The Longitudinal Association Between Frailty, Cognition, and Quality of Life in Older Europeans.

OBJECTIVES: Evidence on the association between frailty and quality of life (QoL) is mostly limited to cross-sectional studies. Thus, the temporal order and potential mechanisms of this association are largely unknown. Our study examines both the directionality of this association and the role of cognition in this association in longitudinal data. METHODS: Cross-lagged panel models were employed to examine the temporal relationship between frailty and QoL, as well as cognition's role among 19,649 older adults in Europe. Frailty, QoL, and cognition were assessed using the health deficit index, CASP-12, and 3 standard cognitive tests, respectively. RESULTS: We observed a bidirectional association between frailty and QoL and their dynamics. High initial levels of frailty predicted poorer QoL later and vice versa (ß = -0.151 and -0.052, p < .001). The early change in frailty predicted the late change in QoL, and vice versa (ß = -0.093 and -0.061, p < .001). Frailty or its early change drives this interrelationship. Cognition at Wave 5 partially mediated frailty's effect at Wave 4 on QoL at Wave 6 (indirect effect: ß = -0.005, 95% confidence interval = -0.006, -0.004). DISCUSSION: Our findings supported that early prevention of frailty and its risk factors may have more influential protective effects on later physical and mental health, as well as the need for ongoing screening for mental health in aging population. Also, the maintenance of good cognitive performance may help interrupt this possible vicious cycle linking frailty and QoL decline.

An Effective Terrain Aided Navigation for Low-Cost Autonomous Underwater Vehicles.

Terrain-aided navigation is a potentially powerful solution for obtaining submerged position fixes for autonomous underwater vehicles. The application of terrain-aided navigation with high-accuracy inertial navigation systems has demonstrated meter-level navigation accuracy in sea trials. However, available sensors may be limited depending on the type of the mission. Such limitations, especially for low-grade navigation sensors, not only degrade the accuracy of traditional navigation systems, but further impact the ability to successfully employ terrain-aided navigation. To address this problem, a tightly-coupled navigation is presented to successfully estimate the critical sensor errors by incorporating raw sensor data directly into an augmented navigation system. Furthermore, three-dimensional distance errors are calculated, providing measurement updates through the particle filter for absolute and bounded position error. The development of the terrain aided navigation system is elaborated for a vehicle equipped with a non-inertial-grade strapdown inertial navigation system, a 4-beam Doppler Velocity Log range sensor and a sonar altimeter. Using experimental data for navigation performance evaluation in areas with different terrain characteristics, the experiment results further show that the proposed method can be successfully applied to the low-cost AUVs and significantly improves navigation performance.