Background: The isthmus is a difficult area in the root canal complex to manage. The research aimed to evaluate the efficiency of three different obturation techniques (lateral condensation, EandQ (thermoplasticized gutta percha system) and Soft Core (thermoplasticized core carrier gutta percha system)) to obturate the isthmus area of roots prepared by two different instrumentation techniques (rotary ProTaper universal and ProTaper Next systems). Material and method: Sixty freshly extracted teeth were randomly divided into two main groups (A and B) of 30 teeth each. Group A was prepared by rotary ProTaper Universal whereas group B was prepared by ProTaper Next system. Each main group was then randomly subdivided into three subgroups of 10 teeth each, to be obturated with the three obturation techniques. All specimens were then placed in cold cure acrylic mold just from the side of the crown leaving the root unmolded to facilitate the sectioning process, then three sections were obtained from each specimen by using microtome at 2, 6 and 10 mm from the apex. Each section was viewed under stereomicroscope(40X) and imaged with digital camera(4X). Each image was managed with image J program to calculate the surface area of the whole isthmus and that of the gutta percha and/or sealer extended into the isthmus so the collected data represented the percentage of extension degree of gutta percha and /or sealer into the isthmus(EDGS). Results: The highest mean value of (EDGS) was evident with Soft Core technique in the apical area and was significantly higher than that of the EandQ and lateral condensation techniques. Conclusion: Under the conditions of this study, Soft Core system showed a higher efficiency in obturating the isthmus area than the other obturation techniques.
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Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide
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Multi-spectral satellite images of the Landsat satellite by the tow sensitive Thematic Mapper (TM) and Thematic Mapper Enhancement (ETM+), which covered the study area located south east of Iraq. In this research; used the sixth thermal spectral band (Thermal Band) for study the water cover in the AlRazzaza Lake located within the province of Karbala. We intended to study the cover a case of the study area, used satellite images showing the status of region during the period from 1990 to 2001 and 2007. From this study we conclude that cover the water of the study area change in sequence case to decrease during these years.
Multi-spectral satellite images of the Landsat satellite by the tow sensitive Thematic Mapper (TM) and Thematic Mapper Enhancement (ETM+), which covered the study area located south east of Iraq. In this research; used the sixth thermal spectral band (Thermal Band) for study the water cover in the Al-Razzaza Lake located within the province of Karbala. We intended to study the cover a case of the study area, used satellite images showing the status of region during the period from 1990 to 2001 and 2007. From this study we conclude that cover the water of the study area change in sequence case to decrease during these years.
Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou
... Show MoreBackground: The aim of this study was to measure the radiopacity (RO) of modified microhybrid composite resins by adding 2 types of nanofillers (Zinc Oxide and Calcium Carbonate) in two concentrations 3% and 5% and comparing them to unmodified microhybrid composite resins and to nanofilled composite resin. Materials and Methods: Two types of composite resin were used (Microhybrid composite MH Quadrent anterior shine and Nanofilled composite resin Filtek Z350 XT), for each tested group five disk-shaped specimens (1-mm-thick and 15 mm diameter) were fabricated. The material samples were radiographed together with the aluminum step wedge. The density of the specimens was determined with a transmission densitometer and was expressed in term of
... Show MoreAlthough the number of implants has increased gradually and consistently over the years to around one million per year globally, there is still far more potential for advancement in the field of dental implantology which is typically growing quickly. This study investigates the effect of nanofiller reinforcement high-performance polymer matrix to enhance mechanical and physical characteristics. Calcium silicate (CS)/Polyetherketoneketone (PEKK) biomedical composite (G0 as a control group) is reinforced with different weight percentages (G1-G4) of tellurium dioxide nanoparticles (TeO2NPs) ( n = 5). This research uses ethanol as a binder for mixing various weight percentages (wt%) of TeO2NPs w
... Show MoreThe recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach
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