Linear and non-linear transmission of equity return volatility: evidence from the US, Japan and Australia

This paper models the transmission of shocks between the US, Japanese and Australian equity markets. Tests for the existence of linear and non-linear transmission of volatility across the markets are performed using parametric and non-parametric techniques. In particular the size and sign of return innovations are important factors in determining the degree of spillovers in volatility. It is found that a multivariate asymmetric GARCH formulation can explain almost all of the non-linear causality between markets. These results have important implications for the construction of models and forecasts of international equity returns.

An investigation into the impact of using various techniques to estimate Arctic surface air temperature anomalies

Time series of global and regional mean Surface Air Temperature (SAT) anomalies are a common metric used to estimate recent climate change. Various techniques can be used to create these time series from meteorological station data. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques relative to the reanalysis reference. Kriging techniques provided the smallest errors in estimates of Arctic anomalies and Simple Kriging was often the best kriging method in this study, especially over sea ice. A linear interpolation technique had, on average, Root Mean Square Errors (RMSEs) up to 0.55 K larger than the two kriging techniques tested. Non-interpolating techniques provided the least representative anomaly estimates. Nonetheless, they serve as useful checks for confirming whether estimates from interpolating techniques are reasonable. The interaction of meteorological station coverage with estimation techniques between 1850 and 2011 was simulated using an ensemble dataset comprising repeated individual years (1979-2011). All techniques were found to have larger RMSEs for earlier station coverages. This supports calls for increased data sharing and data rescue, especially in sparsely observed regions such as the Arctic.

Evaluation of optical techniques for characterising soil organic matter quality in agricultural soils

Soil organic matter (SOM) is one of the main global carbon pools. It is a measure of soil quality as its presence increases carbon sequestration and improves physical and chemical soil properties. The determination and characterisation of humic substances gives essential information of the maturity and stresses of soils as well as of their health. However, the determination of the exact nature and molecular structure of these substances has been proven difficult. Several complex techniques exist to characterise SOM and mineralisation and humification processes. One of the more widely accepted for its accuracy is nuclear magnetic resonance (NMR) spectroscopy. Despite its efficacy, NMR needs significant economic resources, equipment, material and time. Proxy measures like the fluorescence index (FI), cold and hot-water extractable carbon (CWC and HWC) and SUVA-254 have the potential to characterise SOM and, in combination, provide qualitative and quantitative data of SOM and its processes. Spanish and British agricultural cambisols were used to measure SOM quality and determine whether similarities were found between optical techniques and 1H NMR results in these two regions with contrasting climatic conditions. High correlations (p < 0.001) were found between the specific aromatic fraction measured with 1H NMR and SUVA-254 (Rs = 0.95) and HWC (Rs = 0.90), which could be described using a linear model. A high correlation between FI and the aromatics fraction measured with 1H NMR (Rs = −0.976) was also observed. In view of our results, optical measures have a potential, in combination, to predict the aromatic fraction of SOM without the need of expensive and time consuming techniques.

Genetic Algorithm for the Determination of Linear Viscoelastic Relaxation Spectrum from Experimental Data

Conventional procedures employed in the modeling of viscoelastic properties of polymer rely on the determination of the polymer`s discrete relaxation spectrum from experimentally obtained data. In the past decades, several analytical regression techniques have been proposed to determine an explicit equation which describes the measured spectra. With a diverse approach, the procedure herein introduced constitutes a simulation-based computational optimization technique based on non-deterministic search method arisen from the field of evolutionary computation. Instead of comparing numerical results, this purpose of this paper is to highlight some Subtle differences between both strategies and focus on what properties of the exploited technique emerge as new possibilities for the field, In oder to illustrate this, essayed cases show how the employed technique can outperform conventional approaches in terms of fitting quality. Moreover, in some instances, it produces equivalent results With much fewer fitting parameters, which is convenient for computational simulation applications. I-lie problem formulation and the rationale of the highlighted method are herein discussed and constitute the main intended contribution. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 113: 122-135, 2009

Magnetic linear dichroism in absorption spectroscopy of EuTe

The magnetic linear dichroism (MLD) at band-edge photon energies in the Voigt geometry was calculated for EuTe. At the spin-flop transition, MLD shows a step-like increase. Above the spin-flop transition MLD slowly decreases and becomes zero when the averaged electronic charge becomes symmetric relative to the axis of light propagation. Further increase of the magnetic field causes ferromagnetic alignment of the spins along the magnetic field direction, and MLD is recovered but with an opposite sign, and reaches maximum absolute values. These results are explained by the rearrangement of the Eu(2+) spin distribution in the crystal lattice as a function of magnetic field, due to the Zeeman interaction, demonstrating that MLD can be a sensitive probe of the spin order in EuTe, and provides information that is not accessible from other magneto-optical techniques, such as magnetic circular dichroism measurement studies.

DIAGNOSTIC TECHNIQUES OF LOCAL INFLUENCE IN SPATIAL ANALYSIS OF SOYBEAN YIELD

Modeling of spatial dependence structure, concerning geoestatistics approach, is an indispensable tool for fixing parameters that define this structure, applied on interpolation of values in places that are not sampled, by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations on sampled data. Thus, this trial aimed at using diagnostics techniques of local influence in spatial linear Gaussians models, applied at geoestatistics in order to evaluate sensitivity of maximum likelihood estimators and restrict maximum likelihood to small perturbations in these data. So, studies with simulated and experimental data were performed. Those results, obtained from the study of real data, allowed us to conclude that the presence of atypical values among the sampled data can have a strong influence on thematic maps, changing, therefore, the spatial dependence. The application of diagnostics techniques of local influence should be part of any geoestatistic analysis, ensuring that the information from thematic maps has better quality and can be used with greater security by farmers.

Comparison for three Classification Techniques

In this paper we show the results of a comparison simulation study for three classification techniques: Multinomial Logistic Regression (MLR), No Metric Discriminant Analysis (NDA) and Linear Discriminant Analysis (LDA). The measure used to compare the performance of the three techniques was the Error Classification Rate (ECR). We found that MLR and LDA techniques have similar performance and that they are better than DNA when the population multivariate distribution is Normal or Logit-Normal. For the case of log-normal and Sinh(-1)-normal multivariate distributions we found that MLR had the better performance.

Chemical profile of rums as a function of their origin. The use of chemometric techniques for their identification

To identify chemical descriptors to distinguish Cuban from non-Cuban rums, analyses of 44 samples of rum from 15 different countries are described. To provide the chemical descriptors, analyses of the the mineral fraction, phenolic compounds, caramel, alcohols, acetic acid, ethyl acetate, ketones, and aldehydes were carried out. The analytical data were treated through the following chemometric methods: principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and linear discriminate analysis (LDA). These analyses indicated 23 analytes as relevant chemical descriptors for the separation of rums into two distinct groups. The possibility of clustering the rum samples investigated through PCA analysis led to an accumulative percentage of 70.4% in the first three principal components, and isoamyl alcohol, n-propyl alcohol, copper, iron, 2-furfuraldehyde (furfuraldehyde), phenylmethanal (benzaldehyde), epicatechin, and vanillin were used as chemical descriptors. By applying the PLS-DA technique to the whole set of analytical data, the following analytes have been selected as descriptors: acetone, sec-butyl alcohol, isobutyl alcohol, ethyl acetate, methanol, isoamyl alcohol, magnesium, sodium, lead, iron, manganese, copper, zinc, 4-hydroxy3,5-dimethoxybenzaldehyde (syringaldehyde), methaldehyde (formaldehyde), 5-hydroxymethyl-2furfuraldehyde (5-HMF), acetalclehyde, 2-furfuraldehyde, 2-butenal (crotonaldehyde), n-pentanal (valeraldehyde), iso-pentanal (isovaleraldehyde), benzaldehyde, 2,3-butanodione monoxime, acetylacetone, epicatechin, and vanillin. By applying the LIDA technique, a model was developed, and the following analytes were selected as descriptors: ethyl acetate, sec-butyl alcohol, n-propyl alcohol, n-butyl alcohol, isoamyl alcohol, isobutyl alcohol, caramel, catechin, vanillin, epicatechin, manganese, acetalclehyde, 4-hydroxy-3-methoxybenzoic acid, 2-butenal, 4-hydroxy-3,5-dimethoxybenzoic acid, cyclopentanone, acetone, lead, zinc, calcium, barium, strontium, and sodium. This model allowed the discrimination of Cuban rums from the others with 88.2% accuracy.

Likelihood prediction for generalized linear mixed models under covariate uncertainty

This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.

Predição não-linear de curvas de produção de petróleo via redes neurais recursivas

One of the main activities in the petroleum engineering is to estimate the oil production in the existing oil reserves. The calculation of these reserves is crucial to determine the economical feasibility of your explotation. Currently, the petroleum industry is facing problems to analyze production due to the exponentially increasing amount of data provided by the production facilities. Conventional reservoir modeling techniques like numerical reservoir simulation and visualization were well developed and are available. This work proposes intelligent methods, like artificial neural networks, to predict the oil production and compare the results with the ones obtained by the numerical simulation, method quite a lot used in the practice to realization of the oil production prediction behavior. The artificial neural networks will be used due your learning, adaptation and interpolation capabilities

Digestibility and metabolizable energy of maize gluten feed for dogs as measured by two different techniques

Maize gluten feed (MGF) is a co-product of wet milling of maize, and is composed of structures that remain after most starch, gluten and germ has been extracted from the grain. Although currently used in dog foods, its digestibility and energy values have not been documented. Two techniques were used to determine nutrient digestibility of MGF for dog foods. Both techniques used extruded diets fed to Beagle dogs, with six replicates per diet. The first study used a difference method in which 300 g/kg of a reference diet was replaced by MGF. Based on the difference method, the coefficient of total tract apparent digestibility (CTTAD) of MGF was 0.53 for dry matter (DM), 0.69 for crude protein (CP), 0.74 for fat, 0.99 for starch, and 0.55 for gross energy (GE). The calculated metabolizable energy (ME) of MGF was 7.99 MJ/kg (as-fed). The second study used a regression method and included a basal diet and a basal diet with 70, 140 and 210 g MGF/kg of diet (as a substitute for maize starch). Maize gluten feed inclusion resulted in a linear reduction of CTTAD of DM (R(2)=0.99; P<0.001), CP (R(2)=0.95; P=0.002), fat (R(2)=0.87; P=0.009). starch (R(2)=0.81; P<0.001), and GE (R(2)=0.99; P<0.001). Faecal production increased linearly from 56 g to 107 g/dog/d (R(2)=0.99; P<0.001), with a linear reduction of faecal DM (R(2)=0.99: P<0.001) and a linear increase in faecal lactic acid concentration (P<0.02). Both urine (R(2)=0.77; P=0.029) and faeces (R(2)=0.92: P=0.019) showed a linear reduction in pH. Results of ingredient MAD obtained by the regression and difference methods were close (6% or less of variation) for CP, fat, and starch, and also for ME content (1.4% higher for the difference method), but the two methods disagreed on calculated CTTAD of DM and organic matter. The high dietary fiber content of MGF (382 g/kg) may explain the low digestibility of this ingredient. Maize gluten feed could be a useful ingredient for formulations designed to have low energy or reduce the urine pH of dogs. (C) 2011 Elsevier B.V. All rights reserved.

Controlador preditivo não linear aplicado ao controle de golfadas em processos de produção de petróleo

Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

Robust State-Derivative Feedback LMI-Based Designs for Linear Descriptor Systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Biomechanical in vitro evaluation of three stable internal fixation techniques used in sagittal osteotomy of the mandibular ramus: a study in sheep mandibles

Among the osteotomies performed in orthognathic surgery, the sagittal osteotomy of the mandibular ramus (SOMR) is the most common, allowing a great range of movements and stable internal fixation (SIF), therefore eliminating the need of maxillomandibular block in the postoperative period. Objectives: The purpose of this study was to evaluate the biomechanical resistance of three national systems used for SIF in SOMR in sheep mandibles. Material and methods: The study was performed in 30 sheep hemi-mandibles randomly divided into 3 experimental groups, each containing 10 hemi-mandibles. The samples were measured to avoid discrepancies and then subjected to SOMR with 5-mm advancement. In group I, 2.0x12 mm screws were used for fixation, inserted in an inverted "L" pattern (inverted "L" group). In group II, fixation was performed with two 2.0x12 mm screws, positioned in a linear pattern and a 4-hole straight miniplate and four 2.0x6.0 mm monocortical screws (hybrid group). In group III, fixation was performed with two-hole straight miniplates and eight 2.0x6.0 mm monocortical screws (mini plate group). All materials used for SIF were supplied by Osteosin - SIN. The hemimandibles were subjected to vertical linear load test by Kratos K2000MP mechanical testing unit for loading registration and displacement. Results: All groups showed similar resistance during mechanical test for loading and displacement, with no statistically significant differences between groups according to analysis of variance. Conclusion: These results indicate that the three techniques of fixation are equally effective for clinical fixation of SOMR.