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【Objective】 The Budyko’s assumption is that evapotranspiration is limited by water in semi-arid regions and by energy in wet regions. This paper applied it to estimate evapotranspiration from irrigated agricultural lands in China. 【Method】 The results calculated using the Budyko equation were tested against irrigation, precipitation, groundwater evaporation and real evapotranspiration measured from 2010 to 2017 from 282 irrigation districts across China. Based on these data and results, we analyzed the accuracy of the Budyko equation for cropped lands under different climatic conditions. 【Result】 The Budyko equation and the Fu's equation, both considering irrigation and groundwater evaporation, are adequate to estimate evapotranspiration from irrigated cropped lands. The mean relative error between the estimated ET and the measured ET is less than 21.7%. Overall, the estimated ET is more accurate for humid areas, where the planting structure and irrigation are less prone to fluctuation and change, than for other areas. Impacted by meteorology, water supply and distribution, soil texture and planting structure in irrigation districts, the parameter ω in the Budyko curves varies spatially and increases, in general, with humidity. 【Conclusion】 The Budyko equation works well for estimating annual evapotranspiration from irrigated cropped lands in China.

The integration of radar interference is an effective technical path to optimize radio frequency resources and realize directional interference. Radar interference integrated waveform design is a hot spot in radar interference integrated research. This paper presents an radar interference integrated waveform based on Zadoff-Chu sequence and orthogonal frequency division multiplexing (OFDM) architecture, and studies the waveform design and processing methods. The waveform uses OFDM as the modulation mode and time- frequency division multiplexing as the basic architecture. The frequency domain subcarriers are reasonably allocated and modulated through Zadoff-Chu and Mersenne-Twister sequences to achieve the integration of detection and interference functions. In signal processing, the first step in to separate the time and frequency of interference detection, and the second step in to conduct pulse compression and coherent processing, so as to achieve ranging and velocity measurement. Theoretical analysis and simulation test show that the proposed waveform has the advantages of high ratio of main lobe to side lobe of pulse compression, strong Doppler tolerance, flexible frequency alignment and strong interference randomness. [ABSTRACT FROM AUTHOR]

Insufficient reactive oxygen species originating from hypoxia and high glutathione (GSH) in the tumor microenvironment (TME) is an important reason for radiotherapy (RT) resistance. Currently, radiosensitizers that remodel TME are widely investigated to enhance RT. However, developing an effective nano‐radiosensitization system that removes radiotherapy‐resistant factors from TME to boost RT effect while visualizing tumor imaging to aid therapy remains a challenge. Herein, MnO2 nanosheets are grown on the surface of ultrasmall Eu‐doped NaGdF4 (NaGdF4:Eu3+) nanoparticles and modified by biocompatible DSPE‐PEG2000 to prepare NaGdF4:Eu3+@MnO2@PEG nanoparticles (denoted as GMP NPs) as a radiosensitizer, which not only can reverse the TME by degrading H2O2 to produce oxygen and consuming high GSH but also achieve computed tomography (CT)and magnetic resonance (MR) imaging. When GMP NPs synergize with X‐ray, a better antitumor effect is achieved in both HeLa cells and tumor‐bearing mice, compared with X‐ray alone. In addition, both paramagnetic Mn2+ ionsproduced by decomposing MnO2 in TME and NaGdF4:Eu3+ nanoparticles enhance T1‐weighted MR imaging. NaGdF4:Eu3+ nanoparticles containing high atomic number of Gd/Eu effectively attenuate X‐ray to enhance CT imaging. The work provides new insights for developing an efficient RT sensitization platform integrating antitumor therapeutic effect as well as CT/MR dual‐modal imaging. [ABSTRACT FROM AUTHOR]

Budyko's framework has been widely used to study basin-scale water balance. In this study, we focus on the extended application of Fu's equation (one formulation of the Budykotype curves) to 371 large irrigation districts in China over a period of 2010-2017. Water balance method was used to estimate actual evapotranspiration (ET) in the irrigated areas. Considering the contribution of shallow groundwater to ET, the water availability in the Budyko framework defined as equivalent precipitation (Pe) for irrigation areas is the sum of irrigation water (l), precipitation (P) and groundwater evaporation (ET,,,). Results showed that the relationships between evapotranspiration (ET), water availability (Pe) and energy supply (ET0) can be accurately described by the Budyko's curves. The Fu's equation performed better in humid and semi-humid regions than arid and semi-arid regions. The comparison between OET/OP, and OET/OET0 confirmed the relative effect of water availability and energy supply on ET according to the variation of climatic conditions. The optimal values of Budyko parameter ω for each irrigation district was obtained with multi-annual data using least square method. Normalized Difference Vegetation Index (NDVI) and soil property (denoted by the proportion of clay and sand) were selected to develop empirical equation for parameter ω using multiple linear regression analysis method. This study showed that the Budyko framework can be extended to irrigation areas and provide useful information on evapotranspiration to assist in water management in irrigation areas. [ABSTRACT FROM AUTHOR]

The unintentional electromagnetic (EM) emission of computer monitors may cause the leakage of image information displayed on the monitor. Detection of EM information leakage risk is significant for the information security of the monitor. The traditional detection method is to verify EM information leakage by reconstructing an image from EM emission. The detection method based on image reconstruction has limitations: adequate signal sampling rate, accurate synchronization signal, and dependence on operational experience. In this paper, we analyze the principle of image information leakage and propose an innovative detection method based on Convolutional Neural Network (CNN). This method can identify the image information in EM emission to verify the EM information leakage risk of the monitor. It overcomes the limitations of the traditional method with machine learning. This is a new attempt in the field of EM information leakage detection. Experimental results show that it is more adaptable and reliable in complex detection environment. [ABSTRACT FROM AUTHOR]