Can 4D-Var use dynamical information from targeted observations of a baroclinic structure?

Targeted observations are generally taken in regions of high baroclinicity, but often show little impact. One plausible explanation is that important dynamical information, such as upshear tilt, is not extracted from the targeted observations by the data assimilation scheme and used to correct initial condition error. This is investigated by generating pseudo targeted observations which contain a singular vector (SV) structure that is not present in the background field or routine observations, i.e. assuming that the background has an initial condition error with tilted growing structure. Experiments were performed for a single case-study with varying numbers of pseudo targeted observations. These were assimilated by the Met Office four-dimensional variational (4D-Var) data assimilation scheme, which uses a 6 h window for observations and background-error covariances calculated using the National Meteorological Centre (NMC) method. The forecasts were run using the operational Met Office Unified Model on a 24 km grid. The results presented clearly demonstrate that a 6 h window 4D-Var system is capable of extracting baroclinic information from a limited set of observations and using it to correct initial condition error. To capture the SV structure well (projection of 0.72 in total energy), 50 sondes over an area of 1×106 km2 were required. When the SV was represented by only eight sondes along an example targeting flight track covering a smaller area, the projection onto the SV structure was lower; the resulting forecast perturbations showed an SV structure with increased tilt and reduced initial energy. The total energy contained in the perturbations decreased as the SV structure was less well described by the set of observations (i.e. as fewer pseudo observations were assimilated). The assimilated perturbation had lower energy than the SV unless the pseudo observations were assimilated with the dropsonde observation errors halved from operational values. Copyright © 2010 Royal Meteorological Society

Methylxanthines are the psycho-pharmacologically active constituents of chocolate

Rationale: Liking, cravings and addiction for chocolate ("chocoholism") are often explained through the presence of pharmacologically active compounds. However, mere "presence" does not guarantee psycho-activity. Objectives: Two double-blind, placebo-controlled studies measured the effects on cognitive performance and mood of the amounts of cocoa powder and methylxanthines found in a 50 g bar of dark chocolate. Methods: In study 1, participants (n=20) completed a test battery once before and twice after treatment administration. Treatments included 11.6 g cocoa powder and a caffeine and theobromine combination (19 and 250 mg, respectively). Study 2 (n=22) comprised three post-treatment test batteries and investigated the effects of "milk" and "dark" chocolate levels of these methylxanthines. The test battery consisted of a long duration simple reaction time task, a rapid visual information processing task, and a mood questionnaire. Results: Identical improvements on the mood construct "energetic arousal" and cognitive function were found for cocoa powder and the caffeine+theobromine combination versus placebo. In chocolate, both "milk chocolate" and "dark chocolate" methylxanthine doses improved cognitive function compared with "white chocolate". The effects of white chocolate did not differ significantly from those of water. Conclusion: A normal portion of chocolate exhibits psychopharmacological activity. The identical profile of effects exerted by cocoa powder and its methylxanthine constituents shows this activity to be confined to the combination of caffeine and theobromine. Methylxanthines may contribute to the popularity of chocolate; however, other attributes are probably much more important in determining chocolate's special appeal and in explaining related self-reports of chocolate cravings and "chocoholism".

Museum robots: multi-robot systems for public exhibition

Mobile robots provide a versatile platform for research, however they can also provide an interesting educational platform for public exhibition at museums. In general museums require exhibits that are both eye catching and exciting to the public whilst requiring a minimum of maintenance time from museum technicians. In many cases it is simply not possible to continuously change batteries and some method of supplying continous power is required. A powered flooring system is described that is capable of providing power continuously to a group of robots. Three different museum exhibit applications are described. All three robot exhibits are of a similar basic design although the exhibits are very different in appearance and behaviour. The durability and versatility of the robots also makes them extremely good candidates for long duration experiments such as those required by evolutionary robotics.

Motivating farmers: insights from social psychology

We are social beings. What we do and don’t do, what we think, the decisions we take are all influenced by those around us. Sometimes we are conscious of those influences, often we are not. Those who influence us are not just our close family and friends, our own social and professional networks, but the wider societies and cultures to which we belong. The goals we espouse, the values we hold, the image we have of ourselves are all molded to a large extent by our interactions and relationships with other people. The social sciences offer a range of concepts and tools for exploring these influences. In this paper, I introduce some of these and illustrate them with recent research I and my colleagues have been doing at the University of Reading among livestock farmers in the UK, with a view to providing insights that can then be used to plan and implement more effective interventions.

Structural transformation of graphite by arc-discharge

The formation of novel structures by the passage of an electric current through graphite is described. These structures apparently consist of hollow three-dimensional graphitic shells bounded by curved and faceted planes, typically made up of two graphene layers. The curved structures were frequently decorated with nano-scale carbon particles, or short nanotubes. In some cases, nanotubes were found to be seamlessly connected to the thin shells, indicating that the formation of the shells and the nanotubes is intimately connected. Small nanotubes or nanoparticles were also sometimes found encapsulated inside the hollow structures, while fullerene-like particles were often seen attached to the outside surfaces. With their high surface areas and structural perfection, the new carbon structures may have applications as anodes of lithium ion batteries or as components of composite materials.

Introduction and the problems of weather interpretation

Numerical forecasts of the atmosphere based on the fundamental dynamical and thermodynamical equations have now been carried for almost 30 years. The very first models which were used were drastic simplifications of the governing equations and permitting only the prediction of the geostrophic wind in the middle of the troposphere based on the conservation of absolute vorticity. Since then we have seen a remarkable development in models predicting the large-scale synoptic flow. Verification carried out at NMC Washington indicates an improvement of about 40% in 24h forecasts for the 500mb geopotential since the end of the 1950’s. The most advanced models of today use the equations of motion in their more original form (i.e. primitive equations) which are better suited to predicting the atmosphere at low latitudes as well as small scale systems. The model which we have developed at the Centre, for instance, will be able to predict weather systems from a scale of 500-1000 km and a vertical extension of a few hundred millibars up to global weather systems extending through the whole depth of the atmosphere. With a grid resolution of 1.5 and 15 vertical levels and covering the whole globe it is possible to describe rather accurately the thermodynamical processes associated with cyclone development. It is further possible to incorporate sub-grid-scale processes such as radiation, exchange of sensible heat, release of latent heat etc. in order to predict the development of new weather systems and the decay of old ones. Later in this introduction I will exemplify this by showing some results of forecasts by the Centre’s model.

Mobility based energy efficient and multi-sink algorithms for consumer home networks

With the fast development of the Internet, wireless communications and semiconductor devices, home networking has received significant attention. Consumer products can collect and transmit various types of data in the home environment. Typical consumer sensors are often equipped with tiny, irreplaceable batteries and it therefore of the utmost importance to design energy efficient algorithms to prolong the home network lifetime and reduce devices going to landfill. Sink mobility is an important technique to improve home network performance including energy consumption, lifetime and end-to-end delay. Also, it can largely mitigate the hot spots near the sink node. The selection of optimal moving trajectory for sink node(s) is an NP-hard problem jointly optimizing routing algorithms with the mobile sink moving strategy is a significant and challenging research issue. The influence of multiple static sink nodes on energy consumption under different scale networks is first studied and an Energy-efficient Multi-sink Clustering Algorithm (EMCA) is proposed and tested. Then, the influence of mobile sink velocity, position and number on network performance is studied and a Mobile-sink based Energy-efficient Clustering Algorithm (MECA) is proposed. Simulation results validate the performance of the proposed two algorithms which can be deployed in a consumer home network environment.

Lithium and oxygen adsorption at the b-MnO2 (110) surface

The adsorption and co-adsorption of lithium and oxygen at the surface of rutile-like manganese dioxide(b-MnO2), which are important in the context of Li–air batteries, are investigated using density functional theory. In the absence of lithium, the most stable surface of b-MnO2, the (110), adsorbs oxygen in the form of peroxo groups bridging between two manganese cations. Conversely, in the absence of excess oxygen, lithium atoms adsorb on the (110) surface at two different sites, which are both tricoordinated to surface oxygen anions, and the adsorption always involves the transfer of one electron from the adatom to one of the five-coordinated manganese cations at the surface, creating (formally) Li+ and Mn3+ species. The co-adsorption of lithium and oxygen leads to the formation of a surface oxide, involving the dissociation of the O2 molecule, where the O adatoms saturate the coordination of surface Mn cations and also bind to the Li adatoms. This process is energetically more favourable than the formation of gas-phase lithium peroxide (Li2O2) monomers, but less favourable than the formation of Li2O2 bulk. These results suggest that the presence of b-MnO2 in the cathode of a nonaqueous Li–O2 battery lowers the energy for the initial reduction of oxygen during cell discharge.

Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks

With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.