Abstract: There are provided isotope-enriched compounds of Formula (I) and pharmaceutically acceptable salts or esters thereof, as well as pharmaceutical compositions thereof and methods of use thereof for prevention and treatment of amyloid-? related diseases, such as Alzheimer's disease.

Abstract: The present invention discloses a backward anti-collision driving decision-making method for a heavy commercial vehicle. Firstly, a traffic environment model is established, and movement state information of a heavy commercial vehicle and a vehicle behind the heavy commercial vehicle is collected. Secondly, a backward collision risk assessment model based on backward distance collision time is established, and a backward collision risk is accurately quantified. Finally, a backward anti-collision driving decision-making problem is described as a Markov decision-making process under a certain reward function, a backward anti-collision driving decision-making model based on deep reinforcement learning is established, and an effective, reliable and adaptive backward anti-collision driving decision-making policy is obtained.

Abstract: A method for predicting a pedestrian crossing behavior for an intersection includes the following steps: step 1: designing an immediate reward function; step 2: establishing a fully convolutional neural network-long-short term memory network (FCN-LSTM) model to predict a motion reward function; step 3: training the fully convolutional neural network-long-short term memory network (FCN-LSTM) model based on reinforcement learning; and step 4: predicting the pedestrian crossing behavior and performing hazard early-warning.

Abstract: The present invention discloses a backward anti-collision driving decision-making method for a heavy commercial vehicle. Firstly, a traffic environment model is established, and movement state information of a heavy commercial vehicle and a vehicle behind the heavy commercial vehicle is collected. Secondly, a backward collision risk assessment model based on backward distance collision time is established, and a backward collision risk is accurately quantified. Finally, a backward anti-collision driving decision-making problem is described as a Markov decision-making process under a certain reward function, a backward anti-collision driving decision-making model based on deep reinforcement learning is established, and an effective, reliable and adaptive backward anti-collision driving decision-making policy is obtained.

Abstract: The present disclosure discloses a method for Internet of Vehicles (IoV) electronic traffic sign information broadcast with Quality of Service (QoS) guaranteed mechanism based on conflict detection. Compared with the traditional WLAN applied in electronic traffic sign information broadcast, the present disclosure significantly reduces the information broadcast delay, and at the same time provide QoS guaranteed service for the information broadcast. It allows IoV, through distributed algorithm, to achieve the electronic traffic sign information broadcast with self-organization framework, short transmission delay and high efficiency.

Abstract: The present disclosure discloses a method for Internet of Vehicles (IoV) electronic traffic sign information broadcast with Quality of Service (QoS) guaranteed mechanism based on conflict detection. Compared with the traditional WLAN applied in electronic traffic sign information broadcast, the present disclosure significantly reduces the information broadcast delay, and at the same time provide QoS guaranteed service for the information broadcast. It allows IoV, through distributed algorithm, to achieve the electronic traffic sign information broadcast with self-organization framework, short transmission delay and high efficiency.