The potential role of environmental exposures and genomic signaling in development of central nervous system tumors

The etiology of central nervous system tumors (CNSTs) is mainly unknown. Aside from extremely rare genetic conditions, such as neurofibromatosis and tuberous sclerosis, the only unequivocally identified risk factor is exposure to ionizing radiation, and this explains only a very small fraction of cases. Using meta-analysis, gene networking and bioinformatics methods, this dissertation explored the hypothesis that environmental exposures produce genetic and epigenetic alterations that may be involved in the etiology of CNSTs. A meta-analysis of epidemiological studies of pesticides and pediatric brain tumors revealed a significantly increased risk of brain tumors among children whose mothers had farm-related exposures during pregnancy. A dose response was recognized when this risk estimate was compared to those for risk of brain tumors from maternal exposure to non-agricultural pesticides during pregnancy, and risk of brain tumors among children exposed to agricultural activities. Through meta-analysis of several microarray studies which compared normal tissue to astrocytomas, we were able to identify a list of 554 genes which were differentially expressed in the majority of astrocytomas. Many of these genes have in fact been implicated in development of astrocytoma, including EGFR, HIF-1α, c-Myc, WNT5A, and IDH3A. Reverse engineering of these 554 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I-IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme (GBM) were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. Lastly, bioinformatics analysis of environmental databases and curated published results on GBM was able to identify numerous potential pathways and geneenvironment interactions that may play key roles in astrocytoma development. Findings from this research have strong potential to advance our understanding of the etiology and susceptibility to CNSTs. Validation of our ‘key genes’ and pathways could potentially lead to useful tools for early detection and novel therapeutic options for these tumors.

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

System-on-a-Chip (SoC) based hardware acceleration in Register Transfer Level (RTL) design

Today, modern System-on-a-Chip (SoC) systems have grown rapidly due to the increased processing power, while maintaining the size of the hardware circuit. The number of transistors on a chip continues to increase, but current SoC designs may not be able to exploit the potential performance, especially with energy consumption and chip area becoming two major concerns. Traditional SoC designs usually separate software and hardware. Thus, the process of improving the system performance is a complicated task for both software and hardware designers. The aim of this research is to develop hardware acceleration workflow for software applications. Thus, system performance can be improved with constraints of energy consumption and on-chip resource costs. The characteristics of software applications can be identified by using profiling tools. Hardware acceleration can have significant performance improvement for highly mathematical calculations or repeated functions. The performance of SoC systems can then be improved, if the hardware acceleration method is used to accelerate the element that incurs performance overheads. The concepts mentioned in this study can be easily applied to a variety of sophisticated software applications. The contributions of SoC-based hardware acceleration in the hardware-software co-design platform include the following: (1) Software profiling methods are applied to H.264 Coder-Decoder (CODEC) core. The hotspot function of aimed application is identified by using critical attributes such as cycles per loop, loop rounds, etc. (2) Hardware acceleration method based on Field-Programmable Gate Array (FPGA) is used to resolve system bottlenecks and improve system performance. The identified hotspot function is then converted to a hardware accelerator and mapped onto the hardware platform. Two types of hardware acceleration methods – central bus design and co-processor design, are implemented for comparison in the proposed architecture. (3) System specifications, such as performance, energy consumption, and resource costs, are measured and analyzed. The trade-off of these three factors is compared and balanced. Different hardware accelerators are implemented and evaluated based on system requirements. 4) The system verification platform is designed based on Integrated Circuit (IC) workflow. Hardware optimization techniques are used for higher performance and less resource costs. Experimental results show that the proposed hardware acceleration workflow for software applications is an efficient technique. The system can reach 2.8X performance improvements and save 31.84% energy consumption by applying the Bus-IP design. The Co-processor design can have 7.9X performance and save 75.85% energy consumption.

Evaluating the Appropriateness of Project Delivery Systems for Different Trenchless Methods

Trenchless methods have been considered to be a viable solution for pipeline projects in urban areas. Their applicability in pipeline projects is expected to increase with the rapid advancements in technology and emerging concerns regarding social costs related to trenching methods. Selecting appropriate project delivery system (PDS) is a key to the success of trenchless projects. To ensure success of the project, the selected project delivery should be tailored to trenchless project specific characteristics and owner needs, since the effectiveness of project delivery systems differs based on different project characteristics and owners requirements. Since different trenchless methods have specific characteristics such rate of installation, lengths of installation, and accuracy, the same project delivery systems may not be equally effective for different methods. The intent of this paper is to evaluate the appropriateness of different PDS for different trenchless methods. PDS are examined through a structured decision-making process called Fuzzy Delivery System Selection Model (FDSSM). The process of incorporating the impacts of: (a) the characteristics of trenchless projects and (b) owners’ needs in the FDSSM is performed by collecting data using questionnaires deployed to professionals involved in the trenchless industry in order to determine the importance of delivery systems selection attributes for different trenchless methods, and then analyzing this data. The sensitivity of PDS rankings with respect to trenchless methods is considered in order to evaluate whether similar project delivery systems are equally effective in different trenchless methods. The effectiveness of PDS with respect to attributes is defined as follows: a project delivery system is most effective with respect to an attribute (e.g., ability to control growth in costs ) if there is no project delivery system that is more effective than that PDS. The results of this study may assist trenchless project owners to select the appropriate PDS for the trenchless method selected.

Integrated construction project delivery system in the U.S. public sector: An information modeling framework

Integrated project delivery (IPD) method has recently emerged as an alternative to traditional delivery methods. It has the potential to overcome inefficiencies of traditional delivery methods by enhancing collaboration among project participants. Information and communication technology (ICT) facilitates IPD by effective management, processing and communication of information within and among organizations. While the benefits of IPD, and the role of ICT in realizing them, have been generally acknowledged, the US public construction sector is very slow in adopting IPD. The reasons are - lack of experience and inadequate understanding of IPD in public owner as confirmed by the results of the questionnaire survey conducted under this research study. The public construction sector should be aware of the value of IPD and should know the essentials for effective implementation of IPD principles - especially, they should be cognizant of the opportunities offered by advancements in ICT to realize this.^ In order to address the need an IPD Readiness Assessment Model (IPD-RAM) was developed in this research study. The model was designed with a goal to determine IPD readiness of a public owner organization considering selected IPD principles, and ICT levels, at which project functions were carried out. Subsequent analysis led to identification of possible improvements in ICTs that have the potential to increase IPD readiness scores. Termed as the gap identification, this process was used to formulate improvement strategies. The model had been applied to six Florida International University (FIU) construction projects (case studies). The results showed that the IPD readiness of the organization was considerably low and several project functions can be improved by using higher and/or advanced level ICT tools and methods. Feedbacks from a focus group comprised of FIU officials and an independent group of experts had been received at various stages of this research and had been utilized during development and implementation of the model. Focus group input was also helpful for validation of the model and its results. It was hoped that the model developed would be useful to construction owner organizations in order to assess their IPD readiness and to identify appropriate ICT improvement strategies.^

Integrated Surface-Ground Water Modeling in Wetlands With Improved Methods to Simulate Vegetative Resistance to Flow

This dissertation focused on developing an integrated surface – subsurface hydrologic simulation numerical model by programming and testing the coupling of the USGS MODFLOW-2005 Groundwater Flow Process (GWF) package (USGS, 2005) with the 2D surface water routing model: FLO-2D (O’Brien et al., 1993). The coupling included the necessary procedures to numerically integrate and verify both models as a single computational software system that will heretofore be referred to as WHIMFLO-2D (Wetlands Hydrology Integrated Model). An improved physical formulation of flow resistance through vegetation in shallow waters based on the concept of drag force was also implemented for the simulations of floodplains, while the use of the classical methods (e.g., Manning, Chezy, Darcy-Weisbach) to calculate flow resistance has been maintained for the canals and deeper waters. A preliminary demonstration exercise WHIMFLO-2D in an existing field site was developed for the Loxahatchee Impoundment Landscape Assessment (LILA), an 80 acre area, located at the Arthur R. Marshall Loxahatchee National Wild Life Refuge in Boynton Beach, Florida. After applying a number of simplifying assumptions, results have illustrated the ability of the model to simulate the hydrology of a wetland. In this illustrative case, a comparison between measured and simulated stages level showed an average error of 0.31% with a maximum error of 2.8%. Comparison of measured and simulated groundwater head levels showed an average error of 0.18% with a maximum of 2.9%.

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

Development of Innovative Load Transfer Mechanism to Reduce Hurricane-Induced Failures in New and Existing Residential Construction

Implicit in current design practice of minimum uplift capacity, is the assumption that the connection's capacity is proportional to the number of fasteners per connection joint. This assumption may overestimate the capacity of joints by a factor of two or more and maybe the cause of connection failures in extreme wind events. The current research serves to modify the current practice by proposing a realistic relationship between the number of fasteners and the capacity of the joint. The research is also aimed at further development of non-intrusive continuous load path (CLP) connection system using Glass Fiber Reinforced Polymer (GFRP) and epoxy. Suitable designs were developed for stud to top plate and gable end connections and tests were performed to evaluate the ultimate load, creep and fatigue behavior. The objective was to determine the performance of the connections under simulated sustained hurricane conditions. The performance of the new connections was satisfactory.

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

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

Integrated Construction Project Delivery System in the U.S. Public Sector: An Information Modeling Framework

Integrated project delivery (IPD) method has recently emerged as an alternative to traditional delivery methods. It has the potential to overcome inefficiencies of traditional delivery methods by enhancing collaboration among project participants. Information and communication technology (ICT) facilitates IPD by effective management, processing and communication of information within and among organizations. While the benefits of IPD, and the role of ICT in realizing them, have been generally acknowledged, the US public construction sector is very slow in adopting IPD. The reasons are - lack of experience and inadequate understanding of IPD in public owner as confirmed by the results of the questionnaire survey conducted under this research study. The public construction sector should be aware of the value of IPD and should know the essentials for effective implementation of IPD principles - especially, they should be cognizant of the opportunities offered by advancements in ICT to realize this. In order to address the need an IPD Readiness Assessment Model (IPD-RAM) was developed in this research study. The model was designed with a goal to determine IPD readiness of a public owner organization considering selected IPD principles, and ICT levels, at which project functions were carried out. Subsequent analysis led to identification of possible improvements in ICTs that have the potential to increase IPD readiness scores. Termed as the gap identification, this process was used to formulate improvement strategies. The model had been applied to six Florida International University (FIU) construction projects (case studies). The results showed that the IPD readiness of the organization was considerably low and several project functions can be improved by using higher and/or advanced level ICT tools and methods. Feedbacks from a focus group comprised of FIU officials and an independent group of experts had been received at various stages of this research and had been utilized during development and implementation of the model. Focus group input was also helpful for validation of the model and its results. It was hoped that the model developed would be useful to construction owner organizations in order to assess their IPD readiness and to identify appropriate ICT improvement strategies.

Methods for Modeling and Analyzing Concurrent Software

Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.