A modified PNN algorithm with optimal PD modeling using the orthogonal least squares method

In this paper a modified algorithm is suggested for developing polynomial neural network (PNN) models. Optimal partial description (PD) modeling is introduced at each layer of the PNN expansion, a task accomplished using the orthogonal least squares (OLS) method. Based on the initial PD models determined by the polynomial order and the number of PD inputs, OLS selects the most significant regressor terms reducing the output error variance. The method produces PNN models exhibiting a high level of accuracy and superior generalization capabilities. Additionally, parsimonious models are obtained comprising a considerably smaller number of parameters compared to the ones generated by means of the conventional PNN algorithm. Three benchmark examples are elaborated, including modeling of the gas furnace process as well as the iris and wine classification problems. Extensive simulation results and comparison with other methods in the literature, demonstrate the effectiveness of the suggested modeling approach.

Host model uncertainties in aerosol radiative forcing estimates: results from the AeroCom Prescribed intercomparison study

Simulated multi-model “diversity” in aerosol direct radiative forcing estimates is often perceived as a measure of aerosol uncertainty. However, current models used for aerosol radiative forcing calculations vary considerably in model components relevant for forcing calculations and the associated “host-model uncertainties” are generally convoluted with the actual aerosol uncertainty. In this AeroCom Prescribed intercomparison study we systematically isolate and quantify host model uncertainties on aerosol forcing experiments through prescription of identical aerosol radiative properties in twelve participating models. Even with prescribed aerosol radiative properties, simulated clear-sky and all-sky aerosol radiative forcings show significant diversity. For a purely scattering case with globally constant optical depth of 0.2, the global-mean all-sky top-of-atmosphere radiative forcing is −4.47Wm−2 and the inter-model standard deviation is 0.55Wm−2, corresponding to a relative standard deviation of 12 %. For a case with partially absorbing aerosol with an aerosol optical depth of 0.2 and single scattering albedo of 0.8, the forcing changes to 1.04Wm−2, and the standard deviation increases to 1.01W−2, corresponding to a significant relative standard deviation of 97 %. However, the top-of-atmosphere forcing variability owing to absorption (subtracting the scattering case from the case with scattering and absorption) is low, with absolute (relative) standard deviations of 0.45Wm−2 (8 %) clear-sky and 0.62Wm−2 (11 %) all-sky. Scaling the forcing standard deviation for a purely scattering case to match the sulfate radiative forcing in the Aero- Com Direct Effect experiment demonstrates that host model uncertainties could explain about 36% of the overall sulfate forcing diversity of 0.11Wm−2 in the AeroCom Direct Radiative Effect experiment.

Evaluation of milk compositional variables on coagulation properties using partial least squares

The aim of this study was to investigate the effects of numerous milk compositional factors on milk coagulation properties using Partial Least Squares (PLS). Milk from herds of Jersey and Holstein-Friesian cattle was collected across the year and blended (n=55), to maximize variation in composition and coagulation. The milk was analysed for casein, protein, fat, titratable acidity, lactose, Ca2+, urea content, micelles size, fat globule size, somatic cell count and pH. Milk coagulation properties were defined as coagulation time, curd firmness and curd firmness rate measured by a controlled strain rheometer. The models derived from PLS had higher predictive power than previous models demonstrating the value of measuring more milk components. In addition to the well-established relationships with casein and protein levels, CMS and fat globule size were found to have as strong impact on all of the three models. The study also found a positive impact of fat on milk coagulation properties and a strong relationship between lactose and curd firmness, and urea and curd firmness rate, all of which warrant further investigation due to current lack of knowledge of the underlying mechanism. These findings demonstrate the importance of using a wider range of milk compositional variable for the prediction of the milk coagulation properties, and hence as indicators of milk suitability for cheese making.

Molecular species delimitation of a symbiotic fig-pollinating wasp species complex reveals extreme deviation from reciprocal partner specificity

Background: Symbiotic relationships have contributed to major evolutionary innovations, the maintenance of fundamental ecosystem functions, and the generation and maintenance of biodiversity. However, the exact nature of host/symbiont associations, which has important consequences for their dynamics, is often poorly known due to limited understanding of symbiont taxonomy and species diversity. Among classical symbioses, figs and their pollinating wasps constitute a highly diverse keystone resource in tropical forest and savannah environments. Historically, they were considered to exemplify extreme reciprocal partner specificity (one-to-one host-symbiont species relationships), but recent work has revealed several more complex cases. However, there is a striking lack of studies with the specific aims of assessing symbiont diversity and how this varies across the geographic range of the host. Results: Here, we use molecular methods to investigate cryptic diversity in the pollinating wasps of a widespread Australian fig species. Standard barcoding genes and methods were not conclusive, but incorporation of phylogenetic analyses and a recently developed nuclear barcoding gene (ITS2), gave strong support for five pollinator species. Each pollinator species was most common in a different geographic region, emphasising the importance of wide geographic sampling to uncover diversity, and the scope for divergence in coevolutionary trajectories across the host plant range. In addition, most regions had multiple coexisting pollinators, raising the question of how they coexist in apparently similar or identical resource niches. Conclusion: Our study offers a striking example of extreme deviation from reciprocal partner specificity over the full geographical range of a fig-wasp system. It also suggests that superficially identical species may be able to co-exist in a mutualistic setting albeit at different frequencies in relation to their fig host’s range. We show that comprehensive sampling and molecular taxonomic techniques may be required to uncover the true structure of cryptic biodiversity underpinning intimate ecological interactions.

Determination of the absolute accuracy of UK chamber facilities used in measuring methane emissions from livestock

Respiration chambers are one of the primary sources of data on methane emissions from livestock. This paper describes the results from a coordinated set of chamber validation experiments which establishes the absolute accuracy of the methane emission rates measured by the chambers, and for the first time provides metrological traceability to international standards, assesses the impact of both analyser and chamber response times on measurement uncertainty and establishes direct comparability between measurements made across different facilities with a wide range of chamber designs. As a result of the validation exercise the estimated combined uncertainty associated with the overall capability across all facilities reduced from 25.7% (k = 2, 95% confidence) before the validation to 2.1% (k = 2, 95% confidence) when the validation results are applied to the facilities’ data.

Quasi-sure existence of Gaussian rough paths and large deviation principles for capacities

We construct a quasi-sure version (in the sense of Malliavin) of geometric rough paths associated with a Gaussian process with long-time memory. As an application we establish a large deviation principle (LDP) for capacities for such Gaussian rough paths. Together with Lyons' universal limit theorem, our results yield immediately the corresponding results for pathwise solutions to stochastic differential equations driven by such Gaussian process in the sense of rough paths. Moreover, our LDP result implies the result of Yoshida on the LDP for capacities over the abstract Wiener space associated with such Gaussian process.

Improving the TanDEM-X Digital Elevation Model for flood modelling using flood extents from Synthetic Aperture Radar images

The topography of many floodplains in the developed world has now been surveyed with high resolution sensors such as airborne LiDAR (Light Detection and Ranging), giving accurate Digital Elevation Models (DEMs) that facilitate accurate flood inundation modelling. This is not always the case for remote rivers in developing countries. However, the accuracy of DEMs produced for modelling studies on such rivers should be enhanced in the near future by the high resolution TanDEM-X WorldDEM. In a parallel development, increasing use is now being made of flood extents derived from high resolution Synthetic Aperture Radar (SAR) images for calibrating, validating and assimilating observations into flood inundation models in order to improve these. This paper discusses an additional use of SAR flood extents, namely to improve the accuracy of the TanDEM-X DEM in the floodplain covered by the flood extents, thereby permanently improving this DEM for future flood modelling and other studies. The method is based on the fact that for larger rivers the water elevation generally changes only slowly along a reach, so that the boundary of the flood extent (the waterline) can be regarded locally as a quasi-contour. As a result, heights of adjacent pixels along a small section of waterline can be regarded as samples with a common population mean. The height of the central pixel in the section can be replaced with the average of these heights, leading to a more accurate estimate. While this will result in a reduction in the height errors along a waterline, the waterline is a linear feature in a two-dimensional space. However, improvements to the DEM heights between adjacent pairs of waterlines can also be made, because DEM heights enclosed by the higher waterline of a pair must be at least no higher than the corrected heights along the higher waterline, whereas DEM heights not enclosed by the lower waterline must in general be no lower than the corrected heights along the lower waterline. In addition, DEM heights between the higher and lower waterlines can also be assigned smaller errors because of the reduced errors on the corrected waterline heights. The method was tested on a section of the TanDEM-X Intermediate DEM (IDEM) covering an 11km reach of the Warwickshire Avon, England. Flood extents from four COSMO-SKyMed images were available at various stages of a flood in November 2012, and a LiDAR DEM was available for validation. In the area covered by the flood extents, the original IDEM heights had a mean difference from the corresponding LiDAR heights of 0.5 m with a standard deviation of 2.0 m, while the corrected heights had a mean difference of 0.3 m with standard deviation 1.2 m. These figures show that significant reductions in IDEM height bias and error can be made using the method, with the corrected error being only 60% of the original. Even if only a single SAR image obtained near the peak of the flood was used, the corrected error was only 66% of the original. The method should also be capable of improving the final TanDEM-X DEM and other DEMs, and may also be of use with data from the SWOT (Surface Water and Ocean Topography) satellite.

Zero attracting recursive least squares algorithms

The l1-norm sparsity constraint is a widely used technique for constructing sparse models. In this contribution, two zero-attracting recursive least squares algorithms, referred to as ZA-RLS-I and ZA-RLS-II, are derived by employing the l1-norm of parameter vector constraint to facilitate the model sparsity. In order to achieve a closed-form solution, the l1-norm of the parameter vector is approximated by an adaptively weighted l2-norm, in which the weighting factors are set as the inversion of the associated l1-norm of parameter estimates that are readily available in the adaptive learning environment. ZA-RLS-II is computationally more efficient than ZA-RLS-I by exploiting the known results from linear algebra as well as the sparsity of the system. The proposed algorithms are proven to converge, and adaptive sparse channel estimation is used to demonstrate the effectiveness of the proposed approach.

A constrained recursive least squares algorithm for adaptive combination of multiple models

In this paper, we develop a novel constrained recursive least squares algorithm for adaptively combining a set of given multiple models. With data available in an online fashion, the linear combination coefficients of submodels are adapted via the proposed algorithm.We propose to minimize the mean square error with a forgetting factor, and apply the sum to one constraint to the combination parameters. Moreover an l1-norm constraint to the combination parameters is also applied with the aim to achieve sparsity of multiple models so that only a subset of models may be selected into the final model. Then a weighted l2-norm is applied as an approximation to the l1-norm term. As such at each time step, a closed solution of the model combination parameters is available. The contribution of this paper is to derive the proposed constrained recursive least squares algorithm that is computational efficient by exploiting matrix theory. The effectiveness of the approach has been demonstrated using both simulated and real time series examples.

Self-reported Body Changes and Associated Factors in Persons Living with HIV

The study aimed at verifying the associated factors of self-perceived body changes in adults living with HIV in highly-active antiretroviral therapy (HAART) in the city of Sao Paulo, Brazil. This cross-sectional study was conducted among people living with HIV on HAART for at least three months. A standardized questionnaire was used for assessing self-perceived body changes. Associated factors relating to self-reported body changes in people living with HIV (PLHIV) were assessed with Student`s t-test and chi-square test. In total, 507 patients were evaluated. The mean time since diagnosis was 6.6 years [standard deviation (SD)+/-4.1], and the mean duration of HAART was 5.1 years (SD+/-3.3). Self-perceived body changes were reported by 79.5% of the participants and were associated with viral load and duration of HAART. Fibre intake was lower among males who gained in abdominal fat (p=0.035). HAART-related body changes were reported by the large majority of the population and were associated with demographic and clinical variables.

Absolute Thellier paleointensities from Ponta Grossa dikes (southern Brazil) and the early Cretaceous geomagnetic field strength

We report a detailed rock magnetic and Thellier paleointensity study from similar to 130.5 Ma Ponta Grossa Dike Swarms in Southern Brazil. Twenty-nine samples from seven cooling units were pre-selected for paleointensity experiments based on their low viscosity index, stable remanent magnetization and close to reversible continuous thermomagnetic curves. 19 samples characterized by negative pTRM tests, Arai concave- up curves or positive pTRM tests with NRM loss uncorrelated with TRM acquisition were rejected. High quality reliable paleointensity determinations are determined from detailed evaluation criteria, with 10 samples belonging to three dikes passing the tests. The site-mean paleointensity values obtained in this study range from 25.6 +/- 4.3 to 11.3 +/- 2.1 mu T and the corresponding VDM`s range from 5.7 +/- 0.9 to 2.5 +/- 0.5 (10(22) Am(2)). These data yield a VDM mean value of 4.1 +/- 1.6 x 10(22) Am(2). Significant variability of Earth`s magnetic field strength is observed for Ponta Grossa Dikes with the mean value being significantly lower as compared to the mean VDM obtained from the nearby Parana Magmatic Province. The paleointensities for the Ponta Grossa Dikes are in agreement with absolute paleointensities retrieved from the submarine basaltic glasses from 130 to 120 Ma. It seems that a relatively low field prevailed just before the Cretaceous Normal Superchron.

SIZE AS A LINE OF LEAST RESISTANCE II: DIRECT SELECTION ON SIZE OR CORRELATED RESPONSE DUE TO CONSTRAINTS?

Evolutionary change in New World Monkey (NWM) skulls occurred primarily along the line of least resistance defined by size (including allometric) variation (g(max)). Although the direction of evolution was aligned with this axis, it was not clear whether this macroevolutionary pattern results from the conservation of within population genetic covariance patterns (long-term constraint) or long-term selection along a size dimension, or whether both, constraints and selection, were inextricably involved. Furthermore, G-matrix stability can also be a consequence of selection, which implies that both, constraints embodied in g(max) and evolutionary changes observed on the trait averages, would be influenced by selection Here, we describe a combination of approaches that allows one to test whether any particular instance of size evolution is a correlated by-product due to constraints (g(max)) or is due to direct selection on size and apply it to NWM lineages as a case study. The approach is based on comparing the direction and amount of evolutionary change produced by two different simulated sets of net-selection gradients (beta), a size (isometric and allometric size) and a nonsize set. Using this approach it is possible to distinguish between the two hypotheses (indirect size evolution due to constraints or direct selection on size), because although both may produce an evolutionary response aligned with g(max), the amount of change produced by random selection operating through the variance/covariance patterns (constraints hypothesis) will be much smaller than that produced by selection on size (selection hypothesis). Furthermore, the alignment of simulated evolutionary changes with g(max) when selection is not on size is not as tight as when selection is actually on size, allowing a statistical test of whether a particular observed case of evolution along the line of least resistance is the result of selection along it or not. Also, with matrix diagonalization (principal components [PC]) it is possible to calculate directly the net-selection gradient on size alone (first PC [PC1]) by dividing the amount of phenotypic difference between any two populations by the amount of variation in PC1, which allows one to benchmark whether selection was on size or not

Evidence of a genetic bottleneck in an El Nino affected population of South American fur seals, Arctocephalus australis

The South American fur seal, Arctocephalus australis, was one of the earliest otariid seals to be exploited by humans: at least 6000 years ago on the Atlantic coast and 4000 on the Pacific coast of South America. More than 750,000 fur seals were killed in Uruguay until 1991. However, a climatological phenomenon-the severe 1997-1998 El Nino Southern Oscillation (ENSO)-was responsible for the decline of 72% Of the Peruvian fur seal population due to starvation as a consequence of warming of sea-surface temperatures and primary productivity reduction. Currently, there is no precise information on global population size or on the species` conservation status. The present study includes the first bottleneck test for the Pacific and Atlantic populations of A. australis based on the analysis of seven microsatellite loci. Genetic bottleneck compromises the evolutionary potential of a population to respond to environmental changes. The perspective becomes even more alarming due to current global warming models that predict stronger and more frequent ENSO events in the future. Our analysis found moderate support for deviation from neutrality-equilibrium for the Pacific population of fur seals and none for the Atlantic population. This difference among population reflects different demographic histories, and is consistent with a greater reduction in population size in the Pacific. Such an event could be a result of the synergic effects of recurrent ENSO events and the anthropogenic impact (sealing and prey overfishing) on this population.

Least square projection: A fast high-precision multidimensional projection technique and its application to document mapping

The problem of projecting multidimensional data into lower dimensions has been pursued by many researchers due to its potential application to data analyses of various kinds. This paper presents a novel multidimensional projection technique based on least square approximations. The approximations compute the coordinates of a set of projected points based on the coordinates of a reduced number of control points with defined geometry. We name the technique Least Square Projections ( LSP). From an initial projection of the control points, LSP defines the positioning of their neighboring points through a numerical solution that aims at preserving a similarity relationship between the points given by a metric in mD. In order to perform the projection, a small number of distance calculations are necessary, and no repositioning of the points is required to obtain a final solution with satisfactory precision. The results show the capability of the technique to form groups of points by degree of similarity in 2D. We illustrate that capability through its application to mapping collections of textual documents from varied sources, a strategic yet difficult application. LSP is faster and more accurate than other existing high-quality methods, particularly where it was mostly tested, that is, for mapping text sets.