Background: Hyperfunction of the muscles of the upper lip is considered as the most common cause of excessive gingival display (EGD). The aim of this study was to demonstrate the effectiveness of botulinum toxin (BT) injection as a conservative treatment for EGD due to muscular hyperfunction and to compare the outcome of 2 injection methods. Material and methods: This study included 40 participants who were randomly assigned into 2 groups of 20 each, The first group received 2.5IU BT injection at 1 point per side (2-points group), while the second group received a total of 5 IU of BT at 2 points per side (4-points group). The outcome variables were the reduction in the central and lateral gingival display expressed as the difference between

In the recent years, some of the newly constructed asphalt concrete pavements in Baghdad as well as other cities across Iraq showed premature failures with consequential negative impact on both roadway safety and economy. Frequently, load associated mode of failure (rutting and fatigue) as well as, occasionally, moisture damage in some poorly drained sections are the main failure types found in those newly constructed road.

In this research, hydrated lime was introduced into asphalt concrete mixtures of wearing course in two methods. The first one was the addition of dry lime on dry aggregate and the second one was the addition of dry lime on saturated surface dry aggregate moisturized by 2.0 to 3.0 percent of wa

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

Urbanization led to significant changes in the properties of the land surface. That appends additional heat loads at the city, which threaten comfort and health of people. There is unclear understanding represent of the relationship between climate indicators and the features of the early virtual urban design. The research focused on simulation capability, and the affect in urban microclimate. It is assumed that the adoption of certain scenarios and strategies to mitigate the intensity of the UHI leads to the improvement of the local climate and reduce the impact of global warming. The aim is to show on the UHI methods simulation and the programs that supporting simulation and mitigate the effect UHI. UHI reviewed has been conducted the for

In this paper Volterra Runge-Kutta methods which include: method of order two and four will be applied to general nonlinear Volterra integral equations of the second kind. Moreover we study the convergent of the algorithms of Volterra Runge-Kutta methods. Finally, programs for each method are written in MATLAB language and a comparison between the two types has been made depending on the least square errors.

In this paper, the effective computational method (ECM) based on the standard monomial polynomial has been implemented to solve the nonlinear Jeffery-Hamel flow problem. Moreover, novel effective computational methods have been developed and suggested in this study by suitable base functions, namely Chebyshev, Bernstein, Legendre, and Hermite polynomials. The utilization of the base functions converts the nonlinear problem to a nonlinear algebraic system of equations, which is then resolved using the Mathematica^®12 program. The development of effective computational methods (D-ECM) has been applied to solve the nonlinear Jeffery-Hamel flow problem, then a comparison between the methods has been shown. Furthermore, the maximum

The phytoremediation technique has become very efficient for treating soil contaminated with heavy metals. In this study, a pot experiment was conducted where the Dodonaea plant (known as hops) was grown, and soil previously contaminated with metals (Zn, Ni, Cd) was added at concentrations 100, 50, 0 mg·kg-1 for Ni and Zn, and at concentrations of 0, 5, 10 mg·kg-1 for cadmium. Irrigation was done within the limits of the field capacity of the soil. Cadmium, nickel and zinc was estimated in the soil to find out the capacity of plants to the absorption of heavy and contaminated metals by using bioconcentration factors (BCFs), bioaccumulation coefficient (BAC) and translocation factor (TF). Additionally, BCF values of both Ni and Zn were l

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material