In this research, Haar wavelets method has been utilized to approximate a numerical solution for Linear state space systems. The solution technique is used Haar wavelet functions and Haar wavelet operational matrix with the operation to transform the state space system into a system of linear algebraic equations which can be resolved by MATLAB over an interval from 0 to . The exactness of the state variables can be enhanced by increasing the Haar wavelet resolution. The method has been applied for different examples and the simulation results have been illustrated in graphics and compared with the exact solution.

Background: Since the invention of laser in 1960, lasers have been developed and approved in many fields. Lasers can now be regarded as practical tools with unique properties that have been utilized effectively in several applications in fields of medical and biological sciences.Objectives: The aim of the current study was to preparation of vaccines (live attenuated and killed) by irradiation of the bacteria by the low level diode laser.Methods: six bacterial isolates were isolated from human samples of diabetic foot infections, which used for preparation of vaccines. The experiment was conducted on fifteen adult male rabbits; they were divided into three groups with 5 rabbits each. Blood samples were collected from the marginal ear vein

Many conservative sphincter-preserving procedures had been described to be effective in
healing of anal fistula without excision or de roofing.
Objective: To verify the outcome of mere photocoagulation of the fistula tract on healing of low anal
fistula.
Materials and Methods: Using 810nm diode laser, the tracts of low anal fistulae in a cohorts of six male
patients (mean age of 32 yr) had been photocoagulated by retrograde application of laser light through an
orb tip optical fiber threaded in to the tract. Swabs for culture and sensitivity testing were obtained before
and after laser application. Patients were followed up regularly to announce fistula healing.
Results: Mean laser exposure time was 6.6 min., mean

The reliability of optical sources is strongly dependent on the degradation and device characteristics are critically dependent on temperature. The degradation behaviours and reliability test results for the laser diode device (Sony-DL3148-025) will be presented .These devices are usually highly reliable. The degradation behaviour was exhibited in several aging tests, and device lifetimes were then estimated. The temperature dependence of 0.63?m lasers was studied. An aging test with constant light power operation of 5mW was carried out at 10, 25, 50 and 70°C for 100hours. Lifetimes of the optical sources have greatly improved, and these optical sources can be applied to various types of transmission systems. Within this degradation range,

Nowadays, most of the on-chip plasmonic single-photon sources emit an unpolarized stream of single photons that demand a subsequent polarizer stage in a practical quantum cryptography system. In this paper, we numerically demonstrated the coupling of the light emitted from a quantum emitter (QE) at 700 nm wavelength to the propagation mode supported by an on-chip hybrid plasmonic waveguide (HPW) polarization rotator. Our results proved that the light emitted is linearly polarized at 0º, 45º/−45º, and 90º with propagation lengths of 5 μm, 3.3 μm, and 3.9 μm, respectively. Moreover, high power-conversion efficiency was obtained from an applied transverse magnetic (TM) mode (0º-polarization) to a transverse electric (TE) (90º-polari

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial