A flow-based analytical procedure for salbutamol determination exploiting chemiluminescence in a liquid-core waveguide

Salbutamol is a bronchodilator whose use is restricted due to its anabolic effects. A flow-based procedure for salbutamol determination based on the inhibition of chemiluminescence of the luminol/hypochlorite system was developed. A flow cell constructed with a liquid-core waveguide was employed to constrain the emitted radiation, minimizing losses during transport to detector. Linear response was observed within 2.5 x 10(-6) and 1.0 x 10(-5) mol L-1 with a detection limit estimated as 1 x 10(-7) mol L-1 at the 99.7% confidence level. The coefficient of variation (n = 20), sampling rate, and luminol consumption per determination were estimated as 2.8%, 164 determinations h(-1), and 50 mu g, respectively. Results for pharmaceutical samples were in agreement with those obtained by reference procedures at the 95% confidence level.

Sequential injections as an alternative to gradient exploitation for implementing differential kinetic analysis in a flow injection system

A novel flow-based strategy for implementing simultaneous determinations of different chemical species reacting with the same reagent(s) at different rates is proposed and applied to the spectrophotometric catalytic determination of iron and vanadium in Fe-V alloys. The method relies on the influence of Fe(II) and V(IV) on the rate of the iodide oxidation by Cr(VI) under acidic conditions, the Jones reducing agent is then needed Three different plugs of the sample are sequentially inserted into an acidic KI reagent carrier stream, and a confluent Cr(VI) solution is added downstream Overlap between the inserted plugs leads to a complex sample zone with several regions of maximal and minimal absorbance values. Measurements performed on these regions reveal the different degrees of reaction development and tend to be more precise Data are treated by multivariate calibration involving the PLS algorithm The proposed system is very simple and rugged Two latent variables carried out ca 95% of the analytical information and the results are in agreement with ICP-OES. (C) 2010 Elsevier B V. All rights reserved.

Total and inorganic mercury determination in fish tissue by flow injection cold vapour atomic fluorescence spectrometry

A simple and reliable method for Hg determination in fish samples has been developed. Lyophilised fish tissue samples were extracted in a 25% (w/v) tetramethylammonium hydroxide (TMAH) solution; the extracts were then analysed by FI-CVAFS. This method can be used to determine total and inorganic Hg, using the same FI manifold. For total Hg determination, a 0.1% (w/v) KMnO(4) solution was added to the FI manifold at the sample zone, followed by the addition of a 0.5% (w/v) SnCl(2) solution, whereas inorganic Hg was determined by adding a 0.1% (w/v) L-cysteine solution followed by a 1.0% (w/v) SnCl(2) solution to the FI system. The organic fraction was determined as the difference between total and inorganic Hg. Sample preparation, reagent consumption and parameters that can influence the FI-CVAFS performance were also evaluated. The limit of detection for this method is 3.7 ng g(-1) for total Hg and 4.3 ng g(-1) for inorganic Hg. The relative standard deviation for a 1.0 mu gL(-1) CH(3)Hg standard solution (n = 20) was 1.1%, and 1.3% for a 1.0 mu gL(-1) Hg(2+) standard solution (n = 20). Accuracy was assessed by the analysis of Certified Reference Material (dogfish: DORM-2, NRCC). Recoveries of 99.1% for total Hg and 93.9% inorganic Hg were obtained. Mercury losses were not observed when sample solutions were re-analysed after a seven day period of storage at 4 degrees C.

Evidences of turbulent mixing in multi-pumping flow systems

Multi-pumping flow systems exploit pulsed flows delivered by Solenoid pumps. Their improved performance rely on the enhanced radial mass transport inherent to the pulsed flow, which is a consequence of the establishment of vortices thus a tendency towards turbulent mixing. This paper presents several evidences of turbulent mixing in relation to pulsed flows. such as recorded peak shape, establishment of fluidized beds, exploitation of flow reversal, implementation of relatively slow chemical reactions and/or heating of the reaction medium. In addition, Reynolds number associated with the GO period of a pulsed flow is estimated and photographic images of dispersing samples flowing under laminar regime and pulsed flow conditions are presented. (C) 2009 Elsevier B.V. All rights reserved.

Simultaneous flow injection preconcentration of lead and cadmium using cloud point extraction and determination by atomic absorption spectrometry

A flow injection (FI) micelle-mediated separation/preconcentration procedure for the determination of lead and cadmium by flame atomic absorption spectrometry (FAAS) has been proposed. The analytes reacted with 1-(2-thiazolylazo)-2-naphthol (TAN) to form hydrophobic chelates, which were extracted into the micelles of 0.05% (w/v) Triton X-114 in a solution buffered at pH 8.4. In the preconcentration stage, the micellar solution was continuously injected into a flow system with four mini-columns packed with cotton, glass wool. or TNT compresses for phase separation. The analytes-containing micelles were eluted from the mini-columns by a stream of 3 mol L(-1) HCl solution and the analytes were determined by FAAS. Chemical and flow variables affecting the preconcentration of the analytes were studied. For 15 mL. of preconcentrated solution, the enhancement factors varied between 15.1 and 20.3, the limits of detection were approximately 4.5 and 0.75 mu g L(-1) for lead and cadmium, respectively. For a solution containing 100 and 10 mu g L(-1) of lead and cadmium, respectively, the R.S.D. values varied from 1.6 to 3.2% (n = 7). The accuracy of the preconcentration system was evaluated by recovery measurements on spiked water samples. The method was susceptible to matrix effects, but these interferences were minimized by adding barium ions as masking agent in the sample solutions, and recoveries from spiked sample varied in the range of 95.1-107.3%. (C) 2008 Elsevier B.V. All rights reserved.

An expert flow system involving in-line prior assay for turbidimetric determination of chloride and sulphate in natural waters

A multi-pumping flow system exploiting prior assay is proposed for sequential turbidimetric determination of sulphate and chloride in natural waters. Both methods are implemented in the same manifold that provides facilities for: in-line sample clean-up with a Bio-Rex 70 mini-column with fluidized beads: addition of low amounts of sulphate or chloride ions to the reaction medium for improving supersaturation; analyte precipitation with Ba(2+) or Ag(+); real-time decision on the need for next assay. The sample is initially run for chloride determination, and the analytical signal is compared with a preset value. If higher, the sample is run again, now for sulphate determination. The strategy may lead to all increased sample throughput. The proposed system is computer-controlled and presents enhanced figures of merit. About 10 samples are run per hour (about 60 measurements) and results are reproducible and Unaffected by the presence of potential interfering ions at concentration levels usually found in natural waters. Accuracy was assessed against ion chromatography. (C) 2008 Elsevier B.V. All rights reserved.

Zone trapping/merging zones in flow analysis: A novel approach for rapid assays involving relatively slow chemical reactions

A novel strategy for accomplishing zone trapping in flow analysis is proposed. The sample and the reagent solutions are simultaneously inserted into convergent carrier streams and the established zones merge together before reaching the detector, where the most concentrated portion of the entire sample zone is trapped. The main characteristics, potentialities and limitations of the strategy were critically evaluated in relation to an analogous flow system with zone stopping. When applied to the spectrophotometric determination of nitrite in river waters, the main figures of merit were maintained, exception made for the sampling frequency which was calculated as 189h(-1), about 32% higher relatively to the analogous system with zone stopping. The sample inserted volume can be increased up to 1.0 mL without affecting sampling frequency and no problems with pump heating or malfunctions were noted after 8-h operation of the system. In contrast to zone stopping, only a small portion of the sample zone is halted with zone trapping, leading to these beneficial effects. (C) 2011 Elsevier B.V. All rights reserved.

Somesthetic, gustatory, olfactory function and salivary flow in patients with neuropathic trigeminal pain

OBJECTIVES: To determine somesthetic, olfactory, gustative and salivary abnormalities in patients with burning mouth syndrome (BMS), idiopathic trigeminal neuralgia (ITN) and trigeminal postherpetic neuralgia (PHN). SUBJECTS AND METHODS: Twenty patients from each group (BMS, ITN, PHN) and 60 healthy controls were evaluated with a systematized quantitative approach of thermal (cold and warm), mechanical, pain, gustation, olfaction and salivary flow; data were analyzed with ANOVA, Tukey, Kruskal Wallis and Dunn tests with a level of significance of 5%. RESULTS: There were no salivary differences among the groups with matched ages; the cold perception was abnormal only at the mandibular branch of PHN (P = 0.001) and warm was abnormal in all trigeminal branches of PHN and BMS; mechanical sensitivity was altered at the mandibular branch of PHN and in all trigeminal branches of BMS. The salty, sweet and olfactory thresholds were higher in all studied groups; the sour threshold was lower and there were no differences of bitter. CONCLUSION: All groups showed abnormal thresholds of gustation and olfaction; somesthetic findings were discrete in ITN and more common in PHN and BMS; central mechanisms of balance of sensorial inputs might be underlying these observations. Oral Diseases (2010) 16, 482-487

Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration

The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS problems are computationally complex. For large-scale networks, the usual problem formulation has thousands of constraint equations. The node-depth encoding (NDE) enables a modeling of DSs problems that eliminates several constraint equations from the usual formulation, making the problem solution simpler. On the other hand, a multiobjective evolutionary algorithm (EA) based on subpopulation tables adequately models several objectives and constraints, enabling a better exploration of the search space. The combination of the multiobjective EA with NDE (MEAN) results in the proposed approach for solving DSs problems for large-scale networks. Simulation results have shown the MEAN is able to find adequate restoration plans for a real DS with 3860 buses and 632 switches in a running time of 0.68 s. Moreover, the MEAN has shown a sublinear running time in function of the system size. Tests with networks ranging from 632 to 5166 switches indicate that the MEAN can find network configurations corresponding to a power loss reduction of 27.64% for very large networks requiring relatively low running time.

Connection Admission Control for a WDM Optical Network Based on Traffic Monitoring and Bandwidth Release

We proposed a connection admission control (CAC) to monitor the traffic in a multi-rate WDM optical network. The CAC searches for the shortest path connecting source and destination nodes, assigns wavelengths with enough bandwidth to serve the requests, supervises the traffic in the most required nodes, and if needed activates a reserved wavelength to release bandwidth according to traffic demand. We used a scale-free network topology, which includes highly connected nodes ( hubs), to enhance the monitoring procedure. Numerical results obtained from computational simulations show improved network performance evaluated in terms of blocking probability.

Performance analysis of an optical network employing waveband and traffic grooming

This paper analyses an optical network architecture composed by an arrangement of nodes equipped with multi-granular optical cross-connects (MG-OXCs) in addition to the usual optical cross-connects (OXCs). Then, selected network nodes can perform both waveband as well as traffic grooming operations and our goal is to assess the improvement on network performance brought by these additional capabilities. Specifically, the influence of the MG-OXC multi-granularity on the blocking probability is evaluated for 16 classes of service over a network based on the NSFNet topology. A mechanism of fairness in bandwidth capacity is also added to the connection admission control to manage the blocking probabilities of all kind of bandwidth requirements. Comprehensive computational simulation are carried out to compare eight distinct node architectures, showing that an adequate combination of waveband and single-wavelength ports of the MG-OXCs and OXCs allow a more efficient operation of a WDM optical network carrying multi-rate traffic.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

An approach of optimal sensitivity applied in the tertiary loop of the automatic generation control

This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (C) 2008 Elsevier B.V. All rights reserved.

Neural network model for designing automotive devices using SMD LED

The advantages offered by the electronic component LED (Light Emitting Diode) have resulted in a quick and extensive application of this device in the replacement of incandescent lights. In this combined application, however, the relationship between the design variables and the desired effect or result is very complex and renders it difficult to model using conventional techniques. This paper consists of the development of a technique using artificial neural networks that makes it possible to obtain the luminous intensity values of brake lights using SMD (Surface Mounted Device) LEDs from design data. This technique can be utilized to design any automotive device that uses groups of SMD LEDs. The results of industrial applications using SMD LED are presented to validate the proposed technique.

An approach based on neural networks for estimation and generalization of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.