How driving duration influences drivers' visual behaviors and fatigue awareness: a naturalistic truck driving test study

AbstractBackground: Commercial truck drivers stay behind the wheel for long hours. Fatigue is thus a major safety concern among such long distance travelling drivers.Objectives: Primarily, the study explored the effects of driving duration on commercial truck drivers’ visual features and fatigue awareness. It also examined the association between visual variables and subjective level of fatigue.Methods: Participants of the study were 36 commercial truck drivers. During the study, the participants were grouped into nine on the basis of the differences in their age and were made to participate in the naturalistic driving test. In the driving test, the participants were asked to finish 2h, 3h, and 4h continuous driving tasks. Ten visual indicators and self awareness of fatigue level of the drivers were recorded during the driving hours. One-way ANOVA and Pearson product-moment correlation were used to analyze each visual indicator’s variation by age groups over time, and its association with subjective level of fatigue.Results: The statistical analysis revealed that continuous driving duration had a significant effect on changes of visual indicators and self-reported fatigue level. After 2h of driving, both the average closure duration value and average subjective fatigue level changed significantly. After 4h of driving, other than the average number of saccades and average pupil diameter, all of the driver’s visual indicators had a significant change. In addition, the change of fatigue level is positively associated with the variation of pupil diameter, fixation duration, blink frequency, blink duration, and closure duration. On the other hand, the change of fatigue level was negatively related to number of fixations, search angle, number of saccade, saccade speed, and saccade amplitude.Conclusion: Driving duration has a significant effect on driver’s visual variation and fatigue level. For commercial truck drivers, traffic laws and regulations should strictly control the amount of their continuous driving time. Moreover, driving fatigue can also be evaluated through the change rate of driver’s visual indicators. Awareness of the rate of change in their driving fatigue level alerts drivers to the risk of fatigue and rest moment. [Ethiop. J. Health Dev. 2018;32(1):36-45

Impact of the implementation of carbon emission trading on corporate financial performance : Evidence from listed companies in China

With the development of ecological paradigm coupled with the relentless implementation of myriad environmental policies in China, the rapid development of carbon emission trading and carbon trading market has had a vital impact on the financial performance of enterprises at the microlevel. This study has sampled the A-share listed companies in China, from 2009 to 2018, and adopted the difference-in-difference (DID) method to investigate the effect of the carbon emission trading on corporate financial performance from the microlevel. Evidence showed that the implementation of carbon emission trading effectively improved the total asset-liability ratio of enterprises, though it reduced the value of the current capital market. Moreover, in the regions under strict legal environment, the enhancement effect of the total asset-liability ratio was more obvious, whereas in the regions under loose legal environment, the reduction effect of the value of the capital market was more obvious. Further analysis showed that the implementation of carbon emission trading could not promote Chinese enterprises to increase R&D investment. Hence the implementation of carbon emission trading has improved the level of non-business income of enterprises incorporated into the trading system, but its impact on the investment income of enterprises was not significant.Peer reviewe

Numerical study of hydraulic fracturing fracture area changing rules in underground coal mine

To investigate the relationship between the fractured area created by hydraulic fracturing and various fracturing parameters of underground coal mines, we applied fracture and porous media fluid-solid coupling theory to establish a numerical model of hydraulic fracturing. Three-dimensional numerical simulation of hydraulic fracturing of K1 coal seam in a coalmine was performed using the proposed numerical model. We examined the relations between the fractured area and the injection volume, injection rate, and viscosity of the fracturing fluid. The results showed that the fractured area increased with increasing injection rate, however, the extension rate slowed down; the fractured area initially increased then decreased with increasing viscosity; the fractured area increases rapidly with the increase of the water injection volume at the beginning, then begin to slow, eventually approximate linear growth

Alchemical and structural distribution based representation for improved QML

We introduce a representation of any atom in any chemical environment for the generation of efficient quantum machine learning (QML) models of common electronic ground-state properties. The representation is based on scaled distribution functions explicitly accounting for elemental and structural degrees of freedom. Resulting QML models afford very favorable learning curves for properties of out-of-sample systems including organic molecules, non-covalently bonded protein side-chains, (H$_2$O)$_{40}$-clusters, as well as diverse crystals. The elemental components help to lower the learning curves, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training, as evinced for single, double, and triple bonds among main-group elements