236 resultados para Computational Delay-Time
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
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In this paper we study the existence of mild solutions for a class of first order abstract partial neutral differential equations with state-dependent delay. (C) 2008 Elsevier Ltd. All rights reserved.
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It has been demonstrated that laser induced breakdown spectrometry (LIBS) can be used as an alternative method for the determination of macro (P, K. Ca, Mg) and micronutrients (B, Fe, Cu, Mn, Zn) in pellets of plant materials. However, information is required regarding the sample preparation for plant analysis by LIBS. In this work, methods involving cryogenic grinding and planetary ball milling were evaluated for leaves comminution before pellets preparation. The particle sizes were associated to chemical sample properties such as fiber and cellulose contents, as well as to pellets porosity and density. The pellets were ablated at 30 different sites by applying 25 laser pulses per site (Nd:YAG@1064 nm, 5 ns, 10 Hz, 25J cm(-2)). The plasma emission collected by lenses was directed through an optical fiber towards a high resolution echelle spectrometer equipped with an ICCD. Delay time and integration time gate were fixed at 2.0 and 4.5 mu s, respectively. Experiments carried out with pellets of sugarcane, orange tree and soy leaves showed a significant effect of the plant species for choosing the most appropriate grinding conditions. By using ball milling with agate materials, 20 min grinding for orange tree and soy, and 60 min for sugarcane leaves led to particle size distributions generally lower than 75 mu m. Cryogenic grinding yielded similar particle size distributions after 10 min for orange tree, 20 min for soy and 30 min for sugarcane leaves. There was up to 50% emission signal enhancement on LIBS measurements for most elements by improving particle size distribution and consequently the pellet porosity. (C) 2011 Elsevier B.V. All rights reserved.
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The aim of this work is to demonstrate the feasibility of laser induced breakdown spectrometry (LIBS) for the determination of macro and micronutrients in multielement tablets. The experimental setup was designed by using a laser Q-switch (Nd:YAG, 10 Hz, lambda = 1064 nm) and the emission signals were collected by lenses into an optical fiber coupled to an echelle spectrometer equipped with a high-resolution intensified charge coupled device (ICCD). Tablets were cryogenically ground and thereafter pelletized before LIBS analysis. Calibration curves were made by employing samples and mixtures of commercial multielement tablets with binders at different ratios. Best results were achieved by using the following experimental conditions: 29 J cm(-2) laser fluence, 165 mm lens to sample distance (f = 200 mm), 2.0 mu s delay time, 5.0 mu s integration time and 5 accumulated laser pulses. In general, the results obtained by the proposed LIBS procedure were in agreement with those obtained by ICP OES from the corresponding acid digests and coefficients variation of LIBS measurements varied from 2 to 16%. The metrological figures of merit indicate that LIBS fits for the intended purposes, and can be recommended for the analysis of multielement tablets and similar matrices aiming the determination of Ca, Cu, Fe, Mg, Mn, P and Zn.
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A simultaneous optimization strategy based on a neuro-genetic approach is proposed for selection of laser induced breakdown spectroscopy operational conditions for the simultaneous determination of macronutrients (Ca, Mg and P), micro-nutrients (B, Cu, Fe, Mn and Zn), Al and Si in plant samples. A laser induced breakdown spectroscopy system equipped with a 10 Hz Q-switched Nd:YAG laser (12 ns, 532 nm, 140 mJ) and an Echelle spectrometer with intensified coupled-charge device was used. Integration time gate, delay time, amplification gain and number of pulses were optimized. Pellets of spinach leaves (NIST 1570a) were employed as laboratory samples. In order to find a model that could correlate laser induced breakdown spectroscopy operational conditions with compromised high peak areas of all elements simultaneously, a Bayesian Regularized Artificial Neural Network approach was employed. Subsequently, a genetic algorithm was applied to find optimal conditions for the neural network model, in an approach called neuro-genetic, A single laser induced breakdown spectroscopy working condition that maximizes peak areas of all elements simultaneously, was obtained with the following optimized parameters: 9.0 mu s integration time gate, 1.1 mu s delay time, 225 (a.u.) amplification gain and 30 accumulated laser pulses. The proposed approach is a useful and a suitable tool for the optimization process of such a complex analytical problem. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
The performance of laser-induced breakdown spectrometry (LIBS) for the determination of Ba, Cd, Cr and Pb in toys has been evaluated by using a Nd:YAG laser operating at 1064 nm and an Echelle spectrometer with intensified charge-coupled device detector. Samples were purchased in different cities of Sao Paulo State market and analyzed directly without sample preparation. Laser-induced breakdown spectrometry experimental conditions (number of pulses, delay time. integration time gate and pulse energy) were optimized by using a Doehlert design. Laser-induced breakdown spectrometry signals correlated reasonably well with inductively coupled plasma optical emission spectrometry (ICP OES) concentrations after microwave-assisted acid digestion of selected samples. Thermal analysis was used for polymer identification and scanning electron microscopy to Visualize differences in crater geometry of different polymers employed for toy fabrication. Results indicate that laser-induced breakdown spectrometry can be proposed as a rapid screening method for investigation of potentially toxic elements in toys. The unique application of laser-induced breakdown spectrometry for identification of contaminants in successive layers of ink and polymer is also demonstrated. (C) 2009 Elsevier B.V. All rights reserved.
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Laser induced breakdown spectroscopy (LIBS) has become an analytical tool for the direct analysis of a large variety of materials in order to provide qualitative and/or quantitative information. However, there is a lack of information for LIBS analysis of agricultural and environmental samples. In this work a LIBS system has been evaluated for the determination of macronutrients (P, K, Ca, Mg) in pellets of vegetal reference materials. An experimental setup was designed by using a Nd:YAG laser operating at 1064 nm and an Echelle spectrometer with ICCD detector. The plasma temperature was estimated by Boltzmann plots and instrumental paragmeters such as delay time, lens-to-sample distance and pulse energy were evaluated. Certified reference materials as well as reference materials were used for analytical calibrations of P, K, Ca, and Mg. Most results of the direct analysis of plant samples by LIBS were in reasonable agreement with those obtained by ICP OES after wet acid decomposition. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
Laser induced breakdown spectrometry (LIBS) was applied for the determination of macro (P, K, Ca, Mg) and micronutrients (B, Cu, Fe, Mn and Zn) in sugar cane leaves, which is one of the most economically important crops in Brazil. Operational conditions were previously optimized by a neuro-genetic approach, by using a laser Nd:YAG at 1064 nm with 110 mJ per pulse focused on a pellet surface prepared with ground plant samples. Emission intensities were measured after 2.0 mu s delay time, with 4.5 mu s integration time gate and 25 accumulated laser pulses. Measurements of LIBS spectra were based on triplicate and each replicate consisted of an average of ten spectra collected in different sites (craters) of the pellet. Quantitative determinations were carried out by using univariate calibration and chemometric methods, such as PLSR and iPLS. The calibration models were obtained by using 26 laboratory samples and the validation was carried out by using 15 test samples. For comparative purpose, these samples were also microwave-assisted digested and further analyzed by ICP OES. In general, most results obtained by LIBS did not differ significantly from ICP OES data by applying a t-test at 95% confidence level. Both LIBS multivariate and univariate calibration methods produced similar results, except for Fe where better results were achieved by the multivariate approach. Repeatability precision varied from 0.7 to 15% and 1.3 to 20% from measurements obtained by multivariate and univariate calibration, respectively. It is demonstrated that LIBS is a powerful tool for analysis of pellets of plant materials for determination of macro and micronutrients by choosing calibration and validation samples with similar matrix composition.
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Objective: To compare the triggering performance of mid-level ICU mechanical ventilators with a standard ICU mechanical ventilator. Design: Experimental bench study. Setting: The respiratory care laboratory of a university-affiliated teaching hospital. Subject: A computerized mechanical lung model, the IngMar ASL5000. Interventions: Ten mid-level ICU ventilators were compared to an ICU ventilator at two levels of lung model effort, three combinations of respiratory mechanics (normal, COPD and ARDS) and two modes of ventilation, volume and pressure assist/control. A total of 12 conditions were compared. Measurements and main results: Performance varied widely among ventilators. Mean inspiratory trigger time was < 100 ms for only half of the tested ventilators. The mean inspiratory delay time (time from initiation of the breath to return of airway pressure to baseline) was longer than that for the ICU ventilator for all tested ventilators except one. The pressure drop during triggering (Ptrig) was comparable with that of the ICU ventilator for only two ventilators. Expiratory Settling Time (time for pressure to return to baseline) had the greatest variability among ventilators. Conclusions: Triggering differences among these mid-level ICU ventilators and with the ICU ventilator were identified. Some of these ventilators had a much poorer triggering response with high inspiratory effort than the ICU ventilator. These ventilators do not perform as well as ICU ventilators in patients with high ventilatory demand.
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In this paper we use the Hermite-Biehler theorem to establish results on the design of proportional plus integral plus derivative (PID) controllers for a class of time delay systems. Using the property of interlacing at high frequencies of the class of systems considered and linear programming we obtain the set of all stabilizing PID controllers. As far as we know, previous results on the synthesis of PID controllers rely on the solution of transcendental equations. This paper also extends previous results on the synthesis of proportional controllers for a class of delay systems Of retarded type to a larger class of delay systems. (C) 2009 Elsevier Ltd. All rights reserved.
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BACKGROUND - It is not clear how culture media used during transport and the interval between the biopsy procedure and final processing can affect the successful isolation of fungi. OBJECTIVE - The aim of this study was to investigate the effects of late inoculation of skin biopsies, transported in different sterile fluids, on the isolation rate of pathogenic fungi. METHODS -A total of 278 punch biopsy specimens were collected from 47 patients with suspected lesions of invasive mycoses. Each biopsy was transported in vials with Sabouraud medium with chloramphenicol or saline solution and finally inoculated on Sabouraud agar and 2% chloramphenicol after a 48-72-hour (early) or after 72-hour-7-day (late) interval, comprising four groups of study. RESULTS - The medians of isolation rate of the four sporotrichosis groups were 100%. For paracoccidioidomycosis, the medians ranged from 50% to 84%, with no statistically significant difference among the groups (p=0.88). CONCLUSION - It was concluded that skin biopsies can be transported in Sabouraud medium or saline solution within a 7-day interval from specimen collection up to final inoculation, at room temperature, maintaining viability and growth rate of fungus in culture.
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Background: Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges. Results: The results shown here are for an adapted subset of a Saccharomyces cerevisiae gene expression data set with low temporal resolution and poor statistics. The method reveals common transcription factors with a high confidence level and allows the construction of subnetworks with high biological relevance that reveals characteristic features of the processes driving the organism adaptations to specific environmental conditions. Conclusion: Our method allows a reliable and sophisticated analysis of microarray data even under severe constraints. The utilization of systems biology improves the biologists ability to elucidate the mechanisms underlying celular processes and to formulate new hypotheses.
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Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.
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This paper deals with the H(infinity) recursive estimation problem for general rectangular time-variant descriptor systems in discrete time. Riccati-equation based recursions for filtered and predicted estimates are developed based on a data fitting approach and game theory. In this approach, the nature determines a state sequence seeking to maximize the estimation cost, whereas the estimator tries to find an estimate that brings the estimation cost to a minimum. A solution exists for a specified gamma-level if the resulting cost is positive. In order to present some computational alternatives to the H(infinity) filters developed, they are rewritten in information form along with the respective array algorithms. (C) 2009 Elsevier Ltd. All rights reserved.
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The main purpose of this paper is to present architecture of automated system that allows monitoring and tracking in real time (online) the possible occurrence of faults and electromagnetic transients observed in primary power distribution networks. Through the interconnection of this automated system to the utility operation center, it will be possible to provide an efficient tool that will assist in decisionmaking by the Operation Center. In short, the desired purpose aims to have all tools necessary to identify, almost instantaneously, the occurrence of faults and transient disturbances in the primary power distribution system, as well as to determine its respective origin and probable location. The compilations of results from the application of this automated system show that the developed techniques provide accurate results, identifying and locating several occurrences of faults observed in the distribution system.
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This paper deals with the traditional permutation flow shop scheduling problem with the objective of minimizing mean flowtime, therefore reducing in-process inventory. A new heuristic method is proposed for the scheduling problem solution. The proposed heuristic is compared with the best one considered in the literature. Experimental results show that the new heuristic provides better solutions regarding both the solution quality and computational effort.