Parametric design optimisation of proximal humerus plates based on finite element method

Optimal treatment of proximal humerus fractures remains controversial. Locking plates offer theoretical advantages but are associated with complications in the clinic. This study aimed to perform parametric design optimisation of proximal humerus plates to enhance their mechanical performance. A finite element (FE) model was developed that simulated a two-part proximal humerus fracture that had been treated with a Spatial Subchondral Support (S3) plate and subjected to varus bending. The FE model was validated against in vitro biomechanical test results. The predicted load required to apply 5 mm cantilever varus bending was only 0.728% lower. The FE model was then used to conduct a parametric optimisation study to determine the orientations of inferomedial plate screws that would yield minimum fracture gap change (i.e. optimal stability). The feasible design space was automatically identified by imposing clinically relevant constraints, and the creation process of each FE model for the design optimisation was automated. Consequently, 538 FE models were generated, from which the obtained optimal model had 4.686% lower fracture gap change (0.156 mm) than that of the manufacturer’s standard plate. Whereas its screws were oriented towards the inferomedial region and within the range of neck-shaft angle of a healthy subject. The methodology presented in this study promises future applications in patient-specific design optimisation of implants for other regions of the human body

A neurocomputational model for estimating the triple-frequency of T-shaped patch antennas

WOS:000465078300027This article deals with the analysis of T-shaped patch antennas (TPAs) that operates between 1 and 7 GHz at triple-band characteristics. A TPA is composed of three monopole structures so that it has triple-resonant frequency. Neurocomputational (NC) models eliminate the complex procedures for the analysis of patch antennas with irregular shapes. In this study, a NC model based on artificial neural network (ANN) is constructed for analyzing the triple-frequency of TPAs. One hundred TPAs with different electrical and geometric parameters are simulated with a full-wave electromagnetic simulator, and a data matrix is obtained for the training and testing the NC model. The model is trained through the simulated data vector of 80 TPAs and is tested with the remainders 20 TPAs and a fabricated TPA. Therefore, the computed results by the NC model which estimates simply and fast the operating triple-frequency of TPA agree well with the simulated and measured ones.Scientific research fund of Karamanoglu Mehmetbey UniversityKaramanoglu Mehmetbey University [01-M-17]Scientific research fund of Karamanoglu Mehmetbey University, Grant/Award Number: 01-M-1

Transcorneal Electrical Stimulation in Optic Neuropathies

Aim was to achieve improvement in vision and visual fields in optic neuropathies by transcorneal electrical stimulation (TES )

Asymmetric Fundus Autofluorescence Findings in Parkinson's Disease (.pdf)

Motor asymmetry is one of the criteria for the diagnosis of Parkinsons disease ( PD ). Interocular asymmetry in spectral domain optical coherence tomography ( SD-OCT ) of the retina and possibly nerve fiber layer has also been documented