ItemNon-resilience of Resilient Distributed Consensus in Multi-agent Systems(August 2023) Khalyavin, Leon Sergey 2001-; Abbas, Waseem; Yurkovich, Stephen; Ruths, JustinThis thesis explores the resilient distributed consensus in networks that lack the necessary structural robustness to achieve consensus in the presence of malicious agents. While exist- ing solutions provide robustness conditions for consensus among normal agents, they fail to evaluate network performance comprehensively when the graph’s robustness is insufficient. To address this limitation, we introduce the concept of non-convergent nodes, representing agents unable to attain consensus with any arbitrary agent due to malicious agents in the network. This notion allows us to classify graphs based on their robustness levels and assess partial performance. This study initially establishes the (r, s)-robustness of commonly en- countered graphs, such as complete, complete bipartite, 1-D distance, and circulant graphs. Our approach facilitates easier identification of robustness and enables us to gain insights into the behavior of non-convergent nodes. By understanding the dynamics of these non- convergent nodes, we can establish more relaxed conditions for converging subgraphs, which are the subgraphs that are guaranteed to converge. This knowledge enhances our under- standing of resilient algorithms and their behavior in practical scenarios. Furthermore, we present graphs with given robustness levels, including (F + 1, 1), (F, F ), and (F + 1, F ) ro- bustness, and determine the maximal number of non-convergent nodes associated with each graph. This quantification of non-resilience sheds light on the impact of graph robustness on the network’s ability to achieve consensus. Surprisingly, we find that graphs with the same structural robustness may exhibit varying degrees of non-resilience, leading to different network performance outcomes. Through numerical evaluations, we demonstrate that our approach provides a comprehensive resilience perspective beyond the conventional binary view of success or failure in the face of malicious agents. By quantifying network perfor- mance under sub-optimal robustness conditions and identifying converging subgraphs, our study opens up new possibilities for designing more resilient consensus algorithms. ItemMultilingual Extractive Question Answering With Conflibert for Political and Social Science Studies(August 2023) Whitehead, Parker Madden 2001-; Khan, Latifur; Gogate, Vibhav; Mazidi, KarenPolitical conflict and violence have emerged as prominent concerns for political scientists in both academia and policy circles. The overwhelming influx of complex and dense news makes it increasingly challenging to effectively monitor and analyze political events. To address this challenge and contribute to the advancement of conflict research, we propose the introduction of ConfliBERT English and ConfliBERT Spanish. These two domain-specific pre-trained language models are specifically designed for the analysis of political conflict and violence, and have undergone fine-tuning to excel in extractive question answering tasks, which are not susceptible to hallucination. The pre-training of our ConfliBERT models utilized our comprehensive conflict-specific corpus from diverse sources. In order to evaluate the performance of ConfliBERT for extractive question-answering, We performed fine-tuning on SQuAD v1.1 and NewsQA, two large question-answering datasets. Additionally, we created ConfliQA English and Spanish, two crowd-sourced evaluation datasets for conflict- domain extractive QA. Through extensive experimentation and evaluation on all versions of ConfliBERT English and Spanish, we proved that ConfliBERT English outperforms in analyzing political texts compared to BERT English baseline models, and provided detailed insight into further developing ConfliBERT for low-resource languages. ItemAutomated extraction of data constraints from software documentation(August 2023) Zhou, Ying 1998-; Marcus, Andrian; Wei, Shiyi; Chung, LawrenceData constraints encompass crucial business rules that specify the values allowed or required for the data utilized within a software system. These constraints are typically described in textual software artifacts (e.g., requirements and design documents, or user manuals). Previous research on data constraints in software focused on studying their implementation in the code for identifying inconsistencies or to support their traceability. This thesis contribute to the existing knowledge by studying 548 data constraints described in the documentation of nine systems. We identified and documented 15 linguistic discourse patterns employed by stakeholders to describe data constraints in natural language. In a comprehensive extensive study, we explore the use of the discourse patterns we discovered, along with linguistic elements, the operands of the data constraints and their types, as features for automatically classifying sentence fragments as data constraint descriptions. The best combination of features and learner achieves 70.87% precision and 59.73% recall (64.76% F1). The discoveries made in this thesis represent a significant advancement in the automated identification and extraction of data constraints from natural language text, which in turn is essential for enabling the automation of traceability to code and facilitating test generation associated with these constraints. ItemStudy of Wall Turbulence Response to Large-scale Homogeneous and Heterogeneous Surfaces(August 2023) Zheng, Yiran; Anderson, William; Ferruzzi, Jacopo; Iungo, Giacomo Valerio; Jin, Yaqing; Hassanipour, FatemehFully-rough wall-sheared turbulence consists of an inner and outer layer, each with its own distinct characteristics. The inner layer is composed of sinuous structures sustained by an autonomous cycle, while the outer layer boasts inclined parcels of relative momentum deficit and excess. The stair-case pattern of successive uniform momentum zones (UMZs) necessitates the existence of an interfacial shear layer of abrupt velocity change on the wall- normal direction. This phenomenon has been established in prior research and highlights the importance of understanding the structure and behavior of fully-rough wall-sheared turbulence. A conditional sampling procedure has been leveraged in the LES statistics of fully rough channel flow to generalize the positions of UMZs, which prevail where sublayer interactions create large-scale and arbitrary momentum excesses or deficits. By observing the distribution of the interfacial shear layer during different conditions when fast or slow parcels of fluid pass the sampling location, gained are the insight into the flow structures and their interactions within the roughness sublayer. These observations are consistent with previous studies and provide a new perspective on the structure of fully-rough wall-sheared turbulence. The relationship between wall roughness obliquity and the flow regime of the fully-rough wall-sheared turbulence has been investigated through parametric assessments. This research estimates between the flow pattern of the internal boundary layer (IBL) when there is large- scale orthogonal roughness heterogeneity, and the secondary flow of the second kind, i.e., the counter-rotating secondary cells, under the circumstance of the heterogeneity parallel to the streamwise direction. Of particular interest is the transition at the obliquity angle, 22π/56, where a critical obliquity is observed and the sheltering area abruptly changes. These findings provide valuable insights into the behavior of fully-rough wall-sheared turbulence and can be used to improve future turbulence models. Additional research has found that the radial spacing between roughness elements in fully- rough wall-sheared turbulence is a crucial factor in determining the critical obliquity of the wall roughness heterogeneity. By adjusting the radial spacing between adjacent roughness blocks in a row, it is possible to shift the critical obliquity in a predictable way. This theory was discovered by studying turbulent channel flow cases of rows of roughness blocks with different oblique angles and radial spacing. The predictable influence of radial spacing on critical obliquity further highlights the interplay between successive element sheltering, the flow patterns of IBL, and secondary cells, which are all key factors that determine the structure and behavior of turbulence in fully-rough wall-sheared flows, and further to contribute to refining turbulence models and improving the understanding of fully-rough wall-sheared turbulence. ItemHemodynamic Response Variability and its Relationship to the BOLD signal in Younger and Older Adults(August 2023) Taylor, Mackenzie Breann 1996-; Rypma, Bart; Rennaker, Robert; Spence, Jeffrey S.; Seaman, Kendra; Krawczyk, DanielStudies have shown age-related differences in blood-oxygen-level-dependent signal (BOLD) variability, specifically amplitude variability. However, results have been mixed. Little remains known about the sources contributing to this variability. Identifying these sources would have implications for underlying mechanisms contributing to BOLD measurement. Changes in BOLD yield a characteristic hemodynamic response function (HRF) that reflects a combination of blood flow and oxygenation changes that follow neural activity. In healthy aging, multiple components of the HRF (e.g., time-to-peak, rise slope, peak amplitude, full-width half-maximum, peak-to- trough, time-to-trough, fall slope, and trough amplitude) are susceptible to the mediating effects of age-related cerebrovascular alterations and underlying processes. Additionally, several studies have demonstrated that neuro-vascular coupling (NVC) differences in older adults are mirrored in HRF differences. To further explore these phenomena, the current study utilized the publicly available Cambridge Center for Aging and Neuroscience (CamCAN) dataset to estimate HRF variability in a visual-auditory task in 80 younger (18-30 years old; 44 Female/36 Male) and 212 older adults (54-74 years old; 100 Female/112 Male). The proposed study was carried out according to three aims: (1) examine intra-individual HRF variability in younger and older adults, (2) examine inter-individual HRF variability in younger and older adults, and (3) determine the relationship between HRF variability and cognitive performance in younger and older adults. Linear mixed models were used to assess individual and age-related differences in HRF features. I hypothesized that individuals, regardless of age, would have increased HRF variability in higher frequency task conditions compared to lower frequency conditions. For age- related differences, I hypothesized that older adults would have increased HRF feature variability, and that their HRF variability would be inversely related to canonical-derived BOLD voxel extent. Finally, I hypothesized that there would be an interaction between HRF variability, age, and cognitive performance such that low-performing older adults would have increased HRF variability compared to high-performing older and younger adults. For group differences in HRF feature variability, I found that increased/decreased HRF feature variability was associated with increasing auditory frequencies depending on the region examined. For group differences in mean HRF features, I found that increased mean HRF features were associated with increasing auditory frequencies, with the exception of fall slope which exhibited an inverse relationship. Older adults had increased HRF feature variability and mean HRF features, primarily in the precentral and temporal ROIs, compared to younger adults. Older adults’ increased voxel extent was associated with decreased variance of their rise slopes, full-width half-maxima, peak-to- troughs, and time-to-troughs. Finally, younger adults exhibited a significant relationship between their reaction times and mean HRF features in the highest frequency condition while the older adults did not. My results showed that HRF feature variability exhibits region- and task- dependent differences that need to be accounted for when performing age-group comparisons, the latter-half of the HRF evolution and underlying mechanisms are potential sources of additional variability in older adults, and the difference between HRF features in the precentral cortex and other sensory cortices may serve a mediatory role between age and processing speed ability. This study assessed features of BOLD HRF shape as a proxy of NVC to identify potential sources of altered age-related variability and their relationships to behavior. ItemTowards Securing Untrusted Deep Neural Networks(August 2023) Guo, Junfeng; Yang, Wei; Hassanipour, Fatemeh; Wei, Shiyi; Guo, Yunhui; Xiang, YuDeep Neural Network (DNN) models have achieved remarkable success in various domains, ranging from image recognition to natural language processing. However, the increasing reliance on cloud-based services and the proliferation of machine learning applications have raised concerns regarding the security and privacy of these models. Protecting untrusted DNN models from malicious manipulation and exploitation has become a critical challenge. This dissertation addresses the issue of protecting untrusted DNN models from malicious manipulation (ie, Trojan attack) and proposes a framework to enhance their security against Trojan (backdoor) attacks. The framework consists of multiple dimensions of defenses that collectively aim to safeguard the integrity of the models. First, we introduce the background of Trojan attack and the settings of each proposed method. Specifically, we propose two kinds of defense approaches against current Trojan attacks, one is for model-level and another is for input-level. Both two proposed defense approaches are built upon the most practical scenario, i.e., Black-box and Hard-Label scenario. The Black-box means that the defender can not access the detailed parameters for the target model; while the hard-label implies that the defender can only access the final prediction label for the target DNN models. To the best knowledge, such a scenario is one of the most practical and challenging scenarios for Trojan Defense. To tackle the Trojan attacks, we propose two methods, i.e., AEVA and SCALE-UP. AEVA is a novel Trojan detection approach that is implemented upon suspicious models. As for SCALE-UP, it is an input-level Trojan defense technique, which is implemented upon the input data during the inference phase. Both two techniques are inspired by certain intriguing properties of DNN models and shown effective in the backdoor defense task. Lastly, we discuss the potential adaptive attacks against our defense approaches and evaluate their effectiveness. We find that our defense approach can still perform robustness against potential adaptive attacks. ItemSoftware Defined Orchestration of Network and Compute Resources(August 2023) Mirkhanzadeh, Behzad 1989-; Fumagalli, Andrea; Kantarcioglu, Murat; Miguel Razo-Razo; Tacca, Marco; Hu, Yang; Razo-Razo, Miguel; Jue, JasonEdge computing is an attractive architecture to efficiently provide compute resources to many applications that demand specific QoS requirements. The edge compute resources are in close geographical proximity to where the applications’ data originate from and/or are being supplied to, thus avoiding unnecessary back and forth data transmission with a data center far away. This dissertation works towards a federated edge computing system in which compute re- sources at multiple edge sites are dynamically aggregated together to form distributed super- cloudlets and best respond to varying application-driven loads. In order to provide such collaborative system, we build a compute domain that relies on a multi-layer transport networks consist of a Wavelength Division Multiplexing (WDM) optical domain, an Ethernet packet switching domain in a single turnkey solution. The software defined networking (SDN) PROnet Orchestrator is designed and implemented to concurrently manage the resources offered by the optical network equipment, compute nodes, and associated Ethernet switches and achieve the key functionalities of the proposed super- cloudlet architecture. ItemAnalyzing Tidal Circularization In Exoplanet Systems To Determine The Tidal Dissipation Efficiency Of Giant Planets(August 2023) Mahmud, Mohammad M 1986-; Penev, Kaloyan; Wu, Yunan; King, Lindsay J.; Kesden, Michael; Ishak-Boushaki, Mustapha; Anderson, PhillipA planet in the gravitational field of its parent star experiences a tidal force due to the variation of the gravitation at different points on it at different distances from the star. The planet gets distorted, being stretched by this difference of gravity. This distortion raises two bulges (called “tidal bulges”) along the star-planet joining line on two opposite sides of the planet (p). When it (p) revolves in an eccentric orbit, the tidal distortion varies since the tidal force varies with the distance from the star. The repetitive tidal distortion causes a periodic variation of the amplitude of the tidal bulges. The difference between the planet’s rotational angular speed and the system’s orbital angular speed also varies with the planet-star distance. It causes the tidal bulges to move around the planet, creating a tidal wave. The friction and viscous force within the different layers of the planet resist the motion of the tidal wave and the variation of its amplitude, resulting in the generation of heat. Ultimately, some portion of the system’s orbital energy converts into heat. The gradual loss of the system’s orbital energy reduces the orbital eccentricity and semimajor axis. A ubiquitously used term that parameterizes tidal dissipation is the modified tidal quality factor (Q′ pl). Q′ pl is inversely proportional to the tidal dissipation rate. In this project, we determined a possible range of Q′ pl of short-period gas giants. The periodically varying tide acting on different parts of the planet, sometimes coupling with other forces (like Coriolis force), generates multiple components of the tidal wave that depend on the time-dependent tidal frequency. So we prescribe an empirical model where Q′ pl may depend on the frequency to consider different possible tidal wave components. We applied our analysis to 78 exoplanet systems consisting of a single planet orbiting a single host star. We worked out an allowed range of the frequency-dependent Q′ pl for each system and combined them to find general constraints on Q′ pl. We determined the upper limit of Q′ pl by requiring that if the system starts evolution with a sufficiently high initial eccentricity, then the eccentricity simulated at the present age for which the simulated orbital period matches the measured value of the orbital period, should be lower than the envelope observed in the ‘eccentricity vs. semimajor axis to planetary radius scatter plot’ of a collection of exoplanet systems. We determined the lower limit of the same parameter by requiring that it should not be lower than the measured orbital eccentricity at the present age. We find that the value of log10 Q′ pl for HJs is 5.0 ± 0.5 for the range of tidal period from 0.8 to 7 days. We do not see any clear sign of frequency dependence of Q′ pl within the mentioned uncertainties. ItemOptimal Control of Human Balance Models With Reflex Delay(August 2023) Rajapaksha, Lashika Nishamani 1990-; Anderson, Phillip C.; Turi, Janos; Lou, Yifei; Cao, Yan; Pereira, FelipeFalls are the leading cause of injury-related deaths among the elderly, and scientists are increasingly interested in understanding the mechanism of human balance control. A single inverted pendulum is used to model the musculoskeletal dynamics of the human body with an ankle torque. There is a brief period of time between detecting a problem in proper positioning and applying torque to correct it. We present a mathematical optimal control model with delay for identifying human balance postural dynamics considering humans as a single inverted pendulum with an ankle torque. The equation of motion is a second-order delay differential equation, and it is solved numerically. Optimal feedback gains obtained from the optimal control problem with linear quadratic regulator function vary in time for a short period of time before becoming constant. These optimal feed- back gains are time and delay-dependent to compensate for the effect of the delay. We provide numerical simulations for different parameter values and scenarios to investigate human postural dynamics’ stability and demonstrate the model’s capabilities. Finally, we extend our study by investigating the dynamics of ankle and hip movement in response to perturbations using a double-inverted pendulum. ItemSocial Security Reforms in Chile: Effects on Poverty, Labor Supply, and Savings(August 2023) Faundez Madariaga, Sebastian Carlos; Li, Dong; Giertz, Seth; Harrington, James R.; Miranda-Pinto, Jorge; Siqueira, KevinThis dissertation examines the effects of Chile’s solidarity pensions on retirement behavior, poverty reduction in old age, and the consequences of early pension withdrawals during the COVID-19 pandemic. The first study analyzes the impact of expanded solidarity pensions on retirement decisions and poverty rates using a life cycle model for married males and data from the Chilean Social Protection Survey (EPS). The findings show that increased mini- mum pensions discourage labor force participation and lead to earlier retirements, while also reducing poverty among individuals over 65. The second study focuses on the consequences of early pension withdrawals during the pandemic. Using a life cycle model and taking ad- vantage of a supplementary section in the EPS on early withdrawals during the pandemic, the research assesses the effects of these withdrawals on pension wealth, saving rates, and replacement rates. The findings indicate that early withdrawals significantly reduce private pension savings at retirement, resulting in lower replacement rates. However, the inclusion of solidarity pensions helps mitigate the reduction in replacement rates, particularly bene- fiting those who made withdrawals in their 40s and individuals with middle incomes. This dissertation provides valuable insights for policymakers and individuals regarding pension reforms and retirement decisions. ItemDeep Convolutional Neural Network Encoding of Face Shape and Reflectance in Synthetic Face Images(August 2023) Hill, Matthew Q. 1988-; O'Toole, Alice J.; Rugg, Michael; Assmann, Peter F.; Golden, Richard M.; Castillo, Carlos D.Deep Convolutional Neural Networks (DCNNs) trained for face identification recognize faces across a wide range of imaging and appearance variations including illumination, viewpoint, and expression. In the first part of this dissertation, I showed that identity-trained DCNNs retain non-identity information in their top-level face representations, and that this informa- tion is hierarchically organized in this representation (Hill et al., 2019). Specifically, the sim- ilarity space was separated into two large clusters by gender, identities formed sub-clusters within gender, illumination conditions clustered within identity, and viewpoints clustered within illumination conditions. In the second part of this dissertation, I further examined the representations generated by face identification DCNNs by separating face identity into its constituent signals of “shape” and “reflectance”. Object classification DCNNs demon- strate a bias for “texture” over “shape” information, whereas humans show the opposite bias (Geirhos et al., 2018). No studies comparing “shape” and “texture” information have yet been performed on DCNNs trained for face identification. Here, I used a 3D Morphable Model (3DMM, Li, Bolkart, Black, Li, and Romero 2017) to determine the extent to which face identification DCNNs encode the shape and/or spectral reflectance information in a face. I also investigated the presence of illumination, expression, and viewpoint information in the top-level representations of face images generated by DCNNs. Synthetic face stimuli were generated using a 3DMM with separate components for a face shape’s “identity” and “facial expression”, as well as spectral reflectance information in the form of a “texture map”. The dataset comprised ten randomized levels each of face shape, reflectance, and expression, with three levels of illumination (spotlight, ambient, 3 point), three levels of viewpoint pitch (-30°, 0°, 30°), and five levels of viewpoint yaw (0°, 15°, 30°, 45°, 60°) in a complete factorial design for a total of 45,000 images. All analyses were conducted with an Inception ResNet V1-based network (Szegedy, Ioffe, Vanhoucke, & Alemi, 2017) trained on the VGGFace2 dataset (Cao, Shen, Xie, Parkhi, & Zisserman, 2018) and replicated with a ResNet-101- based network (He, Zhang, Ren, & Sun, 2016) trained on University of Maryland’s Universe dataset (Bansal, Castillo, Ranjan, & Chellappa, 2017; Bansal, Nanduri, Castillo, Ranjan, & Chellappa, 2017; Guo, Zhang, Hu, He, & Gao, 2016). Area Under the Receiver Operating Characteristic Curve (AUC) was used as a measure of information for each variable in the top-level representation and t-distributed Stochastic Neighbor Embedding (Van der Maaten & Hinton, 2008) was used to visualize the similarity space of top-level representations. The results showed that both shape and reflectance information were encoded in the top-level representation, and both signals were required for optimal performance. Shape-reflectance bias was mediated by illumination such that the network showed a reflectance bias in ambient and 3 point (photography style) illumination environments, whereas no bias was found under spotlight illumination. Consistent with Hill et al. (2019), we found information about all non-identity variables (illumination, expression, pitch, yaw) in the top-level representation, although each of these signals was weakly encoded. ItemComputational Analysis of Porous Structures Considering Coupled Diffusion Law With Large Volume Expansion(August 2023) Lindsay, Grant Timothy 09/14/1998-; Ryu, Ill; Li, Wei; Qian, DongThe increasing interest of silicon anodes for lithium-ion batteries (LIBs) can be attributed to their high charge capacity and recharge speed. Severe volume expansion from the lithiation process, however, results in pulverization and mechanical failure of the silicon anode. To both improve charge capacity and mechanical stability, designers have tested multiple geometries of nanostructures varying from nanotubes to silicon hollow-spheres. Although failure analysis can be performed by observing the surface morphology of these structures, the physical model of lithiation and corresponding stress analysis is highly limited, not only because geometries of these structures are quite complex to mode, but also because it requires modification of the diffusion law due to large volume expansion which could alter the chemical potential. In this work, we will formulate a modified coupled diffusion law to consider large volume expansion which the Si anode experiences during lithiation and delithiation. We incorporate this generalized diffusion equation into commercial package (ABAQUS) using user-subroutines, in order to develop a physical model under various environments. Through a series of test cases, we can analyze the effects of large deformation on the diffusion profile, as well as the effects of changing geometries on the stress profile. Deformations and stress gradients are shown to be able to expedite the diffusion process, while drastically decreasing the area along the diffusion path is shown to result in stress concentrations. Based on these physical insights, we apply it to models with realistic porous geometries to investigate general design guidelines: columnar void structures along parallel to the diffusion path could alleviate stress concentration, compared to misaligned voids. Structures with gradual area changes such as spherical voids could have a more relaxed stress field. This multi- physical modeling technique could allow us to analyze structural stability and also serve as a standard to develop nanostructures for optimal design. ItemSemantic interference and facilitation: the role of feature cues and category in naming(August 2023) Dugas, Christine Sofka April 12 1985-; Hart Jr., John; Owen, Margaret Tresch; Maguire, Mandy J.; Lee, Yune; Spence, JefferySemantic interference effects have been observed in a variety of naming paradigms where categorically related items, (i.e., cow, horse, sheep), elicit longer naming latencies than categorically unrelated items (i.e., book, knife, mirror). However, under certain conditions, semantic facilitation effects (i.e., shorter naming latencies) may be observed from categorically related items depending on the context and order of presentation within a paradigm. Semantic interference and facilitation effects observed in naming are also proposed to be differentially influenced by the correlational nature of the features that comprise these concepts. Using a lexically cued naming paradigm with word pairs designated as either “distinctive” or “shared” features to elicit a target concept which was either related to other concepts within a category or not, evidence for semantic facilitation effects were found for concepts from categorically related items (e.g., farm animals, zoo animals, pets, etc.) when cued by distinctive features. Interestingly, semantic interference effects were not observed in a lexically cued naming paradigm. Likewise, event-related potentials (ERPs) were evaluated, and a significant effect of category (related vs unrelated) was found in the left frontotemporal and right centroparietal regions between 600-1100ms. These ERPs are proposed to represent in the initiation of feature integration beginning approximately 600ms following stimulus presentation and approximately 1200ms prior to naming, indicating an amplitude divergence between categorically related and unrelated concepts. Given the behavioral and EEG data, the following account of semantic and lexical processing is proposed: Categorically related concepts facilitate semantic processing at the superordinate level (i.e., categorical or domain) and features of concepts less likely to co-occur with other concepts (i.e., “distinctive” features) facilitate activation of concepts at the basic level (i.e., specific concept) as measured by naming. Frequent activation of features common among related concepts facilitate subsequent activation of related concepts which facilitates superordinate level semantic processing and distinctive feature cues facilitate access to the basic-level identification required for naming. Categorical level effects are shown to influence naming and neural correlates and when related concepts (or concepts with increased activation of features) are cued by distinctive feature cues, naming latencies and errors are decreased compared to other conditions. Our results suggest when facilitation occurs at both superordinate and basic levels of conceptual processing, naming performance improves. ItemMurphy: a Framework for Identifying Risks for Collaborative Systems During Requirements Engineering(August 2023) Kolluri, Kirthy 1987-; Chung, Lawrence; Fonseka, John; Wong, W. Eric; Bastani, Farokh B.; Nguyen, Tien N.A risk is an undesirable event that can result in mishaps if not identified early on during requirements engineering adequately. However, requirements engineers may not always be aware if important/critical risks are ignored. For instance, in building a smartphone appli- cation to help blind people navigate indoors, it may not be too evident to the requirements engineer that a blind person may not be able to walk in a straight line, or may not be able to turn at a right angle at the right spot, etc. Similarly, for an Autonomous Vehicle run- ning on the Autodrive System (ADS), it may not be too evident that the driver may ignore instructions from the system or the ADS may not be able to identify obstacles accurately or may not be able to identify any obstacles at all. These are a few examples of many such risks that can occur with collaborative systems, where the (semi-)automated systems and the agents in their environments need to collaborate with each other to achieve the intended goals of the stakeholders. However, identifying risks can be challenging, and there is a lack of systematic risk identification and analysis approaches to identifying risks for collaborative systems. This dissertation presents Murphy and Murphy+G frameworks for identifying and analysing risks. Murphy is an Ontology-based framework that adopts the Reference Model to sys- tematically identify risks by generating a Risk Analysis Graph (RAG). Murphy+G is a goal-oriented framework that extends Murphy Framework for identifying risks, facilitating the requirements for engineers/developers to devise risk-mitigation strategies by adopting the NFR Framework and extending it with the Reference Model to identify risks and perform risk analysis qualitatively. We propose five main technical contributions: 1. The domain-independent, activity-oriented ontology and processes for both Murphy and Murphy+G are presented explicitly for de- scribing categories of essential concepts and relationships and constraints related to agent, action, risk, requirements, specification, domain, etc. The ontology ensures that there are no omissions and commissions of risks. 2. An Augmented Reference Model is obtained by adopting the Reference Model and extending it with risks to perform risk generation and identification. 3. Rules for systematically generating risks and thereby facilitating the devel- opment of risk mitigation strategies later. 4. A Risk Analysis Graph (RAG) shows a bigger picture of all the risks possible for a requirement and its corresponding specification and domain assumptions. 5. The (SIG-PIG)+ RM (Reference Model) graph, which considers NFRs, identifies risks and corresponding mitigation strategies for achieving user goals by us- ing the Reference Model. To see the strengths and weaknesses of Murphy and Murphy+G, we have used the Murphy Assistant tool to identify a set of risks from a requirement. These risks are categorized based on their criticality, and these results are compared against the risks identified by students from team projects. We feel that the proposed framework helps identify the most important and critical risks and devise risk-mitigation strategies for those risks, which would help users to avoid risks to some extent and feel confident about using the system. ItemNeuroimmune and Endocrine Interactions Driving Female-biased Mechanisms in Reproductive Physiology and Pain(August 2023) Lenert, Melissa Elizabeth 1995-; Burton, Michael; Shoup, Angela; Dussor, Gregory; Merriwether, Ericka; Thompson, LucienSex and gender disparities in healthcare have a profound negative impact on women’s health. Until recently, most preclinical neuroscience research has relied almost entirely on male animals to the exclusion of females due to perceived confounds by hormonal cycling. The usage of female animals in preclinical settings in recent years has opened a realm of possibility in neuroscience research as many groups have demonstrated sex biases in neuroimmune and endocrine crosstalk. Several disorders exhibit female-biased prevalence, including many chronic pain disorders and reproductive system disorders. Additionally, treatments for these disorders are often less effective in women and come with ill-tolerated side effects. Thus, there is a strong need to study female- biased mechanisms in these disorders to improve therapeutics and patient outcomes. This work focuses the role of metabolic stress, both cellular and whole-body, in the regulation of female fertility. First, we induced whole-body metabolic stress via consumption of a high-fat diet by young female mice and measured changes in estrous cycling and serum progesterone. We found that a high-fat diet induces transient shifts in estrous cycling and progesterone levels prior to overt weight gain. Next, we utilized a transgenic mouse model with conditional removal of LKB1 in peripheral sensory neurons to model neuronal metabolic stress. Females with LKB1 deletion have greatly enhanced fertility compared to wild-type mice, with no effect of LKB1 removal in male mice. Further, LKB1 in sensory neurons promotes ovarian innervation. We then utilized a preclinical model of chronic muscle pain to validate a battery of pain and functional assessments. Those measurements were directly compared to pain and functional assessments performed in a clinical trial with women with FM. Finally, we assessed changes in adaptive immune cell phenotypes before and after treatment with IL-5, a cytokine previously demonstrated to play a unique role in chronic muscle pain and women with FM. Overall, this work highlights female biased mechanisms that modulate neuroendocrine communication and fertility and neuroimmune crosstalk during chronic muscle pain. ItemLeft Orderability of Cyclic Branched Covers of Rational Knots(August 2023) Meyer, Bradley D 1993-; Tran, Anh; Dieckmann, Gregg R.; Dabkowski, Mieczyslaw K.; Dragovic, Vladimir; Ramakrishna, ViswanathA non-trivial group G is left orderable if there is a total ordering < on G such that g < h implies f g < f h for all f, g, h ∈ G. In this dissertation, we study the left orderability of the fundamental groups of cyclic branched covers of the 3-sphere, S3, branched over rational knots. Specifically, the focus is on the three parameter family of rational knots C(2p, 2m, 2n+1) in the Conway notation. This study is motivated by the L-space conjecture of Boyer-Gordon-Watson, which states that an irreducible rational homology 3-sphere is an L-space if and only if its fundamental group is not left oderable. A sufficient condition for the fundamental group of the r-th cyclic branched cover of S3 branched over a prime knot to be left orderable was given by Hu in . As an application, Turner determined the left orderability of the fundamental groups of the cyclic branched covers of the rational knots C(2n + 1, 2, 2) for a positive integer n. In Chapters 2 and 3, we generalize Turners results to the rational knots C(2p, 2m, 2n + 1) where p, m, n are integers. ItemElectrical Reliability of Twinned Metallic Nanowires(August 2023) Waliullah, Mohammad 1989-; Bernal Montoya, Rodrigo; Henderson, Rashaunda; Kumar, Golden; Minary, Majid; Lu, HongbingIn today’s technology, the transistors have reached such a small size that it is increasingly costly to shrink them more. Therefore, the industry is leaning towards increased functionality of the devices rather than miniaturizing. Thus, new technologies are emerging e.g., stretchable, and wearable electronics. In addition to the high current density (~107 A/cm2) requirement due to smaller size, these technologies require excellent mechanical and optical properties. Metallic nanowires are excellent candidates for these devices meeting all the requirements. However, as surface to volume ratio increases, in nanoscale, the energy carriers- phonons (heat) and electrons (electricity), are scattered increasingly. Additionally, diffusion through the grain boundaries also increases. Moreover, a significant portion of these devices use random networks of nanowires, where conduction is not uniform, leading to more current density in some of its members, and hence localized failure of individual nanowires. Thus, assessing the electrical reliability of individual nanowires is needed. The reliability can be assessed by characterizing- 1) Joule heating and 2) electromigration. Studies show that the presence of a twin boundary across the path of an atomic vacancy slows down its diffusion. Since electromigration is a vacancy diffusion process, we are interested in studying the failure of twinned nanowires. However, silver nanowires are more prone to degradation over time and electromigration tests can go on for weeks. Hence, silver nanowires were selected for Joule heating study, which does not require longevity, and gold nanowires were selected for electromigration study. Thus, the goals of this dissertation are as follows: 1. To quantify the failure current densities of silver nanowires in relation to diameter with theoretical validation. 2. To quantify the median time to failures by electromigration of twinned gold nanowires at different temperatures. 3. To compare the electromigration data between twinned gold nanowires and other interconnects with grain boundaries, to observe the effect of twins on electromigration. In the Joule heating study of silver nanowires, we established the behavior of their failure current density against diameter for 93 samples. Heat transfer modelling was employed to explain the results, and Weibull statistics were used to quantify failure probabilities. The scatter observed in the measurements was attributed to surface roughness variations. The results quantify the Joule heating electrical reliability of silver nanowires and highlight the importance of heat transfer in increasing it. In the electromigration study of gold nanowires, we studied 30 samples at 3 temperatures. The median time to failure at each temperature has a lognormal distribution that can be described with maximum likelihood estimation. Electromigration activation energy was determined using Black’s equation. This is an important indicator of the modes of diffusion and the results highlight the importance of passivating the surface of nanowires to reduce electromigration. The study is divided into 5 chapters. Chapter 1 provides a background. Chapter 2 describes the experimental procedures. The results from Joule heating test are shown in Chapter 3. Chapter 4 shows the results from electromigration test. Chapter 5 shows the direction of future work. ItemTensile Deformation of Metallic Glass: Understanding the Effects of Specimen Size, Structural State and Testing Temperature(August 2023) Jabed, Akib 1994-; Wong, W. Eric; Kumar, Golden; Bernal, Rodrigo A.; Tadesse, Yonas; Toher, CormacThe disordered or amorphous structure of metallic glasses results in a unique physical and chemical feature, which makes them suitable for a variety of applications, such as precise metal parts, sporting equipment, energy conversion technologies, transformer cores, etc. In particular, micro- and nano-sized devices can benefit from the homogenous structure (down to nanoscale), high strength (1-3 GPa), large elastic strain limit (2-3%), and remarkable thermoplastic formability of metallic glasses. However, the disordered structure is also responsible for structural softening, which results in negligible tensile ductility of metallic glasses at room temperature. The lower tensile ductility is considered as a major drawback for limiting their applications. Due to the structural softening, the plastic strain in metallic glasses is localized in narrow shear bands (~20– 40 nm in thickness), which results in catastrophic failure in tension. Numerous factors such as the elastic constants, testing temperature, strain rate, sample size, and cooling rate affect the development of the shear bands. To comprehend the origin of shear band formation and lack of tensile ductility in metallic glasses, it is crucial to investigate the effects of these factors and propose a comprehensive model. While the effect of many parameters on the deformation of metallic glasses has been understood, the sample size effects have remained controversial. The contradictory findings regarding the size effects of metallic glass are triggered by numerous reasons, such as improper sample geometry, use of high-energy irradiation during sample preparation and testing as well as the absence of statistically reliable data from in-situ testing. To understand the tensile deformation behavior of metallic glass on the nanoscale, this study examines the effect of sample diameter, structural state, and testing temperature on the shear band formation process in a Pt57.5Cu14.7Ni5.3P22.5 (Pt-based) metallic glass. The novel thermoplastic drawing method was developed to manufacture numerous dog-bone-shaped tensile specimens with diameters ranging from 100 μm to 100 nm. A custom-built experimental setup was used to fabricate and test hundreds of nanosized tensile samples from Pt-based metallic glass at different temperatures. The fracture morphologies of the samples after tensile testing show a gradual shift from zero ductility (shear band mediated) to ductile necking (homogenous deformation) with decreasing sample diameter. Our observation indicates that a reduction in the testing temperature has a similar effect on the deformation behavior in all stages as the sample diameter. With a smaller sample size and/or lower temperature processing of metallic glass, the critical diameter of homogenous deformation increases. The relationship between the sample size and testing temperature in tensile fracture of metallic glasses can help in understanding the origin of ductility in metallic glass. These findings are verified and analyzed using the current shear band formation models for bulk specimens in metallic glasses. In addition, a comprehensive model for shear band development in metallic glasses is proposed, which describes the effects of sample size, structural state, and testing temperature on size-dependent changes in tensile deformation. ItemReactions to Misconducts: Exploring Diverse Relationships(August 2023) Lee, Minjung 1989-; Lee, Seung-Hyun; Ali, Ashiq; Qian, Cuili; Kautz, Jason; Park, H. DennisIn the media, we observe different kinds of misconduct almost every day. While we may assume that organizations conform to social norms, organizations commit misconduct. Thus, researchers endeavor to discover its root cause. However, a dearth of research focuses on what happens after misconduct is identified. To fill in this research gap, this dissertation contributes to organizational misconduct by highlighting reactions after misconduct. Specifically, we investigate diverse relationships surrounding misconduct. There are three essays that explore the reaction to misconduct by applying the proper theoretical lens. The first essay (Chapter 1), which was accepted and published online first by Business and Politics, dives into the dynamic between the culpable organization and bystanders. Specifically, we highlight the reaction of the shareholders at bystanders to witnesses of the misconduct and discuss the resolution. Among various types of misconduct, we choose the corrupted corporate political activity of lobbying. One of the most corrupted lobbying scandals in U.S. history, the Jack Abramoff case, has drawn considerable attention. The negative impact of the lobbying scandal pushes the boundaries of the impact on the bystanders. We explore the reaction of shareholders of bystanders to the guilty plea of Abramoff and the introduction of the new lobbying law. By using expectancy violation and category theory, we argue shareholders at bystanders show hostile responses to the corrupted lobbying scandal while favoring the new lobbying act. To show the generalizability of our arguments, we reference the Enron scandal and the introduction of the Sarbanes-Oxley act. The second and third essays leverage workplace injuries as a form of misconduct. The second essay (Chapter 2) uses workplace injuries to investigate the tense relationship between peers and the focal organization. This essay asks this research question: Does the focal organization react to peers’ workplace injuries? A theoretical lens from social comparison and impression management provides an insightful explanation to this question by arguing that peers’ workplace injuries trigger fear among the employees at the focal organizations, leading to the focal organizations’ responses: engagement in impression management is used to distinguish themselves from peers. This goal can be achieved through social comparison by their employees. The third essay (Chapter 3) narrowly focuses on the organization itself. Unlike the other two essays, the third essay investigates the reaction to the misconduct that occurred by the organization. Leveraging the fact that organizations are reluctant to invest in the prevention of workplace injuries, we ask: What makes the organization invest in the prevention of workplace injuries? Borrowing the theoretical views from optimism bias and the attention-bias view, we argue that optimism bias among top managers breaks down when workplaces experience direct loss. The breakdown of optimism bias attracts attention to injury and succeeds in deploying more resources. ItemNew Models for Flutter and Edgewise Instability Analysis of Vertical and Horizontal Axis Wind Turbines for Land-based and Floating Offshore Conditions(August 2023) Ahsan, Faraz; Griffith, D. Todd; Ng, Yu Chung Vincent; Jin, Yaqing; Koeln, Justin; Li, YaoyuWind energy is a vital part of renewable energy sector that is increasingly becoming popular to reduce the adverse effect of traditional power production methods in increasing the global temperature. As the demand for wind energy increases, the sizes of the blades of wind turbines are also increasing with the availability of novel materials and manufacturing techniques. On the other hand, these very large wind turbines might be susceptible to design challenges and instability problems because of their sheer size which typically are not concerns for relatively smaller turbines. This has motivated the development of models to predict the unstable behavior of very large vertical axis wind turbines (VAWTs) and horizontal axis wind turbines (HAWTs). This work presents modeling method of rotor-platform system for offshore floating vertical axis wind turbines. Effect of structural design parameters on flutter instability of 2-bladed and 3-bladed VAWTs are studied. An analysis is presented on the effect of floating platform on flutter behavior of rigid body and flexible modes of vibration of the coupled system. A fundamental understanding of how the floating system impacts the resonance and flutter properties of VAWT is sought and presented. Further study has been performed on the impact of aerodynamic modeling assumptions that are conventionally implemented to predict flutter of wind turbines. The shortcomings of simplifying assumptions of standard aerodynamic theory have been demonstrated, and new aerodynamic model is developed to address those shortcomings. Then, this new model is applied to both horizontal axis wind turbines as well as vertical axis wind turbines. Comparative analysis is done of the effect of standard and new aerodynamic model in terms their predictive capability of flutter for both land-based and floating vertical axis wind turbines. Large number of horizontal axis wind turbines with varying sizes and geometry are studied for flutter and edgewise instability with the newly developed aerodynamic model. Similarly, vertical axis wind turbines are examined with the newly developed aerodynamic model. This study also aims at validating numerical models with experimental results. To achieve that goal, a subscale floating VAWT system is manufactured, and experimental test is performed on it to extract modal dynamic properties. The measured structural properties are used to calibrate the rotor model, and free decay test results are used to generate a floating platform model. Finally, the rotor and platform model are coupled and modal analysis (frequency analysis) is performed and the model is further refined by comparing the test results and model predictions. Key findings of this dissertation confirm that moving a VAWT from land-based to floating configuration has the potential to alleviate both resonance and flutter concerns. Developed new aerodynamic model shows higher flutter prediction of tower, propeller and edgewise modes of land-based and floating VAWT compared to the prediction by standard aerodynamic model. For large HAWT blades, the new aerodynamic model has more impact on 3-bladed case than on 2- bladed case in terms of flutter and edgewise instability RPM prediction. Validation study on modal dynamics of floating VAWT confirm reasonably accurate modeling of coupled rotor-platform floating model.