Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles

Process-based integrated modelling of weather and crop yield over large areas is becoming an important research topic. The production of the DEMETER ensemble hindcasts of weather allows this work to be carried out in a probabilistic framework. In this study, ensembles of crop yield (groundnut, Arachis hypogaea L.) were produced for 10 2.5 degrees x 2.5 degrees grid cells in western India using the DEMETER ensembles and the general large-area model (GLAM) for annual crops. Four key issues are addressed by this study. First, crop model calibration methods for use with weather ensemble data are assessed. Calibration using yield ensembles was more successful than calibration using reanalysis data (the European Centre for Medium-Range Weather Forecasts 40-yr reanalysis, ERA40). Secondly, the potential for probabilistic forecasting of crop failure is examined. The hindcasts show skill in the prediction of crop failure, with more severe failures being more predictable. Thirdly, the use of yield ensemble means to predict interannual variability in crop yield is examined and their skill assessed relative to baseline simulations using ERA40. The accuracy of multi-model yield ensemble means is equal to or greater than the accuracy using ERA40. Fourthly, the impact of two key uncertainties, sowing window and spatial scale, is briefly examined. The impact of uncertainty in the sowing window is greater with ERA40 than with the multi-model yield ensemble mean. Subgrid heterogeneity affects model accuracy: where correlations are low on the grid scale, they may be significantly positive on the subgrid scale. The implications of the results of this study for yield forecasting on seasonal time-scales are as follows. (i) There is the potential for probabilistic forecasting of crop failure (defined by a threshold yield value); forecasting of yield terciles shows less potential. (ii) Any improvement in the skill of climate models has the potential to translate into improved deterministic yield prediction. (iii) Whilst model input uncertainties are important, uncertainty in the sowing window may not require specific modelling. The implications of the results of this study for yield forecasting on multidecadal (climate change) time-scales are as follows. (i) The skill in the ensemble mean suggests that the perturbation, within uncertainty bounds, of crop and climate parameters, could potentially average out some of the errors associated with mean yield prediction. (ii) For a given technology trend, decadal fluctuations in the yield-gap parameter used by GLAM may be relatively small, implying some predictability on those time-scales.

Molybdenum eta(3)-allyl dicarbonyl complexes as a new class of precursors for highly reactive epoxidation catalysts with tert-butyl hydroperoxide

New Mo(II) diimine derivatives of [Mo(q (3)allyl)X(CO)(2)(CH3CN)(2)] (allyl = C3H5 and C5H5O; X = Cl, Br) were prepared, and [MO(eta(3)-C3H5)Cl(CO)(2)(BIAN)] (BIAN = 1,4-(4-chloro)phenyl-2,3-naphthalene-diazabutadiene) (7) was structurally characterized by single-crystal X-ray diffraction. This complex adopted an equatorial-axial arrangement of the bidentate ligand (axial isomer), in contrast with the precursors, found as the equatorial isomer in the solid and fluxional in solution. The new complexes of the type [Mo(eta(3)-allyl)X(CO)(2)(N-N)l (N-N is a bidentate chelating dinitrogen ligand) were tested for the catalytic epoxidation of cyclooctene using tert-butyl hydroperoxide as oxidant. All catalytic systems were 100% selective toward epoxide formation. While their turnover frequencies paralleled those of related Mo(eta) carbonyl compounds or Mo(VI) compounds bearing similar N-donor ligands, they exhibited similar olefin conversions in consecutive catalytic runs. The acetonitrile precursors were generally more active than the diimine complexes, and the chloro derivatives more active than the bromo ones. Combined vibrational and NMR spectroscopy and computational studies (DFT) were used to investigate the nature of the molybdenum species formed in the catalytic system with [Mo(eta(3)-C3H5)Cl(CO)(2){1,4-(2,6-dimethyl)phenyl-2.3-dimethyldiazabuta diene}] (4) and to propose that the resulting species may be dimeric bearing oxide bridges.

Influence of apolipoprotein E genotype and dietary alpha-tocopherol on redox status and C-reactive protein levels in apolipoprotein E3 and E4 targeted replacement mice

The molecular basis of the positive association between apoE4 genotype and CVD remains unclear. There is direct in vitro evidence indicating that apoE4 is a poorer antioxidant relative to the apoE3 isoform, with some indirect in vivo evidence also available. Therefore it was hypothesised that apoE4 carriers may benefit from alpha-tocopherol (alpha-Toc) supplementation. Targeted replacement mice expressing the human apoE3 and apoE4 were fed with a diet poor (0 mg/kg diet) or rich (200 mg/kg diet) in alpha-Toc for 12 weeks. Neither apoE genotype nor dietary alpha-Toc exerted any effects on the antioxidant defence system, including glutathione, catalase, superoxide dismutase, glutathione peroxidase and glutathione reductase activities. In addition, no differences were observed in mitogen-induced lymphocyte proliferation. alpha-Toc concentrations were modestly higher in plasma and lower in tissues of apoE4 compared with apoE3 mice, with the greatest differences evident in the lung, suggesting that an apoE4 genotype may reduce alpha-Toc delivery to tissues. A tendency towards increased plasma F-2-isoprostanes in apoE4 mice was observed, while liver thiobarbituric acid-reactive substances did not differ between apoE3 and apoE4 mice. In addition, C-reactive protein (CRP) concentrations were reduced in apoE4 mice indicating that this positive effect on CRP may in part negate the increased CVD risk associated with an apoE4 genotype.

Targeting C-reactive protein for the treatment of cardiovascular disease

Complement-mediated inflammation exacerbates the tissue injury of ischaemic necrosis in heart attacks and strokes, the most common causes of death in developed countries. Large infarct size increases immediate morbidity and mortality and, in survivors of the acute event, larger non-functional scars adversely affect long-term prognosis. There is thus an important unmet medical need for new cardioprotective and neuroprotective treatments. We have previously shown that human C-reactive protein (CRP), the classical acute-phase protein that binds to ligands exposed in damaged tissue and then activates complement(1), increases myocardial and cerebral infarct size in rats subjected to coronary or cerebral artery ligation, respectively(2,3). Rat CRP does not activate rat complement, whereas human CRP activates both rat and human complement(4). Administration of human CRP to rats is thus an excellent model for the actions of endogenous human CRP2,3. Here we report the design, synthesis and efficacy of 1,6-bis(phosphocholine)-hexane as a specific small-molecule inhibitor of CRP. Five molecules of this palindromic compound are bound by two pentameric CRP molecules, crosslinking and occluding the ligand-binding B-face of CRP and blocking its functions. Administration of 1,6-bis(phosphocholine)-hexane to rats undergoing acute myocardial infarction abrogated the increase in infarct size and cardiac dysfunction produced by injection of human CRP. Therapeutic inhibition of CRP is thus a promising new approach to cardioprotection in acute myocardial infarction, and may also provide neuroprotection in stroke. Potential wider applications include other inflammatory, infective and tissue-damaging conditions characterized by increased CRP production, in which binding of CRP to exposed ligands in damaged cells may lead to complement-mediated exacerbation of tissue injury.

Dynamic automata for mobile robot learning

Researchers at the University of Reading have developed over many years some simple mobile robots that explore an environment they perceive through simple ultrasonic sensors. Information from these sensors has allowed the robots to learn the simple task of moving around while avoiding dynamic obstacles using a static set of fuzzy automata, the choice of which has been criticised, due to its arbitrary nature. This paper considers how a dynamic set of automata can overcome this criticism. In addition, a new reinforcement learning function is outlined which is both scalable to different numbers and types of sensors. The innovations compare successfully with earlier work.

Evaluation of probabilistic occupancy map people detection for surveillance systems

In this paper, we evaluate the Probabilistic Occupancy Map (POM) pedestrian detection algorithm on the PETS 2009 benchmark dataset. POM is a multi-camera generative detection method, which estimates ground plane occupancy from multiple background subtraction views. Occupancy probabilities are iteratively estimated by fitting a synthetic model of the background subtraction to the binary foreground motion. Furthermore, we test the integration of this algorithm into a larger framework designed for understanding human activities in real environments. We demonstrate accurate detection and localization on the PETS dataset, despite suboptimal calibration and foreground motion segmentation input.

Classification-based probabilistic modeling of texture transition for fast line search tracking and delineation

We introduce a classification-based approach to finding occluding texture boundaries. The classifier is composed of a set of weak learners, which operate on image intensity discriminative features that are defined on small patches and are fast to compute. A database that is designed to simulate digitized occluding contours of textured objects in natural images is used to train the weak learners. The trained classifier score is then used to obtain a probabilistic model for the presence of texture transitions, which can readily be used for line search texture boundary detection in the direction normal to an initial boundary estimate. This method is fast and therefore suitable for real-time and interactive applications. It works as a robust estimator, which requires a ribbon-like search region and can handle complex texture structures without requiring a large number of observations. We demonstrate results both in the context of interactive 2D delineation and of fast 3D tracking and compare its performance with other existing methods for line search boundary detection.

A forward constrained selection algorithm for probabilistic neural network

A new probabilistic neural network (PNN) learning algorithm based on forward constrained selection (PNN-FCS) is proposed. An incremental learning scheme is adopted such that at each step, new neurons, one for each class, are selected from the training samples arid the weights of the neurons are estimated so as to minimize the overall misclassification error rate. In this manner, only the most significant training samples are used as the neurons. It is shown by simulation that the resultant networks of PNN-FCS have good classification performance compared to other types of classifiers, but much smaller model sizes than conventional PNN.

A multi-level probabilistic neural network

Based on the idea of an important cluster, a new multi-level probabilistic neural network (MLPNN) is introduced. The MLPNN uses an incremental constructive approach, i.e. it grows level by level. The construction algorithm of the MLPNN is proposed such that the classification accuracy monotonically increases to ensure that the classification accuracy of the MLPNN is higher than or equal to that of the traditional PNN. Numerical examples are included to demonstrate the effectiveness of proposed new approach.

Studying reactive processes with classical dynamics: rebinding dynamics in MbNO

A new surface-crossing algorithm suitable for describing bond-breaking and bond-forming processes in molecular dynamics simulations is presented. The method is formulated for two intersecting potential energy manifolds which dissociate to different adiabatic states. During simulations, crossings are detected by monitoring an energy criterion. If fulfilled, the two manifolds are mixed over a finite number of time steps, after which the system is propagated on the second adiabat and the crossing is carried out with probability one. The algorithm is extensively tested (almost 0.5 mu s of total simulation time) for the rebinding of NO to myoglobin. The unbound surface ((FeNO)-N-...) is represented using a standard force field, whereas the bound surface (Fe-NO) is described by an ab initio potential energy surface. The rebinding is found to be nonexponential in time, in agreement with experimental studies, and can be described using two time constants. Depending on the asymptotic energy separation between the manifolds, the short rebinding timescale is between 1 and 9 ps, whereas the longer timescale is about an order of magnitude larger. NO molecules which do not rebind within 1 ns are typically found in the Xenon-4 pocket, indicating the high affinity of NO to this region in the protein.

Reactive Halogens in the Marine Boundary Layer (RHaMBLe): the tropical North Atlantic experiments

The NERC UK SOLAS-funded Reactive Halogens in the Marine Boundary Layer (RHaMBLe) programme comprised three field experiments. This manuscript presents an overview of the measurements made within the two simultaneous remote experiments conducted in the tropical North Atlantic in May and June 2007. Measurements were made from two mobile and one ground-based platforms. The heavily instrumented cruise D319 on the RRS Discovery from Lisbon, Portugal to São Vicente, Cape Verde and back to Falmouth, UK was used to characterise the spatial distribution of boundary layer components likely to play a role in reactive halogen chemistry. Measurements onboard the ARSF Dornier aircraft were used to allow the observations to be interpreted in the context of their vertical distribution and to confirm the interpretation of atmospheric structure in the vicinity of the Cape Verde islands. Long-term ground-based measurements at the Cape Verde Atmospheric Observatory (CVAO) on São Vicente were supplemented by long-term measurements of reactive halogen species and characterisation of additional trace gas and aerosol species during the intensive experimental period. This paper presents a summary of the measurements made within the RHaMBLe remote experiments and discusses them in their meteorological and chemical context as determined from these three platforms and from additional meteorological analyses. Air always arrived at the CVAO from the North East with a range of air mass origins (European, Atlantic and North American continental). Trace gases were present at stable and fairly low concentrations with the exception of a slight increase in some anthropogenic components in air of North American origin, though NOx mixing ratios during this period remained below 20 pptv (note the non-IUPAC adoption in this manuscript of pptv and ppbv, equivalent to pmol mol−1 and nmol mol−1 to reflect common practice). Consistency with these air mass classifications is observed in the time series of soluble gas and aerosol composition measurements, with additional identification of periods of slightly elevated dust concentrations consistent with the trajectories passing over the African continent. The CVAO is shown to be broadly representative of the wider North Atlantic marine boundary layer; measurements of NO, O3 and black carbon from the ship are consistent with a clean Northern Hemisphere marine background. Aerosol composition measurements do not indicate elevated organic material associated with clean marine air. Closer to the African coast, black carbon and NO levels start to increase, indicating greater anthropogenic influence. Lower ozone in this region is possibly associated with the increased levels of measured halocarbons, associated with the nutrient rich waters of the Mauritanian upwelling. Bromide and chloride deficits in coarse mode aerosol at both the CVAO and on D319 and the continuous abundance of inorganic gaseous halogen species at CVAO indicate significant reactive cycling of halogens. Aircraft measurements of O3 and CO show that surface measurements are representative of the entire boundary layer in the vicinity both in diurnal variability and absolute levels. Above the inversion layer similar diurnal behaviour in O3 and CO is observed at lower mixing ratios in the air that had originated from south of Cape Verde, possibly from within the ITCZ. ECMWF calculations on two days indicate very different boundary layer depths and aircraft flights over the ship replicate this, giving confidence in the calculated boundary layer depth.

A modular head/eye platform for real-time reactive vision

This paper describes the design, implementation and testing of a high speed controlled stereo “head/eye” platform which facilitates the rapid redirection of gaze in response to visual input. It details the mechanical device, which is based around geared DC motors, and describes hardware aspects of the controller and vision system, which are implemented on a reconfigurable network of general purpose parallel processors. The servo-controller is described in detail and higher level gaze and vision constructs outlined. The paper gives performance figures gained both from mechanical tests on the platform alone, and from closed loop tests on the entire system using visual feedback from a feature detector.

Path planning of robots in noisy workspaces using learning automata

The problem of a manipulator operating in a noisy workspace and required to move from an initial fixed position P0 to a final position Pf is considered. However, Pf is corrupted by noise, giving rise to Pˆf, which may be obtained by sensors. The use of learning automata is proposed to tackle this problem. An automaton is placed at each joint of the manipulator which moves according to the action chosen by the automaton (forward, backward, stationary) at each instant. The simultaneous reward or penalty of the automata enables avoiding any inverse kinematics computations that would be necessary if the distance of each joint from the final position had to be calculated. Three variable-structure learning algorithms are used, i.e., the discretized linear reward-penalty (DLR-P, the linear reward-penalty (LR-P ) and a nonlinear scheme. Each algorithm is separately tested with two (forward, backward) and three forward, backward, stationary) actions.

Minimum recovery time between reactive hyperemia stimulus in the repeated measurement of brachial flow-mediated dilatation.

The ability to undertake repeat measurements of flow-mediated dilatation (FMD) within a short time of a previous measurement would be useful to improve accuracy or to repeat a failed initial procedure. Although standard methods report that a minimum of 10 min is required between measurements, there is no published data to support this. Thirty healthy volunteers had five FMD measurements performed within a 2-h period, separated by various time intervals (5, 15 and 30 min). In 19 volunteers, FMD was also performed as soon as the vessel had returned to its baseline diameter. There was no significant difference between any of the FMD measurements or parameters across the visits indicating that repeat measurements may be taken after a minimum of 5 min or as soon as the vessel has returned to its baseline diameter, which in some subjects may be less than 5 min.