In this paper, an interleaved switched-capacitor bidirectional DC-DC converter with a high step-up/step-down voltage gain is proposed. The interleaved structure is adopted in the low-voltage side of this converter to reduce the ripple of the current through the low-voltage side, and the series-connected structure is adopted in the high-voltage side to achieve the high step-up/step-down voltage gain. In addition, the bidirectional synchronous rectification operations are carried out without requiring any extra hardware, and the efficiency of the converter is improved. Furthermore, the operating principles, voltage and current stresses, and current ripple characteristics of the converter are analyzed. Finally, a 1kW prototype has been developed which verifies a wide voltage-gain range of this converter between the variable low-voltage side (50V-120V) and the constant high-voltage side (400V). The maximum efficiency of the converter is 95.21% in the step-up mode and 95.30% in the step-down mode. The experimental results also validate the feasibility and the effectiveness of the proposed topology.

In this paper, we develop a simple algorithm to determine the required number of generating units of wind-turbine generator and photovoltaic array, and the associated storage capacity for stand-alone hybrid microgrid. The algorithm is based on the observation that the state of charge of battery should be periodically invariant. The optimal sizing of hybrid microgrid is given in the sense that the life cycle cost of system is minimized while the given load power demand can be satisfied without load rejection. We also report a case study to show the efficacy of the developed algorithm.

A curriculum for teaching thinking based on a structured theoretical model that combines elements of out-of-context and infusion methods has been shown to have long-term far transfer effects on students' thinking ability and academic achievement. More work is needed to meet the needs of a wider range of abilities.

The implementation of Project BOOST was well received by hospitals, although sites faced substantial barriers consistent with other QI research reports. The unique mentorship element of Project BOOST proved extremely valuable in helping sites overcome their distinctive challenges and identify facilitators for success. The findings from this qualitative study should contribute to future BOOST implementation success and others' efforts to optimize hospital discharge transitions.

The automation and intellectualization of the manufacturing processes in the iron and steel industry needs the strong support of inspection technologies, which play an important role in the field of quality control. At present, visual inspection technology based on image processing has an absolute advantage because of its intuitive nature, convenience, and efficiency. A major breakthrough in this field can be achieved if sufficient research regarding visual inspection technologies is undertaken. Therefore, the purpose of this article is to study the latest developments in steel inspection relating to the detected object, system hardware, and system software, existing problems of current inspection technologies, and future research directions. The paper mainly focuses on the research status and trends of inspection technology. The network framework based on deep learning provides space for the development of end-to-end mode inspection technology, which would greatly promote the implementation of intelligent manufacturing.