The genus of Chrysobothris Eschscholtz, 1829 is one of the most diverse and widespread genera of the family Buprestidae of some 700 described species distributed throughout the world. In Iraq, particularly in the Kurdistan region, about 4 species had been recorded so far, many of these species are sympatric, share larval host plants, and are difficult to reliably separate morphologically. The current study investigates species limits and relationships among the recognized species occurring within the Erbil Province; mitochondrial cytochrome C oxidase (COX I) molecular analysis confirmed the monophyly of two Chrysobothris species, Ch. affinis (Fabricius, 1794) and Ch. chrysostigma (Linnaeus, 1758). Implications of the resultant larval mor

The leaves and stems of the local Purslane plant ( Portulaca oleracea oleracea L. ) were used to preapare the extract of two types ( wet and dried extractions) the extracts were prepared by weighting of 60grams of the wet and the dried plant individually, then boiled in 500ml of distal water. Finally the volume was completed to1 liter, then we used these extracts to prepare of 8 types of the culture media contained basic, selective and enrichment media for growing a group of pathogenic bacteria. 8 types of bacteria were used for this purpose: Escherichia coli, Pseudomonas flouresence, Staphylococcus aureus , Staphylococcus epidermidis, Bacillus subtilis , Klebsiella pneumoniae , Proteus mirabilis and Proteus vulgaris. The stastica

Acute appendicitis is the most common surgical abdominal emergency. Its clinical diagnosis remains a challenge to surgeons, so different imaging options were introduced to improve diagnostic accuracy. Among these imaging modality choices, diagnostic medical sonography (DMS) is a simple, easily available, and cost effective clinical tool. The purpose of this study was to assess the accuracy of DMS, in the diagnosis of acute appendicitis compared to the histopathology report, as a gold standard. Between May 2015 and May 2016, 215 patients with suspected appendicitis were examined with DMS. The DMS findings were recorded as positive and negative for acute appendicitis and compared with the histopathological results, as a gold standard

The aim of this study was to isolate and identify the cyanobacterium Scytonema hofmanni Var. calcicolum from the domestic drinking tanks as a new record in Iraqi drinking water. Scytonema hofmanni var. calcicolum, a filamentous freshwater cyanobacterium (blue-green alga). This alga was isolated from the walls of the domestic plastic water tanks in Al- karkh/ Baghdad city on July 2014. The sampling was performed by collecting three samples from this tanks, the three examined samples microscopically revealed the dominance of this cyanobacterium as unialgal in the studied samples. The results showed this alga has the ability to tolerate high temperature up to 42 Cº and very low light intensity inside the tanks which up to 10 μE/m²/s.

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

Background: Although the new treatment methods developed in recent years are aiming to minimize the need for cooperation of the patients; however, the latter still important factor the treatment. The aim of the study was to evaluate the cooperation level of Class III maloc-clusion patients with orthodontic treatment. Materials and methods: This study followed a cross-sectional style; the targeted population was patients with Class III malocclusion who were treated with three different types of orthopaedic appliances. Four questionnaires were delivered to the patient, patient’s parents, and orthodontists. Statistical analyses of the study were performed with SPSS 20.0 software. Descriptive analyses were presented using fre-quency, percenta

ABSTRACT

            The aim of the research is to identify the impact of the areas of organizational change in strategic marketing planning in cement factories operating within the city of Al-Khums, and this effect was measured using a questionnaire consisting of 28 phrases, and it was relied on the descriptive approach that suits the nature of the subject of the research, while the research community consists of heads And members of the board of directors, authorized managers, unit managers and heads of departments in the factories under study, which numbered 55 respondents, during the month of September of the year 2021, and a sample of the compreh

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n