A study of the spreading scheme for viral marketing based on a complex network model

Buzzword-based viral marketing, known also as digital word-of-mouth marketing, is a marketing mode attached to some carriers on the Internet, which can rapidly copy marketing information at a low cost. Viral marketing actually uses a pre-existing social network where, however, the scale of the pre-existing network is believed to be so large and so random, so that its theoretical analysis is intractable and unmanageable. There are very few reports in the literature on how to design a spreading scheme for viral marketing on real social networks according to the traditional marketing theory or the relatively new network marketing theory. Complex network theory provides a new model for the study of large-scale complex systems, using the latest developments of graph theory and computing techniques. From this perspective, the present paper extends the complex network theory and modeling into the research of general viral marketing and develops a specific spreading scheme for viral marking and an approach to design the scheme based on a real complex network on the QQ instant messaging system. This approach is shown to be rather universal and can be further extended to the design of various spreading schemes for viral marketing based on different instant messaging systems.     

Experiment and simulation study on construction of a three-dimensional network model

The construction of a network model is one of the key techniques in organic combination of microscopic flow experiment and simulation. The construction method of a three-dimensional network model is presented on the basis of CT scanning images in this paper. A series of CT slice images describing microscopic pore structure and fluid distribution of actual rock is obtained with the help of the industrial microfocus CT system. Based on the extraction of pore space skeleton, pore and throat information, the corresponding network model is established, and the conversion from three-dimensional CT image information to pore-throat size distribution and topological information is also achieved. The feature of this method lies in the fact that complicated pore space of rock may be characterized by pores and throats with a simple shape while keeping the geometry and flow characteristics. It is indicated that the calculated results of porosity, permeability, relative permeability curve and microscopic remaining oil distribution match very well the experimental results of water flooding and polymer flooding. This network model may fairly well characterize the rock microscopic pore-throat size and topological characteristics. Supported by the National Natural Science Foundation of China (Grant Nos. 10302021 and 10772200)     

Small-time scale network traffic prediction based on a local support vector machine regression model

In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.     

The co-evolution of cultures,social network communities,and agent locations in an extension of Axelrod’s model of cultural dissemination

We introduce a variant of the Axelrod model of cultural dissemination in which agents change their physical locations, social links, and cultures. Numerical simulations are used to investigate the evolution of social network communities and the cultural diversity within and between these communities. An analysis of the simulation results shows that an initial peak in the cultural diversity within network communities is evident before agents segregate into a final configuration of culturally homogeneous communities. Larger long-range interaction probabilities facilitate the initial emergence of culturally diverse network communities, which leads to a more pronounced initial peak in cultural diversity within communities. At equilibrium, the number of communities, and hence cultures, increases when the initial cultural diversity increases. However, the number of communities decreases when the lattice size or population density increases. A phase transition between two regimes of initial cultural diversity is evident. For initial diversities below a critical value, a single network community and culture emerges that dominates the population. For initial diversities above the critical value, multiple culturally homogeneous communities emerge. The critical value of initial diversity at which this transition occurs increases with increasing lattice size and population density and generally with increasing absolute population size. We conclude that larger initial diversities promote cultural heterogenization, while larger lattice sizes, population densities, and in fact absolute population sizes promote homogenization.     

The 3D characteristics of post‐traumatic syringomyelia in a rat model: a propagation‐based synchrotron radiation microtomography study

Many published literature sources have described the histopathological characteristics of post‐traumatic syringomyelia (PTS). However, three‐dimensional (3D) visualization studies of PTS have been limited due to the lack of reliable 3D imaging techniques. In this study, the imaging efficiency of propagation‐based synchrotron radiation microtomography (PB‐SRµCT) was determined to detect the 3D morphology of the cavity and surrounding microvasculature network in a rat model of PTS. The rat model of PTS was established using the infinite horizon impactor to produce spinal cord injury (SCI), followed by a subarachnoid injection of kaolin to produce arachnoiditis. PB‐SRµCT imaging and histological examination, as well as fluorescence staining, were conducted on the animals at the tenth week after SCI. The 3D morphology of the cystic cavity was vividly visualized using PB‐SRµCT imaging. The quantitative parameters analyzed by PB‐SRµCT, including the lesion and spared spinal cord tissue area, the minimum and maximum diameters in the cystic cavity, and cavity volume, were largely consistent with the results of the histological assessment. Moreover, the 3D morphology of the cavity and surrounding angioarchitecture could be simultaneously detected on the PB‐SRµCT images. This study demonstrated that high‐resolution PB‐SRµCT could be used for the 3D visualization of trauma‐induced spinal cord cavities and provides valuable quantitative data for cavity characterization. PB‐SRµCT could be used as a reliable imaging technique and offers a novel platform for tracking cavity formation and morphological changes in an experimental animal model of PTS.     

Analysis of a dynamic model for subfilter scalar dissipation rate in large eddy simulation based on the subfilter scalar variance transport equation

Accurate prediction of non-premixed turbulent combustion using large eddy simulation (LES) requires detailed modelling of the mixing between fuel and oxidizer that occurs at scales smaller than the LES filterwidth. The small-scale mixing process can be quantitatively characterized by two related variables, the subfilter scalar variance and the subfilter scalar dissipation rate. A recently proposed alternative dynamic modelling procedure for the subfilter scale dissipation rate, designed for use with transport equation based models for subfilter scalar variance, is analysed in this work. This new dynamic non-equilibrium modelling approach produces a nonlinear interaction between variance and dissipation rate predictions that makes it difficult to isolate the performance of any single modelling component in a conventional LES simulation. To gain a better understanding of the new model, a three-part study is undertaken here. The first part of the study uses a priori analysis to examine some novel aspects of the model’s computation and guide its practical implementation. In the second part of the study, detailed a posteriori analysis of the model is performed. This analysis suggests that the dynamic estimate of the dissipation rate model coefficient helps to compensate for over-prediction of variance production rates and improves the accuracy of variance prediction. However, improved modelling of the variance production term, which in turn depends on the accuracy of models for the subfilter scalar flux, is necessary to allow both the scalar variance and dissipation rate to be predicted accurately. Therefore, the third part of the study examines the effect of the scalar flux model on the predictions of the dynamic non-equilibrium model. Use of a mixed model for the fluxes, rather than a gradient-diffusion-only model, is found to improve variance predictions in some cases.     

The quest for a better system for evaluating pi‐electron substituent constant: a comparison of benzoic,acrylic and tria‐, penta‐, heptafulvene‐based carboxylic acids. A computational study

Carboxylic acids based on exo‐substituted tria‐, penta‐, heptafulvenes and ethylene (acrylic acids) were examined in order to determine if they are more sensitive to the substituent effect than benzoic acid – the system originally employed by Hammett. In order to accomplish this task, all possible structural isomers of benzoic acid, tria‐, penta‐ and heptafulvene‐based carboxylic acids, acrylic and methacrylic acids substituted by 13 substiuents (BH₂, CHO, CN, COCN, NO₂, CF₃, Me, Cl, F, OH, OMe, NH₂ and NMe₂) were optimized at the B3LYP/6‐311++G(d,p) level of theory, and Gibbs free energies of carboxylic group dissociation (ΔG_dis) were calculated. These energies were subsequently intercorrelated, and from the slopes of linear regressions, it was estimated which system is associated with greatest changes of ΔG_dis due to substitution and thus is most sensitive to the substituent effect. It was found that all fulvene‐based carboxylic acids have greater range of ΔG_dis change than benzoic acid, but the largest range of change was observed in the case of acrylic and methacrylic acids. The acrylic acid as the most sensitive system to substitution could replace benzoic acid for an improved version of substituent constant used to measure pi‐electron substituent effect. Copyright © 2013 John Wiley & Sons, Ltd.