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Title: UNDERSTANDING THE GENETIC BASIS OF HUMAN DISEASES BY COMPUTATIONALLY MODELING THE LARGE-SCALE GENE REGULATORY NETWORKS
Creator: Wang, Hao
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Many severe diseases are known to be caused by the genetic disorder of the human genome, including breast cancer and Alzheimer's disease. Understanding the genetic basis of human diseases plays a vital role in personalized medicine and precision therapy. However, the pervasive spatial correlations between the disease-associated SNPs have hindered the ability of traditional GWAS studies to discover causal SNPs and obscured the underlying mechanisms of disease-associated SNPs. Recently, diverse...
Show moreMany severe diseases are known to be caused by the genetic disorder of the human genome, including breast cancer and Alzheimer's disease. Understanding the genetic basis of human diseases plays a vital role in personalized medicine and precision therapy. However, the pervasive spatial correlations between the disease-associated SNPs have hindered the ability of traditional GWAS studies to discover causal SNPs and obscured the underlying mechanisms of disease-associated SNPs. Recently, diverse biological datasets generated by large data consortia provide a unique opportunity to fill the gap between genotypes and phenotypes using biological networks, representing the complex interplay between genes, enhancers, and transcription factors (TF) in the 3D space. The comprehensive delineation of the regulatory landscape calls for highly scalable computational algorithms to reconstruct the 3D chromosome structures and mechanistically predict the enhancer-gene links. In this dissertation, I first developed two algorithms, FLAMINGO and tFLAMINGO, to reconstruct the high-resolution 3D chromosome structures. The algorithmic advancements of FLAMINGO and tFLAMINGO lead to the reconstruction of the 3D chromosome structures in an unprecedented resolution from the highly sparse chromatin contact maps. I further developed two integrative algorithms, ComMUTE and ProTECT, to mechanistically predict the long-range enhancer-gene links by modeling the TF profiles. Based on the extensive evaluations, these two algorithms demonstrate superior performance in predicting enhancer-gene links and decoding TF regulatory grammars over existing algorithms. The successful application of ComMUTE and ProTECT in 127 cell types not only provide a rich resource of gene regulatory networks but also shed light on the mechanistic understanding of QTLs, disease-associated genetic variants, and high-order chromatin interactions.
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Title: UNDERSTANDING THE PARASITIC VARIABILITY OF THE NORTHERN ROOT KNOT NEMATODE (MELOIDOGYNE HAPLA) THROUGH MULTIDISCIPLINARY APPROACHES OF SOIL BIOME AND ENVIRONMENT
Creator: Lartey, Isaac
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Managing Meloidogyne hapla remains challenging due to the ban of broad-spectrumnematicides, lack of resistant crops and its broad host range. It also has parasitic variability (PV) where populations (pop) are morphologically and genetically similar but vary in pathogenicity and reproductive potential. Although PV in M. hapla appears to have some relationship to soil types, what soil conditions favor its PV and/or its distribution are unknown. The goal of my research was to understand the soil...
Show moreManaging Meloidogyne hapla remains challenging due to the ban of broad-spectrumnematicides, lack of resistant crops and its broad host range. It also has parasitic variability (PV) where populations (pop) are morphologically and genetically similar but vary in pathogenicity and reproductive potential. Although PV in M. hapla appears to have some relationship to soil types, what soil conditions favor its PV and/or its distribution are unknown. The goal of my research was to understand the soil conditions where M. hapla PV exist by quantifying the biophysicochemical (BPC) conditions from the ecosystem down to microbiome level. I designed observational and experimental approaches and tested four objectives. First, was to evaluate the association between soil conditions and M. hapla distribution at the ecosystem level. My hypothesis was that the presence of M. hapla will be associated with degraded soil conditions. I selected 15 (6 muck and 9 mineral soil) agricultural fields with adjacent natural vegetation in southwest, northwest and eastern regions of the lower peninsula of Michigan as study sites. I collected a total of 75 (5 per field) georeferenced soil samples from agricultural fields and equal number from adjacent natural vegetation soils, quantified the soil food web (SFW) conditions using the Ferris SFW model, and screened for M. hapla presence or absence. The fields were described either as disturbed, degraded (worst-case) or maturing (best-case). Meloidogyne hapla was present in 3 mineral (2, 8 and 13) and 6 muck (4, 5, 6, 10, 14 15) agricultural fields with degraded and/or disturbed soil conditions and absent from maturing soils, partially supporting the hypothesis. Degraded soils had low nitrogen content in both soil groups. The second objective was to isolate and culture the 9 M. hapla populations to test a hypothesis that PV is related to specific SFW conditions. I found three categories of reproductive potential: the highest (Pop 13), medium (Pop 8), both from degraded mineral soils, and lowest from disturbed mineral (Pop 2) and disturbed (Pops 4, 6 and 10) and degraded (Pops 5, 14 and 15) muck soils. Thus, the hypothesis was not supported. The third objective, was to determine relationships between microbial community structure and M. hapla distribution. My working hypotheses were that there is a relationship among microbiome, soil health and M. hapla occurrence. Microbial community structure in the fields was determined from sub-samples of the same samples where the nematodes were isolated. I used 16S (bacteria) and ITS (fungi) rDNA analysis and characterized the microbial composition, core- and indicator-microbes co-existing with M. hapla pop in the field soils and soil conditions relative to the Ferris SFW model description. The results showed that bacterial and fungal community abundance and composition varied by soil group, SFW conditions and/or M. hapla occurrence. I found that a core of 39 bacterial and 44 fungal sub-operational taxonomic units (OTUs) were found variably, 25 bacterial OTUs associated with presence or absence of M. hapla, and 1,065 OTUs were associated SFW conditions. All three hypotheses were supported. The final objective was to determine the relationship between PV and the microbes associated with M. hapla pop. I compared bacteria present in M. hapla pop isolated from the field and greenhouse cultures. The hypothesis was that either presence and/or absence of specific bacteria are associated with M. hapla population. Population 8 shared more bacteria with the lowest reproductive potential pop than Population 13. Presence of several bacteria was unique to Population 8 as was the absence of other bacteria to Pop 13 in either field or greenhouse nematodes. Therefore, the hypothesis was supported. My research findings provide a foundation for: a) testing the relationship between M. hapla PV and the BPC conditions and b) designing soil health-based management strategies.
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Title: UNDERSTANDING THE ROLES OF INTERKINGDOM MICROBIAL INTERACTIONS, MICROBIAL TRAITS, AND HOST FACTORS IN THE ASSEMBLY OF PLANT MICROBIOMES
Creator: Liber, Julian Aaron
Date: 2021
Collection: Electronic Theses & Dissertations
Description: The community of organisms that associate with plants are vital to both the survival of the host plant but also the diseases which may kill it. The processes by which this community, called the microbiome, assemble and function can contribute to the traits of the host, including plants that humans rely on for food, resources, and ecosystems services. This thesis focuses on understanding the assembly of microbiomes at the scale of microbe-microbe interactions and traits of individual microbes,...
Show moreThe community of organisms that associate with plants are vital to both the survival of the host plant but also the diseases which may kill it. The processes by which this community, called the microbiome, assemble and function can contribute to the traits of the host, including plants that humans rely on for food, resources, and ecosystems services. This thesis focuses on understanding the assembly of microbiomes at the scale of microbe-microbe interactions and traits of individual microbes, as well as how characters of the host may change this process. I first address this by examining the in vitro and in planta interactions within small synthetic communities of root-inhabiting bacteria and fungi and with the plant host and viral disease of the host. While intermicrobial interactions in vitro were not predictive of in planta interactions, adding host disease or additional organisms to the system altered the assembly process. I then show the development and applications of the CONSTAX2 classifier, a taxonomic assignment tool for metabarcoding studies, which offers improved accuracy and ease of use for conducting metabarcoding studies exploring the diversity and structure of microbial communities. Last, I present a study testing which factors affected the composition of forest fungal communities to understand the ecology of litter-inhabiting fungi and improve methodologies for sampling leaf-associated fungal communities. The factors affecting the assembly of plant microbiomes are complex and varied but connecting individual interactions to community composition and ultimately function may improve our abilities to predict and manage microbiome processes.
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Title: UNDERSTANDING THE SOLID/SOLID AND LIQUID/SOLID INTERFACE PHENOMENA FOR ALTERNATIVE ENERGY APPLICATIONS
Creator: Phongpreecha, Thanaphong
Date: 2018
Collection: Electronic Theses & Dissertations
Description: In many alternative energy technologies, interfacial phenomena are critical in determining process efficiency and feasibility. Previously, a complete application of density functional theory (DFT) as a tool to study interfaces has not only led to fundamental insights into the system, but also predictive models and recommendations for materials that were experimentally validated. In this thesis, it is first demonstrated that such an approach can also be used to solve a well-characterized...
Show moreIn many alternative energy technologies, interfacial phenomena are critical in determining process efficiency and feasibility. Previously, a complete application of density functional theory (DFT) as a tool to study interfaces has not only led to fundamental insights into the system, but also predictive models and recommendations for materials that were experimentally validated. In this thesis, it is first demonstrated that such an approach can also be used to solve a well-characterized interface problems related to sustainable energy technologies. This first problem is a solid/solid interface between the solid oxide fuel cell (SOFC) and its sealant, specifically an interface between SOFC’s exposed electrolyte, which is typically made of yttria-stabilized zirconia (YSZ), and the commercial Ag-CuO sealing braze. The current material, CuO, which helps molten Ag to wet on YSZ surfaces and later adhere once the Ag is solidified, has been previously characterized to form a CuO-rich layer between Ag and YSZ. However, over time it is reduced by the SOFC’s reductive conditions and results in formation of pores. Therefore, alternative oxides are needed that are thermodynamically stable in SOFC’s high operating temperatures and also provide similar adhesion properties to CuO. To that end, this thesis has identified two mechanisms that enable only CuO to work so far. First, it was found that, unlike most other Ag/oxides, the Ag/CuO interface has a particularly strong adhesion ‒ five times that of Ag/YSZ. Second, the dissolved oxygen in molten Ag from air during the brazing process diffuses to the interface and partially improves adhesion. The high adhesion of Ag/CuO was proposed to be from CuO’s unique atomic structure. Therefore, a descriptor based on the oxide’s structural and chemical features was developed to predict Ag/oxide adhesion. The descriptor expedites screening of new oxides as no expensive calculation is needed, leading to several recommendations such as CuAlO2 and Cu3TiO4.In the second problem, a more complex and less well-characterized interface in sustainable energy technologies is investigated. It should be noted that due to the complexity, the screening model cannot be developed yet. This second interface is a liquid/solid interface between solvated lignin and its catalyst. Lignin is a highly heterogeneous polymer in lignocellulosic biomass with many functional groups. Its valorization is essential to the economic feasibility of biorefinery, and its catalytic hydrogenolysis in a liquid phase is well-studied technology route to add value to the lignin. Many experiments have shown that solvent choice can have large impacts on product types and yields. However, the solvent effect on the reaction is still unclear. An understanding of the solvated lignin/catalyst interface would be valuable. For this, we are interested in the adsorption. To achieve this, spectroscopic and wet chemistry techniques are first used to help characterize the system by identifying that the quantity of ether linkages in lignin is the most critical functional group that determines the hydrogenolysis yields. Using a lignin dimer that contains a characteristic ether linkage, DFT shows that, in vacuum, the adsorption of the dimer is much stronger on Ni(111) than Cu(111). Upon solvation with ethanol, it was found that the dimer-metal interactions weaken so significantly that for Cu(111), it no longer adsorbs onto the metal surface. This implies that Cu may not provide high catalytic activity, which agrees with hydrogenolysis experiments performed in this thesis, although there could be other contributing factors. Lastly, to circumvent large DFT calculations, a model based on a thermodynamic cycle was developed to predict adsorption energy of a solvated lignin dimer for a given pair of solvent and catalyst. Although the model is not suitable for screening purposes, it provides a valuable, quantitative insight to the solvent effects.
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Title: USE OF LAGRANGIAN METHODS TO SIMULATE HEAVY STORM-INDUCED RIVER PLUME DYNAMICS AND RECREATIONAL WATER QUALITY IMPACTS IN THE NEARSHORE REGION OF SOUTHWESTERN LAKE MICHIGAN
Creator: Weiskerger, Chelsea
Date: 2022
Collection: Electronic Theses & Dissertations
Description: The Great Lakes are the primary source of drinking water for nearly 30 million people in the region. During storm events runoff from upstream watersheds and (combined) sewer overflows delivers pathogens to the Lakes. The pathogens are then transported to beaches and water intakes by the lake circulation, posing risks to human health. Fecal indicator organisms such as Escherichia coli are used to track pollution levels and to take proactive measures to manage coastal resources and to safeguard...
Show moreThe Great Lakes are the primary source of drinking water for nearly 30 million people in the region. During storm events runoff from upstream watersheds and (combined) sewer overflows delivers pathogens to the Lakes. The pathogens are then transported to beaches and water intakes by the lake circulation, posing risks to human health. Fecal indicator organisms such as Escherichia coli are used to track pollution levels and to take proactive measures to manage coastal resources and to safeguard public health by closing beaches to the public, issuing swimming advisories, etc. Predictive modeling of coastal water quality continues to be an attractive approach to generate water quality forecasts and to gain insights into key processes. Although progress has been made in understanding and quantifying the impacts of tributary loading and river plumes on microbial pollution at beaches, the impacts of extreme storm events on coastal water quality are not well-understood. As the frequency and intensity of storm events increase, the pollution footprint of extreme storm events has not been quantified in a way that can be used to inform policy. Complex nearshore features, including irregular coastlines and coastal structures calls for high-resolution modeling that is computationally demanding. While traditional Eulerian approaches to plume modeling have been previously used, comparisons with available observed plume data indicated that Lagrangian particle tracking improves prediction of plume dimensions (and hence risks) in southwestern Lake Michigan. Therefore, coupled hydrodynamic and reactive particle tracking models were developed and tested to simulate the complex dynamics of multiple river plumes induced by extreme storm events in the Chicago area in southwestern Lake Michigan. The present-day Chicago River normally flows to the Mississippi River and discharges into Lake Michigan only during “backflow” events triggered by these storms. Simulations of extreme storm-induced river plumes during years 2008, 2010, 2011, 2013 and 2017 were reported and models tested using available data on currents, water temperatures, concentrations of indicator bacteria (E. coli) and the spatial extent of turbidity plumes using MODIS Terra satellite imagery. Results suggest that plumes associated with the extreme storms persist along the Chicago shoreline for up to 24 days after the commencement of backflow release and that plume areas of influence range from 7.9 to 291 km2 in the nearshore. Plume spatiotemporal dynamics were largely related to the volume of water released via backflow events and the duration of the backflow releases. Empirical relations were proposed to allow beach and stormwater managers to predict plume spatiotemporal dynamics in real time. Model results from a Lagrangian E. coli fate and transport model were compared against monitoring data collected at 16-18 beaches during and after backflow events in 2010 and 2011. Results indicate that all Chicago Park District beaches are susceptible to E. coli concentrations that exceed USEPA thresholds for safe recreation after extreme storms. Therefore, the current approach to beach management, which involves closing all beaches during and immediately after backflow events, is likely prudent. However, results also suggest that beaches are probably being reopened prematurely after storm events, as beaches may be at risk for degraded water quality for multiple days, post backflow event. To address data gaps, we recommend that future research focus on the collection of additional in situ hydrometeorological and water quality data during and after extreme storms and backflow events. These data may be collected using unmanned aerial vehicles or autonomous sensor systems.
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Title: USING MACHINE LEARNING TO UNCOVER POPULATION HETEROGENEITY IN LONGITUDINAL STUDY
Creator: Lee, Youngjun
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Machine learning has been an emerging data analytic tool in the fields of quantitative social and behavioral sciences. Among others, model-based recursive partitioning (MOB) is one of the popular comprehensive approaches incorporating parametric model into tree-based algorithm. It has gained growing interests as a complementary data analytic tool to address population heterogeneity by detecting parameter instability over candidate covariates. Structural equation models using tree algorithm ...
Show moreMachine learning has been an emerging data analytic tool in the fields of quantitative social and behavioral sciences. Among others, model-based recursive partitioning (MOB) is one of the popular comprehensive approaches incorporating parametric model into tree-based algorithm. It has gained growing interests as a complementary data analytic tool to address population heterogeneity by detecting parameter instability over candidate covariates. Structural equation models using tree algorithm (SEM Trees) has particularly shown its benefits for discovering informative covariates and their complex interactions that predict differences in structural parameters with interpretable results, which in turn produces distinct homogeneous subgroups. While all previous studies make important contributions to use this approach, it has been less examined to investigate the performance of SEM Trees where there exist interaction effects of various types of covariates (i.e., categorical, ordinal, and continuous), which is the key motivation of this study. This study has three main purposes. First, it aims to introduce a framework of MOB for educational researchers and guide them when it can be beneficial with an illustrative example using nationally representative longitudinal data (High School Longitudinal Study of 2009). A parametric latent growth curve model (LGCM) is used as a template model along with MOB. Second, a simulation study for a given LGCM is conduced to investigate the performance of MOB, which provides researchers with statistical evidence of how well MOB recovers true subgroups. Simulation conditions include a) effect size (0.2, 0.4, 0.6, 0.8, and 1.0), b) sample size (1,000, 2,000, 5,000, 10,000, and 20,000), c) three different test statistic for ordinal covariate (chi-square, adapted maximum Lagrange multiplier, and a weighted double maximum), d) pre pruning option of limiting the minimum sample size per subgroup (250 vs. none), and e) post pruning option (BIC vs. none). The main evaluation criteria are a) statistical power to recover true subgroups, b) overall classification accuracy and precision, c) accuracy of cut points of ordinal/continuous covariates and labels of categorical covariates, and d) bias and root mean squared error (RMSE) of the parameter estimates per subgroup. Third, the simulation is parallelly conducted with GMM, and the results of it are compared with the ones of MOB. The key findings suggest that medium effect size (0.4 - 0.6) with relatively large sample sizes (5,000, 10,000, and 20,000) and large effect size (0.8 - 1.0) with adequate sample size (1,000 or 2,000) are enough to distinguish the difference in focal parameters, recovering the true number of subgroups. In addition, treating ordinal variables as either ordinal or categorical is not different in terms of recovering the true subgroups. However, the empirical study suggests that using test statistic for the ordinal covariates is desired when there exist association between the outcome and ordinal covariate. Post pruning using BIC and limiting the minimum size per subgroup simultaneously are also desired options. Without the post pruning with BIC, MOB tends to over-extract the subgroups across conditions. With the same simulated datasets, GMM produced neither accurate subgroups nor reliable parameter estimates. This study sheds light on how to uncover subpopulations using MOB algorithm with a popular parametric model for longitudinal study. This approach is beneficial for large-scale data such as more than 10,000 sizes with large number of potential covariates. Limitations and future directions are also discussed. The findings play a critical role to lay the groundwork of extending the application of MOB into various statistical models by investigating its performance regarding complex covariate effects.
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Title: USING THE “KITE” FRAMEWORK FOR UNDERSTANDING LANDSCAPE CHANGE AND IMPROVING EAST AFRICAN AGRICULTURAL SYSTEMS UNDER CLIMATE CHANGE
Creator: Wanyama, Dan
Date: 2021
Collection: Electronic Theses & Dissertations
Description: The Mount Elgon Ecosystem (MEE), an important hydrological and socio-economic area in East Africa, has exhibited significant landscape changes, driven by both natural factors and human activities, therefore leading to more frequent natural disasters (frequent and extended droughts, floods, and landslides). Yet, few studies have focused on the MEE socio-ecological system; no comprehensive knowledge exists of how humans and nature interact, at multiple scales, to drive ecosystem-wide landscape...
Show moreThe Mount Elgon Ecosystem (MEE), an important hydrological and socio-economic area in East Africa, has exhibited significant landscape changes, driven by both natural factors and human activities, therefore leading to more frequent natural disasters (frequent and extended droughts, floods, and landslides). Yet, few studies have focused on the MEE socio-ecological system; no comprehensive knowledge exists of how humans and nature interact, at multiple scales, to drive ecosystem-wide landscape changes. This dissertation focuses on three interrelated questions: (1.) What is the nature and magnitude of change in MEE greenness for the period 2001-2018, and how is this change related to long-term trends and variability in MEE precipitation? (2.) How is ecological and environmental (eco-environmental) vulnerability distributed across the MEE, and what are the major factors driving these patterns? and (3.) How will the MEE landscape change in the future, and what opportunities exist for streamlining livelihood improvement and environmental conservation efforts?Study 1 characterized comprehensively, over multiple time scales, recent patterns and trends in MEE vegetation greening and browning. The MEE was found to exhibit significant variability in vegetation dynamics and precipitation regimes. There was persistent greening and browning at different time scales and this change was attributed to both natural factors (including changing precipitation) and anthropogenic factors (especially the vegetation-to-cropland conversion). The study also concluded that MEE precipitation had increased substantially in the post-2000 era, which influenced greening and browning patterns observed in the 2006-2010 period. The integration of Mann–Kendall, Sen’s slope and bfast (breaks for additive season and trend) proved useful in comprehensively characterizing recent changes in vegetation greenness within the MEE. Study 2 examined eco-environmental vulnerability for the MEE using freely available remote sensing (RS), topographic, and socio-economic data. The study found that the majority of the MEE (comprising savannas, grasslands, and most of the agricultural land in Ugandan MEE) was moderately vulnerable based on the analysis methods and variables used. The eco-environmental vulnerability index (EEVI) showed a marked increase in vulnerability with decrease in elevation. Eco-environmental vulnerability was strongly associated with multi-year variables based on precipitation, temperature, and population density. Moreover, precipitation distribution was changing especially in the wet season, thus adding another layer of risk for agriculture and ultimately for local community livelihoods.Study 3 simulated possible future land use changes in the MEE based on existing RS LULC products and a well-known land use change model. The study projected that agriculture will possibly expand from approximately 58% in 2001 to more than 64% in 2033 if current and future LULC transformation follows rates in 2001-2017. These new croplands will occur mostly around edges of the protected forest and zones of transition between mixed vegetation and existing croplands. Due to the unpredictable LULC transitions in the MEE, simulating forest-to-cropland conversion was less accurate compared to mixed-to-cropland conversion. This research provides a more complete explanation of the underlying complex human-environment interactions shaping the MEE landscape. This is the first study to comprehensively assess landscape dynamics at multiple scales (10-day, 16-day, monthly, seasonal, and household). It is also the first to define and assess at the annual scale, eco-environmental vulnerability as influenced by climate, topographic and socio-economic variables. In addition, by simulating future LULC change, this research provides the opportunity to quantify and anticipate possible LULC changes in the MEE. This research relies on publicly available RS and geospatial datasets and therefore analyses conducted here can easily be translated to other similar regions.
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Title: Ultrafast transient states in nonequilibrium quantum systems
Creator: Hwang, Bin
Date: 2017
Collection: Electronic Theses & Dissertations
Description: Photo-induced phase transitions (PIPT) in quantum systems are the epitome of challenging non-equilibrium many-body phenomena, that also have a wide range of potential applications. Recently interest in light-matter coupled states with an energy gap have yielded evidence for Floquet topological states. In this study we demonstrate nonequilibrium Floquet band formation under ultrafast optical excitation using a one-dimensional topological insulator. As an example, the effects are illustrated...
Show morePhoto-induced phase transitions (PIPT) in quantum systems are the epitome of challenging non-equilibrium many-body phenomena, that also have a wide range of potential applications. Recently interest in light-matter coupled states with an energy gap have yielded evidence for Floquet topological states. In this study we demonstrate nonequilibrium Floquet band formation under ultrafast optical excitation using a one-dimensional topological insulator. As an example, the effects are illustrated using a new Zig-Zag Su-Schrieffer-Heeger model of polyacetylene, which is a paradigmatic Hamiltonian exhibiting nontrivial edge states. Our results indicate short optical pulses feasible in experiments can induce novel topological states, local spectral selection and novel pseudospin textures in polyacetylene. Pump-probe photoemission spectroscopy is able to study these states by measuring Floquet band formation and sizeable energy gaps on femtosecond time scales. We find that optically activated nontrivial variations of sublattice mixing could lead to novel topological phenomenon.The rich variety of states induced by lasers have a wide range of potential applications so that control of these states has become a key objective. We present a computational approach to finding optimal ultrafast laser pulse shapes to induce target states and population inversion in pump-probe PIPT experiments. The Krotov approach for Quantum optimal control theory (QOCT) is combined with a Keldysh Green’s function calculation to describe experimental outcomes such as photoemission, transient single particle density of states and optical responses. Results for a simple model charge density wave (CDW) system are presented, including generation of almost complete population inversion and negative temperature states.
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Title: Understanding adhesion to monitor and control environmental processes : From virus detection to membrane fouling mitigation
Creator: Wang, Xunhao
Date: 2022
Collection: Electronic Theses & Dissertations
Description: Adhesion is a physicochemical process of great importance for various environmental engineering technologies including those that are employed in water treatment facilities Understanding adhesion is the key to elucidating separation mechanisms in unit processes and operations such as flocculation, granular media filtration, membrane separation. The likelihood of adhesion can be quantified in terms of the interfacial energy of interaction between two objects. The first part of this...
Show moreAdhesion is a physicochemical process of great importance for various environmental engineering technologies including those that are employed in water treatment facilities Understanding adhesion is the key to elucidating separation mechanisms in unit processes and operations such as flocculation, granular media filtration, membrane separation. The likelihood of adhesion can be quantified in terms of the interfacial energy of interaction between two objects. The first part of this dissertation is devoted to the study of virus adhesion to surfaces commonly encountered in various indoor settings. Fomites are inanimate surfaces, which can transfer the pathogens to a new human host. Fomite-based transfer is an important pathway of virus transmission, along with direct contact and transmission through aerosols. The study of fomites has traditionally focused on determining whether there is presence of specific pathogenic organisms. In addition to detecting genetic material and viable microbes on fomite surfaces, it is also important to understand the underlying mechanism of virus adhesion and factors that affect the likelihood of transmission between fomites and humans. In this dissertation, Quartz Crystal Microbalance with Dissipation monitoring (QCM-D) is employed to quantify virus attachment to fomites. XDLVO modeling is applied to predict the virus-fomites interactions. Virion size, surface charge and surface energy components as well as surface charge and surface energy components of various fomites were measured and used as inputs to the XDLVO model.The second part of this dissertation describes the study of membrane filter aging due to membrane’s intermittent exposure to foulants and cleaning agents. This study explores how the surface chemistry of polyvinylidene fluoride (PVDF) membranes evolves in challenge tests with humic acid (HA) fouling and sodium hypochlorite (NaClO) employed as a model foulant and cleaning agent, respectively. The evolution of physicochemical properties of the ageing membranes is characterized based on surface energy calculations. The results point to the formation of a chemically irreversible layer of foulants that is conditioned by consecutive exposures to foulants and is comprised of the adsorbed foulant fraction that is hard to oxidize further.
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Title: Understanding free-carrier accumulation in semiconductor nanomaterials : plasmonic behavior, charge storage energetics, and quantum confinement resilience of colloidal indium nitride nanocrystals
Creator: Liu, Zhihui
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Heavily doped semiconductor nanocrystals (NCs) are promising materials that can reversibly and substantially store electrical charges. Indium nitride (InN) is a particularly interesting semiconductor material for studying charge storage processes. Colloidal InN NCs are spontaneously degenerately doped with carrier densities large enough to lead to strong localized surface plasmon resonances (LSPR) in the infrared (IR) part of the spectrum. Unfortunately, many fundamental quantities that...
Show moreHeavily doped semiconductor nanocrystals (NCs) are promising materials that can reversibly and substantially store electrical charges. Indium nitride (InN) is a particularly interesting semiconductor material for studying charge storage processes. Colloidal InN NCs are spontaneously degenerately doped with carrier densities large enough to lead to strong localized surface plasmon resonances (LSPR) in the infrared (IR) part of the spectrum. Unfortunately, many fundamental quantities that ultimately control the behavior of colloidal InN NCs are currently unknown. In this thesis, we focused on advancing our current understanding of the properties of colloidal InN NCs, with special emphasis on the quantification of free electron density, the LSPR behavior, the charge storage ability, the screening effect on phonon behaviors and few other important fundamental quantities such as the electron effective mass, Fermi level, conduction band (CB) edge potential and IR transition oscillator strength.To understand the LSPR behavior of InN NCs, we first evaluated the free carrier density with a direct, model-independent quantification. We found that the number of free electrons per as-prepared InN NC is directly proportional to the NC volume, such that the free electron density is a size-independent quantity. Furthermore, we demonstrated that free electrons in InN NCs can be reversibly extracted with redox species, which leads to a direct way to manipulate the LSPR. Importantly, the LSPR energy in InN NCs barely shifts with free electron density, a behavior strikingly at odds with what is typically observed in other semiconductor plasmonic systems. These unusual plasmonic signatures are shown to arise from the nonparabolicity of the CB dispersion, which leads to a change in the electron effective mass with the number of free electrons per NC, thus mitigating the shift of LSPR in InN NCs.Consequently, we estimated the charge storage capability of InN NCs by pinning the chemical potential of InN NCs to redox-active molecular species. These studies directly yielded precise information on the Fermi level and on the chemical capacitance of InN NCs, which allowed the CB edge potential of InN NCs to be quantitatively determined for the first time. Surprisingly, the CB edge in InN NCs hardly showed any sign of quantum confinement effects, even for NCs sizes that were clearly smaller than the excitonic Bohr radius of InN. This "resilience to quantum confinement" effect was shown to also arise from the same nonparabolic dispersion effects described above.In addition, the light harvesting ability of free electrons in InN NCs was evaluated by calculating the molar absorptivity per free electron. This value directly yielded the optical oscillator strength of LSPR. We found that optical oscillator strength (per free electron) is independent of NC.Finally, the effects of free electrons on lattice vibrations were also explored. We demonstrated that free electrons weakened the A1(LO) phonon mode by screening the Coulombic restoring force induced by the lattice distortion. The A1(LO) mode frequency red-shifted linearly with the increasing free electron density. This relationship provided a fast way to estimate free electron density of InN NCs by measuring Raman spectroscopy.
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Title: Understanding the intersection of loneliness and recovery setting in older cardiac patients
Creator: Macomber, Catherine A.
Date: 2017
Collection: Electronic Theses & Dissertations
Description: "Loneliness has significant negative impact on health. Loneliness is the difference between the amount of social support you expect to receive and the amount you perceive you are getting. Age is one risk factor of loneliness, and life events such as a move to a nursing home or the need for professional care to provide assistance with Activities of Daily Living also increase the risk of loneliness. There is little evidence comparing the experience of loneliness between settings of nursing...
Show more"Loneliness has significant negative impact on health. Loneliness is the difference between the amount of social support you expect to receive and the amount you perceive you are getting. Age is one risk factor of loneliness, and life events such as a move to a nursing home or the need for professional care to provide assistance with Activities of Daily Living also increase the risk of loneliness. There is little evidence comparing the experience of loneliness between settings of nursing homes and at home with home care, and yet much current policy sees aging-in-place, staying in your own home, as the most appropriate setting for growing older. This mixed methods study compares the experience of loneliness in two settings, nursing home and at home, and the influence demographics and social support have on this relationship. The theoretical framework used is the Health Belief Model." -- Abstract.
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Title: Understanding the relationship between work-life flexstyle, job satisfaction, and turnover intention among new professionals in student affairs
Creator: Artale, Paolo
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Attrition amongst new professionals in student affairs has been cited as high as sixty-percent Holmes, Verrier, & Chisholm 1983; Ward, 1995). High rates of employee turnover are problematic for institutions and result in work inefficiencies, costly rehiring processes, and overburdening current employees with increased load (Kantor, 2016). Studies of attrition within student affairs have found several factors that contribute to these high rates of departure including but not limited to heavy...
Show moreAttrition amongst new professionals in student affairs has been cited as high as sixty-percent Holmes, Verrier, & Chisholm 1983; Ward, 1995). High rates of employee turnover are problematic for institutions and result in work inefficiencies, costly rehiring processes, and overburdening current employees with increased load (Kantor, 2016). Studies of attrition within student affairs have found several factors that contribute to these high rates of departure including but not limited to heavy workloads, working long and unusual hours, lack of opportunities for advancement, low levels of pay compared to the private sector, difficulty keeping tasks and emotions that originated at work with those at home (and vice versa), and emotional stress due to being personally invested in the lives of students (Evans, 1988; Lorden, 1998; Marshall, Gardner, Hughes, & Lowery, 2016; Ward, 1995). Within the discussion of meeting combating turnover, the topic of workplace flexibility has emerged. Employees are requiring more latitude to deal with issues such as childcare, elder care, as well as other day-to-day needs. While studies have often referred to policies and formal mechanisms regarding workplace flexibility and the impact it has on retention, there has been a lack of discussion around the role flexstyle plays in employee performance and satisfaction. Flexstyle refers to a way of thinking about the relationships between work and personal life (Kossek & Lautsch, 2008). The purpose of this study was to understand the potential relationship between work-life flexstyle amongst new student affairs professionals and the variables of job satisfaction and turnover intention. To examine the relationship between flexstyle, job satisfaction, and turnover intention, an electronic survey utilizing Kossek, Ruderman, Braddy, and Hannum's (2012) work-nonwork boundary management assessment, Judge, Locke, Durham, and Kluger's (1998) shortened version of Brayfield and Rothe's (1951) Job Satisfaction Schedule, and Bothma and Roodt's (2013) Turnover Intention Scale - 6 (TIS-6) was administered to those who identified as new professionals to members of the National Association of Student Personnel Administrators (NASPA) Knowledge Community for Graduate Students and New Professionals, the American College Personnel Association (ACPA), and the Southern Association of College Student Affairs (SACSA). A total of 287 members provided usable data for use in analysis. Results from the data that utilized ANCOVA showed that significant differences in means existed for behavior factor groups in relation to both job satisfaction and turnover intention. Results from the data that utilized multiple regression showed that significant positive relationships existed between the flexstyle factors of boundary control and work identity with job satisfaction. In addition, data that utilized multiple regression showed that a significant negative relationship existed between the flexstyle factor of boundary control and turnover intention. Implications for student affairs practitioners and researchers and recommendations for future research are also discussed.
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Title: Understanding work with data in summer STEM programs through an experience sampling method approach
Creator: Rosenberg, Joshua M.
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Data-rich activities provide an opportunity to develop core competencies in both science and mathematics identified in curricular standards. Perhaps even more importantly work with data puts learners in the position to use data to ask and answer questions, a potentially empowering capability. Research on work with data has focused on cognitive outcomes and the development of specific practices at the student and classroom levels, and yet, little research has considered learners’ engagement....
Show moreData-rich activities provide an opportunity to develop core competencies in both science and mathematics identified in curricular standards. Perhaps even more importantly work with data puts learners in the position to use data to ask and answer questions, a potentially empowering capability. Research on work with data has focused on cognitive outcomes and the development of specific practices at the student and classroom levels, and yet, little research has considered learners’ engagement. The present study explores learners engagement in work with data in the context of summer STEM programs. The aspects of work with data that are the focus of this study are: asking questions, observing phenomena, constructing measures and generating data, data modeling, and interpreting findings. Data from measures of learners' engagement was collected through the Experience Sampling Method (ESM) that involves asking learners at random intervals to answer short questions about their engagement to discover profiles of learners' engagement.Data was collected from nine summer STEM programs over four weeks in the Northeastern United States. 203 learners reported 2,970 responses via short ESM surveys of how engaged they were (cognitively, behaviorally, and affectively, assessed through separate items) and of their perceptions of themselves (their competence) and the activity (its challenge). These data were used to examine five specific research questions: 1) What is the frequency and nature of opportunities for youth to engage in each of the five aspects of work with data in summer STEM programs? 2) What profiles of engagement emerge from data collected via ESM in the programs? 3) What are sources of variability for the profiles of engagement? 4) How do the five aspects of work with data relate to profiles of engagement? 5) How do youth characteristics relate to profiles of engagement?Findings show that aspects of work with data were fairly common overall, but that work with data was enacted out in varying ways, including some that were possibly highly engaging. Six profiles of youth engagement were identified, representing distinct configurations of the five indicators of engagement. Substantial variability in the profiles was present at the youth level, with less explained by the program youth were in or the nature of the particular instructional episode present at the times when youth were signaled. Relations between the profiles of engagement and each of the aspects of work with data were somewhat small: Notable exceptions were the generating data and data modeling were significantly associated with full engagement. Youth with higher pre-program interest in STEM were more likely to be engaged and competent but not challenged, though other youth characteristics were not highly related to the profiles.I discuss key findings as regards work with data in summer STEM programs and other informal learning environments, the nature of youths' engagement, and what factors can predict engagement. The design and goals of summer STEM programs, which are not (necessarily) focused on activities related to work with data, as well as other limitations including the measures for work with data used and the analytic approach, are identified and described. The role of generating data and modeling data as well as attention to the specifics of how work with data are enacted are presented as implications for practice. I highlight aspects of the findings and the implications for practice with respect to work with data in general and to engagement in informal learning environments, such as summer STEM programs, in both cases with an emphasis on how work with data can serve as a promising context for learning in STEM subject areas.
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Title: Unexpected journeys : at the crossroads of collaborative filmmaking and feminist scholarship
Creator: Von Petersdorff-Campen, Anne Christin
Date: 2018
Collection: Electronic Theses & Dissertations
Description: This hybrid dissertation combines collaborative, creative filmmaking and feminist scholarship grounded in German studies. The written dissertation addresses fundamental issues in feminist filmmaking--body, voice, and collaboration--and is in part conceived as a complement to the travel documentary Wanderlust, cuerpos en tránsito(2017), a bi-autobiographical account of a journey from Egypt to Germany that was co-directed and produced by the author of this dissertation and Maria Pérez-Escalá.

Title: Urban and cluster agglomeration economies's effects on rural households in Asia
Creator: Hu, Chaoran
Date: 2017
Collection: Electronic Theses & Dissertations
Description: "Agglomeration effects play important roles for rural households in participating in farm and nonfarm activities. With the rapid growth of cities of different sizes and the development of food value chain, how these agglomerations of urban effects, networks, and food value chain clusters will affect rural households' participation in nonfarm employment and farm behavior (technology adoption) are not yet well known. The dissertation consists of three chapters that aim to assess the impacts of...
Show more"Agglomeration effects play important roles for rural households in participating in farm and nonfarm activities. With the rapid growth of cities of different sizes and the development of food value chain, how these agglomerations of urban effects, networks, and food value chain clusters will affect rural households' participation in nonfarm employment and farm behavior (technology adoption) are not yet well known. The dissertation consists of three chapters that aim to assess the impacts of these urban and cluster agglomeration economies' on rural households in Asia."--Excerpted from abstract.
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Title: Urban expansion and urban environmental evaluation in Chengdu, China
Creator: Tao, Shiqi
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Environmental consequences resulting from urbanization jeopardize the life quality and social welfare of urban residents. To date, studies have focused on the urban environment by using integrated assessment methods and providing one evaluation result for the whole geographic area within an administrative boundary. These studies lack consideration of spatial heterogeneity, failing to fully understand the urban environmental statuses and dynamics at the pixel scale. Therefore, this research...
Show moreEnvironmental consequences resulting from urbanization jeopardize the life quality and social welfare of urban residents. To date, studies have focused on the urban environment by using integrated assessment methods and providing one evaluation result for the whole geographic area within an administrative boundary. These studies lack consideration of spatial heterogeneity, failing to fully understand the urban environmental statuses and dynamics at the pixel scale. Therefore, this research aims to fill this gap by systematically evaluating the urban environment at every single spatial unit of urban land against the background of urban expansion in Chengdu, a megacity in western China. Guided by a proposed three-dimensional (self, neighborhood and accessibility) theoretical framework, this study uses remote sensing and GIS data and adapts the catastrophe theory to evaluate Chengdu's urban environment in a spatially explicit manner. Results from change detection of the urban area in Chengdu show a high-speed expansion from the urban center towards all directions, especially southwest during 2000-2015. Environmental assessment analysis reveals an improved urban center but degraded outskirts regarding environmental conditions. The regression analysis suggests a negative effect of rapid urban expansion on the environment, while this effect can be alleviated through better planning strategies. Therefore, it is suggested that policy makers should balance the speed of urban expansion and urban environmental planning to provide a better living environment for urban residents in Chengdu. The integration of remote sensing and urban environmental assessment can be applied to other cities in China and elsewhere around the world.
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Title: Use of Recycled Aggregate Materials Characteristics in Pavement Design Analyses
Creator: Gheibi, Ida
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Use of recycled materials promotes sustainability in roadway construction by reducing consumption of energy and emission of greenhouse gases associated with mining and the production of natural aggregates. Recycled asphalt pavements (RAP) and recycled concrete aggregates (RCA) have comparable characteristics to natural aggregates that are currently used in roadway base course applications. This study has developed a database for RAP and RCA materials’ characteristics including resilient...
Show moreUse of recycled materials promotes sustainability in roadway construction by reducing consumption of energy and emission of greenhouse gases associated with mining and the production of natural aggregates. Recycled asphalt pavements (RAP) and recycled concrete aggregates (RCA) have comparable characteristics to natural aggregates that are currently used in roadway base course applications. This study has developed a database for RAP and RCA materials’ characteristics including resilient modulus (Mr), California bearing ratio (CBR), gradations along with construction specifications. RAP and RCA relationships with different engineering and index properties were investigated and some trends were proposed such as higher RAP content reveals higher summary of resilient modulus (SMr), higher RCA content causes higher optimum moisture content (OMC) and lower maximum dry unit (MDU).In addition, pavement mechanistic-empirical (ME) analyses have been conducted with the material inputs collected for the database to determine whether different values of different characteristics of RCA and RAP can be used in flexible or rigid pavement designs. Results showed that Mr parameter had the highest impact on pavement distress predictions among gradations and hydraulic conductivity.
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Title: Use of administative claims data to design and emulate a clinical trial in acute stroke patients comparing rehabilitation at inpatient rehabilitation facilities to skilled nursing facilities
Creator: Simmonds, Kent P.
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Stroke affects nearly 800,000 people every year in the United States and is a leading cause of adult disability. After hospitalization half of stroke patients continue to require medical and rehabilitation services provided at inpatient rehabilitation facilities (IRFs) or skilled nursing facilities (SNFs). In general, IRFs provide time-intensive therapy for two to three weeks, while SNFs provide moderately intensive therapy for four- to five-weeks. There is substantial variation in the...
Show moreStroke affects nearly 800,000 people every year in the United States and is a leading cause of adult disability. After hospitalization half of stroke patients continue to require medical and rehabilitation services provided at inpatient rehabilitation facilities (IRFs) or skilled nursing facilities (SNFs). In general, IRFs provide time-intensive therapy for two to three weeks, while SNFs provide moderately intensive therapy for four- to five-weeks. There is substantial variation in the utilization of these alternative rehabilitation settings, but their relative comparative effectiveness remains uncertain. A randomized controlled trial (RCT) would provide an unbiased comparative effectiveness estimate, but the design of such a trial is complicated by several practical and ethical issues. The overarching purpose of this dissertation was to use Medicare claims data to inform the design and to emulate such a trial. In the first aim, we sought to identify patient and hospital level factors that were associated with IRF or SNF discharge and characterize the heterogeneity of hospital effects that influenced discharge to an IRF (vs. SNF). From a retrospective cohort of 145,894 stroke patients, we used multi-level multivariable models to identify several patient- and hospital- level factors that were independently associated with discharge setting. We also showed that hospitals contributed around a third of the variation in IRF (vs. SNF) discharge, but there was substantial variation in the effect that specific hospitals had on influencing IRF discharge. The second aim, was to identify a target trial population that optimized the explanatory-pragmatic balance of a subsequent RCT. To identify this population, we profiled hospitals based on their propensity to discharge stroke patients to IRFs (vs. SNFs) and inferred IRF and SNF referral networks for each hospital. The final target trial population included 44,950 patients (30.8% of the starting sample) who were treated at 441 hospitals (14.5%) and subsequently discharged to 745 IRFs (64.8%) and 5,974 SNFs (48.2%).The third aim was to emulate three alternate RCTs that compared patient outcomes at IRFs vs. SNFs. Trial #1 used the target trial population identified in Aim 2, while trials #2 and 3 excluded increasingly infrequently used IRFs and SNFs. Comparative effectiveness was estimated using a matched propensity score analysis. Overall, on a relative basis, patients treated at IRFs were between 18-35% more likely to be successfully discharged home (i.e., alive and at home for >30 days) and were between 11-15% less likely to die within one year of acute care discharge. The variation in the effect size estimates across the trials was driven by poorer outcomes among patients treated at infrequently used SNFs. Finally, we identified that a moderate sized unmeasured confounder would nullify the observed differences.In conclusion, we identified that referring hospitals are a major driver of IRF or SNF use, and that patients treated at IRFs had better outcomes (relative to SNF patients). However, our results were limited by the inability to adjust for potentially important unmeasured confounders. A pragmatic RCT would eliminate such biases and provide a more valid comparative effectiveness estimate of these two alternative rehabilitation settings.
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Title: Use of water mist to reduce the risk of frost damage in tree fruits
Creator: Rijal, Ishara
Date: 2017
Collection: Electronic Theses & Dissertations
Description: Climate variability and change have been major threats to global food security historically and will almost certainly continue to be threats in the future given the sensitivity of agricultural production systems to their surrounding environment. Recent changes in temperature and seasonality have significantly impacted commercial fruit production in the Great Lakes region. Michigan's sour cherry and apple production in 2012 was reduced by about 90% and 88%, respectively, compared to the...
Show moreClimate variability and change have been major threats to global food security historically and will almost certainly continue to be threats in the future given the sensitivity of agricultural production systems to their surrounding environment. Recent changes in temperature and seasonality have significantly impacted commercial fruit production in the Great Lakes region. Michigan's sour cherry and apple production in 2012 was reduced by about 90% and 88%, respectively, compared to the previous year's production due to a series of spring freeze events (USDA, 2013). The timing of the seasonal warm up in the spring and resulting onset of phenological development is a key factor in determining potential cold damage risk for overwintering perennial tree fruit crops, as the vulnerability of vegetation to freeze injury increases rapidly with the stage of development. Application of water prior to the onset of growth has been used in the past to delay early vegetative development of temperate tree fruit crops. Evaporative cooling associated with this approach effectively reduces plant tissue temperature, slowing the rate of growth and leaving it less vulnerable to freezing temperatures. There are several potential drawbacks, however, including consumption of large quantities of water that could increase nutrient leaching along with elevated risks of plant disease risk. This study examined the potential effectiveness of water applied as a spray mist via a new plant management technology, the solid set canopy delivery system (SSCD), to suppress tree fruit bud temperatures and delay the phenological development of the buds. There were two major portions: 1) A detailed collection of field-based phenological and physiological observations associated with the operation of a prototype SSCD cooling system and: 2) Development of a deterministic model of tree fruit bud temperature that was used to examine the potential of water-based cooling of buds in Michigan. The observational study aimed to identify the timing and discharge rate of mist applications on cherry and apple trees was carried out in a growth chamber and at five Michigan orchards (apple at St. Joseph, Charlotte, and Hillsdale, sweet cherry at SWMREC, and sour cherry at Traverse City,) during the 2014, 2015, and 2016 growing seasons with automated instrumentation to monitor and control the water mist flow rate based on environmental conditions. Water mist was applied to apple and cherry buds via the SSCD system after the end of endo-dormancy until king bloom in the non-misted buds based on ambient air temperature and relative humidity. Overall, in three years of the field study misting delayed bloom by 4-9 days in apple and 7- 11 days in cherry, all using substantially less water than that reported in earlier studies; 8.4 to 26 cm/ha in apple and 5.5 to 10.8 cm/ ha in sweet cherry. The deterministic heat transfer model of a tree fruit bud was developed with observational data from growth chamber, potted plant and field-based studies. The model was calibrated using growth chamber data and validated using potted plant and field data. In a model validation study, model simulated one-minute bud temperatures were generally found to be in good agreement with observed bud temperatures, with overall mean average differences of -0.5±0.30C (lab observations) and -0.3±0.15 0C (field observations), mean absolute differences less than 10C and R-square values of 0.80 or greater. The model was then run with ten years of hourly climate data at three locations in major fruit-producing regions of Michigan (2006-2015). Overall, the model estimated a delay in bloom of misted buds by more than a week compared to non-misted buds, which translates into a potential reduction in the frequency of damaging freeze events of 50-75 %, and decrease in freeze injury severity by 10-60 % in misted apple buds and 45-100% in misted cherry buds. Collectively, the results suggest that the spray mist technique has promise as a straightforward and effective indirect frost control strategy with relatively few environmental impacts.
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Title: Using Eventual Consistency to Improve the Performance of Distributed Graph Computation In Key-Value Stores
Creator: Nguyen, Duong Ngoc
Date: 2021
Collection: Electronic Theses & Dissertations
Description: Key-value stores have gained increasing popularity due to their fast performance and simple data model. A key-value store usually consists of multiple replicas located in different geographical regions to provide higher availability and fault tolerance. Consequently, a protocol is employed to ensure that data are consistent across the replicas.The CAP theorem states the impossibility of simultaneously achieving three desirable properties in a distributed system, namely consistency,...
Show moreKey-value stores have gained increasing popularity due to their fast performance and simple data model. A key-value store usually consists of multiple replicas located in different geographical regions to provide higher availability and fault tolerance. Consequently, a protocol is employed to ensure that data are consistent across the replicas.The CAP theorem states the impossibility of simultaneously achieving three desirable properties in a distributed system, namely consistency, availability, and network partition tolerance. Since failures are a norm in distributed systems and the capability to maintain the service at an acceptable level in the presence of failures is a critical dependability and business requirement of any system, the partition tolerance property is a necessity. Consequently, the trade-off between consistency and availability (performance) is inevitable. Strong consistency is attained at the cost of slow performance and fast performance is attained at the cost of weak consistency, resulting in a spectrum of consistency models suitable for different needs. Among the consistency models, sequential consistency and eventual consistency are two common ones. The former is easier to program with but suffers from poor performance whereas the latter suffers from potential data anomalies while providing higher performance.In this dissertation, we focus on the problem of what a designer should do if he/she is asked to solve a problem on a key-value store that provides eventual consistency. Specifically, we are interested in the approaches that allow the designer to run his/her applications on an eventually consistent key-value store and handle data anomalies if they occur during the computation. To that end, we investigate two options: (1) Using detect-rollback approach, and (2) Using stabilization approach. In the first option, the designer identifies a correctness predicate, say $\Phi$, and continues to run the application as if it was running on sequential consistency, as our system monitors $\Phi$. If $\Phi$ is violated (because the underlying key-value store provides eventual consistency), the system rolls back to a state where $\Phi$ holds and the computation is resumed from there. In the second option, the data anomalies are treated as state perturbations and handled by the convergence property of stabilizing algorithms.We choose LinkedIn's Voldemort key-value store as the example key-value store for our study. We run experiments with several graph-based applications on Amazon AWS platform to evaluate the benefits of the two approaches. From the experiment results, we observe that overall, both approaches provide benefits to the applications when compared to running the applications on sequential consistency. However, stabilization provides higher benefits, especially in the aggressive stabilization mode which trades more perturbations for no locking overhead.The results suggest that while there is some cost associated with making an algorithm stabilizing, there may be a substantial benefit in revising an existing algorithm for the problem at hand to make it stabilizing and reduce the overall runtime under eventual consistency.There are several directions of extension. For the detect-rollback approach, we are working to develop a more general rollback mechanism for the applications and improve the efficiency and accuracy of the monitors. For the stabilization approach, we are working to develop an analytical model for the benefits of eventual consistency in stabilizing programs. Our current work focuses on silent stabilization and we plan to extend our approach to other variations of stabilization.
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