Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.

Evaluation of the reference value for the Montenegro skin test

Abstract:INTRODUCTION:The Montenegro skin test (MST) has good clinical applicability and low cost for the diagnosis of American tegumentary leishmaniasis (ATL). However, no studies have validated the reference value (5mm) typically used to discriminate positive and negative results. We investigated MST results and evaluated its performance using different cut-off points.METHODS:The results of laboratory tests for 4,256 patients with suspected ATL were analyzed, and 1,182 individuals were found to fulfill the established criteria. Two groups were formed. The positive cutaneous leishmaniasis (PCL) group included patients with skin lesions and positive direct search for parasites (DS) results. The negative cutaneous leishmaniasis (NCL) group included patients with skin lesions with evolution up to 2 months, negative DS results, and negative indirect immunofluorescence assay results who were residents of urban areas that were reported to be probable sites of infection at domiciles and peridomiciles.RESULTS:The PCL and NCL groups included 769 and 413 individuals, respectively. The mean ± standard deviation MST in the PCL group was 12.62 ± 5.91mm [95% confidence interval (CI): 12.20-13.04], and that in the NCL group was 1.43 ± 2.17mm (95% CI: 1.23-1.63). Receiver-operating characteristic curve analysis indicated 97.4% sensitivity and 93.9% specificity for a cut-off of 5mm and 95.8% sensitivity and 97.1% specificity for a cut-off of 6mm.CONCLUSIONS:Either 5mm or 6mm could be used as the cut-off value for diagnosing ATL, as both values had high sensitivity and specificity.

Polymerase chain reaction with lesion scrapping for the diagnosis of human American tegumentary leishmaniasis

The objective of this work was to compare the polymerase chain reaction (PCR) using lesion scrapping with other conventional techniques for the diagnosis of the American tegumentary leishmaniasis (ATL). For this, patients with cutaneous lesions suspected to be ATL were studied. The DNA was amplified with the MP1L/MP3H primers. From the 156 studied patients, 79 (50.6%) presented positive parasite direct search (PD), 81 (51.9%) had positive Montenegro skin test (MST), and 90 (57.7%) presented PD and/or MST positive. The PCR was positive in all of the positive-PD patients (100% sensitivity), in 91.1% of the positive PD and/or MST patients, and in 27.3% of the patients that presented negative PD and positive MST. The PCR positivity was similar to the PD (P = 0.2482) and inferior to the MST (P = 0.0455), and to the PD/MST association (P = 0.0133). The high PCR sensitivity, and positivity in those cases where the PD was negative, highlights the importance of this technique as an auxiliary tool for the diagnosis of ATL.

Seleção de variáveis em QSAR

The process of building mathematical models in quantitative structure-activity relationship (QSAR) studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible. In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples.

Caracterização composicional e transesterificação de óleo de microalga: uma abordagem computacional

A procedure for compositional characterization of a microalgae oil is presented and applied to investigate a microalgae based biodiesel production process through process simulation. The methodology consists of: proposing a set of triacylglycerides (TAG) present in the oil; assuming an initial TAG composition and simulating the transesterification reaction (UNISIM Design, Honeywell) to obtain FAME characterization values (methyl ester composition); evaluating deviations of experimental from calculated values; minimizing the sum of squared deviations by a non-linear optimization algorithm, with TAG molar fractions as decision variables. Biodiesel from the characterized oil is compared to a rapeseed based biodiesel.

Molecular characterisation of intermediate snail hosts and the search for resistance genes

The relationship between schistosomes and their intermediate hosts is an extremely intricate one with strains and species of the parasite depending on particular species of snail, which in turn may vary in their susceptibility to the parasites. In order to gain a better understanding of the epidemiology of the disease we have been investigating the use of molecular markers for snail identification and for studying host-parasite relationships. In this paper we will draw on examples concerning schistosomiasis in West and East Africa to illustrate how a molecular analysis can be used as part of a "total evidence" approach to characterisation of Bulinus species and provide insights into parasite transmission. Particular emphasis is given to ribosomal RNA genes (rRNA), random amplified polymorphic DNA (RAPDs) and the mitochondrial gene cytochrome oxidase I (COI). Snails resistant to infection occur naturally and there is a genetic basis for this resistance. In Biomphalaria glabrata resistance to Schistosoma mansoni is known to be a polygenic trait and we have initiated a preliminary search for snail genomic regions linked to, or involved in, resistance by using a RAPD based approach in conjunction with progeny pooling methods. We are currently characterising a variety of STSs (sequence tagged sites) associated with resistance. These can be used for local linkage and interval mapping to define genomic regions associated with the resistance trait. The development of such markers into simple dot-blot or specific PCR-based assays may have a direct and practical application for the identification of resistant snails in natural populations.

Estudo do estado fundamental de aglomerados de silício via redes neurais

We introduce a global optimization method based on the cooperation between an Artificial Neural Net (ANN) and Genetic Algorithm (GA). We have used ANN to select the initial population for the GA. We have tested the new method to predict the ground-state geometry of silicon clusters. We have described the clusters as a piling of plane structures. We have trained three ANN architectures and compared their results with those of pure GA. ANN strongly reduces the total computational time. For Si10, it gained a factor of 5 in search speed. This method can be easily extended to other optimization problems.

DIRECT INFUSION ESI-MS APPLIED IN THE DETECTION OF BYPRODUCTS DUE TO REDUCTIVE DEGRADATION OF ACETAMIPRID BY ZERO-VALENT IRON

This study investigated the reductive degradation of acetamiprid (5 mg L-1) in aqueous medium (at pH 2.0) induced by zero-valent iron (50 mg). The process was monitored using high-performance liquid chromatography (HPLC) to determine the degradation rate as a function of reaction time, and direct infusion electrospray ionization mass spectrometry (DI-ESI-MS) to search for (and potentially characterize) any possible byproducts formed during degradation. The results obtained via HPLC showed that after 60 min, the degradation of the substrate reached nearly 100% in an acidic medium, whereas the mineralization rate (as determined by total organic carbon measurements) was as low as 3%. Data obtained by DI-ESI-MS showed that byproducts were formed mainly by insertions of hydrogen atoms into the nitrile, imine, and pyridine ring moieties, in addition to the observation of chlorine substitution by hydrogen replacement (hydrodechlorination) reactions.

Application of simulated annealing in simulation and optimization of drying process of Zea mays malt

Kinetic simulation and drying process optimization of corn malt by Simulated Annealing (SA) for estimation of temperature and time parameters in order to preserve maximum amylase activity in the obtained product are presented here. Germinated corn seeds were dried at 54-76 °C in a convective dryer, with occasional measurement of moisture content and enzymatic activity. The experimental data obtained were submitted to modeling. Simulation and optimization of the drying process were made by using the SA method, a randomized improvement algorithm, analogous to the simulated annealing process. Results showed that seeds were best dried between 3h and 5h. Among the models used in this work, the kinetic model of water diffusion into corn seeds showed the best fitting. Drying temperature and time showed a square influence on the enzymatic activity. Optimization through SA showed the best condition at 54 ºC and between 5.6h and 6.4h of drying. Values of specific activity in the corn malt were found between 5.26±0.06 SKB/mg and 15.69±0,10% of remaining moisture.

Optimization of image analysis techniques for quality assessment of whole-wheat breads made with fat replacer

The cellular structure of healthy food products, with added dietary fiber and low in calories, is an important factor that contributes to the assessment of quality, which can be quantified by image analysis of visual texture. This study seeks to compare image analysis techniques (binarization using Otsu’s method and the default ImageJ algorithm, a variation of the iterative intermeans method) for quantification of differences in the crumb structure of breads made with different percentages of whole-wheat flour and fat replacer, and discuss the behavior of the parameters number of cells, mean cell area, cell density, and circularity using response surface methodology. Comparative analysis of the results achieved with the Otsu and default ImageJ algorithms showed a significant difference between the studied parameters. The Otsu method demonstrated the crumb structure of the analyzed breads more reliably than the default ImageJ algorithm, and is thus the most suitable in terms of structural representation of the crumb texture.