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BackgroundThis study aimed to explore the effect of retaining inferomedial cortical bone contact and fixation with calcar screws on the dynamic and static mechanical stability of proximal humerus fractures treated with a locking plate.MethodsTwelve Synbone prosthetic humeri (SYNBONE-AG, Switzerland) were used for a wedge osteotomy model at the proximal humerus, in four groups. In the cortex contact + screw fixation group and cortex contact group, the inferomedial cortical bone contact was retained. In the screw fixation group and control group, the inferomedial cortical bone contact was not retained. Calcar screw fixation was implemented only in the screw fixation groups. The dynamic and static mechanical stability of the models were tested with dynamic fatigue mechanics testing, quasi-static axial compression, three-point bending, and torsion testing.ResultsThe cortex contact + screw fixation group showed the longest fatigue life and the best stability. There was 35% difference in fatigue life between the cortex contact + screw fixation group and the cortex contact group, 43%between the cortex contact + screw fixation group and screw fixation group, and 63% between the cortex contact + screw fixation group and screw fixation group (P < 0.01). The cortex contact + screw fixation group showed the best axial compressive stiffness, bending stiffness, and torsion stiffness; these were successively decreased in the other three groups (P < 0.01).ConclusionRetaining inferomedial cortical bone contact and fixation with two calcar screws maintained fracture stability with the highest strength and minimum deformation. Of the two methods, restoration of the inferomedial cortical bone support showed better dynamic and static biomechanical properties than placement of calcar screws alone.

Level II, prospective randomised study.

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Dempster-Shafer evidence theory (DST) has shown its great advantages to tackle uncertainty in a wide variety of applications. However, how to quantify the information-based uncertainty of basic probability assignment (BPA) with belief entropy in DST framework is still an open issue. The main work of this study is to define a new belief entropy for measuring uncertainty of BPA. The proposed belief entropy has two components. The first component is based on the summation of the probability mass function (PMF) of single events contained in each BPA, which are obtained using plausibility transformation. The second component is the same as the weighted Hartley entropy. The two components could effectively measure the discord uncertainty and non-specificity uncertainty found in DST framework, respectively. The proposed belief entropy is proved to satisfy the majority of the desired properties for an uncertainty measure in DST framework. In addition, when BPA is probability distribution, the proposed method could degrade to Shannon entropy. The feasibility and superiority of the new belief entropy is verified according to the results of numerical experiments.

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The weapon-target assignment (WTA) problem is a key issue in Command & Control (C2). Asset-based multiobjective static WTA (MOSWTA) problem is known as one of the notable issues of WTA. Since this is an NP-complete problem, multiobjective evolutionary algorithms (MOEAs) can be used to solve it effectively. The multiobjective evolutionary algorithm based on decomposition (MOEA/D) is a practical and promising multiobjective optimization technique. However, MOEA/D is originally designed for continuous multiobjective optimization which loses its efficiency to discrete contexts. In this study, an improved MOEA/D is proposed to solve the asset-based MOSWTA problem. The defining characteristics of this problem are summarized and analyzed. According to these characteristics, an improved MOEA/D framework is introduced. A novel decomposition mechanism is designed. The mating restriction and selection operation are reformulated. Furthermore, a problem-specific population initialization method is presented to improve the efficiency of the proposed algorithm, and a novel nondominated solution-selection method is put forward to handle the constraints of Pareto front. Appropriate extensions of four MOEA variants are developed in comparison with the proposed algorithm on some generated scenarios. Extensive experiments demonstrate that the proposed method is effective and promising.