he genus Hirudo is an invertebrate animal that got major concerns to human. However, genetics of Hirudo has been unwell considered in Iraq. In order to gain a deeper understanding in the outline of the genetic of Hirudo that were used in alternative medicine clinics, nineteen specimens of Hirudo were obtained. Fourteen of them (H.verbana, n=10; H. orientalis, n=4) were obtained from some different clinics and scientific centres in Baghdad, Iraq between January and March 2022, these specimens were considered as non-local leeches. The other (native isolates) leeches (H. orientalis, n=5) were collected in 2014 from two localities in Erbil, northern Iraq. ITS-2, COI and 12S-rRNA of Hirudo spp were amplified using conventional polymerase chain r

The analytic solution for the unsteady flow of generalized Oldroyd- B fluid on oscillating rectangular duct is studied. In the absence of the frequency of oscillations, we obtain the problem for the flow of generalized Oldroyd- B fluid in a duct of rectangular cross- section moving parallel to its length. The problem is solved by applying the double finite Fourier sine and discrete Laplace transforms. The solutions for the generalized Maxwell fluids and the ordinary Maxwell fluid appear as limiting cases of the solutions obtained here. Finally, the effect of material parameters on the velocity profile spotlighted by means of the graphical illustrations

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

This study presents a practical method for solving fractional order delay variational problems. The fractional derivative is given in the Caputo sense. The suggested approach is based on the Laplace transform and the shifted Legendre polynomials by approximating the candidate function by the shifted Legendre series with unknown coefficients yet to be determined. The proposed method converts the fractional order delay variational problem into a set of (n ＋ 1) algebraic equations, where the solution to the resultant equation provides us the unknown coefficients of the terminated series that have been utilized to approximate the solution to the considered variational problem. Illustrative examples are given to show that the recommended appro

This study was design to investigate the dimensional stability of heat-activated acrylic resin with different methods of flask cooling (15 minutes rapid cooling, one hour bench cooling, four hours delayed deflasking, and 24 hours delayed deflasking) at different time intervals (immediately, two days, seven days, 30 days) after deflasking. Heat-activated acrylic resin was used to prepare acrylic samples. Then, measurement of the distances where achieved between the centers of selected marks in the acrylic samples. They were measured at different time intervals for different methods of flask cooling. The results showed that the group samples of the four hours and 24 hours of delayed deflasking was insignificantly different from the control an

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe