Emergence of hysteresis loop in social contagions on complex networks

Understanding the spreading mechanisms of social contagions in complex network systems has attracted much attention in the physics community. Here we propose a generalized threshold model to describe social contagions. Using extensive numerical simulations and theoretical analyses, we find that a hysteresis loop emerges in the system. Specifically, the steady state of the system is sensitive to the initial conditions of the dynamics of the system. In the steady state, the adoption size increases discontinuously with the transmission probability of information about social contagions, and trial size exhibits a non-monotonic pattern, i.e., it first increases discontinuously then decreases continuously. Finally we study social contagions on heterogeneous networks and find that network topology does not qualitatively affect our results.This work was funded in part by the National Key Research and Development Program (Grant No. 2016YFB0800602), the National Natural Science the Foundation of China (Grant Nos 61472045,61573067), and the China Scholarship Council. (2016YFB0800602 - National Key Research and Development Program; 61472045 - National Natural Science the Foundation of China; 61573067 - National Natural Science the Foundation of China; China Scholarship Council)Published versio

R&D subsidies, executive background and innovation of Chinese listed companies

Enterprises are the mainstay of national innovation. The improvement of enterprise productivity and the sustained and rapid development of the economy are inseparable from the research and development (R&D) and innovation of enterprises. Most previous research studies have focused on the economic system and scale of enterprises to study the impact of government–enterprise relations on corporate innovation. This article takes the heterogeneity background characteristics of executives as the starting point, discusses the internal mechanism of R&D subsidies, the background characteristics of corporate executives and the innovative behaviour of Chinese listed companies, and draws two conclusions: (1) The current Chinese government’s innovation subsidy allocation process still has some preferences, such as the company’s executives have more R&D subsidies for listed companies with a background in government, technical background and high academic background; and (2) Although the three types of background characteristics of executives are beneficial to the company’s R&D subsidies, the government background of executives has not significantly promoted the innovation of listed companies, while the background of technology R&D and high academic background of executives have significantly promoted corporate innovation

Disparate Locations of the 52- and 60-kDa Ro/SS-A Antigens in Cultured Human Keratinocytes

Anti-52- and anti-60-kDa Ro/SS-A (Ro) autoantibodies are produced by most patients with subacute cutaneous lupus erythematosus and neonatal lupus erythematosus and are thought to be pathogenic in these two disorders. To learn more about the epidermal antigens targeted by Ro autoantibodies, a panel of anti-52 and anti-60-kDa Ro antibodies was purified from human autoimmune sera and rabbit antisera and then used to: (i) determine the expression and location of the Ro antigens in human keratinocytes; (ii) clarify discrepancies in previous localization studies; and (iii) verify the existence of Ro autoantibodies that cross-react with the 52- and 60-kDa Ro antigens, as previously reported. By immunoblot analysis these antibodies demonstrate that 52- and 60-kDa Ro proteins are expressed in normal human skin and cultured keratinocytes. By indirect immunofluorescence studies with cultured human cells, the anti-52-kDa Ro antibodies produce fine granular cytoplasmic fluorescence and less intense nuclear fluorescence, with apparent nucleolar sparing. The anti-60-kDa Ro autoantibodies produce weak cytoplasmic fluorescence and intense coarse granular nuclear fluorescence with apparent nucleolar sparing. We found distinct differences in the intracellular localization of the 52- and 60-kDa Ro autoantigens. This difference suggests that the 52-and 60-kDa Ro antigens may have independent cellular functions. Finding 60-kDa Ro antigen predominantly in the nucleus challenges the notion that the majority of the intracellular 60-kDa Ro antigen is complexed with the cytoplasmic hY RNA. Additionally, our failure to find a cross-reactive epitope on these two proteins indicates that the 52-kDa Ro antigen is probably a true immunogen and not merely a protein that cross-reacts with anti-60-kDa Ro autoantibodies, as others have suggested

Internal Relationship and Impact Path between Innovation and Entrepreneurship: Based on China’s High-Tech Industry

Innovation is the source of entrepreneurship, entrepreneurship is the value embodiment of innovation, and the two are inseparable. At a time when dividends such as population, reform and opening up, and resources and environment are gradually disappearing, China urgently needs to accelerate scientific and technological innovation to support economic development, incubate scientific and technological enterprises, and ease labor market pressure with technological progress and efficiency improvement. This chapter focuses on China’s high-tech industry, which is dominated by scientific and technological innovation. Starting from the overall, local, and regional perspectives, it organically integrates the traditional DEA, similar SFA, Malmquist index decomposition, chain multiple intermediary effect, and other multilevel research through cross-level analysis. Based on the research foundation of innovation efficiency after eliminating environmental and random factors, it deeply discusses the action path and impact mechanism of “double innovation” and provides targeted policy recommendations for the government and relevant local departments. The research confirms that the total effect of innovation on entrepreneurship is always positive, i.e., promoting “people-to-people innovation” is conducive to promoting “mass entrepreneurship” whether it is analyzed from the whole or from the part

Nonlinear analysis of stress and strain for a clay core rock-fill dam with FEM

AbstractBased on the Duncan-Chang hyperbolic nonlinear elastic material model, this paper carried out the stress and strain numerical analysis of a clay core rock-fill dam, which is a certain building reservoir dam in Yunnan province. By loading on each layer step by step and with the static nonlinear finite element simulation of deposition, it obtained the results of the stress and deformation of the clay core rock-fill dam. The calculation showed that the great difference in deformation modulus causes non-smooth variations in deformation, stress and strain between the transition area and the rock-debris fill. From the analysis it can be seen that the present design of the dam is reasonable since no any abnormal stresses and deformations occurred in the dam. Moreover, this also indicated a feasible and provided a valuable evident for the optimization of cross-section zones in a project

Virtual sensing for gearbox condition monitoring based on extreme learning machine

Gearbox, as a critical component to convert speed and torque to maintain machinery normal operation in the industrial processes, has been received and still needs considerable attentions to ensure its reliable operation. Direct sensing and indirect sensing techniques are widely used for gearbox condition monitoring and fault diagnosis, but both have Pros and Cons. To bridge their gaps and enhance the performance of early fault diagnosis, this paper presents a new virtual sensing technique based on extreme learning machine (ELM) for gearbox degradation status estimation. By fusing the features extracted from indirect sensing measurements (e.g. in-process vibration measurement), ELM based virtual sensing model could infer the gearbox condition which was usually directly indicated by the direct sensing measurements (e.g. offline oil debris mass (ODM)). Different state-of-the-art dimension reduction techniques have been investigated for feature selection and fusion including principal component analysis (PCA) and its kernel version, locality preserving projection (LPP) method. The effectiveness of the presented virtual sensing technique is experimentally validated by the sensing measurements from a spiral bevel gear test rig. The experimental results show that the estimated gearbox condition by the virtual sensing model based on ELM and kernel PCA well follows the trend of truth data and presents the better performance over the support vector regression based virtual sensing scheme