Enterococci are usually encountered and predominate in oral infections, especially those associated with dental root canal infections of necrotic pulp and periodontitis. This study aimed to detect and identify Enterococcus faecium isolated from infected root canals, using polymerase chain reaction ( PCR). Thirty samples were collected from patients with  necrotic pulp, infected root canals, and endodontic treatment failure, attending the Conservative Treatment Department, College of Dentistry, Mosul University, Dental Teaching Hospital. The samples were obtained by inserting sterile paper points into the root canals and transferred in brain heart infusion broth vials to be  inoculated in a selective M-Enterococcus Agar Base . T

The main objective of this paper is present a novel method to choice a certain wind turbine for a specific site by using normalized power and capacity factor curves. The site matching is based on identifying the optimum turbine rotation speed parameters from turbine performance index (TPI) curve, which is obtained from the higher values of normalized power and capacity factor curves. Wind Turbine Performance Index a new ranking parameter, is defined to optimally match turbines to wind site. The relations (plots) of normalized power, capacity factor, and turbine performance index versus normalized rated wind speed are drawn for a known value of Weibull shape parameter of a site, thus a superior method is used for Weibull parameters estima

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

The medicinal plants (Astragalus species) have been used traditionally as anti-inflammatory, antioxidant, and Anti-diabetics. The current research investigates the phytochemistry and some biological activity of methanol extract of different parts of Astragalus bruguieri Bioss., a wild medicinal plant grows on Safeen mountain, Erbil, Iraq. The methanol extracts of A. bruguieri were analyzed for total phenolic, flavonoid, and saponin contents. In-vitro antioxidant activity was analyzed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays. Furthermore, the plant extracts were examined for in-vitro enzyme inhibitory activity and in-v

<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In

A new macrocyclic multidentate Schiff-base ligand Na4L consisting of two submacrocyclic units (10,21-bis-iminomethyl-3,6,14,17- tricyclo[17.3.1.18,12]tetracosa-1(23),2,6,8,10,12(24),13,17,19,21,-decaene-23,24-disodium) and its tetranuclear metal complexes with Mn(II), Co(II), Ni(II), Cu(II), and Zn(II) are reported. Na4L was prepared via a template approach, which is based on the condensation reaction of sodium 2,4,6-triformyl phenolate with ethylenediamine in mole ratios of 2 : 3. The tetranuclear macrocyclic-based complexes were prepared from the reaction of the corresponding metal chloride with the ligand. The mode of bonding and overall geometry of the compounds were determined through physicochemical and spectroscopic methods. These st

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to