Utilization of municipal solid waste rejects in producing wave dispersion and shoreline erosion protection structures (breakwaters)

The work presented in this thesis is about utilizing municipal solid waste (MSW) rejects in producing wave dispersion and shoreline erosion protection structures to counter the negative impacts of sea level rise. The tests selected to evaluate the produced samples included physical property tests, accelerated weather tests and environmental tests. The physical property tests included: specific gravity and density, absorption, compression and abrasion, while the accelerated weather tests included wet-dry test and soundness test. In addition to these tests, leachate was analyzed after the samples were immersed in sea water and fresh water for 28 days. The exhaust gases from the mixing furnace – used to produce samples - were also analyzed to ensure compliance with air emission standards. The produced samples consisted mainly of low density polyethylene rejects (garbage bags), thus the results were compared to low and high density polyethylene as well as concrete bricks and tiles. The produced samples exhibited good floating characteristics at zero percent sand content. The overall characteristics of 40&50% sand content samples were comparable to concrete and superior to polyethylene. The produced material showed excellent reaction to accelerated weather tests. The total percent loss due to abrasion was minimal. Leachate from seawater showed high TDS due to evaporation of water resulting in increased concentration of salt. However, the overall analysis showed no health hazards. The exhaust gas emission parameters were within the air emission standards set by the Egyptian Environmental Law 4/1994. The MSW rejects could thus be utilized as floating breakwaters using 0% sand content, solid submerged structural breakwaters using 40% sand content, and 50% sand content for beach/canal revetments. Future recommended applications for further investigation could include usage as interlocking ground reinforcement tiles, reef ball and artificial reef

Tilapia: From the Nile to the world.

This study addressed the potential of tilapia aquaculture as a major contributor to food production and poverty alleviation all over the world. To encompass this subject, tilapia history, origin, aquaculture potential, constraints, current and future production levels were reviewed. Tilapias are native to the River Nile and Africa in general then they were introduced and disseminated worldwide. Positive aquacultural characteristics of tilapia made tilapias the most cultured species worldwide now and in the near future. Tilapia world production is expected to reach 3 million tons this year 2010. Thus, tilapias could make a significant contribution to the livelihoods support especially in the tropical and subtropical countries

A new marketing mix model to rescue the hospitality industry: Evidence from Egypt after the Arab Spring

After January 25th 2011 Egypt witnessed political, economic and social instability leading to drastic consequences in the hospitality and tourism industry. Thus unstable situation reflected on the deteriorated occupancy percentages that led to declined profit margins, higher employee layoffs and degraded quality of product and services. The objectives of this research is to examine how the Egyptian hospitality properties manage this dilemma through their marketing practices, and to propose a new marketing mix model that adds new layers of depth to the traditional marketing mix model. A methodological framework was designed to help in the assessment process of management practices pertaining to marketing initiatives during times of crisis. Results indicated the presence of tactical elements that assembled the traditional marketing mix model in the investigated hotels. However, these elements are not effectively used and the interaction between them not appears very clear. Results also indicated that the new proposed model would help in providing a framework for the Egyptian hospitality industry to maintain their competitive position during crisis time and avoiding undesired situations for labour force and decline of companies׳ revenues.The authors are grateful to the FEMISE (Forum Euro-Mediterranean of Institutes of Economics). This research received financial assistance of the European union in the contest of the FEMISE programme (projectFEM41-04). We are grateful to the anonymous referees of the journal. Earlier version published at the FEMISE International Conference13–14 February2016.The views expressed in this paper are those of the author and do not necessarily represent the MSA University

Physico-chemical behaviors of shale/fluid/solute interaction in geo-environmental and geo-engineering applications.

This dissertation examines the rich and complex physical-mechanical behaviors exhibited by shales when exposed to differing solutions over time, temperature, chemical, and stress conditions. Using several unique experimental designs and numerical modeling, this study advances the level of understanding of time dependent shale behavior arising from changes in clay mineral structure and crystalline phase.The flux of water and ions over time due to semi-permeable membrane properties of shale and very fine-grained material has been numerically modeled. The purposes of this model are to predict the flux of fluid and ions through natural geological fine-grained and clay-rich materials over time and to predict the effect of this flux on long-term shale membrane behaviors. The required input parameters for the model, including water activity of both interfacial chemical fluid and the pore-fluid of the membrane, membrane properties (reflection coefficient, porosity, hydraulic conductivity, mineral compressibility, diffusion processes), and temperature and pressure conditions, were determined by laboratory work on Pierre Shale using High-Temperature High-Pressure (HTHP) Shale Apparatus. Results of this model reveal that, due to the flux of solute through the semi-permeable membrane, the shale's pore fluid activity will reduce through time, leading to a reduction in the ideality of the membrane. Given enough time (depending on the activity of the chemical used and the membrane thickness and permeability), the chemical and hydraulic difference across the membrane will disappear, leading to a diminishing of the osmotic fluid flux. This model can help in correlating and representing the semi-permeable membrane behavior of fine-grained and clay-rocks, and enhance understanding of the relevant processes. The implications for geo-environmental exploitation of the membrane properties of shales are discussed in light of these results. (Abstract shortened by UMI.)Artificial dewatering of shales is a method to eliminate shale related problems such as wellbore stability, swelling, and soil instability that produces landslides. In this dissertation, the semi-permeable membrane behavior of shale, permitting osmotic flux of fluid to the partial exclusion of ions, has been studied as a means to dewater shales exposed to chemical solutions with ion activities less than that of the in situ shale pore fluid

Modeling of local scour depth downstream hydraulic structures in trapezoidal channel using GEP and ANNs

AbstractLocal scour downstream stilling basins is so complex that it makes it difficult to establish a general empirical model to provide accurate estimation for scour depth. Lack estimation of local scour can endanger to stability of hydraulic structure and can cause risk of failure. This paper presents Gene expression program (GEP) and artificial neural network (ANNs), to simulate local scour depth downstream hydraulic structures. The experimental data is collected from the literature for the scour depth downstream the stilling basin through a trapezoidal channel. Using GEP approach gives satisfactory results compared with artificial neural network (ANN) and multiple linear regression (MLR) modeling in predicting the scour depth downstream of hydraulic structures

Evaluation of Four Novel Imported and Egyptian Curly and Non-Curly Leafed Parsley Genotypes for Yield and Essential Oil Composition Under The Egyptian Sandy Soil Growing Conditions

Four novel parsley genotypes (Moskurl 2 Petra, Moskurl 2 KRA USA, Gewone Dai 3 Rial 10, and Bravour) were imported from Netherlands to be planted and evaluated along with the Egyptian local variety “Egyptian” in the sandy soil under the Middle Egypt growing conditions. Three of the four introduced genotypes are curly-leafed varieties and one is non-curly leafed “Gewone Dai 3 Rial 10” as well as the Egyptian is a non-curly leafed variety. The aims of this experiment were to evaluate and study the growth characteristics (e.g. plant height, plant fresh and dry weights and fresh yield of leaves/m2) and some chemical properties of these genotypes (e.g. TSS and essential oil contents, essential oil composition and leaves content of chlorophyll a, b, and carotenoids) after adaptation and growing during the two successive winter seasons of 2013/2014 and 2014/2015. All introduced genotypes grew very well under these conditions and showed a very acceptable vegetative growth, profitable yield and high levels of volatile oils rich in anticancer and flavor responsible compounds and their horticultural and chemical proprieties were compared with those of the Egyptian local variety. The obtained data are very promising for Egyptian parsley growers to produce these new imported varieties in order to meet the increasing demand of parsley fresh and dry processed products with different shapes and different tastes of the Egyptian and foreign markets

The impact of earnings quality on aspects of capital markets: evidence from UK listed firms

This thesis investigates the association between four accounting-based earnings quality proxies and three capital market aspects of UK listed firms after applying the International Financial Reporting Standards (IFRS). The three capital market aspects are: the cost of equity capital; information symmetry; and analysts’ information environment (number of analysts following, the dispersion of analysts’ forecasts and the accuracy of analysts’ forecasts). It finds evidences that firms with low earnings quality have a higher cost of equity capital, higher information asymmetry, lower number of analysts following, a higher dispersion of analysts’ forecasts and less accurate analysts’ forecasts than firms with high earnings quality. Also, the results show that the innate component of each earnings quality proxy, driven by economic fundamentals, has a larger impact on the three aspects of capital market than the discretionary component, driven by management choices. This is consistent with the theoretical framework of IFRS which the UK adopted in 2005 for listed firms. These findings shed light on the important role of earnings quality in helping analysts and investors to make better financial investment decisions. Theory suggests that this role is achieved by increasing the informativeness of firms’ information environment, improving the precision of financial information, reducing estimation risk and information asymmetry; these are expected to lead to a lower cost of equity capital

Machine learning approaches for epitope prediction

The identification and characterization of epitopes in antigenic sequences is critical for understanding disease pathogenesis, for identifying potential autoantigens, and for designing vaccines and immune-based cancer therapies. As the number of pathogen genomes fully or partially sequenced is rapidly increasing, experimental methods for epitope mapping would be prohibitive in terms of time and expenses. Therefore, computational methods for reliably identifying potential vaccine candidates (i.e., epitopes that invoke strong response from both T-cells and B-cells) are highly desirable. Machine learning offers one of the most cost-effective and widely used approaches to developing epitope prediction tools. In the last few years, several advances in machine learning research have emerged. We utilize recent advances in machine learning research to provide epitope prediction tools with improved predictive performance. First, we introduce two methods, BCPred and FBCPred, for predicting linear B-cell epitopes and flexible length linear B-cell epitopes, respectively, using string kernel based support vector machine (SVM) classifiers. Second, we introduce three scoring matrix methods and show that they are highly competitive with a broad class of machine learning methods, including SVM, in predicting major histocompatibility complex class I (MHC-I) binding peptides. Finally, we formulate the problems of qualitatively and quantitatively predicting flexible length major histocompatibility complex class II (MHC-II) peptides as multiple instance learning and multiple instance regression problems, respectively. Based on this formulation, we introduce MHCMIR, a novel method for predicting MHC-II binding affinity using multiple instance regression. The development of reliable epitope prediction tools is not feasible in the absence of high quality data sets. Unfortunately, most of the existing epitope benchmark data sets are comprised of epitope sequences that share high degree of similarity with other peptide sequences in the same data set. We demonstrate the pitfalls of these commonly used data sets for evaluating the performance of machine learning approaches to epitope prediction. Finally, we propose a similarity reduction procedure that is more stringent than currently used similarity reduction methods

Innovative Service Delivery in Public Sector: An Empirical Assessment in Bahraini Public Organizations

This research paper addresses the issue of innovation within the public sector. However virtually all organizations in general and service organizations in particular talk about innovation, and the importance of “doing” innovation, many actually try to “do it”, and only few actually succeed in doing it.  Therefore measuring innovation in service organizations is very difficult task to perform. This research paper aim is to assess innovative service delivery in Bahrain’ public sector and in order to achieve this aim, a  400 top, middle level managers and supervisors  are surveyed  through utilizing  and testing a Staged Service innovation model created by Song et al. (2009). This model is relating new product development (NPD) process; the five service innovation stages to proficiency of pre-launch service quality training programs. The empirical research results revealed that there is an impact relationship between the proficiency of new service development stage, proficiency of pre-launch service training and the service performance. Furthermore the research results provide new insights for public managers in order to enhance and improve service quality within their organizations by carrying out prelaunch training programs that will lead to more successful service innovation. Keywords: Innovative Service, Empirical Assessment, Public Organization