Mercury-lead-antimony based superconductors with the formula Hg0.5 Pb0.5xSbxBa2Ca2Cu3O8+δ (x=0, 0.10 and 0.15) have been prepared by useing three step solid state reaction processes. Electrical resistivity, using four probe technique, is used to find the transition temperature Tc. It is found from that sample Hg0.5 Pb0.5Ba2Ca2Cu3O8.437 is semiconductor , sample Hg0.5 Pb0.4Sb0.1Ba2Ca2Cu3O8.353 is normal state with metallic behaviors, while sample Hg0.5 Pb0.35Sb0.15Ba2Ca2Cu3O8.233 is superconducting state with critical transition temperature (Tc) is 126K. X-ray diffraction (XRD) analysis showed a tetragonal structure with decrease in the c-axis lattice constant for the samples doped with Sb as compared with these which have no Sb

Schiff bases, named after Hugo Schiff, are aldehyde- or ketone-like compounds in which the carbonyl group is replaced by imine or azomethine group. They are widely used for industrial purposes and also have a broad range of applications as antioxidants. An overview of antioxidant applications of Schiff bases and their complexes is discussed in this review. A brief history of the synthesis and reactivity of Schiff bases and their complexes is presented. Factors of antioxidants are illustrated and discussed. Copyright © 2016 John Wiley & Sons, Ltd.

In a hybrid cooling solar thermal systems , a solar collector is used to convert solar energy into heat energy in order to super heat the refrigerant leaving the compressor, and this process helps in the transformation of refrigerant state from gaseous state to the liquid state in upper two-thirds of the condenser instead of the lower two-thirds such as in the traditional air-conditioning systems and this will reduce the energy needed to run the process of cooling .In this research two systems with a capacity of 2 tons each were used, a hybrid air-conditioning system with an evacuated tubes solar collector and a traditional air-conditioning system . The refrigerant of each type was R22.The comparison was in the amou

This research investigated the effect of adding two groups of reinforcement materials, including bioactive materials Hydroxyapatite (HA) and halloysite nanoclay and bioinert materials Alumina (AL2O3) and Zirconia (ZrO2), each of them with various weight ratios (1,2,3,4 &5)% to the polymer matrix PMMA. The best ratios were selected, and then a hybrid was preparing Composite red from the best ratios from each group. Thermal properties, including thermal conductivity and Thermomechanical Analysis (TMA) technology, have been studied. The results showed that adding 3% Hydroxyapatite (HA) and 5% halloysite nanoclay to the polymethacrylate (PMMA) mer leads to an increase in thermal conductivity. It was also found from the Thermomechanical Analysis

    Semantic segmentation is effective in numerous object classification tasks such as autonomous vehicles and scene understanding. With the advent in the deep learning domain, lots of efforts are seen in applying deep learning algorithms for semantic segmentation. Most of the algorithms gain the required accuracy while compromising on their storage and computational requirements. The work showcases the implementation of Convolutional Neural Network (CNN) using Discrete Cosine Transform (DCT), where DCT exhibit exceptional energy compaction properties. The proposed Adaptive Weight Wiener Filter (AWWF) rearranges the DCT coefficients by truncating the high frequency coefficients. AWWF-DCT model reinstate the convolutional l

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

The majority of systems dealing with natural language processing (NLP) and artificial intelligence (AI) can assist in making automated and automatically-supported decisions. However, these systems may face challenges and difficulties or find it confusing to identify the required information (characterization) for eliciting a decision by extracting or summarizing relevant information from large text documents or colossal content.   When obtaining these documents online, for instance from social networking or social media, these sites undergo a remarkable increase in the textual content. The main objective of the present study is to conduct a survey and show the latest developments about the implementation of text-mining techniqu

This paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.