1,304 research outputs found

    Oxygen radical-scavenging capacities of peptides from swine blood

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    In China, about five hundred million swine are slaughtered yearly, which represents about 45% of the world´s production. Swine blood is generally discarded except for the small amount that is used in soybean curd and other food products. This not only wastes resources, but also contaminates the environment. In this study, we found that peptides from swine blood had molecular masses of less than 2,100 Da and most were about 1,000 Da. Furthermore, the contents of Glu, Val, Met, Ile, Leu, Phe and Lys were higher than those in dried swine blood. Peptides from swine blood most strongly scavenged ·OH among different oxygen species. This is the first reported study on the oxygen radical-scavenging capacities of peptides from swine blood, and the results suggest that swine blood may be promising for use in food or feed.Key words: Peptides of swine blood, components, scavenging capacities, oxygen radicals

    The Study of Dynamic Monitor of Rice Drought in Jiangxi Province with Remote Sensing

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    AbstractMODIS sensor has a high temporal resolution, spectral resolution, and moderate spatial resolution. The data products are widely used in Large-scale and long period dynamic monitoring of drought. This paper focuses on characters of farming rice dominated in Jiangxi province, and analysis on remote sensing monitoring model and drought monitoring indicators which selection the MODIS data products and drought information related from 2000-2008. Established standard for classification of drought in Jiangxi province, and verified instances of 2003 drought in Jiangxi. This study may have a certain significance to agricultural drought monitoring based on rice planting in southern China, because the correspondencematch between the selected TD indices and cloud cover with precipitation and daily maximum temperature evolution curve

    Accelerating polygon beam with peculiar features

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    We report on a novel kind of accelerating beams that follow parabolic paths in free space. In fact, this accelerating peculiar polygon beam (APPB) is induced by the spectral phase symmetrization of the regular polygon beam (RPB) with five intensity beam (RPB) with five intensity peaks, and it preserves a peculiar symmetric structure during propagation. Specially, such beam not only exhibits autofocusing property, but also possesses two types of accelerating intensity maxima, i.e., the cusp and spot-point structure, which does not exist in the previously reported accelerating beams. We also provide a detailed insight into the theoretical origin and characteristics of this spatially accelerating beam through catastrophe theory. Moreover, an experimental scheme based on a digital micromirror device (DMD) with the binary spectral hologram is proposed to generate the target beam by precise modulation, and a longitudinal needle-like focus is observed around the focal region. The experimental results confirm the peculiar features presented in the theoretical findings. Further, the APPB is verified to exhibit self-healing property during propagation with either obstructed cusp or spot intensity maxima point reconstructing after a certain distance. Hence, we believe that the APPB will facilitate the applications in the areas of particle manipulation, material processing and optofludics

    Sinusoidal Frequency Modulation Fourier-Bessel Series for Multicomponent SFM Signal Estimation and Separation

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    Multicomponent sinusoidal frequency modulated (SFM) signals are widely used in radar, acoustics, and biomedicine. The instantaneous frequency (IF) characterizes important physical parameters of the real applications. In this paper, a sinusoidal frequency modulation Fourier-Bessel (SFMFB) series is defined for IF estimation. It provides the signal decomposition on the Bessel function basis with a finer resolution, which proposes an extension of the performance and the applicability of the classic Fourier-Bessel transform (FBT). Based on the property analysis of the SFMFB series, an algorithm of IF estimation and signal separation is introduced. Unlike the existing estimation methods which apply sliding windows to make an instantaneous approximation, the proposed method uses the global data, which provides a longer period gain, therefore achieving a better estimation performance. Moreover, considering that most estimation methods are invalid in multicomponent separation, the individual signals are well separated by the proposed algorithm, which facilitates the further monocomponent analysis. A performance comparison between the proposed method, the FBT, and another recently proposed sinusoidal frequency modulation Fourier transform (SFMFT) is also provided. Simulation results indicate that the proposed method outperforms the existing methods in estimation precision and computation load, and it is free of interference which exists in SFMFT
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