The Dexi-SH* model for a multivariate assessment of agro-ecological sustainability of dairy grazing systems

Dexi-SH* is an ex ante multivariate model for assessing the sustainability of dairy cows grazing systems. This model is composed of three sub-models that evaluate the impact of the systems on: (i) biotic resources; (ii) abiotic resources, and (iii) pollution risks. The structuring of the hierarchical tree was inspired by that of the Masc model. The choice of criteria and their aggregation modalities were discussed within a multi-disciplinary group of scientists. For each cluster, a utility function was established in order to determine weighting and priority functions between criteria. The model can take local and regional conditions and standards into account by adjusting criterion categories to the agroecological context, and the specific views of the decision makers by changing the weighting of criteria

Building safer robots: Safety driven control

In recent years there has been a concerted effort to address many of the safety issues associated with physical human-robot interaction (pHRI). However, a number of challenges remain. For personal robots, and those intended to operate in unstructured environments, the problem of safety is compounded. In this paper we argue that traditional system design techniques fail to capture the complexities associated with dynamic environments. We present an overview of our safety-driven control system and its implementation methodology. The methodology builds on traditional functional hazard analysis, with the addition of processes aimed at improving the safety of autonomous personal robots. This will be achieved with the use of a safety system developed during the hazard analysis stage. This safety system, called the safety protection system, will initially be used to verify that safety constraints, identified during hazard analysis, have been implemented appropriately. Subsequently it will serve as a high-level safety enforcer, by governing the actions of the robot and preventing the control layer from performing unsafe operations. To demonstrate the effectiveness of the design, a series of experiments have been conducted using a MobileRobots PeopleBot. Finally, results are presented demonstrating how faults injected into a controller can be consistently identified and handled by the safety protection system. © The Author(s) 2012

AMPLE: an anytime planning and execution framework for dynamic and uncertain problems in robotics

Acting in robotics is driven by reactive and deliberative reasonings which take place in the competition between execution and planning processes. Properly balancing reactivity and deliberation is still an open question for harmonious execution of deliberative plans in complex robotic applications. We propose a flexible algorithmic framework to allow continuous real-time planning of complex tasks in parallel of their executions. Our framework, named AMPLE, is oriented towards robotic modular architectures in the sense that it turns planning algorithms into services that must be generic, reactive, and valuable. Services are optimized actions that are delivered at precise time points following requests from other modules that include states and dates at which actions are needed. To this end, our framework is divided in two concurrent processes: a planning thread which receives planning requests and delegates action selection to embedded planning softwares in compliance with the queue of internal requests, and an execution thread which orchestrates these planning requests as well as action execution and state monitoring. We show how the behavior of the execution thread can be parametrized to achieve various strategies which can differ, for instance, depending on the distribution of internal planning requests over possible future execution states in anticipation of the uncertain evolution of the system, or over different underlying planners to take several levels into account. We demonstrate the flexibility and the relevance of our framework on various robotic benchmarks and real experiments that involve complex planning problems of different natures which could not be properly tackled by existing dedicated planning approaches which rely on the standard plan-then-execute loop

The influence of viral RNA secondary structure on interactions with innate host cell defences

RNA viruses infecting vertebrates differ fundamentally in their ability to establish persistent infections with markedly different patterns of transmission, disease mechanisms and evolutionary relationships with their hosts. Although interactions with host innate and adaptive responses are complex and persistence mechanisms likely multi-factorial, we previously observed associations between bioinformatically predicted RNA secondary formation in genomes of positive-stranded RNA viruses with their in vivo fitness and persistence. To analyse this interactions functionally, we transfected fibroblasts with non-replicating, non-translated RNA transcripts from RNA viral genomes with differing degrees of genome-scale ordered RNA structure (GORS). Single-stranded RNA transcripts induced interferon-β mediated though RIG-I and PKR activation, the latter associated with rapid induction of antiviral stress granules. A striking inverse correlation was observed between induction of both cellular responses with transcript RNA structure formation that was independent of both nucleotide composition and sequence length. The consistent inability of cells to recognize RNA transcripts possessing GORS extended to downstream differences from unstructured transcripts in expression of TNF-α, other interferon-stimulated genes and induction of apoptosis. This functional association provides novel insights into interactions between virus and host early after infection and provides evidence for a novel mechanism for evading intrinsic and innate immune responses