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In video surveillance and intelligent traffic,bad weather such as foggy,rainy and snowy can seriously affect the visibility of video images.Therefore,it is very important to quickly identify the current weather conditions and make adaptive clearness processing of surveillance videos.Aiming at the problems of poor effect of traditional weather recognition methods and lack of weather image data sets,a multi-class weather image blocks data set is constructed,and a weather recognition algorithm based on image blocks and feature fusion is proposed.The algorithm uses traditional methods to extract four features,namely average gradient,contrast,saturation and dark channel,which are taken as the shallow features of weather images.The algorithm uses transfer learning to fine -tune the VGG16 pre-training model,and extracts the full-connection layer features of the fine-tuning model,which are taken as the deep features of the weather image.The shallow and deep features of weather images are fused and used as the final features to train the Softmax classifier.The classifier can realize the recognition of foggy,rainy,snowy and sunny wea-ther images. Experimental results show that the recognition accuracy of the proposed algorithm can reach 99.26%,and the algorithm can be used as a weather recognition module in the adaptive video image sharpening system.

The subaerial exposure of the modern continental crust through time remains intensely debated, with estimates of the first exposure ranging from the late Archean to the Neoproterozoic. To constrain when and how much of the continental crust was exposed subaerially during Earth's history, we trained a supervised machine learning model on the compositions of modern subaerial and submerged basalts. Then, we applied this well‐trained model to a refined worldwide data set of basaltic compositions and calculated the mean proportions of basalts erupted subaerially since 3.8 billion years ago (Ga). Our results suggest that ∼20% of the basalts were exposed subaerially in the early Archean, which may have driven the synthesis of biopolymers crucial to the origins and evolution of life. The proportion of subaerial basalts increased markedly during two stages between the late Archean and the Paleoproterozoic before reaching the present‐day level no earlier than ∼1.8 Ga. Plain Language Summary: Although land only covers about 30% of Earth's surface, it plays a crucial role in our planet's ecosystem by interacting with the ocean and atmosphere. Scientists are still debating when and how much land was above sea level throughout history. In our study, we used a machine learning technique to analyze the chemical compositions of basalts and classified rocks that formed on land and under water. We then used this program to study rocks from different times in Earth's history and estimate how much land was above the oceans over time. We found that about 15%–30% of the continents were above the oceans about 3.8 to 2.8 billion years ago (Ga). This may have helped life evolve by creating molecules essential for living things. The amount of land above water increased significantly during two periods between 2.8 and 1.8 Ga and reached today's level no earlier than 1.8 Ga. Key Points: Improve the geochemical data quality of global basaltic rocksMachine learning can effectively classify subaerially and subaqueously erupted basaltsThe subaerial proportion of basalts may reach present‐day level at about 1.8 billion years ago to a maximum [ABSTRACT FROM AUTHOR]

Objectives We determined the common clinical characteristics of patients infected with Helicobacter pylori (H. pylori) and investigated the relationship between H. pylori infection, and clinical symptoms, and gastroscopic manifestations. Our focus was specifically on the clinical manifestations in asymptomatic patients. Methods We obtained the physical examination data of patients who underwent the 14C urea breath test between January 2018 and December 2020 at our Hospital. Basic demographic data, questionnaire data on clinical symptoms, and clinical examination data of the patients were also collected, and the correlation analysis was performed. Results A total of 2863 participants were included in the study. The overall H. pylori infection rate was 26.30%. The clinical symptoms between H. pylori -positive patients and H. pylori- negative patients did not differ significantly (P  > .05). However, H. pylori -positive patients exhibited more severe gastroscopic manifestations (P  < .001). The 14C urea breath test disintegrations per minute (DPM) values in H. pylori -positive patients correlated with their serum pepsinogen and gastrin-17 levels. With an increase in the DPM value, more combinations of clinical symptoms appeared in the patients. Among H. pylori -positive patients, DPM levels in asymptomatic patients were lower than those in symptomatic patients (P  < .001). However, gastroscopic manifestations did not vary significantly between asymptomatic and symptomatic patients (P  > .05). Conclusion Patients infected with H. pylori showed no specific gastrointestinal symptoms. Patients with asymptomatic infection showed lower DPM levels, but their gastroscopic manifestations were similar to those of patients with symptomatic infection, and their lesions were more severe than H. pylori -negative people. Key message What is already known on the subject H. pylori is highly contagious and is an important etiological factor for many kinds of disease. Eradication of H. pylori infection can decrease the cost of prevention, diagnosis, and treatment of H. pylori -associated diseases, but the eradication therapy may lead to adverse drug reactions. It has been suggested the treatment for asymptomatic infections should not overkill. What we have found Gastroscopic manifestations of asymptomatic patients were similar to those of symptomatic patients. Both of their lesions were more severe than H. pylori -negative individuals. We provide a theoretical basis for the consideration of the need for further gastroscopy and treatment in clinically asymptomatic infected patients. [ABSTRACT FROM AUTHOR]