In this work, diamond-like carbon (DLC) thin films were prepared from Cyclohexane. Thin films were deposited on quartz substrate by atmospheric pressure Argon plasma jet system. The plasma jet system was applying high voltage sinusoidal waves of frequency 28 kHz and potential difference of 7.5kV peak to peak across the electrodes. The effect of annealing at 400, 500 and 600 °C under vacuum for two hours on optical properties and structural properties of the DLC thin films were investigated. This effect was clarified by X-ray diffraction (XRD), FTIR, UV-Visible absorption, Scanning Electron Microscopy (SEM) and Raman Spectroscopy. The X-ray diffraction patterns for the annealing DLC thin films show two broad peaks at 2θ, 26.62° and 51.58

In the leaves of Olea europaea L. Olive trees an endophytic fungus was discovered. Cladosporium sp. was identified to be the fungus based on its morphological characteristics and nuclear ribosomal DNA ITS sequence analysis and was registered in NCBI as the Cladosporium genus has been registered under the number (0P939922.1) The species was not specified, and it was considered of unknown species after comparing it to global isolates. In comparison to olive leaf extract, Cladosporium sp. including total flavonoid, total phenolic, total terpenoid, and total saponins, Which were 121.9%, 198.1%, 89.13%, and 29.87 % respectively compared to its content in olive leaf extract, which was 61.54 %, 67.88 % , 17.1

A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

This work revealed the spherical aromaticity of some inorganic E4 cages and their protonated E4H+ ions (E=N, P, As, Sb, and Bi). For this purpose, we employed several evaluations like (0D-1D) nucleus independent chemical shift (NICS), multidimensional (2D-3D) off-nucleus isotropic shielding σiso(r), and natural bond orbital (NBO) analysis. The magnetic calculations involved gauge-including atomic orbitals (GIAO) with two density functionals B3LYP and WB97XD, and basis sets of Jorge-ATZP, 6-311+G(d,p), and Lanl2DZp. The Jorge-ATZP basis set showed the best consistency. Our findings disclosed non-classical aromatic characters in the above molecules, which decreased from N to Bi cages. Also, the results showed more aromaticity in E4 than E4H+

The quality of groundwater in the Al-Hawija area was assessed using a water quality index. Data of nine physico-chemical parameters of 28 groundwater wells were used to calculate the water quality index (WQI). A heterogeneous water quality was reported, where in close proximity to the Lesser Zab River (LZR), it has low WQI values and permissible for human consumptions due to the dilution processes by fresh water; whereas, it becomes deteriorated in areas located far away the river. The values of WQI ranges from 22 to 336, indicating a good to very poor groundwater quality.

<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