Microwave-Assisted Reaction Sintering of Bismuth Titanate-Based Ceramics

Bismuth titanate-based ceramics, pure and doped with 5 mol% WO₃, were prepared by reaction-sintering using a microwave oven. High densities, ≥96% of theoretical density were achieved with very short thermal treatments, with soaking time ranging from 5 to 15 min. Relatively small platelet-like grains were formed, and microstructure seemed not to be strongly affected by doping nor soaking time. Electrical measurements were performed and, as expected, a decrease of electrical conductivity was observed in WO₃-doped materials. The results of reaction-sintered samples, both conventional as well as microwave sintered, are compared with those of samples prepared with previously calcined powders and sintered using microwaves as well as a conventional electric furnace.     

Time-Temperature-Transformation Curves for Kaolinite-α-Alumina

The C-shaped time-temperature-transformation curves (T-T-T curves) of cristobalite formation and the L-shaped T-T-T curves of α-alumina reaction were established for a high-purity kaolinite-α-alumina mixture during heating. The results revealed that cristobalite formation in kaolinite was retarded by the presence of α-alumina between 1250° and 1350°C and was totally prohibited above 1380°C due to the reaction of kaolinite with α-alumina to form secondary mullite. The reaction of α-alumina with kaolinite was initiated at about 1250°C. It became quite extensive above 1380°C and was extremely fast at 1600°C and above, indicating the strong effect of the eutectic liquid formation at ∼1587°C in silica-alumina. The effectiveness of the established T-T-T curves was demonstrated and discussed.     

DEMORS: A hybrid multi-objective optimization algorithm using differential evolution and rough set theory for constrained problems

The aim of this paper is to show how the hybridization of a multi-objective evolutionary algorithm (MOEA) and a local search method based on the use of rough set theory is a viable alternative to obtain a robust algorithm able to solve difficult constrained multi-objective optimization problems at a moderate computational cost. This paper extends a previously published MOEA [Hernández-Díaz AG, Santana-Quintero LV, Coello Coello C, Caballero R, Molina J. A new proposal for multi-objective optimization using differential evolution and rough set theory. In: 2006 genetic and evolutionary computation conference (GECCO’2006). Seattle, Washington, USA: ACM Press; July 2006], which was limited to unconstrained multi-objective optimization problems. Here, the main idea is to use this sort of hybrid approach to approximate the Pareto front of a constrained multi-objective optimization problem while performing a relatively low number of fitness function evaluations. Since in real-world problems the cost of evaluating the objective functions is the most significant, our underlying assumption is that, by aiming to minimize the number of such evaluations, our MOEA can be considered efficient. As in its previous version, our hybrid approach operates in two stages: in the first one, a multi-objective version of differential evolution is used to generate an initial approximation of the Pareto front. Then, in the second stage, rough set theory is used to improve the spread and quality of this initial approximation. To assess the performance of our proposed approach, we adopt, on the one hand, a set of standard bi-objective constrained test problems and, on the other hand, a large real-world problem with eight objective functions and 160 decision variables. The first set of problems are solved performing 10,000 fitness function evaluations, which is a competitive value compared to the number of evaluations previously reported in the specialized literature for such problems. The real-world problem is solved performing 250,000 fitness function evaluations, mainly because of its high dimensionality. Our results are compared with respect to those generated by NSGA-II, which is a MOEA representative of the state-of-the-art in the area.     

Multi‐agent system for knowledge‐based event recognition and composition

This work presents a multi‐agent system for knowledge‐based high‐level event composition, which interprets activities, behaviour and situations semantically in a scenario with multi‐sensory monitoring. A perception agent (plurisensory agent and visual agent)‐based structure is presented. The agents process the sensor information and identify (agent decision system) significant changes in the monitored signals, which they send as simple events to the composition agent that searches for and identifies pre‐defined patterns as higher‐level semantic composed events. The structure has a methodology and a set of tools that facilitate its development and application to different fields without having to start from scratch. This creates an environment to develop knowledge‐based systems generally for event composition. The application task of our work is surveillance, and event composition/inference examples are shown which characterize an alarming situation in the scene and resolve identification and tracking problems of people in the scenario being monitored.     

Protein radial distribution function (P-RDF) and Bayesian-Regularized Genetic Neural Networks for modeling protein conformational stability: chymotrypsin inhibitor 2 mutants

Development of novel computational approaches for modeling protein properties is a main goal in applied Proteomics. In this work, we reported the extension of the radial distribution function (RDF) scores formalism to proteins for encoding 3D structural information with modeling purposes. Protein-RDF (P-RDF) scores measure spherical distributions on protein 3D structure of 48 amino acids/residues properties selected from the AAindex data base. P-RDF scores were tested for building predictive models of the change of thermal unfolding Gibbs free energy change (DeltaDeltaG) of chymotrypsin inhibitor 2 upon mutations. In this sense, an ensemble of Bayesian-Regularized Genetic Neural Networks (BRGNNs) yielded an optimum nonlinear model for the conformational stability. The ensemble predictor described about 84% and 70% variance of the data in training and test sets, respectively.     

The effect of the martensitic packet size on the machinability of modified AISI P20 prehardened mold steel

The effect of martensitic packet size on the machinability of prehardened mold steel at a hardness of ~40 HRC (typical hardness for prehardened mold steels) was studied in terms of cutting force and tool life. The machinability tests were performed in end milling using coated, cemented carbide tools at three different cutting speeds. The results showed that an increase in the martensite packet size led to higher cutting force and shorter tool life. The increase in cutting force was related to the increase of work hardening. The work material with a coarser martensite packet size showed a higher amount of work hardening that can explain the higher cutting force. The longer tool life in the workpieces with finer structure was correlated to smaller amplitude of the variation in cutting force.     

Vitamin C Enhances Vitamin E Status and Reduces Oxidative Stress Indicators in Sea Bass Larvae Fed High DHA Microdiets

Docosahexaenoic acid (DHA) is an essential fatty acid necessary for many biochemical, cellular and physiological functions in fish. However, high dietary levels of DHA increase free radical injury in sea bass (Dicentrarchus labrax) larvae muscle, even when vitamin E (α-tocopherol, α-TOH) is increased. Therefore, the inclusion of other nutrients with complementary antioxidant functions, such as vitamin C (ascorbic acid, vitC), could further contribute to prevent these lesions. The objective of the present study was to determine the effect of vitC inclusion (3,600?mg/kg) in high DHA (5?% DW) and α-TOH (3,000?mg/kg) microdiets (diets 5/3,000 and 5/3,000?+?vitC) in comparison to a control diet (1?% DHA DW and 1,500?mg/kg of α-TOH; diet 1/1,500) on sea bass larvae growth, survival, whole body biochemical composition and thiobarbituric acid reactive substances (TBARS) content, muscle morphology, skeletal deformities and antioxidant enzymes, insulin-like growth factors (IGFs) and myosin expression (MyHC). Larvae fed diet 1/1,500 showed the best performance in terms of total length, incidence of muscular lesions and ossification degree. IGFs gene expression was elevated in 5/3,000 diet larvae, suggesting an increased muscle mitogenesis that was confirmed by the increase in the mRNA copies of MyHC. vitC effectively controlled oxidative damages in muscle, increased α-TOH larval contents and reduced TBARS content and the occurrence of skull deformities. The results of the present study showed the antioxidant synergism between vitamins E and C when high contents of DHA are included in sea bass larvae diets.     

Study of the influence of adding styrene–ethylene/butadiene–styrene in acrylonitrile–butadiene–styrene and polyethylene blends

This work studies the recovery of two grades of acrylonitrile–butadiene–styrene (ABS) contaminated with low‐density polyethylene (LDPE), by adding styrene–ethylene/butadiene–styrene (SEBS). To simulate contaminated ABS, virgin ABS was mixed with 1, 2, 4, and 8% of LDPE and then extruded at 220°C. After this, the ABS with the highest percentage of LDPE (8%) was mixed with 1, 2, 4, and 8% of SEBS and then extruded. Different blends were mechanically, rheologically, optically, and dimensionally characterized to study how different percentages of LDPE and SEBS modify their properties. The results obtained show how the tensile strength, Young modulus, elongation, and impact strength linearly decrease as the LDPE amount increases, for both natural and black ABS. Through the addition of SEBS to contaminated ABS, it is possible to improve its impact strength and elongation values nearly to those of virgin ABS. However, its tensile strength and Young modulus show no improvement, and even show a slight reduction. Regarding the rheological properties, the LDPE contamination in ABS causes a remarkable decrease in viscosity, and adding SEBS to the blend lowers its viscosity even further for both natural and black grades. This reduction is not a negative aspect, but rather quite the reverse, as the more fluid the material, the easier the mold injection process becomes. POLYM. ENG. SCI., 54:1313–1324, 2014. © 2013 Society of Plastics Engineers     

Influence of Processing Parameters on the Sintering and Electrical Properties of Pb(Zn1/3Nb2/3)O3-Based Ceramics

Pb(Zn_1/3Nb_2/3)O₃-based ceramics have been prepared by two different processing methods: conventional (PZN-C) and reaction-sintering (PZN-RS). The conventionally prepared PZN-based ceramics densified at lower temperatures (950°C) than the reaction-sintered samples (1100°C), but the perovskite/pyrochlore ratio was always higher in PZN-RS. The presence of a substantial amount of pyrochlore phase in PZN-C ceramics caused a decrease in the electrical properties. The maximum dielectric constant values in PZN-C ceramics were 10%–15% lower than those of PZN-RS, despite a similar average grain size, 7 ± 0.2 μm. The temperature of the maximum of the dielectric constant ( T _max) was lower than that expected from the mixing rule because of the possible formation of Ba–Nb clusters. The higher chemical homogeneity in PZN-RS ceramics is the main reason for the higher dielectric constant, T _max and electromechanical response, as well as for the lower difference between T _max and the depolarization temperature ( T _d) and the lower diffusiveness parameter (δ).