Many of researchers have written about social responsibility and business strategy and competitive advantage, and they have given particular attention to the relationship between economic and social responsibility , but what is missing in this aspect is how the economic units that use their core competencies to advance social responsibility initiatives so that they can achieve a significant competitive advantage and create value for it ?

The current research aims to verify the view that "the economic and social objectives in the long term is not contradictory in nature but complementary objectives essential", as well as make sure that the s

Gas sensors are essential for detecting noxious gases that have a detrimental effect on people's health and welfare. Carbon quantum dots (CQDs) are the fundamental component of gas detectors. CQDs and graphene (Gr) were prepared using the electrochemical method. The gas sensitivity of these materials was evaluated at different temperatures (150, 200, 250 °C) to assess their effectiveness. Subsequently, experiments were conducted at different temperatures to ascertain that the combination of CQDs and Gr, with various percentages of Gr and CQDs, exhibited superior gas sensitization properties compared to CQDs alone. This was evaluated based on criteria such as sensitivity, recovery time, and reaction time. Interestingly, the combination was

The best optimum temperature for the isolate was 30○C while the pH for the maximum mineral removal was 6. The best primary mineral removal was 100mg/L, while the maximum removal for all minerals was obtained after 8 hrs, and the maximum removal efficiency was obtained after 24 hrs. The results have proved that the best aeration for maximum removal was obtained at rotation speed of 150 rpm/ minute. Inoculums of 5ml/ 100ml which contained 106 cell/ ml showed maximum removal for the isolate.

The corrosion protection of low carbon steel in 2.5 M HCl solution by kiwi juice was studied at different temperatures and immersion times by weight loss technique. To study the determination of the optimum conditions from statistical design in evaluation of a corrosion inhibitor, three variables, were considered as the most dominant variables. These variables are: temperature, inhibitor concentration (extracted kiwi juice) and immersion time at static conditions.

These three variables are manipulated through the experimental work using central composite rotatable Box – Wilson Experimental Design (BWED) where second order polynomial model was proposed to correlate the studied variables with the corrosion rate o

The pretreatment process can be considered one of the important processes in wastewater treatment, especially coagulation process to decrease the strength of many pollutants. This paper focused on using powdered date seeds as natural coagulant in addition to chemical coagulants (alum and ferric chloride) to find the optimum dosage of each coagulant that makes efficient removal of turbidity and chemical oxygen demand (COD) from domestic wastewater as a pretreatment process, then finding the optimum combined dosages of date seeds with alum, date seeds with ferric chloride that make efficient removal for both pollutants. Concerning turbidity, the optimum dosage for date seeds, alum and ferric chloride were 40 mg/l (79%), 70

To obtain the approximate solution to Riccati matrix differential equations, a new variational iteration approach was ‎proposed, which is suggested to improve the accuracy and increase the convergence rate of the approximate solutons to the ‎exact solution. This technique was found to give very accurate results in a few number of iterations. In this paper, the ‎modified approaches were derived to give modified solutions of proposed and used and the convergence analysis to the exact ‎solution of the derived sequence of approximate solutions is also stated and proved. Two examples were also solved, which ‎shows the reliability and applicability of the proposed approach. ‎

This study was established to investigate the correlation between the expression of matrix metalloproteinases (MMP-1) and the pathogenesis of osteoarthritis (OA). Blood samples were collected from 55 female patients with inflammatory OA and controls for estimation of serum (MMP-1) levels. In the current study, there is significant increase (p<0.001) in the mean of serum MMP-1 levels in osteoarthritis females (4027.73 ± 1345.28 pg/ml) than that in control females (798.76 ± 136.79 pg/ml). It was concluded that MMP-1 may be associated with the pathogenesis of osteoarthritis.

This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J

Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati