Compact Representation of Photosynthesis Dynamics by Rule-based Models (Full Version)

Traditional mathematical models of photosynthesis are based on mass action kinetics of light reactions. This approach requires the modeller to enumerate all the possible state combinations of the modelled chemical species. This leads to combinatorial explosion in the number of reactions although the structure of the model could be expressed more compactly. We explore the use of rule-based modelling, in particular, a simplified variant of Kappa, to compactly capture and automatically reduce existing mathematical models of photosynthesis. Finally, the reduction procedure is implemented in BioNetGen language and demonstrated on several ODE models of photosynthesis processes. This is an extended version of the paper published in proceedings of 5th International Workshop on Static Analysis and Systems Biology (SASB) 2014.Comment: SASB 2014 full pape

A process algebra for synchronous concurrent constraint programming

Concurrent constraint programming is classically based on asynchronous communication via a shared store. This paper presents new version of the ask and tell primitives which features synchronicity. Our approach is based on the idea of telling new information just in the case that a concurrently running process is asking for it. An operational and an algebraic semantics are defined. The algebraic semantics is proved to be sound and complete with respect to a compositional operational semantics which is also presented in the paper

Robustness Analysis for Value-Freezing Signal Temporal Logic

In our previous work we have introduced the logic STL*, an extension of Signal Temporal Logic (STL) that allows value freezing. In this paper, we define robustness measures for STL* by adapting the robustness measures previously introduced for Metric Temporal Logic (MTL). Furthermore, we present an algorithm for STL* robustness computation, which is implemented in the tool Parasim. Application of STL* robustness analysis is demonstrated on case studies.Comment: In Proceedings HSB 2013, arXiv:1308.572

DiVinE-CUDA - A Tool for GPU Accelerated LTL Model Checking

In this paper we present a tool that performs CUDA accelerated LTL Model Checking. The tool exploits parallel algorithm MAP adjusted to the NVIDIA CUDA architecture in order to efficiently detect the presence of accepting cycles in a directed graph. Accepting cycle detection is the core algorithmic procedure in automata-based LTL Model Checking. We demonstrate that the tool outperforms non-accelerated version of the algorithm and we discuss where the limits of the tool are and what we intend to do in the future to avoid them

Using Strategy Improvement to Stay Alive

We design a novel algorithm for solving Mean-Payoff Games (MPGs). Besides solving an MPG in the usual sense, our algorithm computes more information about the game, information that is important with respect to applications. The weights of the edges of an MPG can be thought of as a gained/consumed energy -- depending on the sign. For each vertex, our algorithm computes the minimum amount of initial energy that is sufficient for player Max to ensure that in a play starting from the vertex, the energy level never goes below zero. Our algorithm is not the first algorithm that computes the minimum sufficient initial energies, but according to our experimental study it is the fastest algorithm that computes them. The reason is that it utilizes the strategy improvement technique which is very efficient in practice

Multi-agent systems as concurrent constraint processes

We present a language Scc for a specication of the direct exchange and/or the global sharing of information in multi-agent systems. Scc is based on concurrent constraint programming paradigm which we modify in such a way that agents can (i) maintain its local private store, (ii) share (read/write) the information in the global store and (iii) communicate with other agents (via multi-party or hand-shake). To justify our proposal we compare Scc to a recently proposed language for the exchange of information in multi-agent systems. Also we provide an operational semantics of Scc. The full semantic treatment is sketched only and done elsewher

Selective Vulnerabilities of N-methyl-D-aspartate (NMDA) Receptors During Brain Aging

N-methyl-D-aspartate (NMDA) receptors are present in high density within the cerebral cortex and hippocampus and play an important role in learning and memory. NMDA receptors are negatively affected by aging, but these effects are not uniform in many different ways. This review discusses the selective age-related vulnerabilities of different binding sites of the NMDA receptor complex, different subunits that comprise the complex, and the expression and functions of the receptor within different brain regions. Spatial reference, passive avoidance, and working memory, as well as place field stability and expansion all involve NMDA receptors. Aged animals show deficiencies in these functions, as compared to young, and some studies have identified an association between age-associated changes in the expression of NMDA receptors and poor memory performance. A number of diet and drug interventions have shown potential for reversing or slowing the effects of aging on the NMDA receptor. On the other hand, there is mounting evidence that the NMDA receptors that remain within aged individuals are not always associated with good cognitive functioning. This may be due to a compensatory response of neurons to the decline in NMDA receptor expression or a change in the subunit composition of the remaining receptors. These studies suggest that developing treatments that are aimed at preventing or reversing the effects of aging on the NMDA receptor may aid in ameliorating the memory declines that are associated with aging. However, we need to be mindful of the possibility that there may also be negative consequences in aged individuals

The tropical shadow-vertex algorithm solves mean payoff games in polynomial time on average

We introduce an algorithm which solves mean payoff games in polynomial time on average, assuming the distribution of the games satisfies a flip invariance property on the set of actions associated with every state. The algorithm is a tropical analogue of the shadow-vertex simplex algorithm, which solves mean payoff games via linear feasibility problems over the tropical semiring $(\mathbb{R} \cup \{-\infty\}, \max, +)$. The key ingredient in our approach is that the shadow-vertex pivoting rule can be transferred to tropical polyhedra, and that its computation reduces to optimal assignment problems through Pl\"ucker relations.Comment: 17 pages, 7 figures, appears in 41st International Colloquium, ICALP 2014, Copenhagen, Denmark, July 8-11, 2014, Proceedings, Part