Broadband lightcurve characteristics of GRBs 980425 and 060218 and comparison with long-lag, wide-pulse GRBs

It has been recently argued that low-luminosity gamma-ray bursts (LL-GRBs) are likely a unique GRB population. Here, we present systematic analysis of the lightcurve characteristics from X-ray to gamma-ray energy bands for the two prototypical LL-GRBs 980425 and 060218. It is found that both the pulse width ($w$) and the ratio of the rising width to the decaying width ($r/d$) of theses two bursts are energy-dependent over a broad energy band. There exists a significant trend that the pulses tend to be narrower and more symmetry with respect to the higher energy bands for the two events. Both the X-rays and the gamma-rays follow the same $w - E$ and $r/d - E$ relations. These facts may indicate that the X-ray emission tracks the gamma-ray emission and both are likely to be originated from the same physical mechanism. Their light curves show significant spectral lags. We calculate the three types of lags with the pulse peaking time ($t_{peak}$), the pulse centroid time ($t_{cen}$), and the cross-correlation function (CCF). The derived $t_{peak}$ and $t_{cen}$ are a power-law function of energy. The lag calculated by CCF is strongly correlated with that derived from $t_{peak}$. But the lag derived from $t_{cen}$ is less correlated with that derived from $t_{peak}$ and CCF. The energy dependence of the lags is shallower at higher energy bands. These characteristics are well consistent with that observed in typical long-lag, wide-pulse GRBs, suggesting that GRBs 980425 and 060218 may share the similar radiation physics with them.Comment: 26 pages, 10 figures, 3 tables, accepted for publication in Ap

Survey of grid resource monitoring and prediction strategies.

This literature focuses on grid resource monitoring and prediction, representative monitoring and prediction systems are analyzed and evaluated, then monitoring and prediction strategies for grid resources are summarized and discussed, recommendations are also given for building monitoring sensors and prediction models. During problem definition, one-step-ahead prediction is extended to multi-step-ahead prediction, which is then modeled with computational intelligence algorithms such as neural network and support vector regression. Numerical simulations are performed on benchmark data sets, while comparative results on accuracy and efficiency indicate that support vector regression models achieve superior performance. Our efforts can be utilized as direction for building online monitoring and prediction system for grid resources

Efficient identity-based broadcast encryption without random oracles.

We propose a new efficient identity-based broadcast encryption scheme without random oracles and prove that it achieves selective identity, chosen plaintext security. Our scheme is constructed based on bilinear Diffie-Hellman inversion assumption and it is a good efficient hybrid encryption scheme, which achieves O(1)-size ciphertexts, public parameters and constant size private keys. In our scheme, either ciphertexts or public parameters has no relation with the number of receivers, moreover, both the encryption and decryption only require one pairing computation. Compared with other identity-based broadcast encryption schemes, our scheme has comparable properties, but with a better efficiency

Solving job shop scheduling problem using genetic algorithm with penalty function

This paper presents a genetic algorithm with a penalty function for the job shop scheduling problem. In the context of proposed algorithm, a clonal selection based hyper mutation and a life span extended strategy is designed. During the search process, an adaptive penalty function is designed so that the algorithm can search in both feasible and infeasible regions of the solution space. Simulated experiments were conducted on 23 benchmark instances taken from the OR-library. The results show the effectiveness of the proposed algorithm

Bridgeness: A Local Index on Edge Significance in Maintaining Global Connectivity

Edges in a network can be divided into two kinds according to their different roles: some enhance the locality like the ones inside a cluster while others contribute to the global connectivity like the ones connecting two clusters. A recent study by Onnela et al uncovered the weak ties effects in mobile communication. In this article, we provide complementary results on document networks, that is, the edges connecting less similar nodes in content are more significant in maintaining the global connectivity. We propose an index named bridgeness to quantify the edge significance in maintaining connectivity, which only depends on local information of network topology. We compare the bridgeness with content similarity and some other structural indices according to an edge percolation process. Experimental results on document networks show that the bridgeness outperforms content similarity in characterizing the edge significance. Furthermore, extensive numerical results on disparate networks indicate that the bridgeness is also better than some well-known indices on edge significance, including the Jaccard coefficient, degree product and betweenness centrality.Comment: 10 pages, 4 figures, 1 tabl

Effects of 22 years of re-vegetation on soil quality in the semi-arid area of the Loess Plateau

Re-vegetation is an important practice for eco-environmental rebuilding of degraded environments. Accordingly, re-vegetation has been widely used to reduce erosion and protect soils against degradation in the Loess Plateau. However, little research has been conducted to study the effects oflong-term re-vegetation on soil properties, which is essential to reveal corresponding changes in soil quality. Therefore, this study was conducted to evaluate the influence of 22 years of re-vegetation on soil quality in a semi-arid area. Soil samples were collected from a bare slope, a re-vegetated northern slope and a re-vegetated southern slope. The soil properties were then determined and the soil quality indices were calculated. The results showed that long-term re-vegetation significantly improved soil properties in the Loess Plateau, but that the effects of re-vegetation varied with slope aspect, slope position and soil depth. The greatest improvement in soil properties was observed in topsoil, onnorthern slopes and in lower positions of the slopes. Significant correlations were observed among soil chemical properties (including organic matter and total N contents) and soil enzymatic activities. Totalnitrogen and organic matter content, activities of urease, invertase and alkaline-phosphatase could all be combined into one factor to indicate soil quality and characterize the distribution of soil properties along slopes. The resulting soil quality index (SQI) can effectively reflect the changes in soil quality in response to 22 years of re-vegetation in the Loess Plateau