A small number of researches were done in the design and synthesis of enkephalin analogues that are able to resist degradation effect of proteolytic enzymes with good bioavailability and half-lives.Through studying structure activity relationships we tried to incorporate phthalyl group, tryptophan and lysine amino acids in different positions in the basic backbone structure of the naturally occurring opioid Leu⁵- and Met⁵- enkephalin, in the hope that such insertion of these amino acids could induce interesting addition in the biological activity of these analogues with enhancement of their bioavailability, in addition to decrease side effects as addiction liability.

These synthesized peptides are:

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this paper some chalcones (C1-C8) are prepared based on the reaction of one mole of substituted acetophenone with one mole of substituted benzaldehydes in the presence of (40%) sodium hydroxide as a base. Pyrazolines (P1–P8) are prepared from the reaction of chalcones (C1-C8) with hydrazine hydrate. Isoxazoline (I1-I8) is prepared from the reaction of chalcones (C1-C8) with hydroxyl amine hydrochloride in the presence of (10%) sodium hydroxide as a base. These compounds are characterized by using various physical and spectral methods. The compounds are screened for their in vitro antibacterial activity using gram-positive bacteria and gram-negative bacteria. Several derivatives of pyrazolines and isoxazolines are produced well to moder

Heterocyclic polymers / silica nanocomposite one of important materials because of excellent properties such as thermal , electrical , and mechanical properties , so that hybrid nanomaterial are widely used in many fields, in this paper nanocomposite had prepared by modification of silica nanoparticals by using acrylic acid and functionalized the surface of nanoparticles, and using free Radical polymerization by AIBN as initiators and anhydrous toluene as solvent to polymerize functionalize silica nanoparticles with heterocyclic monomers to prepare heterocylic polymers / silica nanocomposite and study electrical conductivity , The nanocomposite which had prepared characterized by many analysis technique to study thermal properties such

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

Two ligand ortho-amino phenyl thio benzyl (L1) and 1,3 bis (ortho - amino phenyl thio ) acetone (L2) and their complexes have been prepared and characterized . The L1 ligand is lossing phenyl group on complexcation and forming 1,2 bis (ortho - amino phenyl thio ) ethane L3 and this tetrahedrally coordinated to the metal ion ( M+2 = Ni , Cu , Cd ) and octahedrally coordinated with mercury and cobalt ions , while the ligand L2 is behave as tridentate ligand forming octahedrally around chrome metal ion . Structural , diagnosis were established by i.r , Uv- visible , conductivity elemental analysis and (mass spectra , H nmr spectra for( L1 , L2 ) .

The preparation of a new Azo compounds of highly conjugated dimeric and polymeric liquid crystal to achieve the crystalline characteristics Which have structures assigned based on elemental analysis, IR 1HNMR and CHNS-O while mesogenic properties have been set for DSC and hot-stage polarizing optical microscopy. The compounds show enantiotropicnematic phase being displayed. The compounds show photoluminescence properties in the organic solution at room temperature, with the fluorescence band centered around 400 nm.

The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita