Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem

Background: Saliva plays an important role in oral health. Several salivary proteins are involved in the antimicrobial defence mechanism and are able to eliminate or inhibit bacterial growth in the oral cavity. Secretory IgA (SIgA) is one of the principal antibodies present in saliva, could help oral immunity by preventing microbial adherence, neutralizing enzymes and toxins. The aim of this study was to investigate the relationship between salivary Streptococcus Mutans (SM) count and S IgA in stimulated whole saliva in children with primary dentition compared to those with permanent teeth in relation to some oral hygiene parameters. Material and methods: Stimulated whole saliva was collected from 50 children (25 with primary dentation and

In this paper, a theoretical study of the energy spectra and the heat capacity of one electron quantum dot with Gaussian Confinement in an external magnetic field are presented. Using the exact diagonalization technique, the Hamiltonian of the Gaussian Quantum Dot (GQD) including the electron spin is solved. All the elements in the energy matrix are found in closed form. The eigenenergies of the electron were displayed as a function of magnetic field, Gaussian confinement potential depth and quantum dot size. Explanations to the behavior of the quantum dot heat capacity curve, as a function of external applied magnetic field and temperature, are presented.

Soil movement resulting due unsupported excavation nearby axially loaded piles imposes significant structural troubles on geotechnical engineers especially for piles that are not designed to account for loss of lateral confinement. In this study the field excavation works of 7.0 m deep open tunnel was continuously followed up by the authors. The work is related to the project of developing the Army canal in the east of Baghdad city in Iraq. A number of selected points around the field excavation are installed on the ground surface at different horizontal distance. The elevation and coordinates of points are recorded during 23 days with excavation progress period. The field excavation process was numerically simulated by using the finite

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

Although allowable amounts of glycol contamination in diesel engine oil, no research has been conducted on how these levels and varying loads affect engine performance. The research used a four-stroke diesel engine to investigate the effect of different glycol contamination levels (0, 120, and 220 ppm) under two engine loads (4.5 and 9 kW). Brake specific fuel consumption, brake thermal efficiency, friction power, and exhaust gas temperature were measured to determine the engine performance. The experiment used the factorial arrangement in a completely randomized design (CRD) with three replicates. Increasing the contamination levels from 0 to 120 and then to 220 ppm under constant engine load significantly increased brake specific fuel con

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals