559 research outputs found

    A New Simulation Metric to Determine Safe Environments and Controllers for Systems with Unknown Dynamics

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    We consider the problem of extracting safe environments and controllers for reach-avoid objectives for systems with known state and control spaces, but unknown dynamics. In a given environment, a common approach is to synthesize a controller from an abstraction or a model of the system (potentially learned from data). However, in many situations, the relationship between the dynamics of the model and the \textit{actual system} is not known; and hence it is difficult to provide safety guarantees for the system. In such cases, the Standard Simulation Metric (SSM), defined as the worst-case norm distance between the model and the system output trajectories, can be used to modify a reach-avoid specification for the system into a more stringent specification for the abstraction. Nevertheless, the obtained distance, and hence the modified specification, can be quite conservative. This limits the set of environments for which a safe controller can be obtained. We propose SPEC, a specification-centric simulation metric, which overcomes these limitations by computing the distance using only the trajectories that violate the specification for the system. We show that modifying a reach-avoid specification with SPEC allows us to synthesize a safe controller for a larger set of environments compared to SSM. We also propose a probabilistic method to compute SPEC for a general class of systems. Case studies using simulators for quadrotors and autonomous cars illustrate the advantages of the proposed metric for determining safe environment sets and controllers.Comment: 22nd ACM International Conference on Hybrid Systems: Computation and Control (2019

    A Map-Reduce Parallel Approach to Automatic Synthesis of Control Software

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    Many Control Systems are indeed Software Based Control Systems, i.e. control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for automatic synthesis of control software. Available algorithms and tools (e.g., QKS) may require weeks or even months of computation to synthesize control software for large-size systems. This motivates search for parallel algorithms for control software synthesis. In this paper, we present a Map-Reduce style parallel algorithm for control software synthesis when the controlled system (plant) is modeled as discrete time linear hybrid system. Furthermore we present an MPI-based implementation PQKS of our algorithm. To the best of our knowledge, this is the first parallel approach for control software synthesis. We experimentally show effectiveness of PQKS on two classical control synthesis problems: the inverted pendulum and the multi-input buck DC/DC converter. Experiments show that PQKS efficiency is above 65%. As an example, PQKS requires about 16 hours to complete the synthesis of control software for the pendulum on a cluster with 60 processors, instead of the 25 days needed by the sequential algorithm in QKS.Comment: To be submitted to TACAS 2013. arXiv admin note: substantial text overlap with arXiv:1207.4474, arXiv:1207.409

    Attention and empirical studies of grammar

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    GAPPS (Grading and Assessment of Pharmacokinetic-Pharmacodynamic Studies) a critical appraisal system for antimicrobial PKPD studies - development and application in pediatric antibiotic studies

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    Introduction: There are limited data on optimal dosing of antibiotics in different age groups for neonates and children. Clinicians usually consult pediatric formularies or online databases for dose selection, but these have variable recommendations, are usually based on expert opinion and are not graded based on the existing pharmacokinetic-pharmacodynamic (PKPD) studies. We describe here a potential new tool that could be used to grade the strength of evidence emanating from PKPD studies. Areas covered: A scoring system was developed (GAPPS tool) to quantify the strength of each PK assessment and rate the studies quality in already published articles. GAPPS was evaluated by applying it to pediatric PKPD studies of antibiotics from the 2019 Essential Medicines List for children (EMLC), identified through a search of PubMed. Expert opinion: Evidence for most antibiotic dose selection decisions was generally weak, coming from individual PK studies and lacked PKPD modeling and simulations. However, the quality of evidence appears to have improved over the last two decades. Incorporating a formal grading system, such as GAPPS, into formulary development will provide a transparent tool to support decision-making in clinical practice and guideline development, and guide PKPD authors on study designs most likely to influence guidelines

    Predicting Phenotypic Diversity and the Underlying Quantitative Molecular Transitions

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    During development, signaling networks control the formation of multicellular patterns. To what extent quantitative fluctuations in these complex networks may affect multicellular phenotype remains unclear. Here, we describe a computational approach to predict and analyze the phenotypic diversity that is accessible to a developmental signaling network. Applying this framework to vulval development in C. elegans, we demonstrate that quantitative changes in the regulatory network can render ~500 multicellular phenotypes. This phenotypic capacity is an order-of-magnitude below the theoretical upper limit for this system but yet is large enough to demonstrate that the system is not restricted to a select few outcomes. Using metrics to gauge the robustness of these phenotypes to parameter perturbations, we identify a select subset of novel phenotypes that are the most promising for experimental validation. In addition, our model calculations provide a layout of these phenotypes in network parameter space. Analyzing this landscape of multicellular phenotypes yielded two significant insights. First, we show that experimentally well-established mutant phenotypes may be rendered using non-canonical network perturbations. Second, we show that the predicted multicellular patterns include not only those observed in C. elegans, but also those occurring exclusively in other species of the Caenorhabditis genus. This result demonstrates that quantitative diversification of a common regulatory network is indeed demonstrably sufficient to generate the phenotypic differences observed across three major species within the Caenorhabditis genus. Using our computational framework, we systematically identify the quantitative changes that may have occurred in the regulatory network during the evolution of these species. Our model predictions show that significant phenotypic diversity may be sampled through quantitative variations in the regulatory network without overhauling the core network architecture. Furthermore, by comparing the predicted landscape of phenotypes to multicellular patterns that have been experimentally observed across multiple species, we systematically trace the quantitative regulatory changes that may have occurred during the evolution of the Caenorhabditis genus

    Risk Assessment of a Synthetic Pyrethroid, Bifenthrin on Pulses

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    This work was undertaken to determine the pre-harvest interval of bifenthrin and to minimize its residues in pulses and thereby ensure consumer safety and avoid non-compliance in terms of residues violations in export market. Furthermore the residue dynamics in the soil under pulses was explored to assess the environmental safety. The residues of bifenthrin dissipated following first order kinetics. The residues in harvest time grains were below the maximum residue limit (MRL) of 0.02 mg/kg applicable for European Union. In soil the degradation rate was fast with a half life of 2–3 days. This work is of high practical significance to the domestic and export pulse industry of India to ensure safety compliance in respect of bifenthrin residues, keeping in view the requirements of international trade
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