A study on the mediating-moderate effect of the types of illicit drugs on mental health in China.

Background: In China, over 5 million people have been identified and registered by the public security institutions for using illicit drugs. The aim of this study is to compare the influence of different types of illicit drugs on the self-reported mental health of Chinese people. In particular, we want to assess the damage of Heroin, Methamphetamine and Ketamine to mental health in a social environment where drug use is strictly regulated. Methods: The study is based on survey with 6,906 people who use drugs in Guangdong province, China. Risk of mental health issue is measured using the Brief Symptoms Inventory 18 (BSI-18) Scale, and a higher BSI-18 score indicates more severe mental health problems. The data was analyzed through multilevel regression analysis, propensity score matching analysis and mediation analysis. Results: The three major types of illicit drugs have both moderating and mediating effects on the length of drug-use history, that Heroin use leads to longer drug-use duration, while Ketamine use causes more damage on mental health per unit time of drug-use duration. Average duration of Methamphetamine use is 0.7 year shorter than average duration of Heroin use, and average duration of Ketamine use is 1.7 year shorter than average duration of Heroin use. For each year of increase of drug-use duration, Ketamine use leads to 1.2 times more of BSI score increase than Heroin use, and 2.3 times more of BSI score increase than Methamphetamine use. Conclusion: These three drugs are associated with severe mental health issue in a society with strict drug regulation. Attention should be paid to the mental health of people regardless of the type of drugs they use.

A Real-Time Semantic Segmentation Method Based on STDC-CT for Recognizing UAV Emergency Landing Zones.

With the accelerated growth of the UAV industry, researchers are paying close attention to the flight safety of UAVs. When a UAV loses its GPS signal or encounters unusual conditions, it must perform an emergency landing. Therefore, real-time recognition of emergency landing zones on the ground is an important research topic. This paper employs a semantic segmentation approach for recognizing emergency landing zones. First, we created a dataset of UAV aerial images, denoted as UAV-City. A total of 600 UAV aerial images were densely annotated with 12 semantic categories. Given the complex backgrounds, diverse categories, and small UAV aerial image targets, we propose the STDC-CT real-time semantic segmentation network for UAV recognition of emergency landing zones. The STDC-CT network is composed of three branches: detail guidance, small object attention extractor, and multi-scale contextual information. The fusion of detailed and contextual information branches is guided by small object attention. We conducted extensive experiments on the UAV-City, Cityscapes, and UAVid datasets to demonstrate that the STDC-CT method is superior for attaining a balance between segmentation accuracy and inference speed. Our method improves the segmentation accuracy of small objects and achieves 76.5% mIoU on the Cityscapes test set at 122.6 FPS, 68.4% mIoU on the UAVid test set, and 67.3% mIoU on the UAV-City dataset at 196.8 FPS on an NVIDIA RTX 2080Ti GPU. Finally, we deployed the STDC-CT model on Jetson TX2 for testing in a real-world environment, attaining real-time semantic segmentation with an average inference speed of 58.32 ms per image.

Controlling chaos-assisted directed transport via quantum resonance.

We report on the first demonstration of chaos-assisted directed transport of a quantum particle held in an amplitude-modulated and tilted optical lattice, through a resonance-induced double-mean displacement relating to the true classically chaotic orbits. The transport velocity is controlled by the driving amplitude and the sign of tilt, and also depends on the phase of the initial state. The chaos-assisted transport feature can be verified experimentally by using a source of single atoms to detect the double-mean displacement one by one, and can be extended to different scientific fields.

Does chaos assist localization or delocalization?

We aim at a long-standing contradiction between chaos-assisted tunneling and chaos-related localization study quantum transport of a single particle held in an amplitude-modulated and tilted optical lattice. We find some near-resonant regions crossing chaotic and regular regions in the parameter space, and demonstrate that chaos can heighten velocity of delocalization in the chaos-resonance overlapping regions, while chaos may aid localization in the other chaotic regions. The degree of localization enhances with increasing the distance between parameter points and near-resonant regions. The results could be useful for experimentally manipulating chaos-assisted transport of single particles in optical or solid-state lattices.