Offline Detection, Identification, and Correction of Branch Parameter Errors Based on Several Measurement Snapshots

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.

Low-intensity Ultrasound Increases FAK, ERK-1/2, and IRS-1 Expression of Intact Rat Bones in a Noncumulative Manner

Background Low-intensity pulsed ultrasound stimulation (LIPUS) reportedly increases osteogenesis in fracture models but fails in intact bone, suggesting LIPUS does not act on mechanotransduction and growth factor pathways of intact bone. Questions/Purposes We asked whether daily 20-minute LIPUS applied to intact tibias would act on bone proteins involved in mechanotransduction (focal adhesion kinase [FAK], and extracellular signal-regulated kinase-1/2 [ERK-1/2]), and growth factor signaling (insulin receptor substrate-1 [IRS-1]) pathways at 7, 14, and 21 days of treatment. Methods Immunoblotting was performed to detect FAK, ERK-1/2, and IRS-1 expression and activation from the stimulated intact tibias at 7, 14, and 21 days of daily 20-minute LIPUS. Results LIPUS increased FAK expression (at 7 days), ERK-1/2 (at 14 days), and IRS-1 (at 7 days), but expression decreased 7 days later, indicating a noncumulative effect of LIPUS. As only FAK expression was detected at 21 days, these observations suggest LIPUS influences nuclear reactions that may be modulated by a major cellular mechanism preferentially inhibiting IRS-1 expression and not FAK expression. Increased ERK-1/2 expression at 14 days suggests the differing mechanisms for promoting ERK-1/2, FAK, and IRS-1 syntheses. IRS-1 expression behaved similarly to FAK expression; therefore, LIPUS may modulate growth factor pathways. LIPUS increased sustained FAK and ERK-1/2 activation, but not IRS-1, suggesting sustained ERK-1/2 activation is not the result of mechanically induced growth factor activation. Conclusions LIPUS acts on mechanotransduction and growth factor pathways in intact bone in a noncumulative manner. Clinical relevance These data suggest LIPUS applied to intact bone acts on proteins involved in osteogenesis.

Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks

A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.

Laboratory measurements of biomarkers and individual performances in Chironomus xanthus to evaluate pesticide contamination of sediments in a river of southeastern Brazil

This study aimed at evaluating biomarkers, individual and population responses in the native Chironomus xanthus to assess the toxicity of pesticide-contaminated sediments from the Monjolinho River (Southeast Brazil). We measured cholinesterase (ChE) and glutathione S-transferase activities (GST), as biomarkers and survival, individual growth and adult emergence, as individual performances. There was no response of the ChE activity and a tendency to decreased GST activity in contaminated sites, but this was generally not statistically significant. Therefore, there was no association of the biomarker responses with exposure to sediment containing pesticides. In contrast, ash free dry mass was significantly increased and male emergence was decreased in C. xanthus exposed to the same sediments. In conclusion, the selected biomarkers were not sensitive and specific enough to detect and anticipate effects of pesticide contamination at the levels measured in the study area. Nevertheless, individual performances alterations pointed to potential pollution problems and possible ecological consequences. (C) 2010 Elsevier Inc. All rights reserved.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

A study of plastic deformation around a defect using the magnetic Barkhausen noise in ASTM 36 steel

The present work presents the measurements of the magnetic Barkhausen noise (MBN) in ASTM 36 steel samples around a pit under plastic deformation. The contour maps obtained from these Barkhausen noise measurements are compared with the finite element analysis of the ideal plastic deformation. Also, a parameter of the Barkhausen signal to detect the plastic deformation around the pit in ASTM 36 steel is obtained. Additionally to that, we propose another MBN parameter to estimate the pit width using the Barkhausen noise. (c) 2007 Elsevier Ltd. All rights reserved.

Registration of temporal sequences of coronal and sagittal MR images through respiratory patterns

This work discusses the determination of the breathing patterns in time sequence of images obtained from magnetic resonance (MR) and their use in the temporal registration of coronal and sagittal images. The registration is made without the use of any triggering information and any special gas to enhance the contrast. The temporal sequences of images are acquired in free breathing. The real movement of the lung has never been seen directly, as it is totally dependent on its surrounding muscles and collapses without them. The visualization of the lung in motion is an actual topic of research in medicine. The lung movement is not periodic and it is susceptible to variations in the degree of respiration. Compared to computerized tomography (CT), MR imaging involves longer acquisition times and it is preferable because it does not involve radiation. As coronal and sagittal sequences of images are orthogonal to each other, their intersection corresponds to a segment in the three-dimensional space. The registration is based on the analysis of this intersection segment. A time sequence of this intersection segment can be stacked, defining a two-dimension spatio-temporal (2DST) image. The algorithm proposed in this work can detect asynchronous movements of the internal lung structures and lung surrounding organs. It is assumed that the diaphragmatic movement is the principal movement and all the lung structures move almost synchronously. The synchronization is performed through a pattern named respiratory function. This pattern is obtained by processing a 2DST image. An interval Hough transform algorithm searches for synchronized movements with the respiratory function. A greedy active contour algorithm adjusts small discrepancies originated by asynchronous movements in the respiratory patterns. The output is a set of respiratory patterns. Finally, the composition of coronal and sagittal image pairs that are in the same breathing phase is realized by comparing of respiratory patterns originated from diaphragmatic and upper boundary surfaces. When available, the respiratory patterns associated to lung internal structures are also used. The results of the proposed method are compared with the pixel-by-pixel comparison method. The proposed method increases the number of registered pairs representing composed images and allows an easy check of the breathing phase. (C) 2010 Elsevier Ltd. All rights reserved.

Methodological analysis of gamma tomography system for large random packed columns

Gamma ray tomography experiments have been carried out to detect spatial patterns in the porosity in a 0.27 m diameter column packed with steel Rashig rings of different sizes: 12.6, 37.9, and 76 mm. using a first generation CT system (Chen et al., 1998). A fast Fourier transform tomographic reconstruction algorithm has been used to calculate the spatial variation over the column cross section. Cross-sectional gas porosity and solid holdup distribution were determinate. The values of cross-sectional average gas porosity were epsilon=0.849, 0.938 and 0.966 for the 12.6, 37.9, and 76 mm rings, respectively. Radial holdup variation within the packed bed has been determined. The variation of the circumferentially averaged gas holdup in the radial direction indicates that the porosity in the column wall region is a somewhat higher than that in the bulk region, due to the effect of the column wall. (C) 2009 Elsevier Ltd. All rights reserved.

Ciratefi: An RST-invariant template matching with extension to color images

Template matching is a technique widely used for finding patterns in digital images. A good template matching should be able to detect template instances that have undergone geometric transformations. In this paper, we proposed a grayscale template matching algorithm named Ciratefi, invariant to rotation, scale, translation, brightness and contrast and its extension to color images. We introduce CSSIM (color structural similarity) for comparing the similarity of two color image patches and use it in our algorithm. We also describe a scheme to determine automatically the appropriate parameters of our algorithm and use pyramidal structure to improve the scale invariance. We conducted several experiments to compare grayscale and color Ciratefis with SIFT, C-color-SIFT and EasyMatch algorithms in many different situations. The results attest that grayscale and color Ciratefis are more accurate than the compared algorithms and that color-Ciratefi outperforms grayscale Ciratefi most of the time. However, Ciratefi is slower than the other algorithms.

Occurrence of AFM(1) in urine samples of a Brazilian population and association with food consumption

This survey evaluated the presence of AFM(1) in human urine samples from a specific Brazilian population, as well as corn, peanut, and milk consumption measured by two types of food inquiry. Urine samples from donors who live in the city of Piracicaba, State of Sao Paulo, Brazil were analyzed to detect the presence of aflatoxin M(1) (AFM(1)). an aflatoxin B(1) metabolite, which may be used as aflatoxin B(1) exposure biomarker. The AFM(1) analysis was performed using immunoaffinity clean-up and detection by high-performance-liquid chromatography with fluorescence detector. A total of 69 samples were analyzed and 45 of them (65%) presented contaminations >= 1.8 pg ml(-1), which was the limit of quantification (LOQ). Seventy eight percent (n = 54) of the samples presented detectable concentrations of AFM(1) (>0.6 pg ml(-1)). The AFM(1) concentration among samples above LOQ ranged from 1.8 to 39.9 pg ml(-1). There were differences in food consumption profile among donors, although no association was found between food consumption and AFM(1) concentration in urine. The high frequency of positive samples suggests exposure of the populations studied to aflatoxins. (C) 2009 Elsevier Ltd. All rights reserved.

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

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.

Genetic Diversity and a PCR-Based Method for Xanthomonas axonopodis Detection in Passion Fruit

Xanthomonas axonopodis pv. passiflorae causes bacterial spot in passion fruit. It attacks the purple and yellow passion fruit as well as the sweet passion fruit. The diversity of 87 isolates of pv. passiflorae collected from across 22 fruit orchards in Brazil was evaluated using molecular profiles and statistical procedures, including an unweighted pair-group method with arithmetical averages-based dendrogram, analysis of molecular variance (AMOVA), and an assigning test that provides information on genetic structure at the population level. Isolates from another eight pathovars were included in the molecular analyses and all were shown to have a distinct repetitive sequence-based polymerase chain reaction profile. Amplified fragment length polymorphism technique revealed considerable diversity among isolates of pv. passiflorae, and AMOVA showed that most of the variance (49.4%) was due to differences between localities. Cluster analysis revealed that most genotypic clusters were homogeneous and that variance was associated primarily with geographic origin. The disease adversely affects fruit production and may kill infected plants. A method for rapid diagnosis of the pathogen, even before the disease symptoms become evident, has value for producers. Here, a set of primers (Xapas) was designed by exploiting a single-nucleotide polymorphism between the sequences of the intergenic 16S-23S rRNA spacer region of the pathovars. Xapas was shown to effectively detect all pv. passiflorae isolates and is recommended for disease diagnosis in passion fruit orchards.

Rapid assays for detection of glyphosate-resistant Lolium spp.

Diagnosing herbicide-resistant weed populations is the first step for herbicide resistance management. Monitoring the nature, distribution, and abundance of the resistant plants in fields demands efficient and effective screening tests. Different glyphosate resistant populations of Lolium multiflorum (VA) and L. rigidum (C) were used in assays for testing their effectiveness to detect herbicide resistance. According to a Petri dish bioassay 7 days after treatment (DAT), the VA and the C populations were 27 and 31 times more resistant to glyphosate than the susceptible populations, L. multiflorum (SM) and L. rigidum (SR), respectively. On a whole-plant bioassay (21 DAT), the VA and the C populations were 6 and 11 times more resistant to glyphosate than their respective susceptible populations. The susceptible populations accumulated 2.5 and 1.4-fold more shikimic acid 48 hours after treatment (HAT), than the resistant VA and C. Glyphosate gradually inhibited net photosynthesis in all populations but at 48-72 HAT the resistant plants recovered, whereas no recovery was detected in susceptible populations. All assays were capable of detecting the resistant populations and this may be useful for farmers and consultants as an effective tool to reduce the spread of the resistant populations through quicker implementation of alternative weed management practices. However, they differed in time, costs and equipments necessaries for successfully carrying on the tests. Regarding costs, the cheapest ones were Petri dish and whole-plant bioassays, but they are time-consuming methods as the major constraints are the collection of seeds from the field and at least some weeks to evaluate the resistance. The shikimic acid and net photosynthesis assays were the quickest ones but they demand sophisticated equipments which could restrict its use.