Sequential recommendation is an important research task in the field of recommendation systems. The goal of the sequential recommendation task can be defined as follows: given a user’s interaction sequence and the associated timestamp sequence, predict the next item that the user is likely to interact with at the next time step. The existing methods have limitations in capturing the diversity of long-term interests, the dynamics of short-term user interest, and the hierarchical relationship between them.

Sub-headline: Zhejiang University researchers introduce K-SELinux, leveraging the K framework to automate the verification of complex security policies

Three-dimensional computer vision is becoming more prevalent in everyday lives as advances in technology and its accessibility to the general population increase. This type of tech is seen in autonomous driving vehicles, augmented reality (AR), virtual reality (VR) and robotics, to name a few. However, historically, these types of technologies have been limited by their methods employed: LiDAR (light detection and ranging, a remote sensing tech used to measure distances) is limited by its cost and low-resolution to be as useful as it once was in the burgeoning field that is 3D computer vision. Researchers are looking towards something else: vision-based methods using depth foundation models.

Scientists have made major progress in explaining friction, but predicting and controlling it still depends heavily on experiments. A comprehensive review examines the physics-based models behind friction, highlights why friction remains difficult to predict, and identifies key challenges that could make friction control more precise and reliable.

Increasing pavement skid resistance on a London highway by 50% reduced the total number of accidents over four years by 45%, according to the United Kingdom Transport and Road Research Laboratory. The United States National Transportation Safety Board and Federal Highway Administration stated that poor pavement skid resistance is a major cause of driving accidents. These are just two sources cited by an international team of researchers who recently reviewed more than 3,000 studies on tire-road friction and found that while tire-road friction theory and simulations have been well developed across the research scales — rubber-pavement scale, the tire-road scale and the vehicle scale — the scales themselves remain largely unconnected.