Search

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]

The hydrogen liquefaction process is highly energy-intensive owing to its cryogenic characteristics, and a large proportion of the total energy is consumed in the subcooling cycle. This study aimed to develop an efficient configuration for the subcooling cycle in the hydrogen liquefaction process. The He-Ne Brayton cycle is one of the most energy-efficient cycles of the various proposed hydrogen liquefaction processes, and it was selected as the base case configuration. To improve its efficiency and economic potential, two different process configurations were proposed: (configuration 1) a dual-pressure cycle that simplified the process configuration, and (configuration 2) a split triple-pressure cycle that decreased the flow rate of the medium- and high-pressure compressors. The ortho–para conversion heat of hydrogen is considered by using heat capacity data of equilibrium hydrogen. Genetic algorithm-based optimization was also conducted to minimize the energy consumption of each configuration, and the optimization results showed that the performance of configuration 1 was worse than that of the base case configuration. In this respect, although less equipment was used, the compression load on each compressor was very intensive, which increased the energy requirements and costs. Configuration 2 provided the best results with a specific energy consumption of 5.69 kWh/kg (3.2% lower than the base case configuration). The total expense of configuration 2 shows the lowest value which is USD 720 million. The process performance improvements were analyzed based on the association between the refrigerant composition and the heat exchange efficiency. The analysis demonstrated that energy efficiency and costs were both improved by dividing the pressure levels and splitting the refrigerant flow rate in configuration 2. [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]

Summary: This study focuses primarily on improving large‐scale hydrogen liquefaction process by integrating liquefied natural gas (LNG) stream to utilize LNG cold energy. For the hydrogen liquefaction process, a large amount of energy is required for the compression and the cryogenic refrigeration system. LNG is one of the main sources for producing hydrogen, and it can be an opportunity to save energy because LNG cold energy is normally discarded into seawater during regasification. The objective of this study is to reduce the specific energy consumption and specific liquefaction cost. The proposed design which produces 300 ton/day of liquid hydrogen is compared with a base case design comprising two‐stage mixed refrigerant refrigeration cycles. To minimize the specific energy consumption, multiparameter optimization is conducted by connecting simulation results to a genetic algorithm. Through the optimization, the flow rates of LNG and MR in the precooling cycle decrease by 1.08 and 21.00 kg/s, respectively. The specific energy consumption is reduced from 4.36 to 4.07 kWh/kg‐LH2. Particularly, in the precooling cycle where the LNG stream is integrated, it decreases by more than 26.40%. Regarding the specific liquefaction cost of hydrogen liquefaction, the capital expenses are reduced by 15.16%, and annual operating expenses are diminished by 9.05%. Therefore, the total specific cost liquefaction shows a reduction of approximately 7.7%. Overall, an efficient hydrogen liquefaction process will provide a guideline for LNG‐dependent countries by reducing the specific energy consumption and the specific liquefaction cost by recovering the waste cold energy. [ABSTRACT FROM AUTHOR]

Transient potassium current channels (IA channels), which are expressed in most brain areas, have a central role in modulating feedforward and feedback inhibition along the dendroaxonic axis. Loss of the modulatory channels is tightly associated with a number of brain diseases such as Alzheimer's disease, epilepsy, fragile X syndrome (FXS), Parkinson's disease, chronic pain, tinnitus, and ataxia. However, the functional significance of IA channels in these diseases has so far been underestimated. In this review, we discuss the distribution and function of IA channels. Particularly, we posit that downregulation of IA channels results in neuronal (mostly dendritic) hyperexcitability accompanied by the imbalanced excitation and inhibition ratio in the brain's networks, eventually causing the brain diseases. Finally, we propose a potential therapeutic target: the enhanced action of IA channels to counteract Ca2+-permeable channels including NMDA receptors could be harnessed to restore dendritic excitability, leading to a balanced neuronal state. [ABSTRACT FROM AUTHOR]