When Ecology Needs Economics and Economics Needs Ecology: Interdisciplinary Exchange in the Age of Humans

Evidence that humans play a dominant role in most ecosystems forces scientists to confront systems that contain factors transgressing traditional disciplinary boundaries. However, it is an open question whether this state of affairs should encourage interdisciplinary exchange or integration. With two case studies, we show that exchange between ecologists and economists is preferable, for epistemological and policy-oriented reasons, to their acting independently. We call this “exchange gain.” Our case studies show that theoretical exchanges can be less disruptive to current theory than commonly thought—valuable exchange does not necessarily require disciplinary integration

Spike-adding and reset-induced canard cycles in adaptive integrate and fire models

We study a class of planar integrate and fire (IF) models called adaptive integrate and fire (AIF) models, which possesses an adaptation vari- able on top of membrane potential, and whose subthreshold dynamics is piece- wise linear (PWL). These AIF models therefore have two reset conditions, which enable bursting dynamics to emerge for suitable parameter values. Such models can be thought of as hybrid dynamical systems. We consider a par- ticular slow dynamics within AIF models and prove the existence of bursting cycles with N resets, for any integer N. Furthermore, we study the transition between N- and (N + 1)-reset cycles upon vanishingly small parameter vari- ations and prove (for N = 2) that such transitions are organised by canard cycles. Finally, using numerical continuation we compute branches of bursting cycles, including canard-explosive branches, in these AIF models, by suitably recasting the periodic problem as a two-point boundary-value problem

Classification of bursting patterns: A tale of two ducks

Bursting is one of the fundamental rhythms that excitable cells can generate either in response to incoming stimuli or intrinsically. It has been a topic of intense research in computational biology for several decades. The classification of bursting oscillations in excitable systems has been the subject of active research since the early 1980s and is still ongoing. As a by-product it establishes analytical and numerical foundations for studying complex temporal behaviors in multiple-timescale models of cellular activity. In this review, we first present the seminal works of Rinzel and Izhikevich in classifying bursting patterns of excitable systems. We recall a complementary mathematical classification approach by Bertram et al., and then by Golubitsky et al., which together with the Rinzel-Izhikevich proposals provide the state-of-the-art foundations to these classifications. Beyond classical approaches, we review a recent bursting example that falls outside the previous classification systems. Generalizing this example leads us to propose an extended classification, which requires the analysis of both fast and slow subsystems of an underlying slow-fast model and allows the dissection of a larger class of bursters. Namely, we provide a general framework for bursting systems with both subthreshold and superthreshold oscillations. A new class of bursters with at least two slow variables is then added, which we denote folded-node bursters, to convey the idea that the bursts are initiated or annihilated via a folded-node singularity. Key to this mechanism are so-called canard or duck orbits, organizing the underpinning excitability structure. We describe the two main families of folded-node bursters, depending upon the phase (active/spiking or silent/non-spiking) of the bursting cycle during which folded-node dynamics occurs. We classify both families and give examples of minimal systems displaying these novel bursting patterns. Finally, we provide a biophysical example by reinterpreting a generic conductance-based episodic burster as a folded-node burster, showing that the associated framework can explain its subthreshold oscillations over a larger parameter region than the fast-subsystem approach

A modular architecture for transparent computation in recurrent neural networks

publisher: Elsevier articletitle: A modular architecture for transparent computation in recurrent neural networks journaltitle: Neural Networks articlelink: http://dx.doi.org/10.1016/j.neunet.2016.09.001 content_type: article copyright: © 2016 Elsevier Ltd. All rights reserved

Automated Damage Index Estimation of Reinforced Concrete Columns for Post-Earthquake Evaluations

In emergency scenarios, immediate reconnaissance efforts are necessary. These efforts often take months to complete in full. While underway, building occupants are unable to return to their homes/businesses, and thus, the impact on the society of the disaster-stricken region is increased. In order to mitigate the impact, researchers have focused on creating a more efficient means of assessing the condition of buildings in the post-disaster state. In this paper, a machine vision-based methodology for real-time post-earthquake safety assessment is presented. A novel method of retrieving spalled properties on reinforced concrete (RC) columns in RC frame buildings using image data is presented. In this method, the spalled region is detected using a local entropy-based approach. Following this, the depth properties are retrieved using contextual information pertaining to the amount and type of reinforcement which is exposed. The method is validated using a dataset of damaged RC column images.This material is based in part upon work supported by the National Science Foundation under Grant Numbers CMMI-1034845 and CMMI-0738417.This is the accepted manuscript. The final version is available from ASCE at http://dx.doi.org/10.1061/(ASCE)ST.1943-541X.000120

Fragility curves for non-ductile reinforced concrete frames that exhibit different component response mechanisms

Around the world, a large percentage of buildings in regions of high seismicity are older, non-ductile reinforced concrete. To assess the risk posed by these buildings, fragility functions are required to define the likelihood that these buildings will sustain damage and collapse under earthquake loading. This paper presents the initial phase of a research effort to develop fragility functions for non-ductile concrete frames using numerical simulation; the research presented in this paper focuses on development of the numerical model and application of the model to develop fragility functions for a prototype non-ductile concrete frame. To enable numerical simulation of concrete frame buildings, response models for beam–column joints and columns are developed to provide (1) appropriate simulation of component response and, thereby, reliable assessment of risk and (2) computational efficiency and robustness. These new models are developed using existing experimental data, build on response models proposed by others, and employ component and material models available in the OpenSees analysis platform (http://opensees.berkeley.edu). A new beam–column joint model combines a new expression for joint strength and newly developed cyclic response parameters; a new column response model includes a new shear-strength model and newly developed cyclic response parameters. Numerical models of a prototype non-ductile concrete frame are developed that include simulation of one or more of the following characteristics: (1) rigid beam–column joint, (2) nonlinear joint shear response, (3) nonlinear joint shear and bond–slip response, and (4) column shear failure. Dynamic analyses are performed using these frame models and a suite of ground motions; analysis results are used to develop fragility curves. Fragility curves quantify the vulnerability of the frame and provide understanding of the impact of different component failure mechanisms on frame vulnerability.This research was supported by the National Science Foundation under NSF Grant # 1000700.This is the accepted manuscript of a paper published in Engineering Structures (J-S Jeon, LN Lowes, R DesRoches, I Brilakis, Engineering Structures 2015, 85, 127–143

Anticipation via canards in excitable systems

Neurons can anticipate incoming signals by exploiting a physiological mechanism that is not well understood. This article offers a novel explanation on how a receiver neuron can predict the sender’s dynamics in a unidirectionally-coupled configuration, in which both sender and receiver follow the evolution of a multi-scale excitable system. We present a novel theoretical viewpoint based on a mathematical object, called canard, to explain anticipation in excitable systems. We provide a numerical approach, which allows to determine the transient effects of canards. To demonstrate the general validity of canard-mediated anticipation in the context of excitable systems, we illustrate our framework in two examples, a multi-scale radio-wave circuit (the van der Pol model) that inspired a caricature neuronal model (the FitzHugh-Nagumo model) and a biophysical neuronal model (a 2-dimensional reduction of the Hodgkin-Huxley model), where canards act as messengers to the senders’ prediction. We also propose an experimental paradigm that would enable experimental neuroscientists to validate our predictions. We conclude with an outlook to possible fascinating research avenues to further unfold the mechanisms underpinning anticipation. We envisage that our approach can be employed by a wider class of excitable systems with appropriate theoretical extensions.ERC Advanced Grant NerVi no. 227747 Ikerbasque (The Basque Foundation for Science

Inflection, Canards and Folded Singularities in Excitable Systems: Application to a 3D FitzHugh–Nagumo Model

Specific kinds of physical and biological systems exhibit complex Mixed-Mode Oscillations mediated by folded-singularity canards in the context of slow-fast models. The present manuscript revisits these systems, specifically by analysing the dynamics near a folded singularity from the viewpoint of inflection sets of the flow. Originally, the inflection set method was developed for planar systems [Brøns and Bar-Eli in Proc R Soc A 445(1924):305–322, 1994; Okuda in Prog Theor Phys 68(6):1827–1840, 1982; Peng et al. in Philos Trans R Soc A 337(1646):275–289, 1991] and then extended to N-dimensional systems [Ginoux et al. in Int J Bifurc Chaos 18(11):3409–3430, 2008], although not tailored to specific dynamics (e.g. folded singularities). In our previous study, we identified components of the inflection sets that classify several canard-type behaviours in 2D systems [Desroches et al. in J Math Biol 67(4):989– 1017, 2013]. Herein, we first survey the planar approach and show how to adapt it for 3D systems with an isolated folded singularity by considering a suitable reduction of such 3D systems to planar non-autonomous slow-fast systems. This leads us to the computation of parametrized families of inflection sets of one component of that planar (non-autonomous) system, in the vicinity of a folded node or of a folded saddle. We then show that a novel component of the inflection set emerges, which approximates and follows the axis of rotation of canards associated to folded-node and folded-saddle singularities. Finally, we show that a similar inflection-set component occurs in the vicinity of a delayed Hopf bifurcation, a scenario that can arise at the transition between folded node and folded saddle. These results are obtained in the context of a canonical model for folded-singularity canards and subsequently we show it is also applicable to complex slow-fast models. Specifically, we focus the application towards the self-coupled 3D FitzHugh–Nagumo model, but the method is generically applicable to higher-dimensional models with isolated folded singularities, for instance in conductance-based models and other physical-chemical systems.Ikerbasque (The Basque Foundation for Science