In the present work polymer electrolytes were formulated using the solvent casting technique. Under special conditions, the electrolyte content was of fixed ratio of polyvinylpyrolidone (PVP): polyacrylonitrile (PAN) (25:75), ethylene carbonate (EC) and propylene carbonate (PC) (1:1) with 10% of potassium iodide (KI) and iodine I₂ = 10% by weight of KI. The conductivity was increased with the addition of ZnO nanoparticles. It is also increased with the temperature increase within the range (293 to 343 K). The conductivity reaches maximum value of about (0.0296 S.cm^-1) with (0.25 g) ZnO. The results of FTIR for blend electrolytes indicated a significant degree of interaction between the polymer blend (PVP and PAN)

With the narratives and sayings in the biography of the Prophet and the science of the Koran, Orientalists used this case as a pretext to distort the biography of the Prophet and his character and patience for his call. Researcher in the folds of his research.

Fe, Co and Sb nanopowders were fruitfully prepared by electrical wire explosion method in Double distilled and de-ionized water (DDDW) media. The formation of iron, cobalt and antimony (FeCoSb) alloy nanopowder was monitored by X-ray diffraction. The x-ray diffraction pattern indicates that there are iron, cobalt and antimony peaks. Optical properties of this alloy nanoparticles were characterized by UV-Visible absorption spectra. The absorption peak position is shifted to the lower wavelengths when the current increases. That means the mean size of the nanoparticles controlled by changing the magnitude of the current. The surface morphological analysis is carried out by employing Scanning Electron Microscope (SEM). Particles with varies

The objective of this research is to develop a method for applying financial derivatives in the local environment to reduce the risk of foreign exchange rate fluctuations to enhance quality of accounting profits through Financial reporting to local units In accordance with international financial reporting standards, To accomplish this objective was selected a sample of Iraqi units exposed to the risk of fluctuations in foreign currency rates, As the research found:

• many companies and banks in the local environment a lot of losses due to fluctuations in foreign currency exchange rates.
• that financial derivatives in the Iraqi environment represent

A novel technique Sumudu transform Adomian decomposition method (STADM), is employed to handle some kinds of nonlinear time-fractional equations. We demonstrate that this method finds the solution without discretization or restrictive assumptions. This method is efficient, simple to implement, and produces good results. The fractional derivative is described in the Caputo sense. The solutions are obtained using STADM, and the results show that the suggested technique is valid and applicable and provides a more refined convergent series solution. The MATLAB software carried out all the computations and graphics. Moreover, a graphical representation was made for the solution of some examples. For integer and fractional order problems, solutio

Abstract. This study presents experimental and numerical investigation on the effectiveness of electrode geometry on flushing and debris removal in Electrical Discharge Drilling (EDD) process. A new electrode geometry, namely side-cut electrode, was designed and manufactured based on circular electrode geometry. Several drilling operations were performed on stainless steel 304 using rotary tubular electrodes with circular and side-cut geometries. Drilling performance was characterized by Material Removal Rate (MRR), Electrode Wear Rate (EWR), and Tool Wear Ratio (TWR). Dimensional features and surface quality of drilled holes were evaluated based on Overcut (OC), Hole Depth (HD), and Surface Roughness (SR). Three-dimensional

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial