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Title: Market discipline, integrity, information disclosure and financial misconduct
Creator: Li, Qingqiu (Graduate of Michigan State University)
Date: 2018
Collection: Electronic Theses & Dissertations
Description: In my dissertation, I explore the factors which impact the outcome of financial misconduct. Financial misconduct imposes negative externalities on firm value, influences investment decisions, and results in both wealth transfer and destruction. The unique governance structure in the asset management industry amplifies the role of investors on firm behavior. I provide novel evidence on the variation in response towards enforcement actions by investor types; I find evidence consistent with two...
Show moreIn my dissertation, I explore the factors which impact the outcome of financial misconduct. Financial misconduct imposes negative externalities on firm value, influences investment decisions, and results in both wealth transfer and destruction. The unique governance structure in the asset management industry amplifies the role of investors on firm behavior. I provide novel evidence on the variation in response towards enforcement actions by investor types; I find evidence consistent with two non-mutually exclusive explanations for this heterogeneity. First, investor sophistication affects the effective cost of information acquisition and processing, making the fund flow discipline less prevalent for retail investors. Second, investors are less likely to punish funds when the costs of moving capital become substantial. Besides investors, other market participants also significantly affect firm behavior. Internal factors, such as corporate culture, along with external factors, such as product market competition, have significant impact on corporate fraud. For example, a lack of focus on integrity in corporate culture is associated with unethical corporate behavior, cultures that neglect integrity are associated with a greater probability of SEC enforcement actions for accounting misstatements. In addition, firms with lower product market differentiation exhibit significantly lower rates of fraud; the relationship is more pronounced for complex firms and is robust to controlling for various measures of competition, predictors of fraud, and industry heterogeneity. Overall, the findings suggest that lower differentiation disciplines firms by facilitating fraud detection through a benchmarking channel.
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Title: Statistical inference with high-dimensional dependent data
Creator: Santo, Shawn M.
Date: 2018
Collection: Electronic Theses & Dissertations
Description: High-dimensional time dependent data appear in practice when a large number of variables are repeatedly measured for a relatively small number of experimental units. The number of repeated measurements can range from two to hundreds depending on the application. Advances in technology have made the process of gathering and storing data such as these relatively low-cost and efficient. Demand to analyze such complex data arises in genetics, microbiology, neuroscience, finance, and meteorology....
Show moreHigh-dimensional time dependent data appear in practice when a large number of variables are repeatedly measured for a relatively small number of experimental units. The number of repeated measurements can range from two to hundreds depending on the application. Advances in technology have made the process of gathering and storing data such as these relatively low-cost and efficient. Demand to analyze such complex data arises in genetics, microbiology, neuroscience, finance, and meteorology. In this dissertation, we first introduce and investigate a novel solution to a classical problem that involves high-dimensional time dependent data. In addition, we propose a new approach to analyze high-dimensional dependent genomics data.First, we consider detecting and identifying change points among covariance matrices of high-dimensional longitudinal data and high-dimensional functional data. The proposed methods are applicable under general temporospatial dependence. A new test statistic is introduced for change point detection, and its asymptotic distribution is established under two different asymptotic settings. If a change point is detected, an estimate for the location is provided. We investigate the rate of convergence for the change point estimator and study how it is impacted by dimensionality and temporospatial dependence in each asymptotic framework. Binary segmentation is applied to estimate the locations of possibly multiple change points, and the corresponding estimator is shown to be consistent under mild conditions for each asymptotic setting. Simulation studies demonstrate the empirical size and power of the proposed test and accuracy of the change point estimator. We apply our procedures on a time-course microarray data set and a task-based fMRI data set. In the second part of this dissertation we consider a hierarchical high-dimensional dependent model in the context of genomics. Our model analyzes RNA sequencing data to identify polymorphisms with allele-specific expression that are correlated with phenotypic variation. Through simulation, we demonstrate that our model can consistently select significant predictors among a large number of possible predictors. We apply our model to an RNA sequencing and phenotypic data set derived from a sounder of swine.
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Title: Quantifying groundwater recharge dynamics using a process-based distributed hydrologic model
Creator: Kang, Guoting
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Groundwater--the lifeblood of groundwater-dependent ecosystems and societies--is facing unprecedented threats from over-extraction, contamination, and changing climate. Groundwater recharge provides a sustainable source of water for aquifers and plays an important role in both surface and sub-surface domains. Understanding and accurately estimating the rate, location, and timing of major recharge events and their seasonal and inter-annual variability is key to safely matching societal needs...
Show moreGroundwater--the lifeblood of groundwater-dependent ecosystems and societies--is facing unprecedented threats from over-extraction, contamination, and changing climate. Groundwater recharge provides a sustainable source of water for aquifers and plays an important role in both surface and sub-surface domains. Understanding and accurately estimating the rate, location, and timing of major recharge events and their seasonal and inter-annual variability is key to safely matching societal needs of water and to maintaining healthy groundwater-dependent ecosystems. This work attempts to understand and quantify recharge dynamics in an agricultural watershed in the Ottawa County, Michigan using field observations of baseflows, groundwater heads, satellite-based evapotranspiration (ET) products and an integrated, process-based hydrologic model. Specific objectives of the work are to: (1) understand the spatial and temporal distribution of high- and low-recharge events and (2) assess the relative impacts of climate, land use, soils, and topography on the spatiotemporal distribution of recharge within the region. County-wide synoptic and time-series baseflow data collected from over 40 small streams between July and November of 2015 were used to quantify the uncertainties in recharge estimation. Precipitation data represent important inputs to hydrologic models and have a major influence on model performance and the estimated recharge. Compared to data from a typical network of rain gauges, the Next-Generation Weather Radar (NEXRAD) provides precipitation data at a much higher spatial resolution. NEXRAD data were blended with traditional rain gauge data to estimate recharge and to evaluate differences relative to recharge estimated using rain gauge data alone. Results indicate that caution should be exercised in using NEXRAD precipitation data for recharge estimation. The representation of recharge and its variability within a numerical model are closely related to the representation of meteorological forcing fields and their spatial structure, land use and land cover, the hydraulic properties of underlying soils and aquifers as well as topography--all of which are represented to varying degrees of accuracy depending on the mesh resolution employed and the algorithms used to represent sub grid-scale processes. To understand the effects of grid resolution on recharge and to identify optimal resolution relative to the size of the watershed, models were setup with different grid resolutions. Recharge patterns follow precipitation patterns more closely at coarse grid sizes since the characteristics of LULC, terrain and hydraulic properties are smoothed at this resolution. Insights gained from the study are expected to aid in the sustainable management of natural resources, particularly groundwater-dependent ecosystems.
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Title: Environmental assessment of transparent photovoltaics
Creator: Lee, Eunsang
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Transparent organic photovoltaics (TPV) can harvest energy from the near-infrared (NIR) and ultraviolet region of the solar spectrum and could be used in new applications such as windows. In addition to producing electricity, the transparent organic solar cell absorbs in the NIR region and could reduce the cooling energy demand of buildings during summer. Organic photovoltaic (OPV) is an emerging technology, developed mostly to replace fossil fuel energy, aimed to reduce greenhouse gases...
Show moreTransparent organic photovoltaics (TPV) can harvest energy from the near-infrared (NIR) and ultraviolet region of the solar spectrum and could be used in new applications such as windows. In addition to producing electricity, the transparent organic solar cell absorbs in the NIR region and could reduce the cooling energy demand of buildings during summer. Organic photovoltaic (OPV) is an emerging technology, developed mostly to replace fossil fuel energy, aimed to reduce greenhouse gases emissions. As OPV technology is reaching commercialization, it is essential to quantify its environmental impacts and ensure that new issues are not created. Life cycle assessment (LCA) is often used to compare energy technologies and identify environmental concerns, but this process is challenging for emerging technologies due to lack of inventory data. To guide future transparent OPV development, this work (1) demonstrates a new iterative methodology to evaluate and guide OPV material manufacturing that combines LCA and green chemistry approaches, (2) evaluates the energy saving from organic TPV in window and skylight applications in various cities, and (3) assesses the impact of organic TPV on urban heat island effect.The methodology was used to identify “hotspots,” which correspond to the processes that have the highest impact for chloroaluminum phthalocyanine (ClAlPc) manufacturing. An optimized process that reduces the environmental impact by 3%, the cost by 9% and chemicals hazard by 23% compared to the current process was demonstrated. The impact of TPV during the use phase was studied using ClAlPc based devices in window application. The building energy performance was shown to improve by up to 20 % due to heating and cooling energy saving. The energy saving varies with climate since NIR absorption by TPV in a window is more efficient in a warmer climate. The use of TPV in the window application in an urban area could further reduce the energy demand of buildings. The net energy saving by the TPV application in the urban area was calculated to be higher than in rural area by up to 2 GJ per month.
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Title: Viruses in water and wastewater and their significance to public health
Creator: O'Brien, Evan Patrick
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Viruses are responsible for millions of disease cases and deaths each year worldwide. Water-related viruses are of particular concern to environmental engineers, especially with regards to wastewater. Wastewater can be a valuable tool in the investigation of viral disease. This dissertation seeks to study the presence, quantification, and diversity of viruses in wastewater in the application of various methodologies for the protection of human, animal, and environmental health.

Title: Sweet nanomedicine in vivo : glyconanoparticle for imaging amyloid beta fibrils in Alzheimer's disease, and hyaluronan nanoparticles for imaging and therapy of inflammatory Atherosclerosis disease
Creator: Hossaini Nasr, Seyedmehdi
Date: 2018
Collection: Electronic Theses & Dissertations
Description: This dissertation is about design and synthesis of glyconanoparticles for certain in vivo applications including imaging amyloid beta fibrils in Alzheimer’s disease, imaging inflammatory atherosclerotic plaques and inhibition of atherosclerotic plaque inflammation. Amyloid beta (Aβ) accumulation and deposition in the brain tissue are one of the most important hallmarks of Alzheimer’s disease (AD). Therefore, Aβ is an attractive target for imaging AD, however, designing a nanoprobe with the...
Show moreThis dissertation is about design and synthesis of glyconanoparticles for certain in vivo applications including imaging amyloid beta fibrils in Alzheimer’s disease, imaging inflammatory atherosclerotic plaques and inhibition of atherosclerotic plaque inflammation. Amyloid beta (Aβ) accumulation and deposition in the brain tissue are one of the most important hallmarks of Alzheimer’s disease (AD). Therefore, Aβ is an attractive target for imaging AD, however, designing a nanoprobe with the ability to pass through the blood brain barrier (BBB) and reaching Aβ plaques is a significant challenge. The first part of this dissertation covers the synthesis of a glyconanoparticle enabling to pass the BBB and bind with Aβ fibrils. Briefly, synthesis, characterization and application of this glyconanoparticle for magnetic resonance imaging (MRI) of Aβ plaques in a mouse model of AD (B6C3) have been presented. Majority of patients that experience cardiac arrests have atherosclerosis, which is the inflammatory disease of arterial walls and the major cause of heart attacks and strokes. Imaging techniques that can enable detection of atherosclerotic plaques before clinical manifestation are urgently needed. CD44 is a cell surface protein overexpressed in the plaque tissues and its expression level is associated with the risk of plaque rupture. The second chapter explains atherosclerosis disease and nanomedicine for targeting inflammatory atherosclerotic plaques. The third chapter of this dissertation presents the development of hyaluronan (HA) coated iron oxide nanoparticles for active targeting of the plaques. These nanoprobes can not only bind with atherosclerotic plaques through their HA ligands but also function as T2 based MRI contrast agents for plaque diagnosis. Moreover, the effect of nanoprobe morphology on inflammation has been studied indicating that engineering nanoprobe shape could decrease inflammatory responses, which makes it a superior candidate for imaging inflammatory atherosclerotic plaques. Concisely, design and synthesis of HA conjugated nanoworm (HA-NW) have been explained. Then, inflammatory responses to HA conjugated nanoparticles in vitro and in vivo in apoE knockout mouse model have been presented. Finally, the ability of HA-NW for in vivo imaging of atherosclerotic plaques by MRI has been studied.The last part of this dissertation goes over design and synthesis of hyaluronan conjugated atorvastatin nanoparticle (HA-ATV NP). This therapeutic formulation has been designed to deliver ATV to the inflammatory atherosclerotic plaques to reduce plaque inflammation. Then, HA-ATV NP anti-inflammatory effects in vitro and its therapeutic effect in vivo in apoE knockout mouse model have been explained. It has been shown that intravenous administration of this formulation (high dose, 8.5 mg ATV/ kg), every other day for one week can significantly reduce the plaques inflammation.
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Title: MANAGEMENT AND CHARACTERIZATION OF ALTERNARIA SPP. AND SEEDBORNE PATHOGENS ASSOCIATED WITH AMERICAN GINSENG (PANAX QUINQUEFOLIUS) GARDENS IN WISCONSIN
Creator: Neils, Amber L.
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Leaf blight, caused by Alternaria panax, is a yearly challenge for those who cultivate ginseng, requiring frequent fungicide applications to protect valuable yield. In this study, the incidence and pathogenicity of Alternaria spp. on American ginseng in Wisconsin and effective leaf blight-controlling strategies were assessed. Five hundred and ninety-two isolates of Alternaria spp. were obtained from leaves (491), drupes (88) and seeds (10) of ginseng between 2011 and 2015. Resistance to...
Show moreLeaf blight, caused by Alternaria panax, is a yearly challenge for those who cultivate ginseng, requiring frequent fungicide applications to protect valuable yield. In this study, the incidence and pathogenicity of Alternaria spp. on American ginseng in Wisconsin and effective leaf blight-controlling strategies were assessed. Five hundred and ninety-two isolates of Alternaria spp. were obtained from leaves (491), drupes (88) and seeds (10) of ginseng between 2011 and 2015. Resistance to azoxystrobin was determined using an amended agar plate assay and a molecular assay that detected a common mutation responsible for strobilurin resistance in fungi. The majority (74.5%) of the isolates were identified as small-spored Alternaria spp. and their pathogenicity was confirmed using a detached leaf assay. Wounding increased the occurrence of infection by small-spored Alternaria spp. although infection occasionally (<6%) occurred without wounding. Alternaria panax was consistently pathogenic; lesion area resulting from A. panax and small-spored Alternaria spp. infection ranged from 4.34 to 28.88 mm2 and from 0.04 to 27.72 mm2, respectively. Results from the plate assay show 65.2% of A. panax isolates and 82.6% of small-spored Alternaria spp. isolates were classified as resistant to azoxystrobin at an EC50 of greater than 4.00. Leaf blight-control strategy field trials were conducted in commercial ginseng gardens over two years. One trial compared fourteen fungicides (boscalid, chlorothalonil, cyprodinil+fludioxonil, famoxadone+cymoxanil, penthiopyrad, fluazinam, pyraclostrobin, difenoconazole+azoxystrobin, pyrimethanil, fluxapyroxad+pyraclostrobin, difenoconazole, extract of giant knotweed, mancozeb, and azoxystrobin) and a non-treated control. In a second trial, a disease forecaster program, TOM-CAST, with spray thresholds of 10 or 15 disease severity values (DSVs) was tested. Penthiopyrad, difenoconazole, fluazinam, difenoconazole+azoxystrobin and pyraclostrobin limited disease incidence compared to the control (P < 0.05). Applications of pyraclostrobin and mancozeb resulted in a higher seedhead yield than the control, the highest number of healthy drupes and the lowest number of diseased drupes (P < 0.05). In the forecasting trial, the disease severity rating of TOM-CAST 10 DSV plots was similar to those treated every 10 days, but higher than for plots treated every 7 days. The TOM-CAST 15 DSV plots were severely diseased. Yields were similar among plots treated every 7 days and according to TOM-CAST 10 DSV.The establishment costs of a ginseng planting are high and seed health is an important consideration. Because of this, fungal presence on drupes, green seed coats, and endosperms was surveyed using a plate assay. A field trial to assess seed treatments in commercial ginseng gardens included stratified seed treated with the fungicides penthiopyrad, oxathiapiprolin, fluopicolide, ethaboxam, captan, mefenoxam + fludioxonil, or azoxystrobin. Alternaria spp. were commonly isolated from drupes and green seed coat and Fusarium spp. were recovered from all seed parts, including the endosperm. Cylindrocarpon destructans was only recovered in low numbers on green seed coats. Although none of the treatments significantly increased final plant stand compared to the control, oxathiapiprolin and azoxystrobin resulted in the highest plant stands throughout the season in year one (P < 0.05). In year two the control and fluopicolide resulted in the highest final plant stands (P < 0.05).
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Title: News organizations' news link sharing strategies on Twitter : economic theory and computational text analysis
Creator: Pak, Chankyung
Date: 2018
Collection: Electronic Theses & Dissertations
Description: This dissertation explores news organizations' social media strategies to disseminate their news stories as emergent quasi-editorial decisions. As in traditional editorial decisions, how news organizations share their news links on social media determines the visibility of certain stories and makes certain aspects of news stand out or be unobtrusive. By illustrating how these practices on Twitter resemble and deviate from traditional ones, I argue that social media open up a new path by which...
Show moreThis dissertation explores news organizations' social media strategies to disseminate their news stories as emergent quasi-editorial decisions. As in traditional editorial decisions, how news organizations share their news links on social media determines the visibility of certain stories and makes certain aspects of news stand out or be unobtrusive. By illustrating how these practices on Twitter resemble and deviate from traditional ones, I argue that social media open up a new path by which news organizations mediate news information, relatively free from journalistic norms and routines embedded in the older media and traditional editorial processes.To answer a fundamental question, ?Is there a reason for a news organization to be strategic on social media?? I presented an economic model based on competition for limited attention of social media users. In this model, the scarcity of users' attention capacity relative to the volume of information propagated via social media creates competition between news\ organizations. The model illustrates that one news organization's attempt to capture users' attention undermines the chance for other organizations to do so. Thus, a news organization should strategically decide how many news links it is going to share considering how many others would share. A simple empirical test confirms the model's prediction that news organizations will reduce the proportion of news links they share on social media as more news is published by all organizations. Computational text analyses shed light on the more qualitative aspects of news dissemination strategies on social media. First, using a recently developed machine learning technique, Structural Topic Model (STM), I investigate news organizations' selective news link sharing as a new layer of gatekeeping. The result indicates that the common concern that commercialized media drives news toward human interest rather than newsworthiness is crystallized more visibly on Twitter than on news websites. Further, a comparison of the selective link sharing across different media types shows that topic selection differs depending on a given topic's popularity on Twitter and a news organization's specialty in the topic. Even though a news organization may consider a certain topic to be important in its editorial decision, so that the organization has become specialized in that topic throughout its history, it would not share much about the topic on Twitter because popularity in the short term dominates link sharing strategies.I found that regional media convey less negative sentiment through news stories than other types of news organizations. This seems to be associated with the less controversial news topics they frequently cover compared to national and online media. However, news paraphrasing for Twitter homogenizes emotional framing across different types of organizations. In particular, regional media catch up to other types by adding even more negativity on news paraphrases for Twitter. This finding provides another significant indication that social media strategies are governed by different logic than that which governs traditional editorial practices. Major empirical findings provide evidence that the social media strategies of news organizations are already functioning as a separate information-mediating process. I argue that the distinctiveness of social media strategies as quasi-editorial decisions raises a practical need to publicly monitor news organizations' behaviors on social media to learn whether they will provide news that is informative and diverse enough for news readers' informed decisions. The automated data collection schemes and computational text analysis techniques I adopted in this dissertation will inform the design of infrastructure for such public monitoring.
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Title: Promoting prospective teachers' enactment and appropriation of new instructional strategies in their field placements
Creator: Hinojosa, Denisse M.
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "Prospective teachers experience the complexity of teaching from the moment they start their field placement. Experiencing this complexity without adequate professional guidance could prevent prospective teachers from enacting in practice what is learned in teacher preparation programs. In this dissertation, I explore the ways in which I used onsite coaching moves such as modeling and dialogic feedback in my work coaching two elementary interns throughout their participation in a professional...
Show more"Prospective teachers experience the complexity of teaching from the moment they start their field placement. Experiencing this complexity without adequate professional guidance could prevent prospective teachers from enacting in practice what is learned in teacher preparation programs. In this dissertation, I explore the ways in which I used onsite coaching moves such as modeling and dialogic feedback in my work coaching two elementary interns throughout their participation in a professional development program to appropriate instructional strategies for differentiating instruction in general education classrooms. I seek to understand interns' responses to these coaching moves and implications on the development of interns' teaching practice. In Chapter One, I explore the IDEAL framework which helped me understand how the onsite coaching cycle. In Chapter Two, I explore the types of feedback provided on lesson plans and planning sessions to support teacher learning. In Chapter Three, I explore onsite modeling and dialogic feedback to scaffold prospective teachers' enactment of new instructional strategies. In Chapter Four, I share an approach to onsite coaching that has implications for field supervision to support prospective teachers' enactment and appropriation of new instructional strategies in their field placements. All chapters are related to exploring prospective teachers' enactment and appropriation of new instructional strategies in the context of developing their teaching practice."--Page ii.
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Title: LMX comparisons between peers : a relational approach to studying LMX differences and interpersonal behaviors
Creator: Yu, Andrew
Date: 2019
Collection: Electronic Theses & Dissertations
Description: "To date, a disproportionate amount of research examining the importance of leader-member work relationships has focused on the outcomes for individual employees. However, there has been criticism regarding the myopic focus on the leader-member dyad and failing to consider the broader implications on system of social relationships each LMX relationships is embedded within. This has led to an emerging literature focused on understanding the effects of differences in LMX relationships. In this...
Show more"To date, a disproportionate amount of research examining the importance of leader-member work relationships has focused on the outcomes for individual employees. However, there has been criticism regarding the myopic focus on the leader-member dyad and failing to consider the broader implications on system of social relationships each LMX relationships is embedded within. This has led to an emerging literature focused on understanding the effects of differences in LMX relationships. In this dissertation, I leverage power-approach theory to integrate psychological research on power with extant research on LMX and differences in LMX relationships. Specifically, I argue that that perceived differences in a focal employee's LMX quality to that of a referent coworker will influence his or her sense of psychological power. The extent that the focal employee and referent coworker are task interdependence will moderate this relationship. Subsequently, the effects of LMX differences will influence discretionary interpersonal work behaviors (mediated through psychological power). However, the form of discretionary behavior (i.e., citizenship vs. counterproductive) will be contingent upon the individual characteristics of the focal employee."--Page ii.
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Title: Homeostatic responses of the enteric cholinergic system in stress and enteritis
Creator: Pohl, Calvin Seneca
Date: 2018
Collection: Electronic Theses & Dissertations
Description: Stressful, traumatic events are a well-recognized trigger leading to acute and chronic gastrointestinal (GI) disease like Irritable Bowel Syndrome (IBS) or Inflammatory Bowel Disease (IBD). Two major types of stress which are pervasive within the world population are early life adversity and depression, both of which are strongly associated with GI disease throughout life. Though much of the underlying pathology in IBS and IBD has been described, the underlying mechanisms explain how stress...
Show moreStressful, traumatic events are a well-recognized trigger leading to acute and chronic gastrointestinal (GI) disease like Irritable Bowel Syndrome (IBS) or Inflammatory Bowel Disease (IBD). Two major types of stress which are pervasive within the world population are early life adversity and depression, both of which are strongly associated with GI disease throughout life. Though much of the underlying pathology in IBS and IBD has been described, the underlying mechanisms explain how stress may trigger onset or increased symptom severity in these chronic disease is poorly understood. The enteric cholinergic nervous system is a major regulator of GI homeostasis with broad regulatory roles over epithelial barrier permeability, epithelial cell secretion, smooth muscle contraction and motility, and immune activation. Though a role of the enteric nervous system has been describe in acute stress induced GI dysfunction, little is known about the role of this system in chronic stress, early life adversity, or in infectious models. The objective of this dissertation was to determine if the enteric cholinergic nervous system contributed to GI disease under different types of environmental challenges including early life adversity, chronic stress and pathogen challenge. To answer these questions, we utilized several different small and large animal models in combination with pharmacological agonists and antagonist of the cholinergic system. The results presented here demonstrate that different types of stressors differentially impact the enteric cholinergic system. Following early life adversity, we observed a persistent upregulation of the enteric cholinergic system, which predisposes individuals to increased intestinal secretion, permeability, motility, and upregulation of stress related genes. In a pathogen challenge model, we observed an upregulation of a non-neuronal component of the enteric cholinergic system which correlated positively with disease severity. Finally we observed that chronic stress in adulthood results in a strong down regulation of the enteric cholinergic nervous system with reduced cholinergic mediated functional secretion. Combined these findings demonstrated that different modes of stress have dichotomous impacts the enteric cholinergic system, which differentially impact GI function. Future work should focus on the precise factors impacting the function and expression of the cholinergic system in order to develop better therapies to cope with stress induced GI disease.
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Title: An analysis of the restaurant landscape in the Detroit Metropolitan Area : travel behavior and spatial patterns of difference
Creator: Eckert, Jeanette Elizabeth
Date: 2018
Collection: Electronic Theses & Dissertations
Description: This dissertation examines the spatial pattern and density of fast food restaurants in the Detroit region, and uses the results of a travel survey to analyze what types of restaurants respondents travel to in an average week. These travel characteristics are explored relative to urban form and sociodemographics of the respondents. A primary contribution to the literature is the use of reported restaurant travel trips, as opposed to making assumptions based solely on proximity or density of...
Show moreThis dissertation examines the spatial pattern and density of fast food restaurants in the Detroit region, and uses the results of a travel survey to analyze what types of restaurants respondents travel to in an average week. These travel characteristics are explored relative to urban form and sociodemographics of the respondents. A primary contribution to the literature is the use of reported restaurant travel trips, as opposed to making assumptions based solely on proximity or density of nearby restaurants. The study area is the Detroit region, characterized by a wide range of socioeconomics, demographics, and urban forms in a relatively small geographic area. The study sites selected represent high- and low-density neighborhoods as well as areas of affluence and extreme poverty. The neighborhood study sites include two high-density, low-income neighborhoods in Detroit; two high-density, higher-income neighborhoods in Ann Arbor and Birmingham; and two low-density, high-income neighborhoods in Bloomfield Hills and West Bloomfield, for a total of six neighborhoods. Using data on the locations of licensed restaurants in the study region at the time of the survey (2007-08), fast food density was calculated in multiple ways, including per capita, per square mile, and per road mile. The results show that residents of the City of Detroit have a slightly higher exposure to fast food than suburban counterparts. More notable is that of all restaurants in a municipality, Detroit has a higher proportion that is fast food (22%), compared to 15% in the low-density suburbs and 13% in the high-density suburbs. Using 997 completed travel surveys, the analysis reveals stark differences in the types of restaurants visited by Detroit respondents compared to suburban respondents. The majority of all restaurant trips (77%) for Detroit respondents are to fast food establishments, compared to 22% in the low-density suburbs and 17% in the high-density suburbs. More than half (52%) of Detroit respondents report traveling to a fast food restaurant in an average week, compared to 16% in both the low-density and high-density suburbs. Thus, Detroiters are dining out to fast food about three times as often as their suburban counterparts, despite having only a slightly higher density and proportion of fast food restaurants. Additionally, higher-income respondents travel farther on average to dine out, and are less likely to travel to fast food. While there is little difference in characteristics relating to a likelihood to dine out to restaurants in general, there are significant differences when examining trips to fast food restaurants. One or more trips to fast food in an average week is related to a higher body mass index, fewer servings of vegetables, more servings of soft drinks, less vigorous exercise, and cigarette smoking. The connected street grid design, density, and mixed-use zoning that is often associated with good urban design, walkability, and better health outcomes can be found in the high-density study neighborhoods of urban Detroit and the suburbs of Ann Arbor and Birmingham. Yet despite similar urban form, the suburban communities are reporting a much lower prevalence of obesity, higher likelihood to engage in exercise, more ideal nutritional choices than Detroit. Further examination into these complex relationships is warranted in order to help alleviate the public health disparities we see around obesity and diet-related diseases.
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Title: Politics of epistemic dependence : an epistemological approach to gender-based asylum
Creator: Sertler, Ezgi
Date: 2018
Collection: Electronic Theses & Dissertations
Description: "My dissertation aims to build a bridge between analytic social epistemologies, feminist epistemologies, and refugee studies by bringing them into conversation on gender-based asylum cases, i.e. cases where gender-related persecution is the primary consideration for the determination of refugee status. It does so by using the concept of "epistemic dependence," which refers to our social mechanisms of reliance in the process of knowing, i.e. what we rely on and how we rely on it. In this...
Show more"My dissertation aims to build a bridge between analytic social epistemologies, feminist epistemologies, and refugee studies by bringing them into conversation on gender-based asylum cases, i.e. cases where gender-related persecution is the primary consideration for the determination of refugee status. It does so by using the concept of "epistemic dependence," which refers to our social mechanisms of reliance in the process of knowing, i.e. what we rely on and how we rely on it. In this dissertation, I argue that tracking problematic operations of epistemic dependence can provide an illuminating framework for understanding the epistemological impacts of the social and political structures that govern asylum claims." -- Abstract.
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Title: Modeling parasitic weed emergence across smallholder farming systems : the case of central Malawi
Creator: Silberg, Timothy Robert
Date: 2019
Collection: Electronic Theses & Dissertations
Description: Four out of five households in Malawi rely on farming as a primary source of income, most of whom cultivate maize (Zea mays). Disconcertingly, 63-80% of maize yield losses among these households are attributed to the emergence of invasive and parasitic weeds such as Striga (Striga spp.). A plethora of Striga-control practices (SCPs) have been developed and disseminated to smallholder farmers (cultivating < 2 ha). These SCPs are commonly evaluated at agricultural research stations prior to...
Show moreFour out of five households in Malawi rely on farming as a primary source of income, most of whom cultivate maize (Zea mays). Disconcertingly, 63-80% of maize yield losses among these households are attributed to the emergence of invasive and parasitic weeds such as Striga (Striga spp.). A plethora of Striga-control practices (SCPs) have been developed and disseminated to smallholder farmers (cultivating < 2 ha). These SCPs are commonly evaluated at agricultural research stations prior to dissemination. Mixed results often arise later when they are implemented across the diverse agroecological and socioeconomic landscapes of smallholders. Many agree research will need to assess how SCPs perform under smallholder-conditions, and ultimately, how their uptake will affect emergence. The following dissertation is divided into three empirical studies. In the first essay, discrete choice experiments (DCEs) are used to estimate the percent of maize yield farmers are willing to sacrifice for different SCP attributes (e.g., labor, soil fertility). In the second essay, a seed bank stock and flow model (SB-SFM) is developed to assess emergence rates across different SCPs. In the final essay, results from the DCEs and SB-SFM are integrated within a system dynamics model (SDM) to simulate how environmental and socioeconomic parameters affect emergence across space and time. DCE findings highlight farmers are willing to sacrifice significant tradeoffs to implement SCPs that increase soil fertility and provide legumes. SB-SFM findings indicate the attachment phase and seed bank must simultaneously be addressed with multiple SCPs to suppress emergence over three to five years. Finally, alteration of different climate, farm-management and adoption parameters in the SDM underline that nutrient input subsidies and agricultural extension must be included in an aggregated effort to suppress the spread of Striga across the region.
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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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