The rivers are the main source of fresh water for many countries and the great development which is considered as one of the sustainable development elements in its various agricultural, industrial, domestic and environmental fields .The countries of the world seek food security and water security in order to ensure the basic needs of citizens .Because their distribution is uneven in many regions of the world with different human needs, which leads to conflicts over water sources, especially those located in one international river basin .This has led to the emergence of internationallegal rules governing the management of The problem revolves around the dialectic between limited water resources and increased need for water use b

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Green synthesis methods have emerged as favorable techniques for the synthesis of nano-oxides due to their simplicity, cost-effectiveness, eco-friendliness, and non-toxicity. In this study, Nickel oxide nanoparticles (NiO-NPs) were synthesized using the aqueous extract of Laurus nobilis leaves as a natural capping agent. The synthesized NiO-NPs were employed as an adsorbent for the removal of Biebrich Scarlet (BS) dye from aqueous solution using adsorption technique. Comprehensive characterization of NiO-NPs was performed using various techniques such as atomic force microscopy (AFM), Fourier transform infrared (FTIR), X-ray diffraction (XRD), Brunauer-Emmett and Teller (BET) analysis, and scanning electron microscopy (SEM). Additionally, o

Objective: to evaluate the results of (Modification of Russe method) in treatment of nonunion fracture scaphoid bone by bone graft with external splintage (plaster of paris cast (pop ).
Methods:Prospective study done on 26 patients (24 male, 2 female), age range between 25-42 years (mean age 34 years), fracture site at middle 1/3 with minimal displacements with no carpal bone or radial bone injury, technique of Matte- Russe method (explore the bone through volar approach using bone graft from iliac crest (cortico-cancellous peg plus cancellus bone) with thumb spica for 90 days with period of follow up 12-18 months.
Results: out of 26 patients treated by this method , 23 patients (88.5%) union was achieved radiologically by the end

Conclusion :

The conflict between the fundamentalist and news theory in the methodology that each of the two schools pursued with the Twelver Shi'a Imamiyyah in deriving the legal rulings from the sources of legislation, especially in the second source, which is the noble hadith and narration after the Holy Qur’an, which is the first source has gone through multiple and complex stages that led This struggle to excess, stress, exaggeration, negligence, neglect and indulgence by each of the two schools in dealing with the noble hadith and narration and in the manufacture of rules and laws and fundamentalist and juristic theories of the process of jurisprudential development of legal rulings where every school believed and proceed

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

Two- dimensional numerical simulations are carried out to study the elements of observing a Dirac point source and a Dirac binary system. The essential features of this simulation are demonstrated in terms of the point spread function and the modulation transfer function. Two mathematical equations have been extracted to present, firstly the relationship between the radius of optical telescope and the distance between the central frequency and cut-off frequency of the optical telescope, secondly the relationship between the radius of the optical telescope and the average frequency components of the modulation transfer function.

Shumblan (SH) is one of the most undesirable aquatic plants widespread in the irrigation channels and water bodies. This work focuses on boosting the biogas potential of shumblan by co-digesting it with other types of wastes without employing any chemical or thermal pretreatments as done in previous studies. A maximum biogas recovery of 378 ml/g VS was reached using shumblan with cow manure as inoculum in a ratio of 1:1. The methane content of the biogas was 55%. Based on volatile solid (VS) and C/N ratios, biogas productions of 518, 434, and 580 ml/g VS were obtained when the shumblan was co-digested with food wastes (SH:F), paper wastes (SH:P), and green wastes (SH:G) respectively. No significant changes of methane contents were observ