Background: The aim of this in vitro study was to evaluate and compare the microleakage between Vertise Flow T M composite material and other conventional (Filtek Z250, riva light cure and SDR) composite materials when restoring CII mesial box only cavity at gingival margin through die penetration test Materials and methods: Forty maxillary first premolars were prepared with class II box design only cavities. Samples were divided into four groups of ten teeth according to material used: group I (FiltekZ250 only). Group II (SDR+FiltekZ250). Group III (Vertise Flow +FiltekZ250). Group IV (Riva light cure+ FiltekZ250). After 24 hrs. immersion in 2% in methylene blue, samples were sectioned and micro leakage was estimated. Results: None of the

The primary objective of root canal therapy is adequate biomechanical preparation of root canal system followed by 3D obturation.in clinics we are encountered with several anatomical variations, which we need to manage efficiently. One of the major factors responsible for failure of root canal therapy is missed canals. Recent technological advances have given the clinician opportunity to identify anatomical variations and treat them to satisfaction.

Toxoplasma gondiiis an obligate intracellular protozoan parasite of the phylum Apicomplexa, and toxoplasmosis is an important disease of both humans and economically important animals. With a limited array of drugs available there is a need to identify new therapeutic compounds. Aureobasidin A (AbA) is an antifungal that targets the essential inositol phosphorylceramide (IPC, sphingolipid) synthase in pathogenic fungi. This natural cyclic depsipeptide also inhibitsToxoplasmaproliforation, with the protozoan IPC synthase orthologue proposed as the target. The data presented here show that neither AbA nor an analogue (Compound 20), target the protozoan IPC synthase orthologue or total parasite sphingol

Population density represents an important indicator for determining the growth of the size of urban areas. Population density has a direct impact on the quality of life, and its excessive rise may lead to the deterioration of basic service facilities. The problem of the research is that the increase in the total population densities of the residential neighborhood may reflect negatively on the nature of the services provided to the residents in these shops, and thus the failure to achieve sustainability in the residential locality. The research assumes that the increase in population densities negatively affects the achievement of sustainability in the residential neighborhood.

The present study aims to explore the effectiveness of a proposed study unit based on the funds of knowledge theory in developing the attitudes towards cultural identity and the proposed study unit. In order to achieve the goal of the study, the two researchers followed the quasi-experimental approach, where the study sample consisted of (28) female students of the fifth-grade at Al-Jeelah Basic Education School, Al-Dakhiliyah Governorate in the Sultanate of Oman. The data were collected by two scales: the first is a scale of attitudes towards cultural identity consisting of (26) items. The second was a scale of attitudes towards the proposed study unit, which consisted of (24) items. The results of the study revealed that the effect of

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

Abstract. Full-waveform airborne laser scanning data has shown its potential to enhance available segmentation and classification approaches through the additional information it can provide. However, this additional information is unable to directly provide a valid physical representation of surface features due to many variables affecting the backscattered energy during travel between the sensor and the target. Effectively, this delivers a mis-match between signals from overlapping flightlines. Therefore direct use of this information is not recommended without the adoption of a comprehensive radiometric calibration strategy that accounts for all these effects. This paper presents a practical and reliable radiometric calibration r

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it