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).

Group cognitive-behavioral therapy versus selective serotonin reuptake inhibitors for obsessive-compulsive disorder: A practical clinical trial

Clinical effectiveness of group cognitive-behavioral therapy (GCBT) versus fluoxetine in obsessive-compulsive disorder outpatients that could present additional psychiatric comorbidities was assessed. Patients (18-65 years; baseline Yale-Brown Obsessive-Compulsive-Scale [Y-BOCS] scores >= 16; potentially presenting additional psychiatric comorbidities) were sequentially allocated for treatment with GCBT (n = 70) or fluoxetine (n = 88). Mean Y-BOCS scores decreased by 23.13% in the GCBT and 21.54% in the SSRI groups (p = 0.875). Patients presented a mean of 2.7 psychiatric comorbidities. and 81.4% showed at least one additional disorder. A reduction of at least 35% in baseline Y-BOCS scores and CGI ratings of 1 (much better) or 2 (better) was achieved by 33.3% of GCBT patients and 27.7% in the SSRI group (p = 0.463). The Y-BOCS reduction was significantly lower in patients with one or more psychiatric comorbidities (21.15%, and 18.73%, respectively) than in those with pure OCD (34.62%; p = 0.034). Being male, having comorbidity of Major Depression, Social Phobia, or Dysthymia predicted a worse response to both treatments. Response rates to both treatments were similar and lower than reported in the literature, probably due to the broad inclusion criteria and the resulting sample more similar to the real world population. (C) 2011 Elsevier Ltd. All rights reserved.

Simulation results and applications of an advection bounded scheme to practical flows

This paper reports experiments on the use of a recently introduced advection bounded upwinding scheme, namely TOPUS (Computers & Fluids 57 (2012) 208-224), for flows of practical interest. The numerical results are compared against analytical, numerical and experimental data and show good agreement with them. It is concluded that the TOPUS scheme is a competent, powerful and generic scheme for complex flow phenomena.

Practical synthesis of a functionalized 1-oxo-1,2,3,4-tetrahydroisoquinoline-3-carboxylic acid

The synthesis of a functionalized 1-oxo-1,2,3,4-tetrahydroisoquinoline-3-carboxylic acid has been performed in 10 steps from the readily available dimedone. Only three purifications by flash chromatography are required through the whole sequence. The key step is the reaction between a dimedone derivative and a chlorotetrolic ester, that gives a tetrasubstituted benzene ring (through a Diels-Alder/retro- Diels-Alder process) bearing the substituents in the suitable positions for further functionalization. (C) 2012 Elsevier Ltd. All rights reserved.

Speed Neuro-fuzzy Estimator Applied To Sensorless Induction Motor Control

This work proposes the development of an Adaptive Neuro-fuzzy Inference System (ANFIS) estimator applied to speed control in a three-phase induction motor sensorless drive. Usually, ANFIS is used to replace the traditional PI controller in induction motor drives. The evaluation of the estimation capability of the ANFIS in a sensorless drive is one of the contributions of this work. The ANFIS speed estimator is validated in a magnetizing flux oriented control scheme, consisting in one more contribution. As an open-loop estimator, it is applied to moderate performance drives and it is not the proposal of this work to solve the low and zero speed estimation problems. Simulations to evaluate the performance of the estimator considering the vector drive system were done from the Matlab/Simulink(R) software. To determine the benefits of the proposed model, a practical system was implemented using a voltage source inverter (VSI) to drive the motor and the vector control including the ANFIS estimator, which is carried out by the Real Time Toolbox from Matlab/Simulink(R) software and a data acquisition card from National Instruments.

Novel Sealing Technique for Practical Liquid-Core Photonic Crystal Fibers

In this letter, we describe a simple and effective technique to prevent evaporation in liquid-core photonic crystal fibers (PCFs). The technique consists of using a micropipette to deploy a micro-droplet of an ultraviolet curable polymer adhesive in both core inputs. After it is cured, the adhesive creates sealing polymer plugs with quite satisfactory insertion loss (overall optical transmission of about 15%). Processed fibers remained liquid-filled for at least six weeks. From a practical point of view, we conducted a supercontinuum generation experiment in a water-core PCF to demonstrate a 120-minute spectral width stability and the ability to withstand at least 3-mW average power at the sealed fiber input. Similar experiments carried out with nonsealed fibers produced supercontinuum spectra lasting no longer than 10 minutes, with average powers kept below 0.5 mW to avoid thermally induced evaporation.

Effects of Methylphenidate on performance of a practical pistol shooting task: a quantitative electroencephalography (qEEG) study

Abstract Background The present study examined absolute alpha power using quantitative electroencephalogram (qEEG) in bilateral temporal and parietal cortices in novice soldiers under the influence of methylphenidate (MPH) during the preparatory aiming period in a practical pistol-shooting task. We anticipated higher bi-hemispheric cortical activation in the preparatory period relative to pre-shot baseline in the methylphenidate group when compared with the control group because methylphenidate has been shown to enhance task-related cognitive functions. Methods Twenty healthy, novice soldiers were equally distributed in control (CG; n = 10) and MPH groups 10 mg (MG; n = 10) using a randomized, double blind design. Subjects performed a pistol-shooting task while electroencephalographic activity was acquired. Results We found main effects for group and practice blocks on behavioral measures, and interactions between group and phases on electroencephalographic measures for the electrodes T3, T4, P3 and P4. Regarding the behavioral measures, the MPH group demonstrated significantly poorer in shooting performance when compared with the control and, in addition, significant increases in the scores over practice blocks were found on both groups. In addition, regarding the electroencephalographic data, we observed a significant increase in alpha power over practice blocks, but alpha power was significantly lower for the MPH group when compared with the placebo group. Moreover, we observed a significant decrease in alpha power in electrodes T4 and P4 during PTM. Conclusion Although we found no correlation between behavioral and EEG data, our findings show that MPH did not prevent the learning of the task in healthy subjects. However, during the practice blocks (PBs) it also did not favor the performance when compared with control group performance. It seems that the CNS effects of MPH demanded an initial readjustment period of integrated operations relative to the sensorimotor system. In other words, MPH seems to provoke a period of initial instability due to a possible modulation in neural activity, which can be explained by lower levels of alpha power (i.e., higher cortical activity). However, after the end of the PB1 a new stabilization was established in neural circuits, due to repetition of the task, resulting higher cortical activity during the task. In conclusion, MPH group performance was not initially superior to that of the control group, but eventually exceeded it, albeit without achieving statistical significance.

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.

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.