Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction o

Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction of (4% for AL

Films of pure Poly (methyl methacrylate) (PMMA) doped by potassium iodide (KI) salt with percentages (1%) at different thickness prepared by casting method at room temperature. In order to study the effect of increasing thickness on optical properties, transmission and absorption spectra have been record for five different thicknesses(80,140,210,250,320)µm. The study has been extended to include the changes in the band gap energies, refractive index, extinction coefficient and absorption coefficient with thickness.

   Alterations of trace element concentrations adversely affect biological processes and could promote carcinogenesis. Trace element deficiency or excess is implicated in the development or progression of some cancers like colorectal cancer. The aim of the present study was to compare the serum copper (Cu) and zinc (Zn) concentrations in patients with colorectal cancer from Iraqi male patient with those of healthy subjects. During the period of March 2015 until august 2015, a total of 25 patients with metastatic colon cancer and 20 healthy volunteers were enrolled from the Al-Kadhimia Teaching Hospital after the diagnosis using a histopathological examination for the malignant tumor; their age was between (38-60) years. Higher

Alterations of trace element concentrations adversely affect biological processes and could promote carcinogenesis. Trace element deficiency or excess is implicated in the development or progression of some cancers like colorectal cancer. The aim of the present study was to compare the serum copper (Cu) and zinc (Zn) concentrations in patients with colorectal cancer from Iraqi male patient with those of healthy subjects. During the period of March 2015 until august 2015, a total of 25 patients with metastatic colon cancer and 20 healthy volunteers were enrolled from the Al-Kadhimia Teaching Hospital after the diagnosis using a histopathological examination for the malignant tumor; their age was between (38-60) years. Higher levels o

Grabisch and Labreuche have recently proposed a generalization of capacities, called the bi-capacities. Recently, a new approach for studying bi-capacities through introducing a notion of ternary-element sets proposed by the author. In this paper, we propose many results such as bipolar Mobius transform, importance index, and interaction index of bi-capacities based on our approach.

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to