We present a plasmonic nanostructure design by embedding a layer of hexagonal periodic metallic nanospheres between the active layer and transparent anode for bulk heterojunction organic solar cells. The hybrid structure shows broadband optical absorption enhancement from localized surface plasmon resonance with a weak dependence on polarization of incident light. We also theoretically study the optimization of the design to enhance the absorption up to 1.90 times for a typical hybrid active layer based on a low band gap material. (C) 2011 American Institute of Physics. [doi:10.1063/1.3577611
To assemble a heavy payload to the spacecraft (free-floating base), the present study proposes a scheme of multiobjective trajectory planning for preimpact motion of redundant space manipulator (mounted on the base). Force impulse for self-assembly is derived as the function of joint angles/velocities, base pose, and impact direction. The trajectory planning problem is formulated as multiobjective optimization to minimize force impulse, base attitude disturbance, and energy consumption in the load-carrying process. A two-stage trajectory planning algorithm is proposed. To be specific, at the first stage, multiple desired configurations at the contact point are generated by position-level inverse kinematics with Newton–Raphson iterative method. At the second stage, joint trajectories satisfying joint angle limits and desired motion of the payload are parameterized by coefficients of sinusoidal polynomial functions. Multiobjective particle swarm optimization algorithm is adopted to solve the problem of multiobjective trajectory planning, and screening process is conducted to reserve nondominated solutions in limits of joint torques. The algorithm is implemented to a seven degrees of freedom space manipulator, and the effectiveness of the proposed method is verified by simulation results.
To enhance the treatment of motor function impairment, patients’ brain signals for self-control as an external tool may be an extraordinarily hopeful option. For the past 10 years, researchers and clinicians in the brain–computer interface (BCI) field have been using movement-related cortical potential (MRCP) as a control signal in neurorehabilitation applications to induce plasticity by monitoring the intention of action and feedback. Here, we reviewed the research on robot therapy (RT) and virtual reality (VR)-MRCP-based BCI rehabilitation technologies as recent advancements in human healthcare. A list of 18 full-text studies suitable for qualitative review out of 322 articles published between 2000 and 2022 was identified based on inclusion and exclusion criteria. We used PRISMA guidelines for the systematic review, while the PEDro scale was used for quality evaluation. Bibliometric analysis was conducted using the VOSviewer software to identify the relationship and trends of key items. In this review, 4 studies used VR-MRCP, while 14 used RT-MRCP-based BCI neurorehabilitation approaches. The total number of subjects in all identified studies was 107, whereby 4.375 ± 6.3627 were patient subjects and 6.5455 ± 3.0855 were healthy subjects. The type of electrodes, the epoch, classifiers, and the performance information that are being used in the RT- and VR-MRCP-based BCI rehabilitation application are provided in this review. Furthermore, this review also describes the challenges facing this field, solutions, and future directions of these smart human health rehabilitation technologies. By key items relationship and trends analysis, we found that motor control, rehabilitation, and upper limb are important key items in the MRCP-based BCI field. Despite the potential of these rehabilitation technologies, there is a great scarcity of literature related to RT and VR-MRCP-based BCI. However, the information on these rehabilitation methods can be beneficial in developing RT and VR-MRCP-based BCI rehabilitation devices to induce brain plasticity and restore motor impairment. Therefore, this review will provide the basis and references of the MRCP-based BCI used in rehabilitation applications for further clinical and research development.
According to the requirement of wing weight estimation and frequent adjustments during aircraft conceptual design, a wing weight estimation method considering the constraints of structural strength and stiffness is proposed to help designers make wing weight estimations rapidly and accurately. This method implements weight predictions on the basis of structure weight optimization with stiffness constraints and strength constraints, which include achievement of wing shape parametric modeling, rapid structure layout, finite element (FE) model automated generation, load calculation, structure analysis, weight optimization, and weight computed based on modeling. A software tool is developed with this wing weight estimation method. This software can realize the whole process of wing weight estimation with the method and the workload of wing weight estimation is reduced because much of the work can be completed by the software. Finally, an example is given to illustrate that this weight estimation method is effective.
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