Laser-induced breakdown spectroscopy and chemometrics for classification of toys relying on toxic elements

Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors` laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd. Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb. (C) 2011 Elsevier B.V. All rights reserved.

Exploring the emission intensities of ICP OES aided by chemometrics in the geographical discrimination of mineral waters

A rapid method for classification of mineral waters is proposed. The discrimination power was evaluated by a novel combination of chemometric data analysis and qualitative multi-elemental fingerprints of mineral water samples acquired from different regions of the Brazilian territory. The classification of mineral waters was assessed using only the wavelength emission intensities obtained by inductively coupled plasma optical emission spectrometry (ICP OES), monitoring different lines of Al, B, Ba, Ca, Cl, Cu, Co, Cr, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sb, Si, Sr, Ti, V, and Zn, and Be, Dy, Gd, In, La, Sc and Y as internal standards. Data acquisition was done under robust (RC) and non-robust (NRC) conditions. Also, the combination of signal intensities of two or more emission lines for each element were evaluated instead of the individual lines. The performance of two classification-k-nearest neighbor (kNN) and soft independent modeling of class analogy (SIMCA)-and preprocessing algorithms, autoscaling and Pareto scaling, were evaluated for the ability to differentiate between the various samples in each approach tested (combination of robust or non-robust conditions with use of individual lines or sum of the intensities of emission lines). It was shown that qualitative ICP OES fingerprinting in combination with multivariate analysis is a promising analytical tool that has potential to become a recognized procedure for rapid authenticity and adulteration testing of mineral water samples or other material whose physicochemical properties (or origin) are directly related to mineral content.

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.

Efficiency and feasibility of product disassembly: A case-based study

The productivity associated with commonly available disassembly methods today seldomly makes disassembly the preferred end-of-life solution for massive take back product streams. Systematic reuse of parts or components, or recycling of pure material fractions are often not achievable in an economically sustainable way. In this paper a case-based review of current disassembly practices is used to analyse the factors influencing disassembly feasibility. Data mining techniques were used to identify major factors influencing the profitability of disassembly operations. Case characteristics such as involvement of the product manufacturer in the end-of-life treatment and continuous ownership are some of the important dimensions. Economic models demonstrate that the efficiency of disassembly operations should be increased an order of magnitude to assure the competitiveness of ecologically preferred, disassembly oriented end-of-life scenarios for large waste of electric and electronic equipment (WEEE) streams. Technological means available to increase the productivity of the disassembly operations are summarized. Automated disassembly techniques can contribute to the robustness of the process, but do not allow to overcome the efficiency gap if not combined with appropriate product design measures. Innovative, reversible joints, collectively activated by external trigger signals, form a promising approach to low cost, mass disassembly in this context. A short overview of the state-of-the-art in the development of such self-disassembling joints is included. (c) 2008 CIRP.

Finite element analysis of concrete cracking at early age

The study of the early age concrete properties is becoming more important, as the thermal effects and the shrinkage, even in the first hours, could generate cracks, increasing the permeability of the structure and being able to induce problems of durability and functionality in the same ones. The detailed study of the stresses development during the construction process can be decisive to keep low the cracking levels. In this work a computational model, based on the finite element method, was implemented to simulate the early age concrete behavior and, specially, the evaluation of the cracking risk. The finite element analysis encloses the computational modeling of the following phenomena: chemical, thermal, moisture diffusion and mechanical which occur at the first days after the concrete cast. The developed software results were compared with experimental values found in the literature, demonstrating an excellent approach for all the implemented analysis.

Identification of Elastic, Dielectric, and Piezoelectric Constants in Piezoceramic Disks

Three-dimensional modeling of piezoelectric devices requires a precise knowledge of piezoelectric material parameters. The commonly used piezoelectric materials belong to the 6mm symmetry class, which have ten independent constants. In this work, a methodology to obtain precise material constants over a wide frequency band through finite element analysis of a piezoceramic disk is presented. Given an experimental electrical impedance curve and a first estimate for the piezoelectric material properties, the objective is to find the material properties that minimize the difference between the electrical impedance calculated by the finite element method and that obtained experimentally by an electrical impedance analyzer. The methodology consists of four basic steps: experimental measurement, identification of vibration modes and their sensitivity to material constants, a preliminary identification algorithm, and final refinement of the material constants using an optimization algorithm. The application of the methodology is exemplified using a hard lead zirconate titanate piezoceramic. The same methodology is applied to a soft piezoceramic. The errors in the identification of each parameter are statistically estimated in both cases, and are less than 0.6% for elastic constants, and less than 6.3% for dielectric and piezoelectric constants.

Thermodynamic self-consistency issues related to the Cluster Variation Method: The case of the BCC Cr-Fe (Chromium-Iron) system

The Cluster Variation Method (CVM), introduced over 50 years ago by Prof. Dr. Ryoichi Kikuchi, is applied to the thermodynamic modeling of the BCC Cr-Fe system in the irregular tetrahedron approximation, using experimental thermochemical data as initial input for accessing the model parameters. The results are checked against independent data on the low-temperature miscibility gap, using increasingly accurate thermodynamic models, first by the inclusion of the magnetic degrees of freedom of iron and then also by the inclusion of the magnetic degrees of freedom of chromium. It is shown that a reasonably accurate description of the phase diagram at the iron-rich side (i.e. the miscibility gap borders and the Curie line) is obtained, but only at expense of the agreement with the above mentioned thermochemical data. Reasons for these inconsistencies are discussed, especially with regard to the need of introducing vibrational degrees of freedom in the CVM model. (C) 2008 Elsevier Ltd. All rights reserved.

Modeling technique for honeycomb FRP deck bridges via finite elements

Honeycomb structures have been used in different engineering fields. In civil engineering, honeycomb fiber-reinforced polymer (FRP) structures have been used as bridge decks to rehabilitate highway bridges in the United States. In this work, a simplified finite-element modeling technique for honeycomb FRP bridge decks is presented. The motivation is the combination of the complex geometry of honeycomb FRP decks and computational limits, which may prevent modeling of these decks in detail. The results from static and modal analyses indicate that the proposed modeling technique provides a viable tool for modeling the complex geometry of honeycomb FRP bridge decks. The modeling of other bridge components (e.g., steel girders, steel guardrails, deck-to-girder connections, and pier supports) is also presented in this work.

Thermodynamic Assessment of the Aluminum Corner of the Al-Fe-Mn-Si System

A new assessment of the aluminum corner of the quaternary Al-Fe-Mn-Si system has been made that extends beyond the COST-507 database. This assessment makes use of a recent, improved description of the ternary Al-Fe-Si system. In the present work, modeling of the Al-rich corner of the quaternary Al-Fe-Mn-Si system has been carried out by introducing Fe solubility into the so-called alpha-AlMnSi and beta-AlMnSi phases of the Al-Mn-Si system. A critical review of the data available on the quaternary system is presented and used for the extension of the description of these ternary phases into the quaternary Al-Fe-Mn-Si.

Impact of Endovascular Technique in Vascular Surgery Training at a Large University Hospital in Brazil

OBJECTIVES: The aim of this study was to determine the impact of endovascular surgery versus open vascular technique training in a Brazilian teaching service. DESIGN: Cross-sectional study. SETTING: Hospital das Clinicas-Faculty of Medicine University of Sao Paulo, a tertiary institutional hospital Brazil. PARTICIPANTS: We reviewed 1,040 arterial operations performed during 2 distinct time periods: January 1995 to December 1996, and January 2006 to December 2007. Based on the disease treated, the procedures were classified into the following 5 groups: abdominal aortic aneurysms (AAA), aorto-iliac obstructive disease (Al), obstructive disease of the femoropoplitealtibial segment (FP), carotid disease (C), and others (0). The operations were also divided into an endovascular surgery (ES) group and an open surgery (OS) group. We compared the number of open and endovascular procedures for each arterial disease group during both periods. RESULTS: During the 2006-2007 period, 654 patients were treated surgically, whereas over the 1995-1996 period, 386 arterial operations were performed. A. significant increase in endovascular procedures (p < 0.001) was found from the 1995-1996 period to the 2006-201)7 period (35 vs 351, respectively) in all groups, whereas open surgery showed a slight increase in the number of procedures in the AAA and 0 groups only. In the 1995-1996 period, OS was the primary surgical method for all groups, but in the 2006-2007 time frame, OS was performed more frequently than ES only in the AAA and 0 groups. Considering all vascular disease groups, OS was the technique used in 90.9% (351 of 386) of the operations during 1995-1996, whereas in 2006-2007, OS was performed in only 46.3% (303 of 654) of the procedures. CONCLUSIONS: The increase in the number of ES observed over the past decade has had little impact on OS procedures performed at our medical center, not bringing harm to open surgical training. (J Surg 68:19-23. (C) 2011 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.)

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Surgical Outcomes after Preceptored Laparoscopic Colorectal Surgery: Results of a Brazilian Preceptorship Program

Background/Aims: Safety of laparoscopic colectomy education methods remains unknown. This study aimed at comparing the outcomes of patients undergoing preceptored laparoscopic colectomy with patients operated on by the same preceptor. Methodology: A prospective analysis of 30 preceptored operations performed by nine surgeons (PD group) between 2006 and 2008 was conducted. Data of 30 operations matched for diagnosis and surgery type conducted by the same preceptor (P group) were evaluated. Results: Median age was 56.2 (26-80) and 55.2 (22-81) respectively in P and PD group (p=0.804). Eleven (36.7%) were male in P group, 16 (53.3%) in PD group (p=0.194). Preceptored operations were not significantly longer than operations performed by the preceptor (198 vs. 156 min) - p=0.072. Length of hospital stay did not differ [4 days (3-12) in P group, and 5 (3-15) in PD group, p=0.296]. Conversion occurred in 4 cases in PD and in 2 in P group (p=0.389). Morbidity was similar (23.3% in P and 26.7% in PD group). One patient from P and two from PD group needed re-operation. No deaths occurred. Conclusions: Laparoscopic colorectal surgery preceptorship programs in surgeon learner`s place are safe. Surgeons` introduction through basic and hands-on courses is required for skills acquisition needed to minimize adverse outcomes.

THE EFFECTS OF BROMAZEPAM ON THE PERFORMANCE OF A SENSORY-MOTOR ACTIVITY: AN ELECTROENCEPHALOGRAPHIC STUDY

Aims. To investigate the effects of using bromazepam on the relative power in alpha while performing a typing task. Bearing in mind the particularities of each brain hemisphere, our hypothesis was that measuring the relative power would allow its to investigate the effects of bromazepam oil specific areas of the cortex. More, specifically, we expected to observe different patterns of powers in sensory-motor integration, attention and activation processes. Subjects and methods. The sample was made up of 39 subjects (15 males and 24 females) with a mean age of 30 +/- 10 years. The control (placebo) and experimental (3 mg and 6 mg of bromazepam) groups were trained ill the typing task with a randomised double-blind model. Results. A three-way ANOVA and Scheffe test were used to analyse interactions between the factors condition and moment, and between condition and sector Conclusions. The doses used ill this study facilitated motor performance of the typing task. Ill this study, the use of the drug did not prevent learning of the task, but it did appear to concentrate mental effort on more restricted and specific aspects of typing. It also seemed to influence the rhythm and effectiveness of the operations performed during mechanisms related to the encoding and storage often, information. Likewise, a predominance of activity was observed in the left (dominant) frontal area in the 3 mg bromazepam group, which indicates that this close of the drug affords the subject a greater degree of directionality of cortical activity for planning and performing the task. [REV NEUROL 2009; 49: 295-9]

Haplotypes of the bovine IgG2 heavy gamma chain in tick-resistant and tick-susceptible breeds of cattle

Bovines present contrasting, heritable phenotypes of infestations with the cattle tick, Rhipicephalus (Boophilus) microplus. Tick salivary glands produce IgG-binding proteins (IGBPs) as a mechanism for escaping from host antibodies that these ectoparasites ingest during blood meals. Allotypes that occur in the constant region of IgG may differ in their capacity to bind with tick IGBPs; this may be reflected by the distribution of distinct allotypes according to phenotypes of tick infestations. In order to test this hypothesis, we investigated the frequency of haplotypes of bovine IgG2 among tick-resistant and tick-susceptible breeds of bovines. Sequencing of the gene coding for the heavy chain of IgG2 from 114 tick-resistant (Bos taurus indicus, Nelore breed) and tick-susceptible (B. t. taurus, Holstein breed) bovines revealed SNPs that generated 13 different haplotypes, of which 11 were novel and 5 were exclusive of Holstein and 3 of Nelore breeds. Alignment and modeling of coded haplotypes for hinge regions of the bovine IgG2 showed that they differ in the distribution of polar and hydrophobic amino acids and in shape according to the distribution of these amino acids. We also found that there was an association between genotypes of the constant region of the IgG2 heavy chain with phenotypes of tick infestations. These findings open the possibility of investigating if certain IgG allotypes hinder the function of tick IGBPs. If so, they may be markers for breeding for resistance against tick infestations.