A Variance-Minimizing Filter for Large-Scale Applications

A truly variance-minimizing filter is introduced and its per for mance is demonstrated with the Korteweg– DeV ries (KdV) equation and with a multilayer quasigeostrophic model of the ocean area around South Africa. It is recalled that Kalman-like filters are not variance minimizing for nonlinear model dynamics and that four - dimensional variational data assimilation (4DV AR)-like methods relying on per fect model dynamics have dif- ficulty with providing error estimates. The new method does not have these drawbacks. In fact, it combines advantages from both methods in that it does provide error estimates while automatically having balanced states after analysis, without extra computations. It is based on ensemble or Monte Carlo integrations to simulate the probability density of the model evolution. When obser vations are available, the so-called importance resampling algorithm is applied. From Bayes’ s theorem it follows that each ensemble member receives a new weight dependent on its ‘ ‘distance’ ’ t o the obser vations. Because the weights are strongly var ying, a resampling of the ensemble is necessar y. This resampling is done such that members with high weights are duplicated according to their weights, while low-weight members are largely ignored. In passing, it is noted that data assimilation is not an inverse problem by nature, although it can be for mulated that way . Also, it is shown that the posterior variance can be larger than the prior if the usual Gaussian framework is set aside. However , i n the examples presented here, the entropy of the probability densities is decreasing. The application to the ocean area around South Africa, gover ned by strongly nonlinear dynamics, shows that the method is working satisfactorily . The strong and weak points of the method are discussed and possible improvements are proposed.

Application of data assimilation to ocean and climate prediction

Ocean prediction systems are now able to analyse and predict temperature, salinity and velocity structures within the ocean by assimilating measurements of the ocean’s temperature and salinity into physically based ocean models. Data assimilation combines current estimates of state variables, such as temperature and salinity, from a computational model with measurements of the ocean and atmosphere in order to improve forecasts and reduce uncertainty in the forecast accuracy. Data assimilation generally works well with ocean models away from the equator but has been found to induce vigorous and unrealistic overturning circulations near the equator. A pressure correction method was developed at the University of Reading and the Met Office to control these circulations using ideas from control theory and an understanding of equatorial dynamics. The method has been used for the last 10 years in seasonal forecasting and ocean prediction systems at the Met Office and European Center for Medium-range Weather Forecasting (ECMWF). It has been an important element in recent re-analyses of the ocean heat uptake that mitigates climate change.

Ecological and social drivers of coffee pollination in Santander, Colombia

Bees and other insects provide pollination services that are key to determining the fruit set on coffee plantations. These pollination services are influenced by local ecology as well as human factors, both social and economic. To better understand these different factors, we assessed their effect on pollinators and coffee pollination services in Santander, Colombia. We quantified the effect of key ecological drivers on pollinator community composition, such as the method of farm management (either conventional or organic) and the surrounding landscape composition, specifically the proximity to forest. We found that ambient levels of pollination services provided by the local pollinator fauna (open pollination) accounted for a 10.5 ± 2.0% increase in final coffee fruit set, and that the various pollinators are affected differently by the differing factors. For example, our findings indicate that conventional farm management, using synthetic inputs, can promote pollinators, especially if they are in close proximity to natural forest fragments. This is particularly true for stingless bees. Honeybee visitation to coffee is also positively influenced by the conventional management of farms. Factors associated with greater numbers of stingless bees on farms include greater shade cover, lower tree densities, smaller numbers and types of trees in bloom, and younger coffee plantations. A forested landscape close to farms appears to enhance these factors, giving increased stability and resilience to the pollinating bees and insects. However we found that organic farms also support diverse pollinator communities, even if distant from forest fragments. The contribution of honeybees to pollination value (US$129.6/ha of coffee) is greater than that of stingless bees (US$16.5/ha of coffee). Since the method of farm management has a major impact on the numbers and types of pollinators attracted to farms, we have analysed the statistically significant social factors that influence farmers’ decisions on whether to adopt organic or conventional practices. These include the availability of technology, the type of landowner (whether married couples or individual owners), the number of years of farmers’ formal education, the role of institutions, membership of community organizations, farm size, coffee productivity and the number of coffee plots per farm. It is hoped that the use of our holistic approach, which combines investigation of the social as well as the ecological drivers of pollination, will help provide evidence to underpin the development of best practices for integrating the management of pollination into sustainable agricultural practices.

Kazakhstan: long-term economic growth and the role of the oil sector

This study combines a narrative and modelling framework to analyse the development of Kazakhstan’s oil sector since its takeoff following separation from the USSR. As in the case of other emerging or transitional countries with large natural resource endowments, a key question is whether the exploitation of the natural resource is a benefit to longer term economic development: is it a curse, a blessing – or neither? Narrative evidence suggests that the establishment of good governance, in terms of institutions and policies, provides a background to sound long-term development, especially if combined with the development of sectors outside the natural resource sector, for example diversification into manufacturing and services, often through attracting FDI. The narrative is supported by econometric modelling of the relationship between domestic output, overseas output and exports of oil, which finds in favour of a sustained positive effect of oil exports on GDP. The model then provides a basis for projection of the growth in GDP given a consensus view of likely developments in the oil price.

Bayesian analysis of uncertainty in the GlobCover 2009 land cover product at climate model grid scale

Land cover data derived from satellites are commonly used to prescribe inputs to models of the land surface. Since such data inevitably contains errors, quantifying how uncertainties in the data affect a model’s output is important. To do so, a spatial distribution of possible land cover values is required to propagate through the model’s simulation. However, at large scales, such as those required for climate models, such spatial modelling can be difficult. Also, computer models often require land cover proportions at sites larger than the original map scale as inputs, and it is the uncertainty in these proportions that this article discusses. This paper describes a Monte Carlo sampling scheme that generates realisations of land cover proportions from the posterior distribution as implied by a Bayesian analysis that combines spatial information in the land cover map and its associated confusion matrix. The technique is computationally simple and has been applied previously to the Land Cover Map 2000 for the region of England and Wales. This article demonstrates the ability of the technique to scale up to large (global) satellite derived land cover maps and reports its application to the GlobCover 2009 data product. The results show that, in general, the GlobCover data possesses only small biases, with the largest belonging to non–vegetated surfaces. In vegetated surfaces, the most prominent area of uncertainty is Southern Africa, which represents a complex heterogeneous landscape. It is also clear from this study that greater resources need to be devoted to the construction of comprehensive confusion matrices.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

Astyanax bockmanni Vari and Castro, 2007: an ambiguous karyotype in the Astyanax genus

Despite the widespread distribution of Astyanax bockmanni in streams from Upper Parana River system in central, southeastern, and southern Brazil, just recently, it has been identified as a distinct Astyanax species. Cytogenetic studies were performed in two populations of this species, revealing conservative features. A. bockmanni shows 2n = 50 chromosomes, a karyotypic formula composed of 10 M + 12SM + 12ST + 16A and multiple Ag-NORs. Eight positive signals in subtelocentric/acrocentric chromosomes were identified by fluorescent in situ hybridization (FISH) with 18S rDNA probes. After FISH with 5S rDNA probes, four sites were detected, comprising the interstitial region of a metacentric pair and the terminal region on long arms of another metracentric pair. Little amounts of constitutive heterochromatin were observed, mainly distributed at distal region in two chromosomal pairs. Additionally, heterochromatin was also located close to the centromeres in some chromosomes. No positive signals were detected in the chromosomes of A. bockmanni by FISH with the As-51 satellite DNA probe. The studied species combines a set of characteristics previously identified in two different Astyanax groups. The chromosomal evolution in the genus Astyanax is discussed.

An enhanced content selection mechanism for personalization of video news programmes

In this paper, we propose a content selection framework that improves the users` experience when they are enriching or authoring pieces of news. This framework combines a variety of techniques to retrieve semantically related videos, based on a set of criteria which are specified automatically depending on the media`s constraints. The combination of different content selection mechanisms can improve the quality of the retrieved scenes, because each technique`s limitations are minimized by other techniques` strengths. We present an evaluation based on a number of experiments, which show that the retrieved results are better when all criteria are used at time.

Existence of secondary bifurcations or isolas for PDEs

In this paper, we introduce a method to conclude about the existence of secondary bifurcations or isolas of steady state solutions for parameter dependent nonlinear partial differential equations. The technique combines the Global Bifurcation Theorem, knowledge about the non-existence of nontrivial steady state solutions at the zero parameter value and explicit information about the coexistence of multiple nontrivial steady states at a positive parameter value. We apply the method to the two-dimensional Swift-Hohenberg equation. (C) 2011 Elsevier Ltd. All rights reserved.

Light-induced lens analysis in photorefractive crystals employing phase-shifting real-time holographic interferometry

The purpose of this work is to study the potentialities of phase-shifting real-time holographic interferometry for the analysis of light-induced lens in photoreffactive and nonlinear optical materials. We show that this technique can be used for quantitative evaluation of the phase distribution of a wavefront changed by a light-induced lens and, consequently, the refractive index changes in these materials. The basic principle of this technique combines real-time holographic interferometry with phase-shifting technique for interferogram analysis. This method is demonstrated with in situ visualization, monitoring and analysis in real-time and uses a Bi(12)SiO(20) crystal as the holographic medium and a Bi(12)TiO(20) as the test sample. (C) 2008 Elsevier B.V. All rights reserved.

Realistic calculations of carbon-based disordered systems

Carbon nanotubes rank amongst potential candidates for a new family of nanoscopic devices, in particular for sensing applications. At the same time that defects in carbon nanotubes act as binding sites for foreign species, our current level of control over the fabrication process does not allow one to specifically choose where these binding sites will actually be positioned. In this work we present a theoretical framework for accurately calculating the electronic and transport properties of long disordered carbon nanotubes containing a large number of binding sites randomly distributed along a sample. This method combines the accuracy and functionality of ab initio density functional theory to determine the electronic structure with a recursive Green`s functions method. We apply this methodology on the problem of nitrogen-rich carbon nanotubes, first considering different types of defects and then demonstrating how our simulations can help in the field of sensor design by allowing one to compute the transport properties of realistic nanotube devices containing a large number of randomly distributed binding sites.

IxV Curves of Boron and Nitrogen Doping Zigzag Graphene Nanoribbons

We investigate the transport properties (IxV curves and zero bias transmittance) of pristine graphene nanoribbons (GNRs) as well as doped with boron and nitrogen using an approach that combines nonequilibrium Green`s functions and density functional theory (DFT) [NEGF-DFT]. Even for a pristine nanoribbon we verify a spin-filter effect under finite bias voltage when the leads have an antiparallel magnetization. The presence of the impurities at the edges of monohydrogenated zigzag GNRs changes dramatically the charge transport properties inducing a spin-polarized conductance. The IxV curves for these systems show that depending on the bias voltage the spin polarization can be inverted. (C) 2010 Wiley Periodicals, Inc. Int J Quantum Chem 111: 1379-1386, 2011

Ion beam assisted deposition of an organic light emitting diode electrode

This work presents the electro-optical characterization of metal-organic interfaces prepared by the Ion Beam Assisted Deposition (IBAD) method. IBAD applied in this work combines simultaneously metallic film deposition and bombardment with an independently controlled ion beam, allowing different penetration of the ions and the evaporated metallic elements into the polymer. The result is a hybrid, non-abrupt interface, where polymer, metal and ion coexists. We used an organic light emitting diode, which has a typical vertical-architecture, for the interface characterization: Glass/Indium Tin Oxide (ITO)/Poly[ethylene-dioxythiophene/poly{styrenesulfonicacid}]) (PEDOT:PSS) /Emitting Polymer/Metal. The emitting polymer layer comprised of the Poly[(9,9-dioctyl-2,7-divinylenefluorenylene)-alt-co-{2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylene}] (PFO) and the metal layer of aluminum prepared with different Ar(+) ion energies varying in the range from 0 to 1000 eV. Photoluminescence, Current-Voltage and Electroluminescence measurements were used to study the emission and electron injection properties. Changes of these properties were related with the damage caused by the energetic ions and the metal penetration into the polymer. Computer simulations of hybrid interface damage and metal penetration were confronted with experimental data. (C) 2010 Elsevier B.V. All rights reserved.

Shape classification using complex network and Multi-scale Fractal Dimension

Shape provides one of the most relevant information about an object. This makes shape one of the most important visual attributes used to characterize objects. This paper introduces a novel approach for shape characterization, which combines modeling shape into a complex network and the analysis of its complexity in a dynamic evolution context. Descriptors computed through this approach show to be efficient in shape characterization, incorporating many characteristics, such as scale and rotation invariant. Experiments using two different shape databases (an artificial shapes database and a leaf shape database) are presented in order to evaluate the method. and its results are compared to traditional shape analysis methods found in literature. (C) 2009 Published by Elsevier B.V.

Enhanced visualization of histological samples with an adjustable RGB contrast system with application for tissue used in photodynamic therapy

The analysis of histological sections has long been a valuable tool in the pathological studies. The interpretation of tissue conditions, however, relies directly on visual evaluation of tissue slides, which may be difficult to interpret because of poor contrast or poor color differentiation. The Chromatic Contrast Visualization System (CCV) combines an optical microscope with electronically controlled light-emitting diodes (LEDs) in order to generate adjustable intensities of RGB channels for sample illumination. While most image enhancement techniques rely on software post-processing of an image acquired under standard illumination conditions, CCV produces real-time variations in the color composition of the light source itself. The possibility of covering the entire RGB chromatic range, combined with the optical properties of the different tissues, allows for a substantial enhancement in image details. Traditional image acquisition methods do not exploit these visual enhancements which results in poorer visual distinction among tissue structures. Photodynamic therapy (PDT) procedures are of increasing interest in the treatment of several forms of cancer. This study uses histological slides of rat liver samples that were induced to necrosis after being exposed to PDT. Results show that visualization of tissue structures could be improved by changing colors and intensities of the microscope light source. PDT-necrosed tissue samples are better differentiated when illuminated with different color wavelengths, leading to an improved differentiation of cells in the necrosis area. Due to the potential benefits it can bring to interpretation and diagnosis, further research in this field could make CCV an attractive technique for medical applications.