bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of a method for in vivo mechanical characterization of articular cartilage
Authors:   , Rexwinkle Joe
Published: April 2021

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Arthritis is one of the leading causes of disability in the United States and the second most expensive to treat according to the CDC. One of the key difficulties in diagnosing and treating arthritis, in particular osteoarthritis, is that the mechanisms for progression of the disease are poorly characterized. Mechanical engineer Joe Rexwinkle, working with Dr. Ferris Pfeiffer and the Thompson Lab for Regenerative Orthopaedics, aimed to shed some light on the links between cartilage biology and the degradation seen in osteoarthritis. The study began with obtaining cartilage samples from six patients undergoing total knee replacements and collecting information on several biomarkers with known relevance to osteoarthritis. Specifically, the concentrations of several proteins which may be determined in a standard hospital lab were analyzed. The samples were then tested to determine their mechanical properties, since the progression of osteoarthritis is always accompanied by the physical degradation of the tissue. Machine learning techniques, which are gaining increasing popularity in the field of orthopaedic research, were then used to model the relationships between these biomarkers and the mechanical state of the tissue. These models were found to be highly accurate in characterizing the mechanical state of the tissue, even when limited only to the protein concentrations that one could find in a standard hospital lab. This study has not yet produced a tool which may be used in a hospital setting, considering the low number of patients included in this study, but it does reveal promising early results in using machine learning to characterize osteoarthritis, a task which has thus far eluded the orthopaedic research community.
Views of women with dissociative identity disorder on intimate partner violence : a grounded theory approach
Authors:   , Snyder Briana
Published: April 2021

Abuse and neglect are global phenomena with devastating personal, familial, and societal effects. When occurring in childhood, maltreatment increases the risk for additional abuse experiences across the lifespan. This purpose of this review is to summarize and analyze current research about the relationship between the experience of child maltreatment (CM) and intimate partner violence (IPV) in adulthood. The majority of literature supports that CM increases the risk for IPV, and the link appears to be stronger in specific populations, including female veterans, teens, sexual minorities, and individuals with mental illness. Nurse-midwives are uniquely poised to prevent and address this maltreatment, due to the intimate nature of the care they provide to clients and their families, but continue to encounter barriers in practice. Nurse-midwives need additional resources and training related to abuse, and they must take an active role in assessing, treating, providing resources, and making appropriate referrals to interprofessional colleagues. Keywords: child abuse, child maltreatment, intimate partner violence, domestic violence, spousal abuse
Striatal functional activation and psychosis risk
Authors:   , Karcher Nicole
Published: April 2021

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The striatum is involved in learning from feedback. Psychosis is strongly related to increased striatal dopamine. The goal of the current research is to examine whether psychosis risk is associated with neural evidence consistent with increased striatal dopamine. If psychosis risk is associated with increased striatal dopamine, then it is expected that psychosis risk would be associated with decreased striatal activation on a task involving learning from both positive and negative feedback, a probabilistic category learning task (PCLT; i.e. the Weather Prediction Task). Further, it is also expected that psychosis risk would be associated with increased striatal activation for unexpected reward but decreased striatal activation for unexpected punishment on a task that allows for separate assessment of reward and punishment feedback, a reversal learning task (RLT). In the current study, there were two groups of college student participants: (a) psychosis risk (n = 21) who had both extreme levels of self-reported psychotic-like beliefs and experiences as well as at least moderate levels of interview-rated current attenuated psychotic symptoms (APS); and (b) controls (n = 20) who had average levels of self-reported psychotic-like beliefs and experiences. Participants completed both the PCLT and RLT during fMRI scanning. As expected there was decreased striatal activation on the PCLT in psychosis risk. Further, as expected, on the RLT, for unexpected reward psychosis risk was associated with increased striatal activation, but for unexpected punishment psychosis risk was associated with decreased striatal activation. The current results suggest that psychosis risk is associated with a pattern of neural dysfunction that is consistent with increased striatal dopamine in psychosis risk.
Versinia pestis YopJ, YopT, and YopK coordinate programmed cell death and cytokine responses to promote pneumonic plague
Authors:   , Olson Rachel M.
Published: April 2021

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Yersinia pestis has been responsible for three major pandemics of plague, including the infamous Black Death that killed 250 million people in Europe. The disease progresses rapidly due to a combination of bacterial growth and host immunopathology. During infection, Y. pestis utilizes a type III secretion system (T3SS), which is essential for virulence, to inject effector proteins that disrupt immune cell function. The majority of the Yops are dedicated to the control of programmed cell death of immune cells, namely macrophages and neutrophils, and through this, it has been proposed that initially there is immune suppression followed by an acute inflammatory response that accelerates bacterial growth and disease. Recent work has focused on the inflammasome, cellular machinery that is activated upon insertion of the translocation pore that results in host cell lysis and the release of inflammatory cytokines. In this work, we defined a novel pathogenesis mechanism involving the activation of rapid lysis of inflammatory macrophages via necroptosis by injected bacterial effectors YopT and YopJ, each with cysteine protease activity. We show that YopT is a virulence factor for plague, while deletion of YopJ had no detectable impact on virulence. Further, we found that injection of catalytically inactive YopJ induces strong activation of the inflammasome and stimulates host defense against plague. YopK modulates the effects of YopT and YopJ. Overall, it appears that induction of necroptosis by YopT and YopJ subverts the activation of the inflammasome and contributes to pathogenesis of plague.
Large-amplitude solitary water waves with discontinuous vorticity
Authors:   , Akers Adelaide
Published: April 2021

Consider a two-dimensional body of water with constant density which lies below a vacuum. The ocean bed is assumed to be impenetrable, while the boundary which separates the uid and the vacuum is assumed to be a free boundary. Under the assumption that the vorticity is only bounded and measurable, we prove that for any upstream velocity field, there exists a continuous curve of large-amplitude solitary wave solutions. This is achieved via a local and global bifurcation construction of weak solutions to the elliptic equations which constitute the steady water wave problem. We also show that such solutions possess a number of qualitative features; most significantly that each solitary wave is a symmetric, monotone wave of elevation.
Discovering disease causing variants in dogs through whole genome sequencing
Authors:   , Kolicheski Ana Leticia
Published: April 2021

This dissertation focuses on the use of whole genome sequencing (WGS) for the identification of disease causing variants in canine genomes. A brief review on the historical milestones of genetics, the creation and popularization of the fast throughput DNA sequencing technologies and their advantages and potential problems and biases, the importance of the study of canine genetics and the current state of the canine genome assembly is presented. Our lab sequenced [about]100 dogs in the attempt to discover disease-causing variants. So far 20 such variants have been identified. This dissertation contains detailed accounts of the discovery variants likely to be responsible for four canine diseases. Those diseases are: Paroxysmal dyskinesia in Soft Coated Wheaten Terriers that is associated to the missense mutation PIGN:c.398C greater than T; two different forms of neuronal ceroid lipofuscinosis, one in Australian Cattle dogs caused by CLN5:c.619C greater than T, and one in the Cane Corso caused by the splice site mutation PPT1c.124+1 [greater than] A; and a Shiba Inu GM2 gangliosidosis caused by HEXB.c:948_950delCCT. Furthermore, examples of not so successful attempts, possible reasons for failures and suggestions to successfully conclude other ongoing investigations.
Population level genetic differentiation among temperate Neoconocephalus katydids
Authors:   , Ney Gideon
Published: April 2021

Recent work indicates that radiation events may play a significant role in shaping species diversity across entire continents. Here we quantify population level genetic differentiation in several species of Neoconocephalus katydids in order to determine the mechanisms of genetic isolation across a continental scale. Patterns of genetic isolation can be generalized into four types: isolation by resistance (IBR), isolation by barrier (IBB), isolation by distance (IBD), and epigenetic incompatibility. N. melanorhinus is a salt marsh specialist restricted to a narrow corridor along the Atlantic and Gulf coasts. IBD was the predominant pattern of variation across their range. In addition, we saw evidence of two possible biogeographic barriers to gene flow (IBB), one at the Atlantic-Gulf divide and the other along the Gulf coast. We investigated the impact of IBR by comparing genetic differentiation between a habitat specialist, N. bivocatus, and a habitat generalist, N. robustus. Similar levels of genetic diversity and genetic differentiation were present within populations of both species. Genetic variation and epigenetic changes can diverge between populations in isolation. We found significant variation in total methylation levels between N. bivocatus and N. robustus. Genetic differentiation did a better job of explaining species-specific phenotypes than epigenetic differentiation. Epigenetic differentiation, although present between species, is likely the result of an interaction between genetic and epigenetic loci.
Maize nodal root growth under water deficits
Authors:   , Riggs Kara J.
Published: April 2021

The nodal root system is critical for the development of the mature root system in maize (Zea mays L.) and other grasses. Under drought conditions, nodal root axes may need to grow through surface soil that is dry, hard, and hot. These roots are known to have a superior ability to continue elongation at low water potentials relative to other organs of the plant, but the physiology of this response has been little studied. The objective of this study was to develop an experimental system that models the field situation in which upper soil layers dry, to enable studies of nodal root growth regulation under water deficit conditions. A divided-chamber experimental system was developed to allow the growth of maize primary and seminal root systems in well-watered conditions while the nodal root system is exposed to precise conditions of low soil water potential. The divided-chamber system was used to characterize nodal root growth responses to a range of soil water potentials under steady-state and reproducible conditions. Two contrasting genotypes, selected for differences in root growth response to water stress based on a previous study of the primary root, displayed similarly sensitive growth responses to -0.3 MPa soil, but different capacities to maintain high root tip water potential corresponding with different growth responses at lower soil water potentials. Both genotypes maintained relatively high nodal root tip water potentials in -2.0 MPa soil, despite the decreased soil water potential, suggesting a stress-induced response that enhances water transport to the root tip. The difference in high tissue water potential maintenance was seen not only between the contrasting genotypes but also between the first two developmental nodes of roots. The divided-chamber system provides a powerful experimental approach to investigate the physiological mechanisms regulating nodal root growth responses to adverse soil conditions. Future studies may include measurements of hydraulic conductivity, anatomical characterization of vascular elements near the growth zone, aquaporin content and activity, and suberin deposition in response to low soil water potentials.
Unpacking middle school achievement: how students perceive the effect of home, school, and community influences on their academic success
Authors:   , Worthington Tracy A.
Published: April 2021

This transcendental phenomenological study set out to determine the nature and extent of influence on student success, as perceived by selected rising seventh-grade students at a particular mid-West middle school (grades 6-8), through analysis of a student-centered narrative. In particular, this study sought to ascertain how and why certain students believe they were successful, and how students perceive home, school, and community people and places to be positive and negative influences on their success in and outside of school. Analysis revealed that students see themselves ("self"), as well as individuals and places outside the home and school ("places and faces"), along with rewards and punishments (a "double-edged sword"), as combined influences on their success. Analysis of the student narrative also led to the development of an ecological footprint for the selected school, which revealed more influence from the macro-system than previously suggested by prior research. As such, it may be wise for schools, families, and community agencies, programs and individuals to develop mental health and coping strategies and programs to promote student success. Keywords: ecological systems theory, student voice, student success, middle school
Cubic and spherical nanoparticles for detection and therapy of cancer
Authors:   , Suresh Dhananjay
Published: April 2021

Cancer is the leading cause of high mortality rates. Cancer patients require advanced treatment due to lack of early prevention and diagnosis. Moreover, progression of the disease is unpredictable and personalized therapy options are being explored. Existing cancer therapy leads to drug resistance that worsens patient survival rates, and thus disease management is challenging. This necessitates the need to understand the underlying cause, early detection of possible biomarkers, monitor the disease state and develop effective therapeutics. Current innovations in cancer detection and therapy includes use of newer class of smart nanomaterials. These advances in nanoscale materials, due to their unique size, chemical and physical properties, make them ideal for nanomedicinal and nanoelectronic applications. The work performed in this thesis describes the design and the synthesis of cubic and spherical nanoparticles, and their subsequent applications toward energy interactions, biochemical interactions and cellular targeting. Details of receptor mediated endocytic mechanism, targeted capture of circulating tumor cells (CTC), athermal mechanism of controlled release of biomolecules from nanoparticles using femtosecond pulses, and targeted siRNA delivery using nanoparticles have been explained. Mechanistic studies showed that receptor targeting follows a clathrin mediated endocytic pathway. Receptor-targeted nanoparticles showed effective capture of EpCAM-negative CTCs. The cubic shaped nanoparticles were found to enhance the plasmon-photon coupling to efficiently release biomolecules. Spherical nanoparticle mediated siRNA delivery resensitized drug resistant NSCLC by downregulating two important oncogenes, AXL and FN14 as observed by both in vitro and in vivo studies. Additionally, the study highlights drug resensitization following the effective knockdown of AXL using CRISPR based gene editing. Overall, the results demonstrate the application of nanoparticles for advanced diagnostics and therapeutics.
Utilizing social media to inform inclusive apparel design for baby boomer women
Authors:   , Starkey Sandra
Published: April 2021

Apparel design solutions for an aging population with unique needs are lacking in the retail industry and specifically for baby boomer women. The fashion industry does not acknowledge that older women value fashion and are interested in maintaining a sense of style into old age. This study focused on expanding inclusive apparel design strategies and specifically to evaluate baby boomer womenâ€™s clothing preferences through their fashion blogs. Vital to this research was the design and construction of a mini-collection of clothing that served two purposes. First, as a starting point in the development of apparel prototypes designed specifically to satisfy multiple needs without calling attention to special requirements. Second, to provide physical garments that users interacted with and provided feedback about to inform recommendations for inclusive apparel prototypes designed for baby boomer women. The results from this study found that the study participants were interested in a variety of clothing styles and silhouettes and specifically in fashion trends that could be modified to accommodate an aging body. Design solutions addressed a range of needs without calling attention to disabilities. Simple designs with easy to manage closures and special details to enhance personal style were favored by the study participants. This research contributed to apparel design scholarship, fully documented and evaluated the inclusive design process and added to the body of qualitative research that utilizes social media and specifically blogs as a rich data source.
Exploring the collective knowledge curation process of online health communities
Authors:   , Xing Wanli
Published: April 2021

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] More and more people turn to online health communities for social support to satisfy their health-related needs. Previous studies on social support and online health communities in general have focused on the content of social support and the relationship of social support with other entities using traditional social science methods. Little is known about how social support facilitate the knowledge curation process in an online health community. Moreover, the presence of misinformation in online health communities also calls for research into the knowledge curation process in order to reduce the risk of misinformation. This study uses data mining technologies to analyze around one million posts across 23 online health communities. It aims to reveal how information, through social support, flows between the community users working as a whole to dynamically curate knowledge and further interacts with information accuracy. This data-centric research in online health communities 1) discovered that xperiphery users instead of core users dominate the quantitative and content information flow; 2) identified three temporal information flow patterns for the knowledge curation process -- each with distinct characteristics; 3) found that information accuracy differed significantly over the identified information flow patterns and time and the information accuracy variation trends with each information flow pattern was identified as well. These findings not only have important implications for social support use, delivery and social support research methodologies but also can inform future online health platform design.
Defining the undefinedness of C11 : practical semantics-based program analysis
Authors:   , Hathhorn Chris
Published: April 2021

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This thesis extends the work of Ellison and Ros,u [13, 12] but focuses on the "negative" semantics of the C11 language--the semantics required to not just give meaning to correct programs, but also to reject undefined programs. We investigate undefined behavior in C and discuss the techniques and special considerations needed to formally specify it. Using these techniques, we have modified and extended a semantics of C into one that captures undefined behavior. The amount of semantic infrastructure and effort required to achieve this was unexpectedly high, in the end more than tripling the size of the original semantics. From our semantics, we automatically extract kcc, a tool for checking realworld C programs for undefined behavior and other common programmer mistakes. Previous versions of this tool were used primarily for testing the correctness of the semantics, but we have improved it into a tool for doing practical analysis of real C programs. It beats many similar tools in its ability to catch a broad range of undesirable behaviors. We demonstrate this with comparisons based on our own test suite in addition to third-party benchmarks. Our checker is capable of detecting examples of all 77 categories of core language undefinedness appearing in the C11 standard, more than any other tool we considered. Based on this evaluation, we argue that our work is the most comprehensive and complete semantic treatment of undefined behavior in C, and thus of the C language itself.
Broadband, reconfigurable and multifunctional elastic wave control with smart metamaterials
Authors:   , Chen Yangyang
Published: April 2021

Over the past two decades, an extensive research effort has been devoted to elastic metamaterials, structured artificial materials at subwavelength scales, for elastic wave manipulations in solids. Due to the extreme values of material parameters, negative and/or positive, they achieved, the applications can range from wave and/or vibration attenuations, wave guiding and imaging, enhanced sensing, to invisible cloaking. However, conventional passive metamaterials have limitations, i.e. they can only be operated in narrow frequency regions and their functions are usually locked into space or with minor tunabilities once fabricated, lacking real time reconfigurabilities. Those limitations strongly hinder them from practical usages. With the rapid development of smart materials and structures, more and more intelligent elements are being introduced into wave propagation, vibration and sound control systems. The piezoelectric shunting technique is one well known method that receives considerable attention. In this dissertation, by leveraging the circuit control concept, both analog and digital, we propose some circuit controlled active/adaptive/hybrid/programmable metamaterials and metasurfaces for unprecedent elastic wave manipulations. Analytical, numerically and experimentally approaches are combined throughout the dissertation to illustrate design concepts, characterize wave propagation properties, and valid the designs. Specifically, active elastic metamaterials with tunable stiffness in local resonators are first designed for tunable wave and/or vibration mitigations. We then extend this concept to achieve super broadband wave attenuations with frequency-dependent stiffness elements. By introducing the variable stiffness elements to the host medium, a hybrid metamaterial is developed for switched ON/OFF wave propagations and broadband negative refractions. Based on a developed approximate transformation method, an active metamaterial is designed and placed on a plate to achieve spatially varying effective mass densities for broadband elastic trajectory control. Finally, a programmable metasurface with ultrathin-thickness is demonstrated for broadband, real-time and multifunctional wavefront manipulations in a plate. The active, adaptive, hybrid, and programmable elastic metamaterials and/or metasurfaces are still in their infant stages. The examples presented in the dissertation are transformable to different length and time scales and could serve as efficient and powerful tools in exploring some unconventional wave phenomenon in solid structures, i.e. by using concepts in quantum mechanics, where passive approaches are significantly limited. The designs could also immediately open new possibilities in elastic wave control devices including, but not limited to structural health monitoring, stealth technology, active noise control, as well as medical instrumentation and imaging.
Applying optimization techniques to identify multistate collaborations for improving biopower energy policy
Authors:   , Dundar Bayram
Published: April 2021

The US Environmental Protection Agency (EPA) proposed a rule that aims to reduce carbon emissions from US coal-fired power plants. The proposed "Clean Power Plan" specifies state-specific rate-based goals to achieve a total US carbon emission reduction of 32% below 2005 levels by 2030. An increase in the co-firing of woody biomass with coal to generate biopower is one of the potential approaches that electricity providers could take to comply with EPA's proposed rules. We develop a mixed integer linear programming (MILP) model to identify minimum-cost approaches for reducing CO[subscript 2] emissions via co-firing biomass subject to spatially-explicit biomass availability constraints. An important feature of the EPA recommendations is an allowance for states to participate in multi-state compliance strategies. We extend the MILP model to optimize within a larger geographical framework that allows states to identify minimum-cost partnerships that meet aggregated emission reduction goals. We apply the MILP model to data for five Midwestern US states to determine the role that co-firing biomass could play in achieving their EPA-proposed emission reduction targets, and find that some states can meet their renewable energy generation targets through co-firing, although co-firing alone is not sufficient to achieve any state's emission reduction targets. This MILP is extended to robust MILP model, addressing the uncertainties in power plant boiler installation cost, coal electricity generation cost, as well as the emission rate. We apply this robust model to a set of 18 states in the northern US to identify optimal sets of multi-state collaborations. Finally, we investigate the impact of energy policy-related regulations on biomass demand and procurement cost using econometric models. We develop a demand response model and then incorporated this into a robust mixed-integer nonlinear programming (MINLP) model. We utilize a two-stage approach to solve the resultant robust mixed integer nonlinear programming model. This model is then applied the same set of 18 states in the northern US to identify optimal sets of multi-state collaborations for different feasibility rates and emission levels.
Teachers' beliefs about ability to engage African-American students and identify for advanced placement through the lens of the Ohio State Teacher Efficacy Survey and the Rand Measure
Authors:   , Greely Eric C. Sr.
Published: April 2021

A fundamental right of American children is to have equal opportunities to obtain a quality education regardless of race, class, or economic status. College graduates are less likely to live in poverty and more likely to have greater earning potential. High school students enrolling in rigorous coursework, like Advanced Placement classes, are better prepared for college. Using the instruments of the Ohio Teacher Efficacy Survey and the Rand Measure, this study found that having a rigorous curriculum and avoiding deficit thinking matters in recommending African-American students' to Advanced Placement classes. Race and ethnicity should not be used as a limitation. Educators must recognize the diversity that each student contributes to the classroom. Additionally, this research revealed that what high school teachers believe about their students' capabilities does influence the success of the students. Teachers who teach Advanced Placement courses have to believe all students can learn, regardless of condition, status, race or economic opportunities.
The role of social capital and acculturation in healthcare access : the case of Hispanics in Missouri
Authors:   , Rodriguez-Alcalï¿½ Maria E.
Published: April 2021

Hispanics are today the largest group with the lowest access to health care in the U.S. as measured by several studies that quantify rates of uninsured and percentages who lack a primary care physician (R. Andersen, Lewis, Giachello, Aday, and Chiu, 1981; R. M. Andersen, Giachello, and Aday, 1986; Balcazar, Grineski, and Collins, 2015; Fiscella, Franks, Doescher, and Saver, 2002; Gresenz, Rogowski, and Escarce, 2009; Livingston, 2009). In states like Missouri, where the Hispanic population growth is relatively recent, the issue is new (Haverluk and Trautman, 2008; Stepler and Brown, 2015). Although the percentage of Latinos in Missouri is still low - about 4% - what is noteworthy is the group's population growth of 311% for the period 1990 to 2016 (U.S. Census Bureau, 2014b, 2014a). A theoretical analysis that applies Gramsci's (2014[1948]) idea of cultural hegemony shows that structural barriers have been imposed over the years to restrict access to health care for Hispanics mainly through the intersection of federal healthcare and immigration legislation. A meta-analysis of 83 published studies further corroborate the structural barriers in place and identifies additional ones that apply to acculturation and social capital. Although acculturation has been measured by various studies that focus on Hispanics' access to health care, overall, these usually fail to clearly explain and justify how and why they chose certain ways to operationalize such variable. In addition, social capital is practically neglected in this literature. Although there are studies that measure and discuss the importance of having social networks to access medical resources, almost no study uses the term social capital and even fewer measure or discuss it by subtypes. Data from a survey study conducted in the state of Missouri in 2014 is used as the basis of logistic regression analysis. The study further corroborates that there are structural barriers, but also finds that acculturation and social capital impact access for this population. In particular, I find that Hispanics in Missouri possess low levels of acculturation as it applies specifically to the American healthcare system. Two types of social capital are found to be significant but in opposite directions. Bonding social capital, which stems from strong relationships, is found to hinder access. This may be because many such tight networks may not be as connected to the Anglo portion of the American society that is better linked to resources. On the other hand, bridging social capital, which stems from weak relationships, is found to be an enabler of access. These results indicate that we need to go beyond just offering medical insurance to this group. In order for Hispanics to increase access to health care they need to be better acculturated to the American healthcare system, as well as need to be connected to the proper social networks that can enhance access.
Measuring and modeling rainfall with terrestrial sensors and radar : implications for rainfall heterogeneity and discharge
Authors:   , Simpson Micheal Joseph
Published: April 2021

Quantitative precipitation estimates are fundamental for hydrometeorological analyses. Radars provide a superior spatiotemporal advantage over terrestrial-based precipitation gauges to provide such measures of rainfall. However, many regions of the Continental US (CONUS) reside outside of the optimal range of weather radar surveillance (i.e., 100 km), with few studies analyzing the performance of radar rain rate estimates beyond this range. Several years' worth of radar rain rate estimates were analyzed from distant S-band Weather Surveillance Radars -- 1988 Doppler (WSR-88D) series, demonstrating poor performance in quantitative precipitation estimates (QPE's) at distances beyond 150 km. Furthermore, these S-band radar rain rates were determined to be significantly (p less than 0.10) less accurate in Quantitative Precipitation Estimates (QPE's) when compared to a locally-sited X-band dual polarimetric radar. In general, S-band radars were best utilized when implementing R(Z,ZDR) algorithms, with the bulk of QPE errors due to missed precipitation, whereas the X-band radar was superior overall with either R(Z,ZDR) or R(ZDR,KDP) with errors primarily due to false alarms. These radar QPE's were then used as input to a physically-based hydrologic model, Vflo, which showed superior performance over spatially-averaged rain gauges, which sometimes missed precipitation events. The results presented demonstrate the importance of choosing the proper radar QPE datasets for hydrometeorological studies.
Agendas and committees in American state legislatures : the causes and consequences of matching priorities with institutional roles
Authors:   , Swift Clint S.
Published: April 2021

Legislative scholars largely agree on the importance of the committee system in the legislative process. Committees are generally considered the primary locus of lawmaking activity and individual legislators see them as important for accomplishing their goals. In this dissertation I argue that the value of committee assignments to a legislator is entirely dependent on the legislator's policy priorities. For example, assignment to the Agriculture Committee should be of more value to legislators with interests in agricultural policy than those unconcerned with such policy. I devise a means of measuring the degree of this match between priorities and assignments and demonstrate that legislators with better matches are more effective in their chambers. Further, I identify the ways in which individual characteristics and institutions shape opportunities for matching across a sample of American state legislatures. This research shifts the focus away from aggregate measures of committee assignment value and demonstrates the utility of thinking about the particularized benefits accrued through assignment politics.
Magnetic interactions in the spin-orbit coupled electron gas
Authors:   , Valizadeh Mohammad Mahdi
Published: April 2021

The exchange interaction between two localized magnetic moments embedded in a host material is fundamental to the description of the magnetic behavior of solids and chiral order in magnetic structures. This interaction was originally found by Ruderman, Kittel, Kasuya and Yosida (RKKY). It is currently an area of considerable interest. The potential spintronics applications of chiral magnetic structures, originating from the competition between RKKY and Dzyaloshinsky-Moriya (DM) interactions caused by broken symmetries and the presence of the spin-orbit interaction, have stimulated lots of recent theoretical studies. In the standard spin-degenerate electron gas, it leads to the well-known RKKY interaction. In this dissertation, we study RKKY and DM interactions in the spinpolarized electron gas in one, two and three dimensions. In addition to the Heisenberg form of interaction, we found an Ising-like term appears in the magnetic interaction for the spin-polarized gas. The anisotropic interaction is due to the broken time-reversal symmetry, based on the fact that spin polarization is in the z direction. Furthermore, we study RKKY and DM interactions in a spin-polarized two-dimensional electron gas in the presence of both Rashba and Dresselhaus spin-orbit coupling (SOC). We find that in addition to the scalar RKKY interaction, there are also vector and tensor interactions between the two localized moments. Analytical expressions are found for each term of the total magnetic interaction, and their oscillatory behaviors are studied and compared to the numerical results. We also use our model to find energy of Neel and Bloch magnetic walls. Using our theoretical results we are able to predict which wall is preferred. In the last chapter, we study impurity states in the kagome lattice. The kagome lattice is a 2D lattice that has been of recent interest owing to its graphene-like band structure, the existence of flat band states and exotic quasiparticle excitations. In this chapter, we study the electronic states introduced by impurities in the system by applying the Green's function approach within a tight-binding model Hamiltonian. The impurities introduce localized states close to the Dirac point, in many ways similar to graphene, which will be discussed.
Perceptions of MBA preparation : new Master of Business Administration graduates, their employers, and higher education faculty
Authors:   , Whitlow Jan H.
Published: April 2021

This qualitative study compares perceptions of Master of Business Administration (MBA) students and recent MBA graduates with those of employers of recent MBA graduates and MBA faculty regarding the skills, competencies, and experiences needed to be successful in their new graduate jobs. The researcher gathered stakeholder perspectives of the skills, competencies and experiences needed to create successful new MBA graduates through surveys and archival data. Stakeholders included recent MBA graduates, MBA students, MBA faculty, and employers of recent MBA graduates. Analysis included MBA graduates, MBA employers, MBA faculty, and higher education practices. Results suggest that critical thinking, communication, teamwork, leadership along with data analysis are the necessary skills, competencies, and experiences needed to be successful in a recent MBA graduate position. This research further validates the extant research of DiMartino and Castaneda (2007), which indicated that the skills new job entrants most need for success in the workplace include oral and written communication, time management, critical thinking, problem solving, personal accountability, and the ability to work effectively with others. Implications of this research are to advance the academic preparation of MBA students; to improve their oral and written communications skills, critical thinking, teamwork, leadership, and data analysis.
Babbler : a novel
Authors:   , Habermeyer Ryan
Published: April 2021

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] A satirical novel of post-WWII America depicted through the fictitious memoirs of an ex-Nazi on an absurdist quest to win the Nobel Peace Prize.
Man up : muscular Christianity and the making of 20th-century American religion
Authors:   , Hampton Hunter M.
Published: April 2021

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] "Man Up: Muscular Christianity and the Making of 20th-Century American Religion," examines the history of muscular Christianity in 20th-century America. Specifically, I analyze how liberal Protestants, Catholics, Mormons, fundamentalists, and evangelicals used muscular Christianity to navigate the cultural waters from religious outsiders into the mainstream. My project began by asking why millions of Americans hear sermons filled with sports analogies, attend Bible studies that follow a basketball game, and read books written by NFL quarterbacks? I discovered that over the course of the 20th century religious institutions, particularly religious colleges, used muscular Christianity to attract, convert, and retain men. By using student newspapers from Notre Dame, BYU and Wheaton College as a primary source base, my research provides a grassroots perspective on how the laity lived this religious message preached by religious authorities. I conclude that these communities used muscular Christianity to solidify their distinct religious identities and dissolve barriers with outsiders. Though its iterations shift over time and within each religious community, the blend of masculinity, sports, heroic-savagery, and homosocial community remained the remedy for the next generation to man up. My project expands the interpretation of 20th-century American history in three ways. First, I illustrate that muscular Christianity is one of the primary shapers of 20th-century American religion. Second my research explicates the larger cultural trends of therapeutic and consumer culture on American religion. Finally, my project helps fill the void in the history of religion and sports.
Bayesian partition model for identifying hypo- and hyper- methylation
Authors:   , Wang Henan
Published: April 2021

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation introduces MethyBayes, a full Bayesian partition model for identifying hypo- and hypermethylated loci. The main interest of study on DNA methylation data is to test the methylation difference under two conditions of biological samples. However, the high cost and complexity of this sequencing experiment limits the number of biological replicates, which brings challenges to the development of statistical methods. Current available methods can only provide binary output of a locus being differentially methylated or not, and an extra step based on the sign of test statistics is always needed to further identify hypo- and hyper-methylation. In our proposed full Bayesian partition model, we introduce a latent variable to indicate membership of methylation for each locus, and assign priors for equal-, hypo- and hypermethylation loci separately. One-step output of each locus being either equal-, hypo- or hyper-methylated locus is produced without further post-hoc analysis. We also conduct simulation study and real data analysis including bioinformatic analysis to show that the proposed full Bayesian partition model outperforms existing methods in terms of power while maintaining a low false discovery rate. This dissertation also introduces a non-parametric Bayesian change point model to estimate parameters of a sequence of observations that experiences changes at unknown times, which also involves the identification of these change points. We use a latent variable to represent change point status. A Dirichlet prior is applied to capture the cluster effect without pre-knowledge of the number of clusters. We illustrate the proposed Bayesian change point model via normal distribution in continuous case and Poisson distribution in discrete case.
Deriving information from spatial sampling floor-based personnel detection system
Authors:   , Muheidat Fadi
Published: April 2021

Research has shown and identified a clear link between human gait characteristics and different medical conditions. Therefore, a change in certain gait parameters may be predictive of future falls and adverse events in older adults such as physical functional decline and fall risks. We describe a system that is unobtrusive and continuously monitors the gait during daily activities of elderly people. The early assessment of gait decline will benefit the senior by providing an indication of the risk of falls. We developed a low cost floor-based personnel detection system; we call a smart carpet, which consists of a sensor pad placed under a carpet; the electronics reads walking activity. The smart carpet systems is used as a component of an automated health monitoring system, which helps enable independent living for elderly people and provide a practical environment that improves quality of life, reduces healthcare costs and promotes independence. In this dissertation, we extended the functionalities of the smart carpet to improve its ability to detect falls, estimate gait parameters and compared it to GAITRite system. We counted number of people walking on the carpet in order to distinguish the plurality of people from fall event. Additionally we studied the characteristics and the behavior of the sensor's scavenged signal. Results showed that our system detects falls, using computational intelligence techniques, with 96.2% accuracy and 81% sensitivity and 97.8% specificity. The system reliably estimates the gait parameters; walking speed, stride length and stride time with percentage errors of 1.43%, -4.32%, and -5.73% respectively. Our system can count the number of people on the carpet with high accuracy, and we ran tests with up to four people. We were able to use computational features of the generated waveform, by extracting the Mel Frequency Cepstral Coefficients (MFCC), and using formal computation intelligence to distinguish different people with an average accuracy of 82%, given that the experiments were performed within the same day.
Distributed frequent hierarchical pattern mining for robust and efficient large-scale association discovery
Authors:   , Phinney Michael
Published: April 2021

Frequent pattern mining is a classic data mining technique, generally applicable to a wide range of application domains, and a mature area of research. The fundamental challenge arises from the combinatorial nature of frequent itemsets, scaling exponentially with respect to the number of unique items. Apriori-based and FPTree-based algorithms have dominated the space thus far. Initial phases of this research relied on the Apriori algorithm and utilized a distributed computing environment; we proposed the Cartesian Scheduler to manage Apriori's candidate generation process. To address the limitation of bottom-up frequent pattern mining algorithms such as Apriori and FPGrowth, we propose the Frequent Hierarchical Pattern Tree (FHPTree): a tree structure and new frequent pattern mining paradigm. The classic problem is redefined as frequent hierarchical pattern mining where the goal is to detect frequent maximal pattern covers. Under the proposed paradigm, compressed representations of maximal patterns are mined using a top-down FHPTree traversal, FHPGrowth, which detects large patterns before their subsets, thus yielding significant reductions in computation time. The FHPTree memory footprint is small; the number of nodes in the structure scales linearly with respect to the number of unique items. Additionally, the FHPTree serves as a persistent, dynamic data structure to index frequent patterns and enable efficient searches. When the search space is exponential, efficient targeted mining capabilities are paramount; this is one of the key contributions of the FHPTree. This dissertation will demonstrate the performance of FHPGrowth, achieving a 300x speed up over state-of-the-art maximal pattern mining algorithms and approximately a 2400x speedup when utilizing FHPGrowth in a distributed computing environment. In addition, we allude to future research opportunities, and suggest various modifications to further optimize the FHPTree and FHPGrowth. Moreover, the methods we offer will have an impact on other data mining research areas including contrast set mining as well as spatial and temporal mining.