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Title: Topological Approaches for Quantifying the Shape of Time Series Data
Creator: Tymochko, Sarah
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Topological data analysis (TDA) is field that started only two decades ago and has already shown promise both in theory and in applications. The goal of TDA is to quantify the shape of data in a manner that is concise and robust using concepts from algebraic topology. Persistent homology, arguably the most popular tool from TDA, studies the shape of a filtered space by watching how its homology changes. The output of persistent homology is a persistence diagram, which encodes information...
Show moreTopological data analysis (TDA) is field that started only two decades ago and has already shown promise both in theory and in applications. The goal of TDA is to quantify the shape of data in a manner that is concise and robust using concepts from algebraic topology. Persistent homology, arguably the most popular tool from TDA, studies the shape of a filtered space by watching how its homology changes. The output of persistent homology is a persistence diagram, which encodes information about the changing homology.Persistent homology has shown success in various application areas; one ever growing area of study in this field is time series analysis. Nonlinear time series analysis is a research field in and of itself that aims to capture structure in time series data, however, it lacks theoretically justified tools to analyze the resulting structure. Persistent homology comes with a solid theoretical framework, is robust to noise, and quantifies the same type of structure as appears in time series data. Thus combining tools from time series analysis and TDA provides a new approach to analyze and quantify behavior in time series data.One field where time series are prevalent is dynamical systems, since a time series arises from a projection of a solution to a system. Specifically, given a time series, Takens' theorem can be leveraged to embed the time series as a point cloud in a higher dimensional space, where this point cloud is a sampling of the full state space. Then for each time series, persistent homology can be computed on the embedding. The result is a persistence diagram for each time series. The question then becomes how do we analyze this collection of persistence diagrams to learn something about the original time series data? Many people have developed methods to answer this question, through methods such as machine learning or statistics. This dissertation provides several new methods leveraging tools from both TDA and nonlinear time series analysis to study time varying data.
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Title: Robust Maxwell Solvers for Large Scale Particle-in-Cell Simulations
Creator: Crawford, Zane Daniel
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The design of modern devices is impacted heavily by the use and availability of robust, accurate, and efficient computational tools. This includes modeling devices that exploit plasma physics like particle accelerators, klystrons, ion thrusters, and micro-plasma generators among many other applications. While there are a number of current and emerging applications, the common thread between all is the need to accurately and efficiently capture all the relevant physics in geometrically...
Show moreThe design of modern devices is impacted heavily by the use and availability of robust, accurate, and efficient computational tools. This includes modeling devices that exploit plasma physics like particle accelerators, klystrons, ion thrusters, and micro-plasma generators among many other applications. While there are a number of current and emerging applications, the common thread between all is the need to accurately and efficiently capture all the relevant physics in geometrically intricate structures. The holy grail is to enable topology optimization to explore the design space. But all this requires rigorous translation from the continuous to the discrete world, while capturing all the underlying physics and not adding spurious artifacts due to discretization.A common computational model to perform this analysis is the particle-in-cell (PIC) method. It provides a straightforward paradigm to self-consistently solve for the distribution of the plasma as a collection of particles. The prevailing approach to solve for the fields in PIC is the finite difference time domain method (FDTD), or EM-FDTDPIC. But this effort leaves much to be desired, given the leaps that have been made in the finite element method; indeed, the latter is the method of choice for most commercial tools that that have become the de-facto workhorse in RF design industry. As a result, in the past decade, considerable effort has been expended in developing finite element (FEM) based PIC schemes, EM-FEMPIC. But we are still not there. One major concern of utilizing EM-FEMPIC over EM-FDTDPIC is the computational cost of FEM, which is greater than FDTD, despite the advantages of field and geometry accuracy FEM affords.This dissertation seeks to develop (i) a theoretically rigorous means to translate from the continuous to the discrete world while ensuring that there are no spurious artifacts, (ii) develops a higher order accurate method in both space and time, and (iii) overcomes cost complexity by introducing a linear scaling domain decomposition scheme. In all of these, the methods developed ensure that the necessary conservation properties are satisfied to machine precision. Numerous examples developed demonstrate these claims.
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Title: Machine Learning on Drug Discovery : Algorithms and Applications
Creator: Sun, Mengying
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Drug development is an expensive and time-consuming process where thousands of chemical compounds are being tested and experiments being conducted in order to find out drugs that are safe and effective. Modern drug development aims to speed up the intermediate steps and reduce cost by leveraging machine learning techniques, typically at drug discovery and preclinical research stages. Better identification of promising candidates can significantly reduce the load of later processes, e.g.,...
Show moreDrug development is an expensive and time-consuming process where thousands of chemical compounds are being tested and experiments being conducted in order to find out drugs that are safe and effective. Modern drug development aims to speed up the intermediate steps and reduce cost by leveraging machine learning techniques, typically at drug discovery and preclinical research stages. Better identification of promising candidates can significantly reduce the load of later processes, e.g., clinical trials, saving tons of resources as well as time.In this dissertation, we explored and proposed novel machine learning algorithms for drug discovery from the aspects of robustness, knowledge transfer, molecular generation and optimization. First of all, labels from high-throughput experiments (e.g., biological profiling and chemical screening) often contain inevitable noise due to technical and biological variations. We proposed a method that leverages both disagreement and agreement among deep neural networks to mitigate the negative effect brought by noisy labels and better predict drug responses. Secondly, graph neural networks (GNNs) has become popular for modeling graph-structured data (e.g., molecules). Graph contrastive learning, by maximizing the mutual information between paired graph augmentations, has been shown to be an effective strategy for pretraining GNNs. However, the existing graph contrastive learning methods have intrinsic limitations when adopted for molecular tasks. Therefore, we proposed a method that utilizes domain knowledge at both local- and global-level to assist representation learning. The local-level domain knowledge guides the augmentation process such that variation is introduced without changing graph semantics. The global-level knowledge encodes the similarity information between graphs in the entire dataset and helps to learn representations with richer semantics. Last but not least, we proposed a search-based approach for multi-objective molecular generation and optimization. We show that given proper design and sufficient information, search-based methods can achieve performance comparable or even better than deep learning methods while being computationally efficient. Specifically, the proposed method starts with existing molecules and uses a two-stage search strategy to gradually modify them into new ones, based on transformation rules derived from large compound libraries. We demonstrate all the proposed methods with extensive experiments.
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Title: Toward a Virulent Community Literacy : Constellating the Science, Technology, and Medicine of Queer Sexual Health
Creator: Flores, Wilfredo Antonio
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Toward a Virulent Community Literacy: Constellating the Science, Technology, and Medicine of Queer Sexual Health is a qualitative study (informed by Indigenous and decolonial methodologies) of how queer and trans people of color generate and share knowledge about their sexual health on Twitter with regards to HIV/AIDS. With a Twitter archive of 15,000 discrete tweets built with the keywords “Truvada,” PrEP,” and “HIV,” three datasets were derived comprising general utterances from queer users...
Show moreToward a Virulent Community Literacy: Constellating the Science, Technology, and Medicine of Queer Sexual Health is a qualitative study (informed by Indigenous and decolonial methodologies) of how queer and trans people of color generate and share knowledge about their sexual health on Twitter with regards to HIV/AIDS. With a Twitter archive of 15,000 discrete tweets built with the keywords “Truvada,” PrEP,” and “HIV,” three datasets were derived comprising general utterances from queer users of color, public health officials using social media for outreach, and organizations sharing research findings. Focusing on the data subset comprising 300 discrete users of color and relevant media (i.e., news articles, public health advertisements, other emergent artifacts from the data), this dissertation recounts three case studies focusing on: the rollout of HIV prevention advertisements within queer-centered media; the patent breaking of Truvada, a once-daily medication for preventing HIV; and the use of social media to take to task bad actors and misinformed healthcare providers. The data are used as part of an argument that the manner by which medicine and public health interface with queer and trans people of color hinges on ongoing colonization via the medical and outreach practices derived from colonial practices. Moreover, using a theoretical argument derived from Black and Native technology studies (as well as Black Feminist Thought, Anishinaabe cosmology, settler colonial studies, and digital rhetorical theory), the data was reviewed through a protocol for understanding identity construction amid technology use. The results revealed three rhetorical strategies: 1) continuing community-born public health practices created during the HIV/AIDS crisis of the 1980s and 90s by deploying descriptive hashtags to challenge stigma; 2) creating emergent whisper networks for sharing information about dealing with healthcare providers, navigating insurance networks, and communicating the symptoms of taking the medication; and 3) recognizing and countering the complex systems of late capitalist biomedicalization that prioritize profit over life. To contribute to ongoing commitments within writing and rhetoric studies to create equitable healthcare experiences, an HIV/AIDS health literacy framework follows the data results, which allows for outreach in non-clinical settings through relational design, or a participatory communication design process that incorporates community voices via an attunement to social media such as Twitter. This dissertation contributes to ongoing incursions within technical and professional communication, as well as the rhetoric of health and medicine, to upcycle disciplinary savvy into building better public health and clinical experiences for queer and trans people of color.
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Title: ECOPHYSIOLOGY OF (PERI)ORAL BACTERIA AND IMPACT OF OTIC COLONIZATION
Creator: Jacob, Kristin Marie
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The middle ear is typically assumed to be sterile in health due to its secluded location, closed off from external forces by the tympanic membrane (ear drum) and from the naso/oropharynx by a collapsed Eustachian tube. However, the periodic opening of the Eustachian tube to the naso/oropharyngeal space, which releases pressure across the eardrum and drains otic fluids, could introduce bacteria. Previous studies have tested for the presence of bacteria in the uninfected otic cavity using...
Show moreThe middle ear is typically assumed to be sterile in health due to its secluded location, closed off from external forces by the tympanic membrane (ear drum) and from the naso/oropharynx by a collapsed Eustachian tube. However, the periodic opening of the Eustachian tube to the naso/oropharyngeal space, which releases pressure across the eardrum and drains otic fluids, could introduce bacteria. Previous studies have tested for the presence of bacteria in the uninfected otic cavity using samples collected via invasive surgeries (through or around the eardrum). Findings from these studies are controversial due to contradictory results between studies, lack of critical experimental controls, and sampling of participants with underlying ailments (i.e., cochlear implant surgery) that could impact the microbiology of the otic mucosa. The studies reported herein bypass these limitations by using samples of otic secretions collectively non-invasively (through the mouth) in a cohort of healthy young adults. This dissertation describes cultivation-dependent methods to investigate the microbiology of the middle ear in health. The study used an IRB-approved protocol (#17-502) to collect otic secretions in order to 1) sequence their microbiome (contribution by Dr. Joo-Young Lee) and 2) recover in pure culture otic bacteria for further characterization (my contribution). As controls, we also collected buccal (top palate and inside of cheeks) and oropharyngeal swabs from each participant. Of the collected secretions, samples from 19 individuals were used for culture independent studies, while samples from the remaining 3 participants were subjected to culture dependent studies. 16S rRNA-V4 sequencing detected a diverse and distinct microbiome in otic secretions comprised primarily of strictly anaerobic bacteria belonging to the phyla Bacteroidetes, Firmicutes and Fusobacteria, and to a lesser extent facultative anaerobes (Streptococcus). I recovered from the otic, oropharyngeal, and buccal secretions 39 isolates of predominantly facultative anaerobes belonging to Firmicutes (Streptococcus and Staphylococcus), Actinobacteria (Micrococcus and Corynebacterium), and Proteobacteria (Neisseria) phyla, and used partial 16S rRNA amplicon sequences to demonstrate the distinct phylogenetic placement of otic streptococci compared to the oral ancestors (Chapter 2). This finding is consistent with the ecological diversification of oral streptococci once in the middle ear microenvironment. The recovery of streptococci and transient migrants (Staphylococcus, Neisseria, Micrococcus and Corynebacterium) from otic secretions prompted us to study the adaptive responses that give the streptococcal migrants a competitive advantage during the colonization of the middle ear (Chapter 3). For these studies, I sequenced and partially assembled the genomes of the otic isolates and used the full length 16S rRNA sequences for taxonomic demarcation at the species levels. Phylogenetic analyses demonstrated the oral ancestry of the otic streptococci, which retained from the otic adaptive traits critical for growth and reproduction in the middle ear mucosa (biofilm formation, mucolytic and proteolytic activity, robust growth under redox fluctuations, and fermentative production of lactate, a key metabolic intermediate in the otic trophic webs). These adaptive traits give oral streptococci a colonization advantage over competing (peri)oral migrants such as Staphylococcus. Furthermore, the otic streptococci inhibited the growth of otopathogens, including Staphylococcus aureus. These antagonistic interactions give streptococci a competitive advantage during the colonization of the middle ear and suggest a role for these commensals in promoting mucosal health. The ability of staphylococcal migrants to breach the middle ear mucosal barrier and cause infections prompted us to study the environmental factors that facilitate the spreading of staphylococci from the nasal to the middle ear mucosa. Allergies, respiratory maladies (cold, flu), or (peri)oral bacterial infections (sinus, adenoids, tonsils, etc.) lead to inflammation of the Eustachian tube and changes in the rheological properties of the otic mucus that increase the risk of infections. Thus, we examined the spreading of staphylococci on mucus-like viscous surfaces (semisolid agar plates). In Chapter 4, I show that mucins, the mucosal glycoproteins that control the viscosity and wettability of the mucus layer, induce the rapid spreading and dendritic expansion of clinical isolates closely related to S. aureus and Staphylococcus epidermidis but not of Staphylococcus hominis. Mucin glycosylation controlled the hydration of the mucoid surface and the ability of the cells to spread rapidly, in a process that was dependent on the secretion of surfactant-active, phenol-soluble modulins via the agr-quorum sensing two-component system. These results provide a plausible explanation for the rapid spreading of staphylococcal otopathogens from the nasopharynx to the middle ear through a swollen, and mucin-rich Eustachian tube. The work described in this dissertation provides much needed understanding of the adaptive responses that allow (peri)oral bacteria to colonize the middle ear. The studies add to the accumulating evidence that the middle ear mucosa is not sterile but rather harbors a commensal microbiota in health. These commensal community shares many metabolic similarities with ancestors in oral biofilms and retain adaptive traits critical for growth in the otic mucosa and inhibition of otopathogens. Additionally, this work identifies environmental factors that could contribute to staphylococcal virulence, broadening the understanding of newly identified motility phenotypes in the genus that could provide novel pharmaceutical targets.
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Title: Coalescence and Animal Use : Examining Community Building at the Multi-Ethnic Morton Village Site
Creator: Painter, Autumn Marie
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Across human history, groups of people have come together, found commonalities, and negotiated their differences in order to form new communities; a process known as coalescence. Until recently, archaeologists have primarily studied this social phenomenon by looking at the large-scale changes that occur, including settlement aggregation and demography. New research has begun to focus on smaller scales of analysis, including aspects of daily life and the role of common behaviors in bringing...
Show moreAcross human history, groups of people have come together, found commonalities, and negotiated their differences in order to form new communities; a process known as coalescence. Until recently, archaeologists have primarily studied this social phenomenon by looking at the large-scale changes that occur, including settlement aggregation and demography. New research has begun to focus on smaller scales of analysis, including aspects of daily life and the role of common behaviors in bringing people together. One such aspect of daily life is food. While previous research has recognized that changes in subsistence systems, such as a need to intensify the production of food to feed larger numbers of people, are commonly part of the coalescence process, little has been done to understand how these changes would affect a community or how a socially charged medium, such as food, may have contributed to ongoing coalescence. In this dissertation, I examine how animal use intersects with the broader process of coalescence through a multidimensional analysis of faunal remains from Morton Village, a site of on-going coalescence in the central Illinois River valley. Specifically, three aspects of animal use during the coalescence process were examined: 1) studying the overall diet as it intersects with the negotiation of everyday life, 2) animal access strategies including foodsharing practices, and 3) the use of animals and animal symbolism in ritual activities as a part of the long-term process of coalescence. These analyses found that the occupants of Morton Village used a diverse range of animal species, avian symbolism, and foodsharing/distribution practices within a variety of social interactions and practices. From this data, I argue that the use of animals played an important role in the coalescence process at Morton Village by assisting in building social relationships that were critical to community formation and maintenance during the coalescence process. This study demonstrates that the study of animal use is a fruitful avenue of research that can reveal several mechanisms for how social relationships are formed and community building processes occurred during coalescence.
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Title: Assessing Safety Performance of Roadway Characteristics in Rural and Urban Contexts
Creator: Chakraborty, Meghna
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Evaluating the safety performance of roadway segments and intersections typically involves associating traffic crashes, injuries, and fatalities to various roadway and traffic characteristics, which typically vary broadly between rural and urban contexts. In rural areas, roadway geometric characteristics often play a critical role in the safety performance of a given roadway, while myriad other factors, including driveways and intersections, tend to have a greater influence on urban roadway...
Show moreEvaluating the safety performance of roadway segments and intersections typically involves associating traffic crashes, injuries, and fatalities to various roadway and traffic characteristics, which typically vary broadly between rural and urban contexts. In rural areas, roadway geometric characteristics often play a critical role in the safety performance of a given roadway, while myriad other factors, including driveways and intersections, tend to have a greater influence on urban roadway safety. However, certain geometric aspects, such as the characteristics of the horizontal curvature and the impact of driveway land-use type have not been well-explored in prior roadway safety research. There has also been limited research on the safety performance for roadways of lower functional classifications, such as minor arterial and collector roadways, which comprise a substantial portion of the nationwide roadway network but are often designed to lower standards and possess driver and trip characteristics that typically differ from those of principal arterials. Therefore, assumptions made on the general effect of the predictor variables from typical safety performance functions may not apply to lower roadway classes. This research sought to explore those gaps in the roadway safety research domain. To accomplish this objective, roadway characteristics were collected along with traffic volume and crash data for greater than 13,000 miles of two-lane roadways in rural, urban, and suburban areas from across the state of Michigan for the period of 2011 through 2018. A series of safety performance functions were developed using a mixed-effects negative binomial modeling structure, which included fixed-effects and random-effects to account for the unobserved heterogeneity associated with varying design standards and site characteristics. The results indicated that driveway density significantly influences crash occurrence across all land-use categories for paved highways, although no impact was observed on unpaved roads. Commercial driveways possessed a stronger effect on crash occurrence than residential driveways or industrial driveways. In urban areas, posted speed limit had a significant positive association with crash frequency, and this effect increased when the speed limit exceeded 40 mph. The effect of speed limit was stronger on urban minor arterial segments (compared to collectors) and for fatal and injury crashes (compared to property damage only). This research also assessed the safety impacts associated with horizontal curve characteristics on rural highway segments, including curve type, curve direction, curve-approaching, curve-following, and inner-curve tangent distances, and curve design speed on rural two-lane undivided highways. Similar to prior research, curves with design speeds lower than the posted speed limit showed elevated crash occurrence. Most notably, compound and reverse curves were associated with greater crash occurrence compared to simple curves, with the greatest impact by the reverse curves. The increased approaching tangent distance for the simple curve or the first of a series of compound or reverse curves increased crash likelihood, perhaps due to the decreased driver expectancy for curvature with increasing tangent distance. However, increased inner-curve tangent distance was found to be associated with decreased crash occurrence. Lastly, the left-turning curves were found to be associated with greater crash occurrence than that on the right-turning curves.
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Title: COBALT REDOX MEDIATORS FOR DYE-SENSITIZED SOLAR CELLS
Creator: Raithel, Austin L.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Dye-sensitized solar cells have become an affordable alternative to conventional photovoltaics.Their efficiencies have become competitive by continued optimization of the semiconductor, dye, redox shuttle, and counter electrode. This thesis will evaluate low-spin Co(II) redox shuttles’ ability to minimize photovoltage losses due to dye regeneration and recombination to semiconductor electrons. Their synthesis and properties will be described along with a comparison to typical high-spin Co(II)...
Show moreDye-sensitized solar cells have become an affordable alternative to conventional photovoltaics.Their efficiencies have become competitive by continued optimization of the semiconductor, dye, redox shuttle, and counter electrode. This thesis will evaluate low-spin Co(II) redox shuttles’ ability to minimize photovoltage losses due to dye regeneration and recombination to semiconductor electrons. Their synthesis and properties will be described along with a comparison to typical high-spin Co(II) redox shuttles. The kinetic properties will be evaluated in terms of Marcus Theory with a particular focus being made on reorganization energy and free energy of electron transfer events. Chapter 1 will describe the motivation for dye-sensitized solar cells along with a description of their development and operation. Chapter 2 and 3 will describe the two extremes of redox potential of the redox shuttle. Chapter 4 demonstrates a system with a tunable potential inbetween. Chapter 5 will report other redox shuttle candidates and future directions to surpass 15% power conversion efficiency with low-spin Co(II) redox shuttles.
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Title: CONTRIBUTIONS TO EPIDEMIOLOGICAL RESEARCH ON THE SELLING OF INTERNATIONALLY REGULATED DRUGS
Creator: Yuan, Sha
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The existing research on drug selling among teenagers is limited. A few research teams have studied aspects of adolescent drug dealing. The scope of research includes economic factors relaed to youths involved in drug gangs (Levitt & Venkatesh, 2000) as well as psychosocial factors that might prompt teenagers to sell drugs (Fagan J, 1990; Little & Steinberg, 2006). Few have thought about adolescent drug selling from an epidemiological perspective, with a conceptualization based on agent-host...
Show moreThe existing research on drug selling among teenagers is limited. A few research teams have studied aspects of adolescent drug dealing. The scope of research includes economic factors relaed to youths involved in drug gangs (Levitt & Venkatesh, 2000) as well as psychosocial factors that might prompt teenagers to sell drugs (Fagan J, 1990; Little & Steinberg, 2006). Few have thought about adolescent drug selling from an epidemiological perspective, with a conceptualization based on agent-host-environment triad models, and with attention to potential public health control methods required for effective interventions.An early contributor, Isidore Chein and his research team (1964) launched important psychosocial research on youthful drug selling. According to that research, adolescents involved in heroin use often conducted drug dealing. However, the samples were limited to male adolescents in New York City, and the data collection period was from 1949 to 1955. This doctoral dissertation research project builds upon progress made by Chein and his colleagues. It summarizes a set of studies of youthful drug selling that merit attention. The project then aims to contribute new epidemiological findings on adolescents selling internationally regulated drugs (IRD) such as cannabis and cocaine. From an epidemiologist’s point of view, a drug seller can be considered a vector in the person-to-person spread of drug involvement. For this reason, a comprehensive view of the epidemiology of drug involvement should not neglect drug selling. For this dissertation research project, I conducted four investigations with focus on the drug onset and drug selling experiences of 12-to-17-year-old adolescents in the United States community populations. The first investigation aims to estimate the age-specific prevalence of recent drug selling behaviors for the age period of 12 to 17 years, with attention to the following subgroups that Salas-Wright and colleagues (2017) recently identified as having a higher prevalence of drug selling in the non-institutionalized U.S. population: (a) males and (b) older adolescents. The second study aims to produce estimates concerning birth cohort variations in drug selling prevalence. The third study divides youths into three groups: “never used any IRD” group, “cannabis only at first IRD use” group, and “used a non-cannabis IRD with or without concurrent cannabis use at first IRD use” group. The investigation then turns to an estimation of the likelihood of being a seller of drugs in the past 12 months for each of these three groups, with attention to the duration of IRD use, The fourth study aims to compare non-users and users whose first drug is cannabis with respect to their odds of selling drugs in the second year after first drug use. The population under study was sampled for annual United States National Surveys of Drug Use and Health (NSDUH). The NSDUH sampled, recruited, and assessed non-institutionalized US civilian residents aged 12 and above each year. After Institutional Review Board-approved consent procedures, all participants were assessed using confidential audio computer-assisted self-interviews. There are cannabis and youth experience modules and modules on other drugs and health topics in the self-interview sessions. The findings of all the four studies in this dissertation are from statistical analyses of NSDUH public-use data files based on the survey questions in the aforementioned modules. The main findings and implications, summarized across the four research projects, are as follows: • Study 1: The estimated prevalence of drug selling increases with age during the adolescent years under study. The estimated prevalence for boys is larger than the corresponding estimates for girls. • Study 2: Estimated age-specific prevalence patterns do not vary appreciably across recent birth cohorts. The general pattern is one of cohort-specific increases in the odds of drug-selling from age 12 to age 17; estimates of 17-year olds are larger. • Study 3: Starting to use cannabis and no other IRD is associated with greater odds of drug selling in the subsequent adolescent years. The study estimates suggest that as time passes since first IRD use, the odds of drug selling increase (up to a point). If the first IRD use is not cannabis, then the estimated odds of drug selling may be larger than if cannabis is the only IRD that has been used. • Study 4: Adolescents who start to use cannabis but none of the other internationally regulated drugs are observed to be more likely to sell drugs in the second year after the first use, compared to adolescents who have never used any drug. Subject to limitations described in this dissertation report, these findings merit further investigation and attention in public health initiatives to prevent the person-to-person spread of drug use during adolescence. The dissertation research report also describes some future research directions that can build upon this project’s findings, which include future longitudinal and prospective investigations.
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Title: Quantum coherent transport phenomena in epitaxial halide perovskite thin films
Creator: Zhang, Liangji
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The subject of this dissertation is the experimental study of quantum coherent transport phenomena in epitaxial single-crystal halide perovskite thin films. The experiments consist of low-temperature (down to 10 mK) magnetotransport measurements at high magnetic field (up to 14 T).The recent advent of epitaxial thin film growth of inorganic halide perovskites has made it possible to investigate the quantum behavior of charge carriers in these materials in low-dimensional form. We present...
Show moreThe subject of this dissertation is the experimental study of quantum coherent transport phenomena in epitaxial single-crystal halide perovskite thin films. The experiments consist of low-temperature (down to 10 mK) magnetotransport measurements at high magnetic field (up to 14 T).The recent advent of epitaxial thin film growth of inorganic halide perovskites has made it possible to investigate the quantum behavior of charge carriers in these materials in low-dimensional form. We present results on epitaxial single-domain cesium tin iodide (CsSnI3) thin films that clearly demonstrate quantum transport in this material for the first time. The observed low-field magnetoresistance shows signatures of weak anti-localization (WAL) that reveals coherent quantum interference effects and spin-orbit coupling. A micron-scale (≈5 um) low-temperature phase coherence length for charge carriers in the system is extracted from these WAL measurements.Additionally, we present low-temperature quantum magnetotransport measurements on thin film devices made of epitaxial single-crystal CsSnBr3, which exhibit two-dimensional Mott variable range hopping (VRH) and a large negative magnetoresistance. These findings are described by the Nguyen-Spivak-Shkovskii (NSS) model for quantum interference between different directed hopping paths, and we extract the temperature-dependent hopping length of charge carriers, their localization length, and a lower bound for their phase coherence length of ~100 nm at low temperatures. These results from CsSnI3 and CsSnBr3 devices demonstrate that epitaxial halide perovskite devices are emerging as a material class for low-dimensional quantum coherent transport devices.In addition to the works that are described above, I have also been involved in several additional projects, such as experiments on low-dimensional electron systems and superconducting qubit experiments, which will not be described in this dissertation.
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Title: PLANNING FOR AUTONOMY AND ELECTRIFICATION IN FUTURE TRANSPORTATION SYSTEMS
Creator: Singh, Harprinderjot
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Autonomous vehicles (AVs) and electric vehicles (EVs) will improve safety, mobility, roadway capacity and provide efficient driving, efficient use of travel time, and reduced emissions. However, these technologies affect vehicle miles traveled (VMT), travel time, ownership cost, and electric grid network. Shared mobility systems can ameliorate the high price of these technologies. However, the shared mobility system poses additional problems such as users’ waiting time, inconvenience, and...
Show moreAutonomous vehicles (AVs) and electric vehicles (EVs) will improve safety, mobility, roadway capacity and provide efficient driving, efficient use of travel time, and reduced emissions. However, these technologies affect vehicle miles traveled (VMT), travel time, ownership cost, and electric grid network. Shared mobility systems can ameliorate the high price of these technologies. However, the shared mobility system poses additional problems such as users’ waiting time, inconvenience, and increased VMT. Further, the impact of these emerging technologies varies on different groups of users (different values of travel time (VOTT). Another hurdle to the adoption of EVs is the limited range and scarcity of charging infrastructure. A well-established network of charging infrastructure, especially the direct current fast chargers (DCFC), can alleviate this challenge. However, the widespread adoption of EVs and the growing network of DCFC stations will increase the electric energy demand affecting the electric grid stability, demand-supply imbalance, overloading, and degradation of the electric grid components. Distributed energy resources (DER) such as solar panels and energy storage systems (ESS) can support the EV demand and reduce the load on the electric grid. This study develops modeling frameworks for the optimal adoption of AVs and EVs, considering their effect on transportation systems, the environment, and the electric grid network. Further, it suggests different scenarios that would promote the adoption of these technologies and provide a sustainable and resilient system.This study proposes a multi-objective mathematical model to estimate the optimal fleet configuration in a system of private manual-driven vehicles (PMVs), private AVs (PAVs), and shared AVs (SAVs) while minimizing the purchase and operating costs, time (travel and waiting time), and emission production. SAVs can be the optimal solution with the efficient use of travel time or the purchase price below a certain relative threshold. PAVs can be the optimal solution only if the onboard amenities are improved, lifetime mileage is increased, AV technology is installed in luxurious cars, and adopted by people with high VOTT. The framework is extended to consider different combinations of EVs, AVs, and conventional human-driven vehicles in a private and shared mobility system. The metaheuristics based on genetic and simulated annealing algorithms are developed to solve the large-scale NP-hard nonlinear optimization problem. The model is implemented for the network of Ann Arbor, Michigan. The results suggest that EVs are optimal for the system due to low operating costs and zero tailpipe emissions. Shared autonomous electric vehicles (SAEVs) are the best option for users with low VOTT. Private autonomous electric vehicles (PAEVs) would favor the system if the travel time savings are at least 20% or the price of AV technology is less than one-third of the vehicle price. The study then investigates the optimum investment technology to support the rising energy demand at the DCFC stations and reduce the load on the electric grid network. The different investments include purchasing and installing various ESS (new batteries (NB), second-life batteries (SLB), flywheels), solar panels, electric grid upgrades, and the cost of buying/selling electricity from/to the electric grid. The model is implemented for the DCFC stations supporting the future needs of EV charging demand for urban trips in the major cities of Michigan in 2030. The combination of SLBs and solar panels provides maximum benefits. The total annual and electricity savings are $25,000-$165,000 and $40,000-$300,000 per city.
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Title: Teaching Presence in a Fully Online Asynchronous Undergraduate Mathematics Course and its Impact on Social and Cognitive Presence
Creator: Elmore, Robert Andrew
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The number of fully online asynchronous undergraduate mathematics courses is growing rapidly, making it imperative that the instructional choices that are chosen by instructors and their effects on students’ opportunities to learn in the online learning environment be further explored. Therefore, this research aims to understand instructors' choices when teaching an online undergraduate mathematics course, and how these decisions impact students' communication opportunities. This research...
Show moreThe number of fully online asynchronous undergraduate mathematics courses is growing rapidly, making it imperative that the instructional choices that are chosen by instructors and their effects on students’ opportunities to learn in the online learning environment be further explored. Therefore, this research aims to understand instructors' choices when teaching an online undergraduate mathematics course, and how these decisions impact students' communication opportunities. This research organized the instructors' decisions and their impacts on students using the community of inquiry framework. The three categories of the community of inquiry framework, teaching presence, social presence, and cognitive presence, were analyzed through course artifacts, an instructor interview, student interviews, student surveys, and course usage data. The primary analysis was performed using the interviews with the other data sources providing further detail and explanation. Four claims were generated while analyzing these data sources. Claim one posits that students tend to have singular preferences of the course’s direct instructional elements. Claim 2 proffers that students who chose to work with others report having positive experiences, and those who decided not to work with others report not needing help, with one exception. Claim 3 states that meaningful contact points can be created between the instructor and student using surveys and personalized mass emails; however, most describe learning mathematics in Math 101 as not making them feel a part of a learning community. And claim 4 posits that elements of the teaching presence were more likely to foster participation if they were associated with a grade. The results of this study have implications for both the research and practice communities. The current study’s results imply that—even though sizes of online mathematics classes may still grow—there are ways instructors can facilitate high levels of social processes using mass email, surveys, cooperative learning groups, and other online tools. These specific tools should be studied and evaluated for their effects on social presence and cognitive presence on the mass scale. The present study suggests four specific things that instructors should familiarize themselves with that are available today, (a) prescribe opportunities for students to communicate with each other such as having assignments that are completed in cooperative learning groups, (b) communicate with your students through personalized means (e.g., emails, surveys, and Zoom sessions), (c) use feedback from surveys to inform your future teaching practice, and (d) ensure that students observe your communication and direct instruction by tying them to elements associated with grades. Keywords: teaching presence, social presence, cognitive presence, online mathematics learning.
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Title: DO INTERFACES MATTER? A REEXAMINATION OF XBRL USING FINANCIAL STATEMENT ACQUISITION AND MARKET ACTIVITY
Creator: Anderson, James J.
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Starting in 2009 the eXtensible Business Reporting Language (XBRL) standard was mandated for financial statements by the SEC. The XBRL standard was intended to encourage less-sophisticated trader disclosure processing; however, previous literature has conjectured that the standard primarily aided more-sophisticated traders’ disclosure processing. I reexamine the effect of XBRL on more- and less-sophisticated trader disclosure processing by testing whether XBRL influenced their information...
Show moreStarting in 2009 the eXtensible Business Reporting Language (XBRL) standard was mandated for financial statements by the SEC. The XBRL standard was intended to encourage less-sophisticated trader disclosure processing; however, previous literature has conjectured that the standard primarily aided more-sophisticated traders’ disclosure processing. I reexamine the effect of XBRL on more- and less-sophisticated trader disclosure processing by testing whether XBRL influenced their information acquisition and testing whether the proportional relationship between information acquisition and market activity is different for more- and less-sophisticated traders. I find the staggered implementation of XBRL is associated with a 49% (26%) increase in less (more) sophisticated trader information acquisition. Next, I find the proportional relationship between information acquisition and market activity is greater for less-sophisticated traders when compared to more-sophisticated traders. Specifically, I find information acquisition for less-sophisticated traders has a greater proportional relationship with abnormal price movement, abnormal trading volume, and abnormal bid-ask spreads. Together these findings suggest that XBRL did not provide a disproportionate information advantage to more-sophisticated traders, but rather benefited less-sophisticated traders by decreasing their information acquisition costs.
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Title: QUALITY OF LIFE IN CONTEMPORARY NEIGHBORHOOD DESIGN INITIATIVES : AN EMPIRICAL STUDY TO ASSESS QUALITY OF LIFE THROUGH SPATIAL DIMENSION IN NEW URBANIST AND LEED-ND CERTIFIED NEIGHBORHOODS
Creator: Shaaban, Amal Hamdy
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The overarching purpose of this study is to analyze qualitatively and quantitatively the spatial characteristics of two types of neighborhoods, namely New Urbanist (NU) neighborhoods and Leadership in Energy and Environmental Design (LEED) certified neighborhoods. LEED certified neighborhoods are commonly referred to as LEED for Neighborhood Development (LEED-ND). In this research study, the spatial quality of these two types of neighborhoods was examined through assessing the quality of five...
Show moreThe overarching purpose of this study is to analyze qualitatively and quantitatively the spatial characteristics of two types of neighborhoods, namely New Urbanist (NU) neighborhoods and Leadership in Energy and Environmental Design (LEED) certified neighborhoods. LEED certified neighborhoods are commonly referred to as LEED for Neighborhood Development (LEED-ND). In this research study, the spatial quality of these two types of neighborhoods was examined through assessing the quality of five dimensions of a neighborhood’s urban form, which are: safety, comfort, connectivity, place making and aesthetic quality. Three types of neighborhoods were selected and examined using two main analytical tools: neighborhood scorecard, and residents’ survey. Two neighborhoods were selected to examine NU neighborhoods in Michigan in the United States, which are Cherry Hill Village (CHV) a greenfield residential development, and Mason Run (MR) a brownfield residential development. The third neighborhood was selected to examine LEED-ND certified neighborhoods, which is Saint Luke (SL) neighborhood in Ohio in the United States. The neighborhood scorecard included a total of 150 design guidelines that yield better Quality of Life (QoL) in residential developments through urban form. The residents’ survey included a set of questions that examined the residents’ perceptions regarding the five physical characteristics necessary to yield better QoL. A total of 154 surveys were collected for data analysis that used one-way ANOVA tests, Tukey’s post-hoc tests, and multiple regression models. The major findings from the neighborhood scorecard are that CHV neighborhood provides was safer than the brownfield NU residential development and the LEED-ND certified neighborhood. Both NU neighborhoods provided more comfortable environments of their residents to live in more than the LEED-ND certified neighborhood. The greenfield NU neighborhood earned more points than the other two neighborhoods in terms of the internal and external connectivity degree of the neighborhood. In terms of fulfilling the recommended design guidelines for place making and aesthetic quality, again the Greenfield NU neighborhood had earned higher points than the other two neighborhoods. The major findings from the survey are: Survey participants living in both NU neighborhoods were more satisfied with their QoL more than the participants living in the LEED-ND certified neighborhood. Also, respondents living in NU neighborhoods perceived their neighborhoods as safer places to live in more than participants living in the LEED-ND certified neighborhood. On the other hand, respondents living in the NU brownfield development perceived their neighborhood as the least comfortable neighborhood. In terms of the internal connectivity of the neighborhood, respondents living in NU greenfield development identified the internal connectivity of their neighborhood as the highest compared to the other two neighborhoods. On the other hand, the perception of the internal connectivity perception was the lowest amongst respondents living in the LEED-ND certified neighborhood. Respondents living in the LEED-ND certified neighborhood had the highest mean in terms of their perceptions of sense of belonging. On the other hand, respondents living in the NU brownfield development had the lowest mean in terms of their perception of sense of belonging. The perception of the aesthetic quality of the neighborhood was the highest among respondents living in the NU greenfield development. On the other hand, the perception of aesthetic quality of the neighborhood was the least among respondents living in NU brownfield development.This research study concludes by suggesting recommendations to improve the principles and design guidelines of NU and LEED-ND certified neighborhoods to achieve better QoL. The recommendations suggest emphasizing certain spatial characteristics that yield better QoL in Greenfield, and brownfield residential developments.
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Title: IMPACTS OF DISTANT DRIVERS ON LANDSCAPES AND BIODIVERSITY
Creator: Hovis, Ciara Layne
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Global biodiversity is increasingly impacted by distant drivers. With societies more connected than ever before, natural resource consumption has expanded beyond administrative and political boundaries. International food trade in particular has profound impacts on land-use and socioeconomic and environmental outcomes. At the same time, global biodiversity is threatened at an unprecedented scale, with many of the causes obfuscated by complexities of distant, interacting socioecological...
Show moreGlobal biodiversity is increasingly impacted by distant drivers. With societies more connected than ever before, natural resource consumption has expanded beyond administrative and political boundaries. International food trade in particular has profound impacts on land-use and socioeconomic and environmental outcomes. At the same time, global biodiversity is threatened at an unprecedented scale, with many of the causes obfuscated by complexities of distant, interacting socioecological systems. Understanding the ultimate drivers of biodiversity change and translating them to local biodiversity outcomes is integral to addressing conservation challenges in the age of globalization. This dissertation analyzes the impacts of international trade on biodiversity in an agroecosystem undergoing land-use change driven by global markets. Chapter 1 provides background on the study region, Heilongjiang Province, and describes disruption of soybean production in the area due to changes in global trade. Chapter 2 is a systematic review of studies on distant drivers of biodiversity change. Across all taxa, harmful impacts on biodiversity were the most frequent outcome reported, with distant impacts of trade and tourism most frequently studied. In Chapter 3, satellite imagery was classified into landcover classes to create high-fidelity maps of the agriculture-dominated study landscape. By utilizing phenological, synthetic aperture radar, and vegetation/soil index data, accuracies of 91%- 80% were achieved. In Chapter 4 these landcover maps were used to calculate landscape metrics. These metrics were then used to analyze relationships between landscape structure (i.e., composition and configuration) and bird communities. Functional biodiversity indices derived from life history and morphological traits were examined in addition to taxonomic measures. Though no discernable differences between taxonomic and functional community metrics were observed, several significant relationships between landscape structure and biodiversity metrics were found. Crop diversity, natural landcover, and edge metrics, were positively correlated with bird richness. Aggregation of patches, corn area, and soybean area were negatively correlated. We also compared landscape structure and biodiversity between two regions impacted by global soybean trade. Despite the more impacted region having lower crop diversity and natural area, there was no difference in biodiversity between the two regions. The more impacted region also had more rice area, demonstrating that negative biodiversity impacts may be mitigated by rice cultivation. Chapter 5 built on the previous chapter by modeling bird occupancy to assess species-specific relationships with landscape structure. Results indicated that increased crop diversity significantly increased occupancy of birds at both the taxonomic and functional level, particularly for birds belonging to less common functional groups. Percentage of natural area was not as important as expected, while metrics related to landscape configuration had very few significant impacts on occupancy. Increases in rice area were not as detrimental to bird occupancy as increases in corn and soybean. In fact, soybean area exhibited more significant negative relationships with bird occurrence than corn, suggesting that decreases in soybean area due to global trade may have benefitted bird biodiversity in the case of a monocultural landscape. However, due to the prevalence of small-scale farming practices, the more likely outcome would be a decrease in crop diversity due to soybean fields being converted to more profitable crops (e.g., corn, rice). By linking global trade, changes in landcover/use, landscape structure, and local bird communities in the same context, the results of this dissertation highlight the need for integrated biodiversity studies that place ecosystems in the broader context of globalization.
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Title: A CASE STUDY EXPLORING HOW K-12 STUDENTS LEARN TO USE SOCIAL MEDIA FOR CIVIC GOOD
Creator: Askari, Emilia Shirin
Date: 2022
Collection: Electronic Theses & Dissertations
Description: This case study explores what K-12 students learn from a 13-week class activity about attracting attention to civic issues on social media. This research responds to calls by scholars of civic education to expand notions of civic engagement and digital citizenship, which often have focused on urging students to protect their reputations in digital spaces. In contrast, the learning activity examined here encourages community-oriented digital citizenship, preparing students to inform and...
Show moreThis case study explores what K-12 students learn from a 13-week class activity about attracting attention to civic issues on social media. This research responds to calls by scholars of civic education to expand notions of civic engagement and digital citizenship, which often have focused on urging students to protect their reputations in digital spaces. In contrast, the learning activity examined here encourages community-oriented digital citizenship, preparing students to inform and possibly empower social change. This study is grounded in Cognitive Flexibility Theory, which focuses on learning in ill-structured domains such as public social media. Further, the study builds on the increasingly popular idea of the Fifth Estate, which posits that people acting in civic ways in public spaces can be a powerful check on government, playing a role similar to that of journalism institutions, sometimes referred to as the Fourth Estate. Data collected in this study included a pre-survey, a written reflection and post interviews with 4 students as well as artifacts such as social media posts. Students employed two main strategies to draw attention to civic issues on social media: audience-signaling and networking. Further, students learned to seek credible and diverse information using class accounts on TikTok, Instagram, and Twitter. Finally, students offered definitions of digital citizenship and shared thoughts about how schools should teach it via social media. This study fills a gap in the research literature about K-12 teaching with social media; few prior studies take advantage of social media’s affordance as a bridge between the classroom and communities outside the school. This study also illuminates learning as schools globally moved online in response to the pandemic.
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Title: Examining an Important Assumption in the Faultline Literature
Creator: Guo, Zhiya
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Group faultlines are defined as hypothetical dividing lines that split a team into subgroups based on the alignment of team members’ attributes. Prior faultline research has almost exclusively focused on the implications of between-subgroup relationships assuming that “team members form homophilous ties on either side of a faultline by associating with others in the team who have similar demographic attributes” (Ren et al., 2015, p. 390). However, this important assumption has not been tested...
Show moreGroup faultlines are defined as hypothetical dividing lines that split a team into subgroups based on the alignment of team members’ attributes. Prior faultline research has almost exclusively focused on the implications of between-subgroup relationships assuming that “team members form homophilous ties on either side of a faultline by associating with others in the team who have similar demographic attributes” (Ren et al., 2015, p. 390). However, this important assumption has not been tested. Drawing from social comparison theory and its “similarity hypothesis,” I argue that homogeneous, faultline-based subgroups may serve as a hotbed for social comparisons, and comparisons on social power can engender conflict under certain circumstances, triggering within-subgroup conflict. More specifically, consistent with the emerging research that recognizes different types of group faultlines, I outlined a) different dimensions that different faultline-based subgroups are more likely to compare and b) the downstream effects of these comparisons. Hypotheses were tested using multi-wave, round-robin data from multiple intact work teams of full-time employees. Results largely supported my predictions regarding knowledge-based subgroups but not so much for identity-based subgroups or resource-based subgroups. Implications and future directions are discussed.
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Title: PALETTEVIZ : A METHOD FOR VISUALIZATION OF HIGH-DIMENSIONAL PARETO-OPTIMAL FRONT AND ITS APPLICATIONS TO MULTI-CRITERIA DECISION MAKING AND ANALYSIS
Creator: Talukder, AKM Khaled Ahsan
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Visual representation of a many-objective Pareto-optimal front in four or more dimensional objective space requires a large number of data points. Moreover, choosing a single point from a large set even with certain preference information is problematic, as it imposes a large cognitive burden on the decision-makers. Therefore, many-objective optimization and decision-making practitioners have been interested in effective visualization methods to en- able them to filter down a large set to a...
Show moreVisual representation of a many-objective Pareto-optimal front in four or more dimensional objective space requires a large number of data points. Moreover, choosing a single point from a large set even with certain preference information is problematic, as it imposes a large cognitive burden on the decision-makers. Therefore, many-objective optimization and decision-making practitioners have been interested in effective visualization methods to en- able them to filter down a large set to a few critical points for further analysis. Most existing visualization methods are borrowed from other data analytics domains and they are too generic to be effective for many-criterion decision making. In this dissertation, we propose a visualization method, using star-coordinate and radial visualization plots, for effectively visualizing many-objective trade-off solutions. The proposed method respects some basic topological, geometric and functional decision-making properties of high-dimensional trade- off points mapped to a three-dimensional space. We call this method Palette Visualization (PaletteViz). We demonstrate the use of PaletteViz on a number of large-dimensional multi- objective optimization test problems and three real-world multi-objective problems, where one of them has 10 objective and 16 constraint functions. We also show the uses of NIMBUS and Pareto-Race concepts from canonical multi-criterion decision making and analysis literature and introduce them into PaletteViz to demonstrate the ease and advantage of the proposed method.
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Title: Dynamical Systems Analysis Using Topological Signal Processing
Creator: Myers, Audun
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Topological Signal Processing (TSP) is the study of time series data through the lens of Topological Data Analysis (TDA)—a process of analyzing data through its shape. This work focuses on developing novel TSP tools for the analysis of dynamical systems. A dynamical system is a term used to broadly refer to a system whose state changes in time. These systems are formally assumed to be a continuum of states whose values are real numbers. However, real-life measurements of these systems only...
Show moreTopological Signal Processing (TSP) is the study of time series data through the lens of Topological Data Analysis (TDA)—a process of analyzing data through its shape. This work focuses on developing novel TSP tools for the analysis of dynamical systems. A dynamical system is a term used to broadly refer to a system whose state changes in time. These systems are formally assumed to be a continuum of states whose values are real numbers. However, real-life measurements of these systems only provide finite information from which the underlying dynamics must be gleaned. This necessitates making conclusions on the continuous structure of a dynamical system using noisy finite samples or time series. The interest often lies in capturing qualitative changes in the system’s behavior known as a bifurcation through changes in the shape of the state space as one or more of the system parameters vary. Current literature on time series analysis aims to study this structure by searching for a lower-dimensional representation; however, the need for user-defined inputs, the sensitivity of these inputs to noise, and the expensive computational effort limit the usability of available knowledge especially for in-situ signal processing.This research aims to use and develop TSP tools to extract useful information about the underlying dynamical system's structure. The first research direction investigates the use of sublevel set persistence—a form of persistent homology from TDA—for signal processing with applications including parameter estimation of a damped oscillator and signal complexity measures to detect bifurcations. The second research direction applies TDA to complex networks to investigate how the topology of such complex networks corresponds to the state space structure. We show how TSP applied to complex networks can be used to detect changes in signal complexity including chaotic compared to periodic dynamics in a noise-contaminated signal. The last research direction focuses on the topological analysis of dynamical networks. A dynamical network is a graph whose vertices and edges have state values driven by a highly interconnected dynamical system. We show how zigzag persistence—a modification of persistent homology—can be used to understand the changing structure of such dynamical networks.
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Title: ASSESSING DISASTER MANAGEMENT EFFECTS ON RECOVERY OUTCOMES IN RURAL POST-DISASTER JAPAN
Creator: Ward, Kayleigh
Date: 2022
Collection: Electronic Theses & Dissertations
Description: As a country frequented by natural disasters, Japan has robust disaster management systems that can be employed quickly to mitigate human, environmental, and economic harm and losses. However, these systems tend to be most effective when handling small-scale localized disasters. In the face of the 2011 Great East Japan Earthquake which decimated the northeastern communities of the Tohoku region, Japan’s disaster management system collapsed, unable to handle such large scale and widespread...
Show moreAs a country frequented by natural disasters, Japan has robust disaster management systems that can be employed quickly to mitigate human, environmental, and economic harm and losses. However, these systems tend to be most effective when handling small-scale localized disasters. In the face of the 2011 Great East Japan Earthquake which decimated the northeastern communities of the Tohoku region, Japan’s disaster management system collapsed, unable to handle such large scale and widespread damage. In the ten years since the disaster many rural communities have contended with a variety of social and economic problems, often left unremedied despite on-going government intervention. In this context, this dissertation will explore the complex problems in Minamisanriku, Miyagi—a rural coastal community decimated by the 2011 Great East Japan Earthquake. By engaging and collaborating with organizations in this community, I assess the connections between disaster management and post-disaster recovery outcomes through various applications of social capital and power. I first investigate how historical legacies of national government policies influenced recovery outcomes in the Tohoku region and how have these processes influenced economic restructuring and social development in Minamisanriku during reconstruction. Next, I consider how governance structures within Miyagi prefecture influenced the social and economic development of Minamisanriku during reconstruction. Lastly, I look to how disaster management affects the ability of residents to handle locally-identified and in turn, how residents utilize their social capital to driver social and economic recovery. I assess several key ideas on the connections between forms and theories of social capital and how they affect long-term disaster recovery outcomes through the disaster management process. The dissertation is situated to improve our understanding of how social capital affects rural communities’ ability to respond to these troubles and to craft context specific solutions to them. It also offers a variety of policy recommendations about how to improve community-centered recovery within disaster management frameworks.
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