Horizontal genetic transfer in asexual fungi

Four aspects of horizontal genetic transfer during heterokaryon formation were examined in the asexual pathogen Fusarium oxysporum f.sp. cubense (Foc): (1) variability based on method of heterokaryon formation; (2) differences in nuclear and mitochondrial inheritance; (3) the occurrence of recombination without nuclear fusion; (4) the occurrence of horizontal genetic transfer between distantly related isolates. The use of non-pathogenic strains of Fusarium oxysporum as biocontrol agents warrants a closer examination at the reproductive life cycle of this fungus, particularly if drug resistance or pathogenicity genes can be transmitted horizontally. Experiments were divided into three phases. Phase I looked at heterokaryon formation by hyphal anastomosis and protoplast fusion. Phase II was a time course of heterokaryon formation to look at patterns of nuclear and mitochondrial inheritance. Phase III examined the genetic relatedness of the different vegetative compatibility groups using a multilocus analysis approach. Heterokaryon formation was evident within and between vegetative compatibility groups. Observation of non-parental genotypes after heterokaryon formation confirmed that, although a rare event, horizontal genetic transfer occurred during heterokaryon formation. Uniparental mitochondria inheritance was observed in heterokaryons formed either by hyphal anastomosis or protoplast fusion. Drug resistance was expressed during heterokaryon formation, even across greater genetic distances than those distances imposed by vegetative compatibility. Phylogenies inferred from different molecular markers were incongruent at a significant level, challenging the clonal origins of Foc. Mating type genes were identified in this asexual pathogen Polymorphisms were detected within a Vegetative Compatibility Group (VCG) suggesting non-clonal inheritance and/or sexual recombination in Foc. This research was funded in part by a NIH-NIGMS (National Institutes of Health-National Institute of General Medical Sciences) Grant through the MBRS (Minority Biomedical Research Support), the Department of Biological Sciences and the Tropical Biology Program at FIU. ^

An agent-based model of team coordination and performance

This research is based on the premises that teams can be designed to optimize its performance, and appropriate team coordination is a significant factor to team outcome performance. Contingency theory argues that the effectiveness of a team depends on the right fit of the team design factors to the particular job at hand. Therefore, organizations need computational tools capable of predict the performance of different configurations of teams. This research created an agent-based model of teams called the Team Coordination Model (TCM). The TCM estimates the coordination load and performance of a team, based on its composition, coordination mechanisms, and job’s structural characteristics. The TCM can be used to determine the team’s design characteristics that most likely lead the team to achieve optimal performance. The TCM is implemented as an agent-based discrete-event simulation application built using JAVA and Cybele Pro agent architecture. The model implements the effect of individual team design factors on team processes, but the resulting performance emerges from the behavior of the agents. These team member agents use decision making, and explicit and implicit mechanisms to coordinate the job. The model validation included the comparison of the TCM’s results with statistics from a real team and with the results predicted by the team performance literature. An illustrative 26-1 fractional factorial experimental design demonstrates the application of the simulation model to the design of a team. The results from the ANOVA analysis have been used to recommend the combination of levels of the experimental factors that optimize the completion time for a team that runs sailboats races. This research main contribution to the team modeling literature is a model capable of simulating teams working on complex job environments. The TCM implements a stochastic job structure model capable of capturing some of the complexity not capture by current models. In a stochastic job structure, the tasks required to complete the job change during the team execution of the job. This research proposed three new types of dependencies between tasks required to model a job as a stochastic structure. These dependencies are conditional sequential, single-conditional sequential, and the merge dependencies.

A theory of constraints service systems improvement method: Case of the airline turnaround problem

This dissertation develops a process improvement method for service operations based on the Theory of Constraints (TOC), a management philosophy that has been shown to be effective in manufacturing for decreasing WIP and improving throughput. While TOC has enjoyed much attention and success in the manufacturing arena, its application to services in general has been limited. The contribution to industry and knowledge is a method for improving global performance measures based on TOC principles. The method proposed in this dissertation will be tested using discrete event simulation based on the scenario of the service factory of airline turnaround operations. To evaluate the method, a simulation model of aircraft turn operations of a U.S. based carrier was made and validated using actual data from airline operations. The model was then adjusted to reflect an application of the Theory of Constraints for determining how to deploy the scarce resource of ramp workers. The results indicate that, given slight modifications to TOC terminology and the development of a method for constraint identification, the Theory of Constraints can be applied with success to services. Bottlenecks in services must be defined as those processes for which the process rates and amount of work remaining are such that completing the process will not be possible without an increase in the process rate. The bottleneck ratio is used to determine to what degree a process is a constraint. Simulation results also suggest that redefining performance measures to reflect a global business perspective of reducing costs related to specific flights versus the operational local optimum approach of turning all aircraft quickly results in significant savings to the company. Savings to the annual operating costs of the airline were simulated to equal 30% of possible current expenses for misconnecting passengers with a modest increase in utilization of the workers through a more efficient heuristic of deploying them to the highest priority tasks. This dissertation contributes to the literature on service operations by describing a dynamic, adaptive dispatch approach to manage service factory operations similar to airline turnaround operations using the management philosophy of the Theory of Constraints.

The influence of gender on perceived treatment need among a community sample of substance users

Purpose: Most individuals do not perceive a need for substance use treatment despite meeting diagnostic criteria for substance use disorders and they are least likely to pursue treatment voluntarily. There are also those who perceive a need for treatment and yet do not pursue it. This study aimed to understand which factors increase the likelihood of perceiving a need for treatment for individuals who meet diagnostic criteria for substance use disorders in the hopes to better assist with more targeted efforts for gender-specific treatment recruitment and retention. Using Andersen and Newman's (1973/2005) model of individual determinants of healthcare utilization, the central hypothesis of the study was that gender moderates the relationship between substance use problem severity and perceived treatment need, so that women with increasing problems due to their use of substances are more likely than men to perceive a need for treatment. Additional predisposing and enabling factors from Andersen and Newman's (1973/2005) model were included in the study to understand their impact on perceived need. Method: The study was a secondary data analysis of the 2010 National Survey on Drug Use and Health (NSDUH) using logistic regression. The weighted sample consisted of a total 20,077,235 American household residents (The unweighted sample was 5,484 participants). Results of the logistic regression were verified using Relogit software for rare events logistic regression due to the rare event of perceived treatment need (King & Zeng, 2001a; 2001b). Results: The moderating effect of female gender was not found. Conversely, men were significantly more likely than women to perceive a need for treatment as substance use problem severity increased. The study also found that a number of factors such as race, ethnicity, socioeconomic status, age, marital status, education, co-occurring mental health disorders, and prior treatment history differently impacted the likelihood of perceiving a need for treatment among men and women. Conclusion: Perceived treatment need among individuals who meet criteria for substance use disorders is rare, but identifying factors associated with an increased likelihood of perceiving need for treatment can help the development of gender-appropriate outreach and recruitment for social work treatment, and public health messages.

Exploring Hidden Coherent Feature Groups and Temporal Semantics for Multimedia Big Data Analysis

Thanks to the advanced technologies and social networks that allow the data to be widely shared among the Internet, there is an explosion of pervasive multimedia data, generating high demands of multimedia services and applications in various areas for people to easily access and manage multimedia data. Towards such demands, multimedia big data analysis has become an emerging hot topic in both industry and academia, which ranges from basic infrastructure, management, search, and mining to security, privacy, and applications. Within the scope of this dissertation, a multimedia big data analysis framework is proposed for semantic information management and retrieval with a focus on rare event detection in videos. The proposed framework is able to explore hidden semantic feature groups in multimedia data and incorporate temporal semantics, especially for video event detection. First, a hierarchical semantic data representation is presented to alleviate the semantic gap issue, and the Hidden Coherent Feature Group (HCFG) analysis method is proposed to capture the correlation between features and separate the original feature set into semantic groups, seamlessly integrating multimedia data in multiple modalities. Next, an Importance Factor based Temporal Multiple Correspondence Analysis (i.e., IF-TMCA) approach is presented for effective event detection. Specifically, the HCFG algorithm is integrated with the Hierarchical Information Gain Analysis (HIGA) method to generate the Importance Factor (IF) for producing the initial detection results. Then, the TMCA algorithm is proposed to efficiently incorporate temporal semantics for re-ranking and improving the final performance. At last, a sampling-based ensemble learning mechanism is applied to further accommodate the imbalanced datasets. In addition to the multimedia semantic representation and class imbalance problems, lack of organization is another critical issue for multimedia big data analysis. In this framework, an affinity propagation-based summarization method is also proposed to transform the unorganized data into a better structure with clean and well-organized information. The whole framework has been thoroughly evaluated across multiple domains, such as soccer goal event detection and disaster information management.

The Influence of Gender on Perceived Treatment Need among a Community Sample of Substance Users

Purpose: Most individuals do not perceive a need for substance use treatment despite meeting diagnostic criteria for substance use disorders and they are least likely to pursue treatment voluntarily. There are also those who perceive a need for treatment and yet do not pursue it. This study aimed to understand which factors increase the likelihood of perceiving a need for treatment for individuals who meet diagnostic criteria for substance use disorders in the hopes to better assist with more targeted efforts for gender-specific treatment recruitment and retention. Using Andersen and Newman’s (1973/2005) model of individual determinants of healthcare utilization, the central hypothesis of the study was that gender moderates the relationship between substance use problem severity and perceived treatment need, so that women with increasing problems due to their use of substances are more likely than men to perceive a need for treatment. Additional predisposing and enabling factors from Andersen and Newman’s (1973/2005) model were included in the study to understand their impact on perceived need. Method: The study was a secondary data analysis of the 2010 National Survey on Drug Use and Health (NSDUH) using logistic regression. The weighted sample consisted of a total 20,077,235 American household residents (The unweighted sample was 5,484 participants). Results of the logistic regression were verified using Relogit software for rare events logistic regression due to the rare event of perceived treatment need (King & Zeng, 2001a; 2001b). Results: The moderating effect of female gender was not found. Conversely, men were significantly more likely than women to perceive a need for treatment as substance use problem severity increased. The study also found that a number of factors such as race, ethnicity, socioeconomic status, age, marital status, education, co-occurring mental health disorders, and prior treatment history differently impacted the likelihood of perceiving a need for treatment among men and women. Conclusion: Perceived treatment need among individuals who meet criteria for substance use disorders is rare, but identifying factors associated with an increased likelihood of perceiving need for treatment can help the development of gender-appropriate outreach and recruitment for social work treatment, and public health messages.