Regional estimation of daily to annual regional evapotranspiration with MODIS data in the Yellow River Delta wetland

Evapotranspiration (ET) from the wetland of the Yellow River Delta (YRD) is one of the important components in the water cycle, which represents the water consumption by the plants and evaporation from the water and the non-vegetated surfaces. Reliable estimates of the total evapotranspiration from the wetland is useful information both for understanding the hydrological process and for water management to protect this natural environment. Due to the heterogeneity of the vegetation types and canopy density and of soil water content over the wetland (specifically over the natural reserve areas), it is difficult to estimate the regional evapotranspiration extrapolating measurements or calculations usually done locally for a specific land cover type. Remote sensing can provide observations of land surface conditions with high spatial and temporal resolution and coverage. In this study, a model based on the Energy Balance method was used to calculate daily evapotranspiration (ET) using instantaneous observations of land surface reflectance and temperature from MODIS when the data were available on clouds-free days. A time series analysis algorithm was then applied to generate a time series of daily ET over a year period by filling the gaps in the observation series due to clouds. A detailed vegetation classification map was used to help identifying areas of various wetland vegetation types in the YRD wetland. Such information was also used to improve the parameterizations in the energy balance model to improve the accuracy of ET estimates. This study showed that spatial variation of ET was significant over the same vegetation class at a given time and over different vegetation types in different seasons in the YRD wetlan

A New Method to Calculate Electromagnetic Impedance Matching Degree in One-Layer Microwave Absorbers

A delta-function method was proposed to quantitatively evaluate the electromagnetic impedance matching degree. Measured electromagnetic parameters of {\alpha}-Fe/Fe3B/Y2O3 nanocomposites are applied to calculate the matching degree by the method. Compared with reflection loss and quarter-wave principle theory, the method accurately reveals the intrinsic mechanism of microwave transmission and reflection properties. A possible honeycomb structure with promising high-performance microwave absorption according to the method is also proposed.Comment: 13 pages, 3 figure

Probabilistic teleportation of unknown two-particle state via POVM

We propose a scheme for probabilistic teleportation of unknown two-particle state with partly entangled four-particle state via POVM. In this scheme the teleportation of unknown two-particle state can be realized with certain probability by performing two Bell state measurements, a proper POVM and a unitary transformation.Comment: 5 pages, no figur

Approximating the monomer-dimer constants through matrix permanent

The monomer-dimer model is fundamental in statistical mechanics. However, it is #P-complete in computation, even for two dimensional problems. A formulation in matrix permanent for the partition function of the monomer-dimer model is proposed in this paper, by transforming the number of all matchings of a bipartite graph into the number of perfect matchings of an extended bipartite graph, which can be given by a matrix permanent. Sequential importance sampling algorithm is applied to compute the permanents. For two-dimensional lattice with periodic condition, we obtain $0.6627\pm0.0002$, where the exact value is $h_2=0.662798972834$. For three-dimensional lattice with periodic condition, our numerical result is $0.7847\pm0.0014$, {which agrees with the best known bound $0.7653 \leq h_3 \leq 0.7862$.}Comment: 6 pages, 2 figure

A statistical study on the correlations between plasma sheet and solar wind based on DSP explorations

By using the data of two spacecraft, TC-1 and ACE (Advanced Composition Explorer), a statistical study on the correlations between plasma sheet and solar wind has been carried out. The results obtained show that the plasma sheet at geocentric distances of about 9~13.4 Re has an apparent driving relationship with the solar wind. It is found that (1) there is a positive correlation between the duskward component of the interplanetary magnetic field (IMF) and the duskward component of the geomagnetic field in the plasma sheet, with a proportionality constant of about 1.09. It indicates that the duskward component of the IMF can effectively penetrate into the near-Earth plasma sheet, and can be amplified by sunward convection in the corresponding region at geocentric distances of about 9~13.4 Re; (2) the increase in the density or the dynamic pressure of the solar wind will generally lead to the increase in the density of the plasma sheet; (3) the ion thermal pressure in the near-Earth plasma sheet is significantly controlled by the dynamic pressure of solar wind; (4) under the northward IMF condition, the ion temperature and ion thermal pressure in the plasma sheet decrease as the solar wind speed increases. This feature indicates that plasmas in the near-Earth plasma sheet can come from the magnetosheath through the LLBL. Northward IMF is one important condition for the transport of the cold plasmas of the magnetosheath into the plasma sheet through the LLBL, and fast solar wind will enhance such a transport process

Multistage Random Growing Small-World Networks with Power-law degree Distribution

In this paper, a simply rule that generates scale-free networks with very large clustering coefficient and very small average distance is presented. These networks are called {\bf Multistage Random Growing Networks}(MRGN) as the adding process of a new node to the network is composed of two stages. The analytic results of power-law exponent $\gamma=3$ and clustering coefficient $C=0.81$ are obtained, which agree with the simulation results approximately. In addition, the average distance of the networks increases logarithmical with the number of the network vertices is proved analytically. Since many real-life networks are both scale-free and small-world networks, MRGN may perform well in mimicking reality.Comment: 3 figures, 4 page

A Cellular Automata Model with Probability Infection and Spatial Dispersion

In this article, we have proposed an epidemic model by using probability cellular automata theory. The essential mathematical features are analyzed with the help of stability theory. We have given an alternative modelling approach for the spatiotemporal system which is more realistic and satisfactory from the practical point of view. A discrete and spatiotemporal approach are shown by using cellular automata theory. It is interesting to note that both size of the endemic equilibrium and density of the individual increase with the increasing of the neighborhood size and infection rate, but the infections decrease with the increasing of the recovery rate. The stability of the system around the positive interior equilibrium have been shown by using suitable Lyapunov function. Finally experimental data simulation for SARS disease in China and a brief discussion conclude the paper