ABSTRACT

Metal (II) complexes of Co, Ni, Cu and Zn with cefdinir C₁₄H₁₃N₅O₅S₂ derivative (L) were synthesized and identification by elemental analysis CHNS Uv-Vis, FTIR, TGA, metal analysis AA, magnetic susceptibility and conduct metric measurement. by analysis the ligand behaves as a bidentate. For the cobalt complex, Tetrahedral geometry shape was suggested, while other complexes that have nickel, copper and zinc ions were proposed as octahedral geometry shape. The experimental method was studied for prevention of corrosion carbon steel in 3.5% NaCl by using a novel Cefdinir derivations drugs. The results showed that metal complex was a strong corro

Information and communication technology has a significant influence on employee procedures. Businesses are investing in e-CRM technologies, yet it is difficult to assess the performance of their e-CRM platforms. The DeLone and McLean Information Systems Success framework can be modified to the current e-CRM assessment difficulties. The new framework's different aspects provide a concise framework for organizing the e-CRM key metrics identified in this study. The purpose of this study is to apply and verify that the Updated DeLone and McLean IS Model can be employed to explain e-CRM adoption among employees, along with the extended Updated DeLone and McLean Model with its five output factors, namely system quality, service quality,

This study was carried out to study effect of magnetic water ( M0 and M) and different concentrations of coconut extract in Fragaria x ananassa (Duch) C.V Festival. The results showed significant differences in the plants treated with magnetic water ( 0.12 Tesla) and different concentrations of coconut extract C1 (0%), C2 (2.5%), C3 (5%), C4 (7.5%) and C5 (10%) in vegetative parameters as in leaf area and chlorophyll in treatment M0C3 was (53.72 Dcm2, 50.00), respectively, highest leaf number and plant dry weight in MC4 (12.77,14.22 gm), respectively. Results recorded significant differences in fruit parameters such as weight in MC1 (18.97 gm). The maximum fruit number was in MC3 (110), the greatest fruit size was in MC4 (15.78 cm3) and the

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi