Objective: Knee osteoarthritis is a common disabling chronic disease globally. Many pharmacological agents have been used efficiently in treatment of knee osteoarthritis. This study aims to evaluate metformin and serratiopeptidase together in treatment and stop of osteoarthritis progression by different mechanisms. Methods: Present study was a randomized clinical trial study conducted in Al-Kindi teaching hospital through the period from 1st January to 30th of May, 2017 on two groups of 80 osteoarthritis patients (group I; treated with metformin 850 mg oral tablets) and (group II; treated with metformin 850 mg oral tablets and serratiopeptidase 20 mg oral tablets). Parameters of two groups were compared with those of 40 normal healt

Femtosecond laser pulse propagation in monomode optical fibers is demonstrated and investigated numerically (by simulations) and experimentally in this paper. A passively mode locked Nd:glass laser giving a pulse duration of about 200 fsec at 1053 nm wavelength and 120 mW average optical power with 100 MHz repetition rate is used in the experimental work. Numerical simulations are done by solving the nonlinear Schrödinger equation with the aid of Matlab program. The results show that self phase modulation (SPM) leads to compression of the spectral width from 5 nm to 2.1 nm after propagation of different optical powers (34, 43, 86 and 120 mW) in fibers of different length (5, 15, 35 m). The varying optical powers produced a varying

Purpose: To validate a UV-visible spectrophotometric technique for evaluating niclosamide (NIC) concentration in different media across various values of pH. Methods: NIC was investigated using a UV-visible spectrophotometer in acidic buffer solution (ABS) of pH 1.2, deionized water (DW), and phosphate buffer solution (PBS), pH 7.4. The characterization of NIC was done with differential scanning calorimeter (DSC), powder X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The UV analysis was validated for accuracy, precision, linearity, and robustness. Results: The DSC spectra showed a single endothermic peak at 228.43 °C (corresponding to the melting point of NIC), while XRD and FTIR analysis confirmed the identit

In this work, a simulated study was carried out for designing a novel spiral rectangular patch of microstrip antenna that is used in ultra-wideband applications by using a high frequency structure simulator software (HFSS). A substrate with dielectric constant of 4.4 and height 2.10 mm (commercial substrate height available is about 0.8-1.575 mm) has been used for the design of the proposed antenna. The design basis for enhancing bandwidth in the frequency range 6.63 - 10.93 GHz is based on increasing the edge areas that positively affect the antenna's efficiency. This design makes the designed antenna cost less by reducing the area of the patch. It has been noticed that the bandwidth of the antenna under this study is increasing to 4.30

Simple, sensitive and accurate two methods were described for the determination of terazosin. The spectrophotometric method (A) is based on measuring the spectral absorption of the ion-pair complex formed between terazosin with eosin Y in the acetate buffer medium pH 3 at 545 nm. Method (B) is based on the quantitative quenching effect of terazosin on the native fluorescence of Eosin Y at the pH 3. The quenching of the fluorescence of Eosin Y was measured at 556 nm after excitation at 345 nm. The two methods obeyed Beer’s law over the concentration ranges of 0.1-8 and 0.05-7 µg/mL for method A and B respectively. Both methods succeeded in the determination of terazosin in its tablets

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an