A simple method for integrating a complex model into an ensemble data assimilation system using MPI

This paper details a strategy for modifying the source code of a complex model so that the model may be used in a data assimilation context, {and gives the standards for implementing a data assimilation code to use such a model}. The strategy relies on keeping the model separate from any data assimilation code, and coupling the two through the use of Message Passing Interface (MPI) {functionality}. This strategy limits the changes necessary to the model and as such is rapid to program, at the expense of ultimate performance. The implementation technique is applied in different models with state dimension up to $2.7 \times 10^8$. The overheads added by using this implementation strategy in a coupled ocean-atmosphere climate model are shown to be an order of magnitude smaller than the addition of correlated stochastic random errors necessary for some nonlinear data assimilation techniques.

Situation assessment through multi-modal sensing of dynamic environments to support cognitive robot control

Awareness of emerging situations in a dynamic operational environment of a robotic assistive device is an essential capability of such a cognitive system, based on its effective and efficient assessment of the prevailing situation. This allows the system to interact with the environment in a sensible (semi)autonomous / pro-active manner without the need for frequent interventions from a supervisor. In this paper, we report a novel generic Situation Assessment Architecture for robotic systems directly assisting humans as developed in the CORBYS project. This paper presents the overall architecture for situation assessment and its application in proof-of-concept Demonstrators as developed and validated within the CORBYS project. These include a robotic human follower and a mobile gait rehabilitation robotic system. We present an overview of the structure and functionality of the Situation Assessment Architecture for robotic systems with results and observations as collected from initial validation on the two CORBYS Demonstrators.

Influence of temperature during grain filling on gluten viscoelastic properties and gluten protein composition

BACKGROUND The aim of this study was to investigate the effects of low to moderate temperatures on gluten functionality and gluten protein composition. Four spring wheat cultivars were grown in climate chambers with three temperature regimes (day/night temperatures of 13/10, 18/15 and 23/20 °C) during grain filling. RESULTS The temperature strongly influenced grain weight and protein content. Gluten quality measured by maximum resistance to extension (Rmax) was highest in three cultivars grown at 13 °C. Rmax was positively correlated with the proportion of sodium dodecyl sulfate-unextractable polymeric proteins (%UPP). The proportions of ω-gliadins and D-type low-molecular-weight glutenin subunits (LMW-GS) increased and the proportions of α- and γ-gliadins and B-type LMW-GS decreased with higher temperature, while the proportion of high-molecular-weight glutenin subunits (HMW-GS) was constant between temperatures. The cultivar Berserk had strong and constant Rmax between the different temperatures. CONCLUSION Constant low temperature, even as low as 13 °C, had no negative effects on gluten quality. The observed variation in Rmax related to temperature could be explained more by %UPP than by changes in the proportions of HMW-GS or other gluten proteins. The four cultivars responded differently to temperature, as gluten from Berserk was stronger and more stable over a wide range of temperature