The aim of this study was to evaluate the deflection and stress distribution in endodontically treated molars restored by endocrowns from different materials available for the computer-aided design/computer-aided manufacturing (CAD/CAM) technique using three-dimensional finite element analysis. The models represented extensively damaged molars restored by endocrowns from the following materials: translucent zirconia; zirconia-reinforced glass ceramic; lithium disilicate glass ceramic; polymer-infiltrated ceramic network (PICN) and resin nanoceramic. Axial and oblique loadings were applied and the resulting stress distribution and deflection were analyzed. The Mohr–Coulomb (MC) ratio was also calculated in all models. The translucent zirconia endocrown showed the highest stress concentration within it and the least stress in dental structures. The resin nanoceramic model was associated with the greatest stress concentration in dental tissues, followed by the PICN model. Stress was also concentrated in the distal region of the cement layer. The MC ratio in the cement was higher than 1 in the resin nanoceramic model. Oblique loading caused higher stresses in all components and greater displacement than axial loading, whatever the material of the endocrown was. The translucent zirconia model recorded deflections of enamel and dentin (38.4 µm and 35.7 µm, respectively), while resin nanoceramic showed the highest stress concentration and displacement in the tooth–endocrown complex.

Non-Invasive blood glucose monitoring using infrared (IR) light is considered to be a useful and reliable tool for measuring blood sugar levels during daily activities. IR-based glucose monitoring depends on the variant absorption levels of IR light waves by blood with high or low levels of glucose solution. This paper introduces a low-cost finger probe to measure glucose based on Arduino and embedding a Clarke error grid with fuzzy logic. An electronic blood glucose meter was designed and implemented in a non-invasive and painless manner based on an infrared sensor. The electrical signal expressing the level of glucose in the blood with a mathematical equation was used to calibrate and map the physical and electrical values. The final numerical value was validated with the Clarke error grid by implementing fuzzy logic (FL). The designed device was tested on 30 subjects with 15 diabetes subjects. The results show the high significance of results at points where the FL was able to determine an error range of less than 10% of measured glucose within the same range of the reference measurements. The proposed method of using FL with a Clarke error grid gives more confident and precise outputs in cases of this kind of portable device.