This paper presents a cognition path planning with control algorithm design for a nonholonomic wheeled mobile robot based on Particle Swarm Optimization (PSO) algorithm. The aim of this work is to propose the circular roadmap (CRM) method to plan and generate optimal path with free navigation as well as to propose a nonlinear MIMO-PID-MENN controller in order to track the wheeled mobile robot on the reference path. The PSO is used to find an online tune the control parameters of the proposed controller to get the best torques actions for the wheeled mobile robot. The numerical simulation results based on the Matlab package show that the proposed structure has a precise and highly accurate distance of the generated refere

Background: Glass ionomers have good biocompatibility and the ability to adhere to both enamel and dentin. However, they have certain demerits, mainly low tensile and compressive strengths. Therefore, this study was done to assess consistency and compressive strength of glass ionomer reinforced by different amount of hydroxyapatite. Materials and Methods: In this study hydroxyapatite materials were added to glass ionomer cement at different ratios, 10%, 15%, 20%, 25% and 30% (by weight). The standard consistency test described in America dental association (ADA) specification No. 8 was used, so that all new base materials could be conveniently mixed and the results would be of comparable value and the compressive strength test described by

The aim of the current study was to develop a nanostructured double-layer for hydrophobic molecules delivery system. The developed double-layer consisted of polyethylene glycol-based polymeric (PEG) followed by gelatin sub coating of the core hydrophobic molecules containing sodium citrate. The polymeric composition ratio of PEG and the amount of the sub coating gelatin were optimized using the two-level fractional method. The nanoparticles were characterized using AFM and FT-IR techniques. The size of these nano capsules was in the range of 39-76 nm depending on drug loading concentration. The drug was effectively loaded into PEG-Gelatin nanoparticles (≈47%). The hydrophobic molecules-release characteristics in terms of controlled-releas