This study investigates the inward flux events following sawtooth crashes in the edge of HL-2A neutral beam heated plasmas.We identified three distinct types of inward fluxes with varying magnitudes and durations,each...This study investigates the inward flux events following sawtooth crashes in the edge of HL-2A neutral beam heated plasmas.We identified three distinct types of inward fluxes with varying magnitudes and durations,each associated with unique plasma parameter fluctuations.Magnetic fluctuations,particularly the disruption of magnetic surface structures caused by sawtooth crashes,may play a significant role in modulating plasma dynamics.Moreover,the crossphase term and coherence between density and velocity fluctuations were found to be key factors in these flux events,with high coherence correlating with peak inward flux.These findings enhance the understanding of fluctuation-induced transport after sawtooth crashes and have implications for plasma confinement in fusion devices.展开更多
Understanding crash contributing factors is essential in safety management and improvement. These factors drive investment decisions, policies, regulations, and other safety-related initiatives. This paper analyzes fa...Understanding crash contributing factors is essential in safety management and improvement. These factors drive investment decisions, policies, regulations, and other safety-related initiatives. This paper analyzes factors that contribute to crash occurrence based on two national datasets in the United States (CISS and NASS-CDS) for the years 2017-2022 and 2010-2015, respectively. Three taxonomies were applied to enhance understanding of the various crash contributing factors. These taxonomies were developed based on previous research and practice and involved different groupings of human factors, vehicle factors, and roadway and environmental factors. Statistics for grouping the different types of factors and statistics for specific factors are provided. The results indicate that human factors are present in over 95% of crashes, roadway and environmental factors are present in over 45% of crashes, and vehicle factors are present in less than 2% of crashes. Regarding factors related to human error and vehicle maintenance, speeding is involved in over 25% of crashes, distraction is involved in over 20% of crashes, alcohol and drugs are involved in over 9% of crashes, and vehicle maintenance is involved in approximately 0.45% of crashes. Approximately 4.4% of crashes involve a driver who “looked but did not see.” Weather is involved in over 13% of crashes. Conclusions: The findings indicate that, consistent with previous research, human factors or human error are present in around 95% of crashes. Infrastructure and environmental factors contribute to about 45% of crashes. Vehicle factors contribute to only 1.67% - 1.71% of crashes. The results from this study could potentially be used to inform future safety management and improvement activities, including policy-making, regulation development, safe systems and systemic safety approaches to safety management, and other engineering, education, emergency response, enforcement, evaluation, and encouragement activities. The findings could also be used in the development of future Driver Assistance Technologies (DAT) systems and in enhancing existing technologies.展开更多
Within-Visual-Range(WVR)air combat is a highly dynamic and uncertain domain where effective strategies require intelligent and adaptive decision-making.Traditional approaches,including rule-based methods and conventio...Within-Visual-Range(WVR)air combat is a highly dynamic and uncertain domain where effective strategies require intelligent and adaptive decision-making.Traditional approaches,including rule-based methods and conventional Reinforcement Learning(RL)algorithms,often focus on maximizing engagement outcomes through direct combat superiority.However,these methods overlook alternative tactics,such as inducing adversaries to crash,which can achieve decisive victories with lower risk and cost.This study proposes Alpha Crash,a novel distributional-rein forcement-learning-based agent specifically designed to defeat opponents by leveraging crash induction strategies.The approach integrates an improved QR-DQN framework to address uncertainties and adversarial tactics,incorporating advanced pilot experience into its reward functions.Extensive simulations reveal Alpha Crash's robust performance,achieving a 91.2%win rate across diverse scenarios by effectively guiding opponents into critical errors.Visualization and altitude analyses illustrate the agent's three-stage crash induction strategies that exploit adversaries'vulnerabilities.These findings underscore Alpha Crash's potential to enhance autonomous decision-making and strategic innovation in real-world air combat applications.展开更多
This paper selects the Corporate Social Responsibility(CSR)index from Hexun.com(2010–2020)and the stock price crash index of China’s Shanghai and Shenzhen A-share listed companies from the China Stock Market&Acc...This paper selects the Corporate Social Responsibility(CSR)index from Hexun.com(2010–2020)and the stock price crash index of China’s Shanghai and Shenzhen A-share listed companies from the China Stock Market&Accounting Research Database(CSMAR)for empirical analysis.By examining the impact of CSR performance on stock price crash risk,this study identifies key relationships and further investigates the moderating role of media promotion and communication as an intermediary to explore the transmission mechanisms and influence between the two.The empirical results indicate that CSR performance is significantly negatively correlated with stock price crash risk,suggesting that strong CSR performance can effectively reduce the likelihood of a stock price crash.Furthermore,additional analysis reveals that media plays a moderating role in the relationship between CSR performance and stock price crash risk.This study aims to contribute to the understanding of the formation mechanisms and analytical paradigms of factors influencing stock price crash risk while providing theoretical support and reference value for risk prevention strategies.展开更多
In 2016 alone, around 4000 people died in crashes involving trucks in the USA, with 21% of these fatalities involving only single-unit trucks. Much research has identified the underlying factors for truck crashes.Howe...In 2016 alone, around 4000 people died in crashes involving trucks in the USA, with 21% of these fatalities involving only single-unit trucks. Much research has identified the underlying factors for truck crashes.However, few studies detected the factors unique to single and multiple crashes, and none have examined these underlying factors to severe truck crashes in conjunction with violation data. The current research assessed all of these factors using two approaches to improve truck safety.The first approach used ordinal logistic regression to investigate the contributory factors that increased the odds of severe single-truck and multiple-vehicle crashes, with involvement of at least one truck. The literature has indicated that past violations can be used to predict future violations and crashes. Therefore, the second approach used risky violations, related to truck crashes, to identify the contributory factors to the risky violations and truck crashes. Driver actions of failure to keep proper lane following too close and driving too fast for conditions accounted for about 40% of all the truck crashes. Therefore, the same violations as the aforementioned driver actions were included in the analysis. Based on ordinal logistic regression, the analysis for the first approach indicated that being under non-normal conditions at the time of crash, driving on dry-road condition and having a distraction in the cabin are some of the factors that increase the odds of severe single-truck crashes. On the other hand,speed compliance, alcohol involvement, and posted speed limits are some of the variables that impacted the severity of multiple-vehicle, truck-involved crashes. With the second approach, the violations related to risky driver actions,which were underlying causes of severe truck crashes, were identified and analysis was run to identify the groups at increased risk of truck-involved crashes. The results of violations indicated that being nonresident, driving offpeak hours, and driving on weekends could increase the risk of truck-involved crashes. This paper offers an insight into the capability of using violation data, in addition to crash data, in identification of possible countermeasures to reduce crash frequency.展开更多
Traffic barriers are in widespread all around the USA as safety countermeasures for reducing the severity of run-off-road crashes. The effect of traffic barriers’ dimension had been ignored in past real-world crash s...Traffic barriers are in widespread all around the USA as safety countermeasures for reducing the severity of run-off-road crashes. The effect of traffic barriers’ dimension had been ignored in past real-world crash studies due to the considerable cost and time needed for collecting field data. This paper presented two new analytical models to investigate the effect of different variables on the severity of crashes involving traffic barriers, and end treatments. For this reason, a field survey was conducted on over 1.3 million linear feet of traffic barriers (approximately 4,176 miles road) in Wyoming to measure traffic barriers’ geometric features like height, length, offset, and slope rate. The collected data included 55% of all non-interstate roads of Wyoming. Based on results, the crashes involving box beam barriers were less severe than the crashes involved with W-beam or concrete barriers. The traffic barriers with a height between 28 and 31 in. were found safer than the traffic barriers shorter than 28 in., while there was no significant difference between the traffic barriers taller than 31 in. to those shorter than 28 in. in terms of crash severity. The end treatments located nearer to the traffic lane had lower crash severity.展开更多
基金support of these experiments.This work was supported by the National Natural Science Foundation of China(12405268,12175227,11875255,12375226,and 11975231)the National Magnetic Confinement Fusion Science Program of China(2022YFE03060003,2022YFE03100004)+1 种基金the Fundamental Research Funds for the Central Universities(WK2140000016)the China Postdoctoral Science Foundation(2022M723066).
文摘This study investigates the inward flux events following sawtooth crashes in the edge of HL-2A neutral beam heated plasmas.We identified three distinct types of inward fluxes with varying magnitudes and durations,each associated with unique plasma parameter fluctuations.Magnetic fluctuations,particularly the disruption of magnetic surface structures caused by sawtooth crashes,may play a significant role in modulating plasma dynamics.Moreover,the crossphase term and coherence between density and velocity fluctuations were found to be key factors in these flux events,with high coherence correlating with peak inward flux.These findings enhance the understanding of fluctuation-induced transport after sawtooth crashes and have implications for plasma confinement in fusion devices.
文摘Understanding crash contributing factors is essential in safety management and improvement. These factors drive investment decisions, policies, regulations, and other safety-related initiatives. This paper analyzes factors that contribute to crash occurrence based on two national datasets in the United States (CISS and NASS-CDS) for the years 2017-2022 and 2010-2015, respectively. Three taxonomies were applied to enhance understanding of the various crash contributing factors. These taxonomies were developed based on previous research and practice and involved different groupings of human factors, vehicle factors, and roadway and environmental factors. Statistics for grouping the different types of factors and statistics for specific factors are provided. The results indicate that human factors are present in over 95% of crashes, roadway and environmental factors are present in over 45% of crashes, and vehicle factors are present in less than 2% of crashes. Regarding factors related to human error and vehicle maintenance, speeding is involved in over 25% of crashes, distraction is involved in over 20% of crashes, alcohol and drugs are involved in over 9% of crashes, and vehicle maintenance is involved in approximately 0.45% of crashes. Approximately 4.4% of crashes involve a driver who “looked but did not see.” Weather is involved in over 13% of crashes. Conclusions: The findings indicate that, consistent with previous research, human factors or human error are present in around 95% of crashes. Infrastructure and environmental factors contribute to about 45% of crashes. Vehicle factors contribute to only 1.67% - 1.71% of crashes. The results from this study could potentially be used to inform future safety management and improvement activities, including policy-making, regulation development, safe systems and systemic safety approaches to safety management, and other engineering, education, emergency response, enforcement, evaluation, and encouragement activities. The findings could also be used in the development of future Driver Assistance Technologies (DAT) systems and in enhancing existing technologies.
基金supported by the National Key R&D Program of China(No.2021YFB3300602)。
文摘Within-Visual-Range(WVR)air combat is a highly dynamic and uncertain domain where effective strategies require intelligent and adaptive decision-making.Traditional approaches,including rule-based methods and conventional Reinforcement Learning(RL)algorithms,often focus on maximizing engagement outcomes through direct combat superiority.However,these methods overlook alternative tactics,such as inducing adversaries to crash,which can achieve decisive victories with lower risk and cost.This study proposes Alpha Crash,a novel distributional-rein forcement-learning-based agent specifically designed to defeat opponents by leveraging crash induction strategies.The approach integrates an improved QR-DQN framework to address uncertainties and adversarial tactics,incorporating advanced pilot experience into its reward functions.Extensive simulations reveal Alpha Crash's robust performance,achieving a 91.2%win rate across diverse scenarios by effectively guiding opponents into critical errors.Visualization and altitude analyses illustrate the agent's three-stage crash induction strategies that exploit adversaries'vulnerabilities.These findings underscore Alpha Crash's potential to enhance autonomous decision-making and strategic innovation in real-world air combat applications.
基金R&D Program of Beijing Municipal Education Commission(Grant No.SM202210005007)。
文摘This paper selects the Corporate Social Responsibility(CSR)index from Hexun.com(2010–2020)and the stock price crash index of China’s Shanghai and Shenzhen A-share listed companies from the China Stock Market&Accounting Research Database(CSMAR)for empirical analysis.By examining the impact of CSR performance on stock price crash risk,this study identifies key relationships and further investigates the moderating role of media promotion and communication as an intermediary to explore the transmission mechanisms and influence between the two.The empirical results indicate that CSR performance is significantly negatively correlated with stock price crash risk,suggesting that strong CSR performance can effectively reduce the likelihood of a stock price crash.Furthermore,additional analysis reveals that media plays a moderating role in the relationship between CSR performance and stock price crash risk.This study aims to contribute to the understanding of the formation mechanisms and analytical paradigms of factors influencing stock price crash risk while providing theoretical support and reference value for risk prevention strategies.
文摘In 2016 alone, around 4000 people died in crashes involving trucks in the USA, with 21% of these fatalities involving only single-unit trucks. Much research has identified the underlying factors for truck crashes.However, few studies detected the factors unique to single and multiple crashes, and none have examined these underlying factors to severe truck crashes in conjunction with violation data. The current research assessed all of these factors using two approaches to improve truck safety.The first approach used ordinal logistic regression to investigate the contributory factors that increased the odds of severe single-truck and multiple-vehicle crashes, with involvement of at least one truck. The literature has indicated that past violations can be used to predict future violations and crashes. Therefore, the second approach used risky violations, related to truck crashes, to identify the contributory factors to the risky violations and truck crashes. Driver actions of failure to keep proper lane following too close and driving too fast for conditions accounted for about 40% of all the truck crashes. Therefore, the same violations as the aforementioned driver actions were included in the analysis. Based on ordinal logistic regression, the analysis for the first approach indicated that being under non-normal conditions at the time of crash, driving on dry-road condition and having a distraction in the cabin are some of the factors that increase the odds of severe single-truck crashes. On the other hand,speed compliance, alcohol involvement, and posted speed limits are some of the variables that impacted the severity of multiple-vehicle, truck-involved crashes. With the second approach, the violations related to risky driver actions,which were underlying causes of severe truck crashes, were identified and analysis was run to identify the groups at increased risk of truck-involved crashes. The results of violations indicated that being nonresident, driving offpeak hours, and driving on weekends could increase the risk of truck-involved crashes. This paper offers an insight into the capability of using violation data, in addition to crash data, in identification of possible countermeasures to reduce crash frequency.
基金part of project#RS03218 funded by the Wyoming Department of Transportation(WYDOT)
文摘Traffic barriers are in widespread all around the USA as safety countermeasures for reducing the severity of run-off-road crashes. The effect of traffic barriers’ dimension had been ignored in past real-world crash studies due to the considerable cost and time needed for collecting field data. This paper presented two new analytical models to investigate the effect of different variables on the severity of crashes involving traffic barriers, and end treatments. For this reason, a field survey was conducted on over 1.3 million linear feet of traffic barriers (approximately 4,176 miles road) in Wyoming to measure traffic barriers’ geometric features like height, length, offset, and slope rate. The collected data included 55% of all non-interstate roads of Wyoming. Based on results, the crashes involving box beam barriers were less severe than the crashes involved with W-beam or concrete barriers. The traffic barriers with a height between 28 and 31 in. were found safer than the traffic barriers shorter than 28 in., while there was no significant difference between the traffic barriers taller than 31 in. to those shorter than 28 in. in terms of crash severity. The end treatments located nearer to the traffic lane had lower crash severity.
