Mitochondrial DNA, segments I and II, its applications in population genetics and forensic sciences

The investigations of human mitochondrial DNA (mtDNA) have considerably contributed to human evolution and migration. The Middle East is considered to be an essential geographic area for human migrations out of Africa since it is located at the crossroads of Africa, and the rest of the world. United Arab Emirates (UAE) population inhabits the eastern part of Arabian Peninsula and was investigated in this study. Published data of 18 populations were included in the statistical analysis. The diversity indices showed (1) high genetic distance among African populations and (2) high genetic distance between African populations and non-African populations. Asian populations clustered together in the NJ tree between the African and European populations. MtDNA haplotypes database of the UAE population was generated. By incorporating UAE mtDNA dataset into the existing worldwide mtDNA database, UAE Forensic Laboratories will be able to analyze future mtDNA evidence in a more significant and consistent manner. ^

A research platform for artificial neural networks with applications in pediatric epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Electronic Perception Technology Applications in Food Service

Electronic Perception Technology (EPT) enables automated equipment to gain artificial sight commonly referred to as "machine-vision” by employing specialty software and embedded sensors to create a “Visual" input field that can be used as a front-end application for transactional behavior. The authors review this new technology and present feasible future applications to the food service industry in enhancing guest services while providing a competitive advantage.

Development of safety performance functions for SafetyAnalyst applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency's safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.

Synthesis of multisubstituted halo -olefins via Pd-catalyzed cross -coupling reactions. Applications in nucleoside chemistry

The enzyme S-adenosyl-L-homocysteine (AdoHcy) hydrolase effects hydrolytic cleavage of AdoHcy to adenosine (Ado) and L-homocysteine (Hcy). The cellular levels of AdoHcy and Hcy are critical because AdoHcy is a potent feedback inhibitor of crucial transmethylation enzymes. Also, elevated plasma levels of Hcy in humans have been shown to be a risk factor in coronary artery disease. ^ On the basis of the previous finding that AdoHcy hydrolase is able to add the enzyme-sequestered water molecule across the 5',6'-double bond of (halo or dihalohomovinyl)-adenosines causing covalent binding inhibition, we designed and synthesized AdoHcy analogues with the 5',6'-olefin motif incorporated in place of the carbon-5' and sulfur atoms. From the available synthetic methods we chose two independent approaches: the first approach was based on the construction of a new C5'-C6' double bond via metathesis reactions, and the second approach was based on the formation of a new C6'-C7' single bond via Pd-catalyzed cross-couplings. Cross-metathesis of the suitably protected 5'-deoxy-5'-methyleneadenosine with racemic 2-amino-5-hexenoate in the presence of Hoveyda-Grubb's catalyst followed by standard deprotection afforded the desired analogue as 5' E isomer of the inseparable mixture of 9'R/S diastereomers. Metathesis of chiral homoallylglycine [(2S)-amino-5-hexenoate] produced AdoHcy analogue with established stereochemistry E at C5'atom and S at C9' atom. The 5'-bromovinyl analogue was synthesized using the bromination-dehydrobromination strategy with pyridinium tribromide and DBU. ^ Since literature reports on the Pd-catalyzed monoalkylation of dihaloalkenes (Csp2-Csp3 coupling) were scarce, we were prompted to undertake model studies on Pd-catalyzed coupling between vinyl dihalides and alkyl organometallics. The 1-fluoro-1-haloalkenes were found to undergo Negishi couplings with alkylzinc bromides to give multisubstituted fluoroalkenes. The alkylation was trans-selective affording pure Z-fluoroalkenes. The highest yields were obtained with PdCl 2(dppb) catalyst, but the best stereochemical outcome was obtained with less reactive Pd(PPh3)4. Couplings of 1,1-dichloro-and 1,1-dibromoalkenes with organozinc reagents resulted in the formation of monocoupled 1-halovinyl product. ^

Acoustic Manipulation and Alignment of Particles for Applications in Separation, Micro-Templating, and Device Fabrication

This dissertation studies the manipulation of particles using acoustic stimulation for applications in microfluidics and templating of devices. The term particle is used here to denote any solid, liquid or gaseous material that has properties, which are distinct from the fluid in which it is suspended. Manipulation means to take over the movements of the particles and to position them in specified locations. Using devices, microfabricated out of silicon, the behavior of particles under the acoustic stimulation was studied with the main purpose of aligning the particles at either low-pressure zones, known as the nodes or high-pressure zones, known as anti-nodes. By aligning particles at the nodes in a flow system, these particles can be focused at the center or walls of a microchannel in order to ultimately separate them. These separations are of high scientific importance, especially in the biomedical domain, since acoustopheresis provides a unique approach to separate based on density and compressibility, unparalleled by other techniques. The study of controlling and aligning the particles in various geometries and configurations was successfully achieved by controlling the acoustic waves. Apart from their use in flow systems, a stationary suspended-particle device was developed to provide controllable light transmittance based on acoustic stimuli. Using a glass compartment and a carbon-particle suspension in an organic solvent, the device responded to acoustic stimulation by aligning the particles. The alignment of light-absorbing carbon particles afforded an increase in visible light transmittance as high as 84.5%, and it was controlled by adjusting the frequency and amplitude of the acoustic wave. The device also demonstrated alignment memory rendering it energy-efficient. A similar device for suspended-particles in a monomer enabled the development of electrically conductive films. These films were based on networks of conductive particles. Elastomers doped with conductive metal particles were rendered surface conductive at particle loadings as low as 1% by weight using acoustic focusing. The resulting films were flexible and had transparencies exceeding 80% in the visible spectrum (400-800 nm) These films had electrical bulk conductivities exceeding 50 S/cm.

A Research Platform for Artificial Neural Networks with Applications in Pediatric Epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and non-epileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that 1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and 2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Synthesis of multisubstituted halo-olefins via Pd-catalyzed cross-coupling reactions : applications in nucleoside chemistry

The enzyme S-adenosyl-L-homocysteine (AdoHey) hydrolase effects hydrolytic cleavage of AdoHcy to adenosine (Ado) and L-homocysteine (Hcy). The cellular levels of AdoHcy and Hcy are critical because AdoHcy is a potent feedback inhibitor of crucial transmethylation enzymes. Also, elevated plasma levels of Hcy in humans have been shown to be a risk factor in coronary artery disease. On the basis of the previous finding that AdoHcy hydrolase is able to add the enzyme-sequestered water molecule across the 5',6'-double bond of (halo or dihalohomovinyl)-adenosines causing covalent binding inhibition, we designed and synthesized AdoHcy analogues with the 5',6'-olefin motif incorporated in place of the carbon-5' and sulfur atoms. From the available synthetic methods we chose two independent approaches: the first approach was based on the construction of a new C5'- C6' double bond via metathesis reactions, and the second approach was based on the formation of a new C6'-C7' single bond via Pd-catalyzed cross-couplings. Cross-metathesis of the suitably protected 5'-deoxy-5'-methyleneadenosine with racemic 2-amino-5-hexenoate in the presence of Hoveyda-Grubb's catalyst followed by standard deprotection afforded the desired analogue as 5'E isomer of the inseparable mixture of 9'RIS diastereomers. Metathesis of chiral homoallylglycine [(2S)-amino-5-hexenoate] produced AdoHcy analogue with established stereochemistry E at C5'atom and S at C9' atom. The 5'-bromovinyl analogue was synthesized using the brominationdehydrobromination strategy with pyridinium tribromide and DBU. Since literature reports on the Pd-catalyzed monoalkylation of dihaloalkenes (Csp2-Csp3 coupling) were scarce, we were prompted to undertake model studies on Pdcatalyzed coupling between vinyl dihalides and alkyl organometallics. The 1-fluoro-1- haloalkenes were found to undergo Negishi couplings with alkylzinc bromides to give multisubstituted fluoroalkenes. The alkylation was trans-selective affording pure Zfluoroalkenes. The highest yields were obtained with PdCl 2(dppb) catalyst, but the best stereochemical outcome was obtained with less reactive Pd(PPh3)4 . Couplings of 1,1- dichloro-and 1,1-dibromoalkenes with organozinc reagents resulted in the formation of monocoupled 1-halovinyl product.

ZnO nanorods prepared via ablation of Zn with millisecond laser in liquid media

ZnO nanomaterials with controlled size, shape and surface chemistry are required for applications in diverse areas, such as optoelectronics, photocatalysis, biomedicine and so on. Here, we report on ZnO nanostructures with rod-like and spherical shapes prepared via laser ablation in liquid using a laser with millisecond-long pulses. By changing laser parameters (such as pulse width and peak power), the size or aspect ratio of such nanostructures could be tuned. The surface chemistry and defects of the products were also strongly affected by applied laser conditions. The preparation of different structures is explained by the intense heating of liquid media caused by millisecond-long pulses and secondary irradiation of already-formed nanostructures.

Highly stable PEGylated gold nanoparticles in water: applications in biology and catalysis

Gold nanoparticles (Au NPs) with diameters ranging between 5-60 nm have been synthesised in water, and further stabilized with polyethylene glycol-based thiol polymers (mPEG-SH). Successful PEGylation of the Au NPs was confirmed by Dynamic Light scattering (DLS) and Zeta potential measurements. PEG coating of the Au NPs is the key of their colloidal stabilty, and its successful applications. Catalytic efficiency testing of the PEG-AuNPs were carried out on homocoupling of boronic acid. PEG-Au NPs with AuNps diameter < 30 nm were useful as catalyst in water. Finally, the PEG-Au NPs were also shown to be stable in biological fluid and not cytotoxic on B16.F10 cell line, making them attractive for further studies.

Essays on Firm Heterogeneity with Empirical Applications in Economic History and Agricultural Economics

This thesis uses models of firm-heterogeneity to complete empirical analyses in economic history and agricultural economics. In Chapter 2, a theoretical model of firm heterogeneity is used to derive a statistic that summarizes the welfare gains from the introduction of a new technology. The empirical application considers the use of mechanical steam power in the Canadian manufacturing sector during the late nineteenth century. I exploit exogenous variation in geography to estimate several parameters of the model. My results indicate that the use of steam power resulted in a 15.1 percent increase in firm-level productivity and a 3.0-5.2 percent increase in aggregate welfare. Chapter 3 considers various policy alternatives to price ceiling legislation in the market for production quotas in the dairy farming sector in Quebec. I develop a dynamic model of the demand for quotas with farmers that are heterogeneous in their marginal cost of milk production. The econometric analysis uses farm-level data and estimates a parameter of the theoretical model that is required for the counterfactual experiments. The results indicate that the price of quotas could be reduced to the ceiling price through a 4.16 percent expansion of the aggregate supply of quotas, or through moderate trade liberalization of Canadian dairy products. In Chapter 4, I study the relationship between farm-level productivity and participation in the Commercial Export Milk (CEM) program. I use a difference-in-difference research design with inverse propensity weights to test for causality between participation in the CEM program and total factor productivity (TFP). I find a positive correlation between participation in the CEM program and TFP, however I find no statistically significant evidence that the CEM program affected TFP.

Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud

Cloud computing offers massive scalability and elasticity required by many scien-tific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new oppor-tunities for application developers. This paper investigates how workflow sys-tems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.

Axis Mapping: The Estimation of Surface Orientations and its Applications in Vehicle Localization and Structural Geology

The map representation of an environment should be selected based on its intended application. For example, a geometrically accurate map describing the Euclidean space of an environment is not necessarily the best choice if only a small subset its features are required. One possible subset is the orientations of the flat surfaces in the environment, represented by a special parameterization of normal vectors called axes. Devoid of positional information, the entries of an axis map form a non-injective relationship with the flat surfaces in the environment, which results in physically distinct flat surfaces being represented by a single axis. This drastically reduces the complexity of the map, but retains important information about the environment that can be used in meaningful applications in both two and three dimensions. This thesis presents axis mapping, which is an algorithm that accurately and automatically estimates an axis map of an environment based on sensor measurements collected by a mobile platform. Furthermore, two major applications of axis maps are developed and implemented. First, the LiDAR compass is a heading estimation algorithm that compares measurements of axes with an axis map of the environment. Pairing the LiDAR compass with simple translation measurements forms the basis for an accurate two-dimensional localization algorithm. It is shown that this algorithm eliminates the growth of heading error in both indoor and outdoor environments, resulting in accurate localization over long distances. Second, in the context of geotechnical engineering, a three-dimensional axis map is called a stereonet, which is used as a tool to examine the strength and stability of a rock face. Axis mapping provides a novel approach to create accurate stereonets safely, rapidly, and inexpensively compared to established methods. The non-injective property of axis maps is leveraged to probabilistically describe the relationships between non-sequential measurements of the rock face. The automatic estimation of stereonets was tested in three separate outdoor environments. It is shown that axis mapping can accurately estimate stereonets while improving safety, requiring significantly less time and effort, and lowering costs compared to traditional and current state-of-the-art approaches.