In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the

Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For

Background: Helicobacter pylori are important gastrointestinal pathogen associated with gastritis, peptic ulcers, and an increased risk of gastric carcinoma. There are several popular methods for detection of H. pylori (invasive and non-invasive methods) each having its own advantages, disadvantages, and limitations, and by using PCR technique the ability to detect H. pylori in saliva samples offers a potential for an alternative test for detection of this microorganism. Materials and methods: The study sample consists of fifty participants of both genders, who undergo Oesophageo-gastrodudenoscopy at the Gastroenterology Department of Al-Kindy Teaching Hospital Baghdad/ Iraq, during five months period from January 2014 to May 2014. They we

Community pharmacists faced more complex challenges in meeting patients’ medication needs during the pandemic than previously reported in the literature. Objectives To explore the perception and abilities of community pharmacists in managing patients’ needs in terms of medication dispensing during the pandemic, and to examine its effect on improving the patients’ situations. Materials and Methods A cross-sectional study design, validated by 30 experts, was conducted using an electronic survey (Google Form) to assess the effect of the dispensing practice of Iraqi community pharmacists on the patient’s clinical outcomes during the pandemic. The survey was distributed on professional pharmacist’s social media platforms from December

Artificial Neural Network (ANN) model's application is widely increased for wastewater treatment plant (WWTP) variables prediction and forecasting which can enable the operators to take appropriate action and maintaining the norms. It is much easier modeling tool for dealing with complex nature WWTP modeling comparing with other traditional mathematical models. ANN technique significance has been considered at present study for the prediction of sequencing batch reactor (SBR) performance based on effluent's (BOD5/COD) ratio after collecting the required historical daily SBR data for two years operation (2015-2016) from Baghdad Mayoralty and Al-Rustamiya WWTP office, Iraq. The prediction was gotten by the application of a feed-forwa

Purpose To extract the lower anterior teeth, the oral surgeon needs to anesthetize the pulpal tissue of the accused tooth and the surrounding tissues. The lingual nerve innervates the lingual soft tissue to the lower teeth, this nerve usually anesthetized alongside the inferior alveolar nerve by a block technique. However, the lingual tissue of the lower anterior teeth usually anesthetized by either infiltration or periodontal ligament injection (PDL) techniques. This study was intended to compare between these two techniques. Methods Forty-eight teeth were extracted from 24 patients. Non-adjacent two lower anterior teeth in the same patient were selected. The lingual soft tissue in one of them was anesthetized by PDL injection technique wh

This work aimed PVA nanofibers in a range of concentrations were successfully manufactured via electrospinning. PVA NFs/Si was effectively prepared using the electrospinning process. The structural, morphological, optical and electrical properties of the prepared PVA were studied using XRD, FE-SEM, UV-Vis spectrophotometer and I-V characteristics, respectively. The amorphous structure of PVA nanofibers was observed. The optical energy gap from ultraviolet to visible was between (2.75 and 2.41) eV, making this compound highly sensitive to visible orange light at 610 nm, with a photosensitivity of 66%. The optical energy gap of PVA/Si heterojunction was utilized to modify this film from the UV to the visible spectrum. As show in the results,