Background: Considering the antioxidant, anti-inflammatory, and antimicrobial properties of green tea, this study aimed to evaluate the histopathological effect of the sulcular irrigation of green tea extract in the treatment of experimental gingivitis in rabbit.

Materials and methods: For this experimental study, 45 male rabbits, separated in two groups, control non- irrigated group (5rabbits) and study group (40 rabbits), gingivitis induced by ligatures was packed subgingivally in the lower right central incisors of the experimental group for seven days. Then, the animals were randomly designated to two irrigated groups (20 rabbits

    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

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