《复杂科学 资本市场 项目评价》简介

《复杂科学资本市场项目评价》一书是武汉大学商学院徐绪松教授20余年的系列成果。该书提出了复杂科学管理的理论方法，并将它应用于资本市场、项目评价等重大的决策问题中。全书分三大部分。第一部分：复杂科学的基础算法一求解复杂系统的非数值算法。

浅谈模块化卫生应急队伍建设

目的 探索模块化卫生应急队伍建设路径和运行方式,促进队伍应对突发事件处置与救援能力的提升,防范化解突发事件对人民群众生命安全和身体健康的威胁。方法 研究国家、北京市等有关部门发布的关于加强公共卫生应急队伍建设的要求与政策导向,围绕北京市推进模块化卫生应急队伍建设的实践进行研究分析。结果 组建集合传染病救治、中毒处置、烧伤救治、创伤救治、紧急心理救援、核与辐射事件救治、院前急救、传染病现场处置共8个专业模块的应急救援队伍,队伍建设取得实效,初步具备现代化、专业化、标准化、综合类应急救援队伍的建设目标。结论 通过模块化方式进行队伍建设具有实际的必要性与操作的可行性,平急结合,加强日常培训演练可进一步提升队伍的紧急医学救援能力。

A Conversation About the Sacred in Art, From Kandinsky to the Present

The relationship between art and spiritual are explored by reviewing the published conversation, beginning with Kandinsky＇s On the Spiritual in Art, then viewing highlights from the classic text Art, Creativity and the Sacred and ending with excerpts from the journal Image. The ways in which art is similar to religion are discussed. Pertinent concepts are explored, with awareness of shifting definitions and application of these concepts. This conversation seems to present a consensus that there are aspects of art that overlap with the spiritual or religious. There is not, however, consensus on what these aspects are or their significance to society, as perspectives and understanding continue to change with growing complexities and multiple viewpoints within this interdisciplinary field. It does seem to bring into question the distinction between the spiritual and the secular.

The Parable of the Chicken House： Charles S. Peirce, Complex/Dynamic Systems, and Environmental Science

This paper describes how scientist-philosopher Charles S. Peirce （1839-1914） develops theories that lead eventually to contemporary complex/dynamic systems. In both Peirce and complexity theory, possible bridges appear between analogical/reductionist representations and metaphorical/creative symbols. In complex/dynamic terms, Peirce＇s scientific theories become a conceptual egg that hatches a century later in complex systems, which is relevant in turn to environmental science and engineering.

Complexity and Sociology

This study focuses on the correlation between sociology and complexity and it operates a reflection on the deep epistemological and ontological meaning of complexity, revealing how complexity goes beyond the analysis of the global society and is linked to sociology itself and to the issue of its scientific trait. The study shows how complexity, rediscovered following the globalization processes, reconnects sociology with its own origins and concerns the issue of the relation of sociological science with its own object, that is to say, society and social order. In a more radical manner, the challenge of complexity is intertwined with the road of revisiting modern science and epistemological identifying among ＂order＂, ＂intelligibility＂, and ＂science＂. In such a vision, complexity, not only reconnects sociology to its obiect, but highlights how those traits considered as non-scientific residue of human and social sciences belong to the fundamental issue of scientific knowledge. The challenge of complexity is outlined, as questioning the idea according to which the ＂modern＂ science depletes the ＂scientific vision of the world＂.

Complexity Decision Making and General Systems Theory： An Educational Perspective

The aim of this paper is to look at some important educational aspects of complexity decision making m a mummsc^pnnary manner from the perspective of General Systems Theory （GST）. First, the major issues involved in complexity management and decision making are summarized as they are viewed in literature, and a review of GST and Systems Thinking is given. The discussion in the paper is developed within the context of GST in general, but concentrated on decision making in the three trends of GST： Operations Research, Cybernetics, and Managerial Cybernetics. Here, the role of Cybernetics in complexity decision making is particularly emphasized. The discussion is then extended to the latest developments in complexity decision making in Science of Complexity and Soft Systems Thinking. The study also includes a framework which is expected to guide instructors who are planning to offer contemporary courses on decision making. The framework provides some clues for assessing the level of complexity for a given situation and selecting the appropriate methodology for solution development.

Introducing Sustainability Concepts Into University Curricula Through Systems Thinking

The aim of this paper is to explore the major issues involved in introducing sustainability concepts into university curricula in an interdisciplinary manner, through Systems Thinking. It is generally accepted that a holistic approach is essential in sustainability studies, but teaching such a new and complex topic to a diverse student population is by no means easy. In this study, sustainability is viewed in the context of Systems Thinking, particularly in Complexity Management domain. A general framework is proposed with the intension of guiding potential instructors who are planning to teach sustainability through Systems Thinking. The framework includes only the suggested systems-oriented material and a review of some system methodologies; it does not cover sustainability issues. Methodologies known as System Dynamics and Soft Cybernetics are explored and emphasized particularly in the paper due to their importance. The framework is kept general enough so that it appeals to students and instructors with a variety of background.

Discussion on the Application of Complex Power Network to Software Engineering

Along with the further development of science and technology, computer hardware and the Intemet are in a rapid development, and information technology has been widely used in all fields so that complex problems are simply solved. Because of the needs for the development, software starts to mutually integrate with complex power network, making the scale of software increase greatly. Such a growing trend of software promotes soft-ware development to go beyond a general understanding and control and thus a complex system is formed. It is necessary to strengthen the research of complex network theory, and this is a new way to help people study the complexity of software systems. In this paper, the development course of complex dynamic network is introduced simply and the use of complex power network in the software engineering is summarized. Hopefully, this paper can help the crossover study of complex power network and software engineering in the future.

Key Scientific Issues for Regional Sustainable Development in Northeast Asia

Within the context of global climate change, achieving sustainable development in Northeast Asia will require in-depth research into the key scientific issues from both theoretical and empirical perspectives. This paper assesses that the main issues to be addressed are：（i） researches on the structure, function and differentiation disciplines of the vast and complex regional resources-environment-socio-economic system that is Northeast Asia and on how the region can respond and evolve. （ii） Failing to find a mode for sustainable development is one of the most serious restrictive factors to development in Northeast Asia. （iii） Development of cross-border regional socio-economic models for sustainable development is essential. And （iv） the strategies above require cross-border technical support platforms to guarantee a consistent approach to regional sustainability in Northeast Asia.

Dynamical Criticality:Overview and Open Questions

Systems that exhibit complex behaviours are often found in a particular dynamical con- dition, poised between order and disorder. This observation is at the core of the so-called criticality hypothesis, which states that systems in a dynamical regime between order and disorder attain the highest level of computational capabilities and achieve an optimal trade-off between robustness and flexibility. Recent results in cellular and evolutionary biology, ueuroscience and computer science have revitalised the interest in the criticality hypothesis, emphasising its role as a viable candidate general law in adaptive complex systems. This paper provides an overview of the works on dynamical criticality that are -- To the best of our knowledge -- Particularly relevant for the criticality hypothesis. The authors review the main contributions concerning dynamics and information processing at the edge of chaos, and illustrate the main achievements in the study of critical dynamics in biological systems. Finally, the authors discuss open questions and propose an agenda for future work.

Computing Sparse GCD of Multivariate Polynomials via Polynomial Interpolation

The problem of computing the greatest common divisor（GCD） of multivariate polynomials, as one of the most important tasks of computer algebra and symbolic computation in more general scope, has been studied extensively since the beginning of the interdisciplinary of mathematics with computer science. For many real applications such as digital image restoration and enhancement,robust control theory of nonlinear systems, L1-norm convex optimization in compressed sensing techniques, as well as algebraic decoding of Reed-Solomon and BCH codes, the concept of sparse GCD plays a core role where only the greatest common divisors with much fewer terms than the original polynomials are of interest due to the nature of problems or data structures. This paper presents two methods via multivariate polynomial interpolation which are based on the variation of Zippel＇s method and Ben-Or/Tiwari algorithm, respectively. To reduce computational complexity, probabilistic techniques and randomization are employed to deal with univariate GCD computation and univariate polynomial interpolation. The authors demonstrate the practical performance of our algorithms on a significant body of examples. The implemented experiment illustrates that our algorithms are efficient for a quite wide range of input.

SYSTEMS WITH COMPLEXITY

Science of Complexity is a newly emerging branch of natural science. Althoughwe still haven't a precise definition, there are some principles for justifying whether a systemis a complex system. The purpose of this article is to reveal some of such principles. Onthe basis of them, the concept of a system with complexity is proposed. They may helpus to distinguish a real complex system from complicated objects in common sense. Thenwe propose some fundamental problems faced by the study of systems with complexity.

Integrated research methods in watershed science

We discuss the concepts, research methods, and infrastructure of watershed science. A watershed is a basic unit and possesses all of the complexities of the land surface system, thereby making it the best unit for practicing Earth system science. Watershed science is an Earth system science practiced on a watershed scale, and it has developed rapidly over the previous two decades. The goal of watershed science is to understand and predict the behavior of complex watershed systems and support the sustainable development of watersheds. However, watershed science confronts the difficulties of understanding complex systems, achieving scale transformation, and simulating the co-evolution of the human-nature system. These difficulties are fundamentally methodological challenges. Therefore, we discuss the research methods of watershed science, which include the self-organized complex system method, the upscaling method dominated by statistical mechanics, Darwinian approaches based on selection and evolutionary principles, hydro-economic and eco-economic methods that emphasize the human-nature system co-evolution, and meta-synthesis for addressing unstructured problems. These approaches together can create a bridge between holism and reductionism and work as a group of operational methods to combine hard and soft integrations and capture all aspects of both natural and human systems. These methods will contribute to the maturation of watershed science and to a methodology that can be used throughout land-surface systems science.

Science Letters:A simplified MMSE-based iterative receiver for MIMO systems

A simplified minimum mean square error(MMSE) detector is proposed for joint detection and decoding of multi-ple-input multiple-output(MIMO) systems.The matrix inversion lemma and the singular value decomposition(SVD) of the channel matrix are used to simplify the computation of the coefficient of the MMSE filter.Compared to the original MMSE detector,the proposed detector has a much lower computational complexity with only a marginal performance loss.The proposed detector can also be applied to MIMO systems with high order modulations.

A Lecture Delivered at Beijing Foreign Studies University, May 12, 2019

This article traces the evolution of the field of second language acquisition/development(SLA/SLD). It chronicles the evolution in terms of different disciplines and theories that have been influential, beginning with the origin of SLA/SLD in linguistic thinking and expanding its scope of inquiry to psycholinguistics. It has developed further with the disciplines of anthropology and sociology holding sway. More recently, newer cognitive theories have been influential. The article discusses the recent call for a transdisciplinary approach. More specifically, the author promotes the adoption of complex dynamic systems theory, in keeping with non-reductionist systems thinking. Not only is this sociocognitive theory an interdisciplinary theory, but it also highlights the dynamic, variable, nonlinear nature of second language development. This it does within an ecological conception of development, which insists on the relevance of context. It also maintains that SLA/SLD is not a matter of input becoming output, but rather that language patterns emerge from the interaction of its users, given the affordances that they perceive. The article concludes with a discussion of several instructional issues.