High-sensitivity refractive index sensor based on large-angle tilted fiber grating with carbon nanotube deposition

This paper presents a highly sensitive ambient refractive index (RI) sensor based on 81° tilted fiber grating (81°-TFG) structure UV-inscribed in standard telecom fiber (62.5μm cladding radius) with carbon nanotube (CNT) overlay deposition. The sensing mechanism is based on the ability of CNT to induce change in transmitted optical power and the high sensitivity of 81°-TFG to ambient refractive index. The thin CNT film with high refractive index enhances the cladding modes of the TFG, resulting in the significant interaction between the propagating light and the surrounding medium. Consequently, the surrounding RI change will induce not only the resonant wavelength shift but also the power intensity change of the attenuation band in the transmission spectrum. Result shows that the change in transmitted optical power produces a corresponding linear reduction in intensity with increment in RI values. The sample shows high sensitivities of ∼207.38nm/RIU, ∼241.79nm/RIU at RI range 1.344-1.374 and ∼113.09nm/RIU, ∼144.40nm/RIU at RI range 1.374-1.392 (for X-pol and Y-pol respectively). It also shows power intensity sensitivity of ∼ 65.728dBm/RIU and ∼ 45.898 (for X-pol and Y-pol respectively). The low thermal sensitivity property of the 81°-TFG offers reduction in thermal cross-sensitivity and enhances specificity of the sensor.

Estudo da massa específica básica e da variação dimensional da madeira de três espécies de eucalipto para a indústria moveleira

The utilization of wood from reforested species by the furniture industry is a recent trend. Thus, the present study determined the specific gravity and shrinkage of wood of 18-year-old Eucalyptus grandis, Eucalyptus dunnii and Eucalyptus urophylla, for use as components in solid wood furniture making. The tests to evaluate the specific gravity and shrinkage of wood in the radial and axial variation of the eucalyptus trees were performed according to NBR 7190/96. The results of the analysis of wood from eucalypt species were subjected to the Homogeneity Test, ANOVA, Tukey and Pearson correlation and compared to the performance of sucupira wood (Bowdichia nitida) and cumaru wood (Dipteryx odorata), often used in the furniture industry. The following results were found: Eucalyptus grandis had a lower value of shrinkage, being more suitable for furniture components that require high dimensional stability, as well as parts of larger surface. The wood of this species showed a rate of dimensional variation compatible with the native species used in the furniture industry. The radial variation of the wood was also verified, and a high correlation between specific gravity and shrinkage was found. Longitudinally, the base of the trunk of the eucalyptus trees was shown to be the region of greatest dimensional stability.

Solution structure of alpha-conotoxin ImI by H-1 nuclear magnetic resonance

alpha-Conotoxin ImI derives from the venom of Conus imperialis and is the first and only small-peptide ligand that selectively binds to the neuronal alpha(7) homopentameric subtype of the nicotinic acetylcholine receptor (nAChR). This receptor subtype is a possible drug target for several neurological disorders. The cysteines are connected in the pairs Cys2-Cys8 and Cys3-Cys12, To date it is the only alpha-conotoxin with a 4/3 residue spacing between the cysteines, The structure of ImI has been determined by H-1 NMR spectroscopy in aqueous solution, The NMR structure is of high quality, with a backbone pairwise rmsd of 0.34 Angstrom for a family of 19 structures, and comprises primarily a series of nested beta turns. Addition of organic solvent does not perturb the solution structure. The first eight residues of ImI are identical to the larger, but related, conotoxin EpI and adopt a similar structure, despite a truncated second loop. Residues important for binding of ImI to the alpha 7 nAChR are all clustered on one face of the molecule. Once further binding data for EPI and ImI are available, the ImI structure will allow for design of novel alpha(7) nAChR-specific agonists and antagonists with a wide range of potential pharmaceutical applications.

Population structure of Phytophthora cinnamomi in South Africa

Phytophthora cinnamomi isolates collected from 1977 to 1986 and 1991 to 1993 in two regions in South Africa were analyzed using isozymes. A total of 135 isolates was analyzed for 14 enzymes representing 20 putative loci, of which four were polymorphic. This led to the identification of nine different multilocus isozyme genotypes. Both mating types of P. cinnamomi occurred commonly in the Cape region, whereas, predominantly, the A2 mating type occurred in the Mpumalanga region of South Africa. A2 mating type isolates could be resolved into seven multilocus isozyme genotypes, compared with only two multilocus isozyme genotypes for the A1 mating type isolates. Low levels of gene (0.115) and genotypic (2.4%) diversity and a low number of alleles per locus (1.43) were observed for the South African P. cinnamomi population. The genetic distance between the Cape and Mpumalanga P. cinnamomi populations was relatively low (D-m = 0.165), and no specific pattern in regional distribution of multilocus isozyme genotypes could be observed. The genetic distance between the ''old'' (isolated between 1977 and 1986) and ''new'' (isolated between 1991 and 1993) P. cinnamomi populations from the Cape was low (D-m = 0.164), indicating a stable population over time. Three of the nine multilocus isozyme genotypes were specific to the ''old'' population, and only one multilocus isozyme genotype was specific to the ''new'' population. Significant differences in allele frequencies, a high genetic distance (D-m = 0.581) between the Cape A1 and A2 mating type isolates, significant deviations from Hardy-Weinberg equilibrium, a low overall level of heterozygosity, and a high fixation index (0.71) all indicate that sexual reproduction occurs rarely, if at all, in the South African P. cinnamomi population.

Improvement of the electrolytic properties of Y2O3-based materials using a crystallographic index

Y2O3 is a c-type rare earth oxide with a fluorite-related structure. This material has been used to refractory because of its high thermal stability and excellent resistance to hydration. In this study, the effective index was suggested in order to improve the electrolytic properties of Y2O3-based oxide. (CexY1-x)(2)O3+delta (x = 0.25 and 0.3) and [LaaSrbCe0.25Y(1-a-b)](2)O3+delta (a = 0.05, 0.1 and 0.15, b = 0, 0.006 and 0.0125) were prepared as the examples with intermediate and high index, respectively. The specimens with high index value such as (La0.15Ce0.25Y0.60)(2)O-3.25 and (La0.1Sr0.0125Ce0.25Y0.6375)(2)O-3.24 consisted of two phases such as c-type and fluorite, although (Ce0.25Y0.75)(2)O-3.25 with intermediate index value had a single phase of c-type rare earth oxide. Microanalysis indicates that a grain in the (La0.1Sr0.0125Ce0.25Y0.6375)(2)O-3.23(7) sintered body consists of c-type and fluorite phases. An interface between c-type and fluorite phases is coherent in a grain. This suggests that this effective index guides the crystal structure in the specimen to fluorite and the examined composition introduces the interface between c-type and fluorite in the microstructure. The electrochemical properties of specimens including Y2O3 were characterized on the basis of the suggested index. The electrical conductivity of Y2O3-based materials increased with an increase of the index. The apparent activation energy of Y2O3-based materials decreased with increasing index. The ionic transport number of oxygen of the specimens was improved by enhancement of the index, confirming validity of the index. The oxide ionic conductive region of (La0.1Sr0.0125Ce0.25Y0.(6375))(2)O-3.23(7) with high effective index extended up to P-O2 = 10(-18) atm at 800 degreesC, although the specimens with low or intermediate index showed p- or n-type semi-conduction in the same P-O2 region at 800 and 1000 degreesC. These results suggest that the interface between c-type and fluorite phases also contributes to improve the electrolytic properties in the grain. It is concluded that the improvement of electrolytic properties in Y2O3-based materials is attributable to the microstructure with interface between two phases in a grain and the fluorite structure guided by the suggested index. (C) 2001 Published by Elsevier Science B.V.

Modelling of weather radar echoes from anomalous propagation using a hybrid parabolic equation method and NWP model data

Contamination of weather radar echoes by anomalous propagation (anaprop) mechanisms remains a serious issue in quality control of radar precipitation estimates. Although significant progress has been made identifying clutter due to anaprop there is no unique method that solves the question of data reliability without removing genuine data. The work described here relates to the development of a software application that uses a numerical weather prediction (NWP) model to obtain the temperature, humidity and pressure fields to calculate the three dimensional structure of the atmospheric refractive index structure, from which a physically based prediction of the incidence of clutter can be made. This technique can be used in conjunction with existing methods for clutter removal by modifying parameters of detectors or filters according to the physical evidence for anomalous propagation conditions. The parabolic equation method (PEM) is a well established technique for solving the equations for beam propagation in a non-uniformly stratified atmosphere, but although intrinsically very efficient, is not sufficiently fast to be practicable for near real-time modelling of clutter over the entire area observed by a typical weather radar. We demonstrate a fast hybrid PEM technique that is capable of providing acceptable results in conjunction with a high-resolution terrain elevation model, using a standard desktop personal computer. We discuss the performance of the method and approaches for the improvement of the model profiles in the lowest levels of the troposphere.

Two-dimensional probabilistic inversion of plane-wave electromagnetic data: Methodology, model constraints and joint inversion with electrical resistivity data

Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet, application of such methods to CPU-intensive forward models can be a daunting task, particularly if the parameter space is high dimensional. Here, we present a 2-D pixel-based MCMC inversion of plane-wave electromagnetic (EM) data. Using synthetic data, we investigate how model parameter uncertainty depends on model structure constraints using different norms of the likelihood function and the model constraints, and study the added benefits of joint inversion of EM and electrical resistivity tomography (ERT) data. Our results demonstrate that model structure constraints are necessary to stabilize the MCMC inversion results of a highly discretized model. These constraints decrease model parameter uncertainty and facilitate model interpretation. A drawback is that these constraints may lead to posterior distributions that do not fully include the true underlying model, because some of its features exhibit a low sensitivity to the EM data, and hence are difficult to resolve. This problem can be partly mitigated if the plane-wave EM data is augmented with ERT observations. The hierarchical Bayesian inverse formulation introduced and used herein is able to successfully recover the probabilistic properties of the measurement data errors and a model regularization weight. Application of the proposed inversion methodology to field data from an aquifer demonstrates that the posterior mean model realization is very similar to that derived from a deterministic inversion with similar model constraints.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Factor Analysis of a Large DSGE Model

We study the workings of the factor analysis of high-dimensional data using artificial series generated from a large, multi-sector dynamic stochastic general equilibrium (DSGE) model. The objective is to use the DSGE model as a laboratory that allow us to shed some light on the practical benefits and limitations of using factor analysis techniques on economic data. We explain in what sense the artificial data can be thought of having a factor structure, study the theoretical and finite sample properties of the principal components estimates of the factor space, investigate the substantive reason(s) for the good performance of di¤usion index forecasts, and assess the quality of the factor analysis of highly dissagregated data. In all our exercises, we explain the precise relationship between the factors and the basic macroeconomic shocks postulated by the model.

Numerical Investigations on Soil Structure Interaction of Multistorey Frames

Frames are the most widely used structural system for multistorey buildings. A building frame is a three dimensional discrete structure consisting of a number of high rise bays in two directions at right angles to each other in the vertical plane. Multistorey frames are a three dimensional lattice structure which are statically indeterminate. Frames sustain gravity loads and resist lateral forces acting on it. India lies at the north westem end of the Indo-Australian tectonic plate and is identified as an active tectonic area. Under horizontal shaking of the ground, horizontal inertial forces are generated at the floor levels of a multistorey frame. These lateral inertia forces are transferred by the floor slab to the beams, subsequently to the columns and finally to the soil through the foundation system. There are many parameters that affect the response of a structure to ground excitations such as, shape, size and geometry of the structure, type of foundation, soil characteristics etc. The Soil Structure Interaction (SS1) effects refer to the influence of the supporting soil medium on the behavior of the structure when it is subjected to different types of loads. Interaction between the structure and its supporting foundation and soil, which is a complete system, has been modeled with finite elements. Numerical investigations have been carried out on a four bay, twelve storeyed regular multistorey frame considering depth of fixity at ground level, at characteristic depth of pile and at full depth. Soil structure interaction effects have been studied by considering two models for soil viz., discrete and continuum. Linear static analysis has been conducted to study the interaction effects under static load. Free vibration analysis and further shock spectrum analysis has been conducted to study the interaction effects under time dependent loads. The study has been extended to four types of soil viz., laterite, sand, alluvium and layered.The structural responses evaluated in the finite element analysis are bending moment, shear force and axial force for columns, and bending moment and shear force for beams. These responses increase with increase in the founding depth; however these responses show minimal increase beyond the characteristic length of pile. When the soil structure interaction effects are incorporated in the analysis, the aforesaid responses of the frame increases upto the characteristic depth and decreases when the frame has been analysed for the full depth. It has been observed that shock spectrum analysis gives wide variation of responses in the frame compared to linear elastic analysis. Both increase and decrease in responses have been observed in the interior storeys. The good congruence shown by the two finite element models viz., discrete and continuum in linear static analysis has been absent in shock spectrum analysis.

Exploring Object Perception with Random Image Structure Evolution

We have developed a technique called RISE (Random Image Structure Evolution), by which one may systematically sample continuous paths in a high-dimensional image space. A basic RISE sequence depicts the evolution of an object's image from a random field, along with the reverse sequence which depicts the transformation of this image back into randomness. The processing steps are designed to ensure that important low-level image attributes such as the frequency spectrum and luminance are held constant throughout a RISE sequence. Experiments based on the RISE paradigm can be used to address some key open issues in object perception. These include determining the neural substrates underlying object perception, the role of prior knowledge and expectation in object perception, and the developmental changes in object perception skills from infancy to adulthood.

A reconstructed Siberian High index since A. D. 1599 from Eurasian and North American tree rings

The long-term variability of the Siberian High, the dominant Northern Hemisphere anticyclone during winter, is largely unknown. To investigate how this feature varied prior to the instrumental record, we present a reconstruction of a Dec-Feb Siberian High (SH) index based on Eurasian and North American tree rings. Spanning 1599-1980, it provides information on SH variability over the past four centuries. A decline in the instrumental SH index since the late 1970s, related to Eurasian warming, is the most striking feature over the past four hundred years. It is associated with a highly significant (p < 0.0001) step change in 1989. Significant similar to 3-4 yr spectral peaks in the reconstruction fall within the range of variability of the East Asian winter monsoon (which has also declined recently) and lend further support to proposed relationships between these largescale features of the climate system.

Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

Excitações em cristais fotônicos unidimensionais

In this work, we present a theoretical study of the propagation of electromagnetic waves in multilayer structures called Photonic Crystals. For this purpose, we investigate the phonon-polariton band gaps in periodic and quasi-periodic (Fibonacci-type) multilayers made up of both positive and negative refractive index materials in the terahertz (THz) region. The behavior of the polaritonic band gaps as a function of the multilayer period is investigated systematically. We use a theoretical model based on the formalism of transfer matrix in order to simplify the algebra involved in obtaining the dispersion relation of phonon-polaritons (bulk and surface modes). We also present a quantitative analysis of the results, pointing out the distribution of the allowed polaritonic bandwidths for high Fibonacci generations, which gives good insight about their localization and power laws. We calculate the emittance spectrum of the electromagnetic radiation, in THZ frequency, normally and obliquely incident (s and p polarized modes) on a one-dimensional multilayer structure composed of positive and negative refractive index materials organized periodically and quasi-periodically. We model the negative refractive index material by a effective medium whose electric permittivity is characterized by a phonon-polariton frequency dependent dielectric function, while for the magnetic permeability we have a Drude like frequency-dependent function. Similarity to the one-dimensional photonic crystal, this layered effective medium, called polaritonic Crystals, allow us the control of the electromagnetic propagation, generating regions named polaritonic bandgap. The emittance spectra are determined by means of a well known theoretical model based on Kirchoff s second law, together with a transfer matrix formalism. Our results shows that the omnidirectional band gaps will appear in the THz regime, in a well defined interval, that are independent of polarization in periodic case as well as in quasiperiodic case