Improving the Quality of Wheat Flour Bread by a Thermophilic Xylanase with Ultra Activity and Stability Reconstructed by Ancestral Sequence and Computational-Aided Analysis.

Xylanase is an essential component used to hydrolyze the xylan in wheat flour to enhance the quality of bread. Presently, cold-activated xylanase is popularly utilized to aid in the development of dough. In this study, ancestral sequence reconstruction and molecular docking of xylanase and wheat xylan were used to enhance the activity and stability of a thermophilic xylanase.

Models for predicting vehicle emissions: A comprehensive review.

Air pollution is a primary concern, causing around 7 million premature deaths annually, with traffic-related sources contributing 23 %-45 % of emissions. While several studies have surveyed vehicle emission models, they are either outdated or focus on specific data-driven models. This paper systematically reviews vehicle emission prediction models, comparing traditional approaches with data-driven emission models.

FollowNet: A Comprehensive Benchmark for Car-Following Behavior Modeling.

Car-following is a control process in which a following vehicle adjusts its acceleration to keep a safe distance from the lead vehicle. Recently, there has been a booming of data-driven models that enable more accurate modeling of car-following through real-world driving datasets. Although there are several public datasets available, their formats are not always consistent, making it challenging to determine the state-of-the-art models and how well a new model performs compared to existing ones.

Real-time crash identification using connected electric vehicle operation data.

As the automobile market gradually develops towards intelligence, networking, and information-orientated, intelligent identification based on connected vehicle data becomes a key technology. Specifically, real-time crash identification using vehicle operation data can enable automotive companies to obtain timely information on the safety of user vehicle usage so that timely customer service and roadside rescue can be provided. In this paper, an accurate vehicle crash identification algorithm is developed based on machine learning techniques using electric vehicles' operation data provided by SAIC-GM-Wuling.