Digital Commons Network^™

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 …

Family Care And Health Behavior: A Sociocultural Perspective On Ebola Virus Disease Transmission In Sierra Leone, Abubakarr Jalloh

Journal of Social, Behavioral, and Health Sciences

The 2013–2016 Ebola virus disease (EVD) outbreak in West Africa was the largest and deadliest in the four-decade history of the disease. This study examined the sociocultural context of EVD transmission during the outbreak, with a particular focus on a high-risk behavior—caring for sick relatives. Guided by a sociocultural perspective on health, it specifically explored the role of family-based caregiving practices in the transmission of EVD during an outbreak. Utilizing a qualitative collective case study, I interviewed three Ebola survivors in Makeni, Sierra Leone. Content analysis resulted in two themes: (1) family care and perceived EVD transmission and (2) how …

Revisiting Territorial Sovereignty: Origins, Legitimacy, And Modern Implications, Henan Hu

San Diego International Law Journal

The conventional linkage between territory and sovereignty in international law requires reevaluation, with territorial rights shifting from states to nations. Drawing on Anthony Smith’s theory of historical continuity between pre-modern ethnic communities and modern nations, this article argues that legitimate claims to territory are grounded in the historical consolidation of social, economic, and political ties by ethnic groups to specific lands. It traces the evolution of territorial rights from loosely defined ethnic living areas and fluid state boundaries to the modern conception of national territories under effective control. By distinguishing sovereignty as a construct of the state and territory as …

Synthesis And Characterization Of Novel Diffusible Signal Factor Analogs For Antibiofilm Properties, Elisabeth Rachel Wiley

Electronic Theses and Dissertations Archive

Biofilms are composed of biomolecules, bacteria, and sometimes fungi and are considered the leading cause of antibiotic resistance. Biofilm formation and dispersion is regulated in part by signaling molecules called diffusible signal factors (DSF) through a process termed quorum sensing. However, the mechanism of action behind quorum sensing remains poorly understood. Chapter 1 focuses on the structure activity relationship (SAR) of DSF. DSF are medium chain fatty acids with an alkene at the C2-C3 carbon position. Tail length, branching, and cis/trans configuration all significantly affect antibiofilm action; these affects are also microbe specific. The chapter concludes with a discussion on …

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 …

Pushyk V. Shiyanoff

All Decisions

In this no-grounds holdover proceeding, the landlord sought to evict the tenant. The tenant asserted that the apartment was subject to rent stabilization because the building had been previously altered to contain six apartments. The court agreed with the tenant. The court found that even though the landlord claimed one of the units had been removed, evidence suggested it had previously been rented as a residential unit, triggering rent stabilization for the entire building.

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 …

Integrating Physics And Deep Learning For Transmission-Less Attenuation Compensation In Clinical Spect, Zitong Yu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Attenuation compensation (AC) is beneficial for visual interpretation and serves as a prerequisite for quantification tasks in single-photon emission computed tomography (SPECT) imaging. However, conventional AC methods typically rely on a separate X-ray CT component, leading to multiple challenges. In this context, studies have shown that scatter-window projection data contains information to estimate the attenuation distribution. Furthermore, large amounts of SPECT emission data in both photopeak and scatter-energy windows and corresponding CT scans are available. The ability of deep learning (DL) to model complex relationships by leveraging large datasets motivates its use for transmission-less AC in SPECT. Building upon the …

Development Of Computational Imaging Pipelines To Advance Quantitative Co-Clinical Imaging And Pathology, Kaushik Dutta

McKelvey School of Engineering Graduate Student Theses & Dissertations

Deep learning driven computational methods have profoundly impacted medical imaging by advancing feature extraction, and by establishing a critical foundation for downstream image analysis and interpretation. Co-clinical trials are an emerging area of investigation in which a clinical trial is coupled with a corresponding preclinical study to inform the corresponding clinical trial to enhance translational accuracy and therapeutic development. Within this framework, quantitative imaging and pathology plays a fundamental role in both clinical and preclinical arms of co-clinical trials. Quantitative imaging enables enabling identification and validation of imaging biomarkers which are leveraged to predict therapeutic response, characterize disease phenotypes, and …

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 …

Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor

McKelvey School of Engineering Graduate Student Theses & Dissertations

Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …

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 …

Integrating Physics And Deep Learning For Transmission-Less Attenuation Compensation In Clinical Spect, Zitong Yu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Attenuation compensation (AC) is beneficial for visual interpretation and serves as a prerequisite for quantification tasks in single-photon emission computed tomography (SPECT) imaging. However, conventional AC methods typically rely on a separate X-ray CT component, leading to multiple challenges. In this context, studies have shown that scatter-window projection data contains information to estimate the attenuation distribution. Furthermore, large amounts of SPECT emission data in both photopeak and scatter-energy windows and corresponding CT scans are available. The ability of deep learning (DL) to model complex relationships by leveraging large datasets motivates its use for transmission-less AC in SPECT. Building upon the …

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 …

Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor

McKelvey School of Engineering Graduate Student Theses & Dissertations

Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …

Development Of Computational Imaging Pipelines To Advance Quantitative Co-Clinical Imaging And Pathology, Kaushik Dutta

McKelvey School of Engineering Graduate Student Theses & Dissertations

Deep learning driven computational methods have profoundly impacted medical imaging by advancing feature extraction, and by establishing a critical foundation for downstream image analysis and interpretation. Co-clinical trials are an emerging area of investigation in which a clinical trial is coupled with a corresponding preclinical study to inform the corresponding clinical trial to enhance translational accuracy and therapeutic development. Within this framework, quantitative imaging and pathology plays a fundamental role in both clinical and preclinical arms of co-clinical trials. Quantitative imaging enables enabling identification and validation of imaging biomarkers which are leveraged to predict therapeutic response, characterize disease phenotypes, and …

Spatial Insight Of Kidney Sex-Dimorphism And Tumor Evolution, Chia-Kuei Mo

McKelvey School of Engineering Graduate Student Theses & Dissertations

The landscape of spatial biology research has transformed drastically in recent years allowing a comprehensive understanding of cellular organization and molecular mechanisms in various biological context. This thesis presents three complementary studies that advance our understanding of spatial organization in normal tissue biology and tumor evolution, utilizing cutting-edge spatial multi-omics approaches. The first study presents a comprehensive investigation of kidney sexual dimorphism across the lifespan, integrating six distinct technological platforms: single-nucleus transcriptomics, epigenomics, Visium spatial transcriptomics, Xenium single-cell resolution spatial transcriptomics, conventional immunofluorescence imaging, and co-detection by indexing (CODEX) multiplexed protein imaging. This multi-modal approach reveals that proximal tubules exhibit …

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 …

Womb, Gravity, And Space: Shifting Towards The Cerebellum-Basal Ganglia Paradigm In Dystonia, Diego Iacono

Department of Neurology Faculty Papers

No abstract provided.

From Factories To Homes: A Comparative Analysis Of Adaptive Reuse In New England Industrial Buildings For Multi-Family Residential Conversion, Jeremy Weeden

Theses

The adaptive reuse of industrial buildings offers a promising path toward sustainable urban development, particularly in New England. This study investigates the feasibility and energy efficiency of converting an older, unused industrial building into a multi-family residential structure by evaluating three distinct wall assemblies that preserves the exterior brick facade: existing structural brick, a typical adapted wall assembly with interior 2x4 wood construction, and a high-efficiency adapted wall assembly with an additional interior 2x6 wood construction. Through a detailed case study analysis focusing on the building’s core and shell, this research aims to identify the most effective wall assembly for …