Background: Corticotomy-assisted orthodontic treatment is done to induce a state of increased tissue turnover and transient osteopenia, which is followed by a faster rate of orthodontic tooth movement. It considered as an adjunct treatment option for orthodontic treatment of adults. The aim of this Study was to elucidate the effectiveness of a new surgical approach for acceleration of maxillary canine retraction in human with laser assisted flapless corticotomy and evaluate its effect on vitality of pulp and gingival sulcus depth. Materials and methods: the sample comprised of 15 Iraqi patients (9 females and 6 males; mean age 21.7), who were required extraction for their maxillary first premolars followed by retraction of the canines as pa

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

Globally, the COVID-19 pandemic’s development has presented significant societal and economic challenges. The carriers of COVID-19 transmission have also been identified as asymptomatic infected people. Yet, most epidemic models do not consider their impact when accounting for the disease’s indirect transmission. This study suggested and investigated a mathematical model replicating the spread of coronavirus disease among asymptomatic infected people. A study was conducted on every aspect of the system’s solution. The equilibrium points and the basic reproduction number were computed. The endemic equilibrium point and the disease-free equilibrium point had both undergone local stability analyses. A geometric technique was used

The primary function of commercial banks is the process of converting liquid liabilities such as deposits to illiquid assets, (also known as a loan), liquid assets, (aka cash and cash equivalent) in a balanced manner between liquid and illiquid assets, that guaranteed the preservation of the rights of depositors and the bank and not by converting liquid liabilities into liquid assets in a very large percentage. This comes from its role as depository and intermediary institutions between supply and demand, therefore, we find that the high indicators of bank liquidity and solvency may reflect a misleading picture of the status of commercial banks, to some extent in terms of the strength of their balance sheets and

The performance of job effectively requires narrowing the meaningful routine activities and attempting employing the job procedures in favor of public welfare through adding the green impact as well as removing them from the red tapes which reflect the firmness of procedures, to enable the job parties to make their job independently, and pushing them to gain priority in the competition layer. This is not attaining easily amidst the regulatory problems expressed by the complication of procedures, the thing which make identifying the problem of the study through the following question:

Should we make the complex of procedures and their firmness a way to adopt the idea of the green regulatory tapes supportin

The physical substance at high energy level with specific circumstances; tend to behave harsh and complicated, meanwhile, sustaining equilibrium or non-equilibrium thermodynamic of the system. Measurement of the temperature by ordinary techniques in these cases is not applicable at all. Likewise, there is a need to apply mathematical models in numerous critical applications to measure the temperature accurately at an atomic level of the matter. Those mathematical models follow statistical rules with different distribution approaches of quantities energy of the system. However, these approaches have functional effects at microscopic and macroscopic levels of that system. Therefore, this research study represents an innovative of a wi

The development of Web 2.0 has improved people's ability to share their opinions. These opinions serve as an important piece of knowledge for other reviewers. To figure out what the opinions is all about, an automatic system of analysis is needed. Aspect-based sentiment analysis is the most important research topic conducted to extract reviewers-opinions about certain attribute, for instance opinion-target (aspect). In aspect-based tasks, the identification of the implicit aspect such as aspects implicitly implied in a review, is the most challenging task to accomplish. However, this paper strives to identify the implicit aspects based on hierarchical algorithm incorporated with common-sense knowledge by means of dimensionality reduction.