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Mechanisms terminating phytoplankton blooms are often not well understood. Potentially involved processes such as consumption by grazers, flocculation, and viral lysis each have different post-bloom consequences on the processing of the organic material, therefore it is important to develop a better understanding of the relevance of these processes, and potential interactions between them. In this study, we present a model-based analysis of a spring bloom observed in a mesocosm experiment. The intermediate-complexity (27-state variable) numerical model we extended from an earlier version to this end can resolve C, N, P and Si cycles, and relevant processes like formation of various organic material size classes (low and high molecular weight (hereafter small and large) dissolved organic carbon (DOC), transparent exopolymer particles (TEP), and small/large detritus) and their degradation by two bacterial sub-communities (free-living and particle-attached) and planktonic protists (heterotrophic flagellates and ciliates). The model can explain > 90% of the variation of a rich set of observations consisting of 11 independent variables over the course of 13 days during which a bloom largely dominated by diatoms develops, and disappears almost entirely. Fluxes estimated by the model point to the importance of coagulation (TEP formation) as a sink term for DOC, and a source term for POC. Consequently, aggregation with TEPs constitute an important loss term for phytoplankton. The flocculated phytoplankton, and detrital material, in turn become rapidly degraded by the particle attached bacteria and other protist heterotrophs. Through a scenario analysis, the relevance of nutrient-stress enhanced lysis rates; alterations between small and large DOC in phytoplankton exudates; and coagulation of smaller DOC molecules were investigated. Our results suggest that the former two processes have negligible effects in isolation, but when combined with the latter, they can synergistically cause substantial deviations in TEP formation, hence, in flocculation rates; and consequently in the peak magnitude of the diatom bloom, and in timing of its termination. Our results point to a need for better understanding of processes governing the termination of phytoplankton blooms, their inter-dependencies, and consequences on the global biogeochemical cycles.

A distinguishing feature of many ecological networks in the microbial realm is the diversity of substrates that could potentially serve as energy sources for microbial consumers. The microorganisms are themselves the agents of compound diversification via metabolite excretion or overflow metabolism. It has been suggested that the emerging richness of different substrates is an important condition for the immense biological diversity in microbial ecosystems. In this work, we study how complex cross-feeding networks (CFN) of microbial species may develop from a simple initial community given some elemental evolutionary mechanisms of resource-dependent speciation and extinctions using a network flow model. We report results of several numerical experiments and report an in-depth analysis of the evolutionary dynamics. We find that even in stable environments, the system is subject to persisting turnover, indicating an ongoing co-evolution. Further, we compare the impact of different parameters, such as the ratio of mineralization, as well as the metabolic versatility and variability on the evolving community structure. The results imply that high microbial and molecular diversity is an emergent property of evolution in cross-feeding networks, which affects transformation and accumulation of substrates in natural systems, such as soils and oceans, with potential relevance to biotechnological applications.

In this note we discuss the usage of the Dirac $\delta$ function in models of phase oscillators with pulsatile inputs. Many authors use a product of the delta function and the phase response curve in the right hand side of an ODE to describe the discontinuous phase dynamics in such systems. We point out that this notation has to be treated with care as it is ambiguous. We argue that the presumably most canonical interpretation does not lead to the intended behaviour in many cases., Comment: a serious flaw in the paper

Coupling delays may cause drastic changes in the dynamics of oscillatory networks. In the present paper we investigate how coupling delays alter synchronization processes in networks of all-to-all coupled pulse oscillators. We derive an analytic criterion for the stability of synchrony and study the synchronization areas in the space of the delay and coupling strength. Specific attention is paid to the scenario of destabilization on the borders of the synchronization area. We show that in bifurcation points the system possesses homoclinic loops, which give rise to complex long- or quasi-periodic solutions. These newly born solutions are characterized by a synchronous group, from which an oscillator periodically escapes, laps one period, and rejoins. We call such a dynamical regime “phase slip patterns”.

Highway work zones can induce significant delays and undermine traffic safety. The recent advent of connected and automated vehicles (CAVs) can pose an additional threat to traffic flow performance and safety around highway work zones. CAVs equipped with low – medium level automation systems that cannot reliably address work zone scenarios under all circumstances could induce control transitions and imminent Minimum Risk Manoeuvers (MRMs) that would result in significant traffic disruption and multiple safety critical events. The latter negative effects could be mitigated via the introduction of highly automated vehicles that could utilize sophisticated infrastructure assistance to traverse highway work zones without disengaging automation systems. This study develops novel and utilizes existing vehicle-driver models to simulate manual driving, mixed traffic and infrastructure-assisted highly automated traffic around highway work zones. Traffic operations are evaluated for the latter fleet mixes and three different traffic demand levels. Simulation results indicate that joint deployment of infrastructure-assisted traffic management and cooperative driving can ensure increased traffic efficiency and safety levels for high traffic intensity in a fully connected and automated road environment.

This chapter investigates TA scenarios and performs simulations. In order to start the simulations, several preparatory steps were made. At first, scenarios had to be defined. As capabilities of future AVs are difficult to foresee and as the problem has several dimensions, it has been decided to use service definitions (i.e. the kind of possible infrastructure influences) as the main criterion for clustering the dimensions. Five services have been proposed and converted into five scenarios. In order to perform baseline simulations of the five scenarios, vehicle models had to be chosen and even newly developed, so that simulation of AVs and the TOC became possible. The models needed to be parametrized according to estimations of future traffic shares, future number of TOR, TOC, and MRM. This chapter highlights the measured effects in one of the studied scenarios. It also explains how simulations get more sophisticated and realistic by using the iTETRIS-integrated platform for traffic simulation, communication, and TM. Furthermore, the plans for performing real-world feasibility assessments including V2X message set definitions have been introduced, closing this first report.

Transitions of Control (ToC) play an important role in the simulative impact assessment of automated driving because they may represent major perturbations of smooth and safe traffic operation. The drivers' efforts to take back control from the automation are accompanied by a change of driving behavior and may lead to increased error rates, altered headways, safety critical situations, and, in the case of a failing takeover, even to minimum risk maneuvers. In this work we present modeling approaches for these processes, which have been introduced into SUMO recently in the framework of the TransAID project. Further, we discuss the results of an evaluation of some hierarchical traffic management (TM) procedures devised to ameliorate related disturbances in transition areas, i.e., zones of increased probability for the automation to request a ToC.

Microscopic traffic simulation is an invaluable tool for traffic research. In recent years, both the scope of research and the capabilities of the tools have been extended considerably. This article presents the latest developments concerning intermodal traffic solutions, simulator coupling and model development and validation on the example of the open source traffic simulator SUMO.

The subject of the paper is scalar delay-differential equations with large delay. Firstly, we describe the asymptotic properties of the spectrum of linear equations. Using these properties, we classify possible types of destabilization of steady states. In the limit of large delay, this classification is similar to the one for parabolic partial differential equations. We present a derivation and error estimates for amplitude equations, which describe universally the local behavior of scalar delay-differential equations close to the destabilization threshold.

In oscillatory systems with pulse coupling regular spiking regimes may destabilize via a peculiar scenario called “multi-jitter instability”. At the bifurcation point numerous so-called “jittering” regimes with distinct inter-spike intervals emerge simultaneously. Such regimes were first discovered in a single oscillator with delayed pulse feedback and later were found in networks of coupled oscillators. The present chapter reviews recent results on multi-jitter instability and discussed its features.

We consider the recurrent pulse-coupled networks of excitable elements with delayed connections, which are inspired by the biological neural networks. If the delays are tuned appropriately, the network can either stay in the steady resting state, or alternatively, exhibit a desired spiking pattern. It is shown that such a network can be used as a pattern-recognition system. More specifically, the application of the correct pattern as an external input to the network leads to a self-sustained reverberation of the encoded pattern. In terms of the coupling structure, the tolerance and the refractory time of the individual systems, we determine the conditions for the uniqueness of the sustained activity, i.e., for the functionality of the network as an unambiguous pattern detector. We point out the relation of the considered systems with cyclic polychronous groups and show how the assumed delay configurations may arise in a self-organized manner when a spike-time dependent plasticity of the connection delays is assumed. As excitable elements, we employ the simplistic coincidence detector models as well as the Hodgkin-Huxley neuron models. Moreover, the system is implemented experimentally on a Field-Programmable Gate Array.

A new type of chimera-like regime is reported that we call “jittering chimera”. The regime is observed in a ring of excitable units in which the excitation is invoked by an oscillator included into the ring. The jittering chimera is characterized by the presence of two domains, one with regular spiking and the other with irregular. A method to set and control desired chimera states in a physically implemented electronic circuit is developed.

Spike timing-dependent plasticity is a fundamental adaptation mechanism of the nervous system. It induces structural changes of synaptic connectivity by regulation of coupling strengths between individual cells depending on their spiking behavior. As a biophysical process its functioning is constantly subjected to natural fluctuations. We study theoretically the influence of noise on a microscopic level by considering only two coupled neurons. Adopting a phase description for the neurons we derive a two-dimensional system which describes the averaged dynamics of the coupling strengths. We show that a multistability of several coupling configurations is possible, where some configurations are not found in systems without noise. Intriguingly, it is possible that a strong bidirectional coupling, which is not present in the noise-free situation, can be stabilized by the noise. This means that increased noise, which is normally expected to desynchronize the neurons, can be the reason for an antagonistic response of the system, which organizes itself into a state of stronger coupling and counteracts the impact of noise. This mechanism, as well as a high potential for multistability, is also demonstrated numerically for a coupled pair of Hodgkin-Huxley neurons.

International audience; In this article we study networks of coupled dynamical systems with time-delayed connections. If two such networks hold different delays on the connections it is in general possible that they exhibit different dynamical behavior as well. We prove that for particular sets of delays this is not the case. To this aim we introduce a componentwise timeshift transformation (CTT) which allows to classify systems which possess equivalent dynamics, though possibly different sets of connection delays. In particular, we show for a large class of semiflows (including the case of delay differential equations) that the stability of attractors is invariant under this transformation. Moreover we show that each equivalence class which is mediated by the CTT possesses a representative system in which the number of different delays is not larger than the cycle space dimension of the underlying graph. We conclude that the 'true' dimension of the corresponding parameter space of delays is in general smaller than it appears at first glance.

We study the destabilization mechanism in a unidirectional ring of identical oscillators, perturbed by the introduction of a long-range connection. It is known that for a homogeneous, unidirectional ring of identical Stuart-Landau oscillators the trivial equilibrium undergoes a sequence of Hopf bifurcations eventually leading to the coexistence of multiple stable periodic states resembling the Eckhaus scenario. We show that this destabilization scenario persists under small non-local perturbations. In this case, the Eckhaus line is modulated according to certain resonance conditions. In the case when the shortcut is strong, we show that the coexisting periodic solutions split up into two groups. The first group consists of orbits which are unstable for all parameter values, while the other one shows the classical Eckhaus behavior.

Interaction via pulses is common in many natural systems, especially neuronal. In this article we study one of the simplest possible systems with pulse interaction: a phase oscillator with delayed pulsatile feedback. When the oscillator reaches a specific state, it emits a pulse, which returns after propagating through a delay line. The impact of an incoming pulse is described by the oscillator's phase reset curve (PRC). In such a system we discover an unexpected phenomenon: for a sufficiently steep slope of the PRC, a periodic regular spiking solution bifurcates with several multipliers crossing the unit circle at the same parameter value. The number of such critical multipliers increases linearly with the delay and thus may be arbitrary large. This bifurcation is accompanied by the emergence of numerous "jittering" regimes with non-equal interspike intervals (ISIs). Each of these regimes corresponds to a periodic solution of the system with a period roughly proportional to the delay. The number of different "jittering" solutions emerging at the bifurcation point increases exponentially with the delay. We describe the combinatorial mechanism that underlies the emergence of such a variety of solutions. In particular, we show how a periodic solution exhibiting several distinct ISIs can imply the existence of multiple other solutions obtained by rearranging of these ISIs. We show that the theoretical results for phase oscillators accurately predict the behavior of an experimentally implemented electronic oscillator with pulsatile feedback.

Oscillatory systems with time-delayed pulsatile feedback appear in various applied and theoretical research areas, and received a growing interest in the last years. For such systems, we report a remarkable scenario of destabilization of a periodic regular spiking regime. In the bifurcation point numerous regimes with non-equal interspike intervals emerge simultaneously. We show that this bifurcation is triggered by the steepness of the oscillator's phase resetting curve and that the number of the emerging, so-called "jittering" regimes grows exponentially with the delay value. Although this appears as highly degenerate from a dynamical systems viewpoint, the "multi-jitter" bifurcation occurs robustly in a large class of systems. We observe it not only in a paradigmatic phase-reduced model, but also in a simulated Hodgkin-Huxley neuron model and in an experiment with an electronic circuit.

The subject of this paper is a system of phase-oscillators, which are globally pulse-coupled via excitatory interaction. The appearance and stability of one- and two-cluster-states is investigated for a family of unimodal phase-response-curves (PRC). The PRCs and their derivatives are assumed to be zero at the spiking point. We show that there exist stable homoclinic connections of the one-cluster state for PRCs with the maximum located shortly before the spiking point and coexisting stable two-clusters states when the maximum of the PRC is located shortly after the spike.

For a system of globally pulse-coupled phase-oscillators, we derive conditions for stability of the completely synchronous state and all possible two-cluster states and explain how the different states are naturally connected via bifurcations. The coupling is modeled using the phase-response-curve (PRC), which measures the sensitivity of each oscillator's phase to perturbations. For large systems with a PRC, which turns to zero at the spiking threshold, we are able to find the parameter regions where multiple stable two-cluster states coexist and illustrate this by an example. In addition, we explain how a locally unstable one-cluster state may form an attractor together will its homoclinic connections. This leads to the phenomenon of intermittent, asymptotic synchronization with abating beats away from the perfect synchrony., 12 pages. 6 figures

Connected and automated vehicles can exploit V2X communications to coordinate their maneuvers and improve the traffic safety and efficiency. To support such coordination, ETSI is currently defining the Maneuver Coordination Service (MCS). The current approach is based on a distributed solution where vehicles coordinate their maneuvers using V2V (Vehicle-to-Vehicle) communications. This paper proposes to extend this concept by adding the possibility for the infrastructure to support cooperative maneuvers using V2I (Vehicle-to-Infrastructure) communications. To this aim, we propose a Maneuver Coordination Message (MCM) that can be used in cooperative maneuvers with or without road infrastructure support. First results show the gains that cooperative maneuvers can achieve thanks to the infrastructure support. This paper also analyses and discusses the need to define MCM generation rules that decide when MCM messages should be exchanged. These rules have an impact on the effectiveness of cooperative maneuvers and on the operation and scalability of the V2X network.