Physical Sciences and Mathematics Commons^™

Plasma-Laser Wakefield Acceleration, Jonathan Babu

Physics

Many texts detailing the derivations and science of Wakefield Acceleration are aimed at graduate and doctorate level scholars, and these may seem intimidating to new physics students. This paper is meant to be an introduction to the nature of plasmas, lasers, laser-plasma interactions, and Laser Wakefield Acceleration (LWFA), with sources given where extra detail may be required. I recognize that this paper is not meant to be an all-encompassing review on the nature of the topics, as these topics are complex and subject of entire textbooks. Instead, I aim to provide an introduction to these topics to a college-level scholar …

Swarming Oscillators With Time-Delayed Interactions, Nicholas S. Blum

Physics

We investigate the role of delay in the collective dynamics of particles that swarm in space and possess an internal oscillatory degree of freedom, called swarmalators. Swarmalators were introduced recently by O’Keeffe, Hong, and Strogatz in Nature Communications 8, 1504 (2017). The addition of a time delay into the system of swarmalators was motivated by the biology of early embryonic development. This delay leads to a rich phenomenology, which includes two new collective states, which we call "semi-static crystal" and "boiling". In the semi-static crystal state, all particles in a cluster undergo decaying radial oscillations completely in phase with one …

A Comparative Study Of Machine Learning-Based Approach For Network Traffic Classification, Kien Trang, An Hoang Nguyen

Knowledge Engineering and Data Science

Internet usage has increased rapidly and become an essential part of human life, corresponding to the rapid development of network infrastructure in recent years. Thus, protecting users’ confidential information when joining the global network becomes one of the most significant considerations. Even though multiple encryption algorithms and techniques have been applied in different parties, including internet providers, and web hosting, this situation also allows the hacker to attack the network system anonymously. Therefore, the significance of classifying network data streams to improve network system quality and security is attracting increasing study interests. This work introduces a machine learning-based approach to …

Early Prediction Of Hate Speech Propagation, Ken-Yu Lin, Roy Ka-Wei Lee, Wei Gao, Wen-Chih Peng

Research Collection School Of Computing and Information Systems

Online hate speech has disrupted the social connectedness in online communities and raises public safety concerns in our societies. Motivated by this rising issue, researchers have developed many machine learning and deep learning methods to detect hate speech in social media automatically. However, most of the existing automated solutions have focused on detecting hate speech in a single post, neglecting the network and information propagation effects of social media platforms. Ideally, the content moderators would want to identify the hateful posts and monitor posts and threads that are likely to induce hate. This paper aims to address this research gap …

Efficient Reinforcement Learning In Resource Allocation Problems Through Permutation Invariant Multi-Task Learning, Desmond Cai, Shiau Hong Lim, Laura Wynter

Research Collection School Of Computing and Information Systems

One of the main challenges in real-world reinforcement learning is to learn successfully from limited training samples. We show that in certain settings, the available data can be dramatically increased through a form of multi-task learning, by exploiting an invariance property in the tasks. We provide a theoretical performance bound for the gain in sample efficiency under this setting. This motivates a new approach to multi-task learning, which involves the design of an appropriate neural network architecture and a prioritized task-sampling strategy. We demonstrate empirically the effectiveness of the proposed approach on two real-world sequential resource allocation tasks where this …

Self-Supervised Learning Disentangled Group Representation As Feature, Tan Wang, Zhongqi Yue, Jianqiang Huang, Qianru Sun, Hanwang Zhang

Research Collection School Of Computing and Information Systems

A good visual representation is an inference map from observations (images) to features (vectors) that faithfully reflects the hidden modularized generative factors (semantics). In this paper, we formulate the notion of “good” representation from a group-theoretic view using Higgins’ definition of disentangled representation [38], and show that existing Self-Supervised Learning (SSL) only disentangles simple augmentation features such as rotation and colorization, thus unable to modularize the remaining semantics. To break the limitation, we propose an iterative SSL algorithm: Iterative Partition-based Invariant Risk Minimization (IP-IRM), which successfully grounds the abstract semantics and the group acting on them into concrete contrastive learning. …

Ai And The Future Of Work: What We Know Today, Steven M. Miller, Thomas H. Davenport

Research Collection School Of Computing and Information Systems

To contribute to a better understanding of the contemporary realities of AI workplace deployments, the authors recently completed 29 case studies of people doing their everyday work with AI-enabled smart machines. Twenty-three of these examples were from North America, mostly in the US. Six were from Southeast Asia, mostly in Singapore. In this essay, we compare our findings on job and workplace impacts to those reported in the MIT Task Force on the Work of the Future report, as we consider that to be the most comprehensive recent study on this topic.

Etherlearn: Decentralizing Learning Via Blockchain, Nguyen Binh Duong Ta, Tian Jun Joel Yang

Research Collection School Of Computing and Information Systems

In institutes of higher learning, most of the time course material development and delivery follow a centralized model which is fully lecturer-controlled. In this model, engaging students as partners in learning is a challenging problem as: 1) students are usually hesitant to contribute due to the fear of getting it wrong, 2) not much incentive for them to put in the extra effort, and 3) current online learning systems lack adequate facilities to support seamless and anonymous interactions between students. In this work, we propose EtherLearn, a blockchain based peer-learning system to distribute the control of how course material and …

Checking Smart Contracts With Structural Code Embedding, Zhipeng Gao, Lingxiao Jiang, Xin Xia, David Lo, John Grundy

Research Collection School Of Computing and Information Systems

Smart contracts have been increasingly used together with blockchains to automate financial and business transactions. However, many bugs and vulnerabilities have been identified in many contracts which raises serious concerns about smart contract security, not to mention that the blockchain systems on which the smart contracts are built can be buggy. Thus, there is a significant need to better maintain smart contract code and ensure its high reliability. In this paper, we propose an automated approach to learn characteristics of smart contracts in Solidity, useful for repetitive contract code, bug detection and contract validation. Our new approach is based on …

Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites - Field Sampling Plan (Fsp) Bres No. 154 – Clark Mill Tailings Ne., Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Study Of The Cell Membrane And The Synthesis Of Chimeric Human Bacterial Phospholipids, Opeyemi O. Tade

Electronic Theses and Dissertations

Phospholipid bilayers are the principal component of the cell membrane. Membranes ensure the maintenance of processes required for cells’ survival by regulating the inflow and outflow of nutrients and other molecules using membrane proteins. However, studying the cell membrane is challenging because of its complexity and small size. In-vitro membrane models made of phospholipids are important tools for studying membranes. In this work, we aim to study the fluidity of phospholipid bilayers of different lipids using general polarization (GP) of the fluorescent probe Laurdan as a measure. We will focus on the relative importance of head groups and fatty acids …

Functional Mixed Data Clustering With Fourier Basis Smoothing, Ishmael Amartey

Electronic Theses and Dissertations

Clustering is an important analytical technique that has proven to affect human life positively through its application in cancer research, market segmentation, city planning etc. In this time of growing technological systems, mixed data has seen another face of longitudinal, directional and functional attributes which is worth paying attention to and analyzing. Previous research works on clustering relied largely on the inverse weight technique and B-spline in smoothing data and assessing the performance of various clustering algorithms. In 1971, Gower proposed a method of clustering for mixed variable types which has been extended to include functional and directional variables by …

Distinguishing Mustela From Neogale (Mustelidae) Through Both A Qualitative And Quantitative Analysis Of Skull And Tooth Morphology, Ronald W. Peery

Electronic Theses and Dissertations

Weasels and mink (Mustela and Neogale) can be difficult to distinguish osteologically due to similarities in morphology, thus suggesting the need for an accurate tool in distinguishing among taxa. This study utilized a combination of character state and stepwise discriminant function (DFA) analyses to examine potential distinguishing features of skull and tooth morphology. Measurements and ratios were collected from all 18 extant musteline species, as well as the extinct Neovison macrodon, Mustela rexroadensis, Mustela meltoni, Mustela gazini, and Mustela jacksoni. Unidentified musteline specimens from the Gray Fossil Site were also included. Results of …

Symmetric Representations Of Finite Groups And Related Topics, Connie Corona

Electronic Theses, Projects, and Dissertations

In this thesis, we have presented our discovery of original symmetric presentations of a number of non-abelian simple groups, including several sporatic groups, linear groups, and classical groups.

We have constructed, using our technique of double coset enumeration, J2, M₁₂, J₁, PSU(3, 3):2, M₁₁, A₁₀, S(4,3), M₂₂:2, PSL(3, 4), S₆, 2:S₅, 2:PSL(3, 4) as homomorphic images of the involutory progenitors 2^*32:(2⁵:A₅), 2^*110: PSL(2, 11), 2^*5:A₅, 3^*4:D₈, 2^*110:PSL(2, 11), …

Preparation And Study Of Bacterial Membrane Models, Enoch Asimbisa

Electronic Theses and Dissertations

Fuel molecules are organic solvents that have disruptive effects on the bacterial membrane. This is a significant barrier in biofuel production, as it limits the fuel concentration that can be achieved through fermentation. One potential way of overcoming this barrier is to identify lipid compositions that can better withstand solvent stress, for which it is important to understand how organic solvents disrupt the membrane. Use of biophysical characterization techniques to quantify physical properties like fluidity and thickness will enable us to understand the mechanism by which solvents disrupt membranes. Native membranes are very complex, and we sought to develop in-vitro …

Synthesis Of Phytosulfokine Analogs As Probes For Studying Plant Signaling And Molecular Trafficking, Thomas Ntim

Electronic Theses and Dissertations

Plants are exposed to a wide range of biotic and abiotic stresses that hinder their growth and reduce crop productivity. In their adaptive response, plants use signaling molecules that are trafficked throughout the plant. This research focuses on the chemical synthesis and assessment of analogs of the plant signal phytosulfokine (PSK, a sulfated pentapeptide), its delivery to plants and its observation using a fiber-optic fluorescence microscope. PSK regulates growth, cell expansion, heat tolerance, and tissue longevity. Analogs of PSK were synthesized using solid-phase peptide synthesis. Pure PSK and TAMRA-labeled PSK were delivered into the wild-type Arabidopsis thaliana Col-0 and a …

Triple Oxygen Isotope Constraints On Atmospheric O2 And Biological Productivity During The Mid-Proterozoic, Peng Liu, Jingjin Liu, Aoshaung Ji, Christopher T. Reinhard, Noah J. Planavsky, Dmitri Babikov, Raymond G. Najjar, James F. Kasting

Chemistry Faculty Research and Publications

Reconstructing the history of biological productivity and atmospheric oxygen partial pressure (pO₂) is a fundamental goal of geobiology. Recently, the mass-independent fractionation of oxygen isotopes (O-MIF) has been used as a tool for estimating pO₂ and productivity during the Proterozoic. O-MIF, reported as Δ′¹⁷O, is produced during the formation of ozone and destroyed by isotopic exchange with water by biological and chemical processes. Atmospheric O-MIF can be preserved in the geologic record when pyrite (FeS₂) is oxidized during weathering, and the sulfur is redeposited as sulfate. Here, sedimentary sulfates from …

2d Covalent Organic Frameworks With An Incorporated Manganese Complex For Light Driven Carbon Dioxide Reduction, Denan Wang, Daniel Streater, Yun Peng, Jier Huang

Chemistry Faculty Research and Publications

Covalent organic frameworks (COFs) have emerged as a novel class of crystalline porous photocatalytic materials due to their unique properties such as large surface area, tunable porosity, and rigid structure. In this work, we report the direct incorporation of a manganese CO₂ molecular catalyst (MC) into COFs (Mn−TTA-COF) and the evaluation of its capability as photocatalyst for visible light driven CO₂ reduction to form CO. We found that the photocatalytic activity of Mn−TTA-COF is quite low, which mainly results from the elimination of the CO ligand in the Mn MC upon light illumination, rendering its short duration in …

Identification And Development Of Therapeutics For Covid-19, Halie M. Rando, Nils Wellhausen, Soumita Ghosh, Alexandra J. Lee, Anna Ada Dattoli, Fengling Hu, James Brian Byrd, Diane N. Rafizadeh, Ronan Lordan, Yanjun Qi, Yuchen Sun, Christian Brueffer, Jeffrey M. Field, Marouen Ben Guebila, Nafisa M. Jadavji, Ashwin N. Skelly, Bharath Ramsundar, Jinhui Wang, Rishi Raj Goel, Yoson Park, Simina M. Boca, Anthony Gitter, Casey S. Greene

Computer Science: Faculty Publications

After emerging in China in late 2019, the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread worldwide, and as of mid- 2021, it remains a significant threat globally. Only a few coronaviruses are known to infect humans, and only two cause infections similar in severity to SARS-CoV-2: Severe acute respiratory syndrome-related coronavirus, a species closely related to SARS-CoV-2 that emerged in 2002, and Middle East respiratory syndrome-related coronavirus, which emerged in 2012. Unlike the current pandemic, previous epidemics were controlled rapidly through public health measures, but the body of research investigating severe acute respiratory syndrome and Middle East …

Characterizing Long Covid: Deep Phenotype Of A Complex Condition, Rachel R. Deer, Madeline A. Rock, Nicole Vasilevsky, Leigh Carmody, Halie Rando, Alfred J. Anzalone, Marc D. Basson, Tellen D. Bennett, Timothy Bergquist, Eilis A. Boudreau, Carolyn T. Bramante, James Brian Byrd, Tiffany J. Callahan, Lauren E. Chan, Haitao Chu, Christopher G. Chute, Ben D. Coleman, Hannah E. Davis, Joel Gagnier, Casey S. Greene, William B. Hillegass, Ramakanth Kavuluru, Wesley D. Kimble, Farrukh M. Koraishy, Sebastian Köhler, Chen Liang, Feifan Liu, Hongfang Liu, Vithal Madhira, Charisse R. Madlock-Brown, Nicolas Matentzoglu, Diego R. Mazzotti

Computer Science: Faculty Publications

Background: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or “long COVID”), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies.

Methods: The Human Phenotype Ontology …

Changes In The Abundance And Distribution Of Benthic Mollusks In Polluted Sediments Of A Shallow Subtropical Estuary, Rachael Holtsberg Stark

Theses and Dissertations

The Indian River Lagoon (IRL) has been degraded by decades of eutrophication, and has accumulated an abundance of fine-grained, organic-rich sediments (muck). To quantify the impacts of organic sediments and environmental dredging, benthic mollusks were chosen to serve as bioindicators of environmental change, sediment health, and water quality. Data on species richness, biodiversity, and abundances was collected alongside sediment and water quality data before, during and after dredging. Organic sediment content was found to have an inverse logarithmic relationship benthic mollusk biodiversity, species richness, and abundance. Sediments low in percent organic content (0.7% to 6.1%) were located near the adjacent …

Development And Optimization Of A Denitrification System To Promote Biological Nutrient Removal In A Subtropical Estuary, Abigail Gering

Theses and Dissertations

Eutrophication impacts coastal ecosystems globally and triggers phytoplankton and algal blooms, leading to an increase in oxygen demand in the water column and sediments due to various biogeochemical processes. Naturally, biological nitrification, denitrification and anammox processes help to remove nitrogen predominately by nitrifying and denitrifying bacteria in the sediments. Eutrophic systems have increased nutrient and organic matter loading and are prone to the accumulation of ‘muddy’, fine-grained, organic-rich sediments (locally termed ‘muck’) that may not be able to support high enough populations of these bacteria, and therefore, may not adequately support nitrification/denitrification processes that would otherwise remove nitrogen. To decrease …

Identification And Characterization Of Bisbenzimide Compounds That Inhibit Human Cytomegalovirus Replication, Nicole Falci Finardi, Hyeongjun Kim, Lee Z. Hernandez, Matthew R. G. Russell, Catherine M-K Ho, Vattipally B. Sreenu, Hannah A. Wenham, Andy Merritt, Blair L. Strang

Physics & Astronomy Faculty Publications

The shortcomings of current anti-human cytomegalovirus (HCMV) drugs has stimulated a search for anti-HCMV compounds with novel targets. We screened collections of bioactive compounds and identified a range of compounds with the potential to inhibit HCMV replication. Of these compounds, we selected bisbenzimide compound RO-90-7501 for further study. We generated analogues of RO-90-7501 and found that one compound, MRT00210423, had increased anti-HCMV activity compared to RO-90-7501. Using a combination of compound analogues, microscopy and biochemical assays we found RO-90-7501 and MRT00210423 interacted with DNA. In single molecule microscopy experiments we found RO-90-7501, but not MRT00210423, was able to compact DNA, …

Temperature-Pressure Phase Diagrams Of Metal Nitrogen Compounds Through Density Functional Theory Computations And Thermodynamic Calculations, Hanof Alkhaldi

Chemistry & Biochemistry Dissertations - Archive

The need for novel materials for new generations of applications is growing tremendously. One of many pathways to attain new materials is the route of high pressure synthesis. A particular active area in this high–pressure research is to attain nitrogen-rich compounds. Many of these compounds discovered over the last decades have a potential use as hard material or as high–energy storage material. While it is not possible to predict a potential application for a compound before its experimental realization, it is worthy to explore beforehand what opportunities may exist. This kind of targeted development requires understanding of the synthesis process, …

Multinuclear Copper(I) And Silver(I) Pyrazolates: Synthesis, Luminescence, And Catalysis, Monika R. Patterson

Chemistry & Biochemistry Dissertations - Archive

Copper and silver pyrazolate complexes have numerous fascinating properties such as luminescence, catalytic ability, and complexation with small molecules. Using both more widely studied non-fluorinated pyrazolates and less common highly fluorinated pyrazolates as supporting ligands, we successfully synthesized and investigated several new coinage metal complexes. Synthetic details, structures, and properties i.e., luminescence and catalytic ability, have been studied. Chapter 2 of this research describes the synthesis of a new pyrazole with highly fluorinated aryl groups and corresponding trinuclear copper(I), silver(I), and gold(I) complexes. All three metal complexes exhibit bright blue luminescence under exposure to UV light. Additionally, the copper(I) complex …

Fluoroalcohol Induced Supramolecular Biphasic Systems Of Zwitterionic Surfactants, Mixed Amphiphiles, And Polar Organic Solvents In Proteomics And Environmental Analysis, Durga Khanal

Chemistry & Biochemistry Dissertations - Archive

In this research, we have investigated several HFIP-induced biphasic systems of zwitterionic surfactants like CHAPS and DMMAPS and their mixed amphiphilic systems for the extraction, enrichment, and fractionation of mixture of standard proteins and complex sample mixture of yeast proteins. The biphasic systems of zwitterionic surfactants (CHAPS and DMMAPS) and their mixed amphiphiles with quaternary ammonium salts (QUATS= TBAB, TEAB) provide concomitant extraction of hydrophobic membrane proteins, enrichment of lower abundance proteins to one phase, and fractionation of complex sample mixture into two phases. The results obtained from these biphasic systems were compared with control systems of aqueous solutions of …

Reinforcement Learning Policy Gradient Methods For Reservoir Operation Management And Control, Sadegh Sadeghi Tabas

All Theses

Changes in demand, various hydrological inputs, and environmental stressors are among issues that water managers and policymakers face on a regular basis. These concerns have sparked interest in applying different techniques to determine reservoir operation policy and improve reservoir release decisions. As the resolution of the analysis rises, it becomes more difficult to effectively represent a real-world system using traditional approaches for determining the best reservoir operation policy. One of the challenges is the “curse of dimensionality,” which occurs when the discretization of the state and action spaces becomes finer or when more state or action variables are taken into …

Determining States Of Movement In Humans Using Minimally Processed Eeg Signals And Various Classification Methods, Maurice Barnett

All Theses

Electroencephalography (EEG) is a non-invasive technique used in both clinical and research settings to record neuronal signaling in the brain. The location of an EEG signal as well as the frequencies at which its neuronal constituents fire correlate with behavioral tasks, including discrete states of motor activity. Due to the number of channels and fine temporal resolution of EEG, a dense, high-dimensional dataset is collected. Transcranial direct current stimulation (tDCS) is a treatment that has been suggested to improve motor functions of Parkinson’s disease and chronic stroke patients when stimulation occurs during a motor task. tDCS is commonly administered without …

Soil Moisture And Light Conditions Impact Digital And Visual Soil Color Assessments, Isabella Hill

All Theses

Determining soil color has traditionally been done visually, but inaccuracies with this method have been documented, including disagreement in evaluators, to differences in physical color books. Determining Munsell soil color in the field is also subject to environmental conditions, including soil water content (SWC) and light intensity. New digital spectral technology designed for determining soil color may offer accurate assessments regardless of human inaccuracies and environmental conditions. This research aimed to assess if visual observations differed from digital measurements of Munsell soil color as well as, the impacts of SWC and light on visual observations and digital measurements of soil …

Visualizing Features From Deep Neural Networks Trained On Alzheimer’S Disease And Few-Shot Learning Models For Alzheimer’S Disease, John Reeder

All Theses

Alzheimer’s disease is an incurable neural disease, usually affecting the elderly. The afflicted suffer from cognitive impairments that get dramatically worse at each stage. Previous research on Alzheimer’s disease analysis in terms of classification leveraged statistical models such as support vector machines. However, statistical models such as support vector machines train the from numerical data instead of medical images. Today, convolutional neural networks (CNN) are widely considered as the one which can achieve the state-of-the- art image classification performance. However, due to their black box nature, there can be reluctance amongst medical professionals for their use. On the other hand, …