Sex Offender Registries and Community notification laws are in many ways derived from emotion. It is believed that one can predict views on these social policies by examining aspects of life experience due to Techniques of Neutralization and Labeling theories. Reliability and Factor analyses were used to create factor-based indices to predict views on social policies, specifically views on sex offender registries and community notification laws. Multiple Regression was used to assess the effects of gender, race, age, spirituality, locus of control, beliefs about rape, and religiosity on sex offender registries, community notification laws, and sex offenders. By using regression, it was found that locus of control, beliefs about rape, religiosity, and spirituality all had a significant effect on beliefs about sex offender registries, community notification laws, and sex offenders.

A decomposition D of a graph H by a graph G is a partition of the edge set of H such that the subgraph induced by the edges in each part of the partition is isomorphic to G. A mixed graph on V vertices is an ordered pair (V,C), where V is a set of vertices, |V| = v, and C is a set of ordered and unordered pairs, denoted (x, y) and [x, y] respectively, of elements of V [8]. An ordered pair (x, y) ∈ C is called an arc of (V,C) and an unordered pair [x, y] ∈ C is called an edge of graph (V,C). A path on n vertices is denoted as Pn. A partial orientation on G is obtained by replacing each edge [x, y] ∈ E(G) with either (x, y), (y, x), or [x, y] in such a way that there are twice as many arcs as edges. The complete mixed graph on v vertices, denoted Mv, is the mixed graph (V,C) where for every pair of distinct vertices v1, v2 ∈ V , we have {(v1, v2), (v2, v1), [v1, v2]} ⊂ C. The goal of this thesis is to establish necessary and sufficient conditions for decomposition of Mv by all possible partial orientations of P4.

Although research demonstrates significant stigma towards individuals with mental illness, the relative importance of observed behavior and a psychiatric diagnosis in eliciting stigma remains poorly understood. Using video vignettes, three experiments (ns = 195, 749, and 791) examined the effect of irritable (vs. calm) behavior and the presence (vs. absence) of a psychiatric diagnosis (schizophrenia in Studies 1 and 2; schizophrenia and depression in Study 3) on attitudinal, emotional, and behavioral dimensions of stigma towards a fictitious emergency room patient seeking migraine treatment. In line with labeling theory, irritable behavior resulted in greater blameworthy attributions for behavior, greater fear and anger, less caring emotions, and lower perceived warmth. Both a depression and schizophrenia diagnosis elicited stigma by leading to greater endorsements of other stigmatizing attributions (e.g., substance use) as a reason for behavior. Irritable behavior and both psychiatric diagnoses resulted in patients being rated as less predictable and more dangerous, whereas irritable behavior and schizophrenia only resulted in decreased competence. Irritable behavior and psychiatric diagnosis also interacted to predict desire for social distance. When calm, a psychiatric diagnosis predicted greater distance, such that a patient with no label was least stigmatized, one with depression was moderately stigmatized, and one with schizophrenia was most stigmatized. When irritable, the patient elicited a higher desire for distance regardless of psychiatric diagnosis. Mediational analyses show that when controlling for behavior, perceived dangerousness and fear mediate the effect of a diagnosis on desire for distance. In all, results suggest both diagnostic labels and irritable behavior result in stigma via different attitudinal and emotional mechanisms, and that individuals with psychiatric diagnoses face stigma even if behaving calmly. By enriching understanding of the relative importance of irritable behavior and a psychiatric diagnosis on multiple dimensions of mental illness stigma, this work has implications for anti-stigma interventions.

The graph isomorphism problem has received a great deal of attention on both theoretical and practical fronts. However, a polynomial algorithm for the problem has yet to be found. Even so, the best of the existing algorithms perform well in practice; so well that it is challenging to find hard instances for them. The most efficient algorithms, for determining if a pair of graphs are isomorphic, are based on the individualization-refinement paradigm, pioneered by Brendan McKay in 1981 with his algorithm nauty. Nauty and various improved descendants of nauty, such as bliss and saucy, solve the graph isomorphism problem by determining a canonical representative for each of the graphs. The graphs are isomorphic if and only if their canonical representatives are identical. These algorithms also detect the symmetries in a graph which are used to speed up the search for the canonical representative--an approach that performs well in practice. Yet, several families of graphs have been shown to exist which are hard for nauty-like algorithms. This dissertation investigates why these graph families pose difficulty for individualization-refinement algorithms and proposes several techniques for circumventing these limitations. The first technique we propose addresses a fundamental problem pointed out by Miyazaki in 1993. He constructed a family of colored graphs which require exponential time for nauty (and nauty's improved descendants). We analyze Miyazaki's construction to determine the source of difficulty and identify a solution. We modify the base individualization-refinement algorithm by exploiting the symmetries discovered in a graph to guide the search for its canonical representative. This is accomplished with the help of a novel data structure called a guide tree. As a consequence, colored Miyazaki graphs are processed in polynomial time--thus obviating the only known exponential upper-bound on individualization-refinement algorithms (which has stood for the last 16 years). The preceding technique can only help if a graph has enough symmetry to exploit. It cannot be used for another family of hard graphs that have a high degree of regularity, but possess few actual symmetries. To handle these instances, we introduce an adaptive refinement method which utilizes the guide-tree data structure of the preceding technique to use a stronger vertex-invariant, but only when needed. We show that adaptive refinement is very effective, and it can result in dramatic speedups. We then present a third technique ideally suited for large graphs with a preponderance of sparse symmetries. A method was devised by Darga et al. for dealing with these large and highly symmetric graphs, which can reduce runtime by an order of magnitude. We explain the method and show how to incorporate it into our algorithm. Finally, we develop and implement a parallel algorithm for detecting the symmetries in, and finding a canonical representative of a graph. Our novel parallel algorithm divides the search for the symmetries and canonical representative among each processor, allowing for a high degree of scalability. The parallel algorithm is benchmarked on the hardest problem instances, and shown to be effective in subdividing the search space.

In the last two decades, protein drugs have enjoyed a rapid growth and achieved a tremendous success in treating human diseases. However, the presence of physiological barriers greatly impedes the efficient delivery of such unconventional large molecule drugs, and therefore limits their clinical utility. An elegant way to address this challenge takes advantage of certain endogenous transporter proteins, such as human transferrin (Tf), whose ability to traverse physiological barriers has been extensively exploited. However, methods to investigate Tf-based drug delivery remained insufficient and unsatisfactory until recent development of quantitative mass spectrometry (MS). Hereby, MS-based methods have been developed and validated for quantitation of exogenous Tf in biological fluids. Particularly, different O18-labeling based approaches have been evaluated, modified and developed in this work, in order to achieve the most reliable quantitation. Alternatively, a novel approach based on indium labeling and inductively coupled plasma mass spectrometry (ICP-MS) detection has been developed for sensitive quantitation of Tf in biological fluids. The second aspect of this dissertation work focuses on the application of MS-based methods for characterization of protein drugs at different levels, ranging from protein identification, covalent structure, conformation, and interaction with physiological partners. Particularly, an O18-labeling assisted approach has been developed to identification of protein deamidation products. This new approach can readily distinguish between the two deamidated isomers. Also, an LC-MS based method has been developed for ranking the susceptibility of protein disulfide bonds to reduction, which could be applied to several disulfide bond-related analyses. Finally, a recently designed growth hormone transferrin fusion protein was studied using MS-based methods, and the molecular basis for its successful oral delivery was revealed.

The purpose of this study is to examine how high school students labeled with autism make meaning of their label and how, for them, the label functions in their day-to-day lives. Being diagnosed with autism can have many implications for an individual and his or her family and how a label is understood is very much connected to the impact that it has. A label can be instrumental in accessing resources and supports that enable a person to thrive, but it can also conjure stereotypes which may categorize a person or limit them in particular ways. Using critical theory and phenomenological analysis, short semi-structured interviews were conducted with high school aged participants prior to their attending a full day workshop. The workshop included half-day art creation and a half-day focus group which sought to understand participants’ experiences through their descriptions of their art and through collaborative discussion about their experience living labeled. The findings suggest that while their experiences are as diverse as the individuals who have them, there are similarities in how the label functions which may be more universal. Participants in this study discussed how the label of autism assigns positive or (more often) negative value to a person; how their label linked them with certain resources (and not others), and how they experienced and understood these resources; and the way labels can both protect and confine a person. Consideration of how high school students understand of their label of autism can prompt us all to think more critically about how labels, and the meanings we assign to them, affect and shape experience for those who live labeled. / Thesis / Master of Social Work (MSW)

Antibody-recruiting molecules (ARMs) are therapeutic tools that simultaneously bind a hapten-specific serum antibody and a cancer cell surface protein, resulting in the activation and recruitment of an immune cell to the cancer surface. However, ARM efficacy is limited by the ability of ARMs to form a quaternary complex with the immune cell receptor, antibody, and cancer cell surface. The Rullo lab has previously developed and characterized a covalent ARM (cARM) that irreversibly links the ARM to the antibody and simplifies the quaternary binding equilibria. cARMs have shown a marked increase in both target immune recognition and therapeutic efficacy. However, cARM efficacy is still limited by the affinity of the antibody for the immune receptor. We aim to investigate how direct covalent engagement of the immune receptor and elimination the antibody-immune receptor binding equilibria impacts immune activation and therapeutic efficacy. This thesis focuses on the chemical programming of macrophages through direct covalent immune receptor engagement. We have developed and characterized covalent immune programmers (CIPs), which are molecules that contain a macrophage targeting domain and a tumour targeting domain. The macrophage targeting domain binds the activating receptor CD64 on the macrophage surface and contains a chemical warhead that covalently labels the receptor once bound. The tumour targeting domain can promote macrophage tumour engagement resulting in tumoricidal function. Flow cytometry experiments have shown that CIPS are able to bind Fc receptors specifically and effectively on the surface of macrophages. Further, CIPs were able to induce macrophage activation and induce target specific phagocytosis. These experiments have also shown that direct engagement of the receptor by the CIP is more effective than antibody-mediated engagement, suggesting that overall immune complex stability affects immune cell activation. Taken together, these concepts can be used to guide future immunotherapeutic design. / Thesis / Master of Science (MSc)

In the past fifty years there has been an incredible amount of change made to the agrarian system of the United States. New discoveries in the realm of biotechnology led to the adoption of genetically modified organisms (GMOs) in agriculture, and transformed the industry. Due to regulatory policies set during the nineteen-eighties this technology was able to benefit from widespread commercialization. Today, we see the effects of this approach and are entering into a highly volatile political climate in regard to GMOs. This paper aims to provide an analysis of the regulatory system in place and the discrepancies that exist in US policy. The factors evaluated through this thesis include the current US regulatory approach, advancements in biotechnology, and a comparative perspective on US and EU systems. In each of these reviews it is also relevant to mention consumer opinion on GMOs and the role of interest groups. It is important for every American consumer to understand the politics and technology behind their meals. Through the analysis of recent judicial decisions and the enactment of new laws this thesis explains how the use of GMOs in agriculture is causing an unprecedented change to the political structures in place.

This study explored the relationship between gaze anxiety and the perception of facial expressions. The literature suggests that individuals experiencing Social Anxiety Disorder (SAD) might have a fear of making direct eye contact, and that these individuals also demonstrate a hypervigilance towards the eye region. It was thought that this increased anxiety concerning eye contact might be related to the tendency of socially anxious individuals to mislabel emotion in the faces of onlookers. A better understanding of the cognitive biases common to SAD could lead to more efficient intervention and assessment methods. In the present study, the Depression Anxiety Stress Scale-21 (DASS-21) and the Social Phobia and Anxiety Inventory-23 (SPAI-23) were used to measure social anxiety, depression, and overall distress. These forms allowed us to separate participants who reported high socially anxious and depressive traits from those in the normal range. We then compared anxiety concerning mutual eye contact as measured by the Gaze Anxiety Rating Scale (GARS) to performance on a facial recognition task. Performance was measured as recognition accuracy and average perceived intensity of onlooker expression on a scale of 1-5. A linear regression analysis revealed that higher GARS scores were related to higher perceived intensity of emotion by socially anxious individuals. An exploratory correlation analysis also revealed that higher gaze anxiety was related to lower accuracy at identifying neutral emotions and higher accuracy at identifying angry emotions. While past research has demonstrated these same biases by socially anxious individuals, gaze anxiety had not been explored extensively. Future research should investigate gaze anxiety’s role as a moderating variable.

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