It is highly desirable to realize high-energy-density lithium-ion batteries consisting of nickel-rich layered oxide cathodes (Ni-rich NMC) and Sibased anodes. A critical challenge for Ni-rich NMC is its fast capacity degradation. In addition, the low initial Coulombic efficiency of the Si-based anode consumes the electrochemically active lithium from the cathode and decreases the energy density of full batteries considerably. We consider cathode and anode as a whole to simultaneously resolve the issues of both sides. Ni-rich LiNi 0.65 Mn 0.20 Co 0.15 O 2 (LR-Ni65) consisting of a lithium-enriched gradient interphase layer (∼20 nm) is designed to supply excess electrochemically active lithium to compensate lithium loss at the anode and enhance cycling stability through regulating Li/Ni disorder in the cathode structure. We show that a LR-Ni65||Si/graphite pouch cell displays a capacity (3.29 Ah) greater than that for the counterpart using pristine Ni-rich NMC (2.95 Ah), as well as enhanced cycling stability with 88% capacity retention. The good compatibility with current Ni-rich NMC processing and facile synthesis make the as-fabricated cathode material promising for practical commercial application.

In recent years, several states have undertaken efforts to disseminate evidence-based treatments to agencies and clinicians in their children's service system. In New York, the Evidence Based Treatment Dissemination Center adopted a unique translation-based training and consultation model in which an initial 3-day training was combined with a year of clinical consultation with specific clinician and supervisor elements. This model has been used by the New York State Office of Mental Health for the past 3 years to train 1,210 clinicians and supervisors statewide. This article describes the early adoption and initial implementation of a statewide training program in cognitive-behavioral therapy for youth. The training and consultation model and descriptive findings are presented; lessons learned are described. Future plans include a focus on sustainability and measurement feedback of youth outcomes to enhance the continuity of this program and the quality of the clinical services.

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Abstract-This brief focuses on the problem of H ∞ control for a class of networked control systems with time-varying delay in both forward and backward channels. Based on the average dwell-time method, a novel delay-compensation strategy is proposed by appropriately assigning the subsystem or designing the switching signals. Combined with this strategy, an improved predictive controller design approach in which the controller gain varies with the delay is presented to guarantee that the closed-loop system is exponentially stable with an H ∞ -norm bound for a class of switching signal in terms of nonlinear matrix inequalities. Furthermore, an iterative algorithm is presented to solve these nonlinear matrix inequalities to obtain a suboptimal minimum disturbance attenuation level. A numerical example illustrates the effectiveness of the proposed method.

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This paper presents a robust fuzzy controller design approach for dynamic positioning (DP) system of ships using optimal H ∞ control techniques. The H ∞ control technique is used to exterminate the effects of environmental disturbances. Firstly, a Takagi-Sugeno (TS) fuzzy model is applied to approximate the nonlinear DP system. Next, linear matrix inequality (LMI) and general eigenvalue problem (GEVP) methods are employed to find a positive definite matrix and controller gains. The stability of the controller is proven by using Lyapunov stability theorems. A positive definite matrix is determined by solving LMI equations using robust control toolbox available in MATLAB. The obtained positive definite matrix proves that the designed fuzzy controller is stable. Finally, a uniformly ultimately bound (UUB) and control performance for the dynamic position system is guaranteed. Simulation is carried out, and results are presented to validate the effectiveness and performance of the proposed control system.

Requirement for high accuracy and speed of grasping operation for motion planning is very important. Motion planning algorithms for avoiding obstacles in narrow channels play a vital role for robotic arm effectively operating grasp tasks. The potential function-based RRT*-connect (P-RRT*-connect) algorithm for motion planning is presented by combining the bidirectional artificial potential field into the rapidly exploring random tree star (RRT*) in order to enhance the performance of the RRT*. The motion path is found out by exploring two path trees from the start node and destination node, respectively, with the rapidly exploring random tree star. Two trees advance each other at the same time according to the attractive potential field and the repulsion potential field generated by the artificial potential field method of sampled nodes until they meet. The P-RRT*-connect algorithm is especially suitable for solving the problem of narrow channels. The simulation results prove that the P-RRT*-connect algorithm is more efficient than potential Function-based RRT* (P-RRT*) regardless of the number of iterations or the running time. The experimental data show that the time for the P-RRT*-connect to find the optimal path from the starting node to the target node is half than that of the P-RRT*, and the number of iterations of the P-RRT*-connect is also about one-third less than that of the P-RRT* which is useful for real time.INDEX TERMS Potential function based RRT*-connect, RRT*, artificial potential field, two path trees, narrow channels.