Hollow core photonic bandgap fibers provide a new geometry for the realization and enhancement of many nonlinear optical effects. Such fibers offer novel guidance and dispersion properties that provide an advantage over conventional fibers for various applications. Dispersion, which expresses the variation with wavelength of the guided-mode group velocity, is one of the most important properties of optical fibers. Photonic crystal fibers (PCFs) offer much larger flexibility than conventional fibers with respect to tailoring of the dispersion curve. This is partly due to the large refractive-index contrast available in the silica/air microstructures, and partly due to the possibility of making complex refractive-index structure over the fibe

Background: Decalcification of surface enamel adjacent to fixed orthodontic appliances, in the form of white spot lesions, is a wide spread and familiar well-known side effect of orthodontic treatment. The present study was carried out to evaluate the effect of enamel protective agent (Clinpro white varnish) on shear and tensile bond strength of Dentaurum orthodontic stainless steel brackets by using 3M Unitek and Ormco as orthodontic adhesive agents. Materials and methods: Sixty-four extracted human upper first premolar teeth were selected and randomly divided into two groups with 32 teeth each, representing the shear and tensile bond strength testing groups. Then according to the type of bonding adhesive and the addition of Clinpro before

This study investigates the corrosion inhibition performance of a newly synthesized quinazolinone derivative, AMQ, on mild steel in a hydrochloric acid medium. The inhibition efficiency was evaluated using potentiodynamic polarization at varying inhibitor concentrations (100–250 ppm) and temperatures (303– 333 K). The results showed that AMQ exhibited effective corrosion inhibition, with the highest efficiency of 74% observed at 250 ppm and 323 K. Density Functional Theory (DFT) calculations were conducted to study the electronic properties of AMQ and its adsorption behavior. The thermodynamic parameters, including activation energy, enthalpy, and Gibbs free energy, were calculated, indicating spontaneous adsorption of AMQ onto the meta

In the present work the performance of semifluidized bed adsorber was evaluated for removal of phenolic compound from wastewater using commercial activated carbon as adsorbent. P-chlorophenol (4-Chlorophenol) and o-cresol (2-methylphenol) was selected as a phenolic compound for that purpose. The phenols percent removal, in term of breakthrough curves were studied as affected by hydrodynamics limitations which include minimum and maximum semifluidization velocities and packed bed formation in the column by varying various parameters such as inlet liquid superficial velocity (from U_minsf to 8U_minsf m/s), and retaining grid (sometimes referred to as adsorbent loading) to initial static bed height ratio (from 3-4.5). In

The present work elucidates the utilization of activated carbon (AC) and activated carbon loaded with silver nanoparticles (AgNPs-AC) to remove tetracycline (TC) from synthetically polluted water. The activated carbon was prepared from tea residue and loaded with silver nanoparticles. Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET) were used to characterize the activated carbon (AC) and silver nanoparticles-loaded activated carbon (AgNPs-AC). The impact of various parameters on the adsorption effectiveness of TC was examined. These variables were the initial adsorbate concentration (Co), solution acidity (pH), adsorption time (t), and dosag

Objective: To enhance bonding strength between thermoplastic denture base and acrylic soft liner through ethyl acetate surface treatment. Materials and Methods: Modifications of thermoplastic acrylic denture base surface were investigated with SEM. FTIR was used to detect whether there was a chemical bond between thermoplastic acrylic and the organic solvent. A total of 80 samples were prepared and divided into 20 samples for the surface roughness test and 60 samples for the shear bond strength test. Failure type was assessed visually. Results: Shear bond strength and surface roughness values of un treated samples were lower in comparison to surface treated groups; the greatest post thermocycling bond strength value was recorded for the sam

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the