Probability distributed time delays: integrating spatial effects into temporal models

Background In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive. Results We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation. Conclusions Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere.

Intelligent distribution planning and control incorporating microgrids

This paper proposes a comprehensive approach to the planning of distribution networks and the control of microgrids. Firstly, a Modified Discrete Particle Swarm Optimization (MDPSO) method is used to optimally plan a distribution system upgrade over a 20 year planning period. The optimization is conducted at different load levels according to the anticipated load duration curve and integrated over the system lifetime in order to minimize its total lifetime cost. Since the optimal solution contains Distributed Generators (DGs) to maximize reliability, the DG must be able to operate in islanded mode and this leads to the concept of microgrids. Thus the second part of the paper reviews some of the challenges of microgrid control in the presence of both inertial (rotating direct connected) and non-inertial (converter interfaced) DGs. More specifically enhanced control strategies based on frequency droop are proposed for DGs to improve the smooth synchronization and real power sharing minimizing transient oscillations in the microgrid. Simulation studies are presented to show the effectiveness of the control.

The probability archive : essence, uncertainty, and the ‘Olduvai imperative.’

Starting from a local problem with finding an archival clip on YouTube, this paper expands to consider the nature of archives in general. It considers the technological, communicative and philosophical characteristics of archives over three historical periods: 1) Modern ‘essence archives’ – museums and galleries organised around the concept of objectivity and realism; 2) Postmodern mediation archives – broadcast TV systems, which I argue were also ‘essence archives,’ albeit a transitional form; and 3) Network or ‘probability archives’ – YouTube and the internet, which are organised around the concept of probability. The paper goes on to argue the case for introducing quantum uncertainty and other aspects of probability theory into the humanities, in order to understand the way knowledge is collected, conserved, curated and communicated in the era of the internet. It is illustrated throughout by reference to the original technological 'affordance' – the Olduvai stone chopping tool.

Closing the gap between bandit and full-information online optimization : high-probability regret bound

We demonstrate a modification of the algorithm of Dani et al for the online linear optimization problem in the bandit setting, which allows us to achieve an O( \sqrt{T ln T} ) regret bound in high probability against an adaptive adversary, as opposed to the in expectation result against an oblivious adversary of Dani et al. We obtain the same dependence on the dimension as that exhibited by Dani et al. The results of this paper rest firmly on those of Dani et al and the remarkable technique of Auer et al for obtaining high-probability bounds via optimistic estimates. This paper answers an open question: it eliminates the gap between the high-probability bounds obtained in the full-information vs bandit settings.

Oxygen transport in soil and the vertical distribution of roots

An analytical solution for steady-state oxygen transport in soils including 2 sink terms, viz roots and microbes with the corresponding vertical distribution scaling lengths forming a ratio p, showed p governed the critical air-filled porosity, θ_c, needed by most plants. For low temperature and p, θ_c was <0.1 but at higher temperatures and p = 1, θ_c was >0.15 m³/m³. When root length density at the surface was 10⁴ m/m³ and p > 3, θ_c was 0.25 m³/m³, more than half the pore space. Few combinations of soil and climate regularly meet this condition. However, for sandy soils and seasonally warm, arid regions, the theory is consistent with observation, in that plants may have some deep roots. Critical θ_c values are used to formulate theoretical solutions in a forward mode, so different levels of oxygen uptake by roots may be compared to microbial activity. The proportion of respiration by plant roots increases rapidly with p up to p ≈2.