A functional analysis (FA) is the most commonly used assessment methodology for identifying maintaining variables influencing problem behavior. However, if an FA does not produce clear differentiation, researchers and practitioners often then modify procedures to include additional individualized variables. The interview-informed synthesized contingency analysis (IISCA) provides a marked departure from FA methodology and aims to include individualized factors at the initiation of the assessment in order to more rapidly produce differentiation and clear results. We sought to further evaluate and compare the outcomes of two different functional analysis methods: the single-contingency functional analysis (FA) and the interview-informed synthesized contingency analysis (IISCA) to determine the function of problem behavior and evaluate the subsequent function-based treatment determined from the functional analysis results with two children diagnosed with autism spectrum disorder (ASD). Both participants engaged in problem behavior maintained by single-contingencies of reinforcement identified within the single-contingency FA and emphasized by the effectiveness of each single-contingency function-based treatment.

If mania and depression are part of the same pathological processes, one would predict that episodes of one prospectively increase the odds of episodes of the other. The aim of the present study was to test this hypothesis. For comparison purposes, their relationship was contrasted to the relationship between mania and periods of psychosis. Exploratory analyses also tested the degree to which episodes of each occur with greater frequency over time (i.e., kindling). Participants for the present study came from the Suffolk County Mental Health Project (N = 628), a study of first-admission patients with psychosis. Of these participants, 144 met diagnostic criteria for bipolar I disorder and were analyzed for the current study. Results indicated that mania in a given month predicted depression the following month, even after controlling for other symptoms. The reverse, however, was not the case. Mania and psychosis, in contrast, were found to be robust predictors of one another from month to month. Effects were not due to treatment or demographic differences. These findings provide evidence that mania and depression are weakly related. In contrast, mania and psychosis are more closely linked. Findings are consistent with suggestions that psychiatric nosology regroup mania more closely with …

Collection of poems.

Positive memories play an important role in the etiology and maintenance of posttraumatic stress disorder (PTSD). Additionally, there are potential clinical benefits of recalling positive memories on affect, cognitions, and behaviors. However, most research/clinical work has focused on the role of traumatic memories in PTSD's symptomatology and treatment. The current study examined positive memory recall difficulties and positive memory phenomenology among 185 trauma-exposed individuals with varying PTSD severity. Participants completed the Life Events Checklist for DSM-5, PTSD Checklist for DSM-5, Autobiographical Memory Test, Memory Experiences Questionnaire – Short Form, Ruminative Thought Style Questionnaire, Difficulties in Emotional Regulation Scale – Brief 16-Item Version, Difficulties in Emotional Regulation Scale – Positive Emotions, the Positive Affect subscale of the Affective Control Scale, and two items from the Pittsburg Sleep Quality Index. Results showed that (1) greater PTSD severity was a marginally significant predictor of fewer recalled positive memories; (2) greater positive emotional dysregulation predicted fewer recalled positive memories controlling for PTSD severity; and (3) increasing PTSD severity predicted more negative valence, less vividness, less coherence, less accessibility, less clear time perspective, fewer sensory details, and greater distancing ratings of the recalled positive memory, controlling for sleep quantity/quality. Such findings add to the PTSD-positive …

Training autonomous agents that are capable of performing their assigned job without fail is the ultimate goal of deep reinforcement learning. This thesis introduces a dueling Quantile Regression Deep Q-network, where the network learns the state value quantile function and advantage quantile function separately. With this network architecture the agent is able to learn to control simulated robots in the Gazebo simulator. Carefully crafted reward functions and state spaces must be designed for the agent to learn in complex non-stationary environments. When trained for only 100,000 timesteps, the agent is able reach asymptotic performance in environments with moving and stationary obstacles using only the data from the inertial measurement unit, LIDAR, and positional information. Through the use of transfer learning, the agents are also capable of formation control and flocking patterns. The performance of agents with frozen networks is improved through advice giving in Deep Q-networks by use of normalized Q-values and majority voting.

An interrogation of male behavior in isolated masculine spaces through short stories, an essay, and chapters from a novel-in-progress.

Recent progress in layered transition metal dichalcogenides (TMDs) has led to various promising electronic and optoelectronic applications. However, the structure of materials plays a critical role in electronic and optoelectronic devices, and determines performance. Electronic and optoelectronic devices typically consist of multiple layers that form electrical homojunctions or heterojunctions. Therefore, in a device it can be expected that a WS2 layer may serve as the substrate for a subsequent layer in a multilayer device stack and determine how the layer grows. In transistor structures, roughness at the channel/gate dielectric interface introduces field variations and charge scattering. Therefore, understanding the relations between processing, surface morphology and properties is important. In this project, the effects of pulsed laser deposition (PLD) processing conditions on the surface morphology of few layered WS2 films were studied. WS2 films were synthesized under processing conditions that represent the extremes of surface supersaturation and kinetic energy transfer from the flux to the growing films, and evolution of the surface morphology was studied. The specific conditions were 1Hz/50mJ, 10Hz/50mJ, 1Hz/300mJ, and 10Hz/300mJ respectively. Combining AFM, XRD and Raman analyses, it was determined that deposition at 10Hz/300mJ, provided the best structural properties and surface morphology. Growth appeared to be 3D-cluster, …

Consumer's opinions and sentiments on products can reflect the performance of products in general or in various aspects. Analyzing these data is becoming feasible, considering the availability of immense data and the power of natural language processing. However, retailers have not taken full advantage of online comments. This work is dedicated to a solution for automatically analyzing and summarizing these valuable data at both product and category levels. In this research, a system was developed to retrieve and analyze extensive data from public online resources. A parallel framework was created to make this system extensible and efficient. In this framework, a star topological network was adopted in which each computing unit was assigned to retrieve a fraction of data and to assess sentiment. Finally, the preprocessed data were collected and summarized by the central machine which generates the final result that can be rendered through a web interface. The system was designed to have sound performance, robustness, manageability, extensibility, and accuracy.

Deep reinforcement learning is an area of research that has blossomed tremendously in recent years and has shown remarkable potential in computer games. Real-time strategy game has become an important field of artificial intelligence in game for several years. This paper is about to introduce a kind of algorithm that used to train agents to fight against computer bots. Not only because games are excellent tools to test deep reinforcement learning algorithms for their valuable insight into how well an algorithm can perform in isolated environments without the real-life consequences, but also real-time strategy games are a very complex genre that challenges artificial intelligence agents in both short-term or long-term planning. In this paper, we introduce some history of deep learning and reinforcement learning. Then we combine them with StarCraft. PPO is the algorithm which have some of the benefits of trust region policy optimization (TRPO), but it is much simpler to implement, more general for environment, and have better sample complexity. The StarCraft environment: Blood War Application Programming Interface (BWAPI) is open source to test. The results show that PPO can work well in BWAPI and train units to defeat the opponents. The algorithm presented in the thesis is …

This study focuses on the transgender community's presence and portrayal in advertisements that reach a broad, mainstream audience base. Through a mixed-methods use of focus groups and qualitative content analysis, the content, context, and framings of ads between the years 2015 and 2018 are explored to illustrate current portrayals of the trans community and how the industry is approaching this subcultural group. Its findings contribute to advertising research by exploring current trends in trans portrayals in the cultural context they exist. Because trans advertising in both LGBTQ+ publications and to mainstream audience is largely unexplored, this study seeks to begin a conversation among advertising professionals. The main objective is to ultimately improve the number of genuine, positive portrayals of trans people in advertising and hold the industry accountable for the role they play in serving this community.

Since the adoption of neoliberalism, many cities have taken to integrating nature with capital accumulation to create a sense of place. This has been closely tied to urban greening, or green "revitalization." As part of curating this desired character, city governments are working to roll out plans to restore and renew neighborhoods using their natural landscapes through methods such as reforestation, the creation of parks, and commercial development. These cities, deemed Entrepreneurial cities, are increasingly incorporating natural or green spaces into their development of character as part of their branding schemes. This research focuses on the role of nature as the site of economic development and community revitalization within Dallas, Texas. This research examines how the City of Dallas uses nature to attract capital, and how the narratives of development relate to residents' visions for development in the historically neglected Joppa neighborhood in the Trinity River Corridor. Development near Joppa could be an example of how the natural landscape is being used to not only attract developers but also to bring a different ‘class' of resident into the area. By exploring this intersection of nature and capital in Dallas, we can better understand the nuanced ways through which the neoliberalization …

Has years of citizen-based nutrient sampling and baseline water quality monitoring efforts only had a "trivial" impact on natural resource management decisions? This thesis will explore this and other findings from a qualitative evaluation of the Rock River Coalition (RRC) citizen-based stream monitoring project in Dane County, Wisconsin, USA. These findings are the culmination of 47 semi-structured interviews with decision-makers from seven client-identified categories and participant observations of board meetings and other watershed groups. Interview questions focused on current strategies of data design and dissemination with the goal of constructing a clearer picture of existing data usage by Dane County decision-makers. In the wider picture of citizen science and community-based research, this case study aims to highlight barriers to data use and potential solutions. The results of this case study were understood through four key frames: (1) Bourdieu's concept of symbolic capital, (2) Barzilai‐Nahon's theory of network gatekeeping, (3) Newman et al.'s framework for leveraging the power of place, and (4) a Foucauldian approach to the production of scientific knowledge. The findings of this study highlight the presence of gatekeeping mechanisms within the scientific field as well as government institutions, problematize the practice of placemaking, assert there is untapped symbolic …

Daytime cognitive performance and sleep/wake cycles are strongly interrelated, and cognitive dysfunction has been extensively investigated in relation to insomnia. However, methods and outcomes vary widely by study, making comparison difficult without more systematic evaluation. Review of the literature reveals discrepant findings for the relationship between both subjective and objective measures of cognitive performance and insomnia. The current meta-analysis included 42 studies investigating the relationship between insomnia and cognitive performance. Results confirmed the discrepant nature of previous findings and suggest that type of cognitive performance (e.g., simple attention, procedural memory, verbal functions) is important to consider when discussing the impact of insomnia. Mixed-effect meta-analysis of aggregate effect sizes suggest impairments in working memory, complex attention, and episodic memory are significantly associated with insomnia. Analysis of the grouped subjective cognitive performance effect size revealed no significant impact of insomnia. Average age and gender makeup of the sample, study quality, and type of insomnia measure (i.e., clinical or diagnostic criteria, validated scale, or single unvalidated item) did not consistently moderate findings. These results confirm the equivocal nature of the relationship between insomnia and cognitive performance. Overall, about 44% of the studies included in the analysis failed to use DSM or ICSD criteria …

Running From My Youth: Essays is a collection of nonfiction essays that explore important moments and experiences from the narrator's youth, and how he has addressed and remembered them in the years since. Some of the essays explore the narrator's time as a distance-runner, while others explore the awkwardness and discomfort onset by religion and nudity.

The goal of the current study was to evaluate the ways in which religious behaviors and perceived social support are associated with the relationship between depressive symptoms and health-related quality of life for this group. We hypothesized (1) that religious behaviors moderate the relationship between depressive symptoms and health-related quality of life, (2) perceived social support mediates the relationship between depressive symptoms and health-related quality of life and (3) that religious behaviors moderate the mediational indirect effect of perceived social support in the depression and health-related quality of life relationship. Findings from a sample of 244 HIV-positive individuals provided evidence to support direct, conditional, and indirect effects on the depressive symptoms and health-related quality of life relationship. A discussion of the findings, implications for future research and clinical practice are provided.

This study focuses on dark-skinned, Black women's representation in Black sitcoms. Through a mixed-methods use of a comparative textual analysis and focus group, the content and context of episodes from A Different World and Dear White People are explored to illustrate portrayals of dark-skinned, Black women and how these portrayals affect dark-skinned, Black women's self-esteem. Its findings contribute to colorism research by exploring colorism in Black sitcoms. Because this topic is largely unexplored, this study seeks to begin a conversation about dark skinned, Black women's representation in Black sitcoms. The main objective is to ultimately improve their depictions and roles in Black sitcoms and hold Black creatives responsible for the role they play in promoting colorism and its ultimate effect on Black women's self esteem.

This two-part mixed-methods study analyzed the Twitter activity of two regional magazines – D Magazine and Texas Monthly – and how social media editors implement strategies to maintain journalistic integrity (news values, topics, and ethical standards) while increasing engagement.

Sintering parameter effects on the microstructure of boron carbide and boron carbide/titanium diboride composites are investigated. The resulting microstructure and composition are characterized by scanning electron microscopy (SEM), x-ray microscopy (XRM) and x-ray diffraction (XRD). Starting powder size distribution effects on microstructure are present and effect the mechanical properties. Reactive spark plasma sintering introduces boron nitride (BN) intergranular films (IGF's) and their effects on fracture toughness, hardness and flexural strength are shown. Mechanical testing of Vickers hardness, 3-point bend and Chevron notch was done and the microstructural effects on the resulting mechanical properties are investigated.

High entropy alloys (HEAs) are a new class of solid solution alloys that contain multiple principal elements and possess excellent mechanical properties, from corrosion resistance to fatigue and wear resistance. Even more recently, twinning induced plasticity (TWIP) and transformation induced plasticity (TRIP) non-equiatomic high entropy alloys have been engineered, promising increased strength and ductility as compared to their equiatomic counterparts. However, impact and fracture resistance of these HEAs has not been studied as much as their other mechanical properties. In this thesis, the hardness, tensile properties, and Charpy impact energy of Al0.3CoCrFeNi, a TWIP HEA, and 50Fe-30Mn-10Co-10Cr (at.%), a TRIP HEA, was explored. First, three processing conditions, (1) as-received, (2) recrystallized, and (3) peak hardness, were chosen for each alloy and verified with Vickers microhardness measurements. Next, the tensile properties of each alloy and condition were investigated. Charpy impact specimen size was then selected based on the final plate thickness, and the machined samples were tested. Plastic zone size and change in sample thickness in the deformed region of each condition after testing was measured. Post-impact test inspection of the samples in all conditions showed that the samples were in tension near the V-notch root and in compression at the …

Ulcerative colitis (UC) is a chronic inflammatory disease characterized by periods of relapses and remissions affecting more than 500,000 people in the United States. To achieve the therapeutic goals of UC, which are to first induce and then maintain disease remission, doctors need to evaluate the severity of UC of a patient. However, it is very difficult to evaluate the severity of UC objectively because of non-uniform nature of symptoms and large variations in their patterns. To address this, in our previous works, we developed two different approaches in which one is using the image textures, and the other is using CNN (convolutional neural network) to measure and classify objectively the severity of UC presented in optical colonoscopy video frames. But, we found that the image texture based approach could not handle larger number of variations in their patterns, and the CNN based approach could not achieve very high accuracy. In this paper, we improve our CNN based approach in two ways to provide better accuracy for the classification. We add more thorough and essential preprocessing, and generate more classes to accommodate large variations in their patterns. The experimental results show that the proposed preprocessing can improve the overall accuracy …

With an ever-growing number of publications in the biomedical domain, it becomes likely that important implicit connections between individual concepts of biomedical knowledge are overlooked. Literature based discovery (LBD) is in practice for many years to identify plausible associations between previously unrelated concepts. In this paper, we present a new, completely automatic and interactive system that creates a graph-based knowledge base to capture multifaceted complex associations among biomedical concepts. For a given pair of input concepts, our system auto-generates a list of ranked subgraphs uncovering possible previously unnoticed associations based on context information. To rank these subgraphs, we implement a novel ranking method using the context information obtained by performing random walks on the graph. In addition, we enhance the system by training a Neural Network Classifier to output the likelihood of the two concepts being likely related, which provides better insights to the end user.

This study examined the relationships between the six benefit types and customer loyalty through trust and satisfaction in integrated resorts. A self-administered survey was developed based on previous studies in customer loyalty and was distributed through e-Reward online survey panel. The findings showed that only financial gaming benefits, functional gaming benefits, and psychological non-gaming benefits had impacts on customer attitudinal loyalty and customer behavioral loyalty through trust and satisfaction in integrated resorts. Besides, functional gaming benefits had the most influence on customer loyalty through trust and satisfaction. This study extended existing literature in integrated resorts by showing that benefit types in a loyalty program can build customer attitudinal loyalty and customer behavioral loyalty in integrated resorts. This study also examined different types of benefits affect customer loyalty in different degrees. For operators of integrated resorts, understanding how different benefits of a loyalty program affect customer loyalty will allow them to modify their loyalty programs effectively to increase revenue and maintain customers.

To better understand the impact of type 2 diabetes, the relationship between ethnicity, specifically Mexican/Mexican American ethnicity, and the disease must be further investigated. This study specifically examined the cognitive impact of type 2 diabetes. Data from the 2014 Health and Retirement Study was used to compare the cognitive functioning of non-Hispanic White (n = 10,658) and White Mexican/Mexican American (n = 847) individuals, age 50+ years, with and without type 2 diabetes. Serial 7's and immediate and delayed recall—hypothesized to be more negatively affected by type 2 diabetes and Mexican American status—was compared controlling for age, education, and depression. A multivariate analysis of covariance (MANCOVA) indicated significant main effects for race/ethnicity (F(3,11496) = 11.15, p < .001) and diabetes status (F(3,11496) = 3.15, p < .024), with Mexican Americans and those with diabetes having worse cognitive performance. There were significant effects for all covariates. A step-wise multiple regression indicated that education, age, depression, race/ethnicity and diabetes status accounted for a combined 28.4% of variance in a cognitive performance composite. Implications for assessment and treatment are discussed.

Retail clinics are walk-in clinics designed for convenience and for servicing minor health issues and certain acute conditions. The model began as a way of bringing both convenience and care to areas that have lower levels of access to primary care resources. With the implementation of Affordable Care Act (ACA) in March 2010, populations that were previously uninsured were now required to have access to some level of health insurance. These populations presented a potential new market for retail clinics. This research shows that post implementation of the ACA, retail clinics tend to locate in areas with higher incomes and, generally, greater access to primary care.