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Artificial intelligence has recently seen tremendous growth, and been applied to several fields, including the second-language domain. In this article, we share an innovative practice based on one of potential artificial intelligence technologies for second-language teaching and learning -- artificial intelligence-based content generator, which generates texts based on user's keywords. In total, 121 young English-as-a-foreign-language learners participated in the study, with half of them having engaged in the artificial intelligence-based content generator-based activity, and the other half having received traditional English-as-a-foreign-language reading instruction. We examined the extent to which the artificial intelligence-based content generator-based activity could influence the participants' foreign language enjoyment and interests in reading English books, and the participants were given the survey addressing these variables, prior to and after the innovative practice. It was found that the condition based on the artificial intelligence-based content generator-based activity was more effective in terms of enhancing the target variables, and that the group which engaged in the artificial intelligence-based content generator-based activity was largely in favor of artificial intelligence-based content generator technology. Pedagogical implications for employing this technology in second-language contexts are provided.

Artificial intelligence has recently seen tremendous growth, and been applied to several fields, including the second-language domain. In this article, we share an innovative practice based on one of potential artificial intelligence technologies for second-language teaching and learning – artificial intelligence-based content generator, which generates texts based on user's keywords. In total, 121 young English-as-a-foreign-language learners participated in the study, with half of them having engaged in the artificial intelligence-based content generator-based activity, and the other half having received traditional English-as-a-foreign-language reading instruction. We examined the extent to which the artificial intelligence-based content generator-based activity could influence the participants' foreign language enjoyment and interests in reading English books, and the participants were given the survey addressing these variables, prior to and after the innovative practice. It was found that the condition based on the artificial intelligence-based content generator-based activity was more effective in terms of enhancing the target variables, and that the group which engaged in the artificial intelligence-based content generator-based activity was largely in favor of artificial intelligence-based content generator technology. Pedagogical implications for employing this technology in second-language contexts are provided. [ABSTRACT FROM AUTHOR]

Summary: This study mainly focuses on determining the optimal configuration that efficiently utilizes liquefied natural gas (LNG) cold energy in hydrogen precooling for liquid hydrogen production. To achieve this goal, two different configurations are designed: (a) adding LNG cold energy to the existing hydrogen precooling cycle and (b) replacing the existing hydrogen precooling cycle with LNG cold energy. An equilibrium hydrogen model is developed to reflect the thermodynamic property of ortho‐para conversion of hydrogen. Bayesian optimization is performed to determine the optimal operating conditions which minimize the specific energy consumption for all configurations. The specific energy consumption of the configuration involving hydrogen precooling with only LNG is 5.613 kWh/kg‐LH2, and it is reduced by 8.13% and 3.19% from the base case design and the configuration involving hydrogen precooling with both LNG and a mixed refrigerant cycle, respectively. In addition, a techno‐economic analysis is conducted. Compare to the base case design, the capital cost and operating cost of the design replacing hydrogen precooling with LNG are reduced by 31.76% and 11.55%, respectively. This study shows that the proposed design of replacing the hydrogen precooling cycle with an LNG stream can save energy consumption, moreover, it is highly effective for capital investment saving due to its simple configuration. [ABSTRACT FROM AUTHOR]