Simulation of non-Markovian Processes in BlenX

BlenX is a programming language explicitly designed for modeling biological processes inspired by Beta-binders. The actual framework assumes biochemical interactions being exponentially distributed, i.e., an underlying Markov process is associated with BlenX programs. In this paper we relax this condition by providing formal tools for managing non-Markovian processes within BlenX

Process Calculi Abstractions for Biology

Several approaches have been proposed to model biological systems by means of the formal techniques and tools available in computer science. To mention just a few of them, some representations are inspired by Petri Nets theory, and some other by stochastic processes. A most recent approach consists in interpreting the living entities as terms of process calculi where the behavior of the represented systems can be inferred by applying syntax-driven rules. A comprehensive picture of the state of the art of the process calculi approach to biological modeling is still missing. This paper goes in the direction of providing such a picture by presenting a comparative survey of the process calculi that have been used and proposed to describe the behavior of living entities. This is the preliminary version of a paper that was published in Algorithmic Bioprocesses. The original publication is available at http://www.springer.com/computer/foundations/book/978-3-540-88868-

Formal executable descriptions of biological systems

The similarities between systems of living entities and systems of concurrent processes may support biological experiments in silico. Process calculi offer a formal framework to describe biological systems, as well as to analyse their behaviour, both from a qualitative and a quantitative point of view. A couple of little examples help us in showing how this can be done. We mainly focus our attention on the qualitative and quantitative aspects of the considered biological systems, and briefly illustrate which kinds of analysis are possible. We use a known stochastic calculus for the first example. We then present some statistics collected by repeatedly running the specification, that turn out to agree with those obtained by experiments in vivo. Our second example motivates a richer calculus. Its stochastic extension requires a non trivial machinery to faithfully reflect the real dynamic behaviour of biological systems

Railway bogie stability control from secondary yaw actuators

The idea of active control based upon applying a controllable yaw torque between the body and the two bogies has been studied previously, mainly to try and provide enhanced curving capability. This paper extends the idea by examining the opportunities for using secondary yaw actuators to stabilise a bogie having very soft yaw stiffness between the bogie frame and the wheelsets, the objective being to take advantage of the good curving performance offered by the soft primary yaw stiffness

Active secondary yaw control to improve curving behaviour of a railway vehicle

Active primary / secondary suspensions have been proposed as a means to solve the trade-off between curving and stability which represents a key problem in the design of modern railway vehicles. In particular, one concept proposed for active control of the vehicle’s running behaviour is known as Secondary Yaw Control (SYC) and consists of applying a controllable yaw torque between the carbody and the two bogies. This concept has been studied in the past mainly to enhance the vehicle’s curving ability. This paper extends the idea by examining the implications of designing a bogie with soft yaw stiffness between the bogie frame and the wheelsets and using SYC to provide active stabilisation. To this aim, a state feedback control law is designed according to the LQR and LQG techniques. The paper presents the general concept of active suspension control investigated and the control strategies applied. Then the effectiveness of the proposed actuation concept is investigated by means of numerical simulations performed on mathematical models of the passive and actively controlled vehicles implemented in a fully nonlinear multi-body simulator. Comparisons are performed and benefits assessed between the actively controlled vehicle and the passive one in terms of: non-linear stability in straight track running; and safety and wear in curves