Physical Sciences and Mathematics Commons^™

Cyanobacterial Harmful Algal Blooms Vary Within And Across Years At Lake Fayetteville, Arkansas, Alyssa Ferri

Graduate Theses and Dissertations

The occurrence of cyanobacterial harmful algal blooms (HABs) and toxins are a nationwide concern. Although Lake Fayetteville likely experienced HABs for many years, microcystin, an algal toxin, was not monitored until 2019. The objectives of this study were to: 1) observe temporal variation in water quality and total microcystin concentrations, 2) quantify thresholds with microcystin and nutrients, algal parameters, and environmental factors, and 3) evaluate complex relationships between total microcystin and nutrient supplies, algal parameters, and environmental factors using a classification and regression tree model (CART). Three sites (dam, inlet, and mid) at Lake Fayetteville were sampled weekly to monthly …

Colloidal Monolayers For Concentration Light In Ultra-Thin Semiconductor Layers, Rachel Cherry

Graduate Theses and Dissertations

Thin film semiconductors are used as photoconductive absorber layers for the development of broadband terahertz generation. Using a femtosecond laser pulse, the generation of a transient increase in the conductivity occurs by photoexciting conduction band electrons in the semiconductor. These thermalize through the emission of terahertz radiation. The route to terahertz generation is not particularly efficient as significant losses come from the absorption in the substrate that is beneath the photoconductive antenna layer. This work explores the application of hexagonally close-packed monolayers of chemically synthesized nanospheres as a potential light concentration method for ultra-thin films of GaAs and black phosphorus …

Cyanobacterial And Microcystin Response To Nutrient Additions At Lake Fayetteville Throughout The 2021 Growing Season, Lillie Haddock

Graduate Theses and Dissertations

Harmful Algal Blooms (HABs) are becoming a global concern due to their increasing distribution, frequency, intensity, and the occurrence of toxins. While it is known that eutrophication influences algal blooms, there is less known about what triggers these HABs to produce toxins, especially microcystin. In this study, we conducted 21 community bioassays at Lake Fayetteville, a hypereutrophic reservoir in Fayetteville, Arkansas, from April-November 2021 to examine how the addition of phosphorous and nitrogen influence cyanobacteria concentrations, microcystin concentrations, and microcystin toxin production. These experiments included a control, nitrogen (1.0 mg/L as KNO3), low phosphorus (0.025 mg/L as K2HPO4), high phosphorus …

The Effects Of Metronomic And Maximum-Tolerated Dose Chemotherapy In Colorectal Cancer Angiogenesis: A Combined Approach Using Endoscopic Diffuse Reflectance Spectroscopy And Mrna Expression, Ariel Isaac Mundo Ortiz

Graduate Theses and Dissertations

Colorectal cancer (CRC) continues to be one of the most incident and deadliest types of cancer worldwide. Chemotherapy has proven effective to reduce tumor burden for CRC patients, but there are several disadvantages associated with the use of mainstay maximtolerated dose (MTD) chemotherapeutic strategies. Metronomic chemotherapy (MET) has been developed as an alternative that addresses the shortcomings of maximum-tolerated dose chemotherapy but so far its effectiveness as a neoadjuvant strategy for CRC has not been explored.

This dissertation uses a combined optics and molecular biology approach (using diffuse reflectance spectroscopy and mRNA expression) to study the changes in angiogenesis and …

Gdefects4dl: A Dataset Of General Real-World Deep Learning Program Defects, Yunkai Liang, Yun Lin, Xuezhi Song, Jun Sun, Zhiyong Feng, Jin Song Dong

Research Collection School Of Computing and Information Systems

The development of deep learning programs, as a new programming paradigm, is observed to suffer from various defects. Emerging research works have been proposed to detect, debug, and repair deep learning bugs, which drive the need to construct the bug benchmarks. In this work, we present gDefects4DL, a dataset for general bugs of deep learning programs. Comparing to existing datasets, gDefects4DL collects bugs where the root causes and fix solutions can be well generalized to other projects. Our general bugs include deep learning program bugs such as (1) violation of deep learning API usage pattern (e.g., the standard to implement …

Is Surprisal In Issue Trackers Actionable?, James Caddy, Markus Wagner, Christoph Treude, Earl T. Barr, Miltiadis Allamanis

Research Collection School Of Computing and Information Systems

Background. From information theory, surprisal is a measurement of how unexpected an event is. Statistical language models provide a probabilistic approximation of natural languages, and because surprisal is constructed with the probability of an event occuring, it is therefore possible to determine the surprisal associated with English sentences. The issues and pull requests of software repository issue trackers give insight into the development process and likely contain the surprising events of this process. Objective. Prior works have identified that unusual events in software repositories are of interest to developers, and use simple code metrics-based methods for detecting them. In this …

Watch Your Flavors: Augmenting People's Flavor Perceptions And Associated Emotions Based On Videos Watched While Eating, Meetha Nesam James, Nimesha Ranasinghe, Anthony Tang, Lora Oehlberg

Research Collection School Of Computing and Information Systems

People engage in different activities while eating alone, such as watching television or scrolling through social media on their phones. However, the impacts of these visual contents on human cognitive processes, particularly related to flavor perception and its attributes, are still not thoroughly explored. This paper presents a user study to evaluate the influence of six different types of video content (including nature, cooking, and a new food video genre known as mukbang) on people’s flavor perceptions in terms of taste sensations, liking, and emotions while eating plain white rice. Our findings revealed that the participants’ flavor perceptions are augmented …

Github Sponsors: Exploring A New Way To Contribute To Open Source, Naomichi Shimada, Tao Xiao, Hideaki Hata, Christoph Treude, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

GitHub Sponsors, launched in 2019, enables donations to individual open source software (OSS) developers. Financial support for OSS maintainers and developers is a major issue in terms of sustaining OSS projects, and the ability to donate to individuals is expected to support the sustainability of developers, projects, and community. In this work, we conducted a mixed-methods study of GitHub Sponsors, including quantitative and qualitative analyses, to understand the characteristics of developers who are likely to receive donations and what developers think about donations to individuals. We found that: (1) sponsored developers are more active than non-sponsored developers, (2) the possibility …

Hierarchical Value Decomposition For Effective On-Demand Ride Pooling, Hao Jiang, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

On-demand ride-pooling (e.g., UberPool, GrabShare) services focus on serving multiple different customer requests using each vehicle, i.e., an empty or partially filled vehicle can be assigned requests from different passengers with different origins and destinations. On the other hand, in Taxi on Demand (ToD) services (e.g., UberX), one vehicle is assigned to only one request at a time. On-demand ride pooling is not only beneficial to customers (lower cost), drivers (higher revenue per trip) and aggregation companies (higher revenue), but is also of crucial importance to the environment as it reduces the number of vehicles required on the roads. Since …

Linkbreaker: Breaking The Backdoor-Trigger Link In Dnns Via Neurons Consistency Check, Zhenzhu Chen, Shang Wang, Anmin Fu, Yansong Gao, Shui Yu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Backdoor attacks cause model misbehaving by first implanting backdoors in deep neural networks (DNNs) during training and then activating the backdoor via samples with triggers during inference. The compromised models could pose serious security risks to artificial intelligence systems, such as misidentifying 'stop' traffic sign into '80km/h'. In this paper, we investigate the connection characteristic between the backdoor and the trigger in DNNs and observe the fact that the backdoor is implanted via establishing a link between a cluster of neurons, representing the backdoor, and the triggers. Based on this observation, we design LinkBreaker, a new generic scheme for defending …

Learning Semantically Rich Network-Based Multi-Modal Mobile User Interface Embeddings, Meng Kiat Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Semantically rich information from multiple modalities - text, code, images, categorical and numerical data - co-exist in the user interface (UI) design of mobile applications. Moreover, each UI design is composed of inter-linked UI entities which support different functions of an application, e.g., a UI screen comprising a UI taskbar, a menu and multiple button elements. Existing UI representation learning methods unfortunately are not designed to capture multi-modal and linkage structure between UI entities. To support effective search and recommendation applications over mobile UIs, we need UI representations that integrate latent semantics present in both multi-modal information and linkages between …

Sanitizable Access Control System For Secure Cloud Storage Against Malicious Data Publishers, Willy Susilo, Peng Jiang, Jianchang Lai, Fuchun Guo, Guomin Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cloud computing is considered as one of the most prominent paradigms in the information technology industry, since it can significantly reduce the costs of hardware and software resources in computing infrastructure. This convenience has enabled corporations to efficiently use the cloud storage as a mechanism to share data among their employees. At the first sight, by merely storing the shared data as plaintext in the cloud storage and protect them using an appropriate access control would be a nice solution. This is assuming that the cloud is fully trusted for not leaking any information, which is impractical as the cloud …

Understanding Crowdsourcing Requesters’ Wage Setting Behaviors, Kotaro Hara, Yudai Tanaka

Research Collection School Of Computing and Information Systems

Requesters on crowdsourcing platforms like Amazon Mechanical Turk (AMT) compensate workers inadequately. One potential reason for the underpayment is that the AMT’s requester interface provides limited information about estimated wages, preventing requesters from knowing if they are offering a fair piece-rate reward. To assess if presenting wage information affects requesters’ reward setting behaviors, we conducted a controlled study with 63 participants. We had three levels for a between-subjects factor in a mixed design study, where we provided participants with: no wage information, wage point estimate, and wage distribution. Each participant had three stages of adjusting the reward and controlling the …

Who Are The 'Silent Spreaders'?: Contact Tracing In Spatio-Temporal Memory Models, Yue Hu, Budhitama Subagdja, Ah-Hwee Tan, Chai Quek, Quanjun Yin

Research Collection School Of Computing and Information Systems

The COVID-19 epidemic has swept the world for over two years. However, a large number of infectious asymptomatic COVID-19 cases (ACCs) are still making the breaking up of the transmission chains very difficult. Efforts by epidemiological researchers in many countries have thrown light on the clinical features of ACCs, but there is still a lack of practical approaches to detect ACCs so as to help contain the pandemic. To address the issue of ACCs, this paper presents a neural network model called Spatio-Temporal Episodic Memory for COVID-19 (STEM-COVID) to identify ACCs from contact tracing data. Based on the fusion Adaptive …

Storm The Capitol: Linking Offline Political Speech And Online Twitter Extra-Representational Participation On Qanon And The January 6 Insurrection, Claire Seungeun Lee, Juan Merizalde, John D. Colautti, Jisun An, Haewoon Kwak

Research Collection School Of Computing and Information Systems

The transfer of power stemming from the 2020 presidential election occurred during an unprecedented period in United States history. Uncertainty from the COVID-19 pandemic, ongoing societal tensions, and a fragile economy increased societal polarization, exacerbated by the outgoing president's offline rhetoric. As a result, online groups such as QAnon engaged in extra political participation beyond the traditional platforms. This research explores the link between offline political speech and online extra-representational participation by examining Twitter within the context of the January 6 insurrection. Using a mixed-methods approach of quantitative and qualitative thematic analyses, the study combines offline speech information with Twitter …

On The Transferability Of Pre-Trained Language Models For Low-Resource Programming Languages, Fuxiang Chen, Fatemeh H. Fard, David Lo, Timofey Bryksin

Research Collection School Of Computing and Information Systems

A recent study by Ahmed and Devanbu reported that using a corpus of code written in multilingual datasets to fine-tune multilingual Pre-trained Language Models (PLMs) achieves higher performance as opposed to using a corpus of code written in just one programming language. However, no analysis was made with respect to fine-tuning monolingual PLMs. Furthermore, some programming languages are inherently different and code written in one language usually cannot be interchanged with the others, i.e., Ruby and Java code possess very different structure. To better understand how monolingual and multilingual PLMs affect different programming languages, we investigate 1) the performance of …

Implications Of Metal Coordination In Damage And Recognition Of Nucleic Acids And Lipid Bilayers, Ana Dreab

Chemistry & Biochemistry Theses & Dissertations

Metal ions have a myriad of biological functions from structural stability to enzymatic (de)activation and metabolic electron transfer. Redox-active metals also mediate the formation of reactive oxygen species which may either cause oxidative damage or protect cellular components. Computational modeling is used here to investigate the role of (1) metal-ion binding to antimicrobial peptides, (2) metal-ion removal and disulfide formation on zinc finger (ZF) proteins, and (3) coordination of thiones/selones for the prevention of metal-mediated redox damage.

Piscidins, natural-occurring antimicrobial peptides, efficiently kill bacteria by targeting their membranes. Their efficacy is enhanced in vitro by metal-binding and the presence of …

Transparscit: A Transformer-Based Citation Parser Trained On Large-Scale Synthesized Data, Md Sami Uddin

Computer Science Theses & Dissertations

Accurately parsing citation strings is key to automatically building large-scale citation graphs, so a robust citation parser is an essential module in academic search engines. One limitation of the state-of-the-art models (such as ParsCit and Neural-ParsCit) is the lack of a large-scale training corpus. Manually annotating hundreds of thousands of citation strings is laborious and time-consuming. This thesis presents a novel transformer-based citation parser by leveraging the GIANT dataset, consisting of 1 billion synthesized citation strings covering over 1500 citation styles. As opposed to handcrafted features, our model benefits from word embeddings and character-based embeddings by combining the bidirectional long …

Data-Driven Framework For Understanding & Modeling Ride-Sourcing Transportation Systems, Bishoy Kelleny

Civil & Environmental Engineering Theses & Dissertations

Ride-sourcing transportation services offered by transportation network companies (TNCs) like Uber and Lyft are disrupting the transportation landscape. The growing demand on these services, along with their potential short and long-term impacts on the environment, society, and infrastructure emphasize the need to further understand the ride-sourcing system. There were no sufficient data to fully understand the system and integrate it within regional multimodal transportation frameworks. This can be attributed to commercial and competition reasons, given the technology-enabled and innovative nature of the system. Recently, in 2019, the City of Chicago the released an extensive and complete ride-sourcing trip-level data for …

Improving Intelligent Transportation Safety And Reliability Through Lowering Costs, Integrating Machine Learning, And Studying Model Sensitivity, Cavender Holt

All Theses

As intelligent transportation becomes increasingly prevalent in the domain of transportation, it is essential to understand the safety, reliability, and performance of these systems. We investigate two primary areas in the problem domain. The first area concerns increasing the feasibility and reducing the cost of deploying pedestrian detection systems to intersections in order to increase safety. By allowing pedestrian detection to be placed in intersections, the data can be better utilized to create systems to prevent accidents from occurring. By employing a dynamic compression scheme for pedestrian detection, we show the reduction of network bandwidth improved by 2.12× over the …

Extreme-Contrast Ratio Imaging Of Bright Star Fields Using Charge-Injection Devices, Sailee Mangesh Sawant

Theses and Dissertations

The intrinsic nature of many astronomical sources, such as exoplanets, binary and multiple star systems, circumstellar disks, and active galactic nuclei and their host galaxies, introduces challenging requirements for observational instrumentation and techniques. In each case, we encounter situations where the light from bright sources hampers our abilities to detect surrounding fainter targets. To explore and study all features of such extreme-contrast ratio (ECR) scenes, we must perform observations at the maximum possible contrast ratios. However, direct imaging of fainter objects in the vicinity of bright sources imposes limitations on the type of contrast ratios achievable using ground- and spacebased …

Control Of Irradiation Wavelength And Quantum Yield Of Photocleavable Cages, Jingxuan Ma

Theses and Dissertations

An important component of biological research is the precise regulation of biomolecules in their physiological environment. Recent advances in neuroscience, have made it possible to regulate the activity of neurotransmitters using photocleavable protecting groups (PPGs), which are also known as cages. This enables the use of light as a trigger to activate selected neurons via photo release of agonists with precise control of timing as well as synaptic site, popularly referred to as spatiotemporal control. In recent years, a variety of PPGs have been developed and applied to biomolecular cages. PPGs can be classified according to their absorption wavelengths (from …

North Ecliptic Pole Merging Galaxy Catalogue, W. J. Pearson, L. E. Suelves, S. C.-C. Ho, N. Oi, S. Brough, Benne Holwerda, A. M. Hopkins, T.-C. Huang, H. S. Hwang, L. S. Kelvin, S. J. Kim, Á. R. López-Sánchez, K. Małek, C. Pearson, A. Poliszczuk, A. Pollo, V. Rodriguez-Gomez, H. Shim, Y. Toba, L. Wang

Faculty and Staff Scholarship

Aims. We aim to generate a catalogue of merging galaxies within the 5.4 sq. deg. North Ecliptic Pole over the redshift range 0.0 < z < 0.3. To do this, imaging data from the Hyper Suprime-Cam are used along with morphological parameters derived from these same data.

Methods. The catalogue was generated using a hybrid approach. Two neural networks were trained to perform binary merger non-merger classifications: one for galaxies with z < 0.15 and another for 0.15 ≤ z < 0.30. Each network used the image and morphological parameters of a galaxy as input. The galaxies that were identified as merger candidates by the network were then visually checked by experts. The resulting mergers will be used to calculate the merger fraction as a function of redshift and compared with literature results.

Results. We found that 86.3% of galaxy mergers at z < 0.15 and 79.0% of mergers at 0.15 ≤ z < 0.30 are expected to be correctly identified by the networks. Of the 34 264 galaxies classified by the neural networks, 10 195 were found to be merger candidates. Of these, 2109 were visually identified to be merging galaxies. We find that the merger fraction increases with redshift, consistent with literature results from observations and simulations, and that there is a mild star-formation rate enhancement in the merger population of a factor of 1.102 ± 0.084.

Suitability Of Low-Cost Additive Manufacturing For Polymer Electrolyte Fuel Cells, David Alexander

Open Access Theses & Dissertations

The purpose of this dissertation is to study the feasibility of low-cost additive manufacturing to fabricate polymer electrolyte fuel cell bipolar plate materials. Traditional manufacturing techniques include molding, milling, hollow embossing, hydro-forming, rolling, and electromagnetic forming. These processes are employed when a design has been selected due to higher costs at low volumes. The combination of high initial costs and bipolar plates being the most expensive component of the polymer electrolyte fuel cell creates incentive to mitigate this obstacle. The feasibility of low-cost additive manufactured bipolar plates will be proven by fabrication, post-processing, and characterization of printed test specimen. The …

Tuning Nanoscale Molecular Heterogeneity To Improve Co2 Transport And Binding In Co2 Capture Solvents, Omar Avina

Open Access Theses & Dissertations

Aqueous amine-based technology has been considered the most promising carbon capture solution for post-combustion gas from fossil fuel plants. However, solvent degradation and the high energy cost associated with removing CO2 from the solvent, known as regeneration, have hindered its widespread implementation. It has been proposed that utilizing a water lean solvent, in contrast to aqueous amines, can decrease the required heat to regenerate the solvent. Additionally, Malhotra et al. proposed that controlling the viscosity can help increase the mass transport properties of CO2 in the solvent. A recent study on CO2 binding organic liquids (CO2BOLs) found them to exist …

Nanotechnology-Based Approaches To Mitigate Environmental Pollutants -- Induced Neurological Disorders, Jyoti Ahlawat

Open Access Theses & Dissertations

Neurodegenerative diseases such as Parkinson's disease (PD), Alzheimerâ??s Disease (AD) and Huntingtonâ??s Disease (HD) have no cure despite intensive research efforts geared towards therapeutics development. In the USA, patients with PD and AD alone cost the nation ~ $200 billion annually in patient care and lost productivity. Therefore, there remains an urgent and unmet need to develop novel drugs and drug carriers with the potential to slow down, halt and ideally reverse the course of neurodegenerative disorders. The dissertation focuses on developing approaches towards targeting PD using multifactorial mechanisms including the targeting of protein aggregation and oxidative stress. This is …

Low-Lying Spin-Flip Excitonic States Of ����12��12 (��������)16 [��2��]4 Molecule (Mn12 − ����), Karma Dema

Open Access Theses & Dissertations

Molecules and materials constructed from Mn atoms offer diverse assortments of geomet- rical and spin structures. The diversity of structures, in comparison with other transition metals, along with nature’s decision to use a Mn-based molecule to catalyze solar-driven water splitting and oxygen evolution, suggests that there is indeed something special about the location of Mn valence electrons, both energetically and geometrically, that endows Mn with its multifaceted behaviors that, in turn, provide such chemical, physical and mag- netic diversity. Based upon recent work on the Mn3 monomer and the Mn(taa) there is an expectation that Mn�� �� �� centers can …

Method Development For Preconcentration And Quantification Of Critical And Valuable Elements In Permian Basin Produced Waters, Joshua Matthew Lewis

Open Access Theses & Dissertations

Produced waters are a voluminous byproduct of unconventional oil and gas production. Produced water volumes are primarily addressed by subsurface reinjection through saltwater disposal wells (SWDs) and reuse within the oil and gas industry. Oil and gas operators continue to evaluate and trial novel methods to improve produced water handling, and reduce freshwater use, and disposal volumes. Here, we present results for method development to quantify Critical and Valuable Elements (CVEs; defined here as the lanthanide series, high field strength elements, industrial elements and precious metals in brines. CVE concentrations in produced waters and other high-salinity waters are poorly understood …

Covid Synergy: A Machine Learning Approach Uncovering Potential Treatment Combinations For Sars-Cov-2, Jason Eden Sanchez

Open Access Theses & Dissertations

For more than two years, the COVID-19 pandemic has upended the lives of billions of individualsworldwide leading to disruptions in healthcare, the economy and society at large. As the pandemic enters its third year, the human impact cannot be overstated and the need to develop effective pharmaceuticals remains. Though there currently exits FDA-approved medications for COVID-19, the emergence of novel variants, such as Omicron, highlights the importance of discovering new therapies which will continue to be effective regardless of the pandemicâ??s progression. Because discovering new medications is a costly and timeintensive endeavor, my approach entails drug repurposing to test medications …

Mapping Salt-Affected Land In The South-West Of Western Australia Using Satellite Remote Sensing, P A. Caccetta, John A. Simons, S Furby, Nicholas J. Wright, Richard J. George Dr

Natural resources published reports

Dryland salinity is a pervasive form of land degradation that has resulted from the clearing of about 17 M ha of native vegetation and the introduction of predominately cereal and pasture-based farming systems in the South-West of Western Australia. The change in water balance caused by clearing deep rooted endemic woodlands increased recharge and resulted in rising groundwater levels. After a lag period, the regolith began filling and groundwater approached the soil surface, evaporating and depositing stored salts in the rootzone of salt sensitive crops. Groundwater levels also rise and affect areas of remnant native vegetation, streams, wet-lands and rural …