An accurate classification of bacteria is essential for the proper identification of patient infections and subsequent treatment decisions. Multi-Locus Sequence Typing (MLST) is a genetic technique for bacterial classification. MLST classifications are used to cluster bacteria into clonal complexes. Importantly, clonal complexes can serve as a biological species concept for bacteria, facilitating an otherwise difficult taxonomic classification. In this paper, we argue for the inclusion of terms relating to clonal complexes in biomedical ontologies.

The innovation of the deep learning modeling scheme plays an important role in promoting the research of complex problems handled with artificial intelligence in smart cities and the development of the next generation of information technology. With the widespread use of smart interactive devices and systems, the exponential growth of data volume and the complex modeling requirements increase the difficulty of deep learning modeling, and the classical centralized deep learning modeling scheme has encountered bottlenecks in the improvement of model performance (...) and the diversification of smart application scenarios. The parallel processing system in deep learning links the virtual information space with the physical world, although the distributed deep learning research has become a crucial concern with its unique advantages in training efficiency, and improving the availability of trained models and preventing privacy disclosure are still the main challenges faced by related research. To address these above issues in distributed deep learning, this research developed a clonal selective optimization system based on the federated learning framework for the model training process involving large-scale data. This system adopts the heuristic clonal selective strategy in local model optimization and optimizes the effect of federated training. First of all, this process enhances the adaptability and robustness of the federated learning scheme and improves the modeling performance and training efficiency. Furthermore, this research attempts to improve the privacy security defense capability of the federated learning scheme for big data through differential privacy preprocessing. The simulation results show that the proposed clonal selection optimization system based on federated learning has significant optimization ability on model basic performance, stability, and privacy. (shrink)

Individuation and organization in complex living multi-level ecosystem occurs as dynamical processes from early ontogeny. The notion of living “holon” displaying dynamic self-assertion and integration is used here to explain the ecosystems dynamic processes. The update of the living holon state according to the continuous change of the dynamic system allows for its viability. This is interpreted as adaptation, selection and organization by the human that observes the system a posteriori from its level. Our model concerns the complex dynamics of (...) the adaptive immune system, integrating holon-lymphocytes that collectively preserve the identity and integrity of the organism. Each lymphocyte individualizes as a dynamic holon-lymphocyte, with somatic gene individuation leading to an individual, singular antigen immunoreceptor type, promoting the self-assertion. In turn, the “Immunoception” allows for perception of the environmental antigenic context, thus integration of the holon in its environment. The self-assertion/integration of holon-lymphocyte starts from fetal stages and is influenced by mother Lamarckian acquired historicity transmissions, a requisite for the integrity of the holobiont-organism. We propose a dynamic model of the perception by holon-lymphocyte, and at the supra-clonal level of the immune system functions that sustain the identity and integrity of the holon-holobiont organism. (shrink)

Recent studies of prostate cancer and other tumor types have revealed significant support, as well as unexpected complexities, for the application of concepts from normal stem cell biology to cancer. In particular, the cell of origin and cancer stem cell models have been proposed to explain the heterogeneity of tumors during the initiation, propagation, and evolution of cancer. Thus, a basis of intertumor heterogeneity has emerged from studies investigating whether stem cells and/or non‐stem cells can serve as cells of origin (...) for cancer and give rise to tumor subtypes that vary in disease outcome. Furthermore, analyses of putative cancer stem cells have revealed the genetically diverse nature of cancers and expanded our understanding of intratumor heterogeneity and clonal evolution. Overall, the principles that have emerged from these stem cell studies highlight the challenges to be surmounted to develop effective treatment strategies for cancer. (shrink)

Clonal expansion of T‐lymphocyte populations results from interactions of antigenic structures presented in combination with accessory cells (macrophages) and antibody recognition sites on the surface of T cells. The resulting activation of a membrane phospholipase C plays a crucial role in lymphocyte responses by releasing diglyceride and PIP3. The released diglyceride activates a cellular protein kinase C while PIP3 stimulates Ca2+ influx. Arachidonic acid released by the action of diglyceride lipase serves as substrate for the synthesis of bioactive eicosanoids (...) (prostaglandins and leukotrienes) which in turn modulate cellular adenyl and guanyl cyclases. The eicosanoids serve as both intra‐ and extra‐cellular signals for lymphocytes, regulating the production and expression of lymphokines and mediating the complex interactions between the monocyte‐macrophage components and helper and suppressor T cells.Aspirin and other anti‐inflammatory drugs stimulate mitogenesis by inhibiting production of the negative modulator prostaglandin E2 in accessory cells and by enhancing the production of the lymphokine 1L‐2 by producer T‐cells. (shrink)

Since the 1970s, the origin of cancer is being explored from the point of view of the Somatic Mutation Theory (SMT), focusing on genetic mutations and clonal expansion of somatic cells. As cancer research expanded in several directions, the dominant focus on cells remained steady, but the classes of genes and the kinds of extra-genetic factors that were shown to have causal relevance in the onset of cancer multiplied. The wild heterogeneity of cancer-related mutations and phenotypes, along with the (...) increasing complication of models, led to an oscillation between the hectic search of 'the' few key factors that cause cancer and the discouragement in face of a seeming 'endless complexity'. To tame this complexity, cancer research started to avail itself of the tools that were being developed by Systems Biology. At the same time, anti-reductionist voices began claiming that cancer research was stuck in a sterile research paradigm. This alternative discourse even gave birth to an alternative theory: the Tissue Organization Field Theory (TOFT). A deeper philosophical analysis shows the serious limits of both reductionist and anti-reductionist positions and of their polarization. This book demonstrates that a radical philosophical reflection is necessary to drive cancer research out of its impasses. At the very least, this will be a reflection on the assumptions of different kinds of cancer research, on the implications of what cancer research has been discovering over 40 years and more, on a view of scientific practice that is most able to make sense of the cognitive and social conflicts that are seen in the scientific community (and in its results), and, finally, on the nature of living entities with which we entertain this fascinating epistemological dance that we call scientific research. The proposed Dynamic and Relational View of carcinogenesis is a starting point in all these directions. (shrink)

Gene expression activity is heterogeneous in a population of isogenic cells. Identifying the molecular basis of this variability will improve our understanding of phenomena like tumor resistance to drugs, virus infection, or cell fate choice. The complexity of the molecular steps and machines involved in transcription and translation could introduce sources of randomness at many levels, but a common constraint to most of these processes is its energy dependence. In eukaryotic cells, most of this energy is provided by mitochondria. A (...) clonal population of cells may show a large variability in the number and functionality of mitochondria. Here, we discuss how differences in the mitochondrial content of each cell contribute to heterogeneity in gene products. Changes in the amount of mitochondria can also entail drastic alterations of a cell's gene expression program, which ultimately leads to phenotypic diversity. (shrink)

Mapping the paths that stem and progenitor cells take en route to differentiate and elucidating the underlying molecular controls are key goals in developmental and stem cell biology. However, with population level analyses it is difficult − if not impossible − to define the transition states and lineage trajectory branch points within complex developmental lineages. Single‐cell RNA‐sequencing analysis can discriminate heterogeneity in a population of cells and even identify rare or transient intermediates. In this review, we propose that using these (...) data, one can infer the lineage trajectories of individual stem cells and identify putative branch points. Clonal lineage tracing of stem cells allows one to define the outcome of differentiation. Integrating these single cell‐based approaches provides a robust strategy for establishing and testing models of how an individual stem cell changes through time to differentiate and self‐renew. (shrink)

Bacteria do many things as organized populations. We have recently learned much about the molecular basis of intercellular communication among prokaryotes. Colonies display bacterial capacities for multicellular coordination which can be useful in nature where bacteria predominantly grow as films, chains, mats and colonies. E. coli colonies are organized into differentiated non-clonal populations and undergo complex morphogenesis. Multicellularity regulates many aspects of bacterial physiology, including DNA rearrangement systems. In some bacterial species, colony development involves swarming (active migration of cell (...) groups). Swarm colony development displays precise geometrical controls and periodic phenomena. Motile E. coli cells in semi-solid media form organized patterns due to chemotactic autoaggregation. On poor media, B. subtilis forms branched colonies using group motility and long-range chemical signalling. The significances of bacterial colony patterns thus reside in a deeper understanding of prokaryotic biology and evolution and in experimental systems for studying self-organization and morphogenesis. (shrink)

The differentiation of mammalian neurons during development is a highly complex process involving regulation and coordination of gene expression at multiple steps. The P19 mouse embryonal carcinoma cell line is a suitable model system with which to analyze regulation of neuronal differentiation. These multipotential cells can be maintained and propagated in tissue culture in an undifferentiated state. Exposure of aggregated P19 cells to retinoic acid results in the differentiation of cells with many fundamental phenotypes of mammalian neurons. Undifferentiated P19 cells (...) are amenable to genetic manipulations such as transfection and establishment of stable clonal cell lines expressing introduced genes. Proteins that play a key role in the neuronal differentiation of P19 cells are beginning to be identified. These include retinoic acid receptors, the epidermal growth factor receptor and the transcription factors Oct‐3 and Brn‐2. The biological and technical advantages of this system should facilitate deeper analysis of the activities of proteins that play a role in neuronal differentiation. (shrink)

The random nature of immunoglobulin gene segment rearrangement inevitably leads to the generation of self‐reactive B cells. Avoidance of destructive autoimmune reactions is necessary in order to maintain physiological homeostasis. However, current central and peripheral tolerance concepts fail to explain the massive number of autoantibody‐borne autoimmune diseases. Moreover, recent studies have shown that in physiological mouse models autoreactive B cells were neither clonally deleted nor kept in an anergic state, but were instead able to mount autoantibody responses. We propose that (...) activation of autoreactive B cells is induced by polyvalent autoantigen complexes that can occur under physiological conditions. Repeated encounter of autoantigen complexes leads to the production of affinity‐matured autoreactive IgM that protects its respective self‐targets from degradation. We refer to this novel mechanism as adaptive tolerance. This article discusses the discovery of adaptive tolerance and the unexpected role of high affinity IgM autoantibodies. (shrink)

Recent data show that catastrophic events during one cell cycle can cause massive genome damage producing viable clones with unstable genomes. This is in contrast with the traditional view that tumorigenesis requires a long‐term process in which mutations gradually accumulate over decades. These sudden events are likely to result in a large increase in genomic diversity within a relatively short time, providing the opportunity for selective advantages to be gained by a subset of cells within a population. This genetic diversity (...) amplification, arising from a single aberrant cell cycle, may drive a population conversion from benign to malignant. However, there is likely a period of relative genome stability during the clonal expansion of tumors – this may provide an opportunity for therapeutic intervention, especially if mechanisms that limit tolerance of aneuploidy are exploited. (shrink)

The widespread distribution of fibroblasts underlines their central role in mammalian physiology, development and ageing. The existence of developmentally regulated and site‐specific phenotypic variation in fibroblasts is well documented. Recent evidence has revealed heterogeneity within the fibroblast population of a given tissue at a specified development stage. The relative proportion and tissue distribution of distinct fibroblast subsets must have important consequences in the control of connective tissue and adjacent epithelial functions in health and disease.

This chapter contains section titled: Introduction Emergence of the Stability‐Diversity—Complexity Debate Mathematization of Ecological Stability The End of the Consensus Contextualization and Classification of Ecological Stability Measures of Ecological Diversity and Complexity Evaluating Stability‐Diversity—Complexity Relationships Acknowledgments References Further Reading.

In a spirit of collegial support, this paper argues that Beckett and Hager’s theoretical justification and empirical exemplifications do not do full justice to the complexity of group or team learning. We firstly reaffirm our support for the theoretical argument Becket and Hager make, though expressing some reservations about Complexity Theory, to explain the taken-for-granted assumptions that learning by an individual is the paradigm case of learning and that context plays a minimal role in this process. Drawing on our joint (...) and separate work, we demonstrate that Becket and Hager’s argument is less radical than it may initially seem because it is predicated on: (i) cognitive-bounded rather than “distributed” or “extended” conception of mind; (ii) material rather than a “immaterial” conception of activity; and (iii) co-present rather than a “fractional” or “connective” conception of ontology. Despite making this critique, we conclude by making the case that we are adding further substance to Becket and Hager’s overarching argument and, in doing so, encouraging them to be more radical about how they conceptualise the complexity of learning. (shrink)

Ecosystems, the human brain, ant colonies, and economic networks are all complex systems displaying collective behaviour, or emergence, beyond the sum of their parts. Complexity science is the systematic investigation of these emergent phenomena, and stretches across disciplines, from physics and mathematics, to biological and social sciences. This introductory textbook provides detailed coverage of this rapidly growing field, accommodating readers from a variety of backgrounds, and with varying levels of mathematical skill. Part I presents the underlying principles of complexity science, (...) to ensure students have a solid understanding of the conceptual framework. The second part introduces the key mathematical tools central to complexity science, gradually developing the mathematical formalism, with more advanced material provided in boxes. A broad range of end of chapter problems and extended projects offer opportunities for homework assignments and student research projects, with solutions available to instructors online. Key terms are highlighted in bold and listed in a glossary for easy reference, while annotated reading lists offer the option for extended reading and research. (shrink)

Introduction -- Elucidating complexity theories -- Complexity in the natural sciences -- Complexity in social theory -- Towards transdisciplinarity -- Complexity in philosophy: complexification and the limits to knowledge -- Complexity in ethics -- Earth in the anthropocene -- Complexity and climate change -- American dreams, ecological nightmares and new visions -- Complexity and sustainability: wicked problems, gordian knots and synergistic solutions -- Conclusion.

Proof complexity is a rich subject drawing on methods from logic, combinatorics, algebra and computer science. This self-contained book presents the basic concepts, classical results, current state of the art and possible future directions in the field. It stresses a view of proof complexity as a whole entity rather than a collection of various topics held together loosely by a few notions, and it favors more generalizable statements. Lower bounds for lengths of proofs, often regarded as the key issue in (...) proof complexity, are of course covered in detail. However, upper bounds are not neglected: this book also explores the relations between bounded arithmetic theories and proof systems and how they can be used to prove upper bounds on lengths of proofs and simulations among proof systems. It goes on to discuss topics that transcend specific proof systems, allowing for deeper understanding of the fundamental problems of the subject. (shrink)

In this Very Short Introduction, John H. Holland, one of the leading figures in the field, introduces the key elements and conceptual framework of complexity. From complex physical systems such as fluid flow and the difficulties of predicting weather, to complex adaptive systems such as the diverse and interdependent ecosystems of rainforests, he uses simple examples to illustrate the approach and insights provided by complexity theory.

From carrots to frogs to sheep and finally to humans, the history of cloning is a fascinating study of the interplay between science and popular culture. Imagination and discovery provide mutual impetus in the evolving science and cultural phenomenon of cloning. Its history is a paradigm of science unfiction: What once belonged unequivocally on the pages of science fiction is now emerging in flesh and blood. Writers, movie producers, ethicists, and all manner of social commentators, no less than scientists, have (...) all participated in the creation of the human clone as an idea and as a biological entity. While the clone stands apart as having only one genetic parent, it truly is a brainchild of multifarious origins. (shrink)

Contemporary theories on complex adaptive systems stem from a natural science perspective. Paul Cilliers was one of the first complexity thinkers to translate the theoretical concepts into a qualitative and normative understanding of complexity. This collected volume of essays consolidates his later work. The introduction by Preiser and Woermann reflects on the significance ofhis contribution within the broader field of complex systems thinking.

v. 1. Origins of order-creation science : complexity science from basic disciplines -- v. 2. Self-organization, emergence and self-organized criticality -- v. 3. Organization and management complexity dynamics -- v. 4. Agent-based socio-economic simulation -- v. 5. Power-law distributions in society and business.

This chapter focuses on one of the common fallacies in Western philosophy called 'complex question (CQ)'. The fallacy of the CQ appears in two varieties. The implicit form distracts an interlocutor by assuming the truth of an unproven premise and shifting the focus of the argument in an unfounded direction. While the explicit form collapses two distinct questions into a single question such that a single answer would appear to satisfy both inquiries. The possibility that an undetected CQ might lead (...) a speaker to affirm additional, unspoken premises unintentionally makes this a popular tactic in police interrogations and debate cross‐examinations. Avoiding this rhetorical trap is only possible either by rejecting the question as posed and extemporaneously clarifying the situation on one's own terms or by remaining silent. (shrink)

The concept of complexity has become very important in theoretical biology. It is a many faceted concept and too new and ill defined to have a universally accepted meaning. This review examines the development of this concept from the point of view of its usefulness as a criteria for the study of living systems to see what it has to offer as a new approach. In particular, one definition of complexity has been put forth which has the necessary precision and (...) rigor to be considered as a useful categorization of systems, especially as it pertains to those we call living. This definition, due to Robert Rosen, has been developed in a number of works and involves some deep new concepts about the way we view systems. In particular, it focuses on the way we view the world and actually practice science through the use of the modelling relation. This mathematical object models the process by which we assign meaning to the world we perceive. By using the modelling relation, it is possible to identify the subjective nature of our practices and deal with this issue explicitly. By so doing, it becomes clear that our notion of complexity and especially its most popular manifestations, is in large part a product of the historical processes which lead to the present state of scientific epistemology. In particular, it is a reaction to the reductionist/mechanistic view of nature which can be termed the Newtonian Paradigm. This approach to epistemology has dominated for so long that its use as a model has become implicit in most of what we do in and out of science. The alternative to this approach is examined and related to the special definition of complexity given by Rosen. Some historical examples are used to emphasize the dependence of our view of what is complex in a popular sense on the ever changing state of our knowledge. The role of some popular concepts such as chaotic dynamics are examined in this context. The fields of artificial life and related areas are also viewed from the perspective of this rigorous view of complexity and found lacking. The notion that in some way life exists at the edge of chaos is examined from the perspective of the second law of thermodynamics given by Schneider and Kay. Finally, the causal elements in complex systems are explored in relation to complexity. Rosen has shown that a clear difference in causal relations exists between complex and simple systems and that this difference leads to a uniquely useful definition of what we mean by living. Rosen makes it very clear that the class of systems which are complex is a much larger class than those which we call living. For that reason, the focus of this review will be on complexity as a stepping stone towards the deeper question of what makes a system alive. (shrink)

How does the complex nature of ecological systems affect ecologists' ability to study them? This Element argues that ecological systems are complex in a rather special way: they are causally heterogeneous. The author presents an updated philosophical account with an optimistic outlook of the methods and status of ecological research.

Containing selected papers on the fundamentals and applications of Complexity Science, this multi-disciplinary book presents new approaches for resolving complex issues that cannot be resolved using conventional mathematical or software models. Complex Systems problems can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. Complexity Science problems, the science of open systems consisting of large numbers of diverse components engaged in rich interaction, can occur in a variety (...) of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. The global behaviour of these systems emerges from the interaction of constituent components and is unpredictable but not random. The key attribute of Complex Systems is the ability to self-organise and adapt to unpredictable changes in their environment. (shrink)

Computational complexity theory is a subfield of computer science originating in computability theory and the study of algorithms for solving practical mathematical problems. Amongst its aims is classifying problems by their degree of difficulty — i.e., how hard they are to solve computationally. This paper highlights the significance of complexity theory relative to questions traditionally asked by philosophers of mathematics while also attempting to isolate some new ones — e.g., about the notion of feasibility in mathematics, the $\mathbf{P} \neq \mathbf{NP}$ (...) problem and why it has proven hard to resolve, and the role of non-classical modes of computation and proof. (shrink)

In the post-Apartheid era South Africa’s universities have faced serious questions about the quality of their student learning in the face of near impossible challenges. The University of Cape Town, widely seen as the country’s leading higher education institution, has shown remarkable resilience, however, in the range of initiatives it has launched to support and enhance student learning. These initiatives, designed with a common purpose, are of course intended to work together so that their effects might be compounded and realized (...) in enhanced student learning outcomes. Drawing substantially on the power of compounding (which is itself redolent of the claim made by complexity theory that relations and emergence are crucial concepts), complexity theory offers unique insights into how and why things change – and also into how and why things remain largely the same or inexorably grind towards failure. The networked initiatives undertaken by the University of Cape Town constitute a case of learning refurbishment that is also well explained and understood in terms of complexity theory. This paper draws on concepts from complexity theory both to understand how learning might be enhanced in higher education institutions in severely straitened circumstances and to offer insights for education leaders and policy-makers in this domain. (shrink)

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

Avec Totem et tabou, Freud entame la première démarche majeure d’interprétation psychanalytique de données ethnographiques, le conduisant en particulier à situer le complexe d’Œdipe au fondement des premières institutions sociales et à repérer l’action de processus inconscients dans leur élaboration. De plus, en posant l’universalité du complexe d’Œdipe tant psychique que culturelle, il réalise une véritable effraction dans le champ d’investigation des anthropologues, suscitant chez eux des réactions aussi violentes que variées. C’est cette histoire souvent faite de méconnaissance, de défiance (...) et de malentendus entre la psychanalyse et l’anthropologie — ces deux sciences de l’homme toutes deux nées au XIXe siècle — que relate Éric Smadja. Après avoir exposé les conditions épistémologiques et historiques d’instauration de ce débat conflictuel, l’auteur le développe suivant un fil chronologique qui l’amène à explorer ses déterminants et ses enjeux, mais aussi les caractéristiques de ces deux disciplines. Se dévoile alors un moment de l’histoire des idées. (shrink)

When analyzing complex longitudinal data, especially data from different educational settings, researchers generally focus only on the mean part (i.e., the regression coefficients), ignoring the equally important random part (i.e., the random effect variances) of the model. By using Project English Language and Literacy Acquisition (ELLA) data, we demonstrated the importance of taking the complex data structure into account by carefully specifying the random part of the model, showing that not only can it affect the variance estimates, the standard errors, (...) and the tests of significance of the regression coefficients, it also can offer different perspectives of the data, such as information related to the developmental process. We used xxM (Mehta, 2013), which can flexibly estimate different grade-level variances separately and the potential carryover effect from each grade factor to the later time measures. Implications of the findings and limitations of the study are discussed. (shrink)

Graphical AbstractGene regulatory networks, which are crucial for the proper development of organisms, are extensively studied. From these investigations, coordinative mechanisms are shown to be instructive for further development. Competitive mechanisms as well as environmental and metabolic influences, however, are widely ignored so far but appear to be important for the emergence of shape.

This book explains the relationship between intelligence and environmental complexity, and in so doing links philosophy of mind to more general issues about the relations between organisms and environments, and to the general pattern of 'externalist' explanations. The author provides a biological approach to the investigation of mind and cognition in nature. In particular he explores the idea that the function of cognition is to enable agents to deal with environmental complexity. The history of the idea in the work of (...) Dewey and Spencer is considered, as is the impact of recent evolutionary theory on our understanding of the place of mind in nature. (shrink)

Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. The book integrates insights from complexity and computational theory with the philosophical position of thinkers including Derrida and Lyotard. Paul Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle's superficial contribution to the debate.

The consensus among evolutionists seems to be that the morphological complexity of organisms increases in evolution, although almost no empirical evidence for such a trend exists. Most studies of complexity have been theoretical, and the few empirical studies have not, with the exception of certain recent ones, been especially rigorous; reviews are presented of both the theoretical and empirical literature. The paucity of evidence raises the question of what sustains the consensus, and a number of suggestions are offered, including the (...) possibility that certain cultural and/or perceptual biases are at work. In addition, a shift in emphasis from theoretical to empirical inquiry is recommended for the study of complexity, and guidelines for future empirical studies are proposed. (shrink)

Our socio-economic innovation ecosystem is riddled with ever-increasing complexity, as we are faced with more frequent and intense shocks, such as COVID-19. Unfortunately, addressing complexity requires a different kind of economic governance. There is increasing pressure on economics to not only going beyond its traditional mainstream boundaries but also to tackle real-world problems such as fostering structural change, enhancing sustained growth, promoting inclusive development in the era of the digital economy, and boosting green growth, while addressing the divide between the (...) financial sector and the real economy. This book demonstrates how to apply complexity science to economics, in an effective and instructive way, in the interest of life-enhancing policies. The book revolves around the non-negligible problem of why economics, to date, seems to be insufficient in guiding economic governance to navigate through real and ever-intensifying complex socio-economic and environmental challenges. With its interdisciplinary approach, the book scans the nuanced nexus between complexity and economics by incorporating, as well as transcending the state-of-the-art literature. It identifies ways to trigger opportunities for behaviour change in the economic profession with respect to how to teach and what, introducing and developing further complexity economics thinking with the configuration of its main principles and outlining the silhouette of next-generation economic governance. The book deciphers recommendations both for economic theory, practice, and education and economic governance. It will be of interest to students, scholars, academics, think tank researchers and economic policy practitioners at the national and/or supranational level. Olivér Kovács is a senior research fellow in the Department of Economics and International Economics at the University of Public Service, Budapest, Hungary. (shrink)

In this Very Short Introduction, John H. Holland, one of the leading figures in the field, introduces the key elements and conceptual framework of complexity. From complex physical systems such as fluid flow and the difficulties of predicting weather, to complex adaptive systems such as the diverse and interdependent ecosystems of rainforests, he uses simple examples to illustrate the approach and insights provided by complexity theory.

This volume is both a state-of-the-art display of current thinking on second language development as a complex system. It is also a tribute to Diane Larsen-Freeman for her decades of intellectual leadership in the academic disciplines of applied linguistics and second language acquisition. The chapters therein range from theoretical expositions to methodological analyses, pedagogical proposals, and conceptual frameworks for future research. In a balanced and in-depth manner, the authors provide a comprehensive and interdisciplinary understanding of second language development, with a (...) wealth of insights that promise to break the status-quo of current research and take it to exciting new territory. The book will appeal to both seasoned and novice researchers in applied linguistics, second language acquisition, bilingualism, cognitive psychology, and education, as well as to practitioners in second or foreign language teaching of any language. (shrink)

This Special Issue addresses a range of educational issues linked to main themes from our 2019 book The Emergence of Complexity: Rethinking Education as a Social Science. This book elaborated two major theses that raise fundamental questions for philosophy of education. First, that learning by groups is typically a distinctive kind of learning that is not reducible to learning by individuals. Second, that a degree of holism, as against a focus on individuals, is essential for achieving a convincing understanding of (...) this distinctive type of group learning. These two theses are of direct interest to philosophy of education since they challenges the resources of received theories of learning. Yet this kind of group learning characterises the vast bulk of human learning situations that occur outside of formal education systems. In this Special Issue introductory article we, firstly, introduce some basic principles of complexity theory, and demonstrate that, together with the concept of a ‘co-present group’ (between 2 and about 12 individuals), these ideas offer develop novel understandings of the distinctive learning that occurs within such groups. Secondly, we outline and illustrate with further examples the main features of co-present groups. Thirdly, we consolidate our conceptual work by showing five ways in which our account of group learning serves to refurbish the concept of ‘learning’. (shrink)

In _Complexity and Postmodernism_, Paul Cilliers explores the idea of complexity in the light of contemporary perspectives from philosophy and science. Cilliers offers us a unique approach to understanding complexity and computational theory by integrating postmodern theory into his discussion. _Complexity and Postmodernism_ is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.

What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex systems (...) scientist Melanie Mitchell provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Comprehending such systems requires a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. She explores as well the relationship between complexity and evolution, artificial intelligence, computation, genetics, information processing, and many other fields. Richly illustrated and vividly written, Complexity : A Guided Tour offers a comprehensive and eminently comprehensible overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our time. (shrink)

Managing Complexity in Healthcare introduces the ComEntEth (Complex Entropic Ethical) model as an integrated bio-medical and philosophical approach to understanding how people get things done in healthcare. Drawing on the complexity sciences, studies of entropy in living organisms, and the ethics of Emmanuel Levinas, healthcare is theorised as energetic relational exchanges between people as entropic and ethical entities that unfold around a central attractor: Reduction in elevated entropy or suffering in patients. Living entities are engaged in a continuous struggle against (...) the tendency to produce entropy. From the cellular to the collective of human endeavours, the tendency of complex systems is to disorder and decay. Yet in the micro-activity of healthcare enterprise, people resist this tendency by expending energy to create order and sustain life. Making sense of how this miraculous work is made possible is the foundation of this book. Through practical examples - from analysis of practitioner burnout, rural and remote healthcare, the functioning of emergency departments, to government, social and institutional responses to the COVID-19 pandemic -this new integral philosophy provides practitioners, managers, policy designers, and scholars an effective way to understand the dynamics of daily processes and practices that link the micro of everyday interactions with the macro-trends of healthcare. (shrink)

The presence and role of microbes in human cancers has come full circle in the last century. Tumors are no longer considered aseptic, but implications for cancer biology and oncology remain underappreciated. Opportunities to identify and build translational diagnostics, prognostics, and therapeutics that exploit cancer's second genome—the metagenome—are manifold, but require careful consideration of microbial experimental idiosyncrasies that are distinct from host‐centric methods. Furthermore, the discoveries of intracellular and intra‐metastatic cancer bacteria necessitate fundamental changes in describing clonal evolution and (...) selection, reflecting bidirectional interactions with non‐human residents. Reconsidering cancer clonality as a multispecies process similarly holds key implications for understanding metastasis and prognosing therapeutic resistance while providing rational guidance for the next generation of bacterial cancer therapies. Guided by these new findings and challenges, this Review describes opportunities to exploit cancer's metagenome in oncology and proposes an evolutionary framework as a first step towards modeling multispecies cancer clonality. Also see the video abstract here: https://youtu.be/-WDtIRJYZSs. (shrink)

The complexity of human societies of the past few thousand years rivals that of social insect societies. We hypothesize that two sets of social “instincts” underpin and constrain the evolution of complex societies. One set is ancient and shared with other social primate species, and one is derived and unique to our lineage. The latter evolved by the late Pleistocene, and led to the evolution of institutions of intermediate complexity in acephalous societies. The institutions of complex societies often conflict with (...) our social instincts. The complex societies of the past few thousand years can function only because cultural evolution has created effective “work-arounds” to manage such instincts. We describe a series of work-arounds and use the data on the relative effectiveness of WWII armies to test the work-around hypothesis. (shrink)