Objective: To test the null hypothesis that there are no correlations between the morphology of the upper jaw, the position of the upper incisors, and facial type. Materials and Methods: From a sample of 191 patients, the FMA angle was used to select 20 short face type, 20 norm face type, and 20 long face type patients, aged 12 to 40 years. Using cone-beam computed tomography (CBCT), tomography was carried out on sagittal sections corresponding to the four upper incisors. Some parameters defining the dentoskeletal relationships, the alveolar thickness, the alveolar height, and the dental movement were measured. The measurements were processed using analysis of variance and Tukey's test. Results: At the upper central incisors, short face type patients presented a greater alveolar bone thickness than long face type patients. In short face type and norm face type subjects the root apex of the upper incisors was farther away from the lingual cortex than in the long face type patients. At the central incisors the alveolar thickness was greater and the lingual cortex was higher with respect to the lateral incisors in all three facial types. Conclusion: At the upper incisors, facial type is statistically significantly correlated with both alveolar bone thickness and distance between the root apex and lingual cortex. (Angle Orthod. 2009;79:692-702.)

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Combining renewable energy sources, as photovoltaic arrays (PV), wind turbine (WT), biomass fuel generators (BM), with back-up units to form a Hybrid Renewable Energy System (HRES) can provide a more economic and reliable energy supply architecture compared to the separate usage of such units. In this work an optimization tool for a general HRES is developed: it generates an operating plan over a specified time horizon of the setpoints of each device to meet all electrical and thermal load requirements with possibly minimum operating costs. A large number of devices, such as conventional and renewable source generators, mandatory and deferrable/adjustable electrical loads, batteries, combined heat and power configurations are modeled with high fidelity. The optimization tool is based on a Sequential Linear Programming (SLP) algorithm, equipped with trust region, which is able to efficiently solve a general nonlinear program. A case study of a real HRES in Tuscany is presented to test the major functionalities of the developed optimization tool