Ternary polymer blend of chitosan/poly vinyl alcohol/ poly vinyl pyrrolidone was prepared by solution castingmethod, nanocomposite was prepared by sonication method with nano Ag and Zn. All prepared compounds have been characterizedby FT-IR, SEM, DSC, as well as Biological activity. Antimicrobialactivity related to prepared blendsand Nanocomposites againstsix types of bacteria namely, Staphylococcus aureas, E. faecalis, S.typhi, P. aeruginosa, Bacillus subtilis, Escherichia coli andC. albicans fungal were examined and evaluated. The results reveal that the prepared polymer blends and nanocompositeshavegood antimicrobial activity against all kinds of microbials.

This research introduces a developed analytical method to determine the nominal and maximum tensile stress and investigate the stress concentration factor. The required tooth fillets parametric equations and gears dimensions have been reformulated to take into account the asymmetric fillets radiuses, asymmetric pressure angle, and profile shifting non-standard modifications. An analytical technique has been developed for the determination of tooth weakest section location for standard, asymmetric fillet radiuses, asymmetric pressure angle and profile shifted involute helical and spur gears. Moreover, an analytical equation to evaluate gear tooth-loading angle at any radial distance on the involute profile of spur and hel

   The economical and highly performed anode material is the critical factor affecting the efficiency of electro-oxidation toward organics. The present study aimed to detect the best conditions to prepare Mn-Co oxide composite anode for the electro-oxidation of phenol. Deposition of Mn-Co oxide onto graphite substrate was investigated at 25, 30, and 35 mA/cm² to detect the best conditions for deposition.  The structure and the crystal size of the Mn-Co oxide composite electrode were examined by using an X-Ray diffractometer (XRD), the morphological properties of the prepared electrode were studied by scanning electron microscopy (SEM) and Atomic force microscopy (AFM) techniques, and the chemical composition of the various

The reactions of ozone with 2,3-Dimethyl-2-Butene (CH3)2C=C(CH3)2 and 1,3-Butadiene CH2=CHCH=CH2 have been investigated under atmospheric conditions at 298±3K in air using both relative and absolute rate techniques, and the measured rate coefficients are found to be in good agreement in both techniques used. The obtained results show the addition of ozone to the double bond in these compounds and how it acts as function of the methyl group substituent situated on the double bond. The yields of all the main products have been determined using FTIR and GC-FID and the product studies of these reactions establish a very good idea for the decomposition pathways for the primary formed compounds (ozonides) and give a good information for the effe

Solar cells has been assembly with electrolytes including I−/I−3 redox duality employ polyacrylonitrile (PAN), ethylene carbonate (EC), propylene carbonate (PC), with double iodide salts of tetrabutylammonium iodide (TBAI) and Lithium iodide (LiI) and iodine (I2) were thoughtful for enhancing the efficiency of the solar cells. The rendering of the solar cells has been examining by alteration the weight ratio of the salts in the electrolyte. The solar cell with electrolyte comprises (60% wt. TBAI/40% wt. LiI (+I2)) display elevated efficiency of 5.189% under 1000 W/m2 light intensity. While the solar cell with electrolyte comprises (60% wt. LiI/40% wt. TBAI (+I2)) display a lower efficiency of 3.189%. The conductivity raises with the

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The test considers from important methods and tools when we using the evaluation because it is a basic role in diagnosis & classification & motive & selection &guiding &prediction and the problem was formatted in some questions like ( what is physical variables that tall players needs n the game and effect on the game ? what is the tests that measures these variables also the defense rebound variable and is there a references standard specialized in that ?) , the aims of research represented by knowing to some physical abilities for tall players in basketball school and their tests and putting new tests to measure defense rebound to one player and tow tall players also limiting the standards degrees ( modified un following method ) to resul

The present work aims to study the efficiency of coagulation/ flocculation as 1st stage, natural gravity water filter or microfiltration (MF) as 2nd stage and nanofiltration (NF) technology as final stage for treatment of water of main outfall drain (MOD) for injection in Nasiriyah oil field. Effects of operating parameters such as coagulant dosage, speed and time of slow mixing step and settling time in the 1st stage were studied. Also feed turbidity and total suspended solids (TSS) in the 2