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In recent years, a large number of countries have connected and distributed photovoltaics in remote rural areas, aiming to promote the use of clean energy in rural areas. The solar energy that is not used in time needs to be discarded, resulting in a large amount of wasted energy. Rural areas are closely related to agricultural production, and solar energy can be used for agricultural nitrogen fixation to supplement the nitrogen needed by crops and effectively use the upcoming waste of solar energy. A photovoltaic-driven plasma reactor for nitrogen fixation in agriculture was designed in this study. The air inlet and outlet holes are arranged above and below the reactor to facilitate air entry and directly interact with the gliding arc generated at the bottom of the electrode to achieve atmospheric nitrogen fixation in agriculture. The characteristics of gliding arc development in the process of nitrogen fixation in agriculture were studied experimentally. There are two discharge modes of the gliding arc discharge: one is steady arc gliding mode (A-G Mode), and the other is breakdown gliding mode (B-G Mode). By collecting discharge signals, different discharge modes of gliding arc discharge were analyzed, and the effect of the air flow rate on the discharge period and discharge mode ratio distribution is discussed. The effects of the air flow rate on the yield, specific energy input, and energy consumption in plasma agriculture were studied. The experimental results show that with an increase in the air flow rate, the B-G mode takes up a larger proportion and the gliding arc discharge period is shortened. However, the higher the proportion of the B-G mode, the more unfavorable the production of nitrogen oxides. Although the nitrogen oxides generated by the system are not particularly excellent compared with the Haber-Bosch ammonia process (H-B process), the access to distributed photovoltaic roofs in rural and remote areas can effectively use available resources like water, air, and solar, and avoid energy waste in areas where wind and solar are abandoned. [ABSTRACT FROM AUTHOR]

Abstract: Two thin-film 10B samples on tantalum backings were made for measurement of cross sections of the 10B(n,α)7Li reaction in the MeV neutron energy region. The number of 10B atoms in the samples was determined using the relative comparison method by detecting alpha and triton particles from thermal neutron induced nuclear reactions of 10B(nth,α)7Li and 6Li(nth,t)4He with a 6LiF sample as the reference. A twin gridded ionization chamber was used as the detector of charged particles. [Copyright &y& Elsevier]

Alzheimer's disease (AD) is an irreversible neurodegenerative disease with a high prevalence in the elderly population over 65 years of age. Intervention in the early stages of AD is of great significance to alleviate the symptoms. Recent advances in deep learning have shown extreme advantages in computer-aided diagnosis of AD. However, most studies only focus on extracting features from slices in specific directions or whole brain images, ignoring the complementarity between features from different angles. To overcome the above problem, attention-based multi-view slice fusion (AMSF) is proposed for accurate early diagnosis of AD. It adopts the fusion of three-dimensional (3D) global features with multi-view 2D slice features by using an attention mechanism to guide the fusion of slice features for each view, to generate a comprehensive representation of the MRI images for classification. The experiments on the public dataset demonstrate that AMSF achieves 94.3% accuracy with 1.6-7.1% higher than other previous promising methods. It indicates that the better solution for AD early diagnosis depends not only on the large scale of the dataset but also on the organic combination of feature construction strategy and deep neural networks., Competing Interests: The authors declare that they have no competing interests., (© 2023 Zhang et al.)