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Architectural characterization of metazoan signaling proteins: the TSC protein complex and AKAP350
No full textSignaling is a fundamental property of all cellular life that encompasses the biological processes by which cells detect and respond to signals from themselves, other cells, and the environment. It occurs through transduction pathways generally composed of signals, receptors, effectors, regulators, and scaffolds. In this thesis, biochemical methods and electron microscopy were employed to explore the function and architecture of two distinct metazoan signaling components. First, the TSC protein complex (TSCC), which is the primary negative regulator of the mTORC1 (mechanistic target of rapamycin complex 1) signaling pathway, and second, AKAP350 (A-kinase anchoring protein 350), the largest member of the AKAP family of scaffolding proteins that compartmentalize PKA (protein kinase A) signaling in the cell. In chapter 1, a background on the biology and functions of TSCC and AKAP350 is provided, along with an overview of the latest structural insights into these signaling proteins. Chapter 2 centers on the study of endogenous TSCC made possible by the synthesis and purification of a Fab (fragment antigen-binding) region derived from a commercial antibody specific for TSC2, the largest subunit of TSCC. Using this anti-TSC2 Fab, scarce amounts of TSCC were isolated from rodent and porcine brain tissues then examined by negative stain and immunogold electron microscopy. These analyses revealed the polymerization of endogenous TSCC into a network of filaments. In chapter 3, focus switches to AKAP350 and the establishment of its full-length purification in a functional conformation from human cells. Electron cryo-microscopy (cryo-EM) imaging of purified AKAP350 revealed long, thin filaments and a polydisperse distribution of fibrillar clusters with average diameters of ~50 nm. Chapter 4 presents the discovery that AKAP350 associates with endogenous DNA and DNA-binding proteins based on analyses of purified samples using single particle image analysis, mass spectrometry and DNA sequencing. Finally, in chapter 5, unpublished efforts to locate the region of AKAP350 responsible for associating with DNA are shown, along with future directions of study for both TSCC and AKAP350 based on the work presented in this thesis. Together, these results uncover novel biological insights into the native architectures and functional interactions of TSCC and AKAP350, enhancing our understanding of their complex roles in metazoan cell signaling.Ph.D
Deformation and Failure Characteristics of Sublevel Tunnels under Triple-Level Combined Backfill Mining in Steeply-Dipping and Ultra-Thick Orebodies
Get PDFUnder triple-level combined backfill mining (TLCBM), sublevel tunnels in steeply-dipping and ultra-thick orebodies experience severe deformation and failure, posing significant safety challenges. Based on the field investigation, deformation monitoring, stress measurement, and numerical calculation, this study analyses the deformation behaviour, surrounding rock failure, and stress distribution of sublevel tunnels. A theoretical model is developed to reveal the deformation and failure mechanisms, and targeted engineering countermeasures are proposed. Results show that tunnels deform rapidly and continuously, with damage mainly occurring in the sidewalls and roof. The tunnel cross-section evolves into an asymmetric butterfly shape. The probability and intensity of future deformation and failure are positively correlated with the current damage state. Damage exhibits spatial variability: the near-disturbed side is more affected than the far-disturbed side; vertically, the middle tunnel is the most damaged; horizontally, tunnel ends are more affected than the middle. The damage process follows nine distinct stages. TLCBM places tunnels in a high-stress environment and shifts the highest stress from the lower to the middle sublevel tunnel. Disturbed stress is the dominant factor driving tunnel damage. Variations in disturbance distance lead to spatial variability in tunnel damage. These findings support tunnel design, reinforcement, and risk management in similar mines.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
Diagnostic Assessment of Property Tax in Nigeria – The Case of Kaduna State
Get PDFNigeria has experienced weak tax policies and administration, limiting the funding of essential public goods and services. Property tax has significant revenue potential for subnational governments, but remains underused due to economic, administrative, and political challenges. To uncover these challenges, a diagnostic assessment was conducted to identify gaps and weaknesses in the property tax system in Kaduna State through surveys of stakeholders’ perspectives, including fiscal and tax authorities, land authorities, judiciary and legal professionals, financial services providers including tax practitioners, valuation and technology professionals, non-government actors and civil society organizations, as well as property taxpayers including property owners, developers, and property tenants. The findings from the surveys revealed key challenges relating to property tax administration in the state, including poor billing systems, limited property identification, weak enforcement, low compliance, and lack of transparency in valuation. Therefore, reforms are needed to clarify the role of relevant agencies in the delivery of bills. It is also recommended to enhance enforcement mechanisms, expand property identification, and deploy a transparent, points-based valuation method
Essays in Economic Growth and Development
Get PDFThis thesis contains three papers examining the aggregate economic consequences of policies and institutions that distort resource allocation across firms or sectors. In Chapter 1, I investigate the impact of openness to foreign firms on aggregate productivity in the context of Vietnam, a fast-growing economy. The analysis focuses on Vietnam's policy reforms between 2000 and 2015, aimed at reducing barriers for foreign firms in the manufacturing sector. I use firm-level data and develop a multi-sector model of structural transformation and production heterogeneity in which domestic and foreign firms make decisions on entry and technology investment while facing different institutional distortions. Consistent with the reforms' objective, I find that measured distortions affecting foreign firms were initially larger but substantially decreased to domestic levels over time. The model shows that this reduction in measured distortions to foreign firms substantially increases manufacturing productivity by 64 percent via two channels: (1) improving resource allocation across foreign and domestic firms and (2) incentivizing technology upgrades and more entry of higher-productivity foreign firms. Using difference-in-differences estimation leveraging staggered policy rollouts across locations, I also find significant indirect positive effects of the reforms on agricultural and service productivity. These indirect effects further amplify economy-wide productivity gains through structural transformation.
In Chapter 2, co-authored with Stephen Ayerst and Diego Restuccia, we investigate cross-country differences in aggregate productivity using firm-level data and a quantitative model of production heterogeneity with distortions that affect firms' operational decisions (selection) and productivity-enhancing investments (technology). Empirically, less developed countries exhibit greater distortions and larger dispersion in firm-level productivity distribution, primarily due to the higher prevalence of unproductive firms. Quantitatively, cross-country variations in the elasticity of distortions with respect to firm productivity account for the majority of observed empirical patterns and more than two-thirds of global labor productivity differences. Both selection and technology investment channels play a crucial role, while static misallocation also contributes, though to a lesser extent.
In Chapter 3, I establish new facts and explanations on the heterogeneous paths of structural transformation across countries. First, many countries exhibit flat-manufacturing profiles without noticeable signs of deindustrialization, which differ from the conventional steep-manufacturing hump-shaped profiles in advanced economies. Second, substantial heterogeneity exists in the labor allocation within services sector as flat-manufacturing countries tend to allocate substantially more labor into low-skilled services compared to steep-manufacturing countries. Third, heterogeneous structural transformation paths are prevalent among both earlier and later developers and not subject to the timing of development. Using a standard model of structural transformation, I find that observed differences in sectoral productivity growth are not quantitatively sufficient to generate the heterogeneous paths of structural transformation across countries. Instead, differences in relative productivity levels between manufacturing and low-skilled services account for around the majority, around 70 percent of the heterogeneity, suggesting that country-specific factors are key. I show that the observed heterogeneous paths of structural transformation contribute substantially to economic growth outcomes across countries.Ph.D
Distributed Shape Derivatives for Level-Set Topology Optimization and Their Applications to Robust Topology Optimization
Get PDFIn this thesis, we address challenges faced by level-set topology optimization methods for linear elastic structures.We focus on the formulation, analysis, and implementation of distributed shape derivatives which provide accurate approximations. Conventionally used boundary-based shape derivatives have high regularity requirements that are typically not met in practical applications and converge at a slower rate than the associated objective functionals.
We provide \textit{a priori} error analysis and numerical comparisons of boundary-based and distributed shape derivatives of linear objective functionals for topology optimization. We analyze the error in the degree- polynomial finite element approximations of the two expressions; we show that, for sufficiently regular problems, the boundary-based and distributed shape derivatives provide -th and -th order accurate approximations, respectively, of the true shape derivative. We then assess, through numerical examples, the practical implications of using distributed versus boundary-based shape derivatives in topology optimization problems; we demonstrate that methods based on the distributed shape derivative yield more robust solutions to topology optimization problems.
Next, we investigate problems with nonlinear stress-based objective functionals which are highly sensitive to minor changes in geometry. We derive the distributed shape derivative and extend the shape derivative error analysis to stress minimization problems, where the boundary-based and distributed shape derivatives are -th and -th order accurate approximations under idealized conditions. We also provide numerical comparisons of the shape derivative errors for practical examples. We then use the distributed shape derivative to perform topology optimization for stress minimization problems without the use of problem-specific heuristics or regularization techniques.
Finally, we present a non-intrusive approach to robust structural topology optimization for problems with probabilistic uncertainties in the loading and material properties. We approximate the solution to the stochastic linear elasticity equations using an anchored ANOVA Petrov-Galerkin projection scheme and develop a non-intrusive quadrature-based formulation to evaluate the robustness metric and associated shape derivative. This method significantly reduces the computational cost of evaluating the robustness metric where conventional polynomial chaos methods scale exponentially with respect to the number of random variables. We demonstrate the effectiveness of the proposed approach on various problems under loading and material uncertainties.Ph.D
Infarct Timing and Predictors of Infarct-Free Survival in Patients with Aneurysmal Subarachnoid Hemorrhage
Get PDFBackground/Objectives: Cerebral infarction significantly worsens outcomes after aneurysmal subarachnoid hemorrhage (SAH). This retrospective study analyzed early predictors of infarct-free survival and the impact of infarct timing on clinical outcomes. Methods: We reviewed 988 consecutive SAH patients treated from 2003 to 2016, all with follow-up CT scans. Baseline clinical and SAH characteristics were recorded to identify predictors of infarct-free survival and assess the relationship between infarct timing and outcomes. Results: Cerebral infarctions occurred in 475 patients (48.1%) at a median of 3.4 days post-SAH; 70.9% happened within the first week. Earlier infarctions were associated with higher in-hospital mortality (odds ratio [OR] = 0.91 per day increase, p < 0.0001) and poor 6-month outcomes (modified Rankin Scale > 3; OR = 0.96 per day increase, p = 0.012), especially within 48 h. Independent predictors of infarct-free survival included poor initial condition (WFNS ≥ 4, adjusted hazard ratio [aHR] = 1.82, p < 0.0001), intraventricular hemorrhage (aHR = 1.25, p = 0.041), aneurysm rebleeding (aHR = 1.76, p < 0.0001), acute hydrocephalus (aHR = 1.38, p = 0.020), and daily aspirin intake (aHR = 0.68, p = 0.002). The number of baseline risk factors (0–5) strongly influenced both infarction likelihood and timing (p < 0.0001). Conclusions: Cerebral infarctions predominantly occur within the first week after SAH, with earlier infarctions having a more severe impact on outcomes. Initial risk factor-adapted SAH management may improve functional outcomes
Development of Mobile Robot Architectures for Person Detection, Tracking, and Search
Get PDFAs robotic applications continue to expand into various aspects of daily life, robots in human centered environments must effectively locate and identify people in dynamic, crowded, and cluttered settings such as hospitals, retail stores, and airports. The ability of mobile robots to perform these tasks is essential for effective human-robot interaction, as robots often need to find and assist individuals located elsewhere. Current person detection and tracking methods face challenges due to the presence of intraclass variations such as occlusions, pose deformations, and varying lighting conditions. Meanwhile, person search methods rely on complete knowledge of user schedules and locations. However, robots are often required to locate individuals without prior knowledge of their schedules and must adapt to real-time events that cause deviations from usual routines. To overcome these challenges, this thesis presents three main contributions: 1) a multimodal person detection architecture that introduces Temporal Invariant Multimodal Contrastive Learning (TimCLR), which learns person representation that are invariant under intraclass variations through unsupervised learning; 2) a person tracking architecture that introduces the Latent Diffusion Track (LDTrack) method, which utilizes conditional latent diffusion models to capture temporal person embeddings and adapting to appearance changes of people over time; and 3) a person search architecture, Multimodal Large Language Model Search (MLLM-Search), that leverages multimodal large language models to interpret natural language instructions and spatial map layouts, enabling real-time search planning without complete or any knowledge of user schedules or locations. Extensive experiments conducted in simulated and real world environments, including hospitals, offices, search and rescue settings, and university campuses, validate the effectiveness of the proposed architectures. Results demonstrate significant improvements in detection accuracy, tracking accuracy, and search efficiency compared to state-of-the-art methods. The contributions of this thesis provide a foundation for advancing autonomous person search capabilities in complex, cluttered and crowded human-centeredenvironments, enhancing the potential for robots to assist in a wide range of HRI applications.Ph.D
Testing the efficiency of structured and unstructured surveys for detecting a small population of Jack in the Pulpit (Arisaema triphyllum) plants
Get PDFDetecting inconspicuous species with low abundance is challenging, yet failure to detect these species can have important conservation implications. Few experimental studies have been conducted to assess how survey protocols affect plant species detectability. We tested the efficiency of structured (transect based) and unstructured (unplanned search) surveys for the detection of a small, simulated population of Jack in the Pulpit (Arisaema triphyllum) plants. We found no significant difference in the mean percentage of plants detected between survey types (27% structured, 31% unstructured, 95% CI = -0.23, Inf). However, unstructured surveys detected slightly more plants per unit time, while structured surveys covered a slightly larger portion of the study area. Participants located 33% of plants across all 18 surveys. The probability of finding all plants in a single survey was very low (7.59 x 10-4 to 8.89%). To ensure a 95% probability of detection of at least one plant in our study, a minimum of two to four surveys would be required. These results suggest that for population estimation or presence / absence surveys, particularly for species of conservation concern with low abundance or invasive species at the early stages of invasion, a single survey might not be enough.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
Evaluating the Suitability of CRMB for High Performance Asphalt Applications
Get PDFHigh Modulus Asphalt Concrete (HMAC) offers superior stiffness and durability, making it suitable for hot/mild climates and heavy traffic. However, its performance in cold regions is limited due to binder brittleness at low temperatures. To address this, High Performance Asphalt Concrete (HPAC) tailored for cold climates is needed. This study investigates the optimization of Crumb Rubber Modifier (CRM) content to develop HPAC targeting a high-temperature PG of 82. A PG 64-22 binder was modified with 30-mesh CRM at concentrations of 3–15% and blended for 30–90 minutes at 180°C. Dynamic modulus testing revealed that 12% CRM achieves the desired PG 82, balancing stiffness and flexibility. Blending time had minimal effect on PG grade, suggesting that shorter blending durations are feasible, supporting in-field blending. While phase separation and storage stability remain concerns, in-field blending minimizes these issues and enhances practical applicability of CRM-modified HPAC for cold climate pavement design.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
Sciatic Integrity Is Necessary for Fast and Efficient Scrapie Infection After Footpad Injection
Get PDFThe agents of prion diseases have the capacity to efficiently infect susceptible hosts by peripheral routes and to project to clinical target areas of the central nervous system (CNS) via peripheral nerves. Understanding the process of prion spread from the site of infection to the CNS may allow us to identify novel therapeutic strategies. To investigate the mechanism involved in the intranerval transit of 263K scrapie prions in golden Syrian hamsters (GSHs), we transected the sciatic nerve at increasing times post-footpad injection and recorded the incubation periods as estimates of the efficiency of infection. We calculated that intranerval transit of this strain of scrapie is at least 10 times faster than previously reported and may reach 50 mm/day, similar to other neurotropic viruses. By in vivo exposure/injection of sciatic nerves to 263K infectivity, we have also shown that prion entry likely occurs via nerve terminals rather than by direct contact with the sciatic nerve. Application of this experimental approach in other forms of prion diseases could allow verification of the timing of neuroinvasion, a relevant parameter for the definition of therapeutic interventions