Today, with the rise and development of sports science, athletes and coaches increasingly leverage scientific and medical insights to challenge both personal and human boundaries of performance.
In nearly all sports, improving performance is closely tied to solving fluid dynamics problems.
This is particularly critical in ball sports like baseball, soccer, and table tennis, where the interaction between the ball and the surrounding airflow plays a crucial role during the game.
To address these challenges, fluid dynamics simulations using computers, including high-performance computers, are indispensable.
The origins of various artificial intelligence technologies lie in the exploration of neurons and their network activities.
The MP model of neurons serves as the foundation for the diverse neural network architectures we see today.
With the continuous advancement of AI technology, the focus of current neural network research has moved beyond the construction of individual neurons.
Nevertheless, for neuroscientists, the investigation of the operational principles of the nervous system, particularly the central nervous system, remains profoundly challenging.
Computer technology has introduced powerful tools to the field of neuroscience.
Through simulation methods, it is now feasible to replicate brain activity at the level of individual neurons.
This capability is of significant importance for studying brain tissue patterns and functional principles, as well as for understanding the mechanisms and progression of central nervous system diseases.
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