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Sign prediction is a significant research content in signed social networks, so it has attracted increasing attention from the field of online social networks recently. Traditionally, the basic idea of motif-based predictive method is to calculate the motif number on the predicted edge (i.e., the single edge-dependent motif based method), and then use a machine learning predictor for sign prediction. Although this intuition-based method can achieve great performance for sign prediction, up to now its reasonability has not been proved theoretically. Furthermore, the method of counting the number of edge-dependent motif can not distinguish the distinct role of each node on the neighborhood of the predicted edge. In this study, firstly we propose a Single Motif Naive Bayes (SMNB) model for sign prediction, which can not only explain why the single edge-dependent motif based method is efficient, but also quantify the role of each neighbor node (for 3-node predictors) or neighbor edge (for 4-node predictors) which is connected by the predicted edge for the task of sign prediction. Then, we extend SMNB by merging two types of motifs, and propose a Two Motif Naive Bayes (TMNB) model. Experimental results on real-world networks indicate that the proposed algorithms outperform the state-of-the-art approaches. Finally, we explore the intrinsic relationship among different motifs according to the matrix of Maximal Information Coefficient (MIC). Our research not only extends the traditional motif theory by proving the rationality of the edge-dependent motif based method and distinguishing a node (or an edge) contribution for sign prediction, but also is helpful to further understand the evolution mechanism of signed social networks based on the correlation among different motifs. [ABSTRACT FROM AUTHOR]

In order to calculate the space radiation effects precisely and instantly in a spacecraft, a new Space Environment and Radiation Effect Analysis Tool (SEREAT) is developed based on Open CASCADE and Geant4. The sector analysis module of SEREAT has been developed to calculate the spacecraft shielding at any point by integrating the ray tracing method. This study provides a convenient tool to convert the computer-aided design (CAD) geometry models into the GDML (The Geometry Description Markup Language) models for Geant4 applications. Using the distribution of the shielding thickness produced by the sector analysis module, SEREAT can calculate and analyze the radiation effects, such as the particle flux behind the shielding, total ionization dose, single event upsets, etc. Total ionization dose at a geostationary orbit is calculated by SEREAT, and the result shows that SEREAT can meet the needs of radiation effect analysis in a complex spacecraft. [ABSTRACT FROM AUTHOR]

The article focuses on the view of Brazilian scholar Oliver Stuenkel of Getulio Vargas Foundation in Sao Paulo and author of the book "The BRICS and the Future of Global Order," on the importance of BRICS on the global order. Stuenkel discusses topics including the effots of BRICS to manage transition of the global order, its important role in defending globalization, and the challenges facing BRICS economies since the 2008 global financial crisis.

Several letters to the editor are presented including one from a reader that shares his condolences to the families affected by the earthquake that struck China's Yunnan province in August 2014, another commenting on the environmental problems caused by pollution in many urban centers in China and around the world, and another expressing hopes that the new Education for Sustainable Development (ESD) model will result in positive reforms to the Chinese educational system.

Drag coefficient sequence Cd is obtained by solving Tiangong 1 continuous 55 days (d) GPS orbit data with different arc length. The same period solar radiation flux ƒ10.7 and geomagnetic index ap, Ap sequences are high and low frequency multi-wavelet decomposed. Statistical analysis results of the multilayer sliding correlation between space environmental parameters and decomposition of Cd show that lag correlation between the satellite drag coefficient sequence after wavelet decomposition and the corresponding level of ƒ10.7, Ap sequence is good. It is also verified that the Cd prediction is feasible. Prediction residuals of Cd with different regression models and different sample lengths are analyzed. The results show that the case setting sample length of 20 days and selecting ƒ10.7regression model is best. It is also show that NRLMSIS-00 model's response in the region of 350 km (Tiangong's altitude) and low-middle latitude (Tiangong's inclination) is excessive during the ascent phase of geomagnetic activity Ap and is inadequate during decline phase. Additionally, for the low-frequency decomposition sequence NRLMSIS-00 model's response is appropriate during the ascent rising phase of ƒ10.7. For the high frequency decomposition sequence, NRLMSIS-00 model's response is small-scale inadequate during the ascent phase of ƒ10.7 and is excessive during the decline phase of ƒ10.7. Finally, the summary of potential use and outlook are listed; this method has an important reference value for improving the spacecraft orbit prediction accuracy. [ABSTRACT FROM AUTHOR]

Abstract: Current studies on grey systems are mainly focused on known and deterministic information, rather than uncertain one. Different from previous schemes, this paper proposes an innovative prediction model based on grey number information, which extends its application dealing with uncertain information. By exploiting the geometric features of grey numbers on a two-dimensional surface, all grey numbers can be converted into real numbers without losing any information by means of proposed algorithms. Then a prediction model is established based on those real number sequences. In addition, a general case simulation is carried out to verify the effectiveness and practicability of the proposed model. [Copyright &y& Elsevier]

Atmospheric drag coefficient plays an important role in low Earth satellites orbit determination and prediction. Using precise ephemeris of CHAMP satellite in different period, several drag coefficient values are obtained during the orbit determination process, and these values are applied to the orbit prediction. Specially, all the experiments were done in quiet geomagnetic conditions. By comparing prediction position to precise ephemeris, optimal drag coefficient for orbit forecasting is selected. The relations among optimal drag coefficient, geomagnetic indices and trace orientation error are studied. Subsequently, according to linear regression analysis a drag coefficient correction method is proposed. For the purpose of medium-term orbit prediction with short-term observation, drag coefficient error is reduced by using this method. In addition, the method is applied to verify its validity in CHAMP and Tiangong-1 orbit determination and prediction for different periods. The results show that orbit prediction accuracy is improved by more than 20%. [ABSTRACT FROM AUTHOR]

Hubei Province is one of the endemic regions with severe schistosomiasis in China. To eliminate schistosomiasis in lake and marshland regions, this study detected hotspots of schistosomiasis cases both spatially and spatiotemporally on the basis of spatial autocorrelation; clustering and outlier, purely spatial and spatiotemporal cluster analyses at the village level from 2013 to 2017 in Hubei Province. The number of cases confirmed positive by an immunodiagnostic test and etiological diagnosis and advanced schistosomiasis cases dramatically declined during the study period. Significant global spatial autocorrelation of schistosomiasis patients was found at the village level in the whole province in 5 years. Clustering and outlier analysis showed that most HH villages were mainly concentrated along the Yangtze River, especially in Jianghan Plain. Spatial and spatiotemporal cluster analyses showed that significant clusters of the schistosomiasis cases were detected at the village level. In general, space and spatiotemporal clustering of schistosomiasis cases at the village level demonstrated a downward trend from 2013 from 2017 in Hubei Province. High-risk regions included Jianghan Plain along the middle reach of Yangtze River and Yangxin County in the lower reaches of the Yangtze River in Hubei Province. To eliminate schistosomiasis, precise control and management of schistosomiasis cases should be strictly implemented. Moreover, comprehensive prevention and control measures should be continuously strengthened in these regions. [ABSTRACT FROM AUTHOR]