Background: Pit and fissure sealant have been considered an outstanding adjunct to oral health care in the decrease of occlusal caries onset and low progression. The aims of this in vitro study were to evaluate the marginal microleakage of three different types of fissure sealants (SDI, Tg and tetric N-flow) by time interval, one day and 45 days, in the presence or absence of bonding agent among maxillary and mandibular teeth. Materials and methods: Seventy two sound human maxillary and mandibular first premolar teeth were collected which were free from obvious carious lesions. The teeth were randomly divided into two main equal groups, group (1) and group (2), each group consists of (36) teeth involving equal numbers of maxillary and mandibular teeth. The first group incubated for one day, the second incubated for (45) days. Each group divided into two subgroup; one of them treated with bonding agent while the other without. Then each subgroup was treated with three different materials which were; Tg sealant (without fluoride) group (A), SDI sealant (containing fluoride) group (B) and Tetric N-flow (flowable composite) group (C). Each one consist of six teeth involving three maxillary and three mandibular. Then dye penetration tested by using methylene blue dye, then the teeth cleaned and sectioned by sectioning device and tested under microscope. Results, the results had shown that, group (C+) in both incubation periods have no microleakage (score 0), but there was an opposite effect when using bonding agent with sealant materials not containing filler particles that showed a significant increase in the microleakage rate as shown in groups (A+ and B+). The opposite effect was seen also when used sealant materials containing filler particles but without bonding agent that seen in group (C) during both incubation periods that showed significant increasing in microleakage rate. While the effect of fluoride was very clear in decreasing significantly the microleakage rate after (45) days of incubation in both groups that treated with and without bonding agent (groups B and B+). Concerning the anatomical variation, there were no significant changes in most groups regarding the microleakage rate. Conclusions: Results had shown that the microleakage can be prevented by using of flowable composite containing nanofillers that treated with bonding agent after etching of enamel with 35% phosphoric acid gel.
Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c
... Show Morekinetic studies were carried out the uterine homogenate time course of the association of with LH in benign and malignant uterine
The study aimed to identify how to raise grateful children from an Islamic educational perspective. For that objective to be achieved, the researcher used both of deductive and descriptive approaches using the method of documentary research. The study's results show that children are the real wealth of the community and the foundation of cultural building; therefore, paying attention their raising is a responsibility that must be shared by everyone; gratitude is part parcel of the Islamic doctrine, which is one of the greatest virtues; the virtue of gratitude is the attitude of the believers which in turn strengthens the bonds and expands the network of positive social relationships; It is also considered a cultural significance
... Show MoreThis study was conducted to evaluate the bottled water quality for the six-producing companies in Baghdad city, where selected six brands which are the most marketed in the Iraqi market, especially in Baghdad, where taking the proper amount of bottled water in September 2015 and included the studied characteristics (EC , pH ,TDS, Turbidity, Ca+2, Mg+2, Cl-, No3-, So4-2, HCO3-, Na+ and K+) in addition to the total population of bacteria aerobic and coliform, and compare the results with the standard specifications of the Iraqi and the World Health Organization (WHO), as well as to compare the results of sampling specifications mentioned on the packaging by the producing companies. The results showed the presence of high significant differ
... Show MoreOptimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni
... Show MoreRecent growth in transport and wireless communication technologies has aided the evolution of Intelligent Transportation Systems (ITS). The ITS is based on different types of transportation modes like road, rail, ocean and aviation. Vehicular ad hoc network (VANET) is a technology that considers moving vehicles as nodes in a network to create a wireless communication network. VANET has emerged as a resourceful approach to enhance the road safety. Road safety has become a critical issue in recent years. Emergency incidents such as accidents, heavy traffic and road damages are the main causes of the inefficiency of the traffic flow. These occurrences do not only create the congestion on the road but also increase the fuel consumption and p
... Show MoreEfficient operations and output of outstanding quality distinguish superior manufacturing sectors. The manufacturing process production of bending sheet metal is a form of fabrication in the industry of manufacture in which the plate is bent using punches and dies to the angle of the work design. Product quality is influenced by plate material selection, which includes thickness, type, dimensions, and material. Because no prior research has concentrated on this methodology, this research aims to determine V-bending capacity limits utilizing the press bending method. The inquiry employed finite element analysis (FEA), along with Solidworks was the tool of choice to develop drawings of design and simulations. The ASTM E290
... Show MoreThis paper deals with the modeling of a preventive maintenance strategy applied to a single-unit system subject to random failures.
According to this policy, the system is subjected to imperfect periodic preventive maintenance restoring it to ‘as good as new’ with probability
p and leaving it at state ‘as bad as old’ with probability q. Imperfect repairs are performed following failures occurring between consecutive
preventive maintenance actions, i.e the times between failures follow a decreasing quasi-renewal process with parameter a. Considering the
average durations of the preventive and corrective maintenance actions a
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show More
