Incidence of four major osteoporotic fragility fractures among older individuals in Sado, Japan, in 2020.

INTRODUCTION: This study compared the 2020 incidence of fragility fractures in Sado City with those from 2004 to 2015. MATERIALS AND METHODS: Data from patients aged ≥ 60 years living in Sado City with fragility fractures in the hip, vertebral, distal radius, and proximal humerus between January 1 and December 31, 2020, were collected. We examined the number and incidence of four types of osteoporotic fractures in the older population aged ≥ 60 years living in Sado City in 2020. We compared the results with those of the 2004, 2010, and 2015 surveys, examining the temporal change and trend in the incidence of the four fracture types in this population. We investigated the use rate of anti-osteoporotic medications and the relationship between their administration and the occurrence of fragility fractures. RESULTS: The age-specific incidence of hip fractures slightly decreased from 2015. However, the incidence of the other three fractures slightly increased, although the difference was not statistically significant. The incidence of hip fractures markedly increased in the 80 s. In 2020, the percentage of patients taking anti-osteoporotic agents before the occurrence of fractures decreased to 12.4% from 14.5% in 2015; it increased from 4% in 2004 to 7.6% in 2010. CONCLUSION: The 2020 incidence of the four fractures did not decrease, and the percentage of patients receiving anti-osteoporotic agents did not increase. A higher frequency of osteoporosis treatment is necessary to reduce the incidence of fragility fractures. We recommend using anti-osteoporotic agents to prevent hip fractures among individuals in their mid-70 s and above.

Greater Activity in the Frontal Cortex on Left Curves: A Vector-Based fNIRS Study of Left and Right Curve Driving.

OBJECTIVES: In the brain, the mechanisms of attention to the left and the right are known to be different. It is possible that brain activity when driving also differs with different horizontal road alignments (left or right curves), but little is known about this. We found driver brain activity to be different when driving on left and right curves, in an experiment using a large-scale driving simulator and functional near-infrared spectroscopy (fNIRS). RESEARCH DESIGN AND METHODS: The participants were fifteen healthy adults. We created a course simulating an expressway, comprising straight line driving and gentle left and right curves, and monitored the participants under driving conditions, in which they drove at a constant speed of 100 km/h, and under non-driving conditions, in which they simply watched the screen (visual task). Changes in hemoglobin concentrations were monitored at 48 channels including the prefrontal cortex, the premotor cortex, the primary motor cortex and the parietal cortex. From orthogonal vectors of changes in deoxyhemoglobin and changes in oxyhemoglobin, we calculated changes in cerebral oxygen exchange, reflecting neural activity, and statistically compared the resulting values from the right and left curve sections. RESULTS: Under driving conditions, there were no sites where cerebral oxygen exchange increased significantly more during right curves than during left curves (p > 0.05), but cerebral oxygen exchange increased significantly more during left curves (p < 0.05) in the right premotor cortex, the right frontal eye field and the bilateral prefrontal cortex. Under non-driving conditions, increases were significantly greater during left curves (p < 0.05) only in the right frontal eye field. CONCLUSIONS: Left curve driving was thus found to require more brain activity at multiple sites, suggesting that left curve driving may require more visual attention than right curve driving. The right frontal eye field was activated under both driving and non-driving conditions.

Biosignal analysis to assess mental stress in automatic driving of trucks: palmar perspiration and masseter electromyography.

Nowadays insight into human-machine interaction is a critical topic with the large-scale development of intelligent vehicles. Biosignal analysis can provide a deeper understanding of driver behaviors that may indicate rationally practical use of the automatic technology. Therefore, this study concentrates on biosignal analysis to quantitatively evaluate mental stress of drivers during automatic driving of trucks, with vehicles set at a closed gap distance apart to reduce air resistance to save energy consumption. By application of two wearable sensor systems, a continuous measurement was realized for palmar perspiration and masseter electromyography, and a biosignal processing method was proposed to assess mental stress levels. In a driving simulator experiment, ten participants completed automatic driving with 4, 8, and 12 m gap distances from the preceding vehicle, and manual driving with about 25 m gap distance as a reference. It was found that mental stress significantly increased when the gap distances decreased, and an abrupt increase in mental stress of drivers was also observed accompanying a sudden change of the gap distance during automatic driving, which corresponded to significantly higher ride discomfort according to subjective reports.

Absolutely exponential stability of a class of neural networks with unbounded delay.

In this paper, the existence and uniqueness of the equilibrium point and absolute stability of a class of neural networks with partially Lipschitz continuous activation functions are investigated. The neural networks contain both variable and unbounded delays. Using the matrix property, a necessary and sufficient condition for the existence and uniqueness of the equilibrium point of the neural networks is obtained. By constructing proper vector Liapunov functions and nonlinear integro-differential inequalities involving both variable delays and unbounded delay, using M-matrix theory, sufficient conditions for absolutely exponential stability are obtained.