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• The use of NGS is an efficient technique to diagnose cerebral creatine deficiency syndrome precisely. • A combined mass spectrometry with gene mutation analysis is helpful in CCDS diagnosis. • Genetic diagnosis determined that all seven patients were positive for SLC6A8 or GAMT variation. • A total of 12 variants were identified in this cohort, including six novel ones. Cerebral creatine deficiency syndromes (CCDSs) are a group of rare mendelian disorders mainly characterized by intellectual disability, movement anomaly, behavior disorder and seizures. SLC6A8 , GAMT , and GATM are known genes responsible for CCDS. In this study, seven pediatric patients with developmental delay were recruited and submitted to a series of clinical evaluation, laboratory testing, and genetic analysis. The clinical manifestations and core biochemical indications of each child were basically consistent with the diagnosis of CCDS. Genetic diagnosis determined that all patients were positive for SLC6A8 or GAMT variation. A total of 12 variants were identified in this cohort, including six novel ones. The frequency of these variants, the Revel scores and the conservatism of the affected amino acids support their pathogenicity. Our findings expanded the mutation spectrum of CCDS disorders, and provided solid evidence for the counseling to affected families. [ABSTRACT FROM AUTHOR]

This paper aims to present a new type of series–parallel hybrid electric bus and its energy management strategy. This hybrid bus is a post-transmission coupled system employing a novel transmission as the series–parallel configuration switcher. In this paper, the vehicle architecture, transmission scheme and numerical models are presented. The energy management system governs the mode switching between the series mode and the parallel mode as well as the instantaneous power distribution. In this work, two separated controllers using fuzzy logic called Mode Decision and Parallel-driving Energy Management are employed to fulfill these two tasks. The energy management strategy and the applications of fuzzy logic are described. The strategy is validated by a forward-facing simulation program based on the software Matlab/Simulink. The results show that the energy management strategy is effective to control the engine operating in a high-efficiency region as well as to sustain the battery charge state while satisfy the drive ability. The energy consumption is theoretically reduced by 30.3% to that of the conventional bus under transit bus driving cycle. In addition, works need future study are also presented. [Copyright &y& Elsevier]

This paper proposes a method and an algorithm to implement interpretable fuzzy reinforcement learning (IFRL). It provides alternative solutions to common problems in RL, like function approximation and continuous action space. The learning process resembles that of human beings by clustering the encountered states, developing experiences for each of the typical cases, and making decisions fuzzily. The learned policy can be expressed as human-intelligible IF-THEN rules, which facilitates further investigation and improvement. It adopts the actor–critic architecture whereas being different from mainstream policy gradient methods. The value function is approximated through the fuzzy system AnYa. The state–action space is discretized into a static grid with nodes. Each node is treated as one prototype and corresponds to one fuzzy rule, with the value of the node being the consequent. Values of consequents are updated using the Sarsa(λ) algorithm. Probability distribution of optimal actions regarding different states is estimated through Empirical Data Analytics (EDA), Autonomous Learning Multi-Model Systems (ALMMo), and Empirical Fuzzy Sets (ε FS). The fuzzy kernel of IFRL avoids the lack of interpretability in other methods based on neural networks. Simulation results with four problems, namely Mountain Car, Continuous Gridworld, Pendulum Position, and Tank Level Control, are presented as a proof of the proposed concept. [ABSTRACT FROM AUTHOR]

Clutch-to-clutch shift technology is a key enabler for fast and smooth gearshift for multi gear transmissions. However, conventional hydraulic actuation systems for clutches have drawbacks of oil leakage and low efficiency. Electromechanical devices including wedge mechanism offer potential alternative actuators. The previous studies on the wedge emphasize on self-reinforcement, but neglect self-weakened phenomenon. In this paper, a novel dual-wedge mechanism is proposed to exert self-reinforcement and avoid self-weakened effect by selecting a correct working slope. The design concept and physical structure are thoroughly described. Dynamic models for the actuation system and vehicle powertrain are built for performance validation. The results show that the normal force generated by the wedge under self-reinforced case is 2.74 times that under self-weakened case. Using the same amount of the driving motor current, the upshift can be successfully completed in 0.78 s when the correct slope is used; however, it fails to engage the clutch when the incorrect slope is used due to self-weakened effect. So does the downshift. Moreover, the experimental results of the dual-wedge mechanism using the correct slope are comparable to those from the hydraulic actuator of a conventional automatic transmission. [ABSTRACT FROM AUTHOR]