Pension funds and the financing productive investment: an analysis based on Brazil's recent experience

Includes bibliography

Genetic polymorphism, molecular characterization and relatedness of Macrobrachium species (Palaemonidae) based on RAPD-PCR.

The prawn genus Macrobrachium belongs to the family Palaemonidae. Its species are widely distributed in lakes, reservoirs, floodplains, and rivers in tropical and subtropical regions of South America. Globally, the genus Macrobrachium includes nearly 210 known species, many of which have economic and ecological importance. We analyzed three species of this genus (M. jelskii, M. amazonicum and M. brasiliense) using RAPD-PCR to assess their genetic variability, genetic structure and the phylogenetic relationship between them and to look for molecular markers that enable separation of M. jelskii and M. amazonicum, which are closely related syntopic species. Ten different random decamer primers were used for DNA amplification, yielding 182 fragments. Three of these fragments were monomorphic and exclusive to M. amazonicum or M. jelskii and can be used as specific molecular markers to identify and separate these two species. Similarity indices and a phylogenetic tree showed that M. amazonicum and M. jelskii are closest to each other, while M. brasiliense was the most differentiated species among them; this may be attributed to the different habitat conditions to which these species have been submitted. This information will be useful for further studies on these important crustacean species.

Characterization of the temperature, load and damage effects using piezoelectric transducer patches based on fuzzy clustering

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.

Shunt active compensation based on the Conservative Power Theory current's decomposition

Considering the operation of shunt active compensators, such as active power filters, this paper proposes possible compensation strategies by means of the recent formulation of the Conservative Power Theory (CPT). The CPT current's decomposition results in several current components, which are associated with specific load characteristics (power transfer, energy storage, unbalances and/or non linearities). These current components are used for the definition of different compensation strategies, which can be selective in terms of minimizing particular disturbing effects. In order to validate the applicability of these new compensation strategies, simulation and experimental results for three-phase four-wire systems are presented. © 2011 IEEE.

A DC-DC converter based on the three-state switching cell for high current and voltage step-down applications

This paper presents a pulsewidth modulation dc-dc nonisolated buck converter using the three-state switching cell, constituted by two active switches, two diodes, and two coupled inductors. Only part of the load power is processed by the active switches, reducing the peak current through the switches to half of the load current, as higher power levels can then be achieved by the proposed topology. The volume of reactive elements, i.e., inductors and capacitors, is also decreased since the ripple frequency of the output voltage is twice the switching frequency. Due to the intrinsic characteristics of the topology, total losses are distributed among all semiconductors. Another advantage of this converter is the reduced region for discontinuous conduction mode when compared to the conventional buck converter or, in other words, the operation range in continuous conduction mode is increased, as demonstrated by the static gain plot. The theoretical approach is detailed through qualitative and quantitative analyses by the application of the three-state switching cell to the buck converter operating in nonoverlapping mode $(D < 0.5)$. Besides, the mathematical analysis and development of an experimental prototype rated at 1 kW are carried out. The main experimental results are presented and adequately discussed to clearly identify its claimed advantages. © 1986-2012 IEEE.

Estimation of the metabolic equivalent (MET) of an exercise protocol based on indirect calorimetry

Objective: This study aimed to determine the energy expenditure (EE) in terms of caloric cost and metabolic equivalents (METs) of two sessions of an exercise protocol. Methods: Fifteen subjects (51.0 ± 5.5years) performed the exercise sessions (80min), which were composed by (warming, walking and flexibility exercises; Session A) and (warming, walking and local muscular endurance exercises; Session B). Heart hate (HR) was measured during each part of the sessions. In laboratory environment, maximal oxygen consumption (VO2max) and oxygen uptake in rest and exercise conditions (using mean HR obtained in classes) were measured on different days, using indirect calorimetry. Exercise METs were obtained by dividing VO2 in exercise (mL.kg-1.min-1) by VO2 in rest (mL.kg-1.min-1). The EE of the exercises was calculated by the formula: MET x Weight(kg) x Time(min)/60. The results were analyzed by ANOVA with Tuckey post hoc test (p < 0.05). Results: One MET for this group was 2.7 ± 0.1mL.kg-1.min-1. The mean METs of exercises were 4,7 ± 0,8 (warming), 5,8 ± 0,9 (walking) and 3,6 ± 0,7 (flexibility) on session A, and 4,6 ± 1,2 (warming), 5,6 ± 1,0 (walking) and 4.8 ± 1,0 (local muscular endurance exercises) on Session B. The training sessions showed similar energy cost (A: 398 ± 86.72 kcal and B: 404 ± 38.85 kcal; p > 0,05). None of activities were classified into vigorous intensity (> 7 METs). There were no differences on VO2 between walking (15,6 ± 2,8 or 15,4 ± 2,6 mL.kg-1.min-1) and local muscular endurance exercises (13,2 ± 2,9 mL.kg-1.min-1), although both were higher (p > 0.05) than flexibility exercises (10.1 ± 2.2 mL.kg-1.min-1). Conclusion: The proposed protocol achieves the physical activity needed by healthy adults to improve and maintain health, by their structure, moderate intensity, duration, frequency and caloric expenditure.

Toward pH-controllable bioelectrocatalysis for hydrogen peroxide based on polymer brushes

In the present work, a biosensor was built with smart material based on polymer brushes. The biosensor demonstrated a pH-sensitive on-off property, and it was further used to control or modulate the electrochemical responses of the biosensor. This property could be used to realize pH-controlled electrochemical reaction of hydrogen peroxide and HRP immobilized on polymer brushes. The composite film also showed excellent amperometric i-t response toward hydrogen peroxide in the concentration range of 0-13 μM. In future, this platform might be used for self-regulating targeted diagnostic, drug delivery and biofuel cell based on controllable bioelectrocatalysis. © 2013 Elsevier B.V.

Signal classification of submerged aquatic vegetation based on the hemispherical-conical reflectance factor spectrum shape in the yellow and red regions

The water column overlying the submerged aquatic vegetation (SAV) canopy presents difficulties when using remote sensing images for mapping such vegetation. Inherent and apparent water optical properties and its optically active components, which are commonly present in natural waters, in addition to the water column height over the canopy, and plant characteristics are some of the factors that affect the signal from SAV mainly due to its strong energy absorption in the near-infrared. By considering these interferences, a hypothesis was developed that the vegetation signal is better conserved and less absorbed by the water column in certain intervals of the visible region of the spectrum; as a consequence, it is possible to distinguish the SAV signal. To distinguish the signal from SAV, two types of classification approaches were selected. Both of these methods consider the hemispherical-conical reflectance factor (HCRF) spectrum shape, although one type was supervised and the other one was not. The first method adopts cluster analysis and uses the parameters of the band (absorption, asymmetry, height and width) obtained by continuum removal as the input of the classification. The spectral angle mapper (SAM) was adopted as the supervised classification approach. Both approaches tested different wavelength intervals in the visible and near-infrared spectra. It was demonstrated that the 585 to 685-nm interval, corresponding to the green, yellow and red wavelength bands, offered the best results in both classification approaches. However, SAM classification showed better results relative to cluster analysis and correctly separated all spectral curves with or without SAV. Based on this research, it can be concluded that it is possible to discriminate areas with and without SAV using remote sensing. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company

Due to an increased awareness and significant environmental pressures from various stakeholders, companies have begun to realize the significance of incorporating green practices into their daily activities. This paper proposes a framework using Fuzzy TOPSIS to select green suppliers for a Brazilian electronics company; our framework is built on the criteria of green supply chain management (GSCM) practices. An empirical analysis is made, and the data are collected from a set of 12 available suppliers. We use a fuzzy TOPSIS approach to rank the suppliers, and the results of the proposed framework are compared with the ranks obtained by both the geometric mean and the graded mean methods of fuzzy TOPSIS methodology. Then a Spearman rank correlation coefficient is used to find the statistical difference between the ranks obtained by the three methods. Finally, a sensitivity analysis has been performed to examine the influence of the preferences given by the decision makers for the chosen GSCM practices on the selection of green suppliers. Results indicate that the four dominant criteria are Commitment of senior management to GSCM; Product designs that reduce, reuse, recycle, or reclaim materials, components, or energy; Compliance with legal environmental requirements and auditing programs; and Product designs that avoid or reduce toxic or hazardous material use. © 2013 Elsevier B.V. All rights reserved.

A Framework to Optimize Biodiversity Restoration Efforts Based on Habitat Amount and Landscape Connectivity

The effectiveness of ecological restoration actions toward biodiversity conservation depends on both local and landscape constraints. Extensive information on local constraints is already available, but few studies consider the landscape context when planning restoration actions. We propose a multiscale framework based on the landscape attributes of habitat amount and connectivity to infer landscape resilience and to set priority areas for restoration. Landscapes with intermediate habitat amount and where connectivity remains sufficiently high to favor recolonization were considered to be intermediately resilient, with high possibilities of restoration effectiveness and thus were designated as priority areas for restoration actions. The proposed method consists of three steps: (1) quantifying habitat amount and connectivity; (2) using landscape ecology theory to identify intermediate resilience landscapes based on habitat amount, percolation theory, and landscape connectivity; and (3) ranking landscapes according to their importance as corridors or bottlenecks for biological flows on a broader scale, based on a graph theory approach. We present a case study for the Brazilian Atlantic Forest (approximately 150 million hectares) in order to demonstrate the proposed method. For the Atlantic Forest, landscapes that present high restoration effectiveness represent only 10% of the region, but contain approximately 15 million hectares that could be targeted for restoration actions (an area similar to today's remaining forest extent). The proposed method represents a practical way to both plan restoration actions and optimize biodiversity conservation efforts by focusing on landscapes that would result in greater conservation benefits. © 2013 Society for Ecological Restoration.

Genetic Structure of Lutzomyia longipalpis Populations in Mato Grosso Do Sul, Brazil, Based on Microsatellite Markers

Background:Lutzomyia longipalpis (Diptera: Psychodidae) is the major vector of Leishmania (Leishmania) infantum and thus plays a crucial role in the epidemiology of American visceral leishmaniasis (AVL). This vector is the best studied species of sand fly in the Neotropical region. Many studies claim that this vector is in fact a species complex; however there is still no consensus regarding the number of species that belong into this complex or the geographical distribution of sibling species. The aim of the present study was to analyze the genetic relationships within Lu. longipalpis populations in the state of Mato Grosso do Sul (MS), Brazil.Methodology/Principal Findings:We collected 30 Lu. longipalpis (15 females and 15 males) from five localities (Campo Grande, Três Lagoas, Aquidauana, Miranda and Bonito) and 30 Lu. Cruzi from Corumbá, totaling 180 sandflies from MS, and 30 Lu. longipalpis from Estrela de Alagoas, state of Alagoas (AL), Northeast Brazil. We show that eight previously described microsatellite loci were sufficient in distinguishing Lu. longipalpis from Lu. Cruzi, which is a closely related species, and in differentiating between Lu. longipalpis collected in MS versus Estrela de Alagoas. Analyses of the genotypes revealed introgression between sympatric Lu. longipalpis and Lu. Cruzi.Conclusions/Significance:Our findings support the hypothesis of cryptic species within the Lu. longipalpis complex. Furthermore, our data revealed introgression between Lu. longipalpis and Lu. cruzi. This phenomenon should be further investigated to determine the level and incidence of hybridization between these two species. We also demonstrated that microsatellite markers are a powerful tool for differentiating sand fly populations and species. The present study has elucidated the population structure of Lu. longipalpis in MS and, by extension, the Neotropical Lu. longipalpis complex itself. © 2013 Santos et al.

Evidence for euphotic zone anoxia during the deposition of Aptian source rocks based on aryl isoprenoids in petroleum, Sergipe-Alagoas Basin, northeastern Brazil

Four crude oil samples from the Sergipe-Alagoas Basin, northeastern Brazil, were analyzed using full scan gas chromatography-quadrupole mass spectrometry (GC-qMS) for biomarkers, in order to correlate them using aromatic carotenoids thereby enhancing knowledge about the depositional environment of their source rocks. The geochemical parameters derived from saturated fractions of the oils show evidence of little or no biodegradation and similar thermal maturation (Ts/(Ts+Tm) for terpanes, C29 αββ/(αββ+ααα), C27, and C29 20S/(20S+20R) for steranes). Low pristane/phytane ratios and the abundance of gammacerane and β-carotane are indicative of an anoxic and saline depositional environment for the source rocks. Moreover, we identified a large range of diagenetic and catagenetic products of the aromatic carotenoid isorenieratene, including C40, C33, and C32 diaryl isoprenoids and aryl isoprenoid derivatives with short side chains and/or additional rings. These results indicate anoxia in the photic zone during the deposition of the source rocks. © 2013 The Authors.

Age assessment based on dental calcification in individuals with Down syndrome

It is important to estimate both chronological age (CA) and maturational age of an individual, in order to perform orthopedic treatment or surgery, and in cases of lost documentation. Use of dental age (DA) for these purposes has been widely studied; however, the literature is scarce with regard to individuals with Down syndrome (DS), a prevalent condition worldwide. In this study the chronology of dental maturation was evaluated by analyzing the DA of individuals with DS based on the Chronological Mineralization Table proposed by Nolla (1960). Thus, second molars were evaluated in 57 panoramic radiographs of male and female individuals with DS, between 5 and 16 years-old. These data were compared with a control group of 191 nonsyndromic individuals of the same age group. Correlation between CA and DA was ascertained using Pearson's correlation coefficient (r), and the difference between these variables was measured using Student's t-test for paired samples and the method proposed by Bland and Altman. The difference between DA and CA was compared between the control and DS groups using Student's t-test for independent samples (α=0.05). DA was slightly lower than the CA; however, this difference was only significant for females. The difference between DA and CA was not significant between individuals with DS and control group (both genders, p=0.945; males, p=0.542; females, p=0.381). We concluded that dental maturation in individuals with DS occurs similarly to that of nonsyndromic individuals. © 2013 Elsevier Ltd.

Grãos e subprodutos da canola na alimentação de ovinos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)