This study aimed to synthesize a novel amide prodrug of metformin with aspirin by amide bond. The structure was characterized by (FTIR, 1H-NMR, 13C-NMR and CHNO) ,Purification of the prepared compound was using column chromatography. Using of 40 rabbit having the same weight and devided into 4 groups (4x10) the first group (G1): (the control healthy group) was given drink water and didn’t give any material, second group(G2):( the control infected group) was given hydrogen peroxide concentration % 0.5 until infecting diabetes mellitus, third group(G3): was given hydrogen peroxide concentration as in (G2) and ( 250 mg/kg) of aspirin and (348.8 mg/kg) of metformin, fourth group(G4): was given hydrogen peroxide concentration as in (G2) and (596.3 mg/kg) of the proposed prodrug. After 3 hours, blood was taken from all groups, the serum was separated, and prepared to study it with biochemical and enzymatic study. Statistical data analysis revealed significant decrease in the levels of (lactate dehydrogenase, creatinkinase) , and significant decrease in the concentration of (Glucose) , and significant increase in the concentration of (total protein, albumin, globulin) affected by the prepared Compound [A] as compared with the control infected group. Statistical analysis revealed significant decrease in the levels of (Lactate dehydrogenase) and significant increase in the levels of (creatinkinase) , and significant increase in the concentration of (Glucose, albumin, total protein and globulin) affected by prepared compound [A] as compared with the control healthy group.
In this paper we investigate the use of two types of local search methods (LSM), the Simulated Annealing (SA) and Particle Swarm Optimization (PSO), to solve the problems ( ) and . The results of the two LSMs are compared with the Branch and Bound method and good heuristic methods. This work shows the good performance of SA and PSO compared with the exact and heuristic methods in terms of best solutions and CPU time.
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The integral breadth method has been utilized to analyse line
proIiles broadening and lattice strain of CaO at different temperatures
The effect of tcmperattre on crystallite size and strain has also been investigated . The crystall i tes are found to be highly anisotropic even at high temperatures
Pseudomonas aeruginosa is a common and major opportunistic human pathogen, its causes many and dangersinfectious diseases due to death in some timesex: cystic fibrosis , wounds inflammation , burns inflammation , urinary tract infection , other many infections otitis external , Endocarditis , nosocomial infection and also causes other blood infections (Bacteremia). thereforebecomes founding fast and exact identification of P. aeruginosafrom samples culture very important.However, identification of this species may be problematic due to the marked phenotypic variabilitydemonstrated by samples isolates and the presence of other closely related species. To facilitate species identification, we used 16S ribosomal DNA(rRNA) sequence data
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The groundwater represents the main source of water in the study area due to lack of surface water. The Dammam unconfined aquifer represents the main aquifer in the study area and Southern desert because of the regional extent, the quantity and quality of water. Many groundwater wells have been drilled in the study area to coverage the huge demand of water for agricultural purposes. The Geographic Information System (GIS) was used to estimate the volume of water which calculated (25.6964 × 109 m3) within the study area , automate calculation of the area of Al Salman basin using digital elevation models, derive the thickness maps of Al
Dammam unconfined aquifer from Key holes (KH) and Bore holes (
Unconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute
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The movement and broadening of foreign and European words into Persian is a topic within historical linguistics. Such changes are semantic, phonological
Since many of these European loanwords into Persian took a remarkable space within Persian dictionaries, and became an indispensible part of the language, a study of the original languages of these loanwords may identify the enormous effect of those languages upon Persian, being a receptor language, and may refer to the liveliness.
Among the important factors which helped the movement of various loanwords into Persian are:
- Geographical: this is seen via contact between Persian people and those neighboring people, specifically those speaking Ara
This paper argues the accuracy of behavior based detection systems, in which the Application Programming Interfaces (API) calls are analyzed and monitored. The work identifies the problems that affecting the accuracy of such detection models. The work was extracted (4744) API call through analyzing. The new approach provides an accurate discriminator and can reveal malicious API in PE malware up to 83.2%. Results of this work evaluated with Discriminant Analysis
In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .