Use of Homeostatic Model Assessment Indexes for the Identification of Metabolic Syndrome and Insulin Resistance among Cuban-Americans: A Cross Sectional Study

Aim: to determine cut off points for The Homeostatic Model Assessment Index 1 and 2 (HOMA-1 and HOMA-2) for identifying insulin resistance and metabolic syndrome among a Cuban-American population. Study Design: Cross sectional. Place and Duration of Study: Florida International University, Robert Stempel School of Public Health and Social Work, Department of Dietetics and Nutrition, Miami, FL from July 2010 to December 2011. Methodology: Subjects without diabetes residing in South Florida were enrolled (N=146, aged 37 to 83 years). The HOMA1-IR and HOMA2-IR 90th percentile in the healthy group (n=75) was used as the cut-off point for insulin resistance. A ROC curve was constructed to determine the cut-off point for metabolic syndrome. Results: HOMA1-IR was associated with BMI, central obesity, and triglycerides (P3.95 and >2.20 and for metabolic syndrome were >2.98 (63.4% sensitivity and 73.3% specificity) and >1.55 (60.6% sensitivity and 66.7% specificity), respectively. Conclusion: HOMA cut-off points may be used as a screening tool to identify insulin resistance and metabolic syndrome among Cuban-Americans living in South Florida.

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.

Pulsed parabolic equation model of acoustic transmission (PPEMAT)

Underwater sound is very important in the field of oceanography where it is used for remote sensing in much the same way that radar is used in atmospheric studies. One way to mathematically model sound propagation in the ocean is by using the parabolic-equation method, a technique that allows range dependent environmental parameters. More importantly, this method can model sound transmission where the source emits either a pure tone or a short pulse of sound. Based on the parabolic approximation method and using the split-step Fourier algorithm, a computer model for underwater sound propagation was designed and implemented. This computer model differs from previous models in its use of the interactive mode, structured programming, modular design, and state-of-the-art graphics displays. In addition, the model maximizes the efficiency of computer time through synchronization of loosely coupled dual processors and the design of a restart capability. Since the model is designed for adaptability and for users with limited computer skills, it is anticipated that it will have many applications in the scientific community.

A Static Traffic Assignment Model Combined with an Artificial Neural Network Delay Model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

A model of the hydrothermal system at Casa Diablo in Long Valley, California, based on resistivity profiles and soil mercury analyses

A description and model of the near-surface hydrothermal system at Casa Diablo, with its implications for the larger-scale hydrothermal system of Long Valley, California, is presented. The data include resistivity profiles with penetrations to three different depth ranges, and analyses of inorganic mercury concentrations in 144 soil samples taken over a 1.3 by 1.7 km area. Analyses of the data together with the mapping of active surface hydrothermal features (fumaroles, mudpots, etc.), has revealed that the relationship between the hydrothermal system, surface hydrothermal activity, and mercury anomalies is strongly controlled by faults and topography. There are, however, more subtle factors responsible for the location of many active and anomalous zones such as fractures, zones of high permeability, and interactions between hydrothermal and cooler groundwater. In addition, the near-surface location of the upwelling from the deep hydrothermal reservoir, which supplies the geothermal power plants at Casa Diablo and the numerous hot pools in the caldera with hydrothermal water, has been detected. The data indicate that after upwelling the hydrothermal water flows eastward at shallow depth for at least 2 km and probably continues another 10 km to the east, all the way to Lake Crowley.

A software tool that generates symbolic model verifier (SMV) input language from a predicate transition net

The purpose of this research was to apply model checking by using a symbolic model checker on Predicate Transition Nets (PrT Nets). A PrT Net is a formal model of information flow which allows system properties to be modeled and analyzed. The aim of this thesis was to use the modeling and analysis power of PrT nets to provide a mechanism for the system model to be verified. Symbolic Model Verifier (SMV) was the model checker chosen in this thesis, and in order to verify the PrT net model of a system, it was translated to SMV input language. A software tool was implemented which translates the PrT Net into SMV language, hence enabling the process of model checking. The system includes two parts: the PrT net editor where the representation of a system can be edited, and the translator which converts the PrT net into an SMV program.

A Case Study of the Ellison Model's Use of Mentoring as an Approach Toward Inclusive Community Building

The Ellison Executive Mentoring Inclusive Community Building (ICB) Model is a paradigm for initiating and implementing projects utilizing executives and professionals from a variety of fields and industries, university students, and pre-college students. The model emphasizes adherence to ethical values and promotes inclusiveness in community development. It is a hierarchical model in which actors in each succeeding level of operation serve as mentors to the next. Through a three-step process--content, process, and product--participants must be trained with this mentoring and apprenticeship paradigm in conflict resolution, and they receive sensitivitiy and diversity training, through an interactive and dramatic exposition. The content phase introduces participants to the model's philosophy, ethics, values and methods of operation. The process used to teach and reinforce its precepts is the mentoring and apprenticeship activities and projects in which the participants engage and whose end product demontrates their knowledge and understanding of the model's concepts. This study sought to ascertain from the participants' perspectives whether the model's mentoring approach is an effective means of fostering inclusiveness, based upon their own experiences in using it. The research utilized a qualitative approach and included data from field observations, individual and group interviews, and written accounts of participants' attitudes. Participants complete ICB projects utilizing the Ellison Model as a method of development and implementation. They generally perceive that the model is a viable tool for dealing with diversity issues whether at work, at school, or at home. The projects are also instructional in that whether participants are mentored or seve as apprentices, they gain useful skills and knowledge about their careers. Since the model is relatively new, there is ample room for research in a variety of areas including organizational studies to dertmine its effectiveness in combating problems related to various kinds of discrimination.

An Indexing Structure and Application Model for Vehicles Moving on Road Networks

Moving objects database systems are the most challenging sub-category among Spatio-Temporal database systems. A database system that updates in real-time the location information of GPS-equipped moving vehicles has to meet even stricter requirements. Currently existing data storage models and indexing mechanisms work well only when the number of moving objects in the system is relatively small. This dissertation research aimed at the real-time tracking and history retrieval of massive numbers of vehicles moving on road networks. A total solution has been provided for the real-time update of the vehicles’ location and motion information, range queries on current and history data, and prediction of vehicles’ movement in the near future. To achieve these goals, a new approach called Segmented Time Associated to Partitioned Space (STAPS) was first proposed in this dissertation for building and manipulating the indexing structures for moving objects databases. Applying the STAPS approach, an indexing structure of associating a time interval tree to each road segment was developed for real-time database systems of vehicles moving on road networks. The indexing structure uses affordable storage to support real-time data updates and efficient query processing. The data update and query processing performance it provides is consistent without restrictions such as a time window or assuming linear moving trajectories. An application system design based on distributed system architecture with centralized organization was developed to maximally support the proposed data and indexing structures. The suggested system architecture is highly scalable and flexible. Finally, based on a real-world application model of vehicles moving in region-wide, main issues on the implementation of such a system were addressed.

A dosimetry and radiobiological model for intravascular brachytherapy treatment planning with radioisotope emitting stents

The aim of this study was to develop a practical, versatile and fast dosimetry and radiobiological model for calculation of the 3D dose distribution and radiobiological effectiveness of radioactive stents. The algorithm was written in Matlab 6.5 programming language and is based on the dose point kernel convolution. The dosimetry and radiobiological model was applied for evaluation of the 3D dose distribution of 32P, 90Y, 188Re and 177Lu stents. Of the four, 32P delivers the highest dose, while 90Y, 188Re and 177Lu require high levels of activity to deliver a significant therapeutic dose in the range of 15-30 Gy. Results of the radiobiological model demonstrated that the same physical dose delivered by different radioisotopes produces significantly different radiobiological effects. This type of theoretical dose calculation can be useful in the development of new stent designs, the planning of animal studies and clinical trials, and clinical decisions involving individualized treatment plans.

UV-induced melanoma mouse model dependent on endothelin 3 over-expression

Melanoma is one of the most aggressive types of cancer. It originates from the transformation of melanocytes present in the epidermal/dermal junction of the human skin. It is commonly accepted that melanomagenesis is influenced by the interaction of environmental factors, genetic factors, as well as tumor-host interactions. DNA photoproducts induced by UV radiation are, in normal cells, repaired by the nucleotide excision repair (NER) pathway. The prominent role of NER in cancer resistance is well exemplified by patients with Xeroderma Pigmentosum (XP). This disease results from mutations in the components of the NER pathway, such as XPA and XPC proteins. In humans, NER pathway disruption leads to the development of skin cancers, including melanoma. Similar to humans afflicted with XP, Xpa and Xpc deficient mice show high sensibility to UV light, leading to skin cancer development, except melanoma. The Endothelin 3 (Edn3) signaling pathway is essential for proliferation, survival and migration of melanocyte precursor cells. Excessive production of Edn3 leads to the accumulation of large numbers of melanocytes in the mouse skin, where they are not normally found. In humans, Edn3 signaling pathway has also been implicated in melanoma progression and its metastatic potential. The goal of this study was the development of the first UV-induced melanoma mouse model dependent on the over-expression of Edn3 in the skin. The UV-induced melanoma mouse model reported here is distinguishable from all previous published models by two features: melanocytes are not transformed a priori and melanomagenesis arises only upon neonatal UV exposure. In this model, melanomagenesis depends on the presence of Edn3 in the skin. Disruption of the NER pathway due to the lack of Xpa or Xpc proteins was not essential for melanomagenesis; however, it enhanced melanoma penetrance and decreased melanoma latency after one single neonatal erythemal UV dose. Exposure to a second dose of UV at six weeks of age did not change time of appearance or penetrance of melanomas in this mouse model. Thus, a combination of neonatal UV exposure with excessive Edn3 in the tumor microenvironment is sufficient for melanomagenesis in mice; furthermore, NER deficiency exacerbates this process.^

Eulerian-Lagrangian Two Phase Debris Flow Model

The main objective of this work is to develop a quasi three-dimensional numerical model to simulate stony debris flows, considering a continuum fluid phase, composed by water and fine sediments, and a non-continuum phase including large particles, such as pebbles and boulders. Large particles are treated in a Lagrangian frame of reference using the Discrete Element Method, the fluid phase is based on the Eulerian approach, using the Finite Element Method to solve the depth-averaged Navier–Stokes equations in two horizontal dimensions. The particle’s equations of motion are in three dimensions. The model simulates particle-particle collisions and wall-particle collisions, taking into account that particles are immersed in a fluid. Bingham and Cross rheological models are used for the continuum phase. Both formulations provide very stable results, even in the range of very low shear rates. Bingham formulation is better able to simulate the stopping stage of the fluid when applied shear stresses are low. Results of numerical simulations have been compared with data from laboratory experiments on a flume-fan prototype. Results show that the model is capable of simulating the motion of big particles moving in the fluid flow, handling dense particulate flows and avoiding overlap among particles. An application to simulate debris flow events that occurred in Northern Venezuela in 1999 shows that the model could replicate the main boulder accumulation areas that were surveyed by the USGS. Uniqueness of this research is the integration of mud flow and stony debris movement in a single modeling tool that can be used for planning and management of debris flow prone areas.

An Integrated Flow and Transport Model to Study the Impact of Mercury Remediation Strategies for East Fork Poplar Creek Watershed, Oak Ridge, Tennessee

An integrated flow and transport model using MIKE SHE/MIKE 11 software was developed to predict the flow and transport of mercury, Hg(II), under varying environmental conditions. The model analyzed the impact of remediation scenarios within the East Fork Poplar Creek watershed of the Oak Ridge Reservation with respect to downstream concentration of mercury. The numerical simulations included the entire hydrological cycle: flow in rivers, overland flow, groundwater flow in the saturated and unsaturated zones, and evapotranspiration and precipitation time series. Stochastic parameters and hydrologic conditions over a five year period of historical hydrological data were used to analyze the hydrological cycle and to determine the prevailing mercury transport mechanism within the watershed. Simulations of remediation scenarios revealed that reduction of the highly contaminated point sources, rather than general remediation of the contaminant plume, has a more direct impact on downstream mercury concentrations.

A model of self-transformative identity development in troubled adolescent youth

Within the Stage II program evaluation of the Miami Youth Development Project's (YDP) Changing Lives Program (CLP), this study evaluated CLP intervention effectiveness in promoting positive change in emotion-focused identity exploration (i.e. feelings of personal expressiveness; PE) and a "negative" symptom of identity development (i.e. identity distress; ID) as a first step toward the investigation of a self-transformative model of identity development in adolescent youth. Using structural equation modeling techniques, this study found that participation in the CLP is associated with positive changes in PE (path = .841, p < .002), but not changes in ID. Increase in ID scores was found to be associated with increases in PE (path = .229, p < .002), as well. Intervention effects were not moderated by age/stage, gender, or ethnicity, though differences were found in the degree to which participating subgroups (African- American/Hispanic, male/female, 14-16 years old/17-19 years old) experience change in PE and ID. Findings also suggest that moderate levels of ID may not be deleterious to identity exploration and may be associated with active exploration.

On-screen pre-deblurring of digital images using the wavefront aberration function of the human eye to improve computer access for the visually impaired

Traditional Optics has provided ways to compensate some common visual limitations (up to second order visual impairments) through spectacles or contact lenses. Recent developments in wavefront science make it possible to obtain an accurate model of the Point Spread Function (PSF) of the human eye. Through what is known as the "Wavefront Aberration Function" of the human eye, exact knowledge of the optical aberration of the human eye is possible, allowing a mathematical model of the PSF to be obtained. This model could be used to pre-compensate (inverse-filter) the images displayed on computer screens in order to counter the distortion in the user's eye. This project takes advantage of the fact that the wavefront aberration function, commonly expressed as a Zernike polynomial, can be generated from the ophthalmic prescription used to fit spectacles to a person. This allows the pre-compensation, or onscreen deblurring, to be done for various visual impairments, up to second order (commonly known as myopia, hyperopia, or astigmatism). The technique proposed towards that goal and results obtained using a lens, for which the PSF is known, that is introduced into the visual path of subjects without visual impairment will be presented. In addition to substituting the effect of spectacles or contact lenses in correcting the loworder visual limitations of the viewer, the significance of this approach is that it has the potential to address higher-order abnormalities in the eye, currently not correctable by simple means.

Investigation of spatial patterns of ground-water exchange with lakes, using a three-dimensional numerical model

Hydrogeologic variables controlling groundwater exchange with inflow and flow-through lakes were simulated using a three-dimensional numerical model (MODFLOW) to investigate and quantify spatial patterns of lake bed seepage and hydraulic head distributions in the porous medium surrounding the lakes. Also, the total annual inflow and outflow were calculated as a percentage of lake volume for flow-through lake simulations. The general exponential decline of seepage rates with distance offshore was best demonstrated at lower anisotropy ratio (i.e., Kh/Kv = 1, 10), with increasing deviation from the exponential pattern as anisotropy was increased to 100 and 1000. 2-D vertical section models constructed for comparison with 3-D models showed that groundwater heads and seepages were higher in 3-D simulations. Addition of low conductivity lake sediments decreased seepage rates nearshore and increased seepage rates offshore in inflow lakes, and increased the area of groundwater inseepage on the beds of flow-through lakes. Introduction of heterogeneity into the medium decreased the water table and seepage ratesnearshore, and increased seepage rates offshore in inflow lakes. A laterally restricted aquifer located at the downgradient side of the flow-through lake increased the area of outseepage. Recharge rate, lake depth and lake bed slope had relatively little effect on the spatial patterns of seepage rates and groundwater exchange with lakes.