A novel series of mixed-ligand complexes of the type, [ML 1 (L 2 ) 3 ]Cl x [M = Cr(III), Fe(III), Co(II),Ni(II), Cu(II), Cd(II) and Hg(II), n = 2, 3], was synthesized using Schiffbase (HL 1 ) as main ligand, nicotinamide (L 2 ) as secondary ligand, and the corresponding metal ions in 1:3:1 molar ratio. The main ligand, HL 1 was prepared by the interaction of ampicillin drug and 4-chlorobenzophenone. The synthesized mixed ligand complexes were characterized by elemental analysis, UV-Vis, FT-IR, 1 H-NMR, 13 C-NMR and TG/DTG studies. In the mixed-ligand complexes, the Schiffbase ligand, HL 1 showed coordination to the central metal ion in tridentate manner via azomethine nitrogen, β-lactam ring oxygen and deprotonated carboxylic oxy- gen atom

Background: Type 2 diabetes mellitus is a condition characterized by an elevation of oxidative stress, which has been implicated in diabetic progression and its vascular complications. Aim: Assessing the impact of gliclazide modified release (MR) versus glimepiride on oxidative stress markers, glycemic indices, lipid profile, and estimated glomerular filtration rate in uncontrolled type 2 diabetic patients on metformin monotherapy. Methods: This was an observational comparative study conducted in Thi-Qar specialized diabetic, endocrine, and metabolism center. Sixty-six patients were randomized into two groups based on the addition of the sulfonylureas (SUs). Group 1 (33 patients) was on gliclazide MR, whereas Group 2 (33 patients)

The aim of this study is to evaluate the anti fungal activity of a combination of essential oils against water molds. HPLC analysis was done to evaluate the quantity and quality of the active compounds in this combination which extracted from three herbs( Peppermint Menthapiperita ,Thyme Thymusvulgaris, Common sage Salvia officinalis L.) and the active compounds are Camphor,Menthol,,Thujone and Thymol with different concentrations. In this study (MIC) , (MFC) were measured and (LD50) determined after 48,96 h from fingerlings treatment of common carp in aquariums .The results of (MIC) were 0.025µl/ml for Aphanomyces sp. and 0.015µl/ml for both Achlya sp. and Fusariumsolani which showed significant differences(p<0.05) from Malachite gre

Abstract

Lack of safe available non-resistant treatment for visceral leishmaniasis (Kala-azar) keeps limiting the complete cure of this disease ,drugs that have  toxic side effects or lack of effectiveness  have led to disease relapse ,all these factors have lightened  the way to the search for imperative drugs from natural resources that have been shown to have antileishmanial activity through literature survey

. In the present study, the comparative in vitro anti-leishmania activity of various fractions of Osteospermum ecklonis aerial parts fractions have been evaluated. Extracts were prepared through maceration and Soxhlet apparatus using 85% meth

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

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

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

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