An atom‐economical method for the synthesis of unsymmetrical diaryl selenides from arylhydrazines and stoichiometric amounts of diselenides was developed under mild conditions. The new and facile selenide synthesis involved the use of an inexpensive base in air to form unsymmetrical diaryl selenides in good yields. This C–Se radical arylation of diaryl diselenides was performed by forming aryl radicals from arylhydrazines under oxidative conditions. The formation of a phenyl radical was supported by trapping with 2,2,6,6‐tetramethylpiperidine‐1‐oxyl (TEMPO) in air. Therefore, this synthesis might involve a homolytic aromatic substitution (HAS) mechanism. The synthesis is both low costing and environmentally friendly and, therefore, may be useful for the practical synthesis of unsymmetrical diaryl selenides.

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This paper focuses on the aircraft landing optimization problem where both the landing routes and the landing order of aircrafts should be optimized to minimize an occupancy time of airport, and proposes its optimization method which is robust to dynamical situations such as weather condition change and other aircrafts' landing routes change. As a difficulty of this optimization problem, appropriate landing routes of aircrafts change depending on such an environment change. To tackle this problem, this paper proposes the hierarchical evolutionary computation to solve the aircraft landing optimization problem. Specifically, our method firstly generates candidates of main landing route of all aircrafts with their own additional sub-routes, which can be applied into the main routes depending on the current environmental situation. Secondly, our method evolves the good combination of landing routes (including their sub-routes) of all aircrafts to minimize an occupancy time of airport. Through the intensive experiment on a benchmark problem, the following implications have been found: (1) our method successfully generates robust landing routes including some sub-routes ， which are flexible depending on environmental situations; and (2) Our method can finds an adequate landing order which contributes to reducing the occupancy time.

This paper proposes a learning goal space that visualizes the distribution of the obtained solutions to support the exploration of the learning goals for a learner. Subsequently, we examine the method for assisting a learner to present the novelty of the obtained solution. We conduct a learning experiment using a continuous learning task to identify various solutions. To assign the subjects space to explore the learning goals, several parameters related to the success of the task are not instructed to the subjects. In the comparative experiment, three types of learning feedbacks provided to the subjects are compared. These are presenting the learning goal space with obtained solutions mapped on it, directly presenting the novelty of the obtained solutions mapped on it, and presenting some value that is slightly related to the obtained solution. In the experiments, the subjects to whom the learning goal space or novelty of the obtained solution is shown, continue to identify solutions according to their learning goals until the final stage in the experiment is attained. Therefore, in a continuous learning task, our supporting method of directly or indirectly presenting the novelty of the obtained solution through the learning goal space is effective.