Article Agriculture Food Sciences

A Study on the Effectiveness of Glycerophosphocholine (α-GPC) as an e-Sports Supplement

This study examined the effects of oral intake of Glycerophosphocholine (α-GPC) on stress response and cognitive function in e-sports. α-GPC is a precursor of acetylcholine and is sometimes used to treat Alzheimer's disease and other dementias, but its potential effects in e-sports have not been investigated. In this study, 21 participants from university e-sports clubs and other groups were given α-GPC for 2 weeks. We measured their stress responses induced by e-sports and their performance in cognitive tasks. The results showed that the placebo increased the rate of increase in salivary amylase after e-sports, but α-GPC significantly decreased this increase. It also suppressed the increase in heart rate after e-sports. Furthermore, 1g of α-GPC significantly increased the rate of correct responses in a 3-back task, a cognitive task involving working memory, after ingestion. These results suggest that 2-week intake of α-GPC may enhance cognitive function and contribute to stress reduction and suppression of autonomic nervous system disturbances caused by e-sports. Further study is needed to determine the minimum effective intake period of the supplement.

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Special Issue Agriculture Electrical and Electronic Engineering Food Sciences Information Sciences

Wildlife Approach Detection Using a Custom-Built Multimodal IoT Camera System with Environmental Sound Analysis

This paper presents a custom-built IoT camera system designed for recognizing wild animal approaches, where data transmission and power consumption are critical concerns in resource-constrained outdoor settings. The proposed method involves the spectral analysis on both infrared and environmental sound data before uploading images and videos to the remote server. Experiments, including battery endurance tests and wildlife monitoring, were conducted to validate the system. These results showed that the system minimized false positives caused by environmental factors such as wind or vegetation movement. Importantly, adding frequency features from audio waveforms that capture sounds including wind noise and footsteps led to an improvement in detection accuracy, which increased the AUC from 0.894 to 0.990 in Random Forest (RF) and from 0.900 with infrared sensor data alone to 0.987 in Logistic Regression (LR). These findings contribute to applications in wildlife conservation, agricultural protection, and ecosystem monitoring.

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