<span style="font-family:Verdana;">The eddy covariance technique is an accurate and direct tool to measure the Net Ecosystem Exchange (NEE) of carbon dioxide. However, sometimes conditions are not amen...<span style="font-family:Verdana;">The eddy covariance technique is an accurate and direct tool to measure the Net Ecosystem Exchange (NEE) of carbon dioxide. However, sometimes conditions are not amenable to measurements using this technique. Thus, different methods have been developed to allow gap-filling and quality assessment of eddy covariance data sets. In this study first, two different Artificial Neural Networks (ANNs) approaches, the Multi-layer Perceptron (MLP) trained by the Back-Propagation (BP) algorithm, and the Radial Basis Function (RBF), were used to fill missing NEE data measured above rain-fed maize at the University of Nebraska-Lincoln Agricultural Research and Development Center near Mead, Nebraska. The gap-filled data were then compared by different statistical indices to gap-filled data obtained with the technique suggested by Suyker and Verma in 2005 [S&V method], and the ANN approach presented by Papale in 2003. The results showed that the RBF network was able to find better fits for missing values compared to the MLP (BP) network and S&V method. In addition, unlike the S&V method, which depends on different gap-filling procedures over the year;the structure of RBF and MLP (BP) networks was constant. However, data analysis indicated Papale’s approach gave better fits than the RBF and MLP (BP) methods. Thus, based on this work, Papale’s approach is the best method to estimate the missing data;though the applied statistical indices, which were used for model evaluation, show little difference between Papale’s approach and the RBF and MLP (BP).</span>展开更多
Hole-net structure silicon is fabricated by laser irradiation and annealing, on which a photoluminescence （PL） band in a the region of 650-750 nm is pinned and its intensity increases obviously after oxidation. It i...Hole-net structure silicon is fabricated by laser irradiation and annealing, on which a photoluminescence （PL） band in a the region of 650-750 nm is pinned and its intensity increases obviously after oxidation. It is found that the PL intensity changes with both laser irradiation time and annealing time. Calculations show that some localized states appear in the band gap of the smaller nanocrystal when Silo bonds or Si-O-Si bonds are passivated on the surface. It is discovered that the density and the number of Si=O bonds or Si-O-Si bonds related to both the irradiation time and the annealing time obviously affect the generation of the localized gap states of hole-net silicon, by which the production of stimulated emission through controlling oxidation time can be explained.展开更多
文摘<span style="font-family:Verdana;">The eddy covariance technique is an accurate and direct tool to measure the Net Ecosystem Exchange (NEE) of carbon dioxide. However, sometimes conditions are not amenable to measurements using this technique. Thus, different methods have been developed to allow gap-filling and quality assessment of eddy covariance data sets. In this study first, two different Artificial Neural Networks (ANNs) approaches, the Multi-layer Perceptron (MLP) trained by the Back-Propagation (BP) algorithm, and the Radial Basis Function (RBF), were used to fill missing NEE data measured above rain-fed maize at the University of Nebraska-Lincoln Agricultural Research and Development Center near Mead, Nebraska. The gap-filled data were then compared by different statistical indices to gap-filled data obtained with the technique suggested by Suyker and Verma in 2005 [S&V method], and the ANN approach presented by Papale in 2003. The results showed that the RBF network was able to find better fits for missing values compared to the MLP (BP) network and S&V method. In addition, unlike the S&V method, which depends on different gap-filling procedures over the year;the structure of RBF and MLP (BP) networks was constant. However, data analysis indicated Papale’s approach gave better fits than the RBF and MLP (BP) methods. Thus, based on this work, Papale’s approach is the best method to estimate the missing data;though the applied statistical indices, which were used for model evaluation, show little difference between Papale’s approach and the RBF and MLP (BP).</span>
基金Project supported by the National Natural Science Foundation of China (Grant No 10764002)
文摘Hole-net structure silicon is fabricated by laser irradiation and annealing, on which a photoluminescence （PL） band in a the region of 650-750 nm is pinned and its intensity increases obviously after oxidation. It is found that the PL intensity changes with both laser irradiation time and annealing time. Calculations show that some localized states appear in the band gap of the smaller nanocrystal when Silo bonds or Si-O-Si bonds are passivated on the surface. It is discovered that the density and the number of Si=O bonds or Si-O-Si bonds related to both the irradiation time and the annealing time obviously affect the generation of the localized gap states of hole-net silicon, by which the production of stimulated emission through controlling oxidation time can be explained.
