Digital Commons Network^™

Behavioral Modeling Of Manned-Unmanned Cooperative Air Combat Based On Improved Abc Algorithm, Peng Wang, Haoyu Liu, Ni Li, Zexi Yu, Shangjie Jia

Journal of System Simulation

Abstract: To solve the problem of difficulty in establishing collaborative behavior models and weak adversarial capabilities in typical MAV/UAV air combat scenarios, a mixed decision based MAV/UAV behavior modeling framework is proposed. Using collaborative rule sets, rule subsets, tactical action sets, and other tools, a hierarchical decision collaborative behavior model supporting five types of collaborative tactics, including grinding tactics and unilateral flanking tactics, is constructed in this framework. a behavior model parameter optimization method based on an improved artificial bee colony (ABC) algorithm is proposed. By using the Mason rotation method to initialize the population, a better initial honey source …

At The Core Of Apple And Antitrust: Interoperability, Antoine Bremond

Seattle Journal of Technology, Environmental, & Innovation Law

This paper offers a novel approach to analyzing Apple Inc, (Apple) within the context of antitrust law. As a frequently named party to antitrust litigation, not only in the United States but also worldwide, Apple’s closed garden has already been called into question. However, similar to the U.S. Department of Justice’s (DOJ) attempt on March 21^st, 2024 to “to erect a new landmark decision” in their lawsuit against Apple, this paper focuses on Apple’s iOS ecosystem as a whole. While this article recognizes similar consumer harm concerns the DOJ addresses in United States, et al. v. Apple Inc …

Defining The Social Licence Of Large Language Models In Healthcare, Robin L. Pierce, Jack Gallifant, Ashley Cordes, Amelia Fiske, Matilda Dorotic, Mataroria Lyndon, Shrey Jain, Joe Zhang, Judy Gichoya, Leo Anthony Celi

Seattle Journal of Technology, Environmental, & Innovation Law

As Large Language Models (LLMs) continue to grow and evolve, the ethical, social, and legal challenges they present, especially in terms of data use and sharing, come sharply into focus. Particularly in high-risk domains like healthcare, where the sensitivity of data is pronounced, and the ramifications of data leakages or misuse are profound. These licenses, envisioned to address the complexities introduced by LLMs, still grapple with barriers that hinder their full potential: notably, the absence of authoritative regulatory bodies, ambiguities in defining what constitutes 'sufficient public benefit', issues of data sovereignty, and dilemmas surrounding responsibility and liability. Herein, we delve …

Engineering Biomaterial Interfaces For Microbial Control, Yikang Xu

Dissertations - ALL

Since its inception as early as ancient Chinese placing bamboo pegs in place of missing teeth over 4,000 years ago, biomaterials have been an indispensable component of medical tools at human’s disposal. While early implants rely solely on the material properties themselves, modern devices have become much more than just materials. Topographic features, coatings, surface energy, and even embedded electronics have all added dimensions to the complexity of biomaterials and medical devices. Interaction between these materials and host cells and tissues, as well as microbes that can cause infections. Although well recognized for its significance, controlling biomaterial associated infections is …

Privacy Protection In Machine Learning Via Exploitation Of Constrained Adversarial Evasion, Brian Testa

Dissertations - ALL

Deep neural networks are extensively applied to real-world tasks. In many cases, the data feeding these tasks are human generated content, which emphasizes the criticality of privacy and data protection. The diverse modalities of this user data provide fertile ground for 3rd parties to monetize a user’s data. This work considers two such modalities: user speech when interacting with smart speaker voice assistants (VAs) and images shared with online service providers. In these cases, the user would like to support some form of machine learning (ML) inference without allowing others. A user interacting with a smart speaker would like the …

Elementary Science Instruction: A Document Analysis Of Teacher Messaging Across Two Sets Of Curriculum Materials, Jessica Mary Whisher-Hehl

Dissertations - ALL

Elementary teachers are tasked with teaching multiple subjects within an instructional day. One mechanism to support this task is through strong curriculum materials, which lay out a course of instruction aligned with instructional standards. This is helpful when teachers are trying to teach to a new set of standards, such as the Next Generation Science Standards, which require a significant shift in instructional strategies. In cases such as this, educative features embedded in the curriculum materials can assist teachers in making the required shifts in instruction. However, sometimes the instructional time required by curriculum materials, especially in elementary science, is …

Effects Of Negative Poisson’S Ratio On The Mechanics Of Auxetic Carbon Fiber Composites Under Tensile, Buckling And Low Velocity Impact, Wenhua Lin

Dissertations - ALL

Carbon fiber reinforced polymer (CFRP) matrix composites exhibited superior properties, such as high specific stiffness and specific strength, excellent fatigue and corrosion resistance, and low coefficient of thermal expansion, have been popular across various industries including aerospace, marine, automotive, energy, civil infrastructure, and high-end sports over the past decades. However, one significant drawback of CFRP composites is the susceptibility to low velocity impact damage which, for aircraft, can be results of tool drop, runway debris, and bird strike during takeoff and landing. These impact events could lead to external and internal damages of a CFRP composite structure in various damage …

Cognitive Load Classification From Functional Near-Infrared Spectroscopy Data, Jiyang Wang

Dissertations - ALL

Predicting cognitive workload using physiological sensors, such as functional near-infrared spectroscopy (fNIRS), has gained significant attention in recent years. However, many existing methods are limited by small datasets and narrow brain channel coverage, restricting their generalizability across participants, tasks, and sessions. In this thesis, we introduce two innovative approaches aimed at overcoming these limitations: a CNN-BiGRU model with self-supervised label augmentation (SLA) and a block-wise domain adaptation method (BWise-DA). Our CNN-BiGRU-SLA model, grounded in cognitive load theory, leverages attention mechanisms and multi-label classification to predict working memory load (WML) and visual processing load (VPL) across multiple participants and sessions. Using …

Vimentin Inside And Outside The Cell: From Cell Spreading To Nuclear Mechanics To Covid-19, Maxx Swoger

Dissertations - ALL

Cells are constantly subjected to both external forces encountered from the extracellular environment and internal stresses generated by the cell necessary to migrate and undergo healthy cellular function. Central to the ability of cells to both generate and mediate forces is the cell cytoskeleton, which forms the muscles and bones for cells. There are three main components of the cell cytoskeleton: microtubules, actin, and intermediate filaments. The role of actin and microtubules in cell function, particularly force generation and mediation have been well studied; however, the role of intermediate filaments is less understood. Intermediate filaments represent a broad and diverse …

Thermodynamics And Shear Flow Dynamics Of Block Copolymer Morphologies In Solution, Senyuan Liu

Dissertations - ALL

Block copolymers (BCPs) have been a focal point of research for several decades. They have been engineered to produce various morphologies by altering the combinations of chemically distinct polymer segments that interact selectively with their environment, such as in aqueous or organic solvents, or within a polymer matrix. The ability to tailor morphological features by manipulating polymer chain length, composition, and monomer chemistry has led to applications in advanced material manufacturing, catalysis, emulsification, environmental remediation, targeted drug delivery, gene therapy, and medical diagnostics. Consequently, understanding the relationship between copolymer architecture and the self-assembled morphologies at equilibrium, the pathways of structure …

In The Wholeness Of Time, Ethan Brue

Faculty Work Comprehensive List

"In a world that urges us to consume time, how do we change our approach, moving from simply passing time to filling it with holiness and patience that reflects God's character?"

Posting about ­­­­­­­­a Christian perspective on time from In All Things, an online hub that offers insight into maintaining and faithful and orthodox Reformed Christian worldview while fearlessly engaging in every aspect of contemporary life – until all is made new.

In the Wholeness of Time

Data For: Examining The Impacts Of Demographics, Individual Experiences, And Perceptions On Range Anxiety And Electric Vehicle Road Trips, Joshua Ward, Patrick A. Singleton, Antje Graul, Zane Regan

Browse all Datasets

Electric Vehicle Road Trip Study: These data contain anonymized responses to a survey designed to investigate the experiences, perceptions, barriers, and opportunities identified by electric vehicle (EV) drivers regarding road trips to recreational areas (like national parks) and for recreational activities.

Evolving Uk Biology Education, Helen R. Watson

Peninsula Medical School

School science curriculum reform is underway in the UK. Whilst each of the four devolved nations is at a different stage in this process, it is clear we are entering an era of opportunity for positive change, where curricula can be updated to reflect our current understanding of science and to better prepare learners for further study, work, and modern life more broadly.

From Sampling To Simulating: Single-Cell Multiomics In Systems Pathophysiological Modeling, Alexandra Manchel, Michelle M. Gee, Rajanikanth Vadigepalli

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

As single-cell omics data sampling and acquisition methods have accumulated at an unprecedented rate, various data analysis pipelines have been developed for the inference of cell types, cell states and their distribution, state transitions, state trajectories, and state interactions. This presents a new opportunity in which single-cell omics data can be utilized to generate high-resolution, high-fidelity computational models. In this review, we discuss how single-cell omics data can be used to build computational models to simulate biological systems at various scales. We propose that single-cell data can be integrated with physiological information to generate organ-specific models, which can then be …

Neuvac: Nonlinear Extreme Ultraviolet Irradiance Model For Aeronomic Calculations, Daniel A. Brandt, Aaron J. Ridley

Michigan Tech Publications

The need for reliable estimates of solar extreme ultraviolet (EUV) for operational space weather nowcasting and forecasting has motivated the development of new model of solar irradiance variability in 59 wavelength bins between 1 and 1,750 Å. The model employs a nonlinear parameterization of rebinned daily FISM2 irradiances and is termed NEUVAC: Nonlinear Extreme Ultraviolet Irradiance Model for Aeronomic Calculations. The model is parameterized in terms of F10.7 and 54-day averaged F10.7 in a backwards-looking window. The model takes advantage of the high accuracy and resolution of FISM2, and the consistent availability of F10.7 data in order to provide the …

Harmonic Impedance Modeling And Oscillation Analysis Of Modular Multilevel Converter, Yuhong Wang, Wensheng Chen, Shilin Gao, Jianquan Liao, Yangfan Cheng

Journal of System Simulation

Abstract: To facilitate rapid analysis of the oscillation stability mechanism in modular multilevel converter-based high voltage direct current (MMC-HVDC) systems and streamline the simulation process for determining MMC impedance characteristics, a simplified mathematical simulation model for MMC closed-loop impedance is developed using the harmonic state space method. This model considers various control strategies and includes both AC-side and DC-side impedance models. By applying a Nyquist criterion-based impedance analysis method, the stability mechanisms on the AC and DC sides of the MMC are examined. In addition, a data-driven oscillation stability analysis method is also proposed, leveraging a global sensitivity algorithm based …

Path Planning Of Desert Robot Based On Deep Reinforcement Learning, Ming Li, Wangzhong Ye, Jiehua Yan

Journal of System Simulation

Abstract: Due to the complexity and variability of the desert environment, the key to the high-efficient of mobile robot is how to avoid obstacles and plan its path. To solve the problems of poor search efficiency and slow convergence of deep reinforcement learning algorithm in complex environment, an improved deep reinforcement learning path planning algorithm is proposed. The exploration factor is improved and dynamically adjusted according to the convergence degree of the algorithm, so that the exploration factor dynamically decreases with the increase of the understanding degree of the agent to the environment, thus speeding up the convergence speed of …

Investigating Catalytic Conversion Of Lignin To Valuable Products, Jialiang Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Lignin is a complex, random, and heterogeneous biopolymer in lignocellulosic biomass. It has significant potential for conversion into valuable chemicals and fuels. However, its natural recalcitrant structure has made selective depolymerization challenging. This dissertation presents a detailed investigation into the mechanisms of lignin disassembly and structural evolution under various catalytic and solvent conditions. The research spans three key studies. In Chapter 2, operando magic-angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) spectroscopy was employed to study reaction pathways and kinetics of lignin model polymers during catalytic hydrogenolysis. We used a Ni-Al2O3 catalyst in methanol under high temperature and pressure, and …

Investigating Catalytic Conversion Of Lignin To Valuable Products, Jialiang Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Lignin is a complex, random, and heterogeneous biopolymer in lignocellulosic biomass. It has significant potential for conversion into valuable chemicals and fuels. However, its natural recalcitrant structure has made selective depolymerization challenging. This dissertation presents a detailed investigation into the mechanisms of lignin disassembly and structural evolution under various catalytic and solvent conditions. The research spans three key studies. In Chapter 2, operando magic-angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) spectroscopy was employed to study reaction pathways and kinetics of lignin model polymers during catalytic hydrogenolysis. We used a Ni-Al2O3 catalyst in methanol under high temperature and pressure, and …

Econometric Insights Into Lng Carrier Port Congestion And Energy Inflation: A Data-Driven Approach, Stavros Karamperidis, Konstantinos Melas, Nektarios Michail

Plymouth Business School

We examine how LNG carrier port congestion in European ports, measured via detailed vessel-level AIS data, affects euro area energy inflation. As energy inflation significantly affects headline inflation, this study provides an additional factor that can contribute to inflationary pressures. Overall, the results show that higher port congestion increases natural gas prices with the latter having an impact on energy inflation. The reaction stands at 0.1% per 1% shock in port congestion. These findings underline the relationship between the shipping industry and the real economy and support the view that shipping developments can potentially be used as leading indicators.

Information Management Plan – Delivery Team, Robert Moore

Tools

Information Management Plan – Delivery Team is a support in a spreadsheet format that contains a number of delivery team (tenderers) templates that ISO 19650 recommend the delivery team (tenderers) should consider when responding to a tender to deliver a project for an Asset.

Build Digital has created Industry templates to allow organisations work in accordance with ISO 19650. These templates start to address the information requirements in the ISO 19650 series of standards. The templates are also in accordance with CEN-TR17654-2021” Guideline for the implementation of Exchange Information Requirements (EIR) and BIM Execution Plans (BEP) on European level based …

A New Form Of Greenwashing: Why The Implementation Of Carbon Capture Cannot Be Justified For The Public Good Under The Takings Clause Of The Fifth Amendment, Emma Valiante

Seton Hall Law Review

No abstract provided.

Developing Naturalistic Precision Functional Mapping For High-Density Diffuse Optical Tomography, Aahana Bajracharya

McKelvey School of Engineering Graduate Student Theses & Dissertations

Advancements in non-invasive imaging have enabled extensive research into higher-order cognitive functions of the brain. Functional Magnetic Resonance Imaging (fMRI) has provided valuable insights into brain networks underlying various cognitive processes. However, limitations such as confined environments and scanner noise pose challenges for fMRI to be broadly applicable across all demographics and experimental conditions, especially in speech and language studies. Because of this, there is a need for complementary techniques that can help understand the brain as it functions during everyday scenarios. High Density Diffuse Optical Tomography (HD-DOT) is an emerging functional near-infrared spectroscopy-based technique with comparative advantages over fMRI, …

Bone-Ivd Crosstalk And The Role Of Rage Signaling In An Ivd Injury Model, Remy Walk

McKelvey School of Engineering Graduate Student Theses & Dissertations

Low back pain (LBP) is the number one musculoskeletal cause of disability with a lifetime prevalence of up to 85%. The causes of LBP are multifactorial with potential contributions from factors such as tissue injury and degeneration as well as social economic and psychological factors. Intervertebral disc (IVD) degeneration is associated with 26-40% of LBP cases and in a 2015 meta-analysis, it was estimated that a total 403 million people suffer from symptomatic IVD degeneration. IVD degeneration is characterized by loss of hydration in the nucleus pulposus (NP), damage accumulation in the annulus fibrosus (AF) and calcification of the cartilaginous …

Defining The Chondrocyte “Mechanome”: How Mechanosensitive Ion Channels Trpv4 And Piezo1 Drive Changes In Gene Expression To Affect Cell Behavior And Cartilage Health, Daniel Raymond Palmer

McKelvey School of Engineering Graduate Student Theses & Dissertations

Chondrocytes, the only native cell population of cartilage, utilize mechanosensitive transmembrane ion channels to sense mechanical forces. Transient Receptor Potential Vanilloid 4 (TRPV4) is activated by physiologic levels of load (resulting in ~10% tissue deformation) while PIEZO1 is activated by supraphysiologic levels of load (resulting in >50% tissue deformation). TRPV4 activation promotes the expression of a limited number of chondrogenic genes and the production of vital cartilaginous matrix proteins, while PIEZO1 activation drives cell death and senescence, cytoskeletal weakening, and production of catabolic mediators, which contribute to the development of osteoarthritis (OA). However, the path connecting activation of these channels …

Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar

McKelvey School of Engineering Graduate Student Theses & Dissertations

Alzheimer’s Disease (AD) is the leading cause of dementia, characterised by cognitive and functional impairments that disrupt daily activities. Different clinical modalities such as neuroimaging biomarkers, cognitive assessments, fluid biomarkers and genetic data provide unique and complementary information, contributing to a more comprehensive understanding of disease progression and heterogeneity in disease characteristics. With recent advancements in computational capabilities, particularly in deep learning, multimodal representation learning frameworks aim to integrate diverse clinical modalities into a cohesive framework, capturing the most significant patterns within each modality. Existing data-driven multimodal representation learning frameworks in AD research have two major limitations. First, AD progresses …

Pan-Cancer Analysis Of Rna Dysregulation, Somatic Mutations, And Matrix Stiffness Using Bioinformatics Approaches, Gongyu Tang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Cancer is a complex disease driven by genetic mutations, epigenetic modifications, and alterations in the tumor microenvironment. Understanding these intricate molecular mechanisms is crucial for advancing cancer diagnosis, prognosis, and treatment. RNA sequencing (RNA-seq) has emerged as a powerful tool to study cancer by providing comprehensive insights into gene expression, alternative splicing, and mutations at the transcriptome level. This dissertation leverages RNA-seq data to explore different dimensions of cancer biology through multi-omics integration and computational approaches. The research is divided into three main projects. First, I developed OncoDB, an interactive database to analyze gene expression, methylation patterns, and viral interactions …

The Encoding Of Decision Variables In Orbitofrontal Cortex (Ofc) Is Longitudinally Stable And Varies By Cortical Layer, Manning Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Economic choices entail computing the values of different options and then making choice by comparing values. Work in primates and rodents has shown that these mental processes rely on the OFC. Neurophysiology studies identified in OFC distinct groups of neurons encoding the value of individual options, the binary choice outcome, and the chosen value. These variables capture both the input and the output of the decision process, suggesting a decision circuit existing in OFC. A primary challenge for the field is to assess the structure and mechanisms governing this circuit. A first fundamental question is whether the circuit is stable …

Terpene Bioproduction From Non-Model Yeast: Omics Analysis And Metabolic Modeling For Guiding Scaleup Optimization, Alyssa Worland

McKelvey School of Engineering Graduate Student Theses & Dissertations

Sustainability efforts have driven significant advancements in synthetic biology, particularly through the development of microbial cell factories designed for waste reduction and resource conservation. This dissertation seeks to characterize a microbial biorefinery platform for the biosynthesis of terpene compounds from yeast, with an emphasis on the industrial bioconversion of waste lipids. Terpene compounds play crucial roles in various industrial applications; however, traditional methods of terpene production have sustainability and productivity challenges that could be overcome by using microbial biosynthesis. The yeast Yarrowia lipolytica is a microbial host well suited for converting waste oils into value-added terpenes due to its native …

Quantitative Approaches To Dissect Bivalent Antibody Binding And Detect Viruses From Aerosolized Samples, Ananya Benegal

McKelvey School of Engineering Graduate Student Theses & Dissertations

Influenza A virus (IAV) poses substantial epidemiological burdens around the world, with an estimated annual global mortality rate in the hundreds of thousands. Its rapid rate of mutation gives it a propensity for causing seasonal epidemics and occasional pandemics. As an airborne virus, IAV is most commonly transmitted through droplets and aerosols. Antibodies play a crucial role in the immune defense against IAV infection. By understanding the mechanisms of antibody-mediated defense and the transmission dynamics of IAV, we can better inform strategies for prevention, vaccination, and treatment, ultimately mitigating its impact on public health. The work encompassed in this dissertation …