Simulation methods with extended stability for stiff biochemical kinetics

Background: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows. Results: In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be well-behaved, leading to significantly larger step sizes.Conclusions: The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems.

Characterisation of the LMS200 laser beam under the influence of blockage surfaces. Influence on 3D scanning of tree orchards

The geometric characterisation of tree orchards is a high-precision activity comprising the accurate measurement and knowledge of the geometry and structure of the trees. Different types of sensors can be used to perform this characterisation. In this work a terrestrial LIDAR sensor (SICK LMS200) whose emission source was a 905-nm pulsed laser diode was used. Given the known dimensions of the laser beam cross-section (with diameters ranging from 12 mm at the point of emission to 47.2 mm at a distance of 8 m), and the known dimensions of the elements that make up the crops under study (flowers, leaves, fruits, branches, trunks), it was anticipated that, for much of the time, the laser beam would only partially hit a foreground target/object, with the consequent problem of mixed pixels or edge effects. Understanding what happens in such situations was the principal objective of this work. With this in mind, a series of tests were set up to determine the geometry of the emitted beam and to determine the response of the sensor to different beam blockage scenarios. The main conclusions that were drawn from the results obtained were: (i) in a partial beam blockage scenario, the distance value given by the sensor depends more on the blocked radiant power than on the blocked surface area; (ii) there is an area that influences the measurements obtained that is dependent on the percentage of blockage and which ranges from 1.5 to 2.5 m with respect to the foreground target/object. If the laser beam impacts on a second target/object located within this range, this will affect the measurement given by the sensor. To interpret the information obtained from the point clouds provided by the LIDAR sensors, such as the volume occupied and the enclosing area, it is necessary to know the resolution and the process for obtaining this mesh of points and also to be aware of the problem associated with mixed pixels.