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The El Nino-Southern Oscillation (ENSO) is one of the most important phenomena in climate. By studying the fluctuations of surface air temperature within one year between 1979-01-01 and 2016-12-31 of the region (30S-30N, 0E-360E) with eigen-decomposition, we find that the temperature fluctuations are dominated by the two principal modes whose temporal evolutions respond significantly to the ENSO variability. According to introduce a micro-correlation, we find that the coupling between the first principal mode and the temperature fluctuations in the El Nino region could result in different ENSO phases. Without this coupling, the El Nino region is in a normal phase. With the strong coupling between the El Nino region and the Northern Hemisphere, an El Nino event will appear with a high probability. Then this coupling changes to be strong between the El Nino region and the Southern Hemisphere accounting for the fast decay of El Nino after boreal winter, even leading to a La Nina event. Moreover, the coupling between the El Nino region and the second principal mode is found to be strong in normal or La Nina phases in response to the normal or strong Walker Circulations. We conjecture that the temporal evolutions of these couplings for the first and second principal modes are controlled by the meridional and zonal ocean-atmospheric circulations respectively.

A prominent feature of earthquakes is their empirical laws including memory (clustering) in time and space. Several earthquake forecasting models, like the EpidemicType Aftershock Sequence (ETAS) model, were developed based on earthquake empirical laws. Yet, a recent study showed that the ETAS model fails in reproducing significant long-term memory characteristics found in real earthquake catalogs. Here we modify and generalize the ETAS model to include short- and long-term triggering mechanisms, to account for the short- and long-time memory (exponents) recently discovered in the data. Our generalized ETAS model reproduces accurately the short- and long-term/distance memory observed in the Italian and South California earthquake catalogs. The revised ETAS model is also found to significantly improve earthquake forecasting.

We propose the finite-size scaling of correlation function in a finite system near its critical point. At a distance ${\bf r}$ in the finite system with size $L$, the correlation function can be written as the product of $|{\bf r}|^{-(d-2+\eta)}$ and its finite-size scaling function of variables ${\bf r}/L$ and $tL^{1/\nu}$, where $t=(T-T_c)/T_c$. The directional dependence of correlation function is nonnegligible only when $|{\bf r}|$ becomes compariable with $L$. This finite-size scaling of correlation function has been confirmed by correlation functions of the Ising model and the bond percolation in two-diemnional lattices, which are calculated by Monte Carlo simulation. We can use the finite-size scaling of correlation function to determine the critical point and the critical exponent $\eta$., Comment: 7 pages, 13 figures

Air pollution has become a major issue and caused widespread environmental and health problems. Aerosols or particulate matters are an important component of the atmosphere and can transport under complex meteorological conditions. Based on the data of $PM_{2.5}$ observations, we develop a network approach to study and quantify their spreading and diffusion patterns. We calculate cross-correlation functions of time lag between sites within different season. The probability distribution of correlation changes with season. It is found that the probability distributions in four seasons can be scaled into one scaling function with averages and standard deviations of correlation. This seasonal scaling behavior indicates there is the same mechanism behind correlations of $PM_{2.5}$ concentration in different seasons. Further, from weighted and directional degrees of complex network, different properties of $PM_{2.5}$ concentration are studied. The weighted degrees reveal the strongest correlations of $PM_{2.5}$ concentration in winter and in the North China plain. These directional degrees show net influences of $PM_{2.5}$ along Gobi and inner Mongolia, the North China plain, Central China, and Yangtze River Delta., Comment: 7 pages, 11 figures

For vertical velocity field $v_{\rm z} (r,z;R)$ of granular flow through an aperture of radius $R$, we propose a size scaling form $v_{\rm z}(r,z;R)=v_{\rm z} (0,0;R)f (r/R_{\rm r}, z/R_{\rm z})$ in the region above the aperture. The length scales $R_{\rm r}=R- 0.5 d$ and $R_{\rm z}=R+k_2 d$, where $k_2$ is a parameter to be determined and $d$ is the diameter of granule. The effective acceleration, which is derived from $v_{\rm z}$, follows also a size scaling form $a_{\rm eff} = v_{\rm z}^2(0,0;R)R_{\rm z}^{-1} \theta (r/R_{\rm r}, z/R_{\rm z})$. For granular flow under gravity $g$, there is a boundary condition $a_{\rm eff} (0,0;R)=-g$ which gives rise to $v_{\rm z} (0,0;R)= \sqrt{ \lambda g R_{\rm z}}$ with $\lambda=-1/\theta (0,0)$. Using the size scaling form of vertical velocity field and its boundary condition, we can obtain the flow rate $W =C_2 \rho \sqrt{g } R_{\rm r}^{D-1} R_{\rm z}^{1/2} $, which agrees with the Beverloo law when $R \gg d$. The vertical velocity fields $v_z (r,z;R)$ in three-dimensional (3D) and two-dimensional (2D) hoppers have been simulated using the discrete element method (DEM) and GPU program. Simulation data confirm the size scaling form of $v_{\rm z} (r,z;R)$ and the $R$-dependence of $v_{\rm z} (0,0;R)$., Comment: 5 pages, 8 figures

Self-questioning update rules is the selected process of the optimal strategy of the individuals by comparing the payoff from various alternative strategies. In this paper, a self-questioning dynamical evolutionary game with altruistic or spiteful preferences via weighted sums of own and opponents payoffs is studied. In order to obtain the influence of long-range connections and degree heterogeneity on evolutionary game model, we study three kinds of spatial structure: the two-dimensional lattice, homogeneous small-world networks (only the introduction of long-range connections) and heterogenous small-world networks (both long-range connections and degree heterogeneity). Through the Ising model theory and Monte Carlo simulation the following conclusions are obtained: long-range connections make the individuals perplex in strategic choice which is similar to the state of frustration in spin glass; the degree heterogeneity makes the different individual has the different field (the more neighbours, the larger of field); when the field is positive, long-range connections promote cooperation, but the heterogeneity of degree inhibits the production of cooperation.

A new voltage programmed pixel circuit with top emission design for active-matrix organic light-emitting diode (AMOLED) displays is presented and verified by HSPICE simulations. The proposed pixel circuit consists of five poly-Si TFTs, and can effectively compensate for the threshold voltage variation of the driving TFT. Meanwhile, the proposed pixel circuit offers an AC driving mode for the OLED by the two adjacent pulse voltage sources, which can suppress the degradation of the OLED. Moreover, a high contrast ratio can be achieved by the proposed pixel circuit since the OLED does not emit any light except for the emission period.

This work presents a new voltage programmed pixel circuit for an active-matrix organic light-emitting diode (AMOLED) display. The proposed pixel circuit consists of six low temperature polycrystalline silicon thin-film transistors (LTPS TFTs), one storage capacitor, and one OLED, and is verified by simulation work using HSPICE software. Besides effectively compensating for the threshold voltage variation of the driving TFT and OLED, the proposed pixel circuit offers an AC driving mode for the OLED, which can suppress the degradation of the OLED. Moreover, a high contrast ratio can be achieved by the proposed pixel circuit since the OLED does not emit any light except for the emission period.

Earthquakes involve complex processes that span a wide range of spatial and temporal scales. The limited earthquake predictability is partly due to the erratic nature of earthquakes and partly due to the lack of understanding of the underlying mechanisms of earthquakes. To improve our understanding and possibly the predictability of earthquakes, we develop here a lagged conditional probability method to study the spatial and temporal long-term memory of interevent earthquakes above a certain magnitude. We find, in real data from different locations, that the lagged conditional probabilities show long-term memory for both the interevent times and interevent distances and that the memory functions obey scaling and decay slowly with time, while, at a characteristic time (crossover), the decay rate becomes faster. We also show that the epidemic-type aftershock sequence model, which is often used to forecast earthquake events, fails in reproducing the scaling function of real catalogs as well as the crossover in the scaling function. Our results suggest that aftershock rate is a critical factor to control the long-term memory.