Accurate trajectory prediction of surrounding road users is the fundamental input for motion planning,which enables safe autonomous driving on public roads.In this paper,a safe motion planning approach is proposed bas...Accurate trajectory prediction of surrounding road users is the fundamental input for motion planning,which enables safe autonomous driving on public roads.In this paper,a safe motion planning approach is proposed based on the deep learning-based trajectory prediction method.To begin with,a trajectory prediction model is established based on the graph neural network(GNN)that is trained utilizing the INTERACTION dataset.Then,the validated trajectory prediction model is used to predict the future trajectories of surrounding road users,including pedestrians and vehicles.In addition,a GNN prediction model-enabled motion planner is developed based on the model predictive control technique.Furthermore,two driving scenarios are extracted from the INTERACTION dataset to validate and evaluate the effectiveness of the proposed motion planning approach,i.e.,merging and roundabout scenarios.The results demonstrate that the proposed method can lower the risk and improve driving safety compared with the baseline method.展开更多
For living anionic polymerization(LAP),solvent has a great influence on both reaction mechanism and kinetics.In this work,by using the classical butyl lithium-styrene polymerization as a model system,the effect of sol...For living anionic polymerization(LAP),solvent has a great influence on both reaction mechanism and kinetics.In this work,by using the classical butyl lithium-styrene polymerization as a model system,the effect of solvent on the mechanism and kinetics of LAP was revealed through a strategy combining density functional theory(DFT)calculations and kinetic modeling.In terms of mechanism,it is found that the stronger the solvent polarity,the more electrons transfer from initiator to solvent through detailed energy decomposition analysis of electrostatic interactions between initiator and solvent molecules.Furthermore,we also found that the stronger the solvent polarity,the higher the monomer initiation energy barrier and the smaller the initiation rate coefficient.Counterintuitively,initiation is more favorable at lower temperatures based on the calculated results ofΔG_(TS).Finally,the kinetic characteristics in different solvents were further examined by kinetic modeling.It is found that in benzene and n-pentane,the polymerization rate exhibits first-order kinetics.While,slow initiation and fast propagation were observed in tetrahydrofuran(THF)due to the slow free ion formation rate,leading to a deviation from first-order kinetics.展开更多
In current years,the improvement of deep learning has brought about tremendous changes:As a type of unsupervised deep learning algorithm,generative adversarial networks(GANs)have been widely employed in various fields...In current years,the improvement of deep learning has brought about tremendous changes:As a type of unsupervised deep learning algorithm,generative adversarial networks(GANs)have been widely employed in various fields including transportation.This paper reviews the development of GANs and their applications in the transportation domain.Specifically,many adopted GAN variants for autonomous driving are classified and demonstrated according to data generation,video trajectory prediction,and security of detection.To introduce GANs to traffic research,this review summarizes the related techniques for spatio-temporal,sparse data completion,and time-series data evaluation.GAN-based traffic anomaly inspections such as infrastructure detection and status monitoring are also assessed.Moreover,to promote further development of GANs in intelligent transportation systems(ITSs),challenges and noteworthy research directions on this topic are provided.In general,this survey summarizes 130 GAN-related references and provides comprehensive knowledge for scholars who desire to adopt GANs in their scientific works,especially transportation-related tasks.展开更多
Objective:Real-word data on long-acting luteinizing hormone-releasing hormone(LHRH)agonists in Chinese patients with prostate cancer are limited.This study aimed to determine the real-world effectiveness and safety of...Objective:Real-word data on long-acting luteinizing hormone-releasing hormone(LHRH)agonists in Chinese patients with prostate cancer are limited.This study aimed to determine the real-world effectiveness and safety of the LHRH agonist,goserelin,particularly the long-acting 10.8-mg depot formulation,and the follow-up patterns among Chinese prostate cancer patients.Methods:This was a multicenter,prospective,observational study in hormone treatment-na?ve patients with localized or locally advanced prostate cancer who were prescribed goserelin 10.8-mg depot every 12 weeks or 3.6-mg depot every 4 weeks with or without an anti-androgen.The patients had follow-up evaluations for 26 weeks.The primary outcome was the effectiveness of goserelin in reducing serum testosterone and prostate-specific antigen(PSA)levels.The secondary outcomes included testosterone and PSA levels,attainment of chemical castration(serum testosterone<50 ng/d L),and goserelin safety.The exploratory outcome was the monitoring pattern for serum testosterone and PSA.All analyses were descriptive.Results:Between September 2017 and December 2019,a total of 294 eligible patients received≥1 dose of goserelin;287 patients(97.6%)were treated with goserelin 10.8-mg depot.At week 24±2,the changes from baseline[standard deviation(95%confidence interval)]in serum testosterone(n=99)and PSA(n=131)were-401.0 ng/d L[308.4 ng/d L(-462.5,-339.5 ng/d L)]and-35.4 ng/m L[104.4 ng/m L(-53.5,-17.4 ng/m L)],respectively.Of 112 evaluable patients,100(90.2%)achieved a serum testosterone level<50 ng/d L.Treatment-emergent adverse events(TEAEs)and severe TEAEs occurred in 37.1%and 10.2%of patients,respectively.The mean testing frequency(standard deviation)was 1.6(1.5)for testosterone and 2.2(1.6)for PSA.Conclusions:Goserelin 10.8-mg depot effectively achieved and maintained castration and was well-tolerated in Chinese patients with localized and locally advanced prostate cancer.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.52222215,52072051)Chongqing Municipal Natural Science Foundation of China(Grant No.CSTB2023NSCQ-JQX0003).
文摘Accurate trajectory prediction of surrounding road users is the fundamental input for motion planning,which enables safe autonomous driving on public roads.In this paper,a safe motion planning approach is proposed based on the deep learning-based trajectory prediction method.To begin with,a trajectory prediction model is established based on the graph neural network(GNN)that is trained utilizing the INTERACTION dataset.Then,the validated trajectory prediction model is used to predict the future trajectories of surrounding road users,including pedestrians and vehicles.In addition,a GNN prediction model-enabled motion planner is developed based on the model predictive control technique.Furthermore,two driving scenarios are extracted from the INTERACTION dataset to validate and evaluate the effectiveness of the proposed motion planning approach,i.e.,merging and roundabout scenarios.The results demonstrate that the proposed method can lower the risk and improve driving safety compared with the baseline method.
基金financially supported by the National Natural Science Foundation of China(U21A20313,22222807)。
文摘For living anionic polymerization(LAP),solvent has a great influence on both reaction mechanism and kinetics.In this work,by using the classical butyl lithium-styrene polymerization as a model system,the effect of solvent on the mechanism and kinetics of LAP was revealed through a strategy combining density functional theory(DFT)calculations and kinetic modeling.In terms of mechanism,it is found that the stronger the solvent polarity,the more electrons transfer from initiator to solvent through detailed energy decomposition analysis of electrostatic interactions between initiator and solvent molecules.Furthermore,we also found that the stronger the solvent polarity,the higher the monomer initiation energy barrier and the smaller the initiation rate coefficient.Counterintuitively,initiation is more favorable at lower temperatures based on the calculated results ofΔG_(TS).Finally,the kinetic characteristics in different solvents were further examined by kinetic modeling.It is found that in benzene and n-pentane,the polymerization rate exhibits first-order kinetics.While,slow initiation and fast propagation were observed in tetrahydrofuran(THF)due to the slow free ion formation rate,leading to a deviation from first-order kinetics.
基金supported by the National Natural Science Foundation of China(52221005,52220105001,52272420)European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie(101025896)。
文摘In current years,the improvement of deep learning has brought about tremendous changes:As a type of unsupervised deep learning algorithm,generative adversarial networks(GANs)have been widely employed in various fields including transportation.This paper reviews the development of GANs and their applications in the transportation domain.Specifically,many adopted GAN variants for autonomous driving are classified and demonstrated according to data generation,video trajectory prediction,and security of detection.To introduce GANs to traffic research,this review summarizes the related techniques for spatio-temporal,sparse data completion,and time-series data evaluation.GAN-based traffic anomaly inspections such as infrastructure detection and status monitoring are also assessed.Moreover,to promote further development of GANs in intelligent transportation systems(ITSs),challenges and noteworthy research directions on this topic are provided.In general,this survey summarizes 130 GAN-related references and provides comprehensive knowledge for scholars who desire to adopt GANs in their scientific works,especially transportation-related tasks.
文摘Objective:Real-word data on long-acting luteinizing hormone-releasing hormone(LHRH)agonists in Chinese patients with prostate cancer are limited.This study aimed to determine the real-world effectiveness and safety of the LHRH agonist,goserelin,particularly the long-acting 10.8-mg depot formulation,and the follow-up patterns among Chinese prostate cancer patients.Methods:This was a multicenter,prospective,observational study in hormone treatment-na?ve patients with localized or locally advanced prostate cancer who were prescribed goserelin 10.8-mg depot every 12 weeks or 3.6-mg depot every 4 weeks with or without an anti-androgen.The patients had follow-up evaluations for 26 weeks.The primary outcome was the effectiveness of goserelin in reducing serum testosterone and prostate-specific antigen(PSA)levels.The secondary outcomes included testosterone and PSA levels,attainment of chemical castration(serum testosterone<50 ng/d L),and goserelin safety.The exploratory outcome was the monitoring pattern for serum testosterone and PSA.All analyses were descriptive.Results:Between September 2017 and December 2019,a total of 294 eligible patients received≥1 dose of goserelin;287 patients(97.6%)were treated with goserelin 10.8-mg depot.At week 24±2,the changes from baseline[standard deviation(95%confidence interval)]in serum testosterone(n=99)and PSA(n=131)were-401.0 ng/d L[308.4 ng/d L(-462.5,-339.5 ng/d L)]and-35.4 ng/m L[104.4 ng/m L(-53.5,-17.4 ng/m L)],respectively.Of 112 evaluable patients,100(90.2%)achieved a serum testosterone level<50 ng/d L.Treatment-emergent adverse events(TEAEs)and severe TEAEs occurred in 37.1%and 10.2%of patients,respectively.The mean testing frequency(standard deviation)was 1.6(1.5)for testosterone and 2.2(1.6)for PSA.Conclusions:Goserelin 10.8-mg depot effectively achieved and maintained castration and was well-tolerated in Chinese patients with localized and locally advanced prostate cancer.
