Preparation and characterization of chitosan‐based dispersions

Complexation of chitosan in aqueous solutions by low molecular weight electrolytes is one of the simplest methods for the preparation of aqueous chitosan dispersions. In this work, the influence of storage time, sulfate concentration, method of preparation and surfactant content on some properties of the resultant chitosan dispersions (turbidity, viscosity and zeta potential) was analyzed. Turbidimetry was adequate to monitor the formation of particles, while viscometry was suitable to monitor changes in the dispersing phase. An analysis of the properties of these systems, mainly in terms of particle–particle and macromolecule–macromolecule interactions was carried out. Copyright © 2004 Society of Chemical Industry     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

Screening of supports for the immobilization of pectinmethylesterase from acerola (Malpighia glabra L)

A partially purified extract of pectinmethylesterase (PME) from acerola fruit was immobilized on various supports: glass, celite, chrysotile, agarose, concanavalin A Sepharose 4B, egg shell, polyacrylamide and gelatin. In addition, reticulation with glutaraldehyde was assessed, as well as the use of gelatin in the presence of celite, glass and silica. The highest immobilization yields were obtained when the pectinmethylesterase was immobilized in concanavalin A Sepharose 4B (81.7%) and in gelatin‐water (78.0%). Copyright © 2004 Society of Chemical Industry     

Polymerization Kinetics of Fischer‐Tropsch Reaction on Iron Based Catalysts and Product Grade Optimization

The polymerization kinetics of Fischer‐Tropsch reactions on a K‐promoted Fe catalyst was studied. To represent the product distribution, a kinetic model was developed based on alkyl and alkenyl mechanisms for hydrocarbon chain propagation, which were assumed to occur simultaneously in the Fischer‐Tropsch synthesis. The conclusion was drawn that superimposed Anderson‐Schulz‐Flory (ASF) distributions with different chain growth probabilities, on iron catalysts, can be the result of different chain growth mechanisms. The polymerization mechanism was used to obtain the product distribution for several conditions, and the optimum conditions for the production of transportation fuels were found.     

Development of ceramic floor tile compositions based on quartzite and granite sludges

In the present work, industrial sludges derived from cutting and polishing natural stones (granite and quartzite) were characterised in terms of particles size distribution, chemical and mineralogical composition, and thermal behaviour and their potential to be incorporated as main components in red-clay-based stoneware tiles was evaluated. High levels (60–70 wt.%) of incorporation were attempted aiming at designing new formulations intended to be less expensive and possess better final properties (lower water absorption and higher flexural strength) in comparison to an industrial reference body used in the production of rustic tiles by extrusion, characterised 8–9% water absorption and a flexural strength of 17–18 MPa. Extruded rods of different formulations were produced and fired at 1100 °C, 1125 °C, 1150 °C and 1200 °C. The experimental results showed that all the new formulations performed better with the most significant improvements being obtained with incorporation of granite sludge. Flexural strength values more than triplicate and water absorption decreased by more than one order of magnitude in comparison to the reference paste. The new products fulfil the requirements of the ISO 13006 standard, group BIa (porcelain tiles).     

A comparative study on the performance of dissortative mating and immigrants-based strategies for evolutionary dynamic optimization

Traditional Genetic Algorithms (GAs) mating schemes select individuals for crossover independently of their genotypic or phenotypic similarities. In Nature, this behavior is known as random mating. However, non-random protocols, in which individuals mate according to their kinship or likeness, are more common in natural species. Previous studies indicate that when applied to GAs, dissortative mating - a type of non-random mating in which individuals are chosen according to their similarities - may improve their performance (on both speed and reliability). Dissortative mating maintains genetic diversity at a higher level during the run, a fact that is frequently observed as a possible cause of dissortative GAs’ ability to escape local optima. Dynamic optimization demands a special attention when designing and tuning a GA, since diversity plays an even more crucial role than it does when tackling static ones. This paper investigates the behavior of the Adaptive Dissortative Mating GA (ADMGA) in dynamic problems and compares it to GAs based on random immigrants. ADMGA selects parents according to their Hamming distance, via a self-adjustable threshold value. The method, by keeping population diversity during the run, provides an effective means to deal with dynamic problems. Tests conducted with dynamic trap functions and dynamic versions of Road Royal and knapsack problems indicate that ADMGA is able to outperform other GAs on a wide range of tests, being particularly effective when the frequency of changes is low. Specifically, ADMGA outperforms two state-of-the-art algorithms on many dynamic scenarios. In addition, and unlike preceding dissortative mating GAs and other evolutionary techniques for dynamic optimization, ADMGA self-regulates the intensity of the mating restrictions and does not increase the set of parameters in GAs, thus being easier to tune.     

Improvement of Glycaemia and Endothelial Function by a New Low-Dose Curcuminoid in an Animal Model of Type 2 Diabetes

Curcumin has been suggested as a promising treatment for metabolic diseases, but the high doses required limit its therapeutic use. In this study, a new curcuminoid is synthesised to increase curcumin anti-inflammatory and antioxidant potential and to achieve hypoglycaemic and protective vascular effects in type 2 diabetic rats in a lower dose. In vitro, the anti-inflammatory effect was determined through the Griess reaction, and the antioxidant activity through ABTS and TBARS assays. In vivo, Goto-Kakizaki rats were treated for 2 weeks with the equimolar dose of curcumin (40 mg/kg/day) or curcuminoid (52.4 mg/kg/day). Fasting glycaemia, insulin tolerance, plasma insulin, insulin signalling, serum FFA, endothelial function and several markers of oxidative stress were evaluated. Both compounds presented a significant anti-inflammatory effect. Moreover, the curcuminoid had a marked hypoglycaemic effect, accompanied by higher GLUT4 levels in adipose tissue. Both compounds increased NO-dependent vasorelaxation, but only the curcuminoid exacerbated the response to ascorbic acid, consistent with a higher decrease in vascular oxidative and nitrosative stress. SOD1 and GLO1 levels were increased in EAT and heart, respectively. Altogether, these data suggest that the curcuminoid developed here has more pronounced effects than curcumin in low doses, improving the oxidative stress, endothelial function and glycaemic profile in type 2 diabetes.     

Differential Expression of Proteins in an Atypical Presentation of Autoimmune Lymphoproliferative Syndrome

Autoimmune lymphoproliferative syndrome (ALPS) is a rare disease defined as a defect in the lymphocyte apoptotic pathway. Currently, the diagnosis of ALPS is based on clinical aspects, defective lymphocyte apoptosis and mutations in Fas, FasL and Casp 10 genes. Despite this, ALPS has been misdiagnosed. The aim of this work was to go one step further in the knowledge of the disease, through a molecular and proteomic analysis of peripheral blood mononuclear cells (PBMCs) from two children, a 13-year-old girl and a 6-year-old boy, called patient 1 and patient 2, respectively, with clinical data supporting the diagnosis of ALPS. Fas, FasL and Casp10 genes from both patients were sequenced, and a sample of the total proteins from patient 1 was analyzed by label-free proteomics. Pathway analysis of deregulated proteins from PBMCs was performed on the STRING and PANTHER bioinformatics databases. A mutation resulting in an in-frame premature stop codon and protein truncation was detected in the Fas gene from patient 2. From patient 1, the proteomic analysis showed differences in the level of expression of proteins involved in, among other processes, cell cycle, regulation of cell cycle arrest and immune response. Noticeably, the most down-regulated protein is an important regulator of the cell cycle process. This could be an explanation of the disease in patient 1.     

An approach to accidents modeling based on compounds road environments

The most common approach to study the influence of certain road features on accidents has been the consideration of uniform road segments characterized by a unique feature. However, when an accident is related to the road infrastructure, its cause is usually not a single characteristic but rather a complex combination of several characteristics. The main objective of this paper is to describe a methodology developed in order to consider the road as a complete environment by using compound road environments, overcoming the limitations inherented in considering only uniform road segments. The methodology consists of: dividing a sample of roads into segments; grouping them into quite homogeneous road environments using cluster analysis; and identifying the influence of skid resistance and texture depth on road accidents in each environment by using generalized linear models. The application of this methodology is demonstrated for eight roads. Based on real data from accidents and road characteristics, three compound road environments were established where the pavement surface properties significantly influence the occurrence of accidents. Results have showed clearly that road environments where braking maneuvers are more common or those with small radii of curvature and high speeds require higher skid resistance and texture depth as an important contribution to the accident prevention.     

Electromagnetic Devices Applications of EBG for Systems Communications

This paper presents the study and applications of EBG (Electromagnetic Band Gap)/PBG (Photonic Band Gap) substrates, of planar microstrip structures, including quadrature directional couplers, rat-race (ring coupler) and impedance transformers. Through specific programs developed in FORTRAN PowerStation, the frequencies and couplings for each structure are obtained. Also are used the PACMO—Computer Aided Design in Microwave program developed by H.C.C. Fernandes. Results of the dimensions and coupling of these devices, varying the frequency band (cellular communication and Wimax systems) and permittivity of the substrate, are obtained, comparing the results of conventional materials with EBG/PBG materials in the s and p polarizations.