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In this paper a dynamic model for the simulation of pressurized alkaline water electrolyzers is presented. The model has been developed following a multiphysics approach, integrating electrochemical, thermodynamic, heat transfer and gas evolution processes in order to faithfully reproduce the complete dynamical behavior of these systems. The model has been implemented on MATLAB/Simulink and validated through experimental data from a 1 Nm3/h commercial alkaline water electrolyzer. Validations have been performed under real scenarios where the electrolyzer is working with power profiles characteristic from renewable sources, wind and photovoltaic. The simulated results have been found to be consistent with the real measured values. This model has a great potential to predict the behavior of alkaline water electrolyzers coupled with renewable energy sources, making it a very useful tool for designing efficient green hydrogen production systems.

Many thriving applications where isolation is required, such as LED drivers, traction and EV fast charging, implement $LLC$ resonant converters, particularly when voltage regulation is not required or an additional conversion stage is in charge of it. The $LLC$ converter can be operated under discontinuous conduction mode (DCM), due to its advantages such as unregulated and sensorless operation, fixed switching frequency and voltage gain, and zero-current switching (ZCS). However, ZCS results in EMI and switching losses in the primary converter, particularly for $\geq$1200-V devices. Alternatively, zero-loss switching (ZLS) can be accomplished by means of a proper design of the $LLC$ converter, overcoming the drawbacks of ZCS. The focus of this paper is to perform an exhaustive research on the $LLC$ converter under DCM-ZLS: discontinuous conduction mode with lossless switching in the primary and secondary sides. As a result of this analysis, a set of design boundaries are deduced for parameters such as the magnetizing inductance, the leakage inductance, and the gate resistance. A comprehensive, step-by-step design methodology is proposed and applied to a 18-kW, 200-kHz test bench. The designed parameters are implemented in the converter and several experiments are conducted, including a test at rated input voltage and rated power (600 V, 18 kW). The conduction states studied theoretically in the analysis of the $LLC$ converter are identified in the experimental results, and the operation of the test bench under DCM-ZLS is verified.

This issue marks the first anniversary issue of IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS after it changed its name from IEEE TRANSACTIONS ON NEURAL NETWORKS. I am happy to report that we had a great year! The number of new submissions in a year exceeded 1,000 for the first time in the history of TNN/TNNLS. IEEE TNN had a very successful development for 22 years from 1990 to 2011, and we have good reasons to believe that IEEE TNNLS will have many more years of successful growth.

The field of computational intelligence is the successor of artificial intelligence. It combines elements of learning, evolution and fuzzy logic to create programs that can exhibit, to some degree, intelligent behaviour. The last few years have seen a growth in theoretical and practical developments in this field. This paper presents an extensive survey of the latest patents in the domain of computational intelligence. It discusses and summarises some of these latest developments in terms of patents. The patents are categorised by their domain of application: Artificial Neural Networks, Fuzzy Logic and Evolutionary Algorithms and further classified by the application area.