Synthesis of 2-mercaptobenzothiazole (A₁) is performed from the reaction of  o-aminothiophenol and carbon disulfide CS₂ in ethanol under basic condition. Compound (A₁)  is reacted with chloro acetyl chloride to give compound (A₂). Hydrazide acid compound (A₃) is obtained from the reaction of compound (A₂) with  hydrazine hydrate in ethanol under reflux in the presence of glacial acetic acid .The reaction of hydrazide acid compound (A₃) with ethyl acetoacetate gives pyrazole compound (A₄). The new hydrazone  compound (A₅) was prepared from the reaction of compound (A₃) with  benzaldehyde. Reaction of compound

The aim of this research is to employ starch as a stabilizing and reducing agent in the production of CdS nanoparticles with less environmental risk, easy scaling, stability, economical feasibility, and suitability for large-scale production. Nanoparticles of CdS have been successfully produced by employing starch as a reducing agent in a simple green synthesis technique and then doped with Sn in certain proportions (1%, 2%, 3%, 4%, and 5%).According to the XRD data, the samples were crystallized in a hexagonal pattern, because the average crystal size of pure CdS is 5.6nm and fluctuates in response to the changes in doping concentration 1, 2, 3, 4, 5 %wt Sn, to become   4.8, 3.9, 11.5, 13.1, 9.3 nm respectively. An increase in crystal

 Marketing information system (KMIS) is an essential factor of developing business’ performance and getting sustainable success. The main goal of the research is to measure effect of MIS on customer orientation and product innovation. Also, another goal is to analyze the mediation role of product innovation in relationship MIS and customer orientation. This study sought to analyze the marketing information system and measure its effect on the customer orientation and product innovation. The data of the study were collected using questionnaire. The data were analyzed using statistical tools and SPSS programming. The results of the study showed that the KMIS can positively and significantly effect product innovation. Also, t

Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin