Spectroscopic Multicomponent Analysis Using Multi-objective Optimization for Variable Selection

The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. These variables are obtained by a spectrophotometer device. This device measures hundreds of correlated variables related with physicocbemical properties and that can be used to estimate the component of interest. The problem is the selection of a subset of informative and uncorrelated variables that help the minimization of prediction error. Classical algorithms select a subset of variables for each compound considered. In this work we propose the use of the SPEA-II （strength Pareto evolutionary algorithm II）. We would like to show that the variable selection algorithm can selected just one subset used for multiple determinations using multiple linear regressions. For the case study is used wheat data obtained by NIR （near-infrared spectroscopy） spectrometry where the objective is the determination of a variable subgroup with information about E protein content （%）, test weight （Kg/HI）, WKT （wheat kernel texture） （%） and farinograph water absorption （%）. The results of traditional techniques of multivariate calibration as the SPA （successive projections algorithm）, PLS （partial least square） and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 37%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares.     

Clinical and epidemiological findings during a measles outbreak occurring in a population with a high vaccination coverage

Malignant mesothelioma is caused almost exclusively by occupational exposure to asbestos. During the past few years, however, increasing evidence has mounted that background exposure to asbestos could be sufficient to cause mesothelioma. Treatment of malignant mesothelioma remains a big problem. Some new approaches are on their way, and the most exciting ones are local immunotherapy in very early cases. Some success has been reported with local interferon treatment. As for treatment of metastatic pleural disease, the main purpose is symptomatic relief of dyspnea caused by fluid accumulation. The best way to achieve a lasting palliation is pleurodesis, and the most common way to do this, is by chemical means. The drug of choice in the United States has for many years been tetracycline, but since injectable tetracycline is no longer available, some substitute must be found. The substance that will "win" is not yet clear, but the two leading contestants are talc and doxycycline. Bleomycin also has its supporters, and a dark horse is quinacrine, which although not easily available in the United States, has been used in many European centers for decades.     

A computational model for developing semantic web-based educational systems

Recently, some initiatives to start the so-called semantic web-based educational systems (SWBES) have emerged in the field of artificial intelligence in education (AIED). The main idea is to incorporate semantic web resources to the design of AIED systems aiming to update their architectures to provide more adaptability, robustness and richer learning environments. However, the construction of such systems is highly complex and faces several challenges in terms of software engineering and artificial intelligence aspects. This paper presents a computational model for developing SWBES focusing on the problem of how to make the development easier and more useful for both developers and authors. In order to illustrate the features of the proposed model, a case study is presented. Furthermore, a discussion about the results regarding the computational model construction is available.     

Distributed planning and control systems for the virtual enterprise: organizational requirements and development life-cycle

This paper describes the requirements analysis and system specification of an Order Promise module to be used as part of a broader Decision Support System for production and operations planning of a Virtual Enterprise. This work is part of a broader project with a particular focus on the microelectronics industry which is a good example of Virtual Enterprise, and where a quick response to the customers needs and to unpredictable changes in production conditions is considered a major factor for success. First, the analysis and specification are presented within a development framework that involves the study of organizational issues of semiconductor enterprises. The use of ontological engineering for supporting the communication and shared understanding of the system concepts is explained and a virtual enterprise ontology is outlined. Following the clarification of the concept of virtual enterprise, the generic techno-organizational requirements for the information system are derived. Finally, a specification of the global planning module and a more detailed one regarding the order promise module is presented.     

Hematopoietic progenitor constituents and adherent cell progenitor morphology isolated from black-rumped agouti (Dasyprocta prymnolopha, Wagler 1831) bone marrow

Stem cells are present in the adult tissues of most diverse species. Bone marrow is recognized to be the most exploited site to obtain stem cells and cell progenitors. The objective of the present study was to characterize hematopoietic progenitor (HP) morphology and analyze the performance of adherent cell progenitors (ACPs) cultivated in vitro from black‐rumped agouti bone marrow (Dasyprocta prymnolopha). Bone marrow aspirates were obtained from tibia crest and used to prepare histological slides and identify cell morphology. Cells were also scattered on culture plates for later isolation, expansion, and quantification. Smears obtained from bone marrow demonstrated HPs at different stages of maturity. In culture, these cells showed fibroblastoid morphology and a strong tendency to form colonies, demonstrated by the presence of cell aggregates, cytoplasmic elongations lying side by side. An 80% cell confluence was observed at 18 days in culture and progressive reduction in the percentage of nonadherent mononuclear cells. After eight passes, a mean cell viability of 96.07% was observed, from a pool of 1.6 × 10⁷ cells (ACP). Thirteen 25‐cm² culture bottles were trypsinized, resuspended in freezing medium, stored in 14 criotubes at a concentration of 1 × 10⁶ cells per milliliter, and placed in liquid nitrogen at ?196°C. Agouti bone marrow demonstrated high plasticity, moreover different HP lines, and a population of adherent cells demonstrated morphology similar to mesenchymal stem cells in culture. Microsc. Res. Tech. 2012. © 2012 Wiley Periodicals, Inc.     

A modular Petri net to modeling and scenario analysis of a network of road traffic signals

The dynamic behavior of a group of traffic signals controlling a network of intersections is a complex discrete event system that can be modeled by Petri nets. The approach used in this paper proposes a components-based design, which increases modularity, reduces complexity and is a good practice according to modern Systems Engineering. The main system elements are specified based on the proposed Petri net component with time intervals associated to places. The specified models are simulated through the common token player algorithm, and formal analysis using invariants and theorem proving are applied to verify models' soundness and to reason on specific scenarios.     

Modelling and optimization of laminated adaptive shells of revolution

In this paper two shell finite element models are presented for the structural analysis of composite laminated piezoelectric shells. One is an axisymmetric conical frustum with two nodal rings and the other is a conic shell panel with eight nodes. Both models are based in a mixed laminated theory that combines a higher order shear deformation theory for the mechanical displacement field with a layerwise representation with linear functions for the electric potential through each piezoelectric layer. In order to obtain the optimal design sensitivities analysis and optimization techniques based in the nonlinear mathematical programming are used. The design objectives can be the minimization of the deformed structure or the maximization of the natural fundamental frequency and the design variables are the electric potential difference applied to the actuators or the ply thicknesses among others.     

Active control of forced vibrations in adaptive structures using a higher order model

This paper deals with a finite element formulation for active control of forced vibrations, including resonance, of thin plate/shell laminated structures with integrated piezoelectric layers, acting as sensors and actuators, based on third-order shear deformation theory. The finite element model is a single layer triangular nonconforming plate/shell element with 24 degrees of freedom for the generalized displacements, and one electrical potential degree of freedom for each piezoelectric element layer, which are surface bonded or embedded in the laminate.

The Newmark method is considered to calculate the dynamic response of the laminated structures, forced to vibrate in the first natural frequency. To achieve a mechanism of active control of the structure dynamic response, a feedback control algorithm is used, coupling the sensor and active piezoelectric layers. The model is applied in the solution of illustrative cases, and the results are presented and discussed.     

MODEL‐REFERENCE OUTPUT‐FEEDBACK SLIDING MODE CONTROLLER FOR A CLASS OF MULTIVARIABLE NONLINEAR SYSTEMS

This paper proposes an output‐feedback sliding mode control design for a class of uncertain multivariable plants with nonlinear disturbances. The approach used here is based on the control parameterization employed in model‐reference adaptive control. The disturbances are allowed to be unmatched and to depend not only on the plant output but also on its unmeas‐urable state. A less restrictive condition on the uncertainty of the high frequency gain matrix is also obtained.