Grief and Shock, Discernment and Dificulties, Their Reasons and Motives in the Light of the Teachings of the Holy Prophet (PBUH)

Islam has this faith that everything of the universe, small or big has come into existence with the will, power, method and knowledge of Allah. Fate is the attribution of Allah, which is the truth. It is the condition to have belief of this faith. Since, faith is the attribution of Allah and it’s impossible for anyone to know the extent of godly attributions, so the issue of fate is delicate and precise. One must only have the faith that whatever is happening in the world was already in the knowledge of Allah and god has already saved it on the safe tablet. The dilemma of fate has not been solved by anyone and it will never be solved. There must be a simple faith that whatever is happening in the world has already known by Allah as the Creator of everything is God and everything has come into existence with His creation. All the matters happening in the world are of two kinds. In some of them the will and authority is prevail. In these matters which are to be done which are not to be done orders of their execution or prohibition are given. If they are not performed because of will and authority, there will be accountability for them. Secondly, all those works which have the order of not to be performed, it is necessary not to perform them with one’s will and authority. If those works are not avoided, one must be accountable for them. There are some other works which do not involve our will and authority so, whatever happens is according to our fate. The works having our will and authority for performance will be rewarded and punished accordingly. This study explores the reasons of grief, shock, discernment and difficulties, their reasons and motives in the light of teaching of The Holy Prophet.

Water Quality Assessment Model of the Mediterranean Sea Along Gaza- Palestine

In view of the protection of Gaza coastal and marine environment from further deterioration and reverse the process from polluted to clean marine environment, it was necessary to analyse the seawater quality data and develop several artificial neural network (ANN) models to predict various water quality parameters. Hence, this study was undertaken with this objective. Even though there have been a few monitoring and evaluation literatures on the status of seawater pollution, however to the utmost of facts this work is the initial effort to use (ANN) technology for the prediction of seawater quality along Gaza coast. Additionally the land-based sources causing pollution along Gaza coastal waters have been assessed and also a management plan for Gaza coastal and marine environment protection proposed. All seawater quality monitoring data were inserted into Minitab statistical software and analysed by different tools including: min, max, mean, standard deviation and geometric mean. In addition, the Pearson correlation coefficient and paired sample t- test were used to perceive significant water quality differences at various sampling locations. The core objective of this work was to investigate whether it is possible to predict the next two weeks values of water quality parameters such as pH, electrical conductivity (EC), dissolved oxygen (DO), biological oxygen demand (BOD 5 ), Total kjeldahl nitrogen (TKN) and orthophosphate (Ortho-P). The data used was measured by several water quality monitoring programs in the Mediterranean Sea along Gaza. At the initial stage of the prediction of water quality variables, real water quality data along Gaza coast, over a period of four years beginning from 1997 to 2001, were collected from the Environment Quality Authority, the Environmental and Rural Research Centre-Islamic University of Gaza, Ministry of Health and some other organisations. The training and testing of the developed ANN assessment models was carried out using neural network toolbox in the MATLAB. Two types of feedforward networks have been used. They are Multilayer Perceptron (MLP) and Radial Basis Function (RBF) neural networks. xxiFour different MLP neural networks have been trained and developed with reference to water temperature, wind velocity and turbidity parameters to predict pH and EC fortnight’s values. MLP and RBF neural networks have been used for predicting the next fortnight’s dissolved oxygen concentrations. Both networks are trained and developed with reference to the five oceanographic variables including water temperature, wind velocity, turbidity, pH and conductivity. MLP neural network has also been trained to predict BOD 5 level. MLP and RBF neural networks have been trained with five parameters to predict nutrients (TKN and Ortho-P) level along Gaza coast. Prediction results prove that both types of networks are highly satisfactory for predicting water quality parameters in the Mediterranean Sea along Gaza coast. Results of the developed networks have also been compared with the statistical model and found that ANN predictions are better than the conventional methods. The human activities including: urbanisation in coastal areas, wastewater pollution, coastal activities, agricultural loads, industrial pollution, influence of fisheries and solid waste as well as debris exert pressure on the marine and coastal environment. All these are land-based sources causing pollution along Gaza coastal environment. In order to reduce the load of pollution in the coastal waters of Gaza, it is recommended that the Palestinian Environment Quality Authority (EQA) shall play a major and active role in implementing the Gaza coastal environmental management plan (GCEMP). Therefore, EQA shall prepare the short term and long term action plans through coordination with all the relevant stakeholders. It is hoped that ANN developed models and the proposed management plan will help in assisting the local authorities in developing plans that are necessary to minimise the sources that cause pollution along Gaza coastal waters.