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.     

A new approach to designing reduced scale thermal-hydraulic experiments

Reduced scale experiments are often employed in engineering because they are much cheaper than real scale testing. Unfortunately, though, it is difficult to design a thermal-hydraulic circuit or equipment in reduced scale capable of reproducing, both accurately and simultaneously, all the physical phenomena that occur in real scale and operating conditions. This paper presents a methodology to designing thermal-hydraulic experiments in reduced scale based on setting up a constrained optimization problem that is solved using genetic algorithms (GAs). In order to demonstrate the application of the methodology proposed, we performed some investigations in the design of a heater aimed to simulate the transport of heat and momentum in the core of a pressurized water reactor (PWR) at 100% of nominal power and non-accident operating conditions. The results obtained show that the proposed methodology is a promising approach for designing reduced scale experiments.     

Preparation of polypropylene‐based nanocomposites using nanosized MCM‐41 as support and in situ polymerization

MCM‐41 nanoparticles were used for preparing nanocomposites through the in situ polymerization of propylene. The performance of the catalytic system and the final properties of the materials obtained are highly dependent on the methodology used for impregnation of the catalyst onto the support particles, and therefore an optimization study for the impregnation methodology of the catalyst (Me₂Si(Ind)₂ZrCl₂) was carried out. Two different methodologies were used; the results in terms of catalytic activity and polymer molecular masses indicated that the most promising one involved the pre‐activation of the catalyst with the cocatalyst, methylaluminoxane, followed by impregnation onto the MCM‐41 nanoparticles. Thus, an optimized route for the preparation of polypropylene nanocomposites achieving significant improvements in catalyst activity was developed. The nanocomposite materials were characterized by GPC, TGA and DSC. The dispersion state and the size of the nanoparticles incorporated in the polypropylene matrix were investigated by transmission electron microcopy. Additionally, this methodology allows simultaneous control of the desired amount of support and the concentration of catalyst to be used in the in situ polymerization. © 2015 Society of Chemical Industry     

Enzymatic synthesis of sugar esters and their potential as surface-active stabilizers of coconut milk emulsions

Sugar esters are compounds with surfactant properties (biosurfactants), i.e., capable of reducing the surface tension and promote the emulsification of immiscible liquids. On the other hand, as with all emulsions, coconut milk is not physically stable and is prone to phase separation. Therefore, the aim of this work was to evaluate the synthesis of fructose, sucrose and lactose esters from the corresponding sugars using Candida antarctica type B lipase immobilized in two different supports, namely acrylic resin and chitosan, and evaluate its application in the stabilization of coconut milk emulsions. The enzyme immobilized on chitosan showed the highest yield of lactose ester production (84.1%). Additionally, the production of fructose ester was found to be higher for the enzyme immobilized on the acrylic resin support (74.3%) as compared with the one immobilized on chitosan (70.1%). The same trend was observed for the sucrose ester, although with lower percentage yields. Sugar esters were then added to samples of fresh coconut milk and characterized according to their surface tension, emulsification index and particle size distribution. Although the microscopic analysis showed similar results for all sugar esters, results indicated lactose ester as the best biosurfactant, with a surface tension of 38.0 N/m and an emulsification index of 54.1%, when used in a ratio of 1:10 (biosurfactant:coconut milk, v/v) for 48 h experiments.     

Influence of mesostasis in volcanic rocks on the alkali-aggregate reaction

Mesostasis material present in the interstices of volcanic rocks is the main cause of the alkali-aggregate reaction (AAR) in concretes made with these rock aggregates. Mesostasis often is referred to as volcanic glass, because it has amorphous features when analyzed by optical microscopy. However, this study demonstrates that mesostasis in the interstitials of volcanic rocks most often consists of micro to cryptocrystalline mineral phases of quartz, feldspars, and clays. Mesostasis has been identified as having different characteristics, and, thus, this new characterization calls for a re-evaluation of their influence on the reactivity of the volcanic rocks. The main purpose of this study is to correlate the characteristics of mesostasis with the AAR in mortar bars containing basalts and rhyolites.     

Preconditioning approaches related to canonical correlation by use of cyclic form

There are many situations in engineering where we need to calculate the eigensystem of a matrix A which is given as a product of matrices, that is, A = A ₁ A ₂···A _p . Since, usually, we first perform the multiplication of the factors, the matrix A often becomes very ill-conditioned. Actually this happens even when A is a symmetric matrix, which will be our concern here. In this article we introduce a new approach to calculate the eigensystem of A without performing the indicated multiplication, or performing only partially the multiplication of the factors.     

How much nitrogen is fixed by biological symbiosis in tropical dry forests? 2. Herbs

Although biological nitrogen fixation (BNF) is considered the main input of N in mature and regenerating native tropical vegetation, it has seldom been quantified. Biomass and N accumulation and fixation were determined for spontaneously occurring herbaceous species in caatinga areas in four regeneration stages (2, 17, 39 and >50?years after abandonment from agricultural use). BNF was estimated using the ¹⁵N natural-abundance method. The 2-year regeneration area had the highest total herb (6,355?kg?ha^?1) and legume (262?kg?ha^?1) biomass production, N stocks (82?kg?ha^?1) and fixed N (5.0?kg?ha^?1). N₂-fixing legumes (nine species in the sampled area) contributed over 97?% of legume biomass in all areas. Macroptilium gracile added the largest amount of N (3.9?kg?ha^?1 in the 2-year regeneration area) because of its large biomass production (205?kg?ha^?1), although it was not the species with the highest proportion of fixed N (76?%). All of the N₂-fixing species obtained large proportions of their N from symbiosis, most of them more than 50?%.However, the amounts of fixed N per unit area were relatively low (0.22?C5.00?kg?ha^?1) because the biomass of N₂-fixing species was always less than 5?% of the total herb biomass.     

A framework for increasing the value of predictive data-driven models by enriching problem domain characterization with novel features

The need to leverage knowledge through data mining has driven enterprises in a demand for more data. However, there is a gap between the availability of data and the application of extracted knowledge for improving decision support. In fact, more data do not necessarily imply better predictive data-driven marketing models, since it is often the case that the problem domain requires a deeper characterization. Aiming at such characterization, we propose a framework drawn on three feature selection strategies, where the goal is to unveil novel features that can effectively increase the value of data by providing a richer characterization of the problem domain. Such strategies involve encompassing context (e.g., social and economic variables), evaluating past history, and disaggregate the main problem into smaller but interesting subproblems. The framework is evaluated through an empirical analysis for a real bank telemarketing application, with the results proving the benefits of such approach, as the area under the receiver operating characteristic curve increased with each stage, improving previous model in terms of predictive performance.