In this manuscript has investigated the synthesis of plasma-polymerized pyrrole (C₄H₅N) nano-particles prepared by the proposed atmospheric pressure nonequilibrium plasma jet through the parametric studies, particularly gas flow rate (0.5, 1 and 1.5 L/min). The plasma jet which used operates with alternating voltage 7.5kv and frequency 28kHz. The plasma-flow characteristics were investigated based on optical emission spectroscopy (OES). UV-Vis spectroscopy was used to characterize the  oxidization  state for polypyrrole. The major absorption appears around 464.1, 449.7 and 435.3  nm at the three flow rate of argon gas. The chemical composition and structural properties of the

Leaching process applied for the extraction of bio active compounds from dried roots of (Elecampane) Inula helenium. Ethanol, hexane and distillated water were used as solvents. Roots were soaked with ethanol (5% w/v) with various concentration of ethanol (30 to 98%) at one day to know effect concentration of the solvent with concentration of bio active compound in Inula helenium. The same procedure was done using hexane as solvent. Also distilled water was used as solvent for extraction 5%(w/v) where plant material was soaked in water at different temperatures (25, 40, 65, 80, and 90) C. In all solvents undertaken, the effect of time duration on active ingredient (Thymol, Isoalatolactone, Alatolactone, 10-isobutyryl-oxy 8-9-epoxy thymol is

In the current research, an eco-biosynthesis method for synthesizing silver nanoparticles (AgNPs) is reported using thymus vulgaris leaves (T. vulgaris) extracts. The optical and structural properties of the nanoparticles is determined using UV-visible, x-ray diffraction (XRD) and field emission scanning electron microscope (FESEM). In addition, the synthesis factors such as the temperature, the molar ratio of silver nitride and thymus vulgaris leaves extract have been investigated. The XRD pattern presented higher intensity for the five characteristic peaks of silver. FESEM images for same samples indicated that the particle size was distributed between 24-56 nm. In addition, it’s observed the formation of some aggregated Ag particles

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

              In this work, pure and doped Vanadium Pentoxide (V₂O₅) thin films with different concentration of TiO₂ (0, 0.1, 0.3, 0.5) wt  were obtained using Pulse laser deposition technique on amorphous glass substrate with thickness of (250)nm. The morphological, UV-Visible and Fourier Transform Infrared Spectroscopy (FT-IR) were studied. TiO₂ doping into V₂O₅ matrix revealed an interesting morphological change from an array of high density pure V₂O₅ nanorods (~140 nm) to granular structure in TiO₂-doped V₂O₅ thin film .Transform Infrared Spectro

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol