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The discrepancy in data distribution between training and testing scenarios, as well as the inductive bias of convolutional neural networks towards image styles, reduces the model's generalization ability. Many unsupervised domain generalization methods based on feature decoupling suffer from an initial neglect of explicit decoupling of content and style features, resulting in content features that still contain considerable redundant information, thereby restricting improvements in generalization capability. To tackle this problem, this paper optimizes the learning process of domain‐invariant (content) features into an information compression issue, minimizing redundancy in content features. Furthermore, to enhance decoupled learning, this paper introduces innovative cross‐domain loss functions and image reconstruction modules that explicitly decouple and merge content and style across different domains. Extensive experiments demonstrate the method's significant enhancements over recent cutting‐edge approaches. [ABSTRACT FROM AUTHOR]

Historical data is the real-time data record generated by the operation of equipment in industrial production. Aiming at the problems such as oversize of data, low efficiency in the process of data collection and storage of domestic PLC monitor and control system, a cross-platform, meeting the requirements of industrial production, facilitating the backtracking of problem collection and storage method is proposed. Data is compressed and collected by using the way of key frames and change sets. This design divides multiple memory buffers and uses timestamp change to achieve automatic switching so as to enhance data read and write efficiency. Meanwhile, the signal and slot mechanism of Qt are used to trigger the thread for data storage operation, which implements data collection and storage at the same time. Running on Windows and Linux operating system platforms, both function and performance of the design meet the requirements.

Since China's reform and opening up, the social economy has achieved rapid development, followed by a sharp increase in carbon dioxide (CO2) emissions. Therefore, at the 75th United Nations General Assembly, China proposed to achieve carbon peaking by 2030 and carbon neutrality by 2060. The research work on advance forecasting of CO2 emissions is essential to achieve the above-mentioned carbon peaking and carbon neutrality goals in China. In order to achieve accurate prediction of CO2 emissions, this study establishes a hybrid intelligent algorithm model suitable for CO2 emissions prediction based on China's CO2 emissions and related socioeconomic indicator data from 1971 to 2017. The hyperparameters of Least Squares Support Vector Regression (LSSVR) are optimized by the Adaptive Artificial Bee Colony (AABC) algorithm to build a high-performance hybrid intelligence model. The research results show that the hybrid intelligent algorithm model designed in this paper has stronger robustness and accuracy with relative error almost within ±5% in the advance prediction of CO2 emissions. The modeling scheme proposed in this study can not only provide strong support for the Chinese government and industry departments to formulate policies related to the carbon peaking and carbon neutrality goals, but also can be extended to the research of other socioeconomic-related issues. [ABSTRACT FROM AUTHOR]

SUMMARY: Pollen tube integrity, growth and guidance are crucial factors in plant sexual reproduction. Members of the plant Skewed5 (SKU5) Similar (SKS) family show strong similarity to multicopper oxidases (MCOs), but they lack conserved histidines in MCO active sites. The functions of most SKS family members are unknown. Here, we show that Arabidopsis pollen‐expressed SKS11 and SKS12 play important roles in pollen tube integrity, growth and guidance. The sks11sks12 mutant exhibited significantly reduced male fertility. Most of the pollen from sks11sks12 plants burst when germinated, and the pollen tubes grew slowly and exhibited defective growth along the funiculus and micropyle. SKS11‐GFP and SKS12‐mCherry were detected at the cell wall in pollen tubes. The contents of several cell wall polysaccharides and arabinogalactans were decreased in the pollen tube cell walls of sks11sks12 plants. Staining with a reactive oxygen species (ROS)‐sensitive dye and use of the H2O2 sensor HyPer revealed that the ROS content in the pollen tubes of sks11sks12 plants was remarkably reduced. SKS11444His‐Ala, in which the last conserved histidine was mutated, could restore the mutant phenotypes of sks11sks12. Thus, SKS11/12 are required for pollen tube integrity, growth and guidance possibly by regulating the ROS level and cell wall polysaccharide deposition or remodeling in pollen tubes. Significance Statement: Pollen tube integrity, growth and guidance are crucial for plant sexual reproduction. Arabidopsis SKU5 Similar 11 and 12, which are highly expressed in pollen and pollen tubes, function in pollen tube integrity, growth and guidance to ensure successful double fertilization. [ABSTRACT FROM AUTHOR]

Since China's reform and opening up, the social economy has achieved rapid development, followed by a sharp increase in carbon dioxide (CO 2 ) emissions. Therefore, at the 75th United Nations General Assembly, China proposed to achieve carbon peaking by 2030 and carbon neutrality by 2060. The research work on advance forecasting of CO 2 emissions is essential to achieve the above-mentioned carbon peaking and carbon neutrality goals in China. In order to achieve accurate prediction of CO 2 emissions, this study establishes a hybrid intelligent algorithm model suitable for CO 2 emissions prediction based on China's CO 2 emissions and related socioeconomic indicator data from 1971 to 2017. The hyperparameters of Least Squares Support Vector Regression (LSSVR) are optimized by the Adaptive Artificial Bee Colony (AABC) algorithm to build a high-performance hybrid intelligence model. The research results show that the hybrid intelligent algorithm model designed in this paper has stronger robustness and accuracy with relative error almost within ±5% in the advance prediction of CO 2 emissions. The modeling scheme proposed in this study can not only provide strong support for the Chinese government and industry departments to formulate policies related to the carbon peaking and carbon neutrality goals, but also can be extended to the research of other socioeconomic-related issues., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Pan Wang et al.)