Development of thresholds for surface preparation in repair systems with wet lay -up fiber reinforced polymers

Bonded repair of concrete structures with fiber reinforced polymer (FRP) systems is increasingly being accepted as a cost-efficient and structurally viable method of rapid rehabilitation of concrete structures. However, the relationships between long-term performance attributes, service-life, and details of the installation process are not easy to quantify. Accordingly, there is currently a lack of generally accepted construction specifications, making it difficult for the field engineer to certify the adequacy of the construction process. ^ The objective of the present study, as part of the National Cooperative Highway Research Program (NCHRP) Project 10-59B, was to investigate the effect of surface preparation on the behavior of wet lay-up FRP repair systems and consequently develop rational thresholds that provide sufficient performance. ^ The research program was comprised of both experimental and analytical work for wet lay-up FRP applications. The experimental work included flexure testing of sixty-seven (67) reinforced concrete beams and bond testing of ten (10) reinforced concrete blocks. Four different parameters were studied: surface roughness, surface flatness, surface voids and bug holes, and surface cracks/cuts. The findings were analyzed from various aspects and compared with the data available in the literature. As part of the analytical work, finite element models of the flexural specimens with surface flaws were developed using ANSYS. The purpose of this part was to extend the parametric study on the effects of concrete surface flaws and verify the experimental results based on nonlinear finite element analysis. ^ Test results showed that surface roughness does not appear to have a significant influence on the overall performance of the wet lay-up FRP systems with or without adequate anchorage, and whether failure was by debonding or rupture of FRP. Both experimental and analytical results for surface flatness proved that peaks on concrete surface, in the range studied, do not have a significant effect on the performance of wet lay-up FRP systems. However, valleys of particular size could reduce the strength of wet lay-up FRP systems. Test results regarding surface voids and surface cracks/cuts revealed that previously suggested thresholds for these flaws appear to be conservative, as also confirmed by analytical study. ^

Monitoring of Tree Island Condition in the Southern Everglades: Hydrologic Driven Decadal Changes in Tree Island Woody Vegetation Structure and Composition: 2012 Annual Report

This report examines the interaction between hydrology and vegetation over a 10-year period, between 2001/02 and 2012 within six permanent tree island plots located on three tree islands, two plots each per tree island, established in 2001/02, along a hydrologic and productivity gradient. We hypothesize that: (H1) hydrologic differences within plots between census dates will result in marked differences in a) tree and sapling densities, b) tree basal area, and c) forest structure, i.e., canopy volume and height, and (H2) tree island growth, development, and succession is dependent on hydrologic fluxes, particularly during periods of prolonged droughts or below average hydroperiods.

Statistical dialog management for health interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. ^ Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. ^ The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. ^ In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.^

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Effects of Adolescent Depressive Symptoms, Pubertal Development, and Interpersonal Relationship Satisfaction on Sexual Risk Behaviors in Adolescent Romantic Couples

This study examined links between adolescent depressive symptoms, actual pubertal development, perceived pubertal timing relative to one’s peers, adolescent-maternal relationship satisfaction, and couple sexual behavior. Assessments of these variables were made on each couple member separately and then these variables were used to predict the sexual activity of the couple. Participants were drawn from the National Longitudinal Study of Adolescent Health (Add Health; Bearman et al., 1997; Udry, 1997) data set (N = 20,088; aged 12-18 years). Dimensions of adolescent romantic experiences using the total sample were described and then a subsample of romantically paired adolescents (n = 1,252) were used to test a risk and protective model for predicting couple sexual behavior using the factors noted above. Relevant measures from the Wave 1 Add Health measures were used. Most of the items used in Add Health to assess romantic relationship experiences, adolescent depressive symptoms, pubertal development (actual and perceived), adolescent-maternal relationship satisfaction, and couple sexual behavior were drawn from other national surveys or from scales with well documented psychometric properties. Results demonstrated that romantic relationships are part of most adolescents’ lives and that adolescents’ experiences with these relationships differ markedly by age, sex, and race/ethnicity. Further, each respective couple member’s pubertal development, perceived pubertal timing, and maternal relationship satisfaction were useful in predicting sexual risk-promoting and risk-reducing behaviors in adolescent romantic couples. Findings in this dissertation represent an initial step toward evaluating explanatory models of adolescent couple sexual behavior.

Development of Innovative Load Transfer Mechanism to Reduce Hurricane-Induced Failures in New and Existing Residential Construction

Implicit in current design practice of minimum uplift capacity, is the assumption that the connection's capacity is proportional to the number of fasteners per connection joint. This assumption may overestimate the capacity of joints by a factor of two or more and maybe the cause of connection failures in extreme wind events. The current research serves to modify the current practice by proposing a realistic relationship between the number of fasteners and the capacity of the joint. The research is also aimed at further development of non-intrusive continuous load path (CLP) connection system using Glass Fiber Reinforced Polymer (GFRP) and epoxy. Suitable designs were developed for stud to top plate and gable end connections and tests were performed to evaluate the ultimate load, creep and fatigue behavior. The objective was to determine the performance of the connections under simulated sustained hurricane conditions. The performance of the new connections was satisfactory.

Perceived and actual sex differences in attributional style for affiliative behavior

The objectives of this thesis were threefold: (1) to review the concept of attributional style, (2) to demonstrate its applicability to affiliative behavior, and (3) to document the existence of actual and perceived sex differences in attributional style for affiliative behavior. To fulfill the first two objectives the development of attributional theory was traced from the Abramson, Seligman, and Teasdale (1978) presentation of the reformulated learned helplessness model through Weiner's (1979) examination of attributional style as a motivational feature of achievement behavior to the application of attribution theory to affiliative behavior. To fulfill the third objective the evidence detailing the sex differences in achievement and affiliative attributional styles was reviewed within the framework of perceptions of sex appropriate behavior. A study was then designed to assess both actual and perceived affiliative attributional sex differences. The Escovar, Brown, and Rodriguez Attributional Style Questionnaire for Affiliative Behavior was administered to 107 male and female University of Miami and Florida International University students. Each subject answered the questionnaire twice, once for themselves and once as if they were a member of the opposite sex. The results indicated that the EBR-ASQ maintained previous levels of internal consistency and reliability. Analyses performed on the covariate of the order of perspective presentation were negative; all further analyses were performed without a covariate. The data were analyzed using a 2(Sex) X 2(Perspective) X 2(Outcome) factorial, multivariate, repeated measures design with the three attributional dimensions serving as the dependent variable repeated measures. As expected all multivariate tests revealed that each of the three factors was a significant influence over all three of the dependent variables. Of the 21 univariate tests 12 of the main effect and two-way interactions were significant and one approached significance. Examination of the means revealed that of the eight significant main effects six were in the expected direction; of the four significant two-way interactions three were in the expected direction. Although the results were not totally supportive of the hypotheses they did support the thesis that affiliation is the female sex-role appropriate analogue to male achievement behavior.

The utility of an integrated qualitative/quantitative data analytic strategy (IQ-DAS) to evaluate the impact of youth development interventions on positive qualitative change in the life course

This study reports one of the first controlled studies to examine the impact of a school based positive youth development program (Lerner, Fisher, & Weinberg, 2000) on promoting qualitative change in life course experiences as a positive intervention outcome. The study built on a recently proposed relational developmental methodological metanarrative (Overton, 1998) and advances in use of qualitative research methods (Denzin & Lincoln, 2000). The study investigated the use the Life Course Interview (Clausen, 1998) and an integrated qualitative and quantitative data analytic strategy (IQDAS) to provide empirical documentation of the impact the Changing Lives Program on qualitative change in positive identity in a multicultural population of troubled youth in an alternative public high school. The psychosocial life course intervention approach used in this study draws its developmental framework from both psychosocial developmental theory (Erikson, 1968) and life course theory (Elder, 1998) and its intervention strategies from the transformative pedagogy of Freire's (1983/1970). Using the 22 participants in the Intervention Condition and the 10 participants in the Control Condition, RMANOVAs found significantly more positive qualitative change in personal identity for program participants relative to the non-intervention control condition. In addition, the 2X2X2X3 mixed design RMANOVA in which Time (pre, post) was the repeated factor and Condition (Intervention versus Control), Gender, and Ethnicity the between group factors, also found significant interactions for the Time by Gender and Time by Ethnicity. Moreover, the directionality of the basic pattern of change was positive for participants of both genders and all three ethnic groups. The pattern of the moderation effects also indicated a marked tendency for participants in the intervention group to characterize their sense of self as more secure and less negative at the end of the their first semester in the intervention, that was stable across both genders and all three ethnicities. The basic differential pattern of an increase in the intervention condition of a positive characterization of sense of self relative to both pre test and relative to the directionality of the movement of the non-intervention controls, was stable across both genders and all three ethnic groups.

Data compilation on the biological response to ocean acidification: environmental and experimental context of data sets and related literature

The exponential growth of studies on the biological response to ocean acidification over the last few decades has generated a large amount of data. To facilitate data comparison, a data compilation hosted at the data publisher PANGAEA was initiated in 2008 and is updated on a regular basis (doi:10.1594/PANGAEA.149999). By January 2015, a total of 581 data sets (over 4 000 000 data points) from 539 papers had been archived. Here we present the developments of this data compilation five years since its first description by Nisumaa et al. (2010). Most of study sites from which data archived are still in the Northern Hemisphere and the number of archived data from studies from the Southern Hemisphere and polar oceans are still relatively low. Data from 60 studies that investigated the response of a mix of organisms or natural communities were all added after 2010, indicating a welcomed shift from the study of individual organisms to communities and ecosystems. The initial imbalance of considerably more data archived on calcification and primary production than on other processes has improved. There is also a clear tendency towards more data archived from multifactorial studies after 2010. For easier and more effective access to ocean acidification data, the ocean acidification community is strongly encouraged to contribute to the data archiving effort, and help develop standard vocabularies describing the variables and define best practices for archiving ocean acidification data.

Labeling large scale social media data using budget-driven One-class SVM classification

The social media classification problems draw more and more attention in the past few years. With the rapid development of Internet and the popularity of computers, there is astronomical amount of information in the social network (social media platforms). The datasets are generally large scale and are often corrupted by noise. The presence of noise in training set has strong impact on the performance of supervised learning (classification) techniques. A budget-driven One-class SVM approach is presented in this thesis that is suitable for large scale social media data classification. Our approach is based on an existing online One-class SVM learning algorithm, referred as STOCS (Self-Tuning One-Class SVM) algorithm. To justify our choice, we first analyze the noise-resilient ability of STOCS using synthetic data. The experiments suggest that STOCS is more robust against label noise than several other existing approaches. Next, to handle big data classification problem for social media data, we introduce several budget driven features, which allow the algorithm to be trained within limited time and under limited memory requirement. Besides, the resulting algorithm can be easily adapted to changes in dynamic data with minimal computational cost. Compared with two state-of-the-art approaches, Lib-Linear and kNN, our approach is shown to be competitive with lower requirements of memory and time.

Development of a high-frequency surface-wave radar cross section model for icebergs

In this thesis, the first-order radar cross section (RCS) of an iceberg is derived and simulated. This analysis takes place in the context of a monostatic high frequency surface wave radar with a vertical dipole source that is driven by a pulsed waveform. The starting point of this work is a general electric field equation derived previ- ously for an arbitrarily shaped iceberg region surrounded by an ocean surface. The condition of monostatic backscatter is applied to this general field equation and the resulting expression is inverse Fourier transformed. In the time domain the excitation current of the transmit antenna is specified to be a pulsed sinusoid signal. The result- ing electric field equation is simplified and its physical significance is assessed. The field equation is then further simplified by restricting the iceberg's size to fit within a single radar patch width. The power received by the radar is calculated using this electric field equation. Comparing the received power with the radar range equation gives a general expression for the iceberg RCS. The iceberg RCS equation is found to depend on several parameters including the geometry of the iceberg, the radar frequency, and the electrical parameters of both the iceberg and the ocean surface. The RCS is rewritten in a form suitable for simulations and simulations are carried out for rectangularly shaped icebergs. Simulation results are discussed and are found to be consistent with existing research.

E-service quality:development of a hierarchical model

Using survey data from 358 online customers, the study finds that the e-service quality construct conforms to the structure of a third-order factor model that links online service quality perceptions to distinct and actionable dimensions, including (1) website design, (2) fulfilment, (3) customer service, and (4) security/privacy. Each dimension is found to consist of several attributes that define the basis of e-service quality perceptions. A comprehensive specification of the construct, which includes attributes not covered in existing scales, is developed. The study contrasts a formative model consisting of 4 dimensions and 16 attributes against a reflective conceptualization. The results of this comparison indicate that studies using an incorrectly specified model overestimate the importance of certain e-service quality attributes. Global fit criteria are also found to support the detection of measurement misspecification. Meta-analytic data from 31,264 online customers are used to show that the developed measurement predicts customer behavior better than widely used scales, such as WebQual and E-S-Qual. The results show that the new measurement enables managers to assess e-service quality more accurately and predict customer behavior more reliably.

Colorado's Piceance Basin: Variation in the local public finance effects of oil and gas development

A large increase in natural gas production occurred in western Colorado’s Piceance basin in the mid- to late-2000s, generating a surge in population, economic activity, and heavy truck traffic in this rural region. We describe the fiscal effects related to this development for two county governments: Garfield and Rio Blanco, and two city governments: Grand Junction and Rifle. Counties maintain rural road networks in Colorado, and Garfield County’s ability to fashion agreements with operators to repair roads damaged during operations helped prevent the types of large new costs seen in Rio Blanco County, a neighboring county with less government capacity and where such agreements were not made. Rifle and Grand Junction experienced substantial oil- and gas-driven population growth, with greater challenges in the smaller, more isolated, and less economically diverse city of Rifle. Lessons from this case study include the value of crafting road maintenance agreements, fiscal risks for small and geographically isolated communities experiencing rapid population growth, challenges associated with limited infrastructure, and the desirability of flexibility in the allocation of oil- and gas-related revenue.

Global Mental Health: Five Areas for Value-Driven Training Innovation.

OBJECTIVE: In the field of global mental health, there is a need for identifying core values and competencies to guide training programs in professional practice as well as in academia. This paper presents the results of interdisciplinary discussions fostered during an annual meeting of the Society for the Study of Psychiatry and Culture to develop recommendations for value-driven innovation in global mental health training. METHODS: Participants (n = 48), who registered for a dedicated workshop on global mental health training advertised in conference proceedings, included both established faculty and current students engaged in learning, practice, and research. They proffered recommendations in five areas of training curriculum: values, competencies, training experiences, resources, and evaluation. RESULTS: Priority values included humility, ethical awareness of power differentials, collaborative action, and "deep accountability" when working in low-resource settings in low- and middle-income countries and high-income countries. Competencies included flexibility and tolerating ambiguity when working across diverse settings, the ability to systematically evaluate personal biases, historical and linguistic proficiency, and evaluation skills across a range of stakeholders. Training experiences included didactics, language training, self-awareness, and supervision in immersive activities related to professional or academic work. Resources included connections with diverse faculty such as social scientists and mentors in addition to medical practitioners, institutional commitment through protected time and funding, and sustainable collaborations with partners in low resource settings. Finally, evaluation skills built upon community-based participatory methods, 360-degree feedback from partners in low-resource settings, and observed structured clinical evaluations (OSCEs) with people of different cultural backgrounds. CONCLUSIONS: Global mental health training, as envisioned in this workshop, exemplifies an ethos of working through power differentials across clinical, professional, and social contexts in order to form longstanding collaborations. If incorporated into the ACGME/ABPN Psychiatry Milestone Project, such recommendations will improve training gained through international experiences as well as the everyday training of mental health professionals, global health practitioners, and social scientists.

Development and Optimization of Four-dimensional Magnetic Resonance Imaging (4D-MRI) for Radiation Therapy

A tenet of modern radiotherapy (RT) is to identify the treatment target accurately, following which the high-dose treatment volume may be expanded into the surrounding tissues in order to create the clinical and planning target volumes. Respiratory motion can induce errors in target volume delineation and dose delivery in radiation therapy for thoracic and abdominal cancers. Historically, radiotherapy treatment planning in the thoracic and abdominal regions has used 2D or 3D images acquired under uncoached free-breathing conditions, irrespective of whether the target tumor is moving or not. Once the gross target volume has been delineated, standard margins are commonly added in order to account for motion. However, the generic margins do not usually take the target motion trajectory into consideration. That may lead to under- or over-estimate motion with subsequent risk of missing the target during treatment or irradiating excessive normal tissue. That introduces systematic errors into treatment planning and delivery. In clinical practice, four-dimensional (4D) imaging has been popular in For RT motion management. It provides temporal information about tumor and organ at risk motion, and it permits patient-specific treatment planning. The most common contemporary imaging technique for identifying tumor motion is 4D computed tomography (4D-CT). However, CT has poor soft tissue contrast and it induce ionizing radiation hazard. In the last decade, 4D magnetic resonance imaging (4D-MRI) has become an emerging tool to image respiratory motion, especially in the abdomen, because of the superior soft-tissue contrast. Recently, several 4D-MRI techniques have been proposed, including prospective and retrospective approaches. Nevertheless, 4D-MRI techniques are faced with several challenges: 1) suboptimal and inconsistent tumor contrast with large inter-patient variation; 2) relatively low temporal-spatial resolution; 3) it lacks a reliable respiratory surrogate. In this research work, novel 4D-MRI techniques applying MRI weightings that was not used in existing 4D-MRI techniques, including T2/T1-weighted, T2-weighted and Diffusion-weighted MRI were investigated. A result-driven phase retrospective sorting method was proposed, and it was applied to image space as well as k-space of MR imaging. Novel image-based respiratory surrogates were developed, improved and evaluated.