessed the impact of recharge and pumping rate changes as two mechanisms affecting nitrate-N concentration during drought, assessed the relationship between well depth and …

Optimizing Uncertainty Quantification Of Vision Transformers In Deep Learning On Novel Ai Architectures, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja

Computer Science: Faculty Publications and Other Works

Deep Learning (DL) methods have shown substantial efficacy in computer vision (CV) and natural language processing (NLP). Despite their proficiency, the inconsistency in input data distributions can compromise prediction reliability. This study mitigates this issue by introducing uncertainty evaluations in DL models, thereby enhancing dependability through a distribution of predictions. Our focus lies on the Vision Transformer (ViT), a DL model that harmonizes both local and global behavior. We conduct extensive experiments on the ImageNet-1K dataset, a vast resource with over a million images across 1,000 categories. ViTs, while competitive, are vulnerable to adversarial attacks, making uncertainty estimation crucial for …

Impact Of Silicon Ion Irradiation On Aluminum Nitride-Transduced Microelectromechanical Resonators, David D. Lynes, Joshua Young, Eric Lang, Hengky Chandrahalim

Faculty Publications

Microelectromechanical systems (MEMS) resonators use is widespread, from electronic filters and oscillators to physical sensors such as accelerometers and gyroscopes. These devices' ubiquity, small size, and low power consumption make them ideal for use in systems such as CubeSats, micro aerial vehicles, autonomous underwater vehicles, and micro-robots operating in radiation environments. Radiation's interaction with materials manifests as atomic displacement and ionization, resulting in mechanical and electronic property changes, photocurrents, and charge buildup. This study examines silicon (Si) ion irradiation's interaction with piezoelectrically transduced MEMS resonators. Furthermore, the effect of adding a dielectric silicon oxide (SiO₂) thin film is …

Enhancing Search Engine Results: A Comparative Study Of Graph And Timeline Visualizations For Semantic And Temporal Relationship Discovery, Muhammad Shahiq Qureshi

Electronic Theses and Dissertations

In today’s digital age, search engines have become indispensable tools for finding information among the corpus of billions of webpages. The standard that most search engines follow is to display search results in a list-based format arranged according to a ranking algorithm. Although this format is good for presenting the most relevant results to users, it fails to represent the underlying relations between different results. These relations, among others, can generally be of either a temporal or semantic nature. A user who wants to explore the results that are connected by those relations would have to make a manual effort …

Hydroxyapatite-Based Coatings On Silicon Wafers And Printed Zirconia, Antoine Chauvin

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Dental surgery needs a naturally attract implant design that can ensure both osseointegration and soft tissue integration. Hydroxyapatite (HAp), the main mineral constituent of dentine and tooth enamel, is commonly used as a coating component, notably for overlaying titanium– or ceramics–based implants. This thesis aims to investigate the behavior of a HAp-based coating, specifically designed to be compatible with a porous substrate. Coating layers are made by sol–gel dip coating by immersion of porous substrates made by additive manufacturing into solutions of HAp, having been mixed with polyethyleneimine (PEI), to improve the adhesion of HAp on the substrate. First, the …

Digital Twins Of The Living Knee: From Measurements To Model, Thor Erik Andreassen

Electronic Theses and Dissertations

Modern medicine has dramatically improved the lives of many. In orthopaedics, robotic surgery has given clinicians superior accuracy when performing interventions over conventional methods. Nevertheless, while these and many other methods are available to ensure treatments are performed successfully, far fewer methods exist to predict the proper treatment option for a given person. Clinicians are forced to categorize individuals, choosing the best treatment on “average.” However, many individuals differ significantly from the “average” person, for which many of these treatments are designed. Going forward, a method of testing, evaluating, and predicting different treatment options' short- and long-term effects on an …

Understanding The Contribution Of Recommendation Algorithms On Misinformation Recommendation And Misinformation Dissemination On Social Networks, Royal Pathak, Francesca Spezzano, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Social networks are a platform for individuals and organizations to connect with each other and inform, advertise, spread ideas, and ultimately influence opinions. These platforms have been known to propel misinformation. We argue that this could be compounded by the recommender algorithms that these platforms use to suggest items potentially of interest to their users, given the known biases and filter bubbles issues affecting recommender systems. While much has been studied about misinformation on social networks, the potential exacerbation that could result from recommender algorithms in this environment is in its infancy. In this manuscript, we present the result of …

Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System, Michael Morikone

Complex Biosystems PhD Program: Dissertations

The task of gene prediction has been largely stagnant in algorithmic improvements compared to when algorithms were first developed for predicting genes thirty years ago. Rather than iteratively improving the underlying algorithms in gene prediction tools by utilizing better performing models, most current approaches update existing tools through incorporating increasing amounts of extrinsic data to improve gene prediction performance. The traditional method of predicting genes is done using Hidden Markov Models (HMMs). These HMMs are constrained by having strict assumptions made about the independence of genes that do not always hold true. To address this, a Convolutional Neural Network (CNN) …

Transforming Agriculture In The Pilbara: Newman Managed Aquifer Recharge (Mar) Feasibility Assessment, Michael J. Donn, Joanne L. Vanderzalm, Olga V. Barron

Natural resources commissioned reports

In the Newman region, DPIRD commissioned an assessment of the potential for managed aquifer recharge (MAR) near Newman using surplus water resulting from mine dewatering as the water supply for irrigated agriculture. The objectives of the MAR assessment were to:

• identify focus area for MAR feasibility assessment within the initial larger area of interest for MAR
• assess the viability of MAR with mine dewater near Newman to support development of irrigated agriculture, in keeping with national and state MAR guidelines
• identify key risks associated with MAR with mine dewater for irrigation supply, and identify knowledge/investigation required to adequately assess risks …

Comparison Of Ceneb And Cohyst Hydrologic Models Within A Common Domain In Central Nebraska, William R. Moak

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

The Nebraska Department of Natural Resources (NDNR) has developed several hydrologic models to help effectively manage water resources in the state. These models guide water managers to allocate surface and groundwater supplies to a range of uses (irrigation, environmental protection, interstate water agreements) and evaluate the impacts of changes to the surface water-groundwater system (e.g., new wells, evolving recharge patterns). Two such models, the Central Nebraska (CENEB) model and the Cooperative Hydrology Study (COHYST) model cover north central and south central Nebraska, respectively, but the model domains overlap along a west-east strip between the Platte and Loup Rivers, enabling direct …

A Climatology Of Mesoscale Airmasses With High Theta-E, Charles J. Kropiewnicki

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

A Mesoscale Airmass with High Theta-E (MAHTE) is a narrow region of larger theta-e located on the cool side of an airmass boundary. MAHTEs typically possesses higher CAPE than the warm side of the boundary, creating a more favorable environment for severe convection. MAHTEs can also be characterized by larger low-level shear and lower LCLs and may also have a propensity for supporting tornadogenesis. The majority of MAHTE research to date has been comprised of case studies, and the prevalence of MAHTEs is not well understood. This project fills that knowledge gap by creating a climatology of MAHTE occurrence. This …

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

Tennessee Climate Office Monthly Report

No abstract provided.

Cfa-Treated Mice Induce Hyperalgesia In Healthy Mice Via An Olfactory Mechanism, Yangmiao Zhang, Wentai Luo, Maryt M. Heinricher, Andrey E. Ryabinin

Chemistry Faculty Publications and Presentations

Background

Social interactions with subjects experiencing pain can increase nociceptive sensitivity in observers, even without direct physical contact. In previous experiments, extended indirect exposure to soiled bedding from mice with alcohol withdrawal-related hyperalgesia enhanced nociception in their conspecifics. This finding suggested that olfactory cues could be sufficient for nociceptive hypersensitivity in otherwise untreated animals (also known as “bystanders”).

Aim

The current study addressed this possibility using an inflammation-based hyperalgesia model and long- and short-term exposure paradigms in C57BL/6J mice.

Materials & Method

Adult male and female mice received intraplantar injection of complete Freund's adjuvant (CFA) and were used as stimulus …

Complex Knowledge Base Question Answering: A Survey, Yunshi Lan, Gaole He, Jinhao Jiang, Jing Jiang, Zhao Wayne Xin, Ji Rong Wen

Research Collection School Of Computing and Information Systems

Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Early studies mainly focused on answering simple questions over KBs and achieved great success. However, their performances on complex questions are still far from satisfactory. Therefore, in recent years, researchers propose a large number of novel methods, which looked into the challenges of answering complex questions. In this survey, we review recent advances in KBQA with the focus on solving complex questions, which usually contain multiple subjects, express compound relations, or involve numerical operations. In detail, we begin with introducing the complex KBQA task and …

Turn-It-Up: Rendering Resistance For Knobs In Virtual Reality Through Undetectable Pseudo-Haptics, Martin Feick, Andre Zenner, Oscar Ariza, Anthony Tang, Cihan Biyikli, Antonio Kruger

Research Collection School Of Computing and Information Systems

Rendering haptic feedback for interactions with virtual objects is an essential part of effective virtual reality experiences. In this work, we explore providing haptic feedback for rotational manipulations, e.g., through knobs. We propose the use of a Pseudo-Haptic technique alongside a physical proxy knob to simulate various physical resistances. In a psychophysical experiment with 20 participants, we found that designers can introduce unnoticeable offsets between real and virtual rotations of the knob, and we report the corresponding detection thresholds. Based on these, we present the Pseudo-Haptic Resistance technique to convey physical resistance while applying only unnoticeable pseudo-haptic manipulation. Additionally, we …

Quantumeyes: Towards Better Interpretability Of Quantum Circuits, Shaolun Ruan, Qiang Guan, Paul Griffin, Ying Mao, Yong Wang

Research Collection School Of Computing and Information Systems

Quantum computing offers significant speedup compared to classical computing, which has led to a growing interest among users in learning and applying quantum computing across various applications. However, quantum circuits, which are fundamental for implementing quantum algorithms, can be challenging for users to understand due to their underlying logic, such as the temporal evolution of quantum states and the effect of quantum amplitudes on the probability of basis quantum states. To fill this research gap, we propose QuantumEyes, an interactive visual analytics system to enhance the interpretability of quantum circuits through both global and local levels. For the global-level analysis, …

Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel. Chen, Nan Hu, Peng. Liang, Morgan. Swink

Research Collection School Of Computing and Information Systems

Integrating the real options perspective and resource dependence theory, this study examines how firms adjust their innovation investments to trade policy effect uncertainty (TPEU), a less studied type of firm specific, perceived environmental uncertainty in which managers have difficulty predicting how potential policy changes will affect business operations. To develop a text-based, context-dependent, time-varying measure of firm-level perceived TPEU, we apply Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art deep learning approach. We apply BERT to analyze the texts of mandatory Management Discussion and Analysis (MD&A) sections of annual reports for a sample of 22,669 firm-year observations from 3,181 unique …

An Idealist’S Approach For Smart Contract Correctness, Duy Tai Nguyen, Hong Long Pham, Jun Sun, Quang Loc Le

Research Collection School Of Computing and Information Systems

In this work, we experiment an idealistic approach for smart contract correctness verification and enforcement, based on the assumption that developers are either desired or required to provide a correctness specification due to the importance of smart contracts and the fact that they are immutable after deployment. We design a static verification system with a specification language which supports fully compositional verification (with the help of function specifications, contract invariants, loop invariants and call invariants). Our approach has been implemented in a tool named iContract which automatically proves the correctness of a smart contract statically or checks the unverified part …

Npf-200: A Multi-Modal Eye Fixation Dataset And Method For Non-Photorealistic Videos, Ziyu Yang, Sucheng Ren, Zongwei Wu, Nanxuan Zhao, Junle Wang, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Non-photorealistic videos are in demand with the wave of the metaverse, but lack of sufficient research studies. This work aims to take a step forward to understand how humans perceive nonphotorealistic videos with eye fixation (i.e., saliency detection), which is critical for enhancing media production, artistic design, and game user experience. To fill in the gap of missing a suitable dataset for this research line, we present NPF-200, the first largescale multi-modal dataset of purely non-photorealistic videos with eye fixations. Our dataset has three characteristics: 1) it contains soundtracks that are essential according to vision and psychological studies; 2) it …

Disentangling Multi-View Representations Beyond Inductive Bias, Guanzhou Ke, Yang Yu, Guoqing Chao, Xiaoli Wang, Chenyang Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

Multi-view (or -modality) representation learning aims to understand the relationships between different view representations. Existing methods disentangle multi-view representations into consistent and view-specific representations by introducing strong inductive biases, which can limit their generalization ability. In this paper, we propose a novel multi-view representation disentangling method that aims to go beyond inductive biases, ensuring both interpretability and generalizability of the resulting representations. Our method is based on the observation that discovering multi-view consistency in advance can determine the disentangling information boundary, leading to a decoupled learning objective. We also found that the consistency can be easily extracted by maximizing the …

Opportunities For Spatial Database Research In The Context Of Preference Queries, Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

This is the outline of the keynote speech at LocalRec@ACM SIGSPATIAL 2023. The main objective of the talk is to point out opportunities for spatial database researchers in the area of preference-based querying. We will commence with an overview of the standard queries for multi-objective decision making, and demonstrate their direct connection to recommendations and to market analysis. In this context, there is a number of specific decision criteria, and user preferences are represented as vectors with as many dimensions. We will demonstrate how and why this type of preferences are natural to actual applications and practical for the support …

Towards Llm-Based Fact Verification On News Claims With A Hierarchical Step-By-Step Prompting Method, Xuan Zhang, Wei Gao

Research Collection School Of Computing and Information Systems

While large pre-trained language models (LLMs) have shown their impressive capabilities in various NLP tasks, they are still underexplored in the misinformation domain. In this paper, we examine LLMs with in-context learning (ICL) for news claim verification, and find that only with 4-shot demonstration examples, the performance of several prompting methods can be comparable with previous supervised models. To further boost performance, we introduce a Hierarchical Step-by-Step (HiSS) prompting method which directs LLMs to separate a claim into several subclaims and then verify each of them via multiple questionsanswering steps progressively. Experiment results on two public misinformation datasets show that …