Political corruption in the Caribbean Basin: A comparative analysis of Jamaica and Costa Rica

Political corruption in the Caribbean Basin retards state economic growth and development, undermines government legitimacy, and threatens state security. In spite of recent anti-corruption efforts of intergovernmental and nongovernmental organizations (IGO/NGOs), Caribbean political corruption problems appear to be worsening in the post-Cold War period. This dissertation discovers why IGO/NGO efforts to arrest corruption are failing by investigating the domestic and international causes of political corruption in the Caribbean. The dissertation's theoretical framework centers on an interdisciplinary model of the causes of political corruption built within the rule-oriented constructivist approach to social science. The model first employs a rational choice analysis that broadly explains the varying levels of political corruption found across the region. The constructivist theory of social rules is then used to develop the structural mechanisms that further explain the region's levels of political corruption. The dissertation advances its theory of the causes of political corruption through qualitative disciplined-configurative case studies of political corruption in Jamaica and Costa Rica. The dissertation finds that IGO/NGO sponsored anti-corruption programs are failing because they employ only technical measures (issuing anti-corruption laws and regulations, providing transparency in accounting procedures, improving freedom of the press, establishing electoral reforms, etc.). While these IGO/NGO technical measures are necessary, they are not sufficient to arrest the Caribbean's political corruption problems. This dissertation concludes that to be successful, IGO/NGO anti-corruption programs must also include social measures, e.g., building civil societies and modernizing political cultures, for there to be any hope of lowering political corruption levels and improving Caribbean social conditions. The dissertation also highlights the key role of Caribbean governing elite in constructing the political and economic structures that cause their states' political corruption problems. ^

Valuation of Ecosystem Services for Environmental Decision Making in South Florida

The Greater Everglades system imparts vital ecosystem services (ES) to South Florida residents including high quality drinking water supplies and a habitat for threatened and endangered species. As a result of the altered Everglades system and regional dynamics, restoration may either improve the provision of these services or impose a tradeoff between enhanced environmental goods and services and competing societal demands. The current study aims at understanding public preferences for restoration and generating willingness to pay (WTP) values for restored ES through the implementation of a discrete choice experiment. A previous study (Milon et al., 1999) generated WTP values amongst Floridians of up to $3.42 -$4.07 billion for full restoration over a 10-year period. We have collected data from 2,905 respondents taken from two samples who participated in an online survey designed to elicit the WTP values for selected ecological and social attributes included in the earlier study (Milon et al. 1999). We estimate that the Florida general public is willing to pay up to $854.1- $954.1 million over 10 years to avoid restrictions on their water usage and up to $90.8- $183.7 million over 10 years to restore the hydrological flow within the Water Conservation Area.

Statistical analysis and meta-analysis of microarray data

The microarray technology provides a high-throughput technique to study gene expression. Microarrays can help us diagnose different types of cancers, understand biological processes, assess host responses to drugs and pathogens, find markers for specific diseases, and much more. Microarray experiments generate large amounts of data. Thus, effective data processing and analysis are critical for making reliable inferences from the data. ^ The first part of dissertation addresses the problem of finding an optimal set of genes (biomarkers) to classify a set of samples as diseased or normal. Three statistical gene selection methods (GS, GS-NR, and GS-PCA) were developed to identify a set of genes that best differentiate between samples. A comparative study on different classification tools was performed and the best combinations of gene selection and classifiers for multi-class cancer classification were identified. For most of the benchmarking cancer data sets, the gene selection method proposed in this dissertation, GS, outperformed other gene selection methods. The classifiers based on Random Forests, neural network ensembles, and K-nearest neighbor (KNN) showed consistently god performance. A striking commonality among these classifiers is that they all use a committee-based approach, suggesting that ensemble classification methods are superior. ^ The same biological problem may be studied at different research labs and/or performed using different lab protocols or samples. In such situations, it is important to combine results from these efforts. The second part of the dissertation addresses the problem of pooling the results from different independent experiments to obtain improved results. Four statistical pooling techniques (Fisher inverse chi-square method, Logit method. Stouffer's Z transform method, and Liptak-Stouffer weighted Z-method) were investigated in this dissertation. These pooling techniques were applied to the problem of identifying cell cycle-regulated genes in two different yeast species. As a result, improved sets of cell cycle-regulated genes were identified. The last part of dissertation explores the effectiveness of wavelet data transforms for the task of clustering. Discrete wavelet transforms, with an appropriate choice of wavelet bases, were shown to be effective in producing clusters that were biologically more meaningful. ^

An after tax economic analysis of home equity conversion for the elderly

The FHA program to insure reverse mortgages has brought additional attention to the use of home equity conversion to increase income to the elderly. Using simulation, this study compares the economic consequences of the FHA reverse mortgage with two alternative conversion vehicles: sale of a remainder interest and sale-leaseback. An FHA insured plan is devised for each vehicle, structured to represent fair substitutes for the FHA mortgage. In addition, the FHA mortgage is adjusted to allow for a 4 percent annual increase in distributions to the homeowner. The viability of each plan for the homeowner, the financial institution and the FHA is investigated using different assumptions for house appreciation, tax rates, and homeowners' initial ages. For the homeowner, the return of each vehicle is compared with the choice of not employing home equity conversion. The study examines the impact of tax and accounting rules on the selection of alternatives. The study investigates the sensitivity of the FHA model to some of its assumptions.^ Although none of the vehicles is Pareato optimal, the study shows that neither the sale of a remainder interest nor the sale-leaseback is a viable alternative vehicle to the homeowner. While each of these vehicles is profitable to the financial institution, the profits are not high enough to transfer benefits to the homeowner and still be workable. The effects of tax rate, house appreciation rate, and homeowner's initial age are surprisingly small. As a general rule, none of these factors materially impact the decision of either the homeowner or the financial institution. Tax and accounting rules were found to have minimal impact on the selection of vehicles. The sensitivity analysis indicates that none of the variables studied alone is likely to materially affect the FHA's profitability. ^

A reliability centered maintenance decision system for a discrete part manufacturing facility

This thesis develops and validates the framework of a specialized maintenance decision support system for a discrete part manufacturing facility. Its construction utilizes a modular approach based on the fundamental philosophy of Reliability Centered Maintenance (RCM). The proposed architecture uniquely integrates System Decomposition, System Evaluation, Failure Analysis, Logic Tree Analysis, and Maintenance Planning modules. It presents an ideal solution to the unique maintenance inadequacies of modern discrete part manufacturing systems. Well established techniques are incorporated as building blocks of the system's modules. These include Failure Mode Effect and Criticality Analysis (FMECA), Logic Tree Analysis (LTA), Theory of Constraints (TOC), and an Expert System (ES). A Maintenance Information System (MIS) performs the system's support functions. Validation was performed by field testing of the system at a Miami based manufacturing facility. Such a maintenance support system potentially reduces downtime losses and contributes to higher product quality output. Ultimately improved profitability is the final outcome. ^

Subdural electroencephalogram analysis for extracting discriminating measures in epileptogenic data

This dissertation introduces an integrated algorithm for a new application dedicated at discriminating between electrodes leading to a seizure onset and those that do not, using interictal subdural EEG data. The significance of this study is in determining among all of these channels, all containing interictal spikes, why some electrodes eventually lead to seizure while others do not. A first finding in the development process of the algorithm is that these interictal spikes had to be asynchronous and should be located in different regions of the brain, before any consequential interpretations of EEG behavioral patterns are possible. A singular merit of the proposed approach is that even when the EEG data is randomly selected (independent of the onset of seizure), we are able to classify those channels that lead to seizure from those that do not. It is also revealed that the region of ictal activity does not necessarily evolve from the tissue located at the channels that present interictal activity, as commonly believed.^ The study is also significant in terms of correlating clinical features of EEG with the patient's source of ictal activity, which is coming from a specific subset of channels that present interictal activity. The contributions of this dissertation emanate from (a) the choice made on the discriminating parameters used in the implementation, (b) the unique feature space that was used to optimize the delineation process of these two type of electrodes, (c) the development of back-propagation neural network that automated the decision making process, and (d) the establishment of mathematical functions that elicited the reasons for this delineation process. ^

A non-linear discrete stochastic optimization model for Advanced Access patient appointment scheduling

Access to healthcare is a major problem in which patients are deprived of receiving timely admission to healthcare. Poor access has resulted in significant but avoidable healthcare cost, poor quality of healthcare, and deterioration in the general public health. Advanced Access is a simple and direct approach to appointment scheduling in which the majority of a clinic's appointments slots are kept open in order to provide access for immediate or same day healthcare needs and therefore, alleviate the problem of poor access the healthcare. This research formulates a non-linear discrete stochastic mathematical model of the Advanced Access appointment scheduling policy. The model objective is to maximize the expected profit of the clinic subject to constraints on minimum access to healthcare provided. Patient behavior is characterized with probabilities for no-show, balking, and related patient choices. Structural properties of the model are analyzed to determine whether Advanced Access patient scheduling is feasible. To solve the complex combinatorial optimization problem, a heuristic that combines greedy construction algorithm and neighborhood improvement search was developed. The model and the heuristic were used to evaluate the Advanced Access patient appointment policy compared to existing policies. Trade-off between profit and access to healthcare are established, and parameter analysis of input parameters was performed. The trade-off curve is a characteristic curve and was observed to be concave. This implies that there exists an access level at which at which the clinic can be operated at optimal profit that can be realized. The results also show that, in many scenarios by switching from existing scheduling policy to Advanced Access policy clinics can improve access without any decrease in profit. Further, the success of Advanced Access policy in providing improved access and/or profit depends on the expected value of demand, variation in demand, and the ratio of demand for same day and advanced appointments. The contributions of the dissertation are a model of Advanced Access patient scheduling, a heuristic to solve the model, and the use of the model to understand the scheduling policy trade-offs which healthcare clinic managers must make. ^

Think before you eat: Calories and exercise equivalents presented on menus at point-of-choice

Although calorie information at the point-of-purchase at fast food restaurants is proposed as a method to decrease calorie choices and combat obesity, research results have been mixed. Much of the supportive research has weak methodology, and is limited. There is a demonstrated need to develop better techniques to assist consumers to make lower calorie food choices. Eating at fast food restaurants has been positively associated with weight gain. The current study explored the possibility of adding exercise equivalents (EE) (physical activity required to burn off the calories in the food), along with calorie information as a possible way to facilitate lower calorie choice at the point-of-choice in fast food restaurants. This three-group experimental study, in 18-34 year old, overweight and obese women, examines whether presenting caloric information in the form of EE at the point-of-choice at fast food restaurants, will lead to lower calorie food choices compared to presenting simple caloric information or no information at all. Methods. A randomized repeated measures experiment was conducted. Participants ordered a fast food meal from Burger King with menus that contained only the names of the food choices (Lunch 1). One week later (Lunch 2), study participants were given one of three menus that varied: no information, calorie information, or calorie information and EE. Study participants included 62 college aged students. Additionally, the study controlled for dietary restraint by blocking participants, before randomization, to the three groups. Results. A repeated measures analysis of variance was conducted. The study was not sufficiently powered, and while the study was designed to determine large effect sizes, a small effect size of .026, was determined. No significant differences were found in the foods ordered among the various menu conditions. Conclusion. Menu labeling alone might not be enough to reduce calories at the point-of-choice at restaurants. Additional research is necessary to determine if calorie information and EE at the point-of-choice would lead to fewer calories chosen at a meal. Studies should also look at long-term, repeated exposure to determine the effectiveness of calories and or EE at the point-of-choice at fast food restaurants.

Evaluating the Effectiveness of Discrete Trial Procedures for Teaching Receptive Discrimination to Children with Autism Spectrum Disorders

Research has found that children with autism spectrum disorders (ASD) show significant deficits in receptive language skills (Wiesmer, Lord, & Esler, 2010). One of the primary goals of applied behavior analytic intervention is to improve the communication skills of children with autism by teaching receptive discriminations. Both receptive discriminations and receptive language entail matching spoken words with corresponding objects, symbols (e.g., pictures or words), actions, people, and so on (Green, 2001). In order to develop receptive language skills, children with autism often undergo discrimination training within the context of discrete trial training. This training entails teaching the learner how to respond differentially to different stimuli (Green, 2001). It is through discrimination training that individuals with autism learn and develop language (Lovaas, 2003). The present study compares three procedures for teaching receptive discriminations: (1) simple/conditional (Procedure A), (2) conditional only (Procedure B), and (3) conditional discrimination of two target cards (Procedure C). Six children, ranging in age from 2-years-old to 5-years-old, with an autism diagnosis were taught how to receptively discriminate nine sets of stimuli. Results suggest that the extra training steps included in the simple/conditional and conditional only procedures may not be necessary to teach children with autism how to receptively discriminate. For all participants, Procedure C appeared to be the most efficient and effective procedure for teaching young children with autism receptive discriminations. Response maintenance and generalization probes conducted one-month following the end of training indicate that even though Procedure C resulted in less training sessions overall, no one procedure resulted in better maintenance and generalization than the others. In other words, more training sessions, as evident with the simple/conditional and conditional only procedures, did not facilitate participants’ ability to accurately respond or generalize one-month following training. The present study contributes to the literature on what is the most efficient and effective way to teach receptive discrimination during discrete trial training to children with ASD. These findings are critical as research shows that receptive language skills are predictive of better outcomes and adaptive behaviors in the future.

Access to better education: The school choice experience of families served by low-performing elementary public schools in Miami-Dade County

Public school choice education policy attempts to create an education marketplace. Although school choice research has focused on the parent role in the school choice process, little is known about parents served by low-performing schools. Following market theory, students attending low-performing schools should be the primary students attempting to use school choice policy to access high performing schools rather than moving to a better school. However, students remain in these low-performing schools. This study took place in Miami-Dade County, which offers a wide variety of school choice options through charter schools, magnet schools, and open-choice schools. ^ This dissertation utilized a mixed-methods design to examine the decision-making process and school choice options utilized by the parents of students served by low-performing elementary schools in Miami-Dade County. Twenty-two semi-structured interviews were conducted with the parents of students served by low-performing schools. Binary logistic regression models were fitted to the data to compare the demographic characteristics, academic achievement and distance from alternative schooling options between transfers and non-transfers. Multinomial logistic regression models were fitted to the data to evaluate how demographic characteristics, distance to transfer school, and transfer school grade influenced the type of school a transfer student chose. A geographic analysis was conducted to determine how many miles students lived from alternative schooling options and the miles transfer students lived away from their transfer school. ^ The findings of the interview data illustrated that parents’ perceived needs are not being adequately addressed by state policy and county programs. The statistical analysis found that students from higher socioeconomic social groups were not more likely to transfer than students from lower socioeconomic social groups. Additionally, students who did transfer were not likely to end up at a high achieving school. The findings of the binary logistic regression demonstrated that transfer students were significantly more likely to live near alternative school options.^

Think Before You Eat: Calories and Exercise Equivalents Presented on Menus at Point-of-Choice

Although calorie information at the point-of-purchase at fast food restaurants is proposed as a method to decrease calorie choices and combat obesity, research results have been mixed. Much of the supportive research has weak methodology, and is limited. There is a demonstrated need to develop better techniques to assist consumers to make lower calorie food choices. Eating at fast food restaurants has been positively associated with weight gain. The current study explored the possibility of adding exercise equivalents (EE) (physical activity required to burn off the calories in the food), along with calorie information as a possible way to facilitate lower calorie choice at the point-of-choice in fast food restaurants. This three-group experimental study, in 18-34 year old, overweight and obese women, examines whether presenting caloric information in the form of EE at the point-of-choice at fast food restaurants, will lead to lower calorie food choices compared to presenting simple caloric information or no information at all. Methods: A randomized repeated measures experiment was conducted. Participants ordered a fast food meal from Burger King with menus that contained only the names of the food choices (Lunch 1). One week later (Lunch 2), study participants were given one of three menus that varied: no information, calorie information, or calorie information and EE. Study participants included 62 college aged students. Additionally, the study controlled for dietary restraint by blocking participants, before randomization, to the three groups. Results: A repeated measures analysis of variance was conducted. The study was not sufficiently powered, and while the study was designed to determine large effect sizes, a small effect size of .026, was determined. No significant differences were found in the foods ordered among the various menu conditions. Conclusion: Menu labeling alone might not be enough to reduce calories at the point-of-choice at restaurants. Additional research is necessary to determine if calorie information and EE at the point-of-choice would lead to fewer calories chosen at a meal. Studies should also look at long-term, repeated exposure to determine the effectiveness of calories and or EE at the point-of-choice at fast food restaurants.

Resource, Strategies, Location Determinants, And Host Country Location Choice By Emerging Market Firms

The extant literature had studied the determinants of the firms’ location decisions with help of host country characteristics and distances between home and host countries. Firm resources and its internationalization strategies had found limited attention in this literature. To address this gap, the research question in this dissertation was whether and how firms’ resources and internationalization strategies impacted the international location decisions of emerging market firms. To explore the research question, data were hand-collected from Indian software firms on their location decisions taken between April 2000 and March 2009. To analyze the multi-level longitudinal dataset, hierarchical linear modeling was used. The results showed that the internationalization strategies, namely market-seeking or labor-seeking had direct impact on firms’ location decision. This direct relationship was moderated by firm resource which, in case of Indian software firms, was the appraisal at CMMI level-5. Indian software firms located in developed countries with a market-seeking strategy and in emerging markets with a labor-seeking strategy. However, software firms with resource such as CMMI level-5 appraisal, when in a labor-seeking mode, were more likely to locate in a developed country over emerging market than firms without the appraisal. Software firms with CMMI level-5 appraisal, when in market-seeking mode, were more likely to locate in a developed country over an emerging market than firms without the appraisal. It was concluded that the internationalization strategies and resources of companies predicted their location choices, over and above the variables studied in the theoretical field of location determinants.

Land-cover detection and landscape structure analysis in the Pachitea Basin, Peruvian Amazon

Classification procedures, including atmospheric correction satellite images as well as classification performance utilizing calibration and validation at different levels, have been investigated in the context of a coarse land-cover classification scheme for the Pachitea Basin. Two different correction methods were tested against no correction in terms of reflectance correction towards a common response for pseudo-invariant features (PIF). The accuracy of classifications derived from each of the three methods was then assessed in a discriminant analysis using crossvalidation at pixel, polygon, region, and image levels. Results indicate that only regression adjusted images using PIFs show no significant difference between images in any of the bands. A comparison of classifications at different levels suggests though that at pixel, polygon, and region levels the accuracy of the classifications do not significantly differ between corrected and uncorrected images. Spatial patterns of land-cover were analyzed in terms of colonization history, infrastructure, suitability of the land, and landownership. The actual use of the land is driven mainly by the ability to access the land and markets as is obvious in the distribution of land cover as a function of distance to rivers and roads. When considering all rivers and roads a threshold distance at which disproportional agro-pastoral land cover switches from over represented to under represented is at about 1km. Best land use suggestions seem not to affect the choice of land use. Differences in abundance of land cover between watersheds are more prevailing than differences between colonist and indigenous groups.

Access to Better Education: The School Choice Experience of Families Served by Low-Performing Elementary Public Schools in Miami-Dade County

Public school choice education policy attempts to create an education marketplace. Although school choice research has focused on the parent role in the school choice process, little is known about parents served by low-performing schools. Following market theory, students attending low-performing schools should be the primary students attempting to use school choice policy to access high performing schools rather than moving to a better school. However, students remain in these low-performing schools. This study took place in Miami-Dade County, which offers a wide variety of school choice options through charter schools, magnet schools, and open-choice schools. This dissertation utilized a mixed-methods design to examine the decision-making process and school choice options utilized by the parents of students served by low-performing elementary schools in Miami-Dade County. Twenty-two semi-structured interviews were conducted with the parents of students served by low-performing schools. Binary logistic regression models were fitted to the data to compare the demographic characteristics, academic achievement and distance from alternative schooling options between transfers and non-transfers. Multinomial logistic regression models were fitted to the data to evaluate how demographic characteristics, distance to transfer school, and transfer school grade influenced the type of school a transfer student chose. A geographic analysis was conducted to determine how many miles students lived from alternative schooling options and the miles transfer students lived away from their transfer school. The findings of the interview data illustrated that parents’ perceived needs are not being adequately addressed by state policy and county programs. The statistical analysis found that students from higher socioeconomic social groups were not more likely to transfer than students from lower socioeconomic social groups. Additionally, students who did transfer were not likely to end up at a high achieving school. The findings of the binary logistic regression demonstrated that transfer students were significantly more likely to live near alternative school options.