Melhores Empresas para se Trabalhar: Competências dos Líderes e Formação de Lideranças

Pesquisaram-se as práticas para definir, disseminar e avaliar um perfil de competências para lideranças, bem como os investimentos para formação de lideranças nas organizações brasileiras. A base de dados da FIA - Fundação Instituto de Administração, "150 melhores empresas para se trabalhar", registrou preocupação com lideranças. Alguns setores demonstraram inconstância no nível de aderência, no que tange ao perfil das competências dos líderes. Outros, como serviços, apontaram níveis inferiores, fato relevante, pois uma vantagem competitiva depende de ações assertivas dos empregados, sem o que se pode observar o declínio da qualidade no atendimento aos clientes.

PEDOT:PSS thin films: Applications in Bioelectronics

Owing to their capability of merging the properties of metals and conventional polymers, Conducting Polymers (CPs) are a unique class of carbon-based materials capable of conducting electrical current. A conjugated backbone is the hallmark of CPs, which can readily undergo reversible doping to different extents, thus achieving a wide range of electrical conductivities, while maintaining mechanical flexibility, transparency and high thermal stability. Thanks to these inherent versatility and attracting properties, from their discovery CPs have experienced incessant widespread in a great plethora of research fields, ranging from energy storage to healthcare, also encouraging the spring and growth of new scientific areas with highly innovative content. Nowadays, Bioelectronics stands out as one of the most promising research fields, dealing with the mutual interplay between biology and electronics. Among CPs, the polyelectrolyte complex poly (3,4-ethylenedioxythiophene): poly (styrenesulfonate) (PEDOT:PSS), especially in the form of thin films, has been emphasized as ideal platform for bioelectronic applications. Indeed, in the last two decades PEDOT:PSS has played a key role in the sensing of bioanalytes and living cells interfacing and monitoring. In the present work, development and characterization of two kinds of PEDOT:PSS-based devices for applications in Bioelectronics are discussed in detail. In particular, a low-cost amperometric sensor for the selective detection of Dopamine in a ternary mixture was optimized, taking advantage of the electrocatalytic and antifouling properties that render PEDOT:PSS thin films appealing tools for electrochemical sensing of bioanalytes. Moreover, the potentialities of this material to interact with live cells were explored through the fabrication of a microfluidic trapping device for electrical monitoring of 3D spheroids using an impedance-based approach.

Reduction capability of soil humic substances from the Rio Negro basin, Brazil, towards Hg(II) studied by a multimethod approach and principal component analysis (PCA)

This paper characterizes humic substances (HS) extracted from soil samples collected in the Rio Negro basin in the state of Amazonas, Brazil, particularly investigating their reduction capabilities towards Hg(II) in order to elucidate potential mercury cycling/volatilization in this environment. For this reason, a multimethod approach was used, consisting of both instrumental methods (elemental analysis, EPR, solid-state NMR, FIA combined with cold-vapor AAS of Hg(0)) and statistical methods such as principal component analysis (PCA) and a central composite factorial planning method. The HS under study were divided into groups, complexing and reducing ones, owing to different distribution of their functionalities. The main functionalities (cor)related with reduction of Hg(II) were phenolic, carboxylic and amide groups, while the groups related with complexation of Hg(II) were ethers, hydroxyls, aldehydes and ketones. The HS extracted from floodable regions of the Rio Negro basin presented a greater capacity to retain (to complex, to adsorb physically and/or chemically) Hg(II), while nonfloodable regions showed a greater capacity to reduce Hg(II), indicating that HS extracted from different types of regions contribute in different ways to the biogeochemical mercury cycle in the basin of the mid-Rio Negro, AM, Brazil. (c) 2007 Published by Elsevier B.V.

Sensor for cysteine based on oxovanadium(IV) complex of Salen modified carbon paste electrode

The electrochemical behavior of a carbon paste electrode modified (CPEM) with N,N′-ethylenebis(salicylideneiminato)oxovanadium(IV) complex ([(VO)-O-IV(Salen)]) was investigated as a new sensor for cysteine. Cyclic voltammetry at the modified electrode in 0.1 mol L-1 KCl Solution (pH 5.0) showed a single-electron reduction/oxidation of the Couple VO3+/VO2+. The CPEM with [VO(Salen)] presented good electrochemical stability in a wide pH range (4.0-10.0) and an ability to electrooxidate cysteine at 0.65 V versus SCE. These results demonstrate the viability of the use of this modified electrode as an amperometric sensor for cysteine determination. © 2004 Elsevier B.V. All rights reserved.

Revisitando el imaginario formal e ideológico del constructivismo Ruso

El constructivismo ruso se define como una práctica artística que respondió a las demandas sociales y culturales de una nueva sociedad. Se desarrolló como movimiento vanguardista que se propuso realizar un programa de vinculación de la obra artística con la vida, dejando atrás las formas del arte burgués y abriendo nuevas posibilidades a las funciones del arte en las condiciones sociales de la Revolución. El presente trabajo se propone la actualización de ese legado, me-diante apropiaciones irónicas de algunos de sus productos, en relación con las representaciones del heroísmo y el triunfalismo, del héroe y las masas, en los procesos políticos y culturales de la actualidad. En la medida que ese género de lenguaje ha sido utilizado en otros contex-tos, y las formulas constructivistas desbordan su enclave original en otras coor-denadas geopolíticas, este proyecto procura aprovechar las formulaciones ideoestéticas que fueron sustento de las propuestas constructivistas y productivis-tas al respecto de las experimentaciones del fotomontaje, la faktura y la factogra-fia.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Functionalized Carbon Micro/Nanostructures for Biomolecular Detection

Advancements in the micro-and nano-scale fabrication techniques have opened up new avenues for the development of portable, scalable and easier-to-use biosensors. Over the last few years, electrodes made of carbon have been widely used as sensing units in biosensors due to their attractive physiochemical properties. The aim of this research is to investigate different strategies to develop functionalized high surface carbon micro/nano-structures for electrochemical and biosensing devices. High aspect ratio three-dimensional carbon microarrays were fabricated via carbon microelectromechanical systems (C-MEMS) technique, which is based on pyrolyzing pre-patterned organic photoresist polymers. To further increase the surface area of the carbon microstructures, surface porosity was introduced by two strategies, i.e. (i) using F127 as porogen and (ii) oxygen reactive ion etch (RIE) treatment. Electrochemical characterization showed that porous carbon thin film electrodes prepared by using F127 as porogen had an effective surface area (Aeff 185%) compared to the conventional carbon electrode. To achieve enhanced electrochemical sensitivity for C-MEMS based functional devices, graphene was conformally coated onto high aspect ratio three-dimensional (3D) carbon micropillar arrays using electrostatic spray deposition (ESD) technique. The amperometric response of graphene/carbon micropillar electrode arrays exhibited higher electrochemical activity, improved charge transfer and a linear response towards H2O2 detection between 250μM to 5.5mM. Furthermore, carbon structures with dimensions from 50 nano-to micrometer level have been fabricated by pyrolyzing photo-nanoimprint lithography patterned organic resist polymer. Microstructure, elemental composition and resistivity characterization of the carbon nanostructures produced by this process were very similar to conventional photoresist derived carbon. Surface functionalization of the carbon nanostructures was performed using direct amination technique. Considering the need for requisite functional groups to covalently attach bioreceptors on the carbon surface for biomolecule detection, different oxidation techniques were compared to study the types of carbon–oxygen groups formed on the surface and their percentages with respect to different oxidation pretreatment times. Finally, a label-free detection strategy using signaling aptamer/protein binding complex for platelet-derived growth factor oncoprotein detection on functionalized three-dimensional carbon microarrays platform was demonstrated. The sensor showed near linear relationship between the relative fluorescence difference and protein concentration even in the sub-nanomolar range with an excellent detection limit of 5 pmol.

An automatic classifier of emotions built from entropy of noise

The electrocardiogram (ECG) signal has been widely used to study the physiological substrates of emotion. However, searching for better filtering techniques in order to obtain a signal with better quality and with the maximum relevant information remains an important issue for researchers in this field. Signal processing is largely performed for ECG analysis and interpretation, but this process can be susceptible to error in the delineation phase. In addition, it can lead to the loss of important information that is usually considered as noise and, consequently, discarded from the analysis. The goal of this study was to evaluate if the ECG noise allows for the classification of emotions, while using its entropy as an input in a decision tree classifier. We collected the ECG signal from 25 healthy participants while they were presented with videos eliciting negative (fear and disgust) and neutral emotions. The results indicated that the neutral condition showed a perfect identification (100%), whereas the classification of negative emotions indicated good identification performances (60% of sensitivity and 80% of specificity). These results suggest that the entropy of noise contains relevant information that can be useful to improve the analysis of the physiological correlates of emotion.