Investigation of a Pt3Sn/C Electro-Catalyst in a Direct Ethanol Fuel Cell Operating at Low Temperatures for Portable Applications

A 20% Pt3Sn/C catalyst was prepared by reduction with formic acid and used in a direct ethanol fuel cell at low temperatures. The electro-catalytic activity of this bimetallic catalyst was compared to that of a commercial 20% Pt/C catalyst. The PtSn catalyst showed better results in the investigated temperature range (30 degrees-70 degrees C). Generally, Sn promotes ethanol oxidation by adsorption of OH species at considerably lower potentials compared to Pt, allowing the occurrence of a bifunctional mechanism. The bimetallic catalyst was physico-chemically characterized by X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analyses. The presence of SnO2 in the bulk and surface of the catalyst was observed. It appears that SnO2 can enhance the ethanol electro-oxidation activity at low potentials due to the supply of oxygen-containing species for the oxidative removal of CO and CH3CO species adsorbed on adjacent Pt active sites.

New approach for power transformer protection based on intelligent hybrid systems

A power transformer needs continuous monitoring and fast protection as it is a very expensive piece of equipment and an essential element in an electrical power system. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can mislead the conventional protection affecting the power system stability negatively. This study proposes the development of a new algorithm to improve the protection performance by using fuzzy logic, artificial neural networks and genetic algorithms. An electrical power system was modelled using Alternative Transients Program software to obtain the operational conditions and fault situations needed to test the algorithm developed, as well as a commercial differential relay. Results show improved reliability, as well as a fast response of the proposed technique when compared with conventional ones.

Continuous-wave watt-level Nd:YLF/KGW Raman laser operating at near-IR, yellow and lime-green wavelengths

A Nd:YLF/KGW Raman laser has been investigated in this work. We have demonstrated CW output powers at six different wavelengths, 1147 nm (0.70 W), 1163 nm (0.95 W), 549 nm (0.65 W), 552 nm (1.90 W), 573 nm (0.60 W) and 581 nm (1.10 W), with higher peak powers achieved under quasi-CW operation. Raman conversion of the 1053 nm fundamental emission is reported for the first time, enabling two new wavelengths in crystalline Raman lasers, 549 nm and 552 nm. The weak thermal lensing associated with Nd:YLF has enabled to achieve good beam quality, M-2 <= 2.0, and stable operation in relatively long cavities. (C) 2012 Optical Society of America

Accuracy of five electronic foramen locators with different operating systems: na ex vivo study

Objective: The aim of this study was to evaluate, ex vivo, the precision of five electronic root canal length measurement devices (ERCLMDs) with different operating systems: the Root ZX, Mini Apex Locator, Propex II, iPex, and RomiApex A-15, and the possible influence of the positioning of the instrument tips short of the apical foramen. Material and Methods: Forty-two mandibular bicuspids had their real canal lengths (RL) previously determined. Electronic measurements were performed 1.0 mm short of the apical foramen (-1.0), followed by measurements at the apical foramen (0.0). The data resulting from the comparison of the ERCLMD measurements and the RL were evaluated by the Wilcoxon and Friedman tests at a significance level of 5%. Results: Considering the measurements performed at 0.0 and -1.0, the precision rates for the ERCLMDs were: 73.5% and 47.1% (Root ZX), 73.5% and 55.9% (Mini Apex Locator), 67.6% and 41.1% (Propex II), 61.7% and 44.1% (iPex), and 79.4% and 44.1% (RomiApex A-15), respectively, considering ±0.5 mm of tolerance. Regarding the mean discrepancies, no differences were observed at 0.0; however, in the measurements at -1.0, the iPex, a multi-frequency ERCLMD, had significantly more discrepant readings short of the apical foramen than the other devices, except for the Propex II, which had intermediate results. When the ERCLMDs measurements at -1.0 were compared with those at 0.0, the Propex II, iPex and RomiApex A-15 presented significantly higher discrepancies in their readings. Conclusions: Under the conditions of the present study, all the ERCLMDs provided acceptable measurements at the 0.0 position. However, at the -1.0 position, the ERCLMDs had a lower precision, with statistically significant differences for the Propex II, iPex, and RomiApex A-15.

Ecosystem approach and the Fuzzy logic: a dialectical proposal for information on Environmental Health

The ever-growing production and the problematization of Environmental Health have shown the need to apprehend complex realities and deal with uncertainties from the most diversified instruments which may even incorporate local aspects and subjectivities by means of qualitative realities, while broadening the capacity of the information system. This paper presents a view on the reflection upon some challenges and possible convergences between the ecosystemic approach and the Fuzzy logic in the process of dealing with scientific information and decision-making in Environmental Health.

Knowledge management, market orientation, innovativeness and organizational outcomes: a study on companies operating in Brazil

This article analyzes the study of the relationship among knowledge management, the company's market orientation, innovativeness and organizational outcomes. The survey was conducted based on a survey held with executives from 241 companies in Brazil. The evidence found indicates that knowledge management directly contributes to market orientation, but it requires a clearly defined strategic direction to achieve results and innovativeness. It was also concluded that knowledge, as a resource, leverages other resources of the company, while it requires a direction in relation to the organizational goals in order to be effective.

Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.

Link prediction using a probabilistic description logic

Due to the growing interest in social networks, link prediction has received significant attention. Link prediction is mostly based on graph-based features, with some recent approaches focusing on domain semantics. We propose algorithms for link prediction that use a probabilistic ontology to enhance the analysis of the domain and the unavoidable uncertainty in the task (the ontology is specified in the probabilistic description logic crALC). The scalability of the approach is investigated, through a combination of semantic assumptions and graph-based features. We evaluate empirically our proposal, and compare it with standard solutions in the literature.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).