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Abstract-In this paper, we propose a framework to analyze the interactive behaviors of human and robot in physical interactions. Game theory is employed to describe the system under study, and policy iteration is adopted to provide a solution of Nash equilibrium. The human's control objective is estimated based on the measured interaction force, and it is used to adapt the robot's objective such that human-robot coordination can be achieved. The validity of the proposed method is verified through a rigorous proof and experimental studies.

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Abstract-We compare filter bank multicarrier (FBMC) and orthogonal frequency-division multiplexing (OFDM) in the uplink of a multiple access network. Our study reveals that the high sensitivity of OFDM to carrier frequency offset (CFO) among different users and the need for interference cancellation methods to reduce this sensitivity leads to very complex and yet not very high performance systems. In FBMC-based networks, on the other hand, near-perfect performance is achieved without any need for interference cancellation, thanks to the excellent frequency localized filters used in the realization of FBMC systems.Index Terms-Carrier frequency offset (CFO), computational complexity, filter bank multicarrier (FBMC), offset quadrature amplitude modulation (OQAM), orthogonal frequency division multiple access (OFDMA).

Developing highly efficient and stable photocatalysts for the CO2 reduction reaction (CO2RR) remains a great challenge. We designed a Z‐Scheme photocatalyst with N−Cu1−S single‐atom electron bridge (denoted as Cu‐SAEB), which was used to mediate the CO2RR. The production of CO and O2 over Cu‐SAEB is as high as 236.0 and 120.1 μmol g−1 h−1 in the absence of sacrificial agents, respectively, outperforming most previously reported photocatalysts. Notably, the as‐designed Cu‐SAEB is highly stable throughout 30 reaction cycles, totaling 300 h, owing to the strengthened contact interface of Cu‐SAEB, and mediated by the N−Cu1−S atomic structure. Experimental and theoretical calculations indicated that the SAEB greatly promoted the Z‐scheme interfacial charge‐transport process, thus leading to great enhancement of the photocatalytic CO2RR of Cu‐SAEB. This work represents a promising platform for the development of highly efficient and stable photocatalysts that have potential in CO2 conversion applications.

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Robot-assisted rehabilitation is a growing field that can provide an intensity, quality, and quantity of treatment that exceed therapist-mediated rehabilitation. Several control algorithms have been implemented in rehabilitation robots to develop a patient-cooperative strategy with the capacity to understand the intention of the user and provide suitable rehabilitation training. In this paper, we present an upper-limb motion pattern recognition method using surface electromyography (sEMG) signals with a support vector machine (SVM) to control a rehabilitation robot, ReRobot, which was built to conduct upper-limb rehabilitation training for post-stroke patients. For poststroke rehabilitation training using the ReRobot, the upper-limb motion of the patient's healthy side is first recognized by detecting and processing the sEMG signals; then, the ReRobot assists the impaired arm in conducting mirror rehabilitation therapy. To train and test the SVM model, five healthy subjects participated in the experiments and performed five standard upper-limb motions, including shoulder flexion, abduction, internal rotation, external rotation, and elbow joint flexion. Good accuracy was demonstrated in experimental results from the five healthy subjects. By recognizing the model motion of the healthy side, the rehabilitation robot can provide mirror therapy to the affected side. This method can be used as a control strategy of upper-limb rehabilitation robots for self-rehabilitation training with stroke patients.