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)

Atmospheric residue fluid catalytic cracking was selected as a probe reaction to test the catalytic performance of modified NaY zeolites and prepared NaY zeolites. Modified NaY zeolites have been synthesized by simple ion exchange methods. Three samples of modified zeolite Y have been obtained by replacing the sodium ions in the original sample with lanthanum and the weight percent added are 0.28, 0.53, and 1.02 respectively. The effects of addition of lanthanum to zeolite Y in different weight percent on the cracking catalysts were investigated using an experimental laboratory plant scale of fluidized bed reactor.

The experiments have been performed with weight hourly space velocity (WHSV) range of 6 to 24 h

This study was conducted to examine the discharge capacity of the reach of the Tigris River between Kut and Amarah Barrages of 250km in length. The examination includes simulation the current capacity of the reach by using HEC-RAS model. 247cross sections surveyed in 2012 were used in the simulation. The model was calibrated using observed discharges of 533, 800, 1025 and 3000m³/s discharged at Kut Barrage during 2013, 1995, 1995 and 1988, respectively, and its related water level at three gauge stations located along the reach. The result of calibration process indicated that the lowest Root Mean Square Error of 0.095 can be obtained when using Manning’s n coefficient of 0.026, 0.03 for th

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

Hydrated lime has been recognized as an effective additive used to improve asphalt concrete properties in pavement applications. However, further work is still needed to quantify the effect of hydrated lime on asphaltic concrete performance under varied weather, temperature, and environmental conditions and in the application of different pavement courses. A research project was conducted using hydrated lime to modify the asphalt concretes used for the applications of wearing (surface), leveling (binder), and base courses. A previous publication reported the experimental study on the resistance to Marshall stability and the volumetric properties, the resilient modulus, and permanent deformation at three different weather temperatures. This

Ionic liquids (ILs) and deep eutectic solvents (DESs) have been found to be highly effective as electrolytes in TiO2 NTAs-graphite cells when combined with additives that enhance conductivity by reducing the viscosity of these liquids. The presence of CaCl2.6H2O: Acetamide DES with DI water as an additive resulted in a cell voltage of 1.31V and an internal resistance of 19 ohm. This can be attributed to the concentration and quality of the ionic species. The cells exhibited an interesting response to the AlCl3-chloroacetamide IL with dichloromethane DCM as an additive, with a cell voltage of 1.81V and an internal resistance of 5.0 ohm. Once again, this is influenced by the quality and concentration of the ionic species. Furthermore,

            This paper is interested in certain  subclasses of univalent and bi-univalent functions concerning  to shell- like curves connected with k-Fibonacci numbers involving modified Sigmoid activation function θ(t)=2/(1+e^(-t) ) ,t ≥0 in unit disk |z|<1 . For estimating of the initial coefficients |c_2 | , |c_3 |, Fekete-Szego ̈ inequality and the  second Hankel determinant have been investigated for the functions in our classes. 

This paper describes a microcontroller-based function generator system. By the function generator sine wave, square wave, quasi-square wave, saw-tooth and triangular waveforms are generated over a wide frequency range according to user requirements. By utilizing processing capabilities of the microcontroller the hardware is minimized exceedingly. The output waveform shapes are digitally-controlled to achieve the required wave shape. The single chip microcomputer of waveform generation equipment offers the possibility of improvements in manufacture reliability, maintenance and servicing and increased control flexibility. The system is built and tested. The results of test were satisfactory and appreciated by test engineers at different ce

This work includes design, implementation and testing of a microcontroller – based spectrum analyzer system. Both hardware and software structures are built to verify the main functions that are required by such system. Their design utilizes the permissible and available tools to achieve the main functions of the system in such a way to be modularly permitting any adaptation for a specific changing in the application environment. The analysis technique, mainly, depends on the Fourier analysis based methods of spectral analysis with the necessary required preconditioning processes. The software required for waveform analysis has been prepared. The spectrum of the waveform has been displayed, and the instrument accuracy has been checked.

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an