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Title: THE ROLE OF JAZ PROTEINS IN THE REGULATION OF PLANT GROWTH-DEFENSE TRADEOFFS
Creator: Guo, Qiang
Date: 2018
Collection: Electronic Theses & Dissertations
Description: As sessile organisms, plants constantly experience challenges from the surrounding environment. In response to these biotic stresses, plants invest a prominent portion of their metabolic capacity in the production of defense-associated compounds and physical structures. However, expression of defense traits is often associated with growth restriction and ultimately reduces reproductive output. Although this growth-defense antagonism has a profound impact on plant biology and agricultural...
Show moreAs sessile organisms, plants constantly experience challenges from the surrounding environment. In response to these biotic stresses, plants invest a prominent portion of their metabolic capacity in the production of defense-associated compounds and physical structures. However, expression of defense traits is often associated with growth restriction and ultimately reduces reproductive output. Although this growth-defense antagonism has a profound impact on plant biology and agricultural practice, the mechanisms that regulate tradeoffs between growth and defense are poorly understood. The plant hormone jasmonate (JA) plays a dual role in enhancing immune responses and inhibiting growth. The JA signaling cascade is switched on when the bioactive form of the hormone is recognized by the COI1-JAZ co-receptor complex, which leads to the degradation of JAZ repressors via the SCFCOI1-26S proteasome pathway and subsequent relief of JA-responsive transcription factors (TFs). In this dissertation research, I first show that JAZ proteins promote growth and reproductive fitness in the model plant Arabidopsis thaliana by suppressing metabolic pathways for defense. Characterization of a jaz decuple (jazD) mutant defective in 10 JAZ genes revealed that hyperactivation of JA signaling significantly increased resource allocation to defense pathways, thereby improving plant resistance to insect herbivores and necrotrophic pathogens. The elevated defense of jazD was linked to carbon starvation, curtailed seed production and, under extreme conditions, lethality. Secondly, I show that the allocation costs associated with heightened JA responses in jazD was largely dependent on the bHLH-type TFs MYC2, MYC3 and MYC4, and that MYC2/3/4 played overlapping andconserved roles in metabolic reprogramming in jazD. Characterization of jazD myc mutants further showed that the JAZ-MYC transcriptional module controls the production of endoplasmic reticulum (ER)-derived structures called ER bodies, which are implicated in plant immunity. Finally, the jazD mutant was employed as a parental line in a genetic suppressor screen aimed at identification of novel mutations that uncouple growth-defense antagonism. Characterization of these suppressor of jazD (sjd) mutants revealed that JA signaling interacts with the red light signaling pathway to influence growth-defense balance. One sjd mutant (sjd56) not affected in red light signaling was also shown to partially uncouple growth-defense antagonism in jazD. Taken together, results from this dissertation provide evidence that growth-defense tradeoffs at low to moderate levels of defense are controlled by hardwired transcriptional networks, whereas high levels of defense inhibit growth through metabolic competition (allocation costs) between primary and secondary metabolism. Consistent with this view, JAZ proteins promote growth and reproductive fitness by preventing the negative effects of an unrestrained immune responses. The findings described in this dissertation may benefit the development of crop plants that are optimized for both growth and defense.
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Title: Affective education by design : an experiential pedagogy for natural resources education
Creator: Higley, Corrine A.
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Attitudes and values are considered an important component of learning in higher education, but natural resources and environmental education programs typically emphasize cognitive gains in the design of instructional activities and subsequent assessments. This research suggests that greater consideration of affective learning outcomes should be more explicitly considered to better achieve learning goals, and identifies experiential learning as a pedagogy that integrates the three domains of...
Show moreAttitudes and values are considered an important component of learning in higher education, but natural resources and environmental education programs typically emphasize cognitive gains in the design of instructional activities and subsequent assessments. This research suggests that greater consideration of affective learning outcomes should be more explicitly considered to better achieve learning goals, and identifies experiential learning as a pedagogy that integrates the three domains of learning to facilitate the cognitive and affective development of students. In the first chapter, the relationship between attitudes and subsequent behaviors is explored from various theoretical perspectives in the context of environmental education. It is argued that greater attention to how attitudes are formed and shaped, as well as characteristics of attitudes that influence how resistant to change they are, is necessary to achieve broader goals of affective development. Direct experiences as they relate to the development, accessibility, stability, and strength of attitudes are identified as a significant factor, with important implications for affective learning in higher education. The second chapter explores the influence of experience across the cognitive, affective, and psychomotor domains of learning and presents various approaches for incorporating experiential learning into college and university curricula. Two course models at Michigan State University (MSU) that employ experiential learning pedagogies are described in detail, as well as the benefits and constraints of each model, and concludes with a discussion of barriers to implementing experiential learning pedagogies into college and university curricula more broadly. The third chapter links theory and practice to explore how various dimensions of environmental attitudes are influenced as an outcome of experiential learning in both MSU courses. Connectedness to nature, which measures the cognitive, affective, and experiential components of an individual's relationship with nature, is identified as a relevant construct to assess affective development in the context of learning goals for both courses. Experiential learning was demonstrated to significantly increase overall nature relatedness, as well as the affective and cognitive aspects of students' connectedness to nature as an outcome of learning in both MSU courses. The experiential dimension of connectedness to nature was not influenced by course participation, and may be a relic of students' past experiences in and with nature that contributed to their choice of major. Results indicate that experiential learning to increase students' connectedness to nature may be more impactful for students in other disciplines, those with lower initial nature relatedness scores, or individuals with less previous experience in nature. These results suggest that affective learning outcomes can be achieved when they are explicitly considered in course and curriculum design, and provides evidence in support of experiential learning as a useful pedagogy for the affective development of undergraduate students. The final chapter of this dissertation shifts focus from affective learning gains to cognitive ones to assess whether learning outcomes are influenced by order of instruction in an experiential learning activity. Results indicate that order of instruction does not influence how well students learn course material when experiential pedagogies are employed. The significance of experiential learning on affective and cognitive learning outcomes in higher education to better achieve learning goals warrants further consideration.
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Title: Natural language based control and programming of robotic behaviors
Creator: Cheng, Yu (Graduate of Michigan State University)
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "Robots have been transforming our daily lives by moving from controlled industrial lines to unstructured and dynamic environments such as home, offices, or outdoors working closely with human co-workers. Accordingly, there is an emerging and urgent need for human users to communicate with robots through natural language (NL) due to its convenience and expressibility, especially for the technically untrained people. Nevertheless, two fundamental problems remain unsolved for robots to working...
Show more"Robots have been transforming our daily lives by moving from controlled industrial lines to unstructured and dynamic environments such as home, offices, or outdoors working closely with human co-workers. Accordingly, there is an emerging and urgent need for human users to communicate with robots through natural language (NL) due to its convenience and expressibility, especially for the technically untrained people. Nevertheless, two fundamental problems remain unsolved for robots to working in such environments. On one hand, how to control robot behaviors in dynamic environments due to presence of people is still a daunting task. On the other hand, robot skills are usually preprogrammed while an application scenario may require a robot to perform new tasks. How to program a new skill to robots using NL on the fly also requires tremendous efforts. This dissertation tries to tackle these two problems in the framework of supervisory control. On the control aspect, it will be shown ideas drawn from dynamic discrete event systems can be used to model environmental dynamics and guarantee safety and stability of robot behaviors. Specifically, the procedures to build robot behavioral model and the criteria for model property checking will be presented. As there are enormous utterances in language with different abstraction level, a hierarchical framework is proposed to handle tasks lying in different logic depth. Behavior consistency and stability under hierarchy are discussed. On the programming aspect, a novel online programming via NL approach that formulate the problem in state space is presented. This method can be implemented on the fly without terminating the robot implementation. The advantage of such a method is that there is no need to laboriously labeling data for skill training, which is required by traditional offline training methods. In addition, integrated with the developed control framework, the newly programmed skills can also be applied to dynamic environments. In addition to the developed robot control approach that translates language instructions into symbolic representations to guide robot behaviors, a novel approach to transform NL instructions into scene representation is presented for robot behaviors guidance, such as robotic drawing, painting, etc. Instead of using a local object library or direct text-to-pixel mappings, the proposed approach utilizes knowledge retrieved from Internet image search engines, which helps to generate diverse and creative scenes. The proposed approach allows interactive tuning of the synthesized scene via NL. This helps to generate more complex and semantically meaningful scenes, and to correct training errors or bias. The success of robot behavior control and programming relies on correct estimation of task implementation status, which is comprised of robotic status and environmental status. Besides vision information to estimate environmental status, tactile information is heavily used to estimate robotic status. In this dissertation, correlation based approaches have been developed to detect slippage occurrence and slipping velocity, which provide grasp status to the high symbolic level and are used to control grasp force at lower continuous level. The proposed approaches can be used with different sensor signal type and are not limited to customized designs. The proposed NL based robot control and programming approaches in this dissertation can be applied to other robotic applications, and help to pave the way for flexible and safe human-robot collaboration."--Pages ii-iii.
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Title: Robust multi-task learning algorithms for predictive modeling of spatial and temporal data
Creator: Liu, Xi (Graduate of Michigan State University)
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "Recent years have witnessed the significant growth of spatial and temporal data generated from various disciplines, including geophysical sciences, neuroscience, economics, criminology, and epidemiology. Such data have been extensively used to train spatial and temporal models that can make predictions either at multiple locations simultaneously or along multiple forecasting horizons (lead times). However, training an accurate prediction model in these domains can be challenging especially...
Show more"Recent years have witnessed the significant growth of spatial and temporal data generated from various disciplines, including geophysical sciences, neuroscience, economics, criminology, and epidemiology. Such data have been extensively used to train spatial and temporal models that can make predictions either at multiple locations simultaneously or along multiple forecasting horizons (lead times). However, training an accurate prediction model in these domains can be challenging especially when there are significant noise and missing values or limited training examples available. The goal of this thesis is to develop novel multi-task learning frameworks that can exploit the spatial and/or temporal dependencies of the data to ensure robust predictions in spite of the data quality and scarcity problems. The first framework developed in this dissertation is designed for multi-task classification of time series data. Specifically, the prediction task here is to continuously classify activities of a human subject based on the multi-modal sensor data collected in a smart home environment. As the classes exhibit strong spatial and temporal dependencies, this makes it an ideal setting for applying a multi-task learning approach. Nevertheless, since the type of sensors deployed often vary from one room (location) to another, this introduces a structured missing value problem, in which blocks of sensor data could be missing when a subject moves from one room to another. To address this challenge, a probabilistic multi-task classification framework is developed to jointly model the activity recognition tasks from all the rooms, taking into account the block-missing value problem. The framework also learns the transitional dependencies between classes to improve its overall prediction accuracy. The second framework is developed for the multi-location time series forecasting problem. Although multi-task learning has been successfully applied to many time series forecasting applications such as climate prediction, conventional approaches aim to minimize only the point-wise residual error of their predictions instead of considering how well their models fit the overall distribution of the response variable. As a result, their predicted distribution may not fully capture the true distribution of the data. In this thesis, a novel distribution-preserving multi-task learning framework is proposed for the multi-location time series forecasting problem. The framework uses a non-parametric density estimation approach to fit the distribution of the response variable and employs an L2-distance function to minimize the divergence between the predicted and true distributions. The third framework proposed in this dissertation is for the multi-step-ahead (long-range) time series prediction problem with application to ensemble forecasting of sea surface temperature. Specifically, our goal is to effectively combine the forecasts generated by various numerical models at different lead times to obtain more precise predictions. Towards this end, a multi-task deep learning framework based on a hierarchical LSTM architecture is proposed to jointly model the ensemble forecasts of different models, taking into account the temporal dependencies between forecasts at different lead times. Experiments performed on 29-year sea surface temperature data from North American Multi-Model Ensemble (NAMME) demonstrate that the proposed architecture significantly outperforms standard LSTM and other MTL approaches."--Pages ii-iii.
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Title: Nonlinear Dynamics of Charged Particles : Analysis, Computation and Simulation
Creator: Hipple, Robert
Date: 2019
Collection: Electronic Theses & Dissertations
Description: There is no shortage of simulation software in accelerator physics. Faced with the myriad of options, a researcher will typically select one or two reliable codes, learn them well, and stand by them. It is the very nature of computer simulation that different codes have various strengths and differences. This reality underscores the importance of benchmarking multiple codes against one another. This philosophy holds especially true in accelerator modeling, where nonlinearities and the sheer...
Show moreThere is no shortage of simulation software in accelerator physics. Faced with the myriad of options, a researcher will typically select one or two reliable codes, learn them well, and stand by them. It is the very nature of computer simulation that different codes have various strengths and differences. This reality underscores the importance of benchmarking multiple codes against one another. This philosophy holds especially true in accelerator modeling, where nonlinearities and the sheer complexity of the simulated scenarios make analytic verification of results difficult, if not impossible. An excellent methodology to confirm that the results of a simulation represent real physics is to run the same test across multiple codes and compare the results.While pursuing my graduate studies at MSU, I have been able to implement this multi-code strategy in several contexts. Simulating the COSY-Julich storage ring in MAD8 and Zgoubi, the dynamic aperture seemed acceptable. However, upon porting the lattice to COSY Infinity, we discovered the surprising result that the lattice as specified was unstable when fringe fields were taken into account. This result would not have been apparent had we limited our simulations to only the original two codes. A similar analysis was performed on the HESR storage ring to be constructed at FAIR. There it was discovered that the nonlinearities which limit dynamic aperture were not visible while using impulse approximation modes in the codes MAD8 and MADX. Porting the lattice to COSY INFINITY, we were able to model the nonlinearities to a high degree of accuracy. This time, we had the positive result of determining that fringe fields did not affect the stability of the lattice. Often when codes disagree in their predictions, the cause of the discrepancy is not immediately apparent. Such was the case when comparing the codes LISE++ and COSY INFINITY in their modeling of spherical and cylindrical electrostatic deflectors. Disagreement in the second order aberration initiated a full analytic investigation into the nature of these aberrations. New physics clarified by that work is also presented here for the first time. Finally, an analysis of the Oak Ridge Isomer/Isotope Spectrometer/Separator (ORISS), was performed. ORISS is an electrostatic multiply reflecting time-of-flight (MRTOF) mass separator that was built by the University Radioactive Ion Beam Consortium (UNIRIB). The device was never fully commissioned due to the Oak Ridge group losing funding, and ended up at Michigan State University for use at the Facility for Rare Isotopes and Beams (FRIB). MRTOF devices are typically used at very low particle intensities due to strong Coulomb repulsion at the particle turning points. Questions were opened on whether the device could operate effectively in a high resolution mass separation mode at high particle intensities. Simulations performed on the iCER High Performance Computing Cluster at MSU show that the device can be operated effectively in this mode at high intensities if voltages are adjusted properly. This was the first analysis of the device to take the effects of intense space charge into consideration and the results are presented here for the first time.
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Title: Catalyst studies on the conversion of biobased intermediates to biobased products
Creator: Nezam, Iman
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "The goal of this work is to enhance the production of fuels and chemicals from fermentation-derived materials via two routes. Route (a) focuses on Guerbet chemistry, the n-butanol production from ethanol; route (b) studies the production of acrylate esters from 2-acetoxypropanoic acid (APA) esters. The catalytic condensation of ethanol to n-butanol and higher alcohols, known as the Guerbet reaction, has attracted more attention in recent years due to the commercial availability of ethanol as...
Show more"The goal of this work is to enhance the production of fuels and chemicals from fermentation-derived materials via two routes. Route (a) focuses on Guerbet chemistry, the n-butanol production from ethanol; route (b) studies the production of acrylate esters from 2-acetoxypropanoic acid (APA) esters. The catalytic condensation of ethanol to n-butanol and higher alcohols, known as the Guerbet reaction, has attracted more attention in recent years due to the commercial availability of ethanol as a bio-renewable feedstock. Among various catalysts considered for this process, none have obtained stable and economically affordable yields; alumina-supported metals have been less explored despite their promising primary results in the lower energy-demanding condensed-phase. Experiments on the continuous condensed-phase conversion of ethanol to n-butanol using Ni/La2O3/gamma-Al2O 3 catalyst present a WHSV of > 0.8 h--1 and a temperature range of 210--250 °C as the ideal reaction conditions. Several nickel bimetallic catalysts have been examined to optimize the reaction performance further; characterization techniques have been employed to understand the behavior of these catalysts more effectively. Copper addition shifts the selectivity of the Guerbet products toward n-butanol rather than C 6+ alcohols, which is explained by the copper behavior reducing H2 adsorption on the catalyst. Furthermore, the number of nickel atoms on the surface of the catalyst correlates directly with the performance of the Guerbet reaction, suggesting that the dehydrogenation of ethanol is the rate-limiting step of the reaction. Among different catalysts and reaction conditions studied, the best results were obtained at the temperature of 250 °C and WHSV of 0.8 h--1 using 1.0 wt% Ni/9.0 wt% Ni/La2O3/gamma-Al 2O3 with 41% ethanol conversion and 74% C4+ alcohols selectivity. Fusel alcohol Guerbet studies under the same conditions have resulted in 88% higher alcohols selectivity at 12% conversion. Preliminary kinetic modeling analysis for the isoamyl alcohol-ethanol mixtures shows that the ethanol self-condensation reaction has the highest rate constant among the self-condensation and cross-condensation reactions in the system. Economic analysis for a first-generation facility producing 25 million gallons of n-butanol per year has been performed for several scenarios of catalytic performance and process configuration to investigate the viability of the commercial use of this catalyst. Results indicate that the n-butanol required selling price at 25% return on investment (ROI) can vary between $1.30--$1.60 per kg of n-butanol, which is reasonably competitive with the current n-butanol market price. The highly selective production of 2-acetoxypropanoic acid (APA) from lactic acid and acetic acid through reactive distillation has motivated the study of the elimination reaction of APA esters to acrylate esters. Among different APA esters studied, the best results are obtained for those with no hydrogen on the beta-carbon of the ester functionality. This hydrogen allows the elimination of the ester group as an alkene, leading to the production of highly reactive materials that can decompose to other side-products and reduce the desired products selectivity. The use of CO2 as the diluent gas reduces the amount of carbon deposited on the surface of the contact material and maintains the rate of the elimination reaction in extended operation. Highest yields of 35% for butyl acrylate and 70% for methyl acrylate and benzyl acrylate at 550 °C and LHSV of 1.9 h--1 have been achieved in this study."--Pages ii-iii.
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Title: A novel approach for property modification of cast aluminum alloys with nanostructured chemical additions
Creator: Lu, Yang (Graduate of Michigan State University)
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "Continued weight reduction which involves replacing steel components with lightweight materials is one of the major strategies to achieve the average fuel economy standards in the automotive industry. Based on the significant success of aluminum alloys in non-structural components, aluminum alloys in structural applications attract particular interest. To this end, the ultimate objective is to achieve aluminum alloys with high ductility and strength. However, conventional aluminum-silicon ...
Show more"Continued weight reduction which involves replacing steel components with lightweight materials is one of the major strategies to achieve the average fuel economy standards in the automotive industry. Based on the significant success of aluminum alloys in non-structural components, aluminum alloys in structural applications attract particular interest. To this end, the ultimate objective is to achieve aluminum alloys with high ductility and strength. However, conventional aluminum-silicon (Al-Si) based casting alloys possess low ductility as compensation for the required high strength, since the presence of irregular eutectic silicon crystals in the as-cast condition promotes crack initiation and propagation. Strontium (Sr) is widely used to modify the Si eutectic in commercially available "high ductility" cast aluminum alloys. However, fading issues arise due to Sr oxidation at the casting temperature, and become major concerns for aluminum foundries. Therefore, it is important to develop a universal modifier that can be used in alloys with a larger range of Si content. In this thesis, trisilanol polyhedral silsesquioxane (TSP) was first incorporated in Sn-based binary and ternary alloys, leading to microstructure refinement and high creep resistance. Based on these preliminary results, TSP was further applied to Al based alloys. First, TSP was coated on Al-12Si powders using dip-coating approach. After melting, the microstructure of both primary Al and eutectic microconstituents of Al-12Si ingots was refined. Ductility increased from 5% with no TSP treatment to 18% when treated with TSP. More interestingly, the modified structure was maintained with 150 ppm of TSP addition. The incorporation of TSP reduced the undercooling and arrest temperatures of Al-Si eutectic during solidification. These results suggest TSP bonds with Al to slow down the Al segregation from Al-Si melt during eutectic reaction, leading to the microstructural refinement of Al-Si eutectic microconstituents. Based on the laboratory-scale results, a new TSP master was produced to facilitate the incorporation of TSP into traditional foundry process. The optimized master composition contained 6%TSP in an Al-12Si alloy, and 10% Al-12Si-6TSP master was applied to modify Al-Si binary and commercial alloys at a 100 lbs. scale. In Al-Si binary alloys, TSP addition results 50% improvement in ductility over the Al-7.5Si base alloy without sacrificing the strength. The microstructure of both primary Al and eutectic microconstituents of the Al-7.5Si alloy with TSP addition was refined. Minimal fade was observed up to a 192-hour hold at 720°C, which sheds light on the Sr fading issue. In Aural(TM) 2 and W319 -type commercial alloys, TSP additions reduced the solidification shrinkage of castings. Metallography showed refined Si in the Al-Si eutectic microconstituent and reduced Al secondary dendrite arm spacing (SDAS), resulting in an 100% improvement in ductility without sacrificing strength. Besides microstructural refinement, the mass fraction of theta (Al2Cu) increased while Q (Al4Cu2Mg8Si7) decreased with TSP addition, suggesting TSP changes the Cu intermetallic compounds (IMCs) to favor the formation of theta, which demonstrated its potential as a strengthening precipitate. This study addresses fundamental questions on how the addition of TSP influences microstructure and solidification behavior of Al-Si based casting alloys, thus providing solutions to reinforce aluminum alloys in body structures for the environmental and fuel economy benefits."--Pages ii-iii.
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Title: Improving spectrum efficiency in heterogeneous wireless networks
Creator: Liu, Chin-Jung
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Over the past decades, the bandwidth-intensive applications that are previously confined to wired networks are now migrating to wireless networks. This trend has brought unprecedented high demand for wireless bandwidth. The wireless traffic is destined to dominate the Internet traffic in the future, but many of the popular wireless spectrum bands, especially the cellular and ISM bands, are already congested. On the other hand, some other wireless technologies, such as TV bands, often do not...
Show moreOver the past decades, the bandwidth-intensive applications that are previously confined to wired networks are now migrating to wireless networks. This trend has brought unprecedented high demand for wireless bandwidth. The wireless traffic is destined to dominate the Internet traffic in the future, but many of the popular wireless spectrum bands, especially the cellular and ISM bands, are already congested. On the other hand, some other wireless technologies, such as TV bands, often do not fully utilize their spectrum. However, the spectrum allocation is tightly regulated by the authority and adjusting the allocation is extremely difficult. The uneven utilization and the rigid regulation have led to the proposal of heterogeneous wireless networks, including cognitive radio networks (CRN) and heterogeneous cellular networks (HetNet). The CRNs that usually operate on different technologies from the spectrum owner attempt to reuse the idle spectrum (i.e., white space) from the owner, while HetNets attempt to improve spectrum utilization by smallcells. This dissertation addresses some of the challenging problems in these heterogeneous wireless networks.In CRNs, the secondary users (SU) are allowed to access the white spaces opportunistically as long as the SUs do not interfere with the primary users (PU, i.e., the spectrum owner). The CRN provides a promising means to improve spectral efficiency, which also introduces a set of new research challenges. We identify and discuss two problems in CRNs, namely non-contiguous control channel establishment and k-protected routing protocol design. The first problem deals with the need from SUs for a channel to transfer control information. Most existing approaches are channel-hopping (CH) based, which is inapplicable to NC-OFDM. We propose an efficient method for guaranteed NC-OFDM-based control channel establishment by utilizing short pulses on OFDM subcarriers. The results show that the time needed for establishing control channel is lower than that of CH-based approaches. The second problem deals with the interruption to a routing path in a CRN when a PU becomes active again. Existing reactive approaches that try to seek for an alternative route after PU returns suffer from potential long delay and possible interruption if an alternative cannot be found. We propose a k-protected routing protocol that builds routing paths with preassigned backups that are guaranteed to sustain from k returning PUs without being interrupted. Our result shows that the k-protected routing paths are never interrupted even when k PUs return, and have significantly shorter backup activation delays.HetNets formed by smallcells with different sizes of coverage and macrocells have been proposed to satisfy increased bandwidth demand with the limited and crowded wireless spectrum. Since the smallcells and macrocells operate on the same frequency, interference becomes a critical issue. Detecting and mitigating interference are two of the challenges introduced by HetNets. We first study the interference identification problem. Existing interference identification approaches often regard more cells as interferers than necessary. We propose to identify interference by analyzing the received patterns observed by the mobile stations. The result shows that our approach identifies all true interferers and excludes most non-interfering cells. The second research problem in HetNets is to provide effective solutions to mitigate the interference. The interference mitigation approaches in the literature mainly try to avoid interference, such as resource isolation that leads to significantly fewer resources, or power control that sacrifices signal quality and coverage. Instead of conservatively avoiding interference, we propose to mitigate the interference by precanceling the interfering signals from known interferers. With precancellation, the same set of resources can be shared between cells and thus throughput is improved.This dissertation addresses several challenges in heterogeneous wireless networks, including CRNs and HetNets. The proposed non-contiguous control channel protocol and k-protected routing protocol for CRNs can significantly improve the feasibility of CRNs in future wireless network applications. The proposed interference identification and interference precancellation approaches can effectively mitigate the interference and improve the throughput and spectrum utilization in HetNets. This dissertation aims at breaking the barriers for supporting heterogeneous wireless networks to improve the utilization of the precious and limited wireless spectrum.
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Title: User contribution and its social-welfare value in a mobile navigation app for real-time traffic information around urban areas
Creator: Kim, Tae Hun (Professor of business information systems)
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Today, users of mobile devices (smartphones and tablets) adopt a variety of apps, use social features, and engage in crowdsourcing content as a public good. This dissertation explains their user community, i.e., a mobile virtual community, in terms of user contribution and its social-welfare value around urban areas. Essay 1 conceptualizes a virtual and spatial factor, i.e., virtual crowdedness, and addresses its role in encouraging user contribution. The findings are theoretically explained...
Show moreToday, users of mobile devices (smartphones and tablets) adopt a variety of apps, use social features, and engage in crowdsourcing content as a public good. This dissertation explains their user community, i.e., a mobile virtual community, in terms of user contribution and its social-welfare value around urban areas. Essay 1 conceptualizes a virtual and spatial factor, i.e., virtual crowdedness, and addresses its role in encouraging user contribution. The findings are theoretically explained by the tension between prosocial behavior of and bystander effect on the mobile virtual community. Essay 2 theorizes whether and how user contribution, attributed to self-interest, supports social welfare for the whole citizenry. I found that user contribution improves the mobility of urban transportation and reduces social and economic costs. As an exemplar of citizen-data science, this dissertation takes a spatial and panel data approach to analyze the large-scale data on mobile app users, traffic conditions, and their locations in the urban region. The empirical findings are visualized and discussed to explain practical implications for mobile app design and policy on urban transportation.
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Title: The design of East Lansing & Michigan state college airport
Creator: Rushman, Glenn A.
Date: 1946
Collection: Electronic Theses & Dissertations

Title: A framework for combining ancillary information with primary biometric traits
Creator: Ding, Yaohui
Date: 2018
Collection: Electronic Theses & Dissertations
Description: "Biometric systems recognize individuals based on their biological attributes such as faces, fingerprints and iris. However, in several scenarios, additional ancillary information such as the biographic and demographic information of a user (e.g., name, gender, age, ethnicity), or the image quality of the biometric sample, anti-spoofing measurements, etc. may be available. While previous literature has studied the impact of such ancillary information on biometric system performance, there is...
Show more"Biometric systems recognize individuals based on their biological attributes such as faces, fingerprints and iris. However, in several scenarios, additional ancillary information such as the biographic and demographic information of a user (e.g., name, gender, age, ethnicity), or the image quality of the biometric sample, anti-spoofing measurements, etc. may be available. While previous literature has studied the impact of such ancillary information on biometric system performance, there is limited work on systematically incorporating them into the biometric matching framework. In this dissertation, we develop a principled framework to combine ancillary information with biometric match scores. The incorporation of ancillary information raises several challenges. Firstly, ancillary information such as gender, ethnicity and other demographic attributes lack distinctiveness and can be used to distinguish population groups rather than individuals. Secondly, ancillary information such as image quality and anti-spoof measurements may have different numerical ranges and interpretations. Further, most of the ancillary information cannot be automatically extracted without errors. Even the direct collection of ancillary information from subjects may be susceptible to transcription errors (e.g., errors in entering the data). Thirdly, the relationships between ancillary attributes and biometric traits may not be evident. In this regard, this dissertation makes three contributions. The first contribution entails the design of a Bayesian Belief Network (BBN) to model the relationship between biometric scores and ancillary factors, and exploiting the ensuing structure in a fusion framework. The ancillary information considered by the network includes image quality and anti-spoof measures. Experiments convey the importance of explicitly incorporating such information in a biometric system. The second contribution is the design of a Generalized Additive Model (GAM) that uses spline functions to model the correlation between match scores and ancillary attributes, and then learns a transformation function to normalize the match scores prior to fusion. The resulting framework can also be used to predict in advance if fusing match scores with certain demographic attributes is beneficial in the context of a specific biometric matcher. Experiments indicate that the proposed method can be used to significantly improve the recognition accuracy of state-of-the-art face matchers. The third contribution is the design of an ensemble of One Class Support Vector Machines (OC-SVMs) to combine multiple anti-spoofing measurements in order to mitigate the concerns associated with the issue of "imbalanced training sets" and "insufficient spoof samples" encountered by conventional anti-spoofing algorithms. In the proposed method, the spoof detection problem is formulated as a one-class problem, where the focus is on modeling a real fingerprint using multiple feature sets. The one-class classifiers corresponding to these multiple feature sets are then combined to generate a single classifier for spoof detection. Experimental results convey the importance of this technique in detecting spoofs made of materials that were not included in the training data. In summary, this dissertation seeks to advance our understanding of systematically exploiting ancillary information in designing effective biometric recognition systems by developing and evaluating multiple statistical models."--Pages ii-iii.
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Title: Family income, the home environment, sustained attention, genetic susceptibility, and children's reading outcomes : a structural equation modeling analysis
Creator: Westdal, June N.
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Seemingly small reading delays in early childhood have the potential to compound into more considerable reading difficulties later in childhood (Bast & Reitsma, 1998; Foster & Miller, 2007). Children growing up in at-risk households are especially vulnerable to falling behind in reading. The objective of this study was to explore the successive interactions and indirect effects of environmental and within child variables that influence reading outcomes for at-risk children. The work was...
Show moreSeemingly small reading delays in early childhood have the potential to compound into more considerable reading difficulties later in childhood (Bast & Reitsma, 1998; Foster & Miller, 2007). Children growing up in at-risk households are especially vulnerable to falling behind in reading. The objective of this study was to explore the successive interactions and indirect effects of environmental and within child variables that influence reading outcomes for at-risk children. The work was informed by Bronfenbrenner’s bioecological model (Bronfenbrenner & Ceci, 1994), prevailing models of children’s reading development (National Reading Council, 2000), and mediational theories on the effects of poverty (Yeung, Linver, & Brooks-Gunn, 2002). This study examined the associations between income, the early home environment (home literacy and maternal depression), sustained attention, genetic susceptibility, and children's reading outcomes in kindergarten and third-grade. Data were drawn from a nationally representative dataset of at-risk families and children, the Fragile Families and Child Wellbeing Study (FFCWS). The primary analysis techniques were latent variable structural equation modeling (SEM) that examined the mediated and moderated pathways between environmental and within child variables. The final study sample consisted of approximately 2,062 children and their primary caregivers, mostly mothers. Several direct associations were significant. Results indicated that households with more income had children with better reading scores in kindergarten, but not in third grade. Children’s early sustained attention predicted their kindergarten and third-grade reading scores. Mothers’ endorsements of depression did not predict their children’s reading in kindergarten or third grade. Homes with more home literacy had children with higher reading scores in kindergarten, but the direct effects of the early home literacy environment did not persist until third grade. Analyses only supported the indirect path through the home literacy environment. More specifically, homes with more income had more enriched home literacy environments, and children exposed to better home literacy environments had better reading outcomes in kindergarten and third grade. Moderation analyses did not support the hypothesis that DRD4 long allele would differentiate the associations between income, home literacy environment, and children’s third-grade reading outcomes. Post- hoc analyses were conducted using two group SEM comparison testing. A unique and novel significant moderation effect was identified, where the DRD4 long allele moderated the direct association between the early home literacy environment and children’s kindergarten letter-word reading. The findings provide support for the importance of the home environment during the early developmental period and the genetic susceptibility of children with the DRD4 long allele during kindergarten.
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Title: Towards lignin valorization : pyrolytic and electrochemical upgrading of lignins extracted from pretreated biomass to valuable intermediates
Creator: Garedew, Mahlet
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Hydrocarbons, made from fossil petroleum, currently remain the most practical energy sources for transportation. But with current energy crisis and the implication of burning fossil fuels as one of the major contributors to climate change, the production of fuels from biomass has become a possible alternative to displace fossil-based fuels. Unfortunately, biomass suffers from two flaws: (1) Inefficiency: at best, plants only capture and store about 1% of the sun’s energy in chemical form; and...
Show moreHydrocarbons, made from fossil petroleum, currently remain the most practical energy sources for transportation. But with current energy crisis and the implication of burning fossil fuels as one of the major contributors to climate change, the production of fuels from biomass has become a possible alternative to displace fossil-based fuels. Unfortunately, biomass suffers from two flaws: (1) Inefficiency: at best, plants only capture and store about 1% of the sun’s energy in chemical form; and (2) Energy density: biomass has about one third of the energy that of hydrocarbons. So, deriving value from all components of biomass including lignin, optimizing conversion processes that can harness the chemical energy stored in biomasses efficiently, and converting biomass to fuels that are energy dense is essential. To this end, conventional biomass to ethanol conversion strategies utilize pretreatment methods such as extractive ammonia pretreatment (EA) and alkaline hydrogen peroxide pretreatment (AHP), to improve the rates and extents of subsequent hydrolysis of sugars and maximize biofuel yields. As part of the pretreatment method, EA and AHP also enable the recovery of lignin which is often combusted for heat and power production. Lignin however accounts for 40% of the energy of biomass and is one of the largest natural sources of renewable aromatic compounds so it can be an ideal candidate for the production of higher-value products that would otherwise be derived from petrochemical feedstocks. The challenges in lignin valorization however come from lignin’s complex structure that is naturally designed to be resistant to biological degradation. Thermochemical conversion processes such as fast pyrolysis offer a strategy for lignin depolymerization. During fast pyrolysis the feedstock (biomass, lignin, etc.) is liquefied by heating in an oxygen free environment to form biochar, combustible gas and bio-oil. The biochar co-product has potential for use in soil amendment and carbon sequestration. The combustible gas is often burned for heat and power production. The major product, bio-oil, has the potential to displace liquid hydrocarbon fuels. However, bio-oil’s reactive and corrosive nature along with its low energy content are major barriers for the adaption of this system. Classical catalytic upgrading is usually used to hydrogenate and deoxygenate bio-oil, often at high temperature and very high pressure. These severe conditions can result in barriers, such as catalyst deactivation. To avoid these conditions, electrocatalytic hydrogenation (ECH) can be used to stabilize bio-oil via hydrogenation and deoxygenation of reactive components under mild conditions (25–80 ̊C and 1 atm).As lignin is converted to phenolic monomers, dimers, and oligomers upon pyrolysis, the transformation of lignin model compounds exhibiting similar bonding arrangements indicates the potential for lignin valorization using ECH. In this study, conversion, yield, and faradaic efficiency of ECH of model compounds derived from pyrolysis of lignins extracted from pretreated biomass are examined. ECH of these compounds is carried out using an activated carbon cloth supported ruthenium cathode. Having uncovered surprisingly easy aryl ether cleavages, the outcome of this research will provide understanding to further integrate biomass pretreatment, pyrolysis, and electrocatalysis systems for bio-oil stabilization and lignin valorization.
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Title: Functional data analysis with application to traffic flow data
Creator: Zhang, Yi-Chen
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Functional data has become increasingly popular in the recent statistical literature. Considerable attention has been paid to the development of functional data analysis. This thesis consists of four main chapters to address some important questions that arise from implementing FPCA in practice and to give answer to these questions. In Chapter 2, we investigate the problem of data preprocessing for functional data. We propose and analyzes a nonparametric functional data approach to missing...
Show moreFunctional data has become increasingly popular in the recent statistical literature. Considerable attention has been paid to the development of functional data analysis. This thesis consists of four main chapters to address some important questions that arise from implementing FPCA in practice and to give answer to these questions. In Chapter 2, we investigate the problem of data preprocessing for functional data. We propose and analyzes a nonparametric functional data approach to missing value imputation and outlier detection for functional data. In Chapter 3, a functional naive Bayes classifier has been proposed for functional data which provides a surrogate density estimation for functional random variables that makes a direct extension of density-based classical multivariate classification approaches to functional data classification possible. In Chapter 4, we merge two ideas of functional classification and functional prediction to develop a dynamical prediction for functional data. The proposed functional mixture prediction approach combines functional linear model with functional naive Bayes classifier. In Chapter 5, we suggest a two-step segmentation procedure to estimate both the number and locations of the mean change-points of a functional sequence. Finally, the thesis concludes with a brief discussion of future research directions.
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Title: Perceived Discrimination and Psychological Distress : the Moderating and Mediating Effects of Social Context among Asian Americans
Creator: Bista, Shikha
Date: 2018
Collection: Electronic Theses & Dissertations
Description: This study is based on secondary analyses of the National Latino And Asian American Study (NLAAS). Focusing on Asian Americans as an aggregate, and the three largest subgroups represented in the NLAAS (i.e., Chinese, Filipino and Vietnamese Americans), this study investigated the extent to which (a) perceived discrimination predicted psychological distress, (b) social context variables (family cohesion, family conflict, neighborhood cohesion, subjective socioeconomic status) moderated the...
Show moreThis study is based on secondary analyses of the National Latino And Asian American Study (NLAAS). Focusing on Asian Americans as an aggregate, and the three largest subgroups represented in the NLAAS (i.e., Chinese, Filipino and Vietnamese Americans), this study investigated the extent to which (a) perceived discrimination predicted psychological distress, (b) social context variables (family cohesion, family conflict, neighborhood cohesion, subjective socioeconomic status) moderated the relationship between perceived discrimination and psychological distress, and (c) measures of subjective socioeconomic status (SES) mediated the relationship between perceived discrimination and psychological distress. By testing these models separately for Chinese, Filipino, and Vietnamese American groups, results provided a more nuanced assessment of each group’s unique experience. The results indicated that perceived discrimination was significantly related to increased psychological distress in the total Asian American sample, and the three Asian ethnic groups, however, the moderation and mediation model revealed divergent patterns for each Asian ethnic group and for the aggregate sample. Therefore, the results of this study may have implications for understanding within-group variability in the Asian American community.
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Title: Identity management as a goal-oriented response to stigma communication at work : a self-regulation perspective
Creator: Chatterjee, Deepshikha
Date: 2018
Collection: Electronic Theses & Dissertations
Description: In responding to stigma communication at work, people are often under the influence of environmental constraints that may significantly curtail the availability of different identity management strategies. This dissertation highlights that identity management in workplace settings should be seen as a goal-driven and norm-guided response. I present a conceptual model that opens up the black box of why people choose to accept or challenge stigma communication at work by integrating identity...
Show moreIn responding to stigma communication at work, people are often under the influence of environmental constraints that may significantly curtail the availability of different identity management strategies. This dissertation highlights that identity management in workplace settings should be seen as a goal-driven and norm-guided response. I present a conceptual model that opens up the black box of why people choose to accept or challenge stigma communication at work by integrating identity management and stigma literatures with self-regulation literature. Three multi-method studies were crafted. It was found that work environments indeed constrain possible identity management strategies in response to stigma communication. Under the press of self-enhancement goals women were more likely to accept stigma communication, and accepting stigma communication was implicated in higher levels of depletion and strain. Further, women were (a) more likely to choose accepting identity management strategies when stigma was communicated by their supervisors and clients, (b) less likely to challenge when clients communicated stigma, and (c) more likely to use challenge identity management strategies when they had high levels of coping self-efficacy, and also when they were high on promotion focus. Future research questions and practical recommendations are presented to help practitioners harness the value of diversity in organizations.
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Title: Measuring the accessibility of moral intuitions : a validation study of the Moral Foundations-Affect Misattribution Procedure (MF-AMP)
Creator: Prabhu, Sujay
Date: 2018
Collection: Electronic Theses & Dissertations
Description: It is important to study morality given its varied influences on our lives. Haidt and Joseph (2007) have traced morality to its instinctive roots. They have identified five mental systems (moral intuitions) that guide moral judgment: care, fairness, loyalty, authority and purity. This dissertation attempted to create and test an implicit instrument, known as Moral Foundations-Affect Misattribution Procedure (MF-AMP), to gauge the accessibility of these moral intuitions. Three studies were...
Show moreIt is important to study morality given its varied influences on our lives. Haidt and Joseph (2007) have traced morality to its instinctive roots. They have identified five mental systems (moral intuitions) that guide moral judgment: care, fairness, loyalty, authority and purity. This dissertation attempted to create and test an implicit instrument, known as Moral Foundations-Affect Misattribution Procedure (MF-AMP), to gauge the accessibility of these moral intuitions. Three studies were designed in order to validate the MF-AMP as a trait and state measure of moral intuitions. Results show that the MF-AMP can serve as a useful state measure of moral intuitions, and can serve as an accompaniment to the Moral Foundations Questionnaire (Graham et al., 2011) as a trait measure of moral intuitions.
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Title: Testing exposure to nostalgic messages as an alternative self-affirmation induction to reduce defensive processing and promote message acceptance
Creator: Cheng, Ying (College teacher)
Date: 2018
Collection: Electronic Theses & Dissertations
Description: The study developed a communication-based induction of self-affirmation, and examined how it interacted with argument strength to reduce defensiveness and enhance the persuasiveness of a health message. Unlike traditional self-affirmation inductions that are behavior-based and involve instructing people to engage in a cumbersome task, this alternative induction affirms self-concepts through exposure to a personal nostalgic message. In study 1, this alternative induction was as effective as...
Show moreThe study developed a communication-based induction of self-affirmation, and examined how it interacted with argument strength to reduce defensiveness and enhance the persuasiveness of a health message. Unlike traditional self-affirmation inductions that are behavior-based and involve instructing people to engage in a cumbersome task, this alternative induction affirms self-concepts through exposure to a personal nostalgic message. In study 1, this alternative induction was as effective as the traditional method of ranking values and writing an essay to affirm positive attributes. Study 2 tested whether the alternative induction can offer a broader perspective of the self and generate stronger positive other-directed emotions in the same way as traditional self-affirmation methods used by previous research, and whether these psychological outcomes can interact with argument strength to enhance message acceptance via mitigating defensive processing. A 2 (self-affirmation: personal nostalgic message vs. control) × 2 (argument strength: strong vs. weak) between-group online experiment showed that exposure to a personal nostalgic message (vs. control message) produced broader perspectives of the self and greater other-directed emotions. However, the data were inconsistent with the predicted interaction effects. Rather, there were only main effects of argument strength on reducing defensiveness and promoting attitudes and intentions to adopt the message recommendation. Although the alternative induction did not replicate the persuasive outcome of traditional self-affirmation methods observed in previous research, this study served as a beginning to investigate how communication can play a central role in affirming self-concepts to promote acceptance of a persuasive message. The practical implications of developing a message-based self-affirmation for campaign professionals are discussed. -- Abstract.
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Title: Essays in industrial organization
Creator: Kim, Hyunsoo (Economist)
Date: 2018
Collection: Electronic Theses & Dissertations
Description: The first essay "Tying and Platforms’ R&D Incentives in Two-sided markets" analyzes how the tying arrangements can affect platforms’ R&D incentives in two-sided markets under the possibility of multi-homing. The model shows that when all consumers single-home, the tying distorts platforms’ R&D incentives because the tying acts as a commitment device to invest aggressively in R&D, leading to rival firm being foreclosed in the R&D decision stage even if the tying does not have exclusionary...
Show moreThe first essay "Tying and Platforms’ R&D Incentives in Two-sided markets" analyzes how the tying arrangements can affect platforms’ R&D incentives in two-sided markets under the possibility of multi-homing. The model shows that when all consumers single-home, the tying distorts platforms’ R&D incentives because the tying acts as a commitment device to invest aggressively in R&D, leading to rival firm being foreclosed in the R&D decision stage even if the tying does not have exclusionary effect in the price competition. However, when exclusive contents are offered to each platform so that some of the consumers can engage in multi-homing, the tying raises the rival firm’s R&D incentives as well as the tying firm’s R&D incentives. This is because i) tying induces more consumers to multi-home so that total demand of consumers for both platforms can be increased and ii) the strategic effect in R&D competition disappears in the multi-homing case on the consumer side, implying that the rival firm’s R&D incentives is not affected by more aggressive R&D investment of tying firm. Thus, the anti-competitiveness of tying involved with innovation can vary depending on the possibility of consumer’s multi-homing.The second essay "Information Sharing and R&D Incentives" investigates how sharing of cost information affects firms’ incentives to invest in cost reduction and the role of the observability of rivals’ R&D investment level. I study duopoly price competition with cost reducing R&D in three cases: the complete information case, unobservable investment case and observable investment case. The opponents’ cost information is unknown in both the unobservable investment case and the observable investment case, but the investment level is unobservable and observable, respectively. I find that firms have identical incentives of investment in the complete information and the unobservable investment case, whereas they will tend to underinvest in cost reduction when the investment level is observable because a negative strategic effect makes investment less profitable. Due to this underinvestment, welfare and the consumer surplus decrease in the observable investment case. These results have implications for the analysis of information sharing in markets where cost reduction activities are important.The third essay "The Grandfather of Price Discrimination", coauthored with Brady Vaughan and Aleks Yankelevich, examines firms’ motivations for implementing grandfather clauses that allow certain consumers to continue access to a service at a favorable, but no longer available price. We find that when consumers are fully cognizant of their valuations for available product alternatives, firms are typically better off offering all potential consumers the optimal uniform price. However, if grandfathered consumers are made complacent, failing to reevaluate the service over time, grandfather clauses may permit firms to profitably price discriminate between early adopters and new consumers in exchange for forfeiting the right to optimally set prices for early adopters.
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Title: Control function methods in applied econometrics
Creator: Joshi, Riju
Date: 2018
Collection: Electronic Theses & Dissertations
Description: "This dissertation considers estimation and inference in three econometric models containing issues commonly encountered with observational data. Fundamental issues of self-selection, endogeneity, missing observations are pervasive in observational data. Moreover, often, the observations in a dataset are rarely statistically independent and have complex dependence structures. These issues can have a significant effect on the causal effect analysis and pose serious limitations on the popular...
Show more"This dissertation considers estimation and inference in three econometric models containing issues commonly encountered with observational data. Fundamental issues of self-selection, endogeneity, missing observations are pervasive in observational data. Moreover, often, the observations in a dataset are rarely statistically independent and have complex dependence structures. These issues can have a significant effect on the causal effect analysis and pose serious limitations on the popular methodologies that either maintain restrictive assumptions and/or require complicated and computationally tedious solutions.The dissertation aims to apply control function method as the primary tool to design estimation procedures under relaxed distributional and functional form assumptions. I describe computationally simple solutions to these issues to obtain more precise results. These estimation procedures are obtained under relaxed distributional and functional form assumptions allowing a researcher to incorporate more variability (or heterogeneity)."--from abstract.
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