China's "coal-to-gas" policy had large impact on PM1.0 distribution during 2016-2019.

Particulate matter with an aerodynamic diameter of less than 1 µm (PM1.0) can be extremely hazardous to human health, so it is imperative to accurately estimate the spatial and temporal distribution of PM1.0 and analyze the impact of related policies on it. In this study, a stacking generalization model was trained based on aerosol optical depth (AOD) data from satellite observations, combined with related data affecting aerosol concentration such as meteorological data and geographic data. Using this model, the PM1.0 concentration distribution in China during 2016-2019 was estimated, and verified by comparison with ground-based stations. The coefficient of determination (R2) of the model is 0.94, and the root-mean-square error (RMSE) is 8.49 µg/m3, mean absolute error (MAE) is 4.10 µg/m3, proving that the model has a very high performance. Based on the model, this study analyzed the PM1.0 concentration changes during the heating period (November and December) in the regions where the "coal-to-gas" policy was implemented in China, and found that the proposed "coal-to-gas" policy did reduce the PM1.0 concentration in the implemented regions. However, the lack of natural gas due to the unreasonable deployment of the policy in the early stage caused the increase of PM1.0 concentration. This study can provide a reference for the next step of urban air pollution policy development.

Recent advances on the formation, detection, resistance mechanism, and control technology of Listeria monocytogenes biofilm in food industry.

Listeria monocytogenes is an important foodborne pathogen that causes listeriosis, a severe and fatal condition. Biofilms are communities of microorganisms nested within a self-secreted extracellular polymeric substance, and they protect L. monocytogenes from environmental stresses. Biofilms, once formed, can lead to the persistence of L. monocytogenes in processing equipment and are therefore considered to be a major concern for the food industry. This paper briefly introduces the recent advancements on biofilm formation characteristics and detection methods, and focuses on analysis of the mechanism of L. monocytogenes biofilm resistance; Moreover, this paper also summarizes and discusses the existing different techniques of L. monocytogenes biofilm control according to the physical, chemical, biological, and combined strategies, to provide a theoretical reference to aid the choice of effective control technology in the food industry.

Life regression based patch slimming for vision transformers.

Vision transformers have achieved remarkable success in computer vision tasks by using multi-head self-attention modules to capture long-range dependencies within images. However, the high inference computation cost poses a new challenge. Several methods have been proposed to address this problem, mainly by slimming patches. In the inference stage, these methods classify patches into two classes, one to keep and the other to discard in multiple layers. This approach results in additional computation at every layer where patches are discarded, which hinders inference acceleration. In this study, we tackle the patch slimming problem from a different perspective by proposing a life regression module that determines the lifespan of each image patch in one go. During inference, the patch is discarded once the current layer index exceeds its life. Our proposed method avoids additional computation and parameters in multiple layers to enhance inference speed while maintaining competitive performance. Additionally, our approach1 requires fewer training epochs than other patch slimming methods.