Lactococcus lactis as a vector for oral vaccine delivery : the case of enterohemorrhagic Escherichia coli

In the present thesis we describe the utilization of the live vaccine delivery vector, L. lactis for the development of an oral vaccine against EHEC infection. The vaccine is based on the recombinant expression of the EHEC T3SS protein, EspB in L. lactis. The recombinant vaccine strains could successfully induce mucosal and systemic immune responses in mice upon oral immunization. These responses characterized by the presence of EspB-specific IgA antibodies in the feces and total Igs in the serum. Additionally, a mixed Th1/Th2 response was detected in Peyer’s patches and mesenteric lymph nodes. Furthermore, immunized mice showed protection against intestinal colonization by E. coli O157:H7 upon oral challenge. These findings demonstrate, for the first time, the potential of EspB as a candidate for oral vaccination against EHEC as well as the value of L. lactis as a vaccine delivery vector. The development of an oral vaccine based on the “GRAS” vector, L. lactis, can be particularly beneficial to infants and the elderly, which are the high risk groups for the complications of the hemolytic uremic syndrome. Additionally, the present thesis we address the issue of the gastrointestinal survival of L. lactis in pigs. We offer a proof of concept for the feasible use of aluminium hydroxide (bile acid binder) and camostat mesylate (oral trypsin inhibitor) in oral formulations of L. lactis-based vaccines to improve the gastrointestinal survival of the bacterium in pigs. This will particularly allow the validation of L. lactis-based vaccines in porcine models of infection, which are proven more reliable in the case of EHEC infection. Additionally, with consideration to the physiological similarities between pigs and humans, the application of these protectants can be extended to improve the gastrointestinal survival of L. lactis in humans

GPU Computing Taxonomy

Over the past few years, a number of efforts have been made to obtain benefits from graphic processing unit (GPU) devices by using them in parallel computing. The main advantage of GPU computing is that it provides cheap parallel processing environments for those who need to solve single program multiple data (SPMD) problems. In this chapter, a GPU computing taxonomy is proposed for classifying GPU computing into four different classes depending on different strategies of combining CPUs and GPUs

Comparison of Brachypodium and Wheat Response to Hessian Fly

Wheat (Triticum aestivum) yield is limited by biotic stresses such as Hessian fly [Mayetiola destructor (Say)] attack which causes a significant annual loss. Previous studies have shown that Brachypodium distachyon is resistant to Hessian fly infestation. Since B. distachyon has advantages over wheat to be used as a model plant in genetic and genomics, we compared the response of 5 wheat lines (4 resistant lines, harboring different Hessian fly-resistance H genes, and 1 susceptible line to Hessian fly infestation) to B. distachyon at early stages [12 hours, 1 day, 3 days and 5 Days After Hessian fly egg-Hatch (DAH)] of Hessian fly infestation. Using q-RT-PCR, we studied the expression profile of some Hessian fly-responsive genes as well as genes involved in plant resistance/susceptibility to pathogens and insects. Based on the current data, we conclude that, for some genes, expression level and timing differ among wheat lines carrying different resistance H genes conferring resistance to Hessian fly. We also conclude that the gene-for-gene resistance of wheat and the non-host resistance of B. distachyon utilize a few different gene sets in defense against Hessian fly. We have also investigated the expression profiles of genes associated with Hessian fly resistance and susceptibility expressed in four tissues (leaf 2 base, leaf 2 blade, leaf 3 base and root) of wheat lines H9-Iris (resistant) and Newton (susceptible) at 1, 3 and 5 DAH to determine whether Hessian fly attack caused systemic or localized responses in wheat. qRTPCR data revealed that wheat response to Hessian fly resistance is localized. In contrast to resistance, wheat response to Hessian fly susceptibility is systemic. These results indicate that wheat resistance to Hessian fly is very efficient with less energy and resources consumed than if the entire plant produced defense molecules. Using light microscope, we conducted a study of Hessian fly larval body area on Hessian fly-resistant and -susceptible wheats to determine whether the Hypersensitive Response (HR) might play a role in Hessian fly resistance. Results revealed that sizes of larvae on a resistant wheat line utilizing the HR did not significantly differ from those of larvae on a resistant wheat line that did not express the HR

The effects of using an Electronic Interactive Whiteboard in Developing students’’ Attitude, Cognitive Motivation and Academic achievement

The aim of this study was to identify the effects of the use of an interactive whiteboard on the development of the students’ attitude towards study, cognitive motivation, and academic achievement in the eighth grade in basic education in the Sultanate of Oman. The attitude towards study, cognitive motivation and academic achievement scales was applied to a sample of (176) students from two basic education schools in one area. 86 students were chosen from school one as an experimental group and they used the electronic interactive board in teaching, and 90 students were chosen from school two as a control group using conventional way. Results showed statistically significant differences between the students in the two groups in the attitude towards study, cognitive motivation and its dimensions (motivation to acquire knowledge, the risk of acquiring knowledge and employment of knowledge), and academic achievement in favor to the students using the interactive whiteboard. The researchers recommended the use of interactive whiteboard technology in all schools, and training teachers to integrate it in teaching. Keywords.  electronic interactive whiteboard - attitude towards study- cognitive motivation -academic achievement. DOI: 10.7176/JEP/10-10-15 Publication date: April 30th 201

Optimal Planning and Operation of AC-DC Hybrid Distribution Systems

Recent years have been marked by a significant increase in interest in green technologies, which have led to radical changes in the way electric power is generated and utilized. These changes have been accompanied by greater utilization of DC-based distributed generators (DGs), such as photovoltaic (PV) panels and fuel cells, as well as DC-based load demands, such as electric vehicles (EVs) and modern electronic loads. In addition to accommodating these technologies, future distribution systems (DSs) will also need to support the integration of additional battery storage systems with renewable DGs. A further factor is the number of policies that have been implemented in Ontario, Canada, with the goal of encouraging the use of clean energy. The first, the feed-in-tariff (FIT) program, was introduced to promote the application of renewable DGs, including PV panels and wind DGs, and a second, new program that offers incentives for switching to EVs has been announced recently. The result is that future DSs must include additional DC loads and DC-based DGs along with their present AC loads and energy resources. Future DSs should thus become AC-DC hybrids if they are to provide optimal accommodation of all types of AC and DC loads and DGs. These considerations accentuate the need for reliable techniques appropriate for the planning and operation of future hybrid DSs. This thesis presents new directions for the planning and operation of AC-DC hybrid DSs. The main target of the research presented in this thesis is to optimally accommodate the expected high penetration of DC loads and DC-based DGs in future DSs. Achieving this target entailed the completion of four consecutive parts: 1) developing a unified load flow (LF) model for AC-DC hybrid DSs, 2) introducing an energy management scheme (EMS) for the optimal operation of AC-DC hybrid DSs, 3) introducing a planning model to determine the optimal AC-DC network configuration that minimizes the costs of the hybrid DS, and 4) developing a reliability-based planning technique for the simultaneous optimization of the DS costs and reliability. The first part of this research introduces a novel unified LF model for AC-DC hybrid DSs. The LF model can be applied in hybrid DSs with a variety of configurations for AC/DC buses and AC/DC lines. A new classification of DS buses is introduced for LF analysis. Three binary matrices, which are used as a means of describing the configuration of the AC and DC buses and lines, have been employed in the construction of the unified power equations. The LF model is generic and can be used for both grid-connected and isolated hybrid DSs. The new model has been tested using several case studies of hybrid DSs that include different operational modes for the AC and DC DGs. The effectiveness and accuracy of the developed LF model has been verified against the steady-state solution produced by PSCAD/EMTDC software. The second part presents a two-stage EMS that can achieve optimal and reliable operation for AC-DC hybrid DSs. The first stage introduces a network reconfiguration algorithm to determine the optimal day-ahead reconfiguration schedule for a hybrid DS, while considering the forecasted data for load demands and renewable DGs. The objective of the reconfiguration algorithm is the minimization of DS energy losses. The second stage introduces a real-time optimal power flow (OPF) algorithm that minimizes the DS operation costs. In addition, a load-curtailment-management (LCM) technique is integrated with the OPF algorithm in order to guarantee optimal and reliable DS operation in the case of abnormal operating conditions. The third part presents a novel stochastic planning model for AC-DC hybrid DSs. Taking into account the possibility of each line/bus being AC or DC, the model finds the optimal AC-DC hybrid configuration of buses and lines in the DS. It incorporates consideration of the stochastic behavior of load demands and renewable DGs. The stochastic variations are addressed using a Monte-Carlo simulation (MCS). The objective of the planning model is the minimization of DS investment and operation costs. The developed planning model has been employed for finding the optimal configuration for a suggested case study that included PV panels, wind DGs, and EV charging stations. The same case study was also solved using a traditional AC planning technique in order to evaluate the effectiveness of the hybrid planning model and the associated cost-savings. The last part of this research introduces a stochastic multi-objective optimization model for the planning of AC-DC hybrid DSs. The introduced model determines the optimal AC-DC network configuration that achieves two objectives: 1) minimizing system costs, and 2) maximizing system reliability. Network buses and lines can become either AC or DC in order to achieve the planning objectives. The model features an MCS technique for addressing stochastic variations related to load demands and renewable DGs. The developed model has been tested using a case study involving a hybrid DS that included a variety of types of loads and DGs. Solving the same case study using a traditional AC planning technique provided verification of the benefits offered by the developed model, whose efficacy was confirmed through a comparison of the AC and hybrid Pareto fronts. The developed planning framework represents an effective technique that can be used by DS operators to identify the optimal AC-DC network configuration of future hybrid DSs