The inhibitory effect of acetone, ethanol, and aqueous extracts of ten medicinal plants on β-lactamase from Staphylococcus sciuri and Klebsiella pneumoniae was investigated in vitro by starch-iodine agar plate method. The results revealed the success of starch-iodine method for the detection of the inhibition of β-lactamase activity by the various extracts of each individual plant. The acetone extracts of Catharanthus roseus, Eucalyptus camaldulensis, and Schinus terebinthifolius induced an inhibitory effect on β-lactamase from Staphylococcus sciuri. On the other hand, acetone extracts from only Eucalyptus camaldulensis, and Schinus

Several attempts have been made to modify the quasi-Newton condition in order to obtain rapid convergence with complete properties (symmetric and positive definite) of the inverse of  Hessian matrix (second derivative of the objective function). There are many unconstrained optimization methods that do not generate positive definiteness of the inverse of Hessian matrix. One of those methods is the symmetric rank 1( H-version) update (SR1 update), where this update satisfies the quasi-Newton condition and the symmetric property of inverse of Hessian matrix, but does not preserve the positive definite property of the inverse of Hessian matrix where the initial inverse of Hessian matrix is positive definiteness. The positive definite prope

This paper proposes a new structure of the hybrid 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. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

: In this study, a linear synchronous machine is compared with a linear transverse flux machine. Both machines have been designed and built with the intention of being used as the power take off in a free piston engine. As both topologies are cylindrical, it is not possible to construct either using just flat laminations and so alternative methods are described and demonstrated. Despite the difference in topology and specification, the machines are compared on a common base in terms of rated force and suitability for use as a generator. Experience gained during the manufacture of two prototypes is described.

The performance of a condenser in a domestic refrigerator system without wires and a condenser with a novel design consisted of number of loops as elliptical shape is investigated experimentally in this work. The experiment was conducted with a refrigerator designed to work with HFC134a, under no load and with loads of (1.5,3 and 12 liters of water). In particular, the effects of shape change of the condenser were very important in heat transfer enhancement and reduce of the frictional loss as a result of reducing the pressure drop in the condenser. The results shown that compressor work decreases with elliptical condenser about (8.6% to 11.3%), and then the power consumption decreases also. The performance of household refrigerator with

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

The research aimed: 1. Definition of family climate for the university students. 2. Definition of statistical significance of differences in family climate variable depending on the sex (males - females) and specialization (Scientific - humanity). 3. Definition of academic adjustment for university students. 4. Definition of correlation between climate and academic adjustment. The research sample formed of (300) male and female students by (150) male of scientific and humanitarian specialization and (150) female of scientific and humanitarian specialization randomly selected from the research community. To achieve the objectives of the research the researcher prepared a tool to measure family climate. And adopted the measure (Azzam 2010)