In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.

Hypothyroidism is a frequent disorder in the general population, especially among women, is defined as adeficiency of thyroid activity that results from insufficient production or action of thyroid hormones leading to a totaldecrease of metabolic. Human leukocyte antigen is the most polymorphic genetic system in man. Genes of this regioninfluence susceptibility to certain diseases.Objectives: The purpose of the present study is to investigate the role of HLA-DRB1 genotyping in hypothyroidpatients with and without periodontitis. Sixty hypothyroid patients 30 of patients were with periodontitis and 30without periodontitis compare with 30 healthy subjects as control enrolled in this study. DNA was extracted fromblood samples, then HLA- genotyp

This work studied the electrical and thermal surface conductivity enhancement of polymethylmethacrylate (PMMA) clouded by double-walled carbon nanotubes (DWCNTs) and multi-walled carbon nanotube (MWCNTs) by using pulsed Nd:YAG laser. Variable input factors are considered as the laser energy (or the relevant power), pulse duration and pulse repetition rate. Results indicated that the DWCNTs increased the PMMA’s surface electrical conductivity from 10-15 S/m to 0.813×103 S/m while the MWCNTs raised it to 0.14×103 S/m. Hence, the DWCNTs achieved an increase of almost 6 times than that for the MWCNTs. Moreover, the former increased the thermal conductivity of the surface by 8 times and the later by 5 times.

Background: Contact between implant material and bones must be strong and fast creation, to fulfill these properties appropriate surface modifications must apply on used implants. In this contribution; double surface modifications are applied on Ti-6Al-4V alloy to accelerate osseointegration. Materials and methods: Anodic process is utilized to create titania nanotubes (TNTs) on the screws made from Ti-6Al-4V alloy. These implants were coated with nano ZrO2 particles. Second modification was annealing anodized screws at 8000C, and implanted in tibiae of nine adult New Zealand white rabbits. Results: Physical and histological consequences of two surface modifications on Ti-6Al-4V alloy screws were studied. Scanning electron microscope (SEM)

It is suitable to use precast steel-concrete composite beams to quickly assemble a bridge or a building, particularly in isolated regions where cast-in-situ concrete is not a practical option. If steel-concrete composite beams are designed to allow demountability, they can also be extremely useful in the aftermath of natural disasters, such as earthquakes or flooding, to replace damaged infrastructure. Furthermore, rapid replacement of slabs is extremely beneficial in case of severe deterioration due to long-term stressors such as fatigue or corrosion. The only way to rapidly assemble and disassemble a steel-concrete composite structure is to use demountable shear connectors to connect/disconnect the steel beams to/from the concrete slab. I

In this paper a stirred-bed performed of the copper catalyzed synthesis of ethylchlorosilanes from silicon and ethyl chloride was described. A Si-catalyst mixture prepared by reaction of CuCl and Si was employed. The compositions of products were mainly ethyltrichlorosilane, diethyldichlorosilane, and ethyldichlorosilane and mainly depended on the extent of Cu in the mixture and the reaction temperature. A promoting effect on the extent of adsorption was observed on the addition of certain additives. The kinetic data revealed the direct depended of the reaction rate on C2H5Cl pressure.

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered