The creation and characterization of laser-generated plasma are affected by laser irradiance, representing significant phenomena in many applications.  The present work studied the spectroscopy diagnostic of laser irradiance effect on Zn plasma features created in the air by a Q-switched Nd: YAG laser at the fundamental wavelength (1064nm).  The major plasma parameters (electron temperature and electron density) have been measured using the Boltzmann plot and the Stark broadening methods.  The value of electrons temperature ranged from 6138–6067 K, and the electron density in the range of 1.4×10¹⁸ to 2×10¹⁸ cm^-3, for laser irradiance range from 2.1 to 4.8×10⁸ (W/cm²

In this paper, Al and Cu Plasmas that produced by pulsed Nd:YAG laser with fundamental wave length with a pulse duration of 6 nS focused onto Al and Cu targets in atmospheric air are investigated spectroscopically. The influence of pulse laser energy on the some Al and Cu plasmas characteristics was diagnosed by using optical emission spectroscopy for the wavelength range 320-740 nm. The results observed that the increase of pulse laser energy causes to increase all plasma characteristics of both plasmas under study and shown increasing of the emission line intensity. The appearance of the atomic and ionic emission lines of an element in the emission spectrum depends on the ionization energy of target atoms. The plasma characteristics ar

 Researchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The

A comparative study was done on the adsorption of methyl orange dye (MO) using non-activated and activated corn leaves with hydrochloric acid as an adsorbent material. Scanning electron microscopy (SEM) and Fourier Transform Infrared spectroscopy (FTIR) were utilized to specify the properties of adsorbent material. The effect of several variables (pH, initial dye concentration, temperature, amount of adsorbent and contact time) on the removal efficiency was studied and the results indicated that the adsorption efficiency increases with the increase in the concentration of dye, adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature for both the treated and untreated corn leav

Water pollution as a result of contamination with dye-contaminating effluents is a severe issue for water reservoirs, which instigated the study of biodegradation of Reactive Red 195 and Reactive Blue dyes by E. coli and Bacillus sp. The effects of occupation time, solution pH, initial dyes concentrations, biomass loading, and temperature were investigated via batch-system experiments by using the Design of Experiment (DOE) for 2 levels and 5 factors response surface methodology (RSM). The operational conditions used for these factors were optimized using quadratic techniques by reducing the number of experiments. The results revealed that the two types of bacteria had a powerful effect on biodegradable dyes. The regression analysis reveale

In this work,  an explicit formula for a class of Bi-Bazilevic univalent functions involving differential operator is given, as well as the determination of upper bounds for the general Taylor-Maclaurin coefficient of a functions belong to this class, are established Faber polynomials are used as a coordinated system to study the geometry of the manifold of coefficients for these functions. Also determining bounds for the first two coefficients of such functions.

         In certain cases, our initial estimates improve some of the coefficient bounds and link them to earlier thoughtful results that are published earlier.

In the current work, Punica granatum L. peel, Artemisia herba-alba Asso., Matricaria chamomilla L., and Camellia sinensis extracts were used to prepare manganese dioxide (MnO₂) nanoparticles utilizing a green method. Energy-dispersive X-ray (EDX) analysis, Fourier Transform Infrared Spectroscopy (FTIR) analysis, and Filed emission-scanning electron microscopy (FE-SEM) analysis were used to evaluate the produced MnO₂ NPs. FE-SEM pictures demonstrated how agglomerated nanoparticles formed. According to FE-SEM calculations, the particle size ranged from 18.7-91.5 nm. FTIR spectra show that pure Mn-O is formed, while EDX results show that Mn and O are present. The ability to suppress biofilm growth in the produced MnO

An experimental study was conducted with low cost natural waste adsorbent materials, barley husks and eggshells, for the removal of Levofloxacine (LEVX) antibacterial from synthetic waste water. Batch sorption tests were conducted to study their isothermal adsorption capacity and compared with conventional activated carbon which were, activated carbon > barley husks > eggshells with removal efficiencies 74, 71 and 42 % with adsorbents doses of 5, 5 and 50 g/L of activated carbon, barley husks, and eggshells respectively. The equilibrium sorption isotherms had been analyzed by Langmuir, Freundlich, and Sips models, and their parameters were evaluated. The experimental data were correlated well with the Langmuir model which gives the

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti