Coexistence of forest and savanna in an Amazonian area from a geological perspective

Question: How can the coexistence of savanna and forest in Amazonian areas with relatively uniform climates be explained? Location: Eastern Marajo Island, northeast Amazonia, Brazil. Methods: The study integrated floristic analysis, terrain morphology, sedimentology and delta(13)C of soil organic matter. Floristic analysis involved rapid ecological assessment of 33 sites, determination of occurrence, specific richness, hierarchical distribution and matrix of floristic similarity between paired vegetation types. Terrain characterization was based on analysis of Landsat images using 4(R), 5(G) and 7(B) composition and digital elevation model (DEM). Sedimentology involved field descriptions of surface and core sediments. Finally, radiocarbon dating and analysis of delta(13)C of soil profile organic matter and natural ecotone forest-savanna was undertaken. Results: Slight tectonic subsidence in eastern Marajo Island favours seasonal flooding, making it unsuitable for forest growth. However, this area displays slightly convex-up, sinuous morphologies related to paleochannels, covered by forest. Terra-firme lowland forests are expanding from west to east, preferentially occupying paleochannels and replacing savanna. Slack, running water during channel abandonment leads to disappearance of varzea/gallery forest at channel margins. Long-abandoned channels sustain continuous terra-firme forests, because of longer times for more species to establish. Recently abandoned channels have had less time to become sites for widespread tree development, and are either not vegetated or covered by savanna. Conclusion: Landforms in eastern Marajo Island reflect changes in the physical environment due to reactivation of tectonic faults during the latest Quaternary. This promoted a dynamic history of channel abandonment, which controlled a set of interrelated parameters (soil type, topography, hydrology) that determined species location. Inclusion of a geological perspective for paleoenvironmental reconstruction can increase understanding of plant distribution in Amazonia.

Influence of Post-Clearing Treatment on the Recovery of Herbaceous Plant Communities in Amazonian Secondary Forests

Secondary forests are an increasingly common feature in tropical landscapes worldwide and understanding their regeneration is necessary to design effective restoration strategies. It has previously been shown that the woody species community in secondary forests can follow different successional pathways according to the nature of past human activities in the area, yet little is known about patterns of herbaceous species diversity in secondary forests with different histories of land use. We compared the diversity and abundance of herbaceous plant communities in two types of Central Amazonian secondary forests-those regenerating on pastures created by felling and burning trees and those where trees were felled only. We also tested if plant density and species richness in secondary forests are related to proximity to primary forest. In comparison with primary forest sites, forests regenerating on non-burned habitats had lower herbaceous plant density and species richness than those on burned ones. However, species composition and abundance in non-burned stands were more similar to those of primary forest, whereas several secondary forest specialist species were found in burned stands. In both non-burned and burned forests, distance from the forest edge was not related to herbaceous density and species richness. Overall, our results suggest that the natural regeneration of herbaceous species in secondary tropical forests is dependent on a site`s post-clearing treatment. We recommend evaluating the land history of a site prior to developing and implementing a restoration strategy, as this will influence the biological template on which restoration efforts are overlaid.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Tick saliva induces regulatory dendritic cells: MAP-kinases and Toll-like receptor-2 expression as potential targets

Ticks (Acari: Ixodidae) are bloodsucking ectoparasitic arthropods of human and veterinary medical importance. Tick saliva has been shown to contain a wide range of bioactive molecules with vasodilatory, antihemostatic, and immunomodulatory activities. We have previously demonstrated that saliva from Rhipicephalus sanguineus ticks inhibits the maturation of dendritic cells (DCs) stimulated with LPS. Here we examined the mechanism of this immune subversion, evaluating the effect of tick saliva on Toll-like receptor (TLR)-4 signalling pathway in bone marrow-derived DCs. We demonstrated that R. sanguineus tick saliva impairs maturation of DCs stimulated with LIPS, a TLR-4 ligand, leading to increased production of interleukin (IL)-10 and reduced synthesis of IL-12p70 and TNF-alpha. The immunomodulatory effect of the tick saliva on the production of pro-inflammatory cytokines by DCs stimulated with LPS was associated with the observation that tick saliva inhibits the activation of the ERK 1/2 and p38 MAP kinases. These effects were independent of the expression of TLR-4 on the surface of DCs. Additionally, saliva-treated DCs also presented a similar pattern of cytokine modulation in response to other TLR ligands. Since the recent literature reports that several parasites evade immune responses through TLR-2-mediated production of IL-10, we evaluated the effect of tick saliva on the percentage of TLR-2(+) DCs stimulated with the TLR-2 ligand lipoteicoic acid (LTA). The data showed that the population of DCs expressing TLR-2 was significantly increased in DCs treated with LTA plus saliva. In addition, tick saliva alone increased the expression of TLR-2 in a dose- and time-dependent manner. Our data suggest that tick saliva induces regulatory DCs, which secrete IL-10 and low levels of IL-12 and TNF-alpha when stimulated by TLR ligands. Such regulatory DCs are associated with expression of TLR-2 and inhibition of ERK and p38, which promotes the production of IL-10 and thus down-modulates the host`s immune response, possibly favouring susceptibility to tick infestations. (C) 2009 Elsevier B.V. All rights reserved.

Human gait recognition using extraction and fusion of global motion features

This paper proposes a novel computer vision approach that processes video sequences of people walking and then recognises those people by their gait. Human motion carries different information that can be analysed in various ways. The skeleton carries motion information about human joints, and the silhouette carries information about boundary motion of the human body. Moreover, binary and gray-level images contain different information about human movements. This work proposes to recover these different kinds of information to interpret the global motion of the human body based on four different segmented image models, using a fusion model to improve classification. Our proposed method considers the set of the segmented frames of each individual as a distinct class and each frame as an object of this class. The methodology applies background extraction using the Gaussian Mixture Model (GMM), a scale reduction based on the Wavelet Transform (WT) and feature extraction by Principal Component Analysis (PCA). We propose four new schemas for motion information capture: the Silhouette-Gray-Wavelet model (SGW) captures motion based on grey level variations; the Silhouette-Binary-Wavelet model (SBW) captures motion based on binary information; the Silhouette-Edge-Binary model (SEW) captures motion based on edge information and the Silhouette Skeleton Wavelet model (SSW) captures motion based on skeleton movement. The classification rates obtained separately from these four different models are then merged using a new proposed fusion technique. The results suggest excellent performance in terms of recognising people by their gait.

Fault Detection in Power Distribution Systems Using Automated Integration of Computational Intelligence Tools

The main purpose of this paper is to present architecture of automated system that allows monitoring and tracking in real time (online) the possible occurrence of faults and electromagnetic transients observed in primary power distribution networks. Through the interconnection of this automated system to the utility operation center, it will be possible to provide an efficient tool that will assist in decisionmaking by the Operation Center. In short, the desired purpose aims to have all tools necessary to identify, almost instantaneously, the occurrence of faults and transient disturbances in the primary power distribution system, as well as to determine its respective origin and probable location. The compilations of results from the application of this automated system show that the developed techniques provide accurate results, identifying and locating several occurrences of faults observed in the distribution system.

A Fault-Tolerant Manipulator Robot Based on H(2), H(infinity), and Mixed H(2)/H(infinity) Markovian Controls

This paper develops a Markovian jump model to describe the fault occurrence in a manipulator robot of three joints. This model includes the changes of operation points and the probability that a fault occurs in an actuator. After a fault, the robot works as a manipulator with free joints. Based on the developed model, a comparative study among three Markovian controllers, H(2), H(infinity), and mixed H(2)/H(infinity) is presented, applied in an actual manipulator robot subject to one and two consecutive faults.

Quality of martensitic stainless steel type AISI-420 utilized in the manufacture surgical implements

Until now the martensitic stainless steel type AISI-420 is widely used in the manufacture of surgical implements. These implements present premature corrosion problems identified after cleaning, sterilization and cutting edge loss and/or rupture during the surgical processes.. This study evaluates the steel as to the chemical composition, hardness, microstructure and pitting corrosion resistance in a solution of enzyme detergent diluted in water by anodic cyclic polarization. This mixture is used in the cleaning of surgical implements that are submerged in this solution for 2 h before cleaning and sterilization. The results show steels with martensite microstructures in the ferrite phase, together with impurities. These presented low pitting potential values in compariston to steels with a fully martensitic microstructure.

Macro-Fiber Composite Actuators for Flow Control of a Variable Camber Airfoil

This research employs solid-state actuators for delay of flow separation seen in airfoils at low Reynolds numbers. The flow control technique investigated here is aimed for a variable camber airfoil that employs two active surfaces and a single four-bar (box) mechanism as the internal structure. To reduce separation, periodic excitation to the flow around the leading edge of the airfoil is induced by a total of nine piezocomposite actuated clamped-free unimorph benders distributed in the spanwise direction. An electromechanical model is employed to design an actuator capable of high deformations at the desired frequency for lift improvement at post-stall angles. The optimum spanwise distribution of excitation for increasing lift coefficient is identified experimentally in the wind tunnel. A 3D (non-uniform) excitation distribution achieved higher lift enhancement in the post-stall region with lower power consumption when compared to the 2D (uniform) excitation distribution. A lift coefficient increase of 18.4% is achieved with the identified non-uniform excitation mode at the bender resonance frequency of 125 Hz, the flow velocity of 5 m/s and at the reduced frequency of 3.78. The maximum lift (Clmax) is increased 5.2% from the baseline. The total power consumption of the flow control technique is 639 mW(RMS).

Piezoceramic Composite Actuators for Flow Control in Low Reynolds Number Airflow

The research presented here employs solid-state actuators for flow separation delay or for forced attachment of separated flow seen in airfoils at low Reynolds numbers. To reduce separation, periodic excitation to the flow around the leading edge of the airfoil is induced by Macro-Fiber Composite actuated clamped-free unimorph benders. An electromechanical model of the unimorph is briefly presented and parametric study is conducted to aid the design of a unimorph to output high deformation at a desired frequency. The optimum frequency and amplitude for lift improvement at post-stall angles are identified experimentally. Along with aerodynamic force and structural displacement measurements, helium bubble flow visualization is used to verify existing separated flow, and the attached flow induced by flow control. The lift enhancement induced by several flow control techniques is compared. A symmetric and non-uniform (3D) flow excitation results in the maximum lift enhancement at post-stall region at the lowest power consumption level. A maximum lift coefficient increase of 27.5% (in the post-stall region) is achieved at 125 Hz periodic excitation, with the 3D symmetric actuation mode at 5 m/s and the reduced frequency of 3.78. C(l,max) is increased 7.6% from the baseline.

Extended Fault-Location Formulation for Power Distribution Systems

In this paper, an extended impedance-based fault-location formulation for generalized distribution systems is presented. The majority of distribution feeders are characterized by having several laterals, nonsymmetrical lines, highly unbalanced operation, and time-varying loads. These characteristics compromise traditional fault-location methods performance. The proposed method uses only local voltages and currents as input data. The current load profile is obtained through these measurements. The formulation considers load variation effects and different fault types. Results are obtained from numerical simulations by using a real distribution system from the Electrical Energy Distribution State Company of Rio Grande do Sul (CEEE-D), Southern Brazil. Comparative results show the technique robustness with respect to fault type and traditional fault-location problems, such as fault distance, resistance, inception angle, and load variation. The formulation was implemented as embedded software and is currently used at CEEE-D`s distribution operation center.

Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

Phase Distance Relaying With Fault Resistance Compensation for Unbalanced Systems

This letter presents an extension of an existing ground distance relay algorithm to include phase distance relays. The algorithm uses a fault resistance estimation process in the phase domain, improving efficiency in the distance protection process. The results show that the algorithm is suitable for online applications, and that it has an independent performance from the fault resistance magnitude, the fault location, and the line asymmetry.

Further improvements on impedance-based fault location for power distribution systems

In this study, further improvements regarding the fault location problem for power distribution systems are presented. The proposed improvements relate to the capacitive effect consideration on impedance-based fault location methods, by considering an exact line segment model for the distribution line. The proposed developments, which consist of a new formulation for the fault location problem and a new algorithm that considers the line shunt admittance matrix, are presented. The proposed equations are developed for any fault type and result in one single equation for all ground fault types, and another equation for line-to-line faults. Results obtained with the proposed improvements are presented. Also, in order to compare the improvements performance and demonstrate how the line shunt admittance affects the state-of-the-art impedance-based fault location methodologies for distribution systems, the results obtained with two other existing methods are presented. Comparative results show that, in overhead distribution systems with laterals and intermediate loads, the line shunt admittance can significantly affect the state-of-the-art methodologies response, whereas in this case the proposed developments present great improvements by considering this effect.

Fuzzy risk index for power transformer failures due to external short-circuits

A novel methodology to assess the risk of power transformer failures caused by external faults, such as short-circuit, taking the paper insulation condition into account, is presented. The risk index is obtained by contrasting the insulation paper condition with the probability that the transformer withstands the short-circuit current flowing along the winding during an external fault. In order to assess the risk, this probability and the value of the degree of polymerization of the insulating paper are regarded as inputs of a type-2 fuzzy logic system (T2-FLS), which computes the fuzzy risk level. A Monte Carlo simulation has been used to find the survival function of the currents flowing through the transformer winding during a single-phase or a three-phase short-circuit. The Roy Billinton Test System and a real power system have been used to test the results. (C) 2008 Elsevier B.V. All rights reserved.