Identification of Elastic, Dielectric, and Piezoelectric Constants in Piezoceramic Disks

Three-dimensional modeling of piezoelectric devices requires a precise knowledge of piezoelectric material parameters. The commonly used piezoelectric materials belong to the 6mm symmetry class, which have ten independent constants. In this work, a methodology to obtain precise material constants over a wide frequency band through finite element analysis of a piezoceramic disk is presented. Given an experimental electrical impedance curve and a first estimate for the piezoelectric material properties, the objective is to find the material properties that minimize the difference between the electrical impedance calculated by the finite element method and that obtained experimentally by an electrical impedance analyzer. The methodology consists of four basic steps: experimental measurement, identification of vibration modes and their sensitivity to material constants, a preliminary identification algorithm, and final refinement of the material constants using an optimization algorithm. The application of the methodology is exemplified using a hard lead zirconate titanate piezoceramic. The same methodology is applied to a soft piezoceramic. The errors in the identification of each parameter are statistically estimated in both cases, and are less than 0.6% for elastic constants, and less than 6.3% for dielectric and piezoelectric constants.

Effects of weld strength mismatch on J and CTOD estimation procedure for SE(B) specimens

This work examines the effect of weld strength mismatch on fracture toughness measurements defined by J and CTOD fracture parameters using single edge notch bend (SE(B)) specimens. A central objective of the present study is to enlarge on previous developments of J and CTOD estimation procedures for welded bend specimens based upon plastic eta factors (eta) and plastic rotational factors (r (p) ). Very detailed non-linear finite element analyses for plane-strain models of standard SE(B) fracture specimens with a notch located at the center of square groove welds and in the heat affected zone provide the evolution of load with increased crack mouth opening displacement required for the estimation procedure. One key result emerging from the analyses is that levels of weld strength mismatch within the range +/- 20% mismatch do not affect significantly J and CTOD estimation expressions applicable to homogeneous materials, particularly for deeply cracked fracture specimens with relatively large weld grooves. The present study provides additional understanding on the effect of weld strength mismatch on J and CTOD toughness measurements while, at the same time, adding a fairly extensive body of results to determine parameters J and CTOD for different materials using bend specimens with varying geometries and mismatch levels.

Valve friction and nonlinear process model closed-loop identification

Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.

Frequency Domain Connectivity Identification: An Application of Partial Directed Coherence in fMRI

Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.

Hardware/firmware implementation of a soft sensor using an improved version of a fuzzy identification algorithm

This paper presents the design and implementation of an embedded soft sensor, i. e., a generic and autonomous hardware module, which can be applied to many complex plants, wherein a certain variable cannot be directly measured. It is implemented based on a fuzzy identification algorithm called ""Limited Rules"", employed to model continuous nonlinear processes. The fuzzy model has a Takagi-Sugeno-Kang structure and the premise parameters are defined based on the Fuzzy C-Means (FCM) clustering algorithm. The firmware contains the soft sensor and it runs online, estimating the target variable from other available variables. Tests have been performed using a simulated pH neutralization plant. The results of the embedded soft sensor have been considered satisfactory. A complete embedded inferential control system is also presented, including a soft sensor and a PID controller. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.

Identification of a bioactive compound isolated from Brazilian propolis type 6

A prenylated benzophenone, hyperibone A, was isolated from the hexane fraction of Brazilian propolis type 6. Its structure was determined by spectral analysis including 2D NMR. This compound exhibited cytotoxic activity against HeLa tumor cells (IC(50) = 0.1756 mu M), strong antimicrobial activity (MIC range-0.73-6.6 mu g/mL; MBC range-2.92-106 mu g/mL) against Streptococcus mutans, Streptococcus sobrinus, Streptococcus oralis, Staphylococcus aureus, and Actinomyces naeslundii, and the results of its cytotoxic and antimicrobial activities were considered good. (C) 2009 Elsevier Ltd. All rights reserved.

Identification of protein coding regions using the modified Gabor-wavelet transform

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

Molecular Identification and Phylogenetic Analysis of a Group 16SrI-B Phytoplasma Associated with Sugarcane Yellow Leaf Syndrome in Brazil

Yellow leaf syndrome was a serious problem in the beginning of the 1990s in Brazil, when yield losses were estimated to be around 50%. The disease is currently endemic, but it is considered potentially important. Previous studies have revealed only the presence of a luteovirus associated with the disease in Brazil. We report that a phytoplasma of 16SrI-B is also associated with this disease. This is the first demonstration of the presence of a group 16SrI-B phytoplasma in association with sugarcane yellow leaf in Brazil.

Identification by computer-simulated RFLP of phytoplasmas associated with eggplant giant calyx representative of two subgroups, a lineage of 16SrIII-J and the new subgroup 16SrIII-U

Symptoms resembling giant calyx, a graft-transmissible disease, were observed on 1-5% of eggplant (aubergine; Solanum melongena L.) plants in production fields in Sao Paulo state, Brazil. Phytoplasmas were detected in 1 2 of 1 2 samples from symptomatic plants that were analysed by a nested PCR assay employing 16S rRNA gene primers R16mF2/R16mR1 followed by R16F2n/R16R2. RFLP analysis of the resulting rRNA gene products (1.2 kb) indicated that all plants contained similar phytoplasmas, each closely resembling strains previously classified as members of RFLP group 16SrIII (X-disease group). Virtual RFLP and phylogenetic analyses of sequences derived from PCR products identified phytoplasmas infecting eggplant crops grown in Piracicaba as a lineage of the subgroup 16SrIII-J, whereas phytoplasmas detected in plants grown in Braganca Paulista were tentatively classified as members of a novel subgroup 16SrIII-U. These findings confirm eggplant as a new host of group 16SrIII-J phytoplasmas and extend the known diversity of strains belonging to this group in Brazil.

Identification of microsatellites markers associated with yield components and quality parameters in sugarcane

Marker assisted selection depends on the identification of tightly linked association between marker and the trait of interest. In the present work, functional (EST-SSRs) and genomic (gSSRs) microsatellite markers were used to detect putative QTLs for sugarcane yield components (stalk number, diameter and height) and as well as for quality parameters (Brix, Pol and fibre) in plant cane. The mapping population (200 individuals) was derived from a bi-parental cross (IACSP95-3018 x IACSP93-3046) from the IAC Sugarcane Breeding Program. As the map is under construction, single marker trait association analysis based on the likelihood ratio test was undertaken to detect the QTLs. Of the 215 single dose markers evaluated (1:1 and 3:1), 90 (42%) were associated with putative QTLs involving 43 microsatellite primers (18 gSSRs and 25 EST-SSRs). For the yield components, 41 marker/trait associations were found: 20 for height, 6 for diameter and 15 for stalk number. An EST-SSRs marker with homology to non-phototropic hypocotyls 4 (NPH4) protein was associated with a putative QTL with positive effect for diameter as also with a negative effect for stalk number. In relation to the quality parameters, 18 marker trait associations were found for Brix, 19 for Pol, and 12 for fibre. For fibre, 58% of the QTLs detected showed a negative effect on this trait. Some makers associated with QTLs with a negative effect for fibre showed a positive effect for Pol, reflecting the negative correlation generally observed between these traits.

Test procedure for variable rate fertilizer on coffee

The objective was to develop and test a procedure for applying variable rates of fertilizers and evaluate yield response in coffee (Coffea arabica L.) with regard to the application of phosphorus and potassium. The work was conducted during the 2004 season in a 6.4 ha field located in central Sao Paulo state. Two treatments were applied with alternating strips of fixed and variable rates during the whole season: one following the fertilizing procedures recommended locally, and the other based on a grid soil sampling. A prototype pneumatic fertilizer applicator was used, carrying two conveyor belts, one for each row. Harvesting was done with a commercial harvester equipped with a customized volumetric yield monitor, separating the two treatments. Data were analyzed based on geostatistics, correlations and regressions. The procedure showed to be feasible and effective. The area that received fertilizer applications at a variable rate showed a 34% yield increase compared to the area that received a fixed rate. The variable rate fertilizer resulted in a savings of 23% in phosphate fertilizer and a 13% increase in potassium fertilizer, when compared to fixed rate fertilizer. Yield in 2005, the year after the variable rate treatments, still presented residual effect from treatments carried out during the previous cycle.

Identification and partial characterization of a Carica papaya-infecting isolate of Alfalfa mosaic virus in Brazil

A Carica papaya plant with severe yellow leaf mosaic, leaf distortion, and systemic necrosis was found in the municipality of Piracicaba, state of So Paulo, Brazil. Transmission electron microscopy (TEM) analysis revealed the presence of potyvirus-like particles and bacilliform particles similar to those of the Alfamovirus genus. The potyvirus was identified as Papaya ringspot virus-type P (PRSV-P). Biological, serological, and molecular studies confirmed the bacilliform virus as an isolate of Alfalfa mosaic virus (AMV). Partial nucleotide and amino acid sequences of the coat protein gene of this AMV isolate shared 97-98% identity with the AMV isolates in the GenBank database. This report is the first of the natural infection of papaya plants by AMV.

Identification of Staphylococcus aureus Carrying the mecA Gene in Ready-to-Eat Food Products Sold in Brazil

Since Staphylococcus aureus can cause several types of diseases, the development of antibiotic resistance poses an even greater threat to public health. S. aureus is known to possess the adaptive capability to promptly respond to antibiotics, making it resistant and increasingly difficult to treat; methicillin-resistant strains of S. aureus are a major concern with regard to this species. Previous studies reported the identification of methicillin-resistant S. aureus in food, demonstrating that this can represent a source of S. aureus which may carry the mecA gene. Fifty-seven S. aureus isolates, previously obtained from different types of food, were screened by polymerase chain reaction with specific primers for the mecA gene, which mediates methicillin resistance. Five (9%) isolates showed the presence of mecA gene, demonstrating that food may contain microorganisms possessing resistance genes. This study emphasizes the need to include food as a possible source of S. aureus carrying mecA gene and the need to monitor these products. Moreover, this is the first report of the presence of mecA genes in S. aureus isolated from ready-to-eat food in Brazil and Latin America.

Molecular identification of naturally occurring bacteriocinogenic and bacteriocinogenic-like lactic acid bacteria in raw milk and soft cheese

Lactic acid bacteria ( LAB) are currently used by food industries because of their ability to produce metabolites with antimicrobial activity against gram-positive pathogens and spoilage microorganisms. The objectives of this study were to identify naturally occurring bacteriocinogenic or bacteriocinogenic-like LAB in raw milk and soft cheese and to detect the presence of nisin-coding genes in cultures identified as Lactococcus lactis. Lactic acid bacteria cultures were isolated from 389 raw milk and soft cheese samples and were later characterized for the production of antimicrobial substances against Listeria monocytogenes. Of these, 58 (14.9%) LAB cultures were identified as antagonistic; the nature of this antagonistic activity was then characterized via enzymatic tests to confirm the proteinaceous nature of the antimicrobial substances. In addition, 20 of these antagonistic cultures were selected and submitted to genetic sequencing; they were identified as Lactobacillus plantarum (n = 2) and Lactococcus lactis ssp. lactis (n = 18). Nisin genes were identified by polymerase chain reaction in 7 of these cultures. The identified bacteriocinogenic and bacteriocinogenic-like cultures were highly variable concerning the production and activity of antimicrobial substances, even when they were genetically similar. The obtained results indicated the need for molecular and phenotypic methodologies to properly characterize bacteriocinogenic LAB, as well as the potential use of these cultures as tools to provide food safety.