The non-linear acousto-mechanical and thermodynamic response of spherical absorbers to laser pulses of various temporal profiles

This study is to theoretically investigate shockwave and microbubble formation due to laser absorption by microparticles and nanoparticles. The initial motivation for this research was to understand the underlying physical mechanisms responsible for laser damage to the retina, as well as the predict threshold levels for damage for laser pulses with of progressively shorter durations. The strongest absorbers in the retina are micron size melanosomes, and their absorption of laser light causes them to accrue very high energy density. I theoretically investigate how this absorbed energy is transferred to the surrounding medium. For a wide range of conditions I calculate shockwave generation and bubble growth as a function of the three parameters; fluence, pulse duration and pulse shape. In order to develop a rigorous physical treatment, the governing equations for the behavior of an absorber and for the surrounding medium are derived. Shockwave theory is investigated and the conclusion is that a shock pressure explanation is likely to be the underlying physical cause of retinal damage at threshold fluences for sub-nanosecond pulses. The same effects are also expected for non-biological micro and nano absorbers. ^

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. ^

Comparison of Some Improved Estimators for Linear Regression Model under Different Conditions

Multiple linear regression model plays a key role in statistical inference and it has extensive applications in business, environmental, physical and social sciences. Multicollinearity has been a considerable problem in multiple regression analysis. When the regressor variables are multicollinear, it becomes difficult to make precise statistical inferences about the regression coefficients. There are some statistical methods that can be used, which are discussed in this thesis are ridge regression, Liu, two parameter biased and LASSO estimators. Firstly, an analytical comparison on the basis of risk was made among ridge, Liu and LASSO estimators under orthonormal regression model. I found that LASSO dominates least squares, ridge and Liu estimators over a significant portion of the parameter space for large dimension. Secondly, a simulation study was conducted to compare performance of ridge, Liu and two parameter biased estimator by their mean squared error criterion. I found that two parameter biased estimator performs better than its corresponding ridge regression estimator. Overall, Liu estimator performs better than both ridge and two parameter biased estimator.

Development of operational performance models for truck-lane restrictions on freeway corridors

Highways are generally designed to serve a mixed traffic flow that consists of passenger cars, trucks, buses, recreational vehicles, etc. The fact that the impacts of these different vehicle types are not uniform creates problems in highway operations and safety. A common approach to reducing the impacts of truck traffic on freeways has been to restrict trucks to certain lane(s) to minimize the interaction between trucks and other vehicles and to compensate for their differences in operational characteristics. ^ The performance of different truck lane restriction alternatives differs under different traffic and geometric conditions. Thus, a good estimate of the operational performance of different truck lane restriction alternatives under prevailing conditions is needed to help make informed decisions on truck lane restriction alternatives. This study develops operational performance models that can be applied to help identify the most operationally efficient truck lane restriction alternative on a freeway under prevailing conditions. The operational performance measures examined in this study include average speed, throughput, speed difference, and lane changes. Prevailing conditions include number of lanes, interchange density, free-flow speeds, volumes, truck percentages, and ramp volumes. ^ Recognizing the difficulty of collecting sufficient data for an empirical modeling procedure that involves a high number of variables, the simulation approach was used to estimate the performance values for various truck lane restriction alternatives under various scenarios. Both the CORSIM and VISSIM simulation models were examined for their ability to model truck lane restrictions. Due to a major problem found in the CORSIM model for truck lane modeling, the VISSIM model was adopted as the simulator for this study. ^ The VISSIM model was calibrated mainly to replicate the capacity given in the 2000 Highway Capacity Manual (HCM) for various free-flow speeds under the ideal basic freeway section conditions. Non-linear regression models for average speed, throughput, average number of lane changes, and speed difference between the lane groups were developed. Based on the performance models developed, a simple decision procedure was recommended to select the desired truck lane restriction alternative for prevailing conditions. ^

Tropical seagrass-associated macroalgae distributions and trends relative to water quality

Tropical coastal marine ecosystems including mangroves, seagrass beds and coral reef communities are undergoing intense degradation in response to natural and human disturbances, therefore, understanding the causes and mechanisms present challenges for scientist and managers. In order to protect our marine resources, determining the effects of nutrient loads on these coastal systems has become a key management goal. Data from monitoring programs were used to detect trends of macroalgae abundances and develop correlations with nutrient availability, as well as forecast potential responses of the communities monitored. Using eight years of data (1996–2003) from complementary but independent monitoring programs in seagrass beds and water quality of the Florida Keys National Marine Sanctuary (FKNMS), we: (1) described the distribution and abundance of macroalgae groups; (2) analyzed the status and spatiotemporal trends of macroalgae groups; and (3) explored the connection between water quality and the macroalgae distribution in the FKNMS. In the seagrass beds of the FKNMS calcareous green algae were the dominant macroalgae group followed by the red group; brown and calcareous red algae were present but in lower abundance. Spatiotemporal patterns of the macroalgae groups were analyzed with a non-linear regression model of the abundance data. For the period of record, all macroalgae groups increased in abundance (Abi) at most sites, with calcareous green algae increasing the most. Calcareous green algae and red algae exhibited seasonal pattern with peak abundances (Φi) mainly in summer for calcareous green and mainly in winter for red. Macroalgae Abi and long-term trend (mi) were correlated in a distinctive way with water quality parameters. Both the Abi and mi of calcareous green algae had positive correlations with NO3−, NO2−, total nitrogen (TN) and total organic carbon (TOC). Red algae Abi had a positive correlation with NO2−, TN, total phosphorus and TOC, and the mi in red algae was positively correlated with N:P. In contrast brown and calcareous red algae Abi had negative correlations with N:P. These results suggest that calcareous green algae and red algae are responding mainly to increases in N availability, a process that is happening in inshore sites. A combination of spatially variable factors such as local current patterns, nutrient sources, and habitat characteristics result in a complex array of the macroalgae community in the seagrass beds of the FKNMS.

Effects of shading on calcareous benthic periphyton in a short-hydroperiod oligotrophic wetland (Everglades, FL, USA)

The effects of shade on benthic calcareous periphyton were tested in a short-hydroperiod oligotrophic subtropical wetland (freshwater Everglades). The experiment was a split-plot design set in three sites with similar environmental characteristics. At each site, eight randomly selected 1-m2 areas were isolated individually in a shade house, which did not spectrally change the incident irradiance but reduced it quantitatively by 0, 30, 50, 60, 70, 80, 90 and 98%. Periphyton mat was sampled monthly under each shade house for a 5 month period while the wetland was flooded. Periphyton was analyzed for thickness, DW, AFDW, chlorophyll a (chl a) and incubated in light and dark BOD bottles at five different irradiances to assess its photosynthesis–irradiance (PI) curve and respiration. The PI curves parameters P max, I k and eventually the photoinhibition slope (β) were determined following non-linear regression analyses. Taxonomic composition and total algal biovolume were determined at the end of the experiment. The periphyton composition did not change with shade but the PI curves were significantly affected by it. I k increased linearly with increasing percent irradiance transmittance (%IT = 1−%shade). P max could be fitted with a PI curve equation as it increased with %IT and leveled off after 10%IT. For each shade level, the PI curve was used to integrate daily photosynthesis for a day of average irradiance. The daily photosynthesis followed a PI curve equation with the same characteristics as P max vs. %IT. Thus, periphyton exhibited a high irradiance plasticity under 0–80% shade but could not keep up the same photosynthetic level at higher shade, causing a decrease in daily GPP at 98% shade levels. The plasticity was linked to an increase in the chl a content per cell in the 60–80% shade, while this increase was not observed at lower shade likely because it was too demanding energetically. Thus, chl a is not a good metric for periphyton biomass assessment across variously shaded habitats. It is also hypothesized that irradiance plasticity is linked to photosynthetic coupling between differently comprised algal layers arranged vertically within periphyton mats that have different PI curves.

Estimation of average annual daily traffic (AADT) using geographically weighted regression (GWR) method and geographic information system (GIS)

Annual average daily traffic (AADT) is important information for many transportation planning, design, operation, and maintenance activities, as well as for the allocation of highway funds. Many studies have attempted AADT estimation using factor approach, regression analysis, time series, and artificial neural networks. However, these methods are unable to account for spatially variable influence of independent variables on the dependent variable even though it is well known that to many transportation problems, including AADT estimation, spatial context is important. ^ In this study, applications of geographically weighted regression (GWR) methods to estimating AADT were investigated. The GWR based methods considered the influence of correlations among the variables over space and the spatially non-stationarity of the variables. A GWR model allows different relationships between the dependent and independent variables to exist at different points in space. In other words, model parameters vary from location to location and the locally linear regression parameters at a point are affected more by observations near that point than observations further away. ^ The study area was Broward County, Florida. Broward County lies on the Atlantic coast between Palm Beach and Miami-Dade counties. In this study, a total of 67 variables were considered as potential AADT predictors, and six variables (lanes, speed, regional accessibility, direct access, density of roadway length, and density of seasonal household) were selected to develop the models. ^ To investigate the predictive powers of various AADT predictors over the space, the statistics including local r-square, local parameter estimates, and local errors were examined and mapped. The local variations in relationships among parameters were investigated, measured, and mapped to assess the usefulness of GWR methods. ^ The results indicated that the GWR models were able to better explain the variation in the data and to predict AADT with smaller errors than the ordinary linear regression models for the same dataset. Additionally, GWR was able to model the spatial non-stationarity in the data, i.e., the spatially varying relationship between AADT and predictors, which cannot be modeled in ordinary linear regression. ^

Graduate program culture and intention to persist: Working adults in cohort and non-cohort programs

Cohort programs have been instituted at many universities to accommodate the growing number of mature adult graduate students who pursue degrees while maintaining multiple commitments such as work and family. While it is estimated that as many as 40–60% of students who begin graduate study fail to complete degrees, it is thought that attrition may be even higher for this population of students. Yet, little is known about the impact of cohorts on the learning environment and whether cohort programs affect graduate student retention. Retention theory stresses the importance of the academic department, quality of faculty-student relationships and student involvement in the life of the academic community as critical determinants in students' decisions to persist to degree completion. However, students who are employed full-time typically spend little time on campus engaged in the learning environment. Using academic and social integration theory, this study examined the experiences of working adult graduate students enrolled in cohort (CEP) and non-cohort (non-CEP) programs and the influence of these experiences on intention to persist. The Graduate Program Context Questionnaire was administered to graduate students (N = 310) to examine measures of academic and social integration and intention to persist. Sample t tests and ANOVAs were conducted to determine whether differences in perceptions could be identified between cohort and non-cohort students. Multiple linear regression was used to identify variables that predict students' intention to persist. While there were many similarities, significant differences were found between CEP and non-CEP student groups on two measures. CEP students rated peer-student relationships higher and scored higher on the intention to persist measure than non-CEP students. The psychological integration measure, however, was the strongest predictor of intention to persist for both the CEP and non-CEP groups. This study supports the research literature which suggests that CEP programs encourage the development of peer-student relationships and promote students' commitment to persistence.

Development of prediction models for freeway incident durations using data mining techniques

The nation's freeway systems are becoming increasingly congested. A major contribution to traffic congestion on freeways is due to traffic incidents. Traffic incidents are non-recurring events such as accidents or stranded vehicles that cause a temporary roadway capacity reduction, and they can account for as much as 60 percent of all traffic congestion on freeways. One major freeway incident management strategy involves diverting traffic to avoid incident locations by relaying timely information through Intelligent Transportation Systems (ITS) devices such as dynamic message signs or real-time traveler information systems. The decision to divert traffic depends foremost on the expected duration of an incident, which is difficult to predict. In addition, the duration of an incident is affected by many contributing factors. Determining and understanding these factors can help the process of identifying and developing better strategies to reduce incident durations and alleviate traffic congestion. A number of research studies have attempted to develop models to predict incident durations, yet with limited success. ^ This dissertation research attempts to improve on this previous effort by applying data mining techniques to a comprehensive incident database maintained by the District 4 ITS Office of the Florida Department of Transportation (FDOT). Two categories of incident duration prediction models were developed: "offline" models designed for use in the performance evaluation of incident management programs, and "online" models for real-time prediction of incident duration to aid in the decision making of traffic diversion in the event of an ongoing incident. Multiple data mining analysis techniques were applied and evaluated in the research. The multiple linear regression analysis and decision tree based method were applied to develop the offline models, and the rule-based method and a tree algorithm called M5P were used to develop the online models. ^ The results show that the models in general can achieve high prediction accuracy within acceptable time intervals of the actual durations. The research also identifies some new contributing factors that have not been examined in past studies. As part of the research effort, software code was developed to implement the models in the existing software system of District 4 FDOT for actual applications. ^

Factors Controlling Surface Water Flow in a Low-gradient Subtropical Wetland

Surface water flow patterns in wetlands play a role in shaping substrates, biogeochemical cycling, and ecosystem characteristics. This paper focuses on the factors controlling flow across a large, shallow gradient subtropical wetland (Shark River Slough in Everglades National Park, USA), which displays vegetative patterning indicative of overland flow. Between July 2003 and December 2007, flow speeds at five sites were very low (s−1), and exhibited seasonal fluctuations that were correlated with seasonal changes in water depth but also showed distinctive deviations. Stepwise linear regression showed that upstream gate discharges, local stage gradients, and stage together explained 50 to 90% of the variance in flow speed at four of the five sites and only 10% at one site located close to a levee-canal combination. Two non-linear, semi-empirical expressions relating flow speeds to the local hydraulic gradient, water depths, and vegetative resistance accounted for 70% of the variance in our measured speed. The data suggest local-scale factors such as channel morphology, vegetation density, and groundwater exchanges must be considered along with landscape position and basin-scale geomorphology when examining the interactions between flow and community characteristics in low-gradient wetlands such as the Everglades.

The development of rubrics to measure undergraduate students' global awareness and global perspective: A validity study

Higher education institutions across the United States have developed global learning initiatives to support student achievement of global awareness and global perspective, but assessment options for these outcomes are extremely limited. A review of research for a global learning initiative at a large, Hispanic-serving, urban, public, research university in South Florida found a lack of instruments designed to measure global awareness and global perspective in the context of an authentic performance assessment. This quasi-experimental study explored the development of two rubrics for the global learning initiative and the extent to which evidence supported the rubrics' validity and reliability. One holistic rubric was developed to measure students' global awareness and the second to measure their global perspective. The study utilized a pretest/posttest nonequivalent group design. Multiple linear regression was used to ascertain the rubrics' ability to discern and compare average learning gains of undergraduate students enrolled in two global learning courses and students enrolled in two non-global learning courses. Parallel pretest/posttest forms of the performance task required students to respond to two open-ended questions, aligned with the learning outcomes, concerning a complex case narrative. Trained faculty raters read responses and used the rubrics to measure students' global awareness and perspective. Reliability was tested by calculating the rates of agreement among raters. Evidence supported the finding that the global awareness and global perspective rubrics yielded scores that were highly reliable measures of students' development of these learning outcomes. Chi-square tests of frequency found significant rates of inter-rater agreement exceeding the study's .80 minimum requirement. Evidence also supported the finding that the rubrics yielded scores that were valid measures of students' global awareness and global perspective. Regression analyses found little evidence of main effects; however, post hoc analyses revealed a significant interaction between global awareness pretest scores and the treatment, the global learning course. Significant interaction was also found between global perspective pretest scores and the treatment. These crossover interactions supported the finding that the global awareness and global perspective rubrics could be used to detect learning differences between the treatment and control groups as well as differences within the treatment group.

Investigation of escape and negative student behaviors related to Florida state high stakes test preparation in Miami-Dade County Public High Schools

The purpose of this study was to determine whether there was a relationship between pressure to perform on state mandated, high-stakes tests and the rate of student escape behavior defined as the number of school suspensions and absences. The state assigned grade of a school was used as a surrogate measure of pressure with the assumption that pressure increased as the school grade decreased. Student attendance and suspension data were gathered from all 33 of the regular public high schools in Miami-Dade County Public Schools. The research questions were: Is the number of suspensions highest in the third quarter, when most FCAT preparation takes place for each of the 3 school years 2007-08 through 2009-10? How accurately does the high school's grade predict the number of suspensions and number of absences during each of the 4 school years 2005-06 through 2008-09? The research questions were answered using repeated measures analysis of variance for research question #1 and non-linear multiple regression for research question #2. No significant difference could be found between the numbers of suspensions in each of the grading periods nor was there a relationship between the number of suspensions and school grade. A statistically significant relationship was found between student attendance and school grade. When plotted, this relationship was found to be quadratic in nature and formed a loose inverted U for each of the four years during which data were collected. This indicated that students in very high and very low performing schools had low levels of absences while those in the midlevel of the distribution of school performance (C schools) had the greatest rates of absence. Identifying a relationship between the pressures associated with high stakes testing and student escape behavior suggests that it might be useful for building administrators to reevaluate test preparation activities and procedures being used in their building and to include anxiety reducing strategies. As a relationship was found, it sets the foundation for future studies to identify whether testing related activities are impacting some students emotionally and are causing unintended consequences of testing mandates.

The relationships between elementary school principals' emotional intelligence, leadership style and school culture

The role of the principal in school settings and the principal's perceived effect on student achievement have frequently been considered vital factors in school reform. The relationships between emotional intelligence, leadership style and school culture have been widely studied. The literature reveals agreement among scholars regarding the principal's vital role in developing and fostering a positive school culture. The purpose of this study was to explore the relationships between elementary school principals' emotional intelligence, leadership style and school culture. ^ The researcher implemented a non-experimental ex post facto research design to investigate four specific research hypotheses. Utilizing the Qualtrics Survey Software, 57 elementary school principals within a large urban school district in southeast Florida completed the Emotional Quotient Inventory (EQ-i), and 850 of their faculty members completed the Multifactor Leadership Questionnaire (MLQ Form 5X). Faculty responses to the school district's School Climate Survey retrieved from the district's web site were used as the measure of school culture. ^ Linear regression analyses revealed significant positive associations between emotional intelligence and the following leadership measures: Idealized Influence-Attributes (β = .23, p = < .05), Idealized Influence-Behaviors (β = .34, p = < .01), Inspirational Motivation (β = .39, p = < .01) and Contingent Reward (β = .33, p = < .01). Hierarchical regression analyses revealed positive associations between school culture and both transformational and transactional leadership measures, and negative associations between school culture and passive-avoidant leadership measures. Significant positive associations were found between school culture and the principals' emotional intelligence over and above leadership style. Hierarchical linear regressions to test the statistical hypothesis developed to account for alternative explanations revealed significant associations between leadership style and school culture over and above school grade. ^ These results suggest that emotional intelligence merits consideration in the development of leadership theory. Practical implications include suggestions that principals employ both transformational and transactional leadership strategies, and focus on developing their level of emotional intelligence. The associations between emotional intelligence, transformational leadership, Contingent Reward and school culture found in this study validate the role of the principal as the leader of school reform.^

Investigation of Escape and Negative Student Behaviors Related to Florida State High Stakes Test Preparation in Miami-Dade County Public High Schools, having been approved in respect to style and intellectual content, is referred to you for judgment

The purpose of this study was to determine whether there was a relationship between pressure to perform on state mandated, high-stakes tests and the rate of student escape behavior defined as the number of school suspensions and absences. The state assigned grade of a school was used as a surrogate measure of pressure with the assumption that pressure increased as the school grade decreased. Student attendance and suspension data were gathered from all 33 of the regular public high schools in Miami-Dade County Public Schools. The research questions were: Is the number of suspensions highest in the third quarter, when most FCAT preparation takes place for each of the 3 school years 2007-08 through 2009-10? How accurately does the high school’s grade predict the number of suspensions and number of absences during each of the 4 school years 2005-06 through 2008-09? The research questions were answered using repeated measures analysis of variance for research question #1 and non-linear multiple regression for research question #2. No significant difference could be found between the numbers of suspensions in each of the grading periods nor was there a relationship between the number of suspensions and school grade. A statistically significant relationship was found between student attendance and school grade. When plotted, this relationship was found to be quadratic in nature and formed a loose inverted U for each of the four years during which data were collected. This indicated that students in very high and very low performing schools had low levels of absences while those in the midlevel of the distribution of school performance (C schools) had the greatest rates of absence. Identifying a relationship between the pressures associated with high stakes testing and student escape behavior suggests that it might be useful for building administrators to reevaluate test preparation activities and procedures being used in their building and to include anxiety reducing strategies. As a relationship was found, it sets the foundation for future studies to identify whether testing related activities are impacting some students emotionally and are causing unintended consequences of testing mandates.

The Relationships between Elementary School Principals' Emotional Intelligence, Leadership Style and School Culture

The role of the principal in school settings and the principal’s perceived effect on student achievement have frequently been considered vital factors in school reform. The relationships between emotional intelligence, leadership style and school culture have been widely studied. The literature reveals agreement among scholars regarding the principal’s vital role in developing and fostering a positive school culture. The purpose of this study was to explore the relationships between elementary school principals’ emotional intelligence, leadership style and school culture. The researcher implemented a non-experimental ex post facto research design to investigate four specific research hypotheses. Utilizing the Qualtrics Survey Software, 57 elementary school principals within a large urban school district in southeast Florida completed the Emotional Quotient Inventory (EQ-i), and 850 of their faculty members completed the Multifactor Leadership Questionnaire (MLQ Form 5X). Faculty responses to the school district’s School Climate Survey retrieved from the district’s web site were used as the measure of school culture. Linear regression analyses revealed significant positive associations between emotional intelligence and the following leadership measures: Idealized Influence-Attributes (β = .23, p = < .05), Idealized Influence-Behaviors (β = .34, p = < .01), Inspirational Motivation (β = .39, p = < .01) and Contingent Reward (β = .33, p = < .01). Hierarchical regression analyses revealed positive associations between school culture and both transformational and transactional leadership measures, and negative associations between school culture and passive-avoidant leadership measures. Significant positive associations were found between school culture and the principals’ emotional intelligence over and above leadership style. Hierarchical linear regressions to test the statistical hypothesis developed to account for alternative explanations revealed significant associations between leadership style and school culture over and above school grade. These results suggest that emotional intelligence merits consideration in the development of leadership theory. Practical implications include suggestions that principals employ both transformational and transactional leadership strategies, and focus on developing their level of emotional intelligence. The associations between emotional intelligence, transformational leadership, Contingent Reward and school culture found in this study validate the role of the principal as the leader of school reform.