Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation

Decision tree induction algorithms represent one of the most popular techniques for dealing with classification problems. However, traditional decision-tree induction algorithms implement a greedy approach for node splitting that is inherently susceptible to local optima convergence. Evolutionary algorithms can avoid the problems associated with a greedy search and have been successfully employed to the induction of decision trees. Previously, we proposed a lexicographic multi-objective genetic algorithm for decision-tree induction, named LEGAL-Tree. In this work, we propose extending this approach substantially, particularly w.r.t. two important evolutionary aspects: the initialization of the population and the fitness function. We carry out a comprehensive set of experiments to validate our extended algorithm. The experimental results suggest that it is able to outperform both traditional algorithms for decision-tree induction and another evolutionary algorithm in a variety of application domains.

A new HPLC-DAD-MS/MS method for the simultaneous determination of major compounds in the crude extract of Lychnophora salicifolia Mart. (Brazilian arnicao) leaves: Application to chemical variability evaluation

Lychnophora salicifolia Mart., which occurs in the Brazilian Cerrado in the states of Bahia and Minas Gerais as well as in the southeast of the state of Goias, is the most widely distributed and also the most polymorphic species of the genus. This plant is popularly known to have anti-inflammatory and analgesic activities. In this work, we have studied the variation in terms of polar metabolites of ninety-three Lychnophora salicifolia Mart, specimens collected from different regions of the Brazilian Cerrado. Identification of the constituents of this mixture was carried out by analysis of the UV spectra and MS data after chromatographic separation. Twenty substances were identified, including chlorogenic acid derivatives, a flavonoid C-glucoside, and other sesquiterpenes. The analytical method was validated, and the reliability and credibility of the results was ensured for the purposes of this study. The concentration range required for analysis of content variability within the analyzed group of specimens was covered with appropriate values of limits of detection and quantitation, as well as satisfactory precision and recovery. A quantitative variability was observed among specimens collected from the same location, but on average they were similar from a chemical viewpoint. In relation to the study involving specimens from different locations, there were both qualitative and quantitative differences among plants collected from different regions of Brazil. Statistical analysis revealed that there is a correlation between geographical localization and polar metabolites profile for specimens collected from different locations. This is evidence that the pattern of metabolites concentration depends on the geographical distribution of the specimens. (C) 2012 Elsevier B.V. All rights reserved.

Evaluation of sun protection factor of cosmetic formulations by a simple visual in vitro method mimicking the in vivo method

A new concept for in vitro visual evaluation of sun protection factor (SPF) of cosmetic formulations based on a supramolecular ultraviolet (UV) dosimeter was clearly demonstrated. The method closely parallels the method validated for in vivo evaluation and relies on the determination of the slightest perceptible bleaching of an iron-complex dye/nanocrystallinetitanium dioxide interface (UV dosimeter) in combination with an artificial skin substrate simulating the actual human skin in the presence and absence of a cosmetic formulation. The successful evaluation of SPF was ensured by the similarity of the erythema response of our dosimeter and human skin to UV light irradiation. A good linear correlation of in vitro and in vivo data up to SPF 40 confirmed the effectiveness of such a simple, cheap, and fast method. In short, here we unravel a convenient and accessible visual FPS evaluation method that can help improving the control on cosmetic products contributing to the reduction of skin cancer, one of the critical public health issues nowadays. (C) 2011 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:726732, 2012

Evaluation of Inductively Coupled Plasma Mass Spectrometry for Determining Ca, Cu, Fe, Mg, Mn, Se and Zn in Bovine Semen Samples using a Simple Sample Dilution Method

A simple and fast method for the determination of Ca, Cu, Fe, Mg, Mn, Se and Zn in bovine semen by quadrupole inductively coupled plasma spectrometry (q-ICP-MS) is described. Prior to analysis, samples (200 mu L) were diluted 1:50 in a solution containing 0.01% v/v Triton (R) X-100 and 0.5% v/v nitric acid and directly analyzed by ICP-MS. The limits of detection of the method are 0.3, 0.03, 0.2, 0.04, 0.04, 0.03 and 0.03 mu g L-1 for Ca-44, Cu-63, Fe-57, Mg-24, Zn-64, Se-82 and Mn-55, respectively. For purposes of comparison and method validation, four ordinary bovine semen samples were directly analyzed by ICP-MS and by flame atomic absorption spectrometry (FAAS) or graphite furnace atomic absorption spectrometry (GF AAS), with no statistical difference between the techniques at the 95% level when applying the t-test. Then, the proposed method was applied in the determinations of Ca, Cu, Fe, Mg, Mn, Se and Zn in collected samples of bovine semen from different breeds, which are used in reproduction programs and artificial insemination.

Evaluation of the efficiencies of helical anchor plates in sand by centrifuge model tests

The uplift capacity of helical anchors normally increases with the number of helical plates. The rate of capacity gain is variable, considering that the disturbance caused by the anchor installation is generally more pronounced in the soil mass above the upper plates than above the lower plates, because the upper soil layers are penetrated more times. The present investigation examines the effect of the number of helices on the performance of helical anchors in sand, based on the results of centrifuge model tests. Uplift loading tests were performed on 12 different types of piles installed in two containers of dry sand prepared with different densities. The measured fractions of the uplift capacity related to each individual helical plate of multi-helix anchors were compared with the fractions predicted by the individual bearing method. The results of this investigation indicate that in double- and triple-helix anchors, the contributions of the second and third plate to the total anchor uplift capacity decreased with the increase of sand relative density and plate diameter. In addition, these experiments demonstrated that the variation of the anchor load-displacement behavior with the number of helices also depends on these parameters.

Employment of a noninvasive magnetic method for evaluation of gastrointestinal transit in rats

AC Biosusceptometry (ACB) was previously employed towards recording gastrointestinal motility. Our data show a reliable and successful evaluation of gastrointestinal transit of liquid and solid meals in rats, considering the methods scarcity and number of experiments needed to endorsement of drugs and medicinal plants. ACB permits real time and simultaneous experiments using the same animal, preserving the physiological conditions employing both meals with simplicity and accuracy.

A new method for decision making in multi-objective optimization problems

Many engineering sectors are challenged by multi-objective optimization problems. Even if the idea behind these problems is simple and well established, the implementation of any procedure to solve them is not a trivial task. The use of evolutionary algorithms to find candidate solutions is widespread. Usually they supply a discrete picture of the non-dominated solutions, a Pareto set. Although it is very interesting to know the non-dominated solutions, an additional criterion is needed to select one solution to be deployed. To better support the design process, this paper presents a new method of solving non-linear multi-objective optimization problems by adding a control function that will guide the optimization process over the Pareto set that does not need to be found explicitly. The proposed methodology differs from the classical methods that combine the objective functions in a single scale, and is based on a unique run of non-linear single-objective optimizers.

Evaluation of inductively coupled plasma mass spectrometry for determining Ca, Cu, Fe, Mg, Mn, Se and Zn in bovine semen samples using a simple sample dilution method

A simple and fast method for the determination of Ca, Cu, Fe, Mg, Mn, Se and Zn in bovine semen by quadrupole inductively coupled plasma spectrometry (q-ICP-MS) is described. Prior to analysis, samples (200 µL) were diluted 1:50 in a solution containing 0.01% v/v Triton® X-100 and 0.5% v/v nitric acid and directly analyzed by ICP-MS. The limits of detection of the method are 0.3, 0.03, 0.2, 0.04, 0.04, 0.03 and 0.03 µg L-1 for 44Ca, 63Cu, 57Fe, 24Mg, 64Zn, 82Se and 55Mn, respectively. For purposes of comparison and method validation, four ordinary bovine semen samples were directly analyzed by ICP-MS and by flame atomic absorption spectrometry (FAAS) or graphite furnace atomic absorption spectrometry (GF AAS), with no statistical difference between the techniques at the 95% level when applying the t-test. Then, the proposed method was applied in the determinations of Ca, Cu, Fe, Mg, Mn, Se and Zn in collected samples of bovine semen from different breeds, which are used in reproduction programs and artificial insemination.

Hierarchical multi-label classification using local neural networks

Hierarchical multi-label classification is a complex classification task where the classes involved in the problem are hierarchically structured and each example may simultaneously belong to more than one class in each hierarchical level. In this paper, we extend our previous works, where we investigated a new local-based classification method that incrementally trains a multi-layer perceptron for each level of the classification hierarchy. Predictions made by a neural network in a given level are used as inputs to the neural network responsible for the prediction in the next level. We compare the proposed method with one state-of-the-art decision-tree induction method and two decision-tree induction methods, using several hierarchical multi-label classification datasets. We perform a thorough experimental analysis, showing that our method obtains competitive results to a robust global method regarding both precision and recall evaluation measures.