CSFPre: Expressway key sections based on CEEMDAN-STSGCN-FCM during the holidays for traffic flow prediction.

The implementation of the toll free during holidays makes a large number of traffic jams on the expressway. Real-time and accurate holiday traffic flow forecasts can assist the traffic management department to guide the diversion and reduce the expressway's congestion. However, most of the current prediction methods focus on predicting traffic flow on ordinary working days or weekends. There are fewer studies for festivals and holidays traffic flow prediction, it is challenging to predict holiday traffic flow accurately because of its sudden and irregular characteristics. Therefore, we put forward a data-driven expressway traffic flow prediction model based on holidays. Firstly, Electronic Toll Collection (ETC) gantry data and toll data are preprocessed to realize data integrity and accuracy. Secondly, after Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) processing, the preprocessed traffic flow is sorted into trend terms and random terms, and the spatial-temporal correlation and heterogeneity of each component are captured simultaneously using the Spatial-Temporal Synchronous Graph Convolutional Networks (STSGCN) model. Finally, the fluctuating traffic flow of holidays is predicted using Fluctuation Coefficient Method (FCM). Through experiments of real ETC gantry data and toll data in Fujian Province, this method is superior to all baseline methods and has achieved good results. It can provide reference for future public travel choices and further road network operation.

Multi-View Travel Time Prediction Based on Electronic Toll Collection Data.

The travel time prediction of vehicles is an important part of intelligent expressways. It can not only provide the vehicle distribution trend of each section for the expressway management department to assist the fine management of the expressway, but it can also provide owners with dynamic and accurate travel time prediction services to assist the owners to formulate more reasonable travel plans. However, there are still some problems in the current travel time prediction research (e.g., different types of vehicles are not processed separately, the proximity of the road network is not considered, and the capture of important information in the spatial-temporal perspective is not considered in depth). In this paper, we propose a Multi-View Travel Time Prediction (MVPPT) model. First, the travel times of different types of vehicles of each section in the expressway are analyzed, and the main differences in the travel times of different types of vehicles are obtained. Second, multiple travel time features are constructed, which include a novel spatial proximity feature. On this basis, we use CNN to capture the spatial correlation and the spatial attention mechanism to capture key information, the BiLSTM to capture the time correlation of time series, and the time attention mechanism capture key time information. Experiments on large-scale real traffic data demonstrate the effectiveness of our proposal over state-of-the-art methods.

Iron-Catalyzed Diastereoselective Intramolecular Olefin Aminobromination with Bromide Ion.

A new iron-catalyzed diastereoselective aminobromination method is reported for both internal and terminal olefins (yield up to 90% and dr up to >20:1). In this transformation, a functionalized hydroxylamine and bromide ion were used as the nitrogen and bromine source, respectively. This method is compatible with a broad range of olefins and provides a convenient approach to synthetically valuable vicinal bromo primary amines. Our studies suggest that both the diastereoselectivity and enantioselectivity for the olefin aminobromination can be controlled by iron catalysts.

Iron(II)-catalyzed asymmetric intramolecular olefin aminochlorination using chloride ion.

An iron-catalyzed enantioselective and diastereoselective intramolecular olefin aminochlorination reaction is reported (ee up to 92%, dr up to 15 : 1). In this reaction, a functionalized hydroxylamine and chloride ion are utilized as nitrogen and chlorine sources, respectively. This new method tolerates a range of synthetically valuable internal olefins that are all incompatible with existing asymmetric olefin aminochlorination methods.

Organocatalytic and scalable synthesis of the anti-influenza drugs zanamivir, laninamivir, and CS-8958.

Zanamivir, laninamivir, and CS-8958 are three neuraminidase inhibitors that have been clinically used to combat influenza. We report herein a novel organocatalytic route for preparing these agents. Only 13 steps are needed for the assembly of zanamivir and laninamivir from inexpensive D-araboascorbic acid by this synthetic route, which relies heavily on a thiourea-catalyzed enantioselective Michael addition of acetone to tert-butyl (2-nitrovinyl)carbamate and an anti-selective Henry reaction of the resulting Michael adduct with an aldehyde prepared from D-araboascorbic acid. The synthetic procedures are scalable, as evident from the preparation of more than 3.5 g of zanamivir.