Background: The purpose of this study was to evaluate the effect of in vitro long-term simulation of oral conditions on the bond strength of PEEK CAD/CAM lingual retainers.

Material and methods: The sample consisted of 12 PEEK CAD/CAM retainers each composed of 2 centrally perforated 3x4mm pads joined by a connector. They were treated by 98% sulfuric acid for 1 minute and then conditioned with Single Bond Universal and bonded to the lingual surface of premolar teeth by 3M Transbond TM System. Half of the retainers were artificially aged using a 30-day water storage and 5000 thermocycling protocol before bond strength testing to compare with the non-aged specimens.

Results: The artificially aged retainers showed a marginally

The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat

Hartree-Fock calculations for even-even Tin isotopes using
Skyrme density dependent effective nucleon-nucleon interaction are
discussed systematically. Skyrme interaction and the general formula
for the mean energy of a spherical nucleus are described. The charge
and matter densities with their corresponding rms radii and the
nuclear skin for Sn isotopes are studied and compared with the
experimental data. The potential energy curves obtained with
inclusion of the pairing force between the like nucleons in Hartree-
Fock-Bogoliubov approach are also discussed.

This work deals with thermal cracking of three samples of extract lubricating oil produced as a by-product from furfural extraction process of lubricating oil base stock in AL-Dura refinery. The thermal cracking processes were carried out at a temperature range of 325-400 ºC and atmospheric pressure by batch laboratory reactor. The distillation of cracking liquid products was achieved by general ASTM distillation (ASTM D -86) for separation of gasoline fraction up to 220 ºC from light cycle oil fraction above 220 ºC. The comparison between the conversions at different operating conditions of thermal cracking processes indicates that a high conversion was obtained at 375°C, according to gasoline production. According to gasoline produ

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

Evaluating the behavior of a ring foundation resting on multi-layered soil is one of the important issues facing civil engineers. Many researchers have studied the behavior of ring foundation rests on multi-layered soil with vertical loads acting on the foundation. In real life ring foundation can be subjected to both vertical and horizontal loads at the same time due to wind or the presence of soil. In this research, the behavior of ring footing subjected to inclined load has been studied using PLAXIS software. Furthermore, the effect of multi-layered soil has been simulated in the model. The results showed that both vertical and horizontal stresses are mainly affected when the inclination angle of the load exceeded 45 degrees with a reduc

Existence of these soils, sometimes with high gypsum content, caused difficult problems to the buildings and strategic projects due to dissolution and leaching of gypsum by the action of waterflow through soil mass. In this research, a new technique is adopted to investigate the performance of replacement and geosynthetic reinforcement materials to improve the gypseous soil behavior through experimential set up manufactured loaclally specially for this work. A series of tests were carried out using steel container (600*600*500) mm. A square footing (100*100) mm was placed at the center of the top surface of the bed soil. The results showed that the most effective thickness for the dune sand layer with geotextile at the interface, within