نوجوان کی تربیت اور منہج نبوی

Undoubtedly, Youth play cardinal role in the development and reformation of any society. Their activities produce an immense influence in the social development and progress. This article aimed at highlighting the important role of youth in social reforms by keeping in view the Islamic personalities like great companions of Holy Prophet (r). Descriptive and qualitative research approach was employed for the collection and analysis of data. The systematic review of scholarly literature on Islamic history revealed that the Prophet Muhammad (r) gave particular emphasize to nourish young generation in order to mold their lives into an ideal and balanced personality. He by developing intellectual, spiritual, and emotional skills produced such great men who led the mankind and became heroes of history. At the same time they appeared as ideal traders, peaceful citizens, just rulers, true followers of Holy Prophet (r) and loyal worshiper of Allah Almighty. The research by observing present condition of youth found that unfortunately our youth was found in illicit, unethical, useless, and peace demoting activities which promoted social evils and criminal activities. They got involved in unlawful activities including terrorism, killing, robbery, and kidnapping etc. By keeping view the above findings the research strongly recommends to nurture our youth on the footsteps of companions of Holy Prophet (r) in order to bring peace and prosperity in the country. Moreover they should be given awareness about the lives of heroes of Islam who appeared with great titles on the horizon.

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.