Background: The aim of this study was for estimation and comparism of masticatory efficiency in patient wearing heat cured acrylic and flexible base partial denture, finding out the role of peanuts and carrots on the measurement of chewing efficiency, and to find out whether the types of P.D. (being single or two opposing each other) has any effect on the masticatory performance. Materials and methods: Twenty partially edentulous patients were selected. Five of these patients were selected having Kennedy class I with no modification against natural dentition, other 5patients having Cl.I against Cl.I . The other 5 patients having Cl.III against natural dentition and the last 5 patients were with Cl.III against Cl.III. several ways were used

A number of pulsed experiments have been carried out using a high-voltage circuit containing R,L, and C in certain arrangements. A spherical spark gap of steel electrodes was used as a high-current switch operated by a voltage of up to 8kV and triggered in both self-triggering and third-electrode triggering modes. Current measurements were carried out by using both current-viewing resistor and Rogowski coils designed for this purpose. Typical current waveforms have shown obvious dominating inductance effect of the circuit components in an underdamped oscillation. The behavior of the circuit impedance was studied by recording both pulsed current peaks and the charging voltages when currents of up to 2.5kA were recorded. The dur

إحدى أهم الطرق لتقصي توزيع المجرات عبر الزمن الكوني هي دالة اللمعان LF بدلالة كتلة القرص الباريوني ψS(Mb)، القدر . لقد درسنا تقديرًا لكثافة كتلة الباريون في عينة من المجرات الحلزونية القضيبية وغير القضيبية من الادبيات السابقة، والتي تتضمن فعليًا، لكل صنف من الاجرام السماوية ذات المحتوى الباريون المرئي، جزءًا لا يتجزأ من ناتج دالة الضيائية (LF) ونسبة الكتلة إلى الضوء. استخدمت تقنية الانحدار المتعدد لحزمة الب

Road-side dust samples were collected during August in 2020 from selected areas of, Al-Rusafa, Baghdad, Iraq. A sedimentological and mineralogical analysis of street dust was conducted. Three areas were selected to study street dusts which are Al-Baladitat, Al-Obaidi and Ziona. The laboratory analyses were done in the Department of Geology, College of Science, University of Baghdad. The heavy metal contents were determined in the roadside dust using XRF Method. It was found that the dust is of muddy texture, and is believed to be transmitted with the various storms blowing on Baghdad or by the wheels of Cars. The results of mineralogical investigation revealed that the dust samples composed of quartz, feldspar, calcite, gypsum and s

This research aims to understand the mineralogical and geochemical characteristics of the nickel laterite deposit in the East Sulawesi Ophiolite Belt in Wiwirano District, North Konawe, Southeast Sulawesi, Indonesia. The deposit is analyzed and described to determine the laterization process and supergene enrichment. The geochemical data was obtained from X-ray fluorescence analysis, and mineralogical data from petrography and X-ray diffraction analysis. The minerals in the limonite zone are dominated by goethite and hematite. Minerals found in the saprolite zone include quartz, orthopyroxene, and lizardite, whereas the bedrock is made up of olivine, orthopyroxene, serpentine, and chromite. Fe2O3, Al2O3, and Co contents are high in

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Six proposed simply supported high strength-steel fiber reinforced concrete (HS-SFRC) beams reinforced with FRP (fiber reinforced polymer) rebars were numerically tested by finite element method using ABAQUS software to investigate their behavior under the flexural failure. The beams were divided into two groups depending on their cross sectional shape. Group A consisted of four trapezoidal beams with dimensions of (height 200 mm, top width 250 mm, and bottom width 125 mm), while group B consisted of two rectangular beams with dimensions of (125 ×200) mm. All specimens have same total length of 1500 mm, and they were also considered to be made of same high strength concrete designed material with 1% volume fraction of steel fiber.