The evolution of cooperation in asymmetric systems

Explaining "Tragedy of the Commons" of evolution of cooperation remains one of the greatest problems for both biology and social science. Asymmetrical interaction, which is one of the most important characteristics of cooperative system, has not been sufficiently considered in the existing models of the evolution of cooperation. Considering the inequality in the number and payoff between the cooperative actors and recipients in cooperation systems, discriminative density-dependent interference competition will occur in limited dispersal systems. Our model and simulation show that the local but not the global stability of a cooperative interaction can be maintained if the utilization of common resource remains unsaturated, which can be achieved by density-dependent restraint or competition among the cooperative actors. More intense density dependent interference competition among the cooperative actors and the ready availability of the common resource, with a higher intrinsic contribution ratio of a cooperative actor to the recipient, will increase the probability of cooperation. The cooperation between the recipient and the cooperative actors can be transformed into conflict and, it oscillates chaotically with variations of the affecting factors under different environmental or ecological conditions. The higher initial relatedness (i.e. similar to kin or reciprocity relatedness), which is equivalent to intrinsic contribution ratio of a cooperative actor to the recipient, can be selected for by penalizing less cooperative or cheating actors but rewarding cooperative individuals in asymmetric systems. The initial relatedness is a pivot but not the aim of evolution of cooperation. This explains well the direct conflict observed in almost all cooperative systems.

Synchronization in climate dynamics and other extended systems

Synchronization is now well established as representing coherent behaviour between two or more otherwise autonomous nonlinear systems subject to some degree of coupling. Such behaviour has mainly been studied to date, however, in relatively low-dimensional discrete systems or networks. But the possibility of similar kinds of behaviour in continuous or extended spatiotemporal systems has many potential practical implications, especially in various areas of geophysics. We review here a range of cyclically varying phenomena within the Earth's climate system for which there may be some evidence or indication of the possibility of synchronized behaviour, albeit perhaps imperfect or highly intermittent. The exploitation of this approach is still at a relatively early stage within climate science and dynamics, in which the climate system is regarded as a hierarchy of many coupled sub-systems with complex nonlinear feedbacks and forcings. The possibility of synchronization between climate oscillations (global or local) and a predictable external forcing raises important questions of how models of such phenomena can be validated and verified, since the resulting response may be relatively insensitive to the details of the model being synchronized. The use of laboratory analogues may therefore have an important role to play in the study of natural systems that can only be observed and for which controlled experiments are impossible. We go on to demonstrate that synchronization can be observed in the laboratory, even in weakly coupled fluid dynamical systems that may serve as direct analogues of the behaviour of major components of the Earth's climate system. The potential implications and observability of these effects in the long-term climate variability of the Earth is further discussed. © 2010 Springer-Verlag Berlin Heidelberg.

Futures of inland aquatic agricultural systems and implications for fish agri-food systems in southern Africa

The CGIAR Research Program on Aquatic Agricultural Systems (AAS) is collaborating with partners to develop and implement a foresight-based engagement with diverse stakeholders linked to aquatic agricultural systems. The program’s aim is to understand the implications of current drivers of change for fish agri-food systems, and consequently food and nutrition security, in Africa, Asia and the Pacific. Partners include the Global Forum on Agricultural Research (GFAR), the Forum for Agricultural Research in Africa (FARA) and the African Union’s New Partnership for Africa’s Development (AU-NEPAD). A key part of the program was a participatory scenario-building workshop held in July 2015 under the theme of "futures of aquatic agricultural systems and implications for fish agri-food systems in southern Africa." The objectives for the workshop were (i) to engage local stakeholders in exploring plausible futures of aquatic agricultural systems, and (ii) to broker and catalyze collaborative plans of action based on the foresight analysis. This report presents technical findings from the workshop. The CGIAR Research Program on Aquatic Agricultural Systems (AAS) is collaborating with partners to develop and implement a foresight-based engagement with diverse stakeholders linked to aquatic agricultural systems. The program’s aim is to understand the implications of current drivers of change for fish agri-food systems, and consequently food and nutrition security, in Africa, Asia and the Pacific. Partners include the Global Forum on Agricultural Research (GFAR), the Forum for Agricultural Research in Africa (FARA) and the African Union’s New Partnership for Africa’s Development (AU-NEPAD). A key part of the program was a participatory scenario-building workshop held in July 2015 under the theme of "futures of aquatic agricultural systems and implications for fish agri-food systems in southern Africa." The objectives for the workshop were (i) to engage local stakeholders in exploring plausible futures of aquatic agricultural systems, and (ii) to broker and catalyze collaborative plans of action based on the foresight analysis. This report presents technical findings from the workshop.

Global solutions

As manufacturing enterprises become increasingly globalised, the supply chain is becoming more fragmented, with multiple players engaged in key aspects of the value chain. This has seen the emergence of suppliers offering specialised operations (research, design, production, service) which are capable of serving widely dispersed markets. It is generally assumed that managing these increasingly complex international supply chains requires sophisticated management techniques. Many companies have installed advanced planning systems for just this reason - systems that require skilled staff to implement the complex processes involved.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.

Global analysis of dynamical decision-making models through local computation around the hidden saddle

Bistable dynamical switches are frequently encountered in mathematical modeling of biological systems because binary decisions are at the core of many cellular processes. Bistable switches present two stable steady-states, each of them corresponding to a distinct decision. In response to a transient signal, the system can flip back and forth between these two stable steady-states, switching between both decisions. Understanding which parameters and states affect this switch between stable states may shed light on the mechanisms underlying the decision-making process. Yet, answering such a question involves analyzing the global dynamical (i.e., transient) behavior of a nonlinear, possibly high dimensional model. In this paper, we show how a local analysis at a particular equilibrium point of bistable systems is highly relevant to understand the global properties of the switching system. The local analysis is performed at the saddle point, an often disregarded equilibrium point of bistable models but which is shown to be a key ruler of the decision-making process. Results are illustrated on three previously published models of biological switches: two models of apoptosis, the programmed cell death and one model of long-term potentiation, a phenomenon underlying synaptic plasticity. © 2012 Trotta et al.

A perturbation approach to the stabilization of nonlinear cascade systems with time-delay

The effect of bounded input perturbations on the stability of nonlinear globally asymptotically stable delay differential equations is analyzed. We investigate under which conditions global stability is preserved and if not, whether semi-global stabilization is possible by controlling the size or shape of the perturbation. These results are used to study the stabilization of partially linear cascade systems with partial state feedback.

Lyapunov functions for stable cascades and applications to global stabilization

This paper generalizes recent Lyapunov constructions for a cascade of two nonlinear systems, one of which is stable rather than asymptotically stable. A new cross-term construction in the Lyapunov function allows us to replace earlier growth conditions by a necessary boundedness condition. This method is instrumental in the global stabilization of feedforward systems, and new stabilization results are derived from the generalized construction.

An approach to multi-fidelity optimization of aeroengine compression systems

The aerodynamic design of turbomachinery presents the design optimisation community with a number of exquisite challenges. Chief among these are the size of the design space and the extent of discontinuity therein. This discontinuity can serve to limit the full exploitation of high-fidelity computational fluid dynamics (CFD): such codes require detailed geometric information often available only sometime after the basic configuration of the machine has been set by other means. The premise of this paper is that it should be possible to produce higher performing designs in less time by exploiting multi-fidelity techniques to effectively harness CFD earlier in the design process, specifically by facilitating its participation in configuration selection. The adopted strategy of local multi-fidelity correction, generated on demand, combined with a global search algorithm via an adaptive trust region is first tested on a modest, smooth external aerodynamic problem. Speed-up of an order of magnitude is demonstrated, comparable to established techniques applied to smooth problems. A number of enhancements aimed principally at effectively evaluating a wide range of configurations quickly is then applied to the basic strategy, and the emerging technique is tested on a generic aeroengine core compression system. A similar order of magnitude speed-up is achieved on this relatively large and highly discontinuous problem. A five-fold increase in the number of configurations assessed with CFD is observed. As the technique places constraints neither on the underlying physical modelling of the constituent analysis codes nor on first-order agreement between those codes, it has potential applicability to a range of multidisciplinary design challenges. © 2012 by Jerome Jarrett and Tiziano Ghisu.

Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning.

Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.