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Additional file 1: Table S1. Associations between physical activity, vitamin D and obesity/sarcopenia according to age group. Table S2. Vitamin D levels of the total sample and according to physical activity level.

Additional file 1.

The Architecture Analysis and Design Language (AADL) is widely used in the modeling, analysis and verification of the dependability-critical system. Previously, we have implemented the multi-objective (based on dependability and cost) architecture optimization analysis of the AADL model. The cost attribute modeling, however, was only assumed to be a simple numerical value. It cannot accurately reflect the actual cost model. In addition, there is still a lack of mature cost modeling methods for AADL. In this paper, we develop a cost modeling method for the latest AADL2. The factors that affect the cost of components and systems are firstly summarized and concluded. Based on those summarized factors, a cost meta-model is secondly abstracted and developed. The cost meta-model is finally defined as a property set in the AADL model. With this cost property set, users can not only use the developed life cycle cost properties directly, but also can define individualized cost properties to meet specific cost requirements. The proposed method has greatly extended the cost modeling capabilities for the AADL.

Considering the problem of autonomous course-tracking of Unmanned Surface Vessel (USV) with uncertain systems, this paper put forwards a control method based on the clustering algorithm. The designed controller is composed of a clustering algorithm controller and a PID controller. Because of the uncertainty of the system, the clustering algorithm analysis controller online learned and classified the expected course to control the rudder, the PID controller adjusts the error. This method solves the problems of low control accuracy and poor control performance of robustness brought by the single system controller. By applying the proposed control method to the control design of USV autonomous course-tracking, the results of the simulation experiment show the effectiveness of the control method.

An improved analytic model predictive control method is proposed to deal with a class of bounded uncertain nonlinear systems. Firstly, invoking the standard results from the Moore-Penrose inverse of matrix, the unmatched problem which exists commonly in input and output dimensions of systems is solved. Secondly, the improved analytic model predictive control method is bounded and the control law can be eliminated uncertainties by utilizing the boundary value. So that the proposed control method can be realized without extra compensation of uncertainties in the process of controlling nonlinear systems. Finally, for an unmatched input-output nonlinear example of rudder roll stabilization system, the simulation results show that the proposed method demonstrates the effectiveness.

To deal with the problem how to control the yaw and roll using rudder together for nonlinear ship roll stabilization motion, a nonlinear control method based on the feedback linearization method and closed-loop gain shaping algorithm is proposed in this paper. Firstly, the feedback linearization method is used to design the nonlinear controller, then closed-loop gain shaping algorithm is used to get the linear control law. When the roll motion is controlled by rudder, the loss of steering gear can be increase, to deal with this problem, the fuzzy algorithm is applied in the roll and yaw weighted coefficients optimization. Finally, simulation results show that the controller has a better adaptation for roll and yaw, and the loss of steering gear can be reduced by a rational selection of weighted coefficients. This method of ship motion control provides a new theory for rudder roll stabilization and it is proved that the control method has important theoretical significance and engineering application values.