Stable development of strategic emerging industries promotes its industrial transformation and upgrading, which has affected the development of not only the society and the economy but also other fields, thereby having a great impact on employment. To measure the impact of structural change of strategic emerging industries on employment in China, this paper constructs a regression equation, in which the employment of strategic emerging industries is the dependent variable, while the change direction of strategic emerging industry structure, the employment elasticity of strategic emerging industries and the change speed of industrial structure are the independent variables. The research results are as follows: (i) The change direction of strategic emerging industries is positively correlated with employment. (ii) The employment elasticity of strategic emerging industries is on the rise, and is positively correlated with employment. (iii) The speed of change of strategic emerging industries is unstable, and is negatively correlated with employment. As a result, the structural change in strategic emerging industries has played a role in promoting employment. The government should recognize the impact of structural changes in strategic emerging industries on China’s employment. By implementing the existing strategic emerging industry policies and improving the external environment for the development of strategic emerging industries, the strategic emerging industries will play the role of “innovation, growth and leadership” in economic and social development.

The purpose of this research is to explain the financing dilemma of China's strategic emerging industries and improve their financing efficiency, seize the commanding heights of economic science and technology to provide theoretical support.

海洋牧场是我国海洋经济发展的重要组成部分，本文基于协同创新网络视角探索海洋牧场的技术创新策略，包括明晰海洋牧场技术创新协同网络中各类行动者的职能和角色，构建海洋牧场技术创新协同网络，运用案例研究法解析协同创新网络的运行机制，依据行动者网络理论分析协同创新网络的演化形态和演化特征，最后得出相关结论。本文的研究观点可为今后海洋牧场的重大技术突破和研发攻关提供可借鉴的思路和依据，并有助于推动现代化海洋牧场建设的技术供给，对我国海洋牧场的健康发展具有重要意义。

Marine ranching is an important part of China's marine economic development. This paper explores the technological innovation strategy of marine ranching based on the perspective of collaborative innovation network. From three dimensions of cooperation projects, patent applications and published papers, the paper selects the relevant data of China's marine ranching technology innovation collaboration from 2012 to 2021. First of all, based on the analysis of the existing collaborative network, the actor network theory is used to build the marine ranching technology innovation collaborative network, and the functions and roles of various actors in the marine ranching technology innovation collaborative network are analyzed; Secondly, the multi case study method is used to clarify the operation mechanism of the collaborative innovation network. The government policy promotion mechanism is the driving force for network expansion, the trust cooperation mechanism is the basis for the stable operation of the network, the interactive feedback mechanism is the way for the high-quality operation of the network, and the organization coordination mechanism is the guarantee for the stable operation of the network; Then, the UCINET software is used to analyze the data, calculate the network density, average path length, and the core edge structure evolution shape of the network centrality at each stage of the evolution of China's marine ranching technology collaborative innovation network, and make corresponding analysis. Using the UCINET software plug-in NETDRAW, the network evolution map of the five stages of China's marine ranching technology collaborative innovation network was drawn, and the characteristics of network evolution and the evolution of the relationship between actors were analyzed. Finally, the research conclusions and views of the paper are drawn.The study found that the overall number of technological innovation in the field of marine ranching is not large, and the main innovation subjects are mainly scientific research institutes, universities and high-tech enterprises. Take patent application as an example. At present, the research and development of a single institution is the main form, and the number of cooperative innovations is relatively low. The cooperation mode is mainly in the form of scientific research institutes universities and scientific research institutes scientific research institutes. Among the actors in the marine ranching technology innovation collaboration network, the government and leading enterprises are the core actors of the network, and universities, research institutes and technology suppliers are the indispensable main actors. Small and medium-sized enterprises in marine ranching can actively or passively join the network. In addition, various service institutions, enterprises and customers related to marine products, marine industry associations and public welfare organizations, media, etc. are common actors in the marine ranching technology innovation collaboration network. At this stage, the marine ranching technology innovation collaboration network is still in a period of rapid development and turbulence. Collaborative innovation has not been separated from the primary mode of government industry university research cooperation, and science and technology intermediaries, customers, industry associations, etc. are less involved. But on the whole, the number of network innovation subjects is still increasing, the network structure is becoming increasingly complex, the cooperation path within the network is becoming longer, and the cooperation accumulation of innovation subjects is declining. The current collaborative innovation network is low density.The research viewpoints in this paper can provide referential ideas and basis for major technological breakthroughs and research and development of marine ranching in the future, and help promote the technology supply of modern marine ranching construction, which is of great significance for the healthy development of marine ranching in China.

Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

Curved exponential family models are a useful generalization of exponential random graph models (ERGMs). In particular, models involving the alternating k-star, alternating k-triangle, and alternating k-twopath statistics of Snijders et al (2006) may be viewed as curved exponential family models. This article unifies recent material in the literature regarding curved exponential family models for networks in general and models involving these alternating statistics in particular. It also discusses the intuition behind rewriting the three alternating statistics in terms of the degree distribution and the recently introduced shared partner distributions. This intuition suggests a redefinition of the alternating k-star statistic. Finally, this article demonstrates the use of the statnet package in R for fitting models of this sort, comparing new results on an oft-studied network dataset with results found in the literature.

［目的/意义］为发掘影响美国科研协作的各个因素，提出各维度邻近性对美国城市间科研协作影响的假设。［方法/过程］以WoS中IS&R等主题期刊论文为测度数据，构建美国城市科研协作网络，探测网络结构和特征；利用参与科研协作城市节点的期刊数据、专利数据、地理数据、经济数据等构建各维度邻近矩阵，利用QAP分析测度四个邻近维度对美国城市间科研协作强度的影响。［结果/结论］结果发现地理邻近、经济邻近、实力邻近、技术邻近与科研协作强度呈显著负相关关系，但各维度影响程度表现存在一定差异。