Scalable Verification of Linear Controller Software

We consider the problem of verifying software implementations of linear time-invariant controllers against mathematical specifications. Given a controller specification, multiple correct implementations may exist, each of which uses a different representation of controller state (e.g., due to optimizations in a third-party code generator). To accommodate this variation, we first extract a controller\u27s mathematical model from the implementation via symbolic execution, and then check input-output equivalence between the extracted model and the specification by similarity checking. We show how to automatically verify the correctness of C code controller implementation using the combination of techniques such as symbolic execution, satisfiability solving and convex optimization. Through evaluation using randomly generated controller specifications of realistic size, we demonstrate that the scalability of this approach has significantly improved compared to our own earlier work based on the invariant checking method

Towards the Verification of Hybrid Co-simulation Algorithms

International audienceEngineering modern, hybrid systems is becoming increasingly difficult due to the heterogeneity between different subsystems. Modelling and simulation techniques have traditionally been used to tackle complexity, but with increasing heterogeneity of the subsystems, it becomes impossible to find appropriate modelling languages and tools to specify and analyse the system as a whole. Co-simulation is a technique to combine multiple models and their simulators in order to analyse the behaviour of the whole system over time. Past research, however, has shown that the na¨ıvena¨ıve combination of simulators can easily lead to incorrect simulation results, especially when co-simulating hybrid systems. This paper shows (i) how co-simulation of a family of hybrid systems can fail to reproduce the order of events that should have occurred (event ordering); (ii) how to prove that a co-simulation algorithm is correct (w.r.t. event ordering), and if it is incorrect, how to obtain a counterexample showing how the co-simulation fails; and (iii) how to correct an incorrect co-simulation algorithm. We apply the above method to two well known co-simulation algorithms used with the FMI Standard, and we show that one of them is incorrect for the family of hybrid systems under study, under the restrictions of the standard. The conclusion is that either the standard needs to be revised, or one of the algorithms should be avoided

A theory of how active behavior stabilises neural activity: neural gain modulation by closed-loop environmental feedback

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone

Addressing vulnerability, building resilience:community-based adaptation to vector-borne diseases in the context of global change

Abstract Background The threat of a rapidly changing planet – of coupled social, environmental and climatic change – pose new conceptual and practical challenges in responding to vector-borne diseases. These include non-linear and uncertain spatial-temporal change dynamics associated with climate, animals, land, water, food, settlement, conflict, ecology and human socio-cultural, economic and political-institutional systems. To date, research efforts have been dominated by disease modeling, which has provided limited practical advice to policymakers and practitioners in developing policies and programmes on the ground. Main body In this paper, we provide an alternative biosocial perspective grounded in social science insights, drawing upon concepts of vulnerability, resilience, participation and community-based adaptation. Our analysis was informed by a realist review (provided in the Additional file 2) focused on seven major climate-sensitive vector-borne diseases: malaria, schistosomiasis, dengue, leishmaniasis, sleeping sickness, chagas disease, and rift valley fever. Here, we situate our analysis of existing community-based interventions within the context of global change processes and the wider social science literature. We identify and discuss best practices and conceptual principles that should guide future community-based efforts to mitigate human vulnerability to vector-borne diseases. We argue that more focused attention and investments are needed in meaningful public participation, appropriate technologies, the strengthening of health systems, sustainable development, wider institutional changes and attention to the social determinants of health, including the drivers of co-infection. Conclusion In order to respond effectively to uncertain future scenarios for vector-borne disease in a changing world, more attention needs to be given to building resilient and equitable systems in the present

Dynamic metabolic control: towards precision engineering of metabolism

Advances in metabolic engineering have led to the synthesis of a wide variety of valuable chemicals in microorganisms. The key to commercializing these processes is the improvement of titer, productivity, yield, and robustness. Traditional approaches to enhancing production use the “push–pull-block” strategy that modulates enzyme expression under static control. However, strains are often optimized for specific laboratory set-up and are sensitive to environmental fluctuations. Exposure to sub-optimal growth conditions during large-scale fermentation often reduces their production capacity. Moreover, static control of engineered pathways may imbalance cofactors or cause the accumulation of toxic intermediates, which imposes burden on the host and results in decreased production. To overcome these problems, the last decade has witnessed the emergence of a new technology that uses synthetic regulation to control heterologous pathways dynamically, in ways akin to regulatory networks found in nature. Here, we review natural metabolic control strategies and recent developments in how they inspire the engineering of dynamically regulated pathways. We further discuss the challenges of designing and engineering dynamic control and highlight how model-based design can provide a powerful formalism to engineer dynamic control circuits, which together with the tools of synthetic biology, can work to enhance microbial production