The body matters: Understanding social differences in mental health

This doctoral dissertation illuminates the salience of body image to sociological investigations of mental health. It is argued that concerns over body-appearance evident in America embody a dimension of distress over the physical self that may be appropriately considered a mental health outcome, called body dysphoria. Using cross-sectional data on 1,183 young adults comprising Hispanic, African American, and non-Hispanic white males and females from varying social classes, a valid and reliable measure of body dysphoria is developed and demonstrated to be a distinct dimension of psychological distress. ^ From the standpoint of the sociology of mental health, the social distribution of body dysphoria makes known individual consequences of the stratified arrangements of society based on gender, race/ethnicity, and social class. Results reveal significant social differences in body dysphoria that are both consistent with and contrary to clinical studies attributing eating disorders to white, upper-class females. Body dysphoria is substantially greater among females supporting that unrealistic cultural ideals and standards of body-appearance remain disproportionately targeted at females in the development and presentation of self. Compared to non-Hispanic whites, Hispanics exhibit higher average levels of body dysphoria while African Americans exhibit lower levels of comparable proportion. The question is addressed whether identification with the dominant (white) culture influences distress over body-appearance among racial/ethnic minorities. A small inverse association is revealed between social class origin and body dysphoria suggesting that individuals from lower social class backgrounds are as greatly affected by body image concerns generally presumed to preoccupy upper social classes. ^ The stress process is a widely used theoretical paradigm for explaining structurally driven social differences in mental health outcomes. New evidence is introduced that the stress process may contribute to understanding body image problems. Regression analyses reveal that stress exposure has a significant positive association with body dysphoria that is mediated by varying psychosocial resources. Overall, the stress process explains the effects of social class origin and African American race/ethnicity on body dysphoria but does not account for the larger effects of being female or Hispanic. ^

Physical dynamic simulation of shipboard power system components in a distributed computational environment

Shipboard power systems have different characteristics than the utility power systems. In the Shipboard power system it is crucial that the systems and equipment work at their peak performance levels. One of the most demanding aspects for simulations of the Shipboard Power Systems is to connect the device under test to a real-time simulated dynamic equivalent and in an environment with actual hardware in the Loop (HIL). The real time simulations can be achieved by using multi-distributed modeling concept, in which the global system model is distributed over several processors through a communication link. The advantage of this approach is that it permits the gradual change from pure simulation to actual application. In order to perform system studies in such an environment physical phase variable models of different components of the shipboard power system were developed using operational parameters obtained from finite element (FE) analysis. These models were developed for two types of studies low and high frequency studies. Low frequency studies are used to examine the shipboard power systems behavior under load switching, and faults. High-frequency studies were used to predict abnormal conditions due to overvoltage, and components harmonic behavior. Different experiments were conducted to validate the developed models. The Simulation and experiment results show excellent agreement. The shipboard power systems components behavior under internal faults was investigated using FE analysis. This developed technique is very curial in the Shipboard power systems faults detection due to the lack of comprehensive fault test databases. A wavelet based methodology for feature extraction of the shipboard power systems current signals was developed for harmonic and fault diagnosis studies. This modeling methodology can be utilized to evaluate and predicate the NPS components future behavior in the design stage which will reduce the development cycles, cut overall cost, prevent failures, and test each subsystem exhaustively before integrating it into the system.

Freeway travel time estimation and prediction using dynamic neural networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. ^ This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.^

The influence of body size on the ecology of coastal fish predators in the Bahamas

Body size is a fundamental structural characteristic of organisms, determining critical life history and physiological traits, and influencing population dynamics, community structure, and ecosystem function. For my dissertation, I focused on effects of body size on habitat use and diet of important coastal fish predators, as well as their influence on faunal communities in Bahamian wetlands. First, using acoustic telemetry and stable isotope analysis, I identified high variability in movement patterns and habitat use among individuals within a gray snapper (Lutjanus griseus) and schoolmaster snapper (L. apodus) population. This intrapopulation variation was not explained by body size, but by individual behavior in habitat use. Isotope values differed between individuals that moved further distances and individuals that stayed close to their home sites, suggesting movement differences were related to specific patterns of foraging behavior. Subsequently, while investigating diet of schoolmaster snapper over a two-year period using stomach content and stable isotope analyses, I also found intrapopulation diet variation, mostly explained by differences in size class, individual behavior and temporal variability. I then developed a hypothesis-testing framework examining intrapopulation niche variation between size classes using stable isotopes. This framework can serve as baseline to categorize taxonomic or functional groupings into specific niche shift scenarios, as well as to help elucidate underlying mechanisms causing niche shifts in certain size classes. Finally, I examined the effect of different-sized fish predators on epifaunal community structure in shallow seagrass beds using exclusion experiments at two spatial scales. Overall, I found that predator effects were rather weak, with predator size and spatial scale having no impact on the community. Yet, I also found some evidence of strong interactions on particular common snapper prey. As Bahamian wetlands are increasingly threatened by human activities (e.g., overexploitation, habitat degradation), an enhanced knowledge of the ecology of organisms inhabiting these systems is crucial for developing appropriate conservation and management strategies. My dissertation research contributed to this effort by providing critical information about the resource use of important Bahamian fish predators, as well as their effect on faunal seagrass communities.

High energy three -body breakup of three -nucleon systems

The main goal of this dissertation was to study two- and three-nucleon Short Range Correlations (SRCs) in high energy three-body breakup of 3He nucleus in 3He(e, e'NN) N reaction. SRCs are characterized by quantum fluctuations in nuclei during which constituent nucleons partially overlap with each other. ^ A theoretical framework is developed within the Generalized Eikonal Approximation (GEA) which upgrades existing medium-energy methods that are inapplicable for high momentum and energy transfer reactions. High momentum and energy transfer is required to provide sufficient resolution for probing SRCs. GEA is a covariant theory which is formulated through the effective Feynman diagrammatic rules. It allows self-consistent calculation of single and double re-scatterings amplitudes which are present in three-body breakup processes. The calculations were carried out in detail and the analytical result for the differential cross section of 3He(e, e'NN)N reaction was derived in a form applicable for programming and numerical calculations. The corresponding computer code has been developed and the results of computation were compared to the published experimental data, showing satisfactory agreement for a wide range of values of missing momenta. ^ In addition to the high energy approximation this study exploited the exclusive nature of the process under investigation to gain more information about the SRCs. The description of the exclusive 3He( e, e'NN)N reaction has been done using the formalism of the nuclear decay function, which is a practically unexplored quantity and is related to the conventional spectral function through the integration of the phase space of the recoil nucleons. Detailed investigation showed that the decay function clearly exhibits the main features of two- and three-nucleon correlations. Four highly practical types of SRCs in 3He nucleus were discussed in great detail for different orders of the final state re-interactions using the decay function as an unique identifying tool. ^ The overall conclusion in this dissertation suggests that the investigation of the decay function opens up a completely new venue in studies of short range nuclear properties. ^

Managing small-scale commercial fisheries for adaptive capacity: Insights from dynamic social-ecological drivers of change in Monterey Bay

Globally, small-scale fisheries (SSFs) are driven by climate, governance, and market factors of social-ecological change, presenting both challenges and opportunities. The ability of small-scale fishermen and buyers to adapt to changing conditions allows participants to survive economic or environmental disturbances and to benefit from optimal conditions. This study presented here identifies key large-scale factors that drive SSFs in California to shift focus among targets and that dictate long-term trends in landings. We use Elinor Ostrom’s Social-Ecological System (SES) framework to apply an interdisciplinary approach when identifying potential factors and when understanding the complex dynamics of these fisheries. We analyzed the interactions among Monterey Bay SSFs over the past four decades since the passage of the Magnuson Stevens Fisheries Conservation and Management Act of 1976. In this region, the Pacific sardine (Sardinops sagax), northern anchovy (Engraulis mordax), and market squid (Loligo opalescens) fisheries comprise a tightly linked system where shifting focus among fisheries is a key element to adaptive capacity and reduced social and ecological vulnerability. Using a cluster analysis of landings, we identified four modes from 1974 to 2012 that were dominated by squid, sardine, anchovy, or lacked any dominance, enabling us to identify external drivers attributed to a change in fishery dominance during seven distinct transition points. Overall, we show that market and climate factors drive the transitions among dominance modes. Governance phases most dictated long-term trends in landings and are best viewed as a response to changes in perceived biomass and thus a proxy for biomass. Our findings suggest that globally, small-scale fishery managers should consider enabling shifts in effort among fisheries and retaining existing flexibility, as adaptive capacity is a critical determinant for social and ecological resilience.

Dynamic job quoting system for printed circuit board fabrication

This research deals with the development of a dynamic job quotation system for printed circuit board (PCB) fabrication, which can estimate the price and completion time of a job based on customer preference and current capacity of the shop floor. The primary purpose of building a dynamic quotation system is to maximize the company's profit by quoting optimum lead-time and competitive price for the day-to-day orders received from different customers and original equipment manufacturers. The system was developed using MS-Access relational database. Evaluating the output of the system it was observed that the dynamic system provided more reliable estimation of the lead-time needed for fabricating new jobs. The overall price quoted by the system was competitive with higher profit margin when compared to traditional static systems. This system would therefore provide a vital link between the job quoting and scheduling system of the firm enabling better utilization of the available resources.

Freeway Travel Time Estimation and Prediction Using Dynamic Neural Networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.

Physical dynamic simulation of shipboard power system components in a distributed computational environment

Shipboard power systems have different characteristics than the utility power systems. In the Shipboard power system it is crucial that the systems and equipment work at their peak performance levels. One of the most demanding aspects for simulations of the Shipboard Power Systems is to connect the device under test to a real-time simulated dynamic equivalent and in an environment with actual hardware in the Loop (HIL). The real time simulations can be achieved by using multi-distributed modeling concept, in which the global system model is distributed over several processors through a communication link. The advantage of this approach is that it permits the gradual change from pure simulation to actual application. In order to perform system studies in such an environment physical phase variable models of different components of the shipboard power system were developed using operational parameters obtained from finite element (FE) analysis. These models were developed for two types of studies low and high frequency studies. Low frequency studies are used to examine the shipboard power systems behavior under load switching, and faults. High-frequency studies were used to predict abnormal conditions due to overvoltage, and components harmonic behavior. Different experiments were conducted to validate the developed models. The Simulation and experiment results show excellent agreement. The shipboard power systems components behavior under internal faults was investigated using FE analysis. This developed technique is very curial in the Shipboard power systems faults detection due to the lack of comprehensive fault test databases. A wavelet based methodology for feature extraction of the shipboard power systems current signals was developed for harmonic and fault diagnosis studies. This modeling methodology can be utilized to evaluate and predicate the NPS components future behavior in the design stage which will reduce the development cycles, cut overall cost, prevent failures, and test each subsystem exhaustively before integrating it into the system.

High energy three-body breakup of three-nucleon systems

The main goal of this dissertation was to study two- and three-nucleon Short Range Correlations (SRCs) in high energy three-body breakup of 3He nucleus in 3He(e, e'NN)N reaction. SRCs are characterized by quantum fluctuations in nuclei during which constituent nucleons partially overlap with each other. A theoretical framework is developed within the Generalized Eikonal Approximation (GEA) which upgrades existing medium-energy methods that are inapplicable for high momentum and energy transfer reactions. High momentum and energy transfer is required to provide sufficient resolution for probing SRCs. GEA is a covariant theory which is formulated through the effective Feynman diagrammatic rules. It allows self-consistent calculation of single and double re-scatterings amplitudes which are present in three-body breakup processes. The calculations were carried out in detail and the analytical result for the differential cross section of 3He(e, e'NN)Nreaction was derived in a form applicable for programming and numerical calculations. The corresponding computer code has been developed and the results of computation were compared to the published experimental data, showing satisfactory agreement for a wide range of values of missing momenta. In addition to the high energy approximation this study exploited the exclusive nature of the process under investigation to gain more information about the SRCs. The description of the exclusive 3He(e, e'NN)N reaction has been done using the formalism of the nuclear decay function, which is a practically unexplored quantity and is related to the conventional spectral function through the integration of the phase space of the recoil nucleons. Detailed investigation showed that the decay function clearly exhibits the main features of two- and three-nucleon correlations. Four highly practical types of SRCs in 3He nucleus were discussed in great detail for different orders of the final state re-interactions using the decay function as an unique identifying tool. The overall conclusion in this dissertation suggests that the investigation of the decay function opens up a completely new venue in studies of short range nuclear properties.