Search results

This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.

This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.

This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.

This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.

The purpose of this study is to develop an efficient model to solve the electromagnetic forward problem using a novel semi-analytical approach to compute the electromagnetic fields because of the presence of a scatterer.

The proposed model involves a novel formulation of a complete orthonormal set of radiating/nonradiating polarization currents. Furthermore, an integral equation-based representation is derived, and the appropriate boundary conditions are imposed to get the scattered electromagnetic field. An error term is introduced to evaluate the obtained results.

The proposed model was tested using several examples at different frequencies. The results of this study show that the novel representation exhibits fast convergence behavior and achieves highly accurate results, when compared to the results provided by the transmission line method.

The derived formulations presented in this study are significant in the electromagnetic forward modelling field because of the meaningful physical representation they provide. This is an important aspect that leads to precise calculation of electromagnetic fields for various applications.

A numerical solution for ‘running wet’ aircraft anti‐icing systems is developed. The model includes breakup of the water film, which exists in regions of direct impingement, into individual rivulets. The wetness factor distribution resulting from the film breakup and rivulet configuration on the surface are predicted in the numerical solution procedure. The solid wall is modelled as a multi‐layer structure and the anti‐icing system used is of the thermal type utilizing hot air and/or electrical heating elements embedded within the layers. Details of the calculation procedure and the methods used are presented.

Based on the base force element method, a two-dimensional random circle aggregate model with Monte Carlo principle is proposed to carry out research on softening curve in meso-level.

The meso-level structure of recycled concrete is considered as the five-phase materials composed of aggregate, old interfacial transition zone, old mortar, new interfacial transition zone and new mortar. A multi-polyline damage model is adopted to describe the nonlinear mechanical behavior of recycled concrete material. The destruction state of the element is determined by the first strength theory. The research studies on damage process of recycled concrete under the loading conditions of uniaxial tension were established using the base force element method.

The softening curves of recycled concrete are obtained, which are in good agreement with experiment results. Simulation results show that the macroscopic mechanical properties and failure mechanism can analyze more reasonably from mesoscopic structure. Besides that, it can be investigated from the numerical results of the size effect in recycled concrete through the mesoscopic heterogeneity. Furthermore, the form of aggregate distribution has influence on the crack path but little effect on the tensile strength of recycled concrete.

The results show that the base force element method has been successfully applied to the study of softening curve of recycled concrete under uniaxial tension.

Based on the random aggregate model of recycled aggregate concrete (RAC), this paper aims to focus on the effect of loading rate on the failure pattern and the macroscopic mechanical properties.

RAC is regarded as a five-phase inhomogeneous composite material at the mesoscopic level. The number and position of the aggregates are modeled by the Walraven formula and Monte–Carlo stochastic method, respectively. The RAC specimen is divided by the finite-element mesh to establish the dynamic base force element model. In this model, the element mechanical parameters of each material phase satisfy Weibull distribution. To simulate and analyze the dynamic mechanical behavior of RAC under axial tension, flexural tension and shear tension, the dynamic tensile modes of the double-notched specimens, the simply supported beam and the L specimens are modeled, respectively. In addition, the different concrete samples are numerically investigated under different loading rates.

The failure strength and failure pattern of RAC have strong rate-dependent characteristics because of the inhomogeneity and the inertial effect of the material.

The dynamic base force element method has been successfully applied to the study of recycled concrete.

The hydrodynamics and thermal characteristics of a laminar rivulet flow down a vertical surface are investigated. The velocity distribution within a rivulet is determined numerically by the use of a finite element method. In turn, a regression analysis is performed to fit the numerical data with an assumed closed form function. The breakup of a thin liquid film into rivulets is also considered. Heat transfer characteristics are determined. Nusselt numbers were obtained for the two cases of prescribed constant wall temperature and constant wall heat flux.

This paper aims to debate the main factors influencing trust in mobile government (m-government) in the developing country of Jordan. The transformation from government services offered through a government website to services offered via smartphone devices needs further investigation to better understand the factors that might influence citizens’ trust in m-government, in particular, young citizens. This paper presents the concept of m-government and reports on a study of the main predictors affecting citizens’ trust in it. The theoretical framework used is based on the unified theory of acceptance and use of technology (UTAUT).

A survey study of 510 Jordanian young citizens, who had access to the internet and were smartphone users, investigated the influence of the identified factors on their trust in m-government. The hypotheses testing used multiple regression analysis.

Contrary to previous claims reported in relation to facilitating conditions, the following predictors: trust in government, word of mouth (WOM), social influence and facilitating conditions were found to be significant factors in predicting Jordanian citizens’ trust in m-government services.

This is one of few studies to investigate what influences trust in m-government by citizens in Jordan. The current research significantly contributes to the literature by incorporating factors from the UTAUT model with personal perception factors to elucidate m-government adoption. The integration of UTAUT with factors such as “WOM”, is a direction that can be followed in research on the adoption of and trust in e-government and m-government by citizens in any social community. This study clearly identities the relationship between m-government trust and the WOM construct, which is rarely discussed in this type of research context. Although the facilitating conditions construct is claimed to be non-significant in the presence of performance expectancy and effort expectancy, the current research shows the importance of including the facilitating conditions construct when considering the topic of m-government trust in Jordan. Finally, this paper provides a foundation for future empirical studies on the adoption of m-government.

This study used data envelopment analysis (DEA) models to measure financial efficiency of twelve commercial banks listed in the Egyptian stock exchange (CBLSE), along with evaluating changes to the financial efficiency during the period 2017–2019.

The study used BCC-I, cross-efficiency, super-efficiency models, and Malmquist productivity index (MPI) to assess financial efficiency of the examined banks. The available data from both inputs and outputs were analyzed using R. studio V.I.3. 1056 software.

Out of twelve banks examined, only four banks were efficient under BCC-I model over different years of the study period; however, only one bank (CIB) appeared to be the most efficient compared to other peers in the study sample. Moreover, MPI results revealed decreased financial efficiency during the study period, due to the decreased technological innovation, except for HDB. Tobit regression results confirmed that total assets and total equity are significant factors impacted financial efficiency of CBLSE.

This study sheds light on the importance of evaluating financial efficiency of CBLSE to all stakeholders, to pinpoint weaknesses in banks' performance, and for evaluating financial policies and investment decisions.

Several studies sought to implement different models of DEA to assess banking performance in different regions of the world, but very few studies examined financial efficiency of banks. To the best of authors’ knowledge, this study is one of those few that addressed financial efficiency of banks in Egypt.

Wool yarns are dyed with natural colouring matter that is extracted from cochineal, turmeric and madder, and mordanted with different mordants by using the exhaustion method. Many measurements of mordanted dyed wool samples have been carried out after exposure to air and light for different periods of time in the time frame of one year in an urban area (Helwan city). The variables that are measured include changes in colour and physical properties (tensile strength, tenacity and elongation) of mordanted dyed wool samples. Also, air pollution in Helwan city is determined by studying suspended and deposited particulate matter and sulpher dioxide concentrations.

This study aims to develop and test a framework for integration between data envelopment analysis (DEA) and artificial neural networks (ANN) to predict the best financial performance concerning return on assets and return on equity for banks listed on the Egyptian Exchange, to help managers generate what-if scenarios? For performance improvement and benchmarking.

The study empirically tested the three-stage DEA-ANN framework. First, DEA was used as a preprocessor of the banks’ efficiency scores. Second, a back-propagation neural network as a multi-layer perceptron-ANN’s model was designed using expected data sets from DEA to learn optimal performance patterns. Third, the superior performance of banks was forecasted.

The results indicated that banks are not operating under their most productive operations, and there is room for potential improvements to reach outperformance. Moreover, the neural networks’ empirical test results showed high correlations between the actual and expected values, with low prediction errors in both the test and prediction phases.

Based on best performance prediction, banks can generate alternative scenarios for future performance improvement and enabling managers to develop effective strategies for performance control under uncertainty and limited data. Besides, supporting the decision-making process and proactive management of performance.

Despite the growing research stream supporting DEA-ANN integration applications, these are still limited and scarce, especially in the Middle East and North Africa region. Therefore, the study trying to fill this gap to help bank managers predict the best financial performance.