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Articles 32881 - 32910 of 302621

Full-Text Articles in Physical Sciences and Mathematics

The Impact Of Framing On Natural Gas Pipeline Siting In Virginia, Ritvik Shukla Apr 2022

The Impact Of Framing On Natural Gas Pipeline Siting In Virginia, Ritvik Shukla

Theses and Dissertations

Natural gas has become a major share of energy consumption in the U.S. over the past two decades. This rise has resulted in considerable investment in the natural gas pipeline network so that the supply can be maximized. However, pipeline infrastructures, much like other fossil fuel energy infrastructures and activities, have an uneven distribution of benefits and costs across different regions. In regions where natural gas activities and infrastructure are being developed, local communities can become increasingly dependent on natural gas systems for stable revenue and employment. Such communities risk becoming “locked in” to carbon energy at a time when …

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Modification Of Active Sites In Catalytic Materials For Gas-Phase Heterogeneous Catalysis, Deependra Man Shakya Apr 2022

Modification Of Active Sites In Catalytic Materials For Gas-Phase Heterogeneous Catalysis, Deependra Man Shakya

Theses and Dissertations

Heterogeneous catalysis remains at the core of chemical manufacturing industries with 80-90 % of chemical processes relying on the use of catalysts. Unlike homogeneous catalyst that has extremely well-defined active sites, active sites in heterogeneous catalysis are complex and show dynamic behavior under reaction conditions, and change their structures, composition, particle size. The complexity associated with these systems has made the rational design of the catalyst a difficult problem. Highly crystalline metalorganic frameworks (MOFs) as heterogeneous catalysts present the unique opportunity to systematically modify the geometries, ensemble sizes, and compositions of highly dispersed active sites due to their tailorable, and …

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Tailored Nanomaterials For Advancing Fast-Charge Research, Wessel Van Den Bergh Apr 2022

Tailored Nanomaterials For Advancing Fast-Charge Research, Wessel Van Den Bergh

Theses and Dissertations

The demand for fast, energy-dense storage has driven research into nanoscale intercalation materials. Nanoscale materials not only accelerate kinetics but also can modify reaction path thermodynamics, intercalant solubility, and diffusivity. Pioneering works have revealed such nanoscale changes, often without the need to separately probe each fundamental transport process. While electrodes can be designed to have one transport processes dominant, there remain opportunities to better understand energy-dense designs with multiple concomitant transport constraints. The contents herein highlight emerging an method using tailored, energy-dense nanomaterials and the process of elimination to clearly correlate architectural features to performance. For example, this method revealed …

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Quantifying The Controls Of Shear-Coupled P-Waves, Jackson Saftner Apr 2022

Quantifying The Controls Of Shear-Coupled P-Waves, Jackson Saftner

Theses and Dissertations

Shear-coupled P-waves have been shown to possess great utility in resolving crustal and upper mantle models, however these phases remain largely untapped due to their ephemeral nature. Shear-coupled P-waves are a type of seismic phase that undergo S-to-P conversion either at the free-surface or at the base of the crust. Under the proper conditions, it is possible for the converted crustal P phases to achieve total internal reflection, allowing these phases to remain large in amplitude and sample long segments of the crust. In this study, we use a combination of real-world observations collected from literature, and synthetic seismograms, to …

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On Providing Efficient Real-Time Solutions To Motion Planning Problems Of High Complexity, Marios Xanthidis Apr 2022

On Providing Efficient Real-Time Solutions To Motion Planning Problems Of High Complexity, Marios Xanthidis

Theses and Dissertations

The holy grail of robotics is producing robotic systems capable of efficiently executing all the tasks that are hard, or even impossible, for humans. Humans, undoubtedly, from both a hardware and software perspective, are extremely complex systems capable of executing many complicated tasks. Thus, the complexity of many state-of-the-art robotic systems is also expected to progressively increase, with the goal to match or even surpass human abilities. Recent developments have emphasized mostly hardware, providing highly complex robots with exceptional capabilities. On the other hand, they have illustrated that one important bottleneck of realizing such systems as a common reality is …

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Galaxy And Mass Assembly (Gama): The Weak Environmental Dependence Of Quasar Activity At 0.1 < Z < 0.35, Clare F. Wethers, Nischal Acharya, Roberto De Propris, Jari Kotilainen, Ivan K. Baldry, Sarah Brough, Simon P. Driver, Alister W. Graham, Benne Holwerda, Andrew M. Hopkins, Angel R. López-Sánchez, Jonathan Loveday, Steven Phillipps, Kevin A. Pimbblet, Edward Taylor, Lingyu Wang, Angus H. Wright Apr 2022

Galaxy And Mass Assembly (Gama): The Weak Environmental Dependence Of Quasar Activity At 0.1 < Z < 0.35, Clare F. Wethers, Nischal Acharya, Roberto De Propris, Jari Kotilainen, Ivan K. Baldry, Sarah Brough, Simon P. Driver, Alister W. Graham, Benne Holwerda, Andrew M. Hopkins, Angel R. López-Sánchez, Jonathan Loveday, Steven Phillipps, Kevin A. Pimbblet, Edward Taylor, Lingyu Wang, Angus H. Wright

Faculty and Staff Scholarship

Understanding the connection between nuclear activity and galaxy environment remains critical in constraining models of galaxy evolution. By exploiting the extensive cataloged data from the Galaxy and Mass Assembly survey, we identify a representative sample of 205 quasars at 0.1 < z < 0.35 and establish a comparison sample of galaxies, closely matched to the quasar sample in terms of both stellar mass and redshift. On scales <1 Mpc, the galaxy number counts and group membership of quasars appear entirely consistent with those of the matched galaxy sample. Despite this, we find that quasars are ∼1.5 times more likely to be classified as the group center, indicating a potential link between quasar activity and cold gas flows or galaxy interactions associated with rich group environments. On scales of ∼a few Mpc, the clustering strengths of both samples are statistically consistent, and beyond 10 Mpc, we find no evidence that quasars trace large-scale structures any more than the galaxy control sample. Both populations are found to prefer intermediate-density sheets and filaments to either very high-density environments or very low-density environments. This weak dependence of quasar activity on galaxy environment supports a paradigm in which quasars represent a phase in the lifetime of all massive galaxies and in which secular processes and a group-centric location are the dominant triggers of quasars at low redshift.

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The Territory, John C. Lyden Apr 2022

The Territory, John C. Lyden

Journal of Religion & Film

This is a film review of The Territory (2022), directed by Alex Pritz.

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Gps-Derived Interseismic Fault Locking Along The Jalisco–Colima Segment Of The Mexico Subduction Zone, Beatriz Cosenza-Muralles, Charles Demets, B. Márquez-Azúa, O. Sánchez, J. Stock, Enrique Cabral-Cano, Robert Mccaffrey Apr 2022

Gps-Derived Interseismic Fault Locking Along The Jalisco–Colima Segment Of The Mexico Subduction Zone, Beatriz Cosenza-Muralles, Charles Demets, B. Márquez-Azúa, O. Sánchez, J. Stock, Enrique Cabral-Cano, Robert Mccaffrey

Geology Faculty Publications and Presentations

Northeastward subduction of the oceanic Rivera and Cocos plates in western Mexico poses a poorly understood seismic hazard to the overlying areas of the North America plate. We estimate the magnitude and distribution of interseismic locking along the northern ∼500 km of the Mexico subduction zone, with a series of elastic half-space inversions that optimize the fits to the velocities of 57 GPS stations in western Mexico. All velocities were corrected for the co-seismic, afterslip and viscoelastic rebound effects of the 1995 Colima–Jalisco and 2003 Tecomán earthquakes. We explore the robustness of interseismic locking estimates to a variety of mantle …

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A Proposed Treatment Of Mixed Connective Tissue Disease By Competitive Inhibition Of Autoantibodies, Thomas Russell Apr 2022

A Proposed Treatment Of Mixed Connective Tissue Disease By Competitive Inhibition Of Autoantibodies, Thomas Russell

Senior Honors Theses

Mixed Connective Tissue Disease is an autoimmune disease characterized by Raynaud’s phenomenon and arthritis among other symptoms. It is primarily caused by antibodies that target the U1-RNP 70K peptide. The treatment proposed in this paper uses competitive inhibition to prevent the binding of the anti-U1-RNP 70K antibodies with the U1-RNP 70K peptide. A method for testing the designed treatment in silico is proposed using AutoDock Vina docking software.

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Gödel's Incompleteness Theorems, Derick Swarey Apr 2022

Gödel's Incompleteness Theorems, Derick Swarey

Senior Honors Theses

The Incompleteness Theorems of Kurt Godel are very famous both within and outside of mathematics. They focus on independence and consistency within mathematics and hence a more thorough understanding of these is beneficial to their study. The proofs of the theorems involve many ideas which may be unfamiliar to many, including those of formal systems, Godel numbering, and recursive functions and relations. The arguments themselves mirror the Liar’s Paradox in that Godel constructs a statement asserting its own unprovability and then shows that such a statement and its negation must both be independent of the system, otherwise the system is …

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Media Coverage Of Anthropogenic Climate Change: Analysis Of Coverage, Issues, And Implications For Public Engagement And Government Policy, Renee Farmer Apr 2022

Media Coverage Of Anthropogenic Climate Change: Analysis Of Coverage, Issues, And Implications For Public Engagement And Government Policy, Renee Farmer

Senior Honors Theses

Media coverage of climate change is responsible for shaping both public understanding and government policies regarding the environment. The public relies on the media to translate the oftentimes complex terminology, processes, and implications of environmental research and findings. Unfortunately, miscommunication frequently occurs as the media seek to bridge this knowledge gap, with implications including hostile public sentiment, failure to take necessary action, and ineffective or harmful governmental policies. This thesis will provide an overview of how the media cover climate change, including analyses of both poor and successful coverage of issues, identification of risks and reoccurring problems present in media …

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Assessing Security Risks With The Internet Of Things, Faith Mosemann Apr 2022

Assessing Security Risks With The Internet Of Things, Faith Mosemann

Senior Honors Theses

For my honors thesis I have decided to study the security risks associated with the Internet of Things (IoT) and possible ways to secure them. I will focus on how corporate, and individuals use IoT devices and the security risks that come with their implementation. In my research, I found out that IoT gadgets tend to go unnoticed as a checkpoint for vulnerability. For example, often personal IoT devices tend to have the default username and password issued from the factory that a hacker could easily find through Google. IoT devices need security just as much as computers or servers …

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The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick Apr 2022

The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick

Senior Honors Theses

One of the most investigated topics in operations research is the Traveling Salesman Problem (TSP) and the algorithms that can be used to solve it. Despite its relatively simple formulation, its computational difficulty keeps it and potential solution methods at the forefront of current research. This paper defines and analyzes numerous proposed solutions to the TSP in order to facilitate understanding of the problem. Additionally, the efficiencies of different heuristics are studied and compared to the aforementioned algorithms’ accuracy, as a quick algorithm is often formulated at the expense of an exact solution.

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Security Posture: A Systematic Review Of Cyber Threats And Proactive Security, Amanda Jones Apr 2022

Security Posture: A Systematic Review Of Cyber Threats And Proactive Security, Amanda Jones

Senior Honors Theses

In the last decade, several high-profile cyber threats have occurred with global impact and devastating consequences. The tools, techniques, and procedures used to prevent cyber threats from occurring fall under the category of proactive security. Proactive security methodologies, however, vary among professionals where differing tactics have proved situationally effective. To determine the most effective tactics for preventing exploitation of vulnerabilities, the author examines the attack vector of three incidents from the last five years in a systematic review format: the WannaCry incident, the 2020 SolarWinds SUNBURST exploit, and the recently discovered Log4j vulnerability. From the three cases and existing literature, …

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Enhancing The Opportunities For Adults With Autism To Find Jobs Using A Job-Matching Algorithm, Joseph T. Bills Apr 2022

Enhancing The Opportunities For Adults With Autism To Find Jobs Using A Job-Matching Algorithm, Joseph T. Bills

Theses and Dissertations

Adults with autism face many difficulties when finding employment, such as struggling with interviews and needing accommodating environments for sensory issues. However, autistic adults also have unique skills to contribute to the workplace that companies have recently started to seek after, such as close attention to detail and trustworthiness. To work around these difficulties and help companies find the talent they are looking for we have developed a job-matching system. Our system is based around the stable matching of the Gale-Shapley algorithm to match autistic adults with employers after estimating how both adults with autism and employers would rank the …

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The Development Of Inhibitors For Sars-Cov-2 Orf8, My Thanh Thao Nguyen Apr 2022

The Development Of Inhibitors For Sars-Cov-2 Orf8, My Thanh Thao Nguyen

CSB and SJU Distinguished Thesis

An unexpected outbreak of SARS-CoV-2 caused a worldwide pandemic in 2020. Many repurposed drugs were tested, but there are currently only three FDA approved antivirals (Merck’s antiviral Molnupiravir, Pfizer’s antiviral Paxlovid, and Remdisivir).1 Most of the antiviral drugs tested SARS-CoV-2 main protease and RNA-dependent RNA polymerase. However, it is important to explore different drug targets of SARS-CoV-2 to prepare for the virus mutations of the future. This research looks at an alternative approach in which SARSCoV- 2 Open Reading Frame 8 (ORF8), which has been shown to be a rapidly evolving hypervariable gene, was chosen to be the protein of …

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Sars-Cov-2 Main Protease Inhibitors Repurposed For Hiv-1 Protease Binding, Jacob Minkkinen Apr 2022

Sars-Cov-2 Main Protease Inhibitors Repurposed For Hiv-1 Protease Binding, Jacob Minkkinen

CSB and SJU Distinguished Thesis

Severe acute respiratory syndrome (SARS-CoV-2) led to the COVID-19 global pandemic, with over 460 million cases of infection and over 6 million deaths since the start of the pandemic. SARS-CoV-2 is a retrovirus that utilizes a main protease (Mpro). Mpro is a catalytic cys/his protease. Several treatments were proposed to stop the pandemic including repurposing drugs to inhibit the Mpro. Another retrovirus that uses a protease is human immunodeficiency virus (HIV-1) which has been a global epidemic for 40 years and is a devastating disease that attacks the immune system. HIV-1 has infected 79.5 million people and has killed an …

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A Remote Sensing And Machine Learning-Based Approach To Forecast The Onset Of Harmful Algal Bloom (Red Tides), Moein Izadi Apr 2022

A Remote Sensing And Machine Learning-Based Approach To Forecast The Onset Of Harmful Algal Bloom (Red Tides), Moein Izadi

Dissertations

In the last few decades, harmful algal blooms (HABs, also known as “red tides”) have become one of the most detrimental natural phenomena all around the world especially in Florida’s coastal areas due to local environmental factors and global warming in a larger scale. Karenia brevis produces toxins that have harmful effects on humans, fisheries, and ecosystems. In this study, I developed and compared the efficiency of state-of-the-art machine learning models (e.g., XGBoost, Random Forest, and Support Vector Machine) in predicting the occurrence of HABs. In the proposed models, the K. brevis abundance is used as the target, and 10 …

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Victor: An Implicit Approach To Mitigate Misinformation Via Continuous Verification Reading, Kuan-Chieh Lo, Shih-Chieh Dai, Aiping Xiong, Jing Jiang, Lun-Wei Ku Apr 2022

Victor: An Implicit Approach To Mitigate Misinformation Via Continuous Verification Reading, Kuan-Chieh Lo, Shih-Chieh Dai, Aiping Xiong, Jing Jiang, Lun-Wei Ku

Research Collection School Of Computing and Information Systems

We design and evaluate VICTOR, an easy-to-apply module on top of a recommender system to mitigate misinformation. VICTOR takes an elegant, implicit approach to deliver fake-news verifications, such that readers of fake news can continuously access more verified news articles about fake-news events without explicit correction. We frame fake-news intervention within VICTOR as a graph-based question-answering (QA) task, with Q as a fake-news article and A as the corresponding verified articles. Specifically, VICTOR adopts reinforcement learning: it first considers fake-news readers’ preferences supported by underlying news recommender systems and then directs their reading sequence towards the verified news articles. To …

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Surveying Structural Complexity In Quantum Many-Body Systems, Whei Yeap Suen, Thomas J. Elliott, Jayne Thompson, Andrew J. P. Garner, John R. Mahoney, Vlatko Vedral, Mile Gu Apr 2022

Surveying Structural Complexity In Quantum Many-Body Systems, Whei Yeap Suen, Thomas J. Elliott, Jayne Thompson, Andrew J. P. Garner, John R. Mahoney, Vlatko Vedral, Mile Gu

Research Collection School Of Computing and Information Systems

Quantum many-body systems exhibit a rich and diverse range of exotic behaviours, owing to their underlying non-classical structure. These systems present a deep structure beyond those that can be captured by measures of correlation and entanglement alone. Using tools from complexity science, we characterise such structure. We investigate the structural complexities that can be found within the patterns that manifest from the observational data of these systems. In particular, using two prototypical quantum many-body systems as test cases-the one-dimensional quantum Ising and Bose-Hubbard models-we explore how different information-theoretic measures of complexity are able to identify different features of such patterns. …

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Sibnet: Food Instance Counting And Segmentation, Huu-Thanh. Nguyen, Chong-Wah Ngo, Wing-Kwong Chan Apr 2022

Sibnet: Food Instance Counting And Segmentation, Huu-Thanh. Nguyen, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Food computing has recently attracted considerable research attention due to its significance for health risk analysis. In the literature, the majority of research efforts are dedicated to food recognition. Relatively few works are conducted for food counting and segmentation, which are essential for portion size estimation. This paper presents a deep neural network, named SibNet, for simultaneous counting and extraction of food instances from an image. The problem is challenging due to varying size and shape of food as well as arbitrary viewing angle of camera, not to mention that food instances often occlude each other. SibNet is novel for …

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Comai: Enabling Lightweight, Collaborative Intelligence By Retrofitting Vision Dnns, Kasthuri Jayarajah, Dhanuja Wanniarachchige, Tarek Abdelzaher, Archan Misra Apr 2022

Comai: Enabling Lightweight, Collaborative Intelligence By Retrofitting Vision Dnns, Kasthuri Jayarajah, Dhanuja Wanniarachchige, Tarek Abdelzaher, Archan Misra

Research Collection School Of Computing and Information Systems

While Deep Neural Network (DNN) models have transformed machine vision capabilities, their extremely high computational complexity and model sizes present a formidable deployment roadblock for AIoT applications. We show that the complexity-vs-accuracy-vs-communication tradeoffs for such DNN models can be significantly addressed via a novel, lightweight form of “collaborative machine intelligence” that requires only runtime changes to the inference process. In our proposed approach, called ComAI, the DNN pipelines of different vision sensors share intermediate processing state with one another, effectively providing hints about objects located within their mutually-overlapping Field-of-Views (FoVs). CoMAI uses two novel techniques: (a) a secondary shallow ML …

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Resil: Revivifying Function Signature Inference Using Deep Learning With Domain-Specific Knowledge, Yan Lin, Debin Gao, David Lo Apr 2022

Resil: Revivifying Function Signature Inference Using Deep Learning With Domain-Specific Knowledge, Yan Lin, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Function signature recovery is important for binary analysis and security enhancement, such as bug finding and control-flow integrity enforcement. However, binary executables typically have crucial information vital for function signature recovery stripped off during compilation. To make things worse, recent studies show that many compiler optimization strategies further complicate the recovery of function signatures with intended violations to function calling conventions.In this paper, we first perform a systematic study to quantify the extent to which compiler optimizations (negatively) impact the accuracy of existing deep learning techniques for function signature recovery. Our experiments show that a state-of-the-art deep learning technique has …

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User Satisfaction Estimation With Sequential Dialogue Act Modeling In Goal-Oriented Conversational Systems, Yang Deng, Wenxuan Zhang, Wai Lam, Hong Cheng, Helen Meng Apr 2022

User Satisfaction Estimation With Sequential Dialogue Act Modeling In Goal-Oriented Conversational Systems, Yang Deng, Wenxuan Zhang, Wai Lam, Hong Cheng, Helen Meng

Research Collection School Of Computing and Information Systems

User Satisfaction Estimation (USE) is an important yet challenging task in goal-oriented conversational systems. Whether the user is satisfied with the system largely depends on the fulfillment of the user’s needs, which can be implicitly reflected by users’ dialogue acts. However, existing studies often neglect the sequential transitions of dialogue act or rely heavily on annotated dialogue act labels when utilizing dialogue acts to facilitate USE. In this paper, we propose a novel framework, namely USDA, to incorporate the sequential dynamics of dialogue acts for predicting user satisfaction, by jointly learning User Satisfaction Estimation and Dialogue Act Recognition tasks. In …

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Utama, Sheila J. Nayar Apr 2022

Utama, Sheila J. Nayar

Journal of Religion & Film

This is a film review of Utama (2022), directed by Alejandro Loayza Grisi.

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State Energy Research Center, University Of North Dakota. Energy And Environmental Research Center Apr 2022

State Energy Research Center, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet about the State Energy Research Center (SERC). Highlights technological innovation and SERC projects.

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Classifying Pretzel Links Obtained By Strong Fusion, Jonathan Homan Apr 2022

Classifying Pretzel Links Obtained By Strong Fusion, Jonathan Homan

Honors Theses

A link is a collection of circles embedded into 3-dimensional space. Pretzel links are an important family of links which comprises those links that fit a general form that includes many of the most common links. The strong fusion of a link joins two components of the link via a band and adds an unknotted circle about the band [4]; this naturally arises in the study of concordance and has been used to model biological phenomena such as site specific recombination in DNA [2]. Here we present a complete and original classification of those pretzel links which can be obtained …

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Dynamic Corrosion Test System, University Of North Dakota. Energy And Environmental Research Center Apr 2022

Dynamic Corrosion Test System, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet about the Energy & Environmental Research Center’s Dynamic Corrosion Test System. Includes information on how the system evaluates alloy coupons in environments that mimic CO2 cycles.

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Synthesis And Characterization Of Aluminum Complexes Implementing Redox-Active Nitroxide Bidentate Ligands, Omar Saleh , '22 Apr 2022

Synthesis And Characterization Of Aluminum Complexes Implementing Redox-Active Nitroxide Bidentate Ligands, Omar Saleh , '22

Senior Theses, Projects, and Awards

Aluminum is an abundant, sustainable, and non-toxic metal, which would be a great candidate to be used in redox and catalytic chemistry in lieu of the currently used heavy metals. However, aluminum can only exist over one stable oxidation state, which is a major obstacle in this pursuit. To tackle this issue, the Graves Lab has been focusing on incorporating redox active ligands into aluminum complexes. Nitroxide (NO⁻) is an exceptionally important functional group, as it can reversibly exist over three stable oxidation states. In this work, I synthesized and characterized neutral aluminum complexes, [(^(OMe)pyNO)AlMe₂]₂ (1b) and [(^(OMe)pyNO)AlMe₂]AlMe₃ (2b), with …

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Exploring The Kinetics And Thermodynamics Of O–H Bond Activation By Tripodal Tris(Nitroxide) Aluminum And Gallium Complexes, Joseph S. Scott , '22 Apr 2022

Exploring The Kinetics And Thermodynamics Of O–H Bond Activation By Tripodal Tris(Nitroxide) Aluminum And Gallium Complexes, Joseph S. Scott , '22

Senior Theses, Projects, and Awards

Aluminum is one of earth’s most abundant and cheapest metals, and it is also nontoxic and environmentally friendly. This makes it an ideal candidate to be implemented in organometallic chemistry as a greener alternative to metal-based systems based on heavy and/or precious metals. One of the realms in which aluminum and other group 13 elements show promise is metal-ligand cooperative chemistry, which can afford transition metal-reminiscent small molecule activation chemistry. Our studies of organic ligands with nitroxide-functionalities within Al and Ga coordinative systems has led us to the discovery of tripodal tris(nitroxide) Al and Ga complexes with abilities to engage …

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