Antipathogenic activity of probiotics against Salmonella Typhimurium and Clostridium difficile in anaerobic batch culture systems: is it due to synergies in probiotic mixtures or the specificity of single strains?

Probiotics are currently being investigated for prevention of infections caused by enteric pathogens. The aim of this in vitro study was to evaluate the influence of three single probiotics: Lactobacillus casei NCIMB 30185 (PXN 37), Lactobacillus acidophilus NCIMB 30184 (PXN 35), Bifidobacterium breve NCIMB 30180 (PXN 25) and a probiotic mixture containing the above strains plus twelve other strains belonging to the Lactobacillus, Bifidobacterium, Lactococcus, Streptococcus and Bacillus genera on the survival of Salmonella Typhimurium and Clostridium difficile using pH-controlled anaerobic batch cultures containing mixed fecal bacteria. Changes in relevant bacterial groups and effects of probiotic addition on survival of the two pathogens were assessed over 24 h. Quantitative analysis of bacterial populations revealed that there was a significant increase in lactobacilli and/or bifidobacteria numbers, depending on probiotic addition, compared with the control (no added probiotic). There was also a significant reduction in S. Typhimurium and C. difficile numbers in the presence of certain probiotics compared with controls. Of the probiotic treatments, two single strains namely L. casei NCIMB 30185 (PXN 37), and B. breve NCIMB 30180 (PXN 25) were the most potent in reducing the numbers of S. Typhimurium and C. difficile. In addition, the supplementation with probiotics into the systems influenced some fermentations parameters. Acetate was found in the largest concentrations in all vessels and lactate and formate were generally detected in higher amounts in vessels with probiotic addition compared to controls.

A survey for planetary transits in the field of NGC 7789

We present results from 30 nights of observations of the open cluster NGC 7789 with the Wide Field Camera on the Isaac Newton Telescope, La Palma. From ~900 epochs, we obtained light curves and Sloan r'-i' colours for ~33000 stars, with ~2400 stars having better than 1 per cent precision. We expected to detect ~2 transiting hot Jupiter planets if 1 per cent of stars host such a companion and a typical hot Jupiter radius is ~1.2R_J. We find 24 transit candidates, 14 of which we can assign a period. We rule out the transiting planet model for 21 of these candidates using various robust arguments. For two candidates, we are unable to decide on their nature, although it seems most likely that they are eclipsing binaries as well. We have one candidate exhibiting a single eclipse, for which we derive a radius of 1.81+0.09-0.00R_J. Three candidates remain that require follow-up observations in order to determine their nature.

Forecasting US output growth with non-linear models in the presence of data uncertainty

We consider the impact of data revisions on the forecast performance of a SETAR regime-switching model of U.S. output growth. The impact of data uncertainty in real-time forecasting will affect a model's forecast performance via the effect on the model parameter estimates as well as via the forecast being conditioned on data measured with error. We find that benchmark revisions do affect the performance of the non-linear model of the growth rate, and that the performance relative to a linear comparator deteriorates in real-time compared to a pseudo out-of-sample forecasting exercise.

Real-time forecasting of inflation and output growth with autoregressive models in the presence of data revisions

We examine how the accuracy of real-time forecasts from models that include autoregressive terms can be improved by estimating the models on ‘lightly revised’ data instead of using data from the latest-available vintage. The benefits of estimating autoregressive models on lightly revised data are related to the nature of the data revision process and the underlying process for the true values. Empirically, we find improvements in root mean square forecasting error of 2–4% when forecasting output growth and inflation with univariate models, and of 8% with multivariate models. We show that multiple-vintage models, which explicitly model data revisions, require large estimation samples to deliver competitive forecasts. Copyright © 2012 John Wiley & Sons, Ltd.

A systematic approach to identify the sources of tropical SST errors in coupled models using the adjustment of initialised experiments

Understanding the sources of systematic errors in climate models is challenging because of coupled feedbacks and errors compensation. The developing seamless approach proposes that the identification and the correction of short term climate model errors have the potential to improve the modeled climate on longer time scales. In previous studies, initialised atmospheric simulations of a few days have been used to compare fast physics processes (convection, cloud processes) among models. The present study explores how initialised seasonal to decadal hindcasts (re-forecasts) relate transient week-to-month errors of the ocean and atmospheric components to the coupled model long-term pervasive SST errors. A protocol is designed to attribute the SST biases to the source processes. It includes five steps: (1) identify and describe biases in a coupled stabilized simulation, (2) determine the time scale of the advent of the bias and its propagation, (3) find the geographical origin of the bias, (4) evaluate the degree of coupling in the development of the bias, (5) find the field responsible for the bias. This strategy has been implemented with a set of experiments based on the initial adjustment of initialised simulations and exploring various degrees of coupling. In particular, hindcasts give the time scale of biases advent, regionally restored experiments show the geographical origin and ocean-only simulations isolate the field responsible for the bias and evaluate the degree of coupling in the bias development. This strategy is applied to four prominent SST biases of the IPSLCM5A-LR coupled model in the tropical Pacific, that are largely shared by other coupled models, including the Southeast Pacific warm bias and the equatorial cold tongue bias. Using the proposed protocol, we demonstrate that the East Pacific warm bias appears in a few months and is caused by a lack of upwelling due to too weak meridional coastal winds off Peru. The cold equatorial bias, which surprisingly takes 30 years to develop, is the result of an equatorward advection of midlatitude cold SST errors. Despite large development efforts, the current generation of coupled models shows only little improvement. The strategy proposed in this study is a further step to move from the current random ad hoc approach, to a bias-targeted, priority setting, systematic model development approach.

Decadal predictions of the cooling and freshening of the North Atlantic in the 1960s and the role of ocean circulation

In the 1960s North Atlantic sea surface temperatures (SST) cooled rapidly. The magnitude of the cooling was largest in the North Atlantic subpolar gyre (SPG), and was coincident with a rapid freshening of the SPG. Here we analyze hindcasts of the 1960s North Atlantic cooling made with the UK Met Office’s decadal prediction system (DePreSys), which is initialised using observations. It is shown that DePreSys captures—with a lead time of several years—the observed cooling and freshening of the North Atlantic SPG. DePreSys also captures changes in SST over the wider North Atlantic and surface climate impacts over the wider region, such as changes in atmospheric circulation in winter and sea ice extent. We show that initialisation of an anomalously weak Atlantic Meridional Overturning Circulation (AMOC), and hence weak northward heat transport, is crucial for DePreSys to predict the magnitude of the observed cooling. Such an anomalously weak AMOC is not captured when ocean observations are not assimilated (i.e. it is not a forced response in this model). The freshening of the SPG is also dominated by ocean salt transport changes in DePreSys; in particular, the simulation of advective freshwater anomalies analogous to the Great Salinity Anomaly were key. Therefore, DePreSys suggests that ocean dynamics played an important role in the cooling of the North Atlantic in the 1960s, and that this event was predictable.

Urban and agricultural soils: conflicts and trade-offs in the optimization of ecosystem services

On-going human population growth and changing patterns of resource consumption are increasing global demand for ecosystem services, many of which are provided by soils. Some of these ecosystem services are linearly related to the surface area of pervious soil, whereas others show non-linear relationships, making ecosystem service optimization a complex task. As limited land availability creates conflicting demands among various types of land use, a central challenge is how to weigh these conflicting interests and how to achieve the best solutions possible from a perspective of sustainable societal development. These conflicting interests become most apparent in soils that are the most heavily used by humans for specific purposes: urban soils used for green spaces, housing, and other infrastructure and agricultural soils for producing food, fibres and biofuels. We argue that, despite their seemingly divergent uses of land, agricultural and urban soils share common features with regards to interactions between ecosystem services, and that the trade-offs associated with decision-making, while scale- and context-dependent, can be surprisingly similar between the two systems. We propose that the trade-offs within land use types and their soil-related ecosystems services are often disproportional, and quantifying these will enable ecologists and soil scientists to help policy makers optimizing management decisions when confronted with demands for multiple services under limited land availability.

Market research and the ethics of big data

The term 'big data' has recently emerged to describe a range of technological and commercial trends enabling the storage and analysis of huge amounts of customer data, such as that generated by social networks and mobile devices. Much of the commercial promise of big data is in the ability to generate valuable insights from collecting new types and volumes of data in ways that were not previously economically viable. At the same time a number of questions have been raised about the implications for individual privacy. This paper explores key perspectives underlying the emergence of big data, and considers both the opportunities and ethical challenges raised for market research.

Heuristic based evolution for the coordination of autonomous vehicles in the absence of speed lanes

The current state of the art in the planning and coordination of autonomous vehicles is based upon the presence of speed lanes. In a traffic scenario where there is a large diversity between vehicles the removal of speed lanes can generate a significantly higher traffic bandwidth. Vehicle navigation in such unorganized traffic is considered. An evolutionary based trajectory planning technique has the advantages of making driving efficient and safe, however it also has to surpass the hurdle of computational cost. In this paper, we propose a real time genetic algorithm with Bezier curves for trajectory planning. The main contribution is the integration of vehicle following and overtaking behaviour for general traffic as heuristics for the coordination between vehicles. The resultant coordination strategy is fast and near-optimal. As the vehicles move, uncertainties may arise which are constantly adapted to, and may even lead to either the cancellation of an overtaking procedure or the initiation of one. Higher level planning is performed by Dijkstra's algorithm which indicates the route to be followed by the vehicle in a road network. Re-planning is carried out when a road blockage or obstacle is detected. Experimental results confirm the success of the algorithm subject to optimal high and low-level planning, re-planning and overtaking.

Coupled versus uncoupled hindcast simulations of the Madden-Julian oscillation in the Year of Tropical Convection

This study investigates the impact of a full interactive ocean on daily initialised 15 day hindcasts of the Madden-Julian oscillation (MJO), measured against a Met Office Unified Model (MetUM) atmosphere control simulation (AGCM) during a 3 month period of the Year of Tropical Convection (YOTC). Results indicated that the coupled configuration (CGCM) extends MJO predictability over that of the AGCM, by up to 3-5 days. Propagation is improved in the CGCM, which we partly attribute to a more realistic phase relationship between sea surface temperature (SST) and convection. In addition, the CGCM demonstrates skill in representing downwelling oceanic Kelvin and Rossby waves which warm SSTs along their trajectory, with the potential to feed back on the atmosphere. These results imply that an ocean model capable of simulating internal ocean waves may be required to capture the full effect of air-sea coupling for the MJO.

Nonpsychotropic plant cannabinoids, cannabidivarin (CBDV) and cannabidiol (CBD), activate and desensitize transient receptor potential vanilloid 1 (TRPV1) channels in vitro: potential for the treatment of neuronal hyperexcitability

Epilepsy is the most common neurological disorder, with over 50 million people worldwide affected. Recent evidence suggests that the transient receptor potential cation channel subfamily V member 1 (TRPV1) may contribute to the onset and progression of some forms of epilepsy. Since the two nonpsychotropic cannabinoids cannabidivarin (CBDV) and cannabidiol (CBD) exert anticonvulsant activity in vivo and produce TRPV1-mediated intracellular calcium elevation in vitro, we evaluated the effects of these two compounds on TRPV1 channel activation and desensitization and in an in vitro model of epileptiform activity. Patch clamp analysis in transfected HEK293 cells demonstrated that CBD and CBDV dose-dependently activate and rapidly desensitize TRPV1, as well as TRP channels of subfamily V type 2 (TRPV2) and subfamily A type 1 (TRPA1). TRPV1 and TRPV2 transcripts were shown to be expressed in rat hippocampal tissue. When tested on epileptiform neuronal spike activity in hippocampal brain slices exposed to a Mg2+-free solution using multielectrode arrays (MEAs), CBDV reduced both epileptiform burst amplitude and duration. The prototypical TRPV1 agonist, capsaicin, produced similar, although not identical effects. Capsaicin, but not CBDV, effects on burst amplitude were reversed by IRTX, a selective TRPV1 antagonist. These data suggest that CBDV antiepileptiform effects in the Mg2+-free model are not uniquely mediated via activation of TRPV1. However, TRPV1 was strongly phosphorylated (and hence likely sensitized) in Mg2+-free solution-treated hippocampal tissue, and both capsaicin and CBDV caused TRPV1 dephosphorylation, consistent with TRPV1 desensitization. We propose that CBDV effects on TRP channels should be studied further in different in vitro and in vivo models of epilepsy.

Wavelet based detection of changes in the composition of RLC networks

The current work discusses the compositional analysis of spectra that may be related to amorphous materials that lack discernible Lorentzian, Debye or Drude responses. We propose to model such response using a 3-dimensional random RLC network using a descriptor formulation which is converted into an input-output transfer function representation. A wavelet identification study of these networks is performed to infer the composition of the networks. It was concluded that wavelet filter banks enable a parsimonious representation of the dynamics in excited randomly connected RLC networks. Furthermore, chemometric classification using the proposed technique enables the discrimination of dielectric samples with different composition. The methodology is promising for the classification of amorphous dielectrics.

The evolution of the sun’s open magnetic flux: II. full solar cycle simulations

In this paper the origin and evolution of the Sun’s open magnetic flux is considered by conducting magnetic flux transport simulations over many solar cycles. The simulations include the effects of differential rotation, meridional flow and supergranular diffusion on the radial magnetic field at the surface of the Sun as new magnetic bipoles emerge and are transported poleward. In each cycle the emergence of roughly 2100 bipoles is considered. The net open flux produced by the surface distribution is calculated by constructing potential coronal fields with a source surface from the surface distribution at regular intervals. In the simulations the net open magnetic flux closely follows the total dipole component at the source surface and evolves independently from the surface flux. The behaviour of the open flux is highly dependent on meridional flow and many observed features are reproduced by the model. However, when meridional flow is present at observed values the maximum value of the open flux occurs at cycle minimum when the polar caps it helps produce are the strongest. This is inconsistent with observations by Lockwood, Stamper and Wild (1999) and Wang, Sheeley, and Lean (2000) who find the open flux peaking 1–2 years after cycle maximum. Only in unrealistic simulations where meridional flow is much smaller than diffusion does a maximum in open flux consistent with observations occur. It is therefore deduced that there is no realistic parameter range of the flux transport variables that can produce the correct magnitude variation in open flux under the present approximations. As a result the present standard model does not contain the correct physics to describe the evolution of the Sun’s open magnetic flux over an entire solar cycle. Future possible improvements in modeling are suggested.