This study was undertaken to prepare Nano zinc oxide (ZnO) by precipitation and microemulsion methods. Scanning electron microscopy (SEM), X-ray diffraction (XRD), FTIR spectrometry, atomic force microscopy (AFM), and Brunauer Emmett Teller (BET) surface area were the techniques employed for the preparation. The particle size of prepared nano ZnO was 69.15nm and 88.49nm for precipitation and microemulsion methods, respectively, which corresponded to the BET surface area 20.028 and 16.369m²/g respectively. The activity of prepared nano ZnO as a photocatalyst was estimated by the removal of ampicillin (Amp) under visible light. This study, therefore, examined the effect of pH in the range of 5-11, initial concen

The Electrocardiogram records the heart's electrical signals. It is a practice; a painless diagnostic procedure used to rapidly diagnose and monitor heart problems. The ECG is an easy, noninvasive method for diagnosing various common heart conditions. Due to its unique advantages that other humans do not share, in addition to the fact that the heart's electrical activity may be easily detected from the body's surface, security is another area of concern. On this basis, it has become apparent that there are essential steps of pre-processing to deal with data of an electrical nature, signals, and prepare them for use in Biometric systems. Since it depends on the structure and function of the heart, it can be utilized as a biometric attribute

Lifestyle Medicine is the application of evidence-based lifestyle approaches for the prevention, treatment, and even the reversal of lifestyle-related chronic diseases such as diabetes, hypertension, heart disease, obesity, polycystic ovarian diseases, dementia, arthritis, and cancers

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.

Background: Periodontal diseases (PD) are common chronic inflammatory diseases caused by pathogenic microorganisms colonizing the gingival area and inducing local and systemic elevations of pro-inflammatory cytokines resulting in tissue destruction by a destructive inflammatory process. Stress was considered as one of the important risk factors that cause many inflammatory diseases including PD. The purpose of this study wasto determines and compares clinical periodontal parameters (PLI, GI and BOP), stress level and salivary IL-1? level among dental students before, during and after mid-year exam, also to find the correlation among stress, IL-1? and clinical periodontal parameters. Materials and methods: The sample was consisted of 24 dent