Epidemic processes in complex networks Pastor-Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet ...
Reviews of modern physics,
08/2015, Letnik:
87, Številka:
3
Journal Article, Publication
Recenzirano
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Complex networks arise in a wide range of biological and sociotechnical systems. Epidemic spreading is central to our understanding of dynamical processes in complex networks, and is of interest to ...physicists, mathematicians, epidemiologists, and computer and social scientists. This review presents the main results and paradigmatic models in infectious disease modeling and generalized social contagion processes. In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.
The ability to effectively control brain dynamics holds great promise for the enhancement of cognitive function in humans and the betterment of their quality of life. Yet, successfully controlling ...dynamics in neural systems is challenging, in part due to the immense complexity of the brain and the large set of interactions that can drive any single change. While some understanding has been gained of the control of single neurons, the control of large-scale neural systems-networks of multiply interacting components-remains poorly understood. Efforts to address this gap include the construction of tools for the control of brain networks, mostly adapted from control and dynamical systems theory. Informed by current opportunities for practical intervention, these theoretical contributions provide models that draw from a wide array of mathematical approaches. Recent developments are presented for effective strategies of control in dynamic brain networks, and potential mechanisms are also described that underlie such processes. Efforts are reviewed on the control of general neurophysiological processes with implications for brain development and cognitive function, as well as the control of altered neurophysiological processes in medical contexts such as anesthesia administration, seizure suppression, and deep-brain stimulation for Parkinson’s disease. This Colloquium is concluded with a forward-looking discussion regarding how emerging results from network control, especially approaches that deal with nonlinear dynamics or more realistic trajectories for control transitions, could be used to directly address pressing questions in neuroscience.
The discovery of physical laws consistent with empirical observations is at the heart of (applied) science and engineering. These laws typically take the form of nonlinear differential equations ...depending on parameters; dynamical systems theory provides, through the appropriate normal forms, an “intrinsic” prototypical characterization of the types of dynamical regimes accessible to a given model. Using an implementation of data-informed geometry learning, we directly reconstruct the relevant “normal forms”: a quantitative mapping from empirical observations to prototypical realizations of the underlying dynamics. Interestingly, the state variables and the parameters of these realizations are inferred from the empirical observations; without prior knowledge or understanding, they parametrize the dynamics intrinsically without explicit reference to fundamental physical quantities.
Agency has attracted considerable attention, especially of late. Nevertheless, perceptions of language learners as nonagentive persist. In this article the Douglas Fir Group's call for a ...transdisciplinary perspective is heeded in a Complex Dynamic Systems Theory's (CDST) conceptualization of agency. It is suggested that CDST maintains the structure-agency complementarity while bringing to the fore the relational and emergent nature of agency. Coordination dynamics is identified as a possible mechanism for the phylogenetic and ontogenetic emergence of agency. CDST further characterizes agency as spatially-temporally situated. It can be achieved and changed through iteration and co-adaptation. It is also multidimensional and heterarchical. In this era of posthumanism, an issue that is also taken up is whether it is only humans who have agency. The article then discusses educational practices that could support learner agency. Finally, the article closes with a discussion of agency and ethical action.
The classical, disembodied approach to music cognition conceptualizes action and perception as separate, peripheral processes. In contrast, embodied accounts of music cognition emphasize the central ...role of the close coupling of action and perception. It is a commonly established fact that perception spurs action tendencies. We present a theoretical framework that captures the ways in which the human motor system and its actions can reciprocally influence the perception of music. The cornerstone of this framework is the common coding theory, postulating a representational overlap in the brain between the planning, the execution, and the perception of movement. The integration of action and perception in so-called internal models is explained as a result of associative learning processes. Characteristic of internal models is that they allow intended or perceived sensory states to be transferred into corresponding motor commands (inverse modeling), and vice versa, to predict the sensory outcomes of planned actions (forward modeling). Embodied accounts typically refer to inverse modeling to explain action effects on music perception (Leman, 2007). We extend this account by pinpointing forward modeling as an alternative mechanism by which action can modulate perception. We provide an extensive overview of recent empirical evidence in support of this idea. Additionally, we demonstrate that motor dysfunctions can cause perceptual disabilities, supporting the main idea of the paper that the human motor system plays a functional role in auditory perception. The finding that music perception is shaped by the human motor system and its actions suggests that the musical mind is highly embodied. However, we advocate for a more radical approach to embodied (music) cognition in the sense that it needs to be considered as a dynamical process, in which aspects of action, perception, introspection, and social interaction are of crucial importance.
The climate is a forced, dissipative, nonlinear, complex, and heterogeneous system that is out of thermodynamic equilibrium. The system exhibits natural variability on many scales of motion, in time ...as well as space, and it is subject to various external forcings, natural as well as anthropogenic. This review covers the observational evidence on climate phenomena and the governing equations of planetary-scale flow and presents the key concept of a hierarchy of models for use in the climate sciences. Recent advances in the application of dynamical systems theory, on the one hand, and nonequilibrium statistical physics, on the other hand, are brought together for the first time and shown to complement each other in helping understand and predict the system's behavior. These complementary points of view permit a self-consistent handling of subgrid-scale phenomena as stochastic processes, as well as a unified handling of natural climate variability and forced climate change, along with a treatment of the crucial issues of climate sensitivity, response, and predictability.
The primary goal of dynamic building envelopes is to meet and balance antagonistic performance criteria utilizing automatic operation. As opposed to static systems, automated shading and daylighting ...systems are increasingly being used in façade design with the intent to improve building performance. Taking this into consideration, the question that arises is whether such systems can significantly improve buildings energy performance and occupants׳ visual and thermal comfort. The present paper is a review of dynamic operation methods of shading/daylighting systems and their associated implications in building energy balance. Based on the subject distribution of the reviewed studies, the majority of the systems examined are versions of motorized blinds while the analysis of new emerging ideas on deployable and foldable façade systems is limited. User acceptance is quite crucial and is strongly dependent on the system׳s intuitive operation. According to the paper findings, energy savings with automatically controlled blinds depend on the type of control strategy and their connection to dimmable electric lighting systems. Even though control strategies enhance energy performance and occupants׳ comfort, their level of complexity highly affects their efficiency and therefore influences their performance.
A cognitive radio network is a multiuser system, in which different users compete for limited resources in an opportunistic manner, interacting with each other for access to the available resources. ...The fact that both users and spectrum holes (i.e., unused spectrum subbands) can come and go makes a cognitive radio network a highly dynamic and challenging wireless environment. Therefore, finding robust resource-allocation algorithms, which are capable of achieving reasonably good solutions fast enough in order to guarantee an acceptable level of performance under worst case interference conditions, is crucial in such environment. The focus of this paper is the transmit-power control in cognitive radio networks, considering a noncooperative framework. Moreover, tools from control theory are used to study both the equilibrium and transient behaviors of the network under dynamically varying conditions.
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