The current standard for treating pilonidal sinus (PNS) is surgical intervention with excision of the sinus. Recurrence of PNS can be controlled with good hygiene and regular shaving of the natal cleft, laser treatment is a useful adjunct to prevent recurrence. Carbon dioxide (CO2) laser is a gold standard of soft tissue surgical laser due to its wavelength (10600 nm) thin depth (0.03mm) and collateral thermal zone (150mic).It effectively seals blood vessels, lymphatic, and nerve endings, Moreover wound is rendered sterile by effect of laser. Aim of this study was to apply and assess the clinical usefulness of CO2 10600nm laser in pilonidal sinus excision and decrease chance of recurrence. Design: For 10 patients, between 18 and 39 year

In our article, three iterative methods are performed to solve the nonlinear differential equations that represent the straight and radial fins affected by thermal conductivity. The iterative methods are the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM) to get the approximate solutions. For comparison purposes, the numerical solutions were further achieved by using the fourth Runge-Kutta (RK4) method, Euler method and previous analytical methods that available in the literature. Moreover, the convergence of the proposed methods was discussed and proved. In addition, the maximum error remainder values are also evaluated which indicates that the propo

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

Porosity is important because it reflects the presence of oil reserves. Hence, the number of underground reserves and a direct influence on the essential petrophysical parameters, such as permeability and saturation, are related to connected pores. Also, the selection of perforation interval and recommended drilling additional infill wells. For the estimation two distinct methods are used to obtain the results: the first method is based on conventional equations that utilize porosity logs. In contrast, the second approach relies on statistical methods based on making matrices dependent on rock and fluid composition and solving the equations (matrices) instantaneously. In which records have entered as equations, and the matrix is sol

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

This study aimed to compare the safety and efficacy of laser lithotripsy and pneumatic lithotripsy, the two most commonly used transurethral lithotripsy methods for treating bladder stones in children in Iraq. Between January 2013 and December 2016, 64 children with bladder stones were included in this prospective randomized study, after ethical committee approval and written consent from the children’s parents or caregivers were obtained. Patients were assigned randomly by computer software to two groups treated with either pneumatic cystolithotripsy or laser lithotripsy. A 9 Fr. semirigid ureteroscope was used to pass the lithotripter through and fragment the stone. A catheter of 8–12 Fr. was then introduced and kept in place

The objective of this study was to compare the sensitivity and specificity of rK39,
ELISA and IFA tests for the diagnosis of visceral leishmaniasis using blood
samples. Samples were collected from 146 suspected patients and 30 healthy
individual as control. The results showed 52 (35.62%), 58 (39.73%) and 71
(48.64%) positive samples by rK39, ELISA and IFA , respectively. IFA test showed
a higher sensitivity (48.63%) than ELISA and rk39 dip stick (39.72%) and (35.61%)
respectively. The highest sensitivity of agreement (K: 0.912) was found between
rK39 dipstick and ELISA. Therefore, we suggest the application of rK39 dipstick
and ELISA methods in endemic areas of visceral leishmaniasis for early and
accurate diag

Linear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust