Hypertension is a cardiovascular problem with high rates of epidemiology and risks of morbidity and mortality in the global area. Nitric oxide (NO) is one of the reactive oxygen species (ROS) that produced from L-arginine by nitric oxide synthase (NOS) enzyme. NO involves in various vital processes in human health, one of which is the modulation of vasoconstriction and relaxation of the vascular system. We have aimed to investigate the link between NO and NOS with hypertension in women. The relationship between NO and NOS, as well as the usefulness of them as indicators of hypertension risks were subjects of study in this article. The results have revealed that hypertensive women had significant (P<0.05) lower levels of NO (15.07±3.41 IU/m

Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

SUMMARY. – Nanocrystalline thin fi lms of CdS are deposited on glass substrate by chemical bath deposited technique using polyvinyl alcohol (PVA) matrix solution. Crystallite size of the nanocrystalline films are determining from broading of X-ray diffraction lines and are found to vary from 0.33-0.52 nm, an increase of molarity the grain size decreases which turns increases the band gap. The band gap of nanocrystalline material is determined from the UV spectrograph. The absorption edge and absorption coefficient increases when the molarity increases and shifted towards the lower wavelength.

In this work, silicon nitride (Si₃N₄) thin films were deposited on metallic substrates (aluminium and titanium sheets) by the DC reactive sputtering technique using two different silicon targets (n-type and p-type Si wafers) as well as two Ar:N₂ gas mixing ratios (50:50 and 70:30). The electrical conductivity of the metallic (aluminium and titanium) substrates was measured before and after the deposition of silicon nitride thin films on both surfaces of the substrates. The results obtained from this work showed that the deposited films, in general, reduced the electrical conductivity of the substrates, and the thin films prepared from n-type silicon targets using a 50:50 mixing ratio and deposited on both

Water pollution is one of the global challenges that the society must address in the 21^st century aiming to improve the water quality, reduce human pollutants and ecosystem health impacts. In phytotoxicity test, the plant of Iresine herbstii was exposed to remove nickel from simulated wastewater using two different ratios (mass of plant to the mass of nickel) (,R_p/Ni) for 21 days with sub-surface batch system. During the exposure period, the removal of Ni concentrations (2, 5 and 10 mg/L) for two mass ratio (2,800 and 34,000) were (83.6%, 77.2%, 78.0%) and (86.8%, 97% and 95.6%), respectively. final result of the rate was found that the highest removal occurred, 97%, at a mass ratio of 34,000 and

The present study aims to remove nickel ions from solution of the simulated wastewater using (Laminaria saccharina) algae as a biosorbent material. Effects of experimental parameters such as temperature at (20 - 40) C⁰, pH at (3 - 7) at time (10 - 120) min on the removal efficiency were studied.
Box-Wilson method was adopted to obtain a relationship between the above three experimental parameters and removal percentage of the nickel ions. The experimental data were fitted to second order polynomial model, and the optimum conditions for the removal process of nickel ions were obtained.
The highest removal percentage of nickel ions obtained was 98.8 %, at best operating conditions (Temperature 35 C⁰, pH 5 and Time 10 min).