Quantitative reactive modeling and verification

Formal verification aims to improve the quality of software by detecting errors before they do harm. At the basis of formal verification is the logical notion of correctness, which purports to capture whether or not a program behaves as desired. We suggest that the boolean partition of software into correct and incorrect programs falls short of the practical need to assess the behavior of software in a more nuanced fashion against multiple criteria. We therefore propose to introduce quantitative fitness measures for programs, specifically for measuring the function, performance, and robustness of reactive programs such as concurrent processes. This article describes the goals of the ERC Advanced Investigator Project QUAREM. The project aims to build and evaluate a theory of quantitative fitness measures for reactive models. Such a theory must strive to obtain quantitative generalizations of the paradigms that have been success stories in qualitative reactive modeling, such as compositionality, property-preserving abstraction and abstraction refinement, model checking, and synthesis. The theory will be evaluated not only in the context of software and hardware engineering, but also in the context of systems biology. In particular, we will use the quantitative reactive models and fitness measures developed in this project for testing hypotheses about the mechanisms behind data from biological experiments

LNCS

In the analysis of reactive systems a quantitative objective assigns a real value to every trace of the system. The value decision problem for a quantitative objective requires a trace whose value is at least a given threshold, and the exact value decision problem requires a trace whose value is exactly the threshold. We compare the computational complexity of the value and exact value decision problems for classical quantitative objectives, such as sum, discounted sum, energy, and mean-payoff for two standard models of reactive systems, namely, graphs and graph games

Early maturation processes in coal. Part 1: Pyrolysis mass balances and structural evolution of coalified wood from the Morwell Brown Coal seam

In this work, we develop a theoretical approach to evaluate maturation process of kerogen-like material, involving molecular dynamic reactive modeling with a reactive force field to simulate the thermal stress. The Morwell coal has been selected to study the thermal evolution of terrestrial organic matter. To achieve this, a structural model is first constructed based on models from the literature and analytical characterization of our samples by modern 1-and 2-D NMR, FTIR, and elemental analysis. Then, artificial maturation of the Morwell coal is performed at low conversions in order to obtain, quantitative and qualitative, detailed evidences of structural evolution of the kerogen upon maturation. The observed chemical changes are a defunctionalization of the carboxyl, carbonyl and methoxy functional groups coupling with an increase of cross linking in the residual mature kerogen. Gaseous and liquids hydrocarbons, essentially CH4, C4H8 and C14+ liquid hydrocarbons, are generated in low amount, merely by cleavage of the lignin side chain

Diagnostic techniques in deflagration and detonation studies

Advances in experimental, high-speed techniques can be used to explore the processes occurring within energetic materials. This review describes techniques used to study a wide range of processes: hot-spot formation, ignition thresholds, deflagration, sensitivity and finally the detonation process. As this is a wide field the focus will be on small-scale experiments and quantitative studies. It is important that such studies are linked to predictive models, which inform the experimental design process. The stimuli range includes, thermal ignition, drop-weight, Hopkinson Bar and Plate Impact studies. Studies made with inert simulants are also included as these are important in differentiating between reactive response and purely mechanical behaviour

Looking at Mean-Payoff through Foggy Windows

Mean-payoff games (MPGs) are infinite duration two-player zero-sum games played on weighted graphs. Under the hypothesis of perfect information, they admit memoryless optimal strategies for both players and can be solved in NP-intersect-coNP. MPGs are suitable quantitative models for open reactive systems. However, in this context the assumption of perfect information is not always realistic. For the partial-observation case, the problem that asks if the first player has an observation-based winning strategy that enforces a given threshold on the mean-payoff, is undecidable. In this paper, we study the window mean-payoff objectives that were introduced recently as an alternative to the classical mean-payoff objectives. We show that, in sharp contrast to the classical mean-payoff objectives, some of the window mean-payoff objectives are decidable in games with partial-observation

Theory of weakly nonlinear self sustained detonations

We propose a theory of weakly nonlinear multi-dimensional self sustained detonations based on asymptotic analysis of the reactive compressible Navier-Stokes equations. We show that these equations can be reduced to a model consisting of a forced, unsteady, small disturbance, transonic equation and a rate equation for the heat release. In one spatial dimension, the model simplifies to a forced Burgers equation. Through analysis, numerical calculations and comparison with the reactive Euler equations, the model is demonstrated to capture such essential dynamical characteristics of detonations as the steady-state structure, the linear stability spectrum, the period-doubling sequence of bifurcations and chaos in one-dimensional detonations and cellular structures in multi- dimensional detonations

Early Gabapentin Treatment during the Latency Period Increases Convulsive Threshold, Reduces Microglial Activation and Macrophage Infiltration in the Lithium-Pilocarpine Model of Epilepsy

The lithium-pilocarpine model of epilepsy reproduces several features of temporal lobe epilepsy in humans, including the chronological timeline of an initial latency period followed by the development of spontaneous seizures. Epilepsy therapies in humans are implemented, as a rule, after the onset of the spontaneous seizures. We here studied the potential effect on epileptogenesis of starting an early treatment during the latency period, in order to prevent the development of spontaneous seizures. Adult male Wistar rats were treated with 3 mEq/kg LiCl, and 20 h later 30 mg/kg pilocarpine. Once status epilepticus (SE) was achieved, it was allowed to last for 20 min, and then motor seizures were controlled with the administration of 20 mg/kg diazepam. At 1DPSE (DPSE, days post-status epilepticus), animals started to receive 400 mg/kg/day gabapentin or saline for 4 days. At 5DPSE, we observed that SE induced an early profuse microglial and astroglial reactivity, increased synaptogenic trombospondin-1 expression and reduced AQP4 expression in astroglial ending feet. Blood brain barrier (BBB) integrity seemed to be compromised, as infiltrating NG2+ macrophages and facilitated access to the CNS was observed by transplanting eGFP+ blood cells and bone marrow-derived progenitors in the SE animals. The early 4-day gabapentin treatment successfully reduced microglial cell reactivity and blood-borne cell infiltration, without significantly altering the mRNA of proinflammatory cytokines IL-1β and TNFα immediately after the treatment. After 21DSPE, another group of animals that developed SE and received 4 days of gabapentin treatment, were re-exposed to subconvulsive accumulative doses of pilocarpine (10 mg/kg/30 min) and were followed by recording the Racine scale reached. Early 4-day gabapentin treatment reduced the Racine scale reached by the animals, reduced animal mortality, and reduced the number of animals that achieved SE (34% vs. 72%). We conclude that early gabapentin treatment following SE, during the latency period, is able to reduce neuroinflammation and produces a persistent effect that limits seizures and increases convulsive threshold, probably by restricting microglial reactivity and spurious synaptogenesis.Fil: Rossi, Alicia Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia ; ArgentinaFil: Murta, Verónica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia ; ArgentinaFil: Auzmendi, Jerónimo Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia ; ArgentinaFil: Ramos, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia ; Argentin

A uniform framework for modelling nondeterministic, probabilistic, stochastic, or mixed processes and their behavioral equivalences

Labeled transition systems are typically used as behavioral models of concurrent processes, and the labeled transitions define the a one-step state-to-state reachability relation. This model can be made generalized by modifying the transition relation to associate a state reachability distribution, rather than a single target state, with any pair of source state and transition label. The state reachability distribution becomes a function mapping each possible target state to a value that expresses the degree of one-step reachability of that state. Values are taken from a preordered set equipped with a minimum that denotes unreachability. By selecting suitable preordered sets, the resulting model, called ULTraS from Uniform Labeled Transition System, can be specialized to capture well-known models of fully nondeterministic processes (LTS), fully probabilistic processes (ADTMC), fully stochastic processes (ACTMC), and of nondeterministic and probabilistic (MDP) or nondeterministic and stochastic (CTMDP) processes. This uniform treatment of different behavioral models extends to behavioral equivalences. These can be defined on ULTraS by relying on appropriate measure functions that expresses the degree of reachability of a set of states when performing single-step or multi-step computations. It is shown that the specializations of bisimulation, trace, and testing equivalences for the different classes of ULTraS coincide with the behavioral equivalences defined in the literature over traditional models