Airborne measurements of the spatial distribution of aerosol chemical composition across Europe and evolution of the organic fraction

The spatial distribution of aerosol chemical composition and the evolution of the Organic Aerosol (OA) fraction is investigated based upon airborne measurements of aerosol chemical composition in the planetary boundary layer across Europe. Sub-micron aerosol chemical composition was measured using a compact Time-of-Flight Aerosol Mass Spectrometer (cToF-AMS). A range of sampling conditions were evaluated, including relatively clean background conditions, polluted conditions in North-Western Europe and the near-field to far-field outflow from such conditions. Ammonium nitrate and OA were found to be the dominant chemical components of the sub-micron aerosol burden, with mass fractions ranging from 20--50% each. Ammonium nitrate was found to dominate in North-Western Europe during episodes of high pollution, reflecting the enhanced NO_x and ammonia sources in this region. OA was ubiquitous across Europe and concentrations generally exceeded sulphate by 30--160%. A factor analysis of the OA burden was performed in order to probe the evolution across this large range of spatial and temporal scales. Two separate Oxygenated Organic Aerosol (OOA) components were identified; one representing an aged-OOA, termed Low Volatility-OOA and another representing fresher-OOA, termed Semi Volatile-OOA on the basis of their mass spectral similarity to previous studies. The factors derived from different flights were not chemically the same but rather reflect the range of OA composition sampled during a particular flight. Significant chemical processing of the OA was observed downwind of major sources in North-Western Europe, with the LV-OOA component becoming increasingly dominant as the distance from source and photochemical processing increased. The measurements suggest that the aging of OA can be viewed as a continuum, with a progression from a less oxidised, semi-volatile component to a highly oxidised, less-volatile component. Substantial amounts of pollution were observed far downwind of continental Europe, with OA and ammonium nitrate being the major constituents of the sub-micron aerosol burden. Such anthropogenically perturbed air masses can significantly perturb regional climate far downwind of major source regions.

Diversification of a large genus in a continental biodiversity hotspot: temporal and spatial origin of Muraltia (Polygalaceae) in the Cape of South Africa

Phylogenetic relationships in the largely South African genus Muraltia (Polygalaceae) are assessed based on DNA sequence data (nuclear ribosomal ITS, plastid atpB-rbcL spacer, trnL intron, and trnL-F spacer) for 73 of the 117 currently recognized species in the genus. The previously recognised subgenus Muraltia is monophyletic, but the South African endemic genus Nylandtia is embedded in Muraltia subgenus Psiloclada. Subgenus Muraltia is found to be sister to subgenus Psiloclada. Estimates show the beginning of diversification of the two subgenera in the early Miocene (Psiloclada, 19.3+/-3.4 Ma; Muraltia, 21.0+/-3.5 Ma) pre-dating the establishment of the Benguela current (intermittent in the middle to late Oligocene and markedly intensifying in the late Miocene), and summer-dry climate in the Cape region. However, the later increase in species numbers is contemporaneous with these climatic phenomena. Results of dispersal-vicariance analyses indicate that major clades in Muraltia diversified from the southwestern and northwestern Cape, where most of the species are found today.

Perceived spatial displacement of motion-defined contours in peripheral vision

The perceived displacement of motion-defined contours in peripheral vision was examined in four experiments. In Experiment 1, in line with Ramachandran and Anstis' finding [Ramachandran, V. S., & Anstis, S. M. (1990). Illusory displacement of equiluminous kinetic edges. Perception, 19, 611-616], the border between a field of drifting dots and a static dot pattern was apparently displaced in the same direction as the movement of the dots. When a uniform dark area was substituted for the static dots, a similar displacement was found, but this was smaller and statistically insignificant. In Experiment 2, the border between two fields of dots moving in opposite directions was displaced in the direction of motion of the dots in the more eccentric field, so that the location of a boundary defined by a diverging pattern is perceived as more eccentric, and that defined by a converging as less eccentric. Two explanations for this effect (that the displacement reflects a greater weight given to the more eccentric motion, or that the region containing stronger centripetal motion components expands perceptually into that containing centrifugal motion) were tested in Experiment 3, by varying the velocity of the more eccentric region. The results favoured the explanation based on the expansion of an area in centripetal motion. Experiment 4 showed that the difference in perceived location was unlikely to be due to differences in the discriminability of contours in diverging and converging pattems, and confirmed that this effect is due to a difference between centripetal and centrifugal motion rather than motion components in other directions. Our result provides new evidence for a bias towards centripetal motion in human vision, and suggests that the direction of motion-induced displacement of edges is not always in the direction of an adjacent moving pattern. (C) 2008 Elsevier Ltd. All rights reserved.

Sparse kernel density construction using orthogonal forward regression with leave-one-out test score and local regularization

This paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. Computational efficiency of the density construction is ensured using an orthogonal forward regression, and the algorithm incrementally minimizes the leave-one-out test score. A local regularization method is incorporated naturally into the density construction process to further enforce sparsity. An additional advantage of the proposed algorithm is that it is fully automatic and the user is not required to specify any criterion to terminate the density construction procedure. This is in contrast to an existing state-of-art kernel density estimation method using the support vector machine (SVM), where the user is required to specify some critical algorithm parameter. Several examples are included to demonstrate the ability of the proposed algorithm to effectively construct a very sparse kernel density estimate with comparable accuracy to that of the full sample optimized Parzen window density estimate. Our experimental results also demonstrate that the proposed algorithm compares favorably with the SVM method, in terms of both test accuracy and sparsity, for constructing kernel density estimates.

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.

Multiple hydrogen bonds induce formation of nanoparticles with internal microemulsion structure by an amphiphilic copolymer

A particulate microemulsion is generated in a simple two-component system comprising an amphiphilic copolymer (Pluronic P123) in mixtures with tannic acid. This is correlated to complexation between the poly(ethylene oxide) in the Pluronic copolymer and the multiple hydrogen bonding units in tannic acid which leads to the breakup of the ordered structure formed in gels of Pluronic copolymers, and the formation of dispersed nanospheres containing a bicontinuous internal structure. These novel nanoparticles termed ‘‘emulsomes’’ are self-stabilized by a coating layer of Pluronic copolymer. The microemulsion exhibits a pearlescent appearance due to selective light scattering from the emulsion droplets. This simple formulation based on a commercial copolymer and a biofunctional and biodegradable additive is expected to find applications in the fast moving consumer goods sector.

Variability of starch-based thickened drinks for patients with dysphagia in the hospital setting

Starch-based thickening agents may be prescribed for patients with dysphagia. Thickened fluids alter variables of the swallow reflex, allowing more time for bolus manipulation without compromising airway closure. This investigation explored the variation in viscosity and physical characteristics of thickened drinks prepared in different media under laboratory conditions and compared the results with those of thickened drinks presented to dysphagic patients in one hospital. The rheological characteristics were tested on a simple plastometer and a Bohlin CVOR rheometer (Malvern Instruments, Worcestershire, UK). Samples prepared to “syrup” consistency both in the laboratory and in the hospitalwere significantly different from each other (P < 0.0001). This was also the case for samples prepared to “custard” consistency. Differences existed not only in viscosity, but drinks prepared in different media produced different rheological matrices. This signifies different viscoelastic behaviors that may effect manipulation in the mouth. From this study, preparation of thickened drinks using starch-based instant thickening powders appears to be a highly variable practice.

Real-time application of a constrained predictive controller based on dynamic neural networks with feedback linearization

This paper describes an experimental application of constrained predictive control and feedback linearisation based on dynamic neural networks. It also verifies experimentally a method for handling input constraints, which are transformed by the feedback linearisation mappings. A performance comparison with a PID controller is also provided. The experimental system consists of a laboratory based single link manipulator arm, which is controlled in real time using MATLAB/SIMULINK together with data acquisition equipment.

Bayesian estimation of the spatial Durbin error model with an application to voter turnout in the 2004 presidential election

The potential for spatial dependence in models of voter turnout, although plausible from a theoretical perspective, has not been adequately addressed in the literature. Using recent advances in Bayesian computation, we formulate and estimate the previously unutilized spatial Durbin error model and apply this model to the question of whether spillovers and unobserved spatial dependence in voter turnout matters from an empirical perspective. Formal Bayesian model comparison techniques are employed to compare the normal linear model, the spatially lagged X model (SLX), the spatial Durbin model, and the spatial Durbin error model. The results overwhelmingly support the spatial Durbin error model as the appropriate empirical model.

Development of a dense SNP-based linkage map of an apple rootstock progeny using the Malus Infinium whole genome genotyping array

Background A whole-genome genotyping array has previously been developed for Malus using SNP data from 28 Malus genotypes. This array offers the prospect of high throughput genotyping and linkage map development for any given Malus progeny. To test the applicability of the array for mapping in diverse Malus genotypes, we applied the array to the construction of a SNPbased linkage map of an apple rootstock progeny. Results Of the 7,867 Malus SNP markers on the array, 1,823 (23.2 %) were heterozygous in one of the two parents of the progeny, 1,007 (12.8 %) were heterozygous in both parental genotypes, whilst just 2.8 % of the 921 Pyrus SNPs were heterozygous. A linkage map spanning 1,282.2 cM was produced comprising 2,272 SNP markers, 306 SSR markers and the S-locus. The length of the M432 linkage map was increased by 52.7 cM with the addition of the SNP markers, whilst marker density increased from 3.8 cM/marker to 0.5 cM/marker. Just three regions in excess of 10 cM remain where no markers were mapped. We compared the positions of the mapped SNP markers on the M432 map with their predicted positions on the ‘Golden Delicious’ genome sequence. A total of 311 markers (13.7 % of all mapped markers) mapped to positions that conflicted with their predicted positions on the ‘Golden Delicious’ pseudo-chromosomes, indicating the presence of paralogous genomic regions or misassignments of genome sequence contigs during the assembly and anchoring of the genome sequence. Conclusions We incorporated data for the 2,272 SNP markers onto the map of the M432 progeny and have presented the most complete and saturated map of the full 17 linkage groups of M. pumila to date. The data were generated rapidly in a high-throughput semi-automated pipeline, permitting significant savings in time and cost over linkage map construction using microsatellites. The application of the array will permit linkage maps to be developed for QTL analyses in a cost-effective manner, and the identification of SNPs that have been assigned erroneous positions on the ‘Golden Delicious’ reference sequence will assist in the continued improvement of the genome sequence assembly for that variety.

Probabilistic physically-based cloud screening of satellite infra-red imagery for operational sea surface temperature retrieval

We propose and demonstrate a fully probabilistic (Bayesian) approach to the detection of cloudy pixels in thermal infrared (TIR) imagery observed from satellite over oceans. Using this approach, we show how to exploit the prior information and the fast forward modelling capability that are typically available in the operational context to obtain improved cloud detection. The probability of clear sky for each pixel is estimated by applying Bayes' theorem, and we describe how to apply Bayes' theorem to this problem in general terms. Joint probability density functions (PDFs) of the observations in the TIR channels are needed; the PDFs for clear conditions are calculable from forward modelling and those for cloudy conditions have been obtained empirically. Using analysis fields from numerical weather prediction as prior information, we apply the approach to imagery representative of imagers on polar-orbiting platforms. In comparison with the established cloud-screening scheme, the new technique decreases both the rate of failure to detect cloud contamination and the false-alarm rate by one quarter. The rate of occurrence of cloud-screening-related errors of >1 K in area-averaged SSTs is reduced by 83%. Copyright © 2005 Royal Meteorological Society.

Serial clustering of extratropical cyclones over the North Atlantic and Europe under recent and future climate conditions

Under particular large-scale atmospheric conditions, several windstorms may affect Europe within a short time period. The occurrence of such cyclone families leads to large socioeconomic impacts and cumulative losses. The serial clustering of windstorms is analyzed for the North Atlantic/western Europe. Clustering is quantified as the dispersion (ratio variance/mean) of cyclone passages over a certain area. Dispersion statistics are derived for three reanalysis data sets and a 20-run European Centre Hamburg Version 5 /Max Planck Institute Version–Ocean Model Version 1 global climate model (ECHAM5/MPI-OM1 GCM) ensemble. The dependence of the seriality on cyclone intensity is analyzed. Confirming previous studies, serial clustering is identified in reanalysis data sets primarily on both flanks and downstream regions of the North Atlantic storm track. This pattern is a robust feature in the reanalysis data sets. For the whole area, extreme cyclones cluster more than nonextreme cyclones. The ECHAM5/MPI-OM1 GCM is generally able to reproduce the spatial patterns of clustering under recent climate conditions, but some biases are identified. Under future climate conditions (A1B scenario), the GCM ensemble indicates that serial clustering may decrease over the North Atlantic storm track area and parts of western Europe. This decrease is associated with an extension of the polar jet toward Europe, which implies a tendency to a more regular occurrence of cyclones over parts of the North Atlantic Basin poleward of 50°N and western Europe. An increase of clustering of cyclones is projected south of Newfoundland. The detected shifts imply a change in the risk of occurrence of cumulative events over Europe under future climate conditions.

Temporal and spatial variability of auroral forms in the 10–14 MLT sector: Relationship to plasma convection and solar wind-magnetosphere coupling

Ground-based observations of dayside auroral forms and magnetic perturbations in the arctic sectors of Svalbard and Greenland, in combination with the high-resolution measurements of ionospheric ion drift and temperature by the EISCAT radar, are used to study temporal/spatial structures of cusp-type auroral forms in relation to convection. Large-scale patterns of equivalent convection in the dayside polar ionosphere are derived from the magnetic observations in Greenland and Svalbard. This information is used to estimate the ionospheric convection pattern in the vicinity of the cusp/cleft aurora. The reported observations, covering the period 0700-1130 UT, on January 11, 1993, are separated into four intervals according to the observed characteristics of the aurora and ionospheric convection. The morphology and intensity of the aurora are very different in quiet and disturbed intervals. A latitudinally narrow zone of intense and dynamical 630.0 nm emission equatorward of 75 degrees MLAT, was observed during periods of enhanced antisunward convection in the cusp region. This (type 1 cusp aurora) is considered to be the signature of plasma entry via magnetopause reconnection at low magnetopause latitudes, i.e. the low-latitude boundary layer (LLB I,). Another zone of weak 630.0 nm emission (type 2 cusp aurora) was observed to extend up to high latitudes (similar to 79 degrees MLAT) during relatively quiet magnetic conditions, when indications of reverse (sunward) convection was observed in the dayside polar cap. This is postulated to be a signature of merging between a northward directed IMF (B-z > 0) and the geomagnetic field poleward of the cusp. The coexistence of type 1 and 2 auroras was observed under intermediate circumstances. The optical observations from Svalbard and Greenland were also used to determine the temporal and spatial evolution of type 1 auroral forms, i.e. poleward-moving auroral events occurring in the vicinity of a rotational convection reversal in the early post-noon sector. Each event appeared as a local brightening at the equatorward boundary of the pre-existing type 1 cusp aurora, followed by poleward and eastward expansions of luminosity. The auroral events were associated with poleward-moving surges of enhanced ionospheric convection and F-layer ion temperature as observed by the EISCAT radar in Tromso. The EISCAT ion flow data in combination with the auroral observations show strong evidence for plasma flow across the open/closed field line boundary.

A spatial view of ensemble spread in convection permitting ensembles

With movement toward kilometer-scale ensembles, new techniques are needed for their characterization. A new methodology is presented for detailed spatial ensemble characterization using the fractions skill score (FSS). To evaluate spatial forecast differences, the average and standard deviation are taken of the FSS calculated over all ensemble member–member pairs at different scales and lead times. These methods were found to give important information about the ensemble behavior allowing the identification of useful spatial scales, spinup times for the model, and upscale growth of errors and forecast differences. The ensemble spread was found to be highly dependent on the spatial scales considered and the threshold applied to the field. High thresholds picked out localized and intense values that gave large temporal variability in ensemble spread: local processes and undersampling dominate for these thresholds. For lower thresholds the ensemble spread increases with time as differences between the ensemble members upscale. Two convective cases were investigated based on the Met Office United Model run at 2.2-km resolution. Different ensemble types were considered: ensembles produced using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and an ensemble produced using different model physics configurations. Comparison of the MOGREPS and multiphysics ensembles demonstrated the utility of spatial ensemble evaluation techniques for assessing the impact of different perturbation strategies and the need for assessing spread at different, believable, spatial scales.