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 exergy based engineering and economic analysis of sustainable building

To achieve the goal of sustainable development, the building energy system was evaluated from both the first and second law of thermodynamics point of view. The relationship between exergy destruction and sustainable development were discussed at first, followed by the description of the resource abundance model, the life cycle analysis model and the economic investment effectiveness model. By combining the forgoing models, a new sustainable index was proposed. Several green building case studies in U.S. and China were presented. The influences of building function, geographic location, climate pattern, the regional energy structure, and the technology improvement potential of renewable energy in the future were discussed. The building’s envelope, HVAC system, on-site renewable energy system life cycle analysis from energy, exergy, environmental and economic perspective were compared. It was found that climate pattern had a dramatic influence on the life cycle investment effectiveness of the building envelope. The building HVAC system energy performance was much better than its exergy performance. To further increase the exergy efficiency, renewable energy rather than fossil fuel should be used as the primary energy. A building life cycle cost and exergy consumption regression model was set up. The optimal building insulation level could be affected by either cost minimization or exergy consumption minimization approach. The exergy approach would cause better insulation than cost approach. The influence of energy price on the system selection strategy was discussed. Two photovoltaics (PV) systems—stand alone and grid tied system were compared by the life cycle assessment method. The superiority of the latter one was quite obvious. The analysis also showed that during its life span PV technology was less attractive economically because the electricity price in U.S. and China did not fully reflect the environmental burden associated with it. However if future energy price surges and PV system cost reductions were considered, the technology could be very promising for sustainable buildings in the future.

What makes online grocers work? A case study analysis of factors contributing to online grocery store profitability

This research examined the factors contributing to the performance of online grocers prior to, and following, the 2000 dot.com collapse. The primary goals were to assess the relationship between a company’s business model(s) and its performance in the online grocery channel and to determine if there were other company and/or market related factors that could account for company performance. ^ To assess the primary goals, a case based theory building process was utilized. A three-way cross-case analysis comprising Peapod, GroceryWorks, and Tesco examined the common profit components, the structural category (e.g., pure-play, partnership, and hybrid) profit components, and the idiosyncratic profit components related to each specific company. ^ Based on the analysis, it was determined that online grocery store business models could be represented at three distinct, but hierarchically, related levels. The first level was termed the core model and represented the basic profit structure that all online grocers needed in order to conduct operations. The next model level was termed the structural model and represented the profit structure associated with the specific business model configuration (i.e., pure-play, partnership, hybrid). The last model level was termed the augmented model and represented the company’s business model when idiosyncratic profit components were included. In relation to the five company related factors, scalability, rate of expansion, and the automation level were potential candidates for helping to explain online grocer performance. In addition, all the market structure related factors were deemed possible candidates for helping to explain online grocer performance. ^ The study concluded by positing an alternative hypothesis concerning the performance of online grocers. Prior to this study, the prevailing wisdom was that the business models were the primary cause of online grocer performance. However, based on the core model analysis, it was hypothesized that the customer relationship activities (i.e., advertising, promotions, and loyalty program tie-ins) were the real drivers of online grocer performance. ^

The construction and optimization of an ion mobility spectrometer for the analysis of explosives and drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs.^ In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug.^ Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). ^ The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.^

Exergoeconomic analysis of solar organic rankine cycle for geothermal air conditioned net zero energy buildings

This study is an attempt at achieving Net Zero Energy Building (NZEB) using a solar Organic Rankine Cycle (ORC) based on exergetic and economic measures. The working fluid, working conditions of the cycle, cycle configuration, and solar collector type are considered the optimization parameters for the solar ORC system. In the first section, a procedure is developed to compare ORC working fluids based on their molecular components, temperature-entropy diagram and fluid effects on the thermal efficiency, net power generated, vapor expansion ratio, and exergy efficiency of the Rankine cycle. Fluids with the best cycle performance are recognized in two different temperature levels within two different categories of fluids: refrigerants and non-refrigerants. Important factors that could lead to irreversibility reduction of the solar ORC are also investigated in this study. In the next section, the system requirements needed to maintain the electricity demand of a geothermal air-conditioned commercial building located in Pensacola of Florida is considered as the criteria to select the optimal components and optimal working condition of the system. The solar collector loop, building, and geothermal air conditioning system are modeled using TRNSYS. Available electricity bills of the building and the 3-week monitoring data on the performance of the geothermal system are employed to calibrate the simulation. The simulation is repeated for Miami and Houston in order to evaluate the effect of the different solar radiations on the system requirements. The final section discusses the exergoeconomic analysis of the ORC system with the optimum performance. Exergoeconomics rests on the philosophy that exergy is the only rational basis for assigning monetary costs to a system’s interactions with its surroundings and to the sources of thermodynamic inefficiencies within it. Exergoeconomic analysis of the optimal ORC system shows that the ratio Rex of the annual exergy loss to the capital cost can be considered a key parameter in optimizing a solar ORC system from the thermodynamic and economic point of view. It also shows that there is a systematic correlation between the exergy loss and capital cost for the investigated solar ORC system.

Analysis of Housing Partnerships using the Balanced Scorecard framework

Housing Partnerships (HPs) are collaborative arrangements that assist communities in the delivery of affordable housing by combining the strengths of the public and private sectors. They emerged in several states, counties, and cities in the eighties as innovative solutions to the challenges in affordable housing resulting from changing dynamics of delivery and production. ^ My study examines HPs with particular emphasis upon the identification of those factors associated with the successful performance of their mission of affordable housing. I will use the Balanced Scorecard (BSC) framework in this study. The identification of performance factors facilitates a better understanding of how HPs can be successful in achieving their mission. The identification of performance factors is significant in the context of the current economic environment because HPs can be viewed as innovative institutional mechanisms in the provision of affordable housing. ^ The present study uses a mixed methods research approach, drawing on data from the IRS Form 990 tax returns, a survey of the chief executives of HPs, and other secondary sources. The data analysis is framed according to the four perspectives of BSC: the financial, customer, internal business, and learning and growth. Financially, revenue diversification affects the financial health of HPs and overall performance. Although HPs depend on private and government funding, they also depend on service fees to carry out their mission. From a customer perspective, the HPs mainly serve low and moderate income households, although some serve specific groups such as seniors, homeless, veterans, and victims of domestic violence. From an internal business perspective, HPs’ programs are oriented toward affordable housing needs, undertaking not only traditional activities such as construction, loan provision, etc., but also advocacy and educational programs. From an employee and learning growth perspective, the HPs are small in staff size, but undertake a range of activities with the help of volunteers. Every part of the HP is developed to maximize resources, knowledge, and skills in order to assist communities in the delivery of affordable housing and related needs. Overall, housing partnerships have played a key role in affordable housing despite the housing market downturn since 2006. Their expenses on affordable housing activities increased despite the decrease in their revenues.^

Dynamic modeling and analysis of single-stage boost inverters under normal and abnormal conditions

Inverters play key roles in connecting sustainable energy (SE) sources to the local loads and the ac grid. Although there has been a rapid expansion in the use of renewable sources in recent years, fundamental research, on the design of inverters that are specialized for use in these systems, is still needed. Recent advances in power electronics have led to proposing new topologies and switching patterns for single-stage power conversion, which are appropriate for SE sources and energy storage devices. The current source inverter (CSI) topology, along with a newly proposed switching pattern, is capable of converting the low dc voltage to the line ac in only one stage. Simple implementation and high reliability, together with the potential advantages of higher efficiency and lower cost, turns the so-called, single-stage boost inverter (SSBI), into a viable competitor to the existing SE-based power conversion technologies.^ The dynamic model is one of the most essential requirements for performance analysis and control design of any engineering system. Thus, in order to have satisfactory operation, it is necessary to derive a dynamic model for the SSBI system. However, because of the switching behavior and nonlinear elements involved, analysis of the SSBI is a complicated task.^ This research applies the state-space averaging technique to the SSBI to develop the state-space-averaged model of the SSBI under stand-alone and grid-connected modes of operation. Then, a small-signal model is derived by means of the perturbation and linearization method. An experimental hardware set-up, including a laboratory-scaled prototype SSBI, is built and the validity of the obtained models is verified through simulation and experiments. Finally, an eigenvalue sensitivity analysis is performed to investigate the stability and dynamic behavior of the SSBI system over a typical range of operation. ^

Frameworks for Systemic and Structural Analysis of Financial Innovations in Infrastructure

Financial innovations have emerged globally to close the gap between the rising global demand for infrastructures and the availability of financing sources offered by traditional financing mechanisms such as fuel taxation, tax-exempt bonds, and federal and state funds. The key to sustainable innovative financing mechanisms is effective policymaking. This paper discusses the theoretical framework of a research study whose objective is to structurally and systemically assess financial innovations in global infrastructures. The research aims to create analysis frameworks, taxonomies and constructs, and simulation models pertaining to the dynamics of the innovation process to be used in policy analysis. Structural assessment of innovative financing focuses on the typologies and loci of innovations and evaluates the performance of different types of innovative financing mechanisms. Systemic analysis of innovative financing explores the determinants of the innovation process using the System of Innovation approach. The final deliverables of the research include propositions pertaining to the constituents of System of Innovation for infrastructure finance which include the players, institutions, activities, and networks. These static constructs are used to develop a hybrid Agent-Based/System Dynamics simulation model to derive propositions regarding the emergent dynamics of the system. The initial outcomes of the research study are presented in this paper and include: (a) an archetype for mapping innovative financing mechanisms, (b) a System of Systems-based analysis framework to identify the dimensions of Systems of Innovation analyses, and (c) initial observations regarding the players, institutions, activities, and networks of the System of Innovation in the context of the U.S. transportation infrastructure financing.

Elemental analysis of biological matrices by laser ablation high resolution inductively coupled plasma mass spectrometry (LA-HR-ICP-MS) and high resolution inductively coupled plasma mass spectrometry (HR -ICP -MS)

The need for elemental analysis of biological matrices such as bone, teeth, and plant matter for sourcing purposes has emerged within the forensic and geochemical laboratories. Trace elemental analyses for the comparison of materials such as glass by inductively coupled plasma mass spectrometry (ICP-MS) and laser ablation ICP-MS has been shown to offer a high degree of discrimination between different manufacturing sources. Unit resolution ICP-MS instruments may suffer from some polyatomic interferences including 40Ar16O+, 40Ar 16O1H+, and 40Ca 16O+ that affect iron measurement at trace levels. Iron is an important element in the analysis of glass and also of interest for the analysis of several biological matrices. A comparison of the analytical performance of two different ICP-MS systems for iron analysis in glass for determining the method detection limits (MDLs), accuracy, and precision of the measurement is presented. Acid digestion and laser ablation methods are also compared. Iron polyatomic interferences were reduced or resolved by using dynamic reaction cell and high resolution ICP-MS. MDLs as low as 0.03 μg g-1 and 0.14 μg g-1 for laser ablation and solution based analyses respectively were achieved. The use of helium as a carrier gas demonstrated improvement in the detection limits of both iron isotopes (56Fe and 57Fe) in medium resolution for the HR-ICP-MS and with a dynamic reaction cell (DRC) coupled to a quadrupole ICP-MS system. ^ The development and application of robust analytical methods for the quantification of trace elements in biological matrices has lead to a better understanding of the potential utility of these measurements in forensic chemical analyses. Standard reference materials (SRMs) were used in the development of an analytical method using HR-ICP-MS and LA-HR-ICP-MS that was subsequently applied on the analysis of real samples. Bone, teeth and ashed marijuana samples were analyzed with the developed method. ^ Elemental analysis of bone samples from 12 different individuals provided discrimination between individuals, when femur and humerus bones were considered separately. Discrimination of 14 teeth samples based on elemental composition was achieved with the exception of one case where samples from the same individual were not associated with each other. The discrimination of 49 different ashed plant (cannabis) samples was achieved using the developed method. ^

Comprehensive forensic toxicological analysis of designer drugs

New designer drugs are constantly emerging onto the illicit drug market and it is often difficult to validate and maintaincomprehensive analytical methods for accurate detection of these compounds. Generally, toxicology laboratories utilize a screening method, such as immunoassay, for the presumptive identification of drugs of abuse. When a positive result occurs, confirmatory methods, such as gas chromatography (GC) or liquid chromatography (LC) coupled with mass spectrometry (MS), are required for more sensitive and specific analyses. In recent years, the need to study the activities of these compounds in screening assays as well as to develop confirmatory techniques to detect them in biological specimens has been recognized. Severe intoxications and fatalities have been encountered with emerging designer drugs, presenting analytical challenges for detection and identification of such novel compounds. The first major task of this research was to evaluate the performance of commercially available immunoassays to determine if designer drugs were cross-reactive. The second major task was to develop and validate a confirmatory method, using LC-MS, to identify and quantify these designer drugs in biological specimens.^ Cross-reactivity towards the cathinone derivatives was found to be minimal. Several other phenethylamines demonstrated cross-reactivity at low concentrations, but results were consistent with those published by the assay manufacturer or as reported in the literature. Current immunoassay-based screening methods may not be ideal for presumptively identifying most designer drugs, including the "bath salts." For this reason, an LC-MS based confirmatory method was developed for 32 compounds, including eight cathinone derivatives, with limits of quantification in the range of 1-10 ng/mL. The method was fully validated for selectivity, matrix effects, stability, recovery, precision, and accuracy. In order to compare the screening and confirmatory techniques, several human specimens were analyzed to demonstrate the importance of using a specific analytical method, such as LC-MS, to detect designer drugs in serum as immunoassays lack cross-reactivity with the novel compounds. Overall, minimal cross-reactivity was observed, highlighting the conclusion that these presumptive screens cannot detect many of the designer drugs and that a confirmatory technique, such as the LC-MS, is required for the comprehensive forensic toxicological analysis of designer drugs.^

Numerical heat transfer analysis of carbon-based foams for use in thermal protection system

The applicability of carbon-based foams as an insulating or active cooling material in thermal protection systems (TPSs) of space vehicles is considered using a computer modeling. This study focuses on numerical investigation of the performance of carbon foams for use in TPSs of space vehicles. Two kinds of carbon foams are considered in this study. For active cooling, the carbon foam that has a thermal conductivity of 100 W/m-k is used and for the insulation, the carbon foam having a thermal conductivity of 0.225 W/m-k is used. A 3D geometry is employed to simulate coolant flow and heat transfer through carbon foam model. Gambit has been used to model the 3D geometry and the numerical simulation is carried out in FLUENT. Numerical results from this thesis suggests that the use of CFOAM and HTC carbon foams in TPS's may effectively protect the aluminum structure of the space shuttle during reentry of the space vehicle.

An Exergy Based Engineering and Economic Analysis of Sustainable Building

To achieve the goal of sustainable development, the building energy system was evaluated from both the first and second law of thermodynamics point of view. The relationship between exergy destruction and sustainable development were discussed at first, followed by the description of the resource abundance model, the life cycle analysis model and the economic investment effectiveness model. By combining the forgoing models, a new sustainable index was proposed. Several green building case studies in U.S. and China were presented. The influences of building function, geographic location, climate pattern, the regional energy structure, and the technology improvement potential of renewable energy in the future were discussed. The building’s envelope, HVAC system, on-site renewable energy system life cycle analysis from energy, exergy, environmental and economic perspective were compared. It was found that climate pattern had a dramatic influence on the life cycle investment effectiveness of the building envelope. The building HVAC system energy performance was much better than its exergy performance. To further increase the exergy efficiency, renewable energy rather than fossil fuel should be used as the primary energy. A building life cycle cost and exergy consumption regression model was set up. The optimal building insulation level could be affected by either cost minimization or exergy consumption minimization approach. The exergy approach would cause better insulation than cost approach. The influence of energy price on the system selection strategy was discussed. Two photovoltaics (PV) systems – stand alone and grid tied system were compared by the life cycle assessment method. The superiority of the latter one was quite obvious. The analysis also showed that during its life span PV technology was less attractive economically because the electricity price in U.S. and China did not fully reflect the environmental burden associated with it. However if future energy price surges and PV system cost reductions were considered, the technology could be very promising for sustainable buildings in the future.

The Construction and Optimization on an Ion Mobility Spectrometer for the Analysis of Explosives and Drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs. In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug. Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.

An analysis of five original compositions

The purpose of this thesis is to analyze in detail five original compositions, each written for the performance of these pieces on March 14, 2009 for a Master's recital. In order to maintain a certain level of musical continuity among these compositions, each was created in such a way as to possess similar musical characteristics of melodic and harmonic structure. These similarities are also reflected within the overall arrangement of each composition and use of instrumentation as well. The following pages will analyze each of these compositions in accordance with several important musical factors. These elements are form and chord analysis, melodic and harmonic content, and meter and rhythm. The author's original scores are included in the appendix.

The phonological analysis of bilingual Creole/English children living in South Florida

The purpose of this study was to gather normative data regarding the phonological system of bilingual Creole-English children ages three and five and to compare performance to norms for English speaking children. The forty participants lived in Miami and represented low socio-economic groups. Participants were assessed using the Goldman-Fristoe Test of Articulation-2 and a Haitian Creole Picture Naming Assessment. The results indicated that the percentage of correct phonemes in Creole (M=91.6) were not significantly different when compared to the correct production of the same phonemes in English (M=92.8). Further analysis revealed that the accuracy of all phonemes was higher for the five-year (M= 90.8) as compared to the three-year-olds (M= 85) in Creole. In English, the five-year-olds performed better than the three-year-olds participants. These findings revealed patterns of phonological development in bilingual Creole/English Children similar to patterns reported in other bilingual children. This information is essential in the evaluation and treatment of this population.