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Misunderstanding of driver correction behaviors (DCB) is the primary reason for false warnings of lane-departureprediction systems. We propose a learning-based approach to predicting unintended lane-departure behaviors (LDB) and the chance for drivers to bring the vehicle back to the lane. First, in this approach, a personalized driver model for lanedeparture and lane-keeping behavior is established by combining the Gaussian mixture model and the hidden Markov model. Second, based on this model, we develop an online model-based prediction algorithm to predict the forthcoming vehicle trajectory and judge whether the driver will demonstrate an LDB or a DCB. We also develop a warning strategy based on the model-based prediction algorithm that allows the lane-departure warning system to be acceptable for drivers according to the predicted trajectory. In addition, the naturalistic driving data of 10 drivers is collected through the University of Michigan Safety Pilot Model Deployment program to train the personalized driver model and validate this approach. We compare the proposed method with a basic time-to-lane-crossing (TLC) method and a TLC-directional sequence of piecewise lateral slopes (TLC-DSPLS) method. The results show that the proposed approach can reduce the falsewarning rate to 3.07%.Index Terms-Learning-based approach, lane departure warning system, Gaussian mixture model, hidden Markov model, personalized driver model

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This study aimed to investigate the effects of sleep deprivation on postural control, subjective fatigue assessment and psychomotor performance, and to assess the efficiency of an objective post urographic test as an indicator of mental fatigue. Postural sway using static posturography (Romberg's test), subjective fatigue assessment (Stanford Sleepiness Scale) and psychomotor performance (Sternberg dual-task test) were assessed in 12 subjects before and after 24 h of sustained wakefulness. After sustained wakefulness, the Romberg test parameters of circumference area and rectangle area with the eyes-closed, and standard deviation in the anterior-posterior direction with the eyes-open were significantly higher compared with baseline values (before sustained wakefulness). Subjective fatigue assessment scores were also significantly increased, while psychomotor performance was unchanged. Sleep deprivation can arouse a feeling of fatigue and can affect postural stability, hence an objective posturographic test score may be useful as an indicator of mental fatigue.

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Enhanced deposition of atmospheric nitrogen (N) leads to loss of plant diversity in grassland ecosystems. Numerous theories have provided potential explanations for the negative effects of N enrichment on plant diversity. However, the relative importance of each mechanism and the time‐scales of responses for the different functional groups remain unclear. We investigated the temporal responses of plant community in a temperate steppe to N enrichment by linking above‐ground to below‐ground processes using a series of field N‐addition and greenhouse experiments. The N enrichment‐induced declines in plant diversity of grasslands were phase‐based, functional group‐dependent and driven by three below‐ground processes. The rapid accumulation of NH4+-N by N addition inhibited photosynthetic rates of broad‐leaf non‐rhizomatous forbs, contributing to loss of these N‐sensitive species during early phase of N enrichment (≤3 years). The N‐induced changes in this phase were independent of soil pH as evidenced by results from application of lime to mitigate N‐evoked soil acidification. With progression of N addition, manganese (Mn) toxicity to narrow‐leaf non‐rhizomatous forbs due to soil acidification‐induced Mn2+ mobilization in soil accounted for their loss in the second phase of N enrichment (~4–9 years). When N addition proceeded longer than ~10 years, N enrichment stimulated below‐ground meristem differentiation and rhizome growth of the rhizomatous species, leading to the dominance by rhizomatous sedges/grasses in the community at the later phase of N enrichment. Synthesis. The hierarchical mechanisms not only provide a comprehensive explanation for the N enrichment‐induced diversity decline in grasslands, but can also facilitate us to understand the differential sensitivities of ecosystems to chronic N enrichment, and predict future ecosystem dynamics.

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