Background: Thermocycling simulates the temperature dynamics in the oral environment. This in vitro study done to measure and compare the effect of thermocycling on the shear bond strength of stainless steel and sapphire brackets bonded to human enamel teeth using light cured orthodontic adhesive and debonded at various time, and to measure adhesive remnant index after debonding. Materials and Methods: one-hundred-twenty extracted upper first premolars for orthodontic reason were used in this study; depending on weather thermocycled or not, the sample was divided into two main groups, then within each group 30 teeth were used for stainless-steel brackets (Bionic®) and for sapphire brackets (Pure®). Both groups were subdivided into three groups (n = 10) according to the debond times: I: debond after 24 hour, II: debond after 7 days and III: debond after 30 days. Within 24 hr, half of the sample was thermocycled manually for 500 complete cycles between 5/55°C and the remaining sample was stored in distilled water at room temperature and water was changed daily until debond time for each group was performed. The adhesive remnant index was tested under 20X magnification lens using stereomicroscope. Results and Conclusions: Both bracket types demonstrated high shear bond strength values before thermocycling (P?0.05), whereas after 500 thermocycles, there were significant changes in shear bond strength resulted in marked reduction in the stainless steel brackets than in the sapphire brackets (P?0.05). Shear bond strength values increased with time for both stainless steel and sapphire brackets with and without thermocycling (P?0.05). The tendency of bond failure was increased at the bracket/adhesive interface rather than enamel/bracket interface in the stainless steel brackets whereas at the enamel/bracket interface rather than bracket/adhesive interface in the sapphire brackets.
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The current study presents the simulative study and evaluation of MANET mobility models over UDP traffic pattern to determine the effects of this traffic pattern on mobility models in MANET which is implemented in NS-2.35 according to various performance metri (Throughput, AED (Average End-2-end Delay), drop packets, NRL (Normalize Routing Load) and PDF (Packet Delivery Fraction)) with various parameters such as different velocities, different environment areas, different number of nodes, different traffic rates, different traffic sources, different pause times and different simulation times . A routing protocol.…was exploited AODV(Adhoc On demand Distance Vector) and RWP (Random Waypoint), GMM (Gauss Markov Model), RPGM (Refere
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This study was aimed to investigate the response surface methodology (RSM) to evaluate the effects of various experimental conditions on the removal of levofloxacin (LVX) from the aqueous solution by means of electrocoagulation (EC) technique with stainless steel electrodes. The EC process was achieved successfully with the efficiency of LVX removal of 90%. The results obtained from the regression analysis, showed that the data of experiential are better fitted to the polynomial model of second-order with the predicted correlation coefficient (pred. R2) of 0.723, adjusted correlation coefficient (Adj. R2) of 0.907 and correlation coefficient values (R2) of 0.952. This shows that the predicted models and experimental values are in go
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The Hubble telescope is characterized by the accuracy of the image formed in it, as a result of the fact that the surrounding environment is free of optical pollutants. Such as atmospheric gases and dust, in addition to light pollution emanating from industrial and natural light sources on the earth's surface. The Hubble telescope has a relatively large objective lens that provides appropriate light to enter the telescope to get a good image. Because of the nature of astronomical observation, which requires sufficient light intensity emanating from celestial objects (galaxies, stars, planets, etc.). The Hubble telescope is classified as type of the Cassegrain reflecting telescopes, which gives it the advantage of eliminating chromat
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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
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