Mechanical,Thermal, and Morphological Behavior of Silicone Rubber during Accelerated Aging

An accelerated aging study on silicone rubber exploring the effects of exposure to a functional oil (polyalkylene glycol) at elevated temperature (195°C) is reported in this paper. Variations in mechanical (tensile, tear, hardness) and thermal (conductivity, specific heat capacity) properties were monitored versus aging time while permanent deformation of the rubber was evaluated through creep and recovery measurements. Morphology and surface chemistry of the aged rubber were also investigated through scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy, respectively. Aging had a significant impact on the mechanical properties with the ultimate tensile strength and elongation at break decreasing from 7.4?MPa and 2250% in unaged samples to 1.5?MPa and 760% in 6-week aged samples, respectively. The tear strength and hardness exhibited an initial increase during the early stages of aging, followed by a decreasing trend. In contrast, the thermal properties did not change significantly and FTIR did not detect any changes in the surface chemistry of the rubber with aging. SEM however, provided evidence of an increase in brittle behavior from the morphology of the fractured surfaces.     

Spatial correlation of incidence of dengue with socioeconomic, demographic and environmental variables in a Brazilian city

Dengue is endemic in most tropical countries. The reasons for its maintenance are related to several risk factors including socioeconomic factors. Urban space and time are also two important dimensions to describe the dynamics of an outbreak. The aim of this study was to evaluate the existence of a spatial correlation of the incidence of dengue and to identify variables that explain the spatial dependence in a medium-sized city of Brazil. We analyzed registered autochthonous dengue cases from September 1994 to August 2002 correlating them with socioeconomic, demographic and environmental variables using the Moran index. Our results indicate spatial dependence of the incidence of dengue and that socioeconomic factors were critical both at the beginning of the study and later on; other variables related to the organization of urban space were also involved in the occurrence of the disease. The use of spatial analysis tools is important to identify critical control areas with several variables intimately related to the modulation of the disease dynamics.     

Microbiological water quality in urban coastal beaches: the influence of water dynamics and optimization of the sampling strategy

In the summer 2001, the microbiological water quality of two contiguous urban coastal beaches (Porto, Portugal) was surveyed for 18 consecutive days. The sampling strategy consisted in sampling surface water in early morning, noon and afternoon. A total of 184 samples were processed at Pastoras beach, a confined area between two jetties, and Ourigo Beach more open to the ocean. At the first beach site, all samples exceeded fecal contamination above guide values (GV) and 82.6% above mandatory values (MV) set out in the EU Bathing Water Directive; whereas at Pastoras Beach, the figures were 93.5% for GV and 26.1% for MV, showing a potential health risk. The periodicity of fecal indicators in raw sewage, the tidal status and wind conditions dramatically influenced the water quality. The quality decreased in the morning regardless of tide conditions, but improved subsequently during the day, particularly during high tide and under the influence of afternoon NW winds. These dynamics are incompatible with the fortnight routine sampling according to the recommendations of the EU Bathing Water Directive, and the strategy should be revised on a beach-to-beach basis, having in mind the profile for the coastal zone.     

Double-codified gold nanolabels for enhanced immunoanalysis

A novel double-codified nanolabel (DC-AuNP) based on gold nanoparticle (AuNP) modified with anti-human IgG peroxidase (HRP)-conjugated antibody is reported. It represents a simple assay that allows enhanced spectrophotometric and electrochemical detection of antigen human IgG as a model protein. The method takes advantage of two properties of the DC-AuNP label: first, the HRP label activity toward the OPD chromogen that can be related to the analyte concentration and measured spectrophotometrically; second, the intrinsic electrochemical properties of the gold nanoparticle labels that being proportional to the protein concentration can be directly quantified by stripping voltammetry. Beside these two main direct determinations of human IgG, a secondary indirect detection was also applicable to this system, exploiting the high molar absorptivity of gold colloids, by which, the color intensity of their solution was proportional to the concentration of the antigen used in the assay. Paramagnetic beads were used as supporting material to immobilize the sandwich-type immunocomplexes resulting in incubation and washing times shorter than those typically needed in classical ELISA tests by means of a rapid magnetic separation of the unbound components. A built-in magnet graphite-epoxy-composite electrode allowed a sensibly enhanced adsorption and electrochemical quantification of the specifically captured AuNPs. The used DC-AuNP label showed an excellent specificity/selectivity, as a matter of fact using a different antigen (goat IgG) a minimal nonspecific electrochemical or spectrophotometric signal was measured. The detection limits for this novel double-codified nanoparticle-based assay were 52 and 260 pg of human IgG/mL for the spectrophotometric (HRP-based) and electrochemical (AuNP-based) detections, respectively, much lower than those typically achieved by ELISA tests. The developed label and method is versatile, offers enhanced performances, and can be easily extended to other protein detection schemes as well as in DNA analysis.     

Composites Between Alumina and an Ester‐Ether‐Ester Bioresorbable Copolymer

Composites between alumina and the bioresorbable poly(ε‐caprolactone)‐block‐poly(oxyethylene)‐block‐poly(ε‐caprolactone) copolymer were obtained by reacting ε‐caprolactone with preformed poly(ethylene glycol), in the presence of ceramic alumina powder, at 185°C under vacuum. The mechanical properties, tested by compression and flexural strengths and Young's modulus, show that the copolymer interacts poorly with the alumina grains. Both scanning electron and atomic force microscopy show a scarce wettability between alumina and copolymer, as well as the aggregation of alumina micro‐particles into clusters of big size. Both mechanical and morphological tests seem to indicate a stronger interaction between the alumina micro‐particles than between the alumina surface and the reaction mixture during the polymerization, as well as a “compacting effect” by alumina on the forming copolymer. The FT‐IR spectra of the composites show both copolymer and alumina absorption bands. The FT‐IR analysis on the fractions of an extraction with CHCl₃ indicates the presence of traces of poly(ε‐caprolactone), stably linked to alumina. The polymerization of ε‐caprolactone with alumina alone in the same conditions gives poly(ε‐caprolactone), mainly free and in minor part linked to the alumina surface. Two polymerization mechanisms, simultaneously occurring, are proposed. The most relevant result of this work is the lack of chemical inertness of alumina towards ε‐caprolactone, which leads to reconsider also the use of alumina as a biochemically inert material.     

Characterisation of cellulose-hydrolysing enzymes from the fungus Bipolaris sorokiniana

Cellulose-hydrolysing enzymes from the phytopathogenic fungus Bipolaris sorokiniana were partially purified and characterised. The enzyme production was variable according to the carbon source. β-Glucosidase and cellobiohydrolase activities were higher by growing the fungus on cellulose than on other carbon sources. Carboxymethyl cellulase production was stimulated by other carbohydrates, mainly lactose. Partial enzyme purification was carried out by liquid chromatography on Sepharose CL4B. The purification was about 17-fold, with a yield of 41% as judged by assay with p-nitrophenyl-β-D -glucopyranoside as substrate. The optimum pH and temperature were 5.0 and 55–60 °C respectively. The enzyme was stable at 28 and 37 °C but lost about 50% of its initial activity after 120 min at 55 °C. Saccharification of cellulosic materials such as crystalline cellulose, filter paper and wheat straws was carried out using the partially purified enzyme, resulting in the production of reducing sugars. © 1999 Society of Chemical Industry     

Determination of ultratrace levels of selenium in fruit and vegetable samples grown and consumed in Portugal

The selenium content in fruit and vegetable samples from two regions in Portugal were analysed using hydride generation atomic fluorescence spectrometry (HG-AFS) and radiochemical nuclear activation analysis (RNAA) – two analytical methods with very low limits of detection. The lower detection limits of HG-AFS, 3 μg kg⁻¹ and 8 μg kg⁻¹ (according to conditions used for digestion), and for RNAA, 10 μg kg⁻¹, meant that it was possible to determine selenium in samples previously analysed using the replicate sample instrumental nuclear activation analysis (RSINAA) with a higher detection limit associated.     

Natural convection in a partially open square cavity with internal heat source: An analysis of the opening mass flow

A steady buoyancy-driven flow of air in a partially open square 2D cavity with internal heat source, adiabatic bottom and top walls, and vertical walls maintained at different constant temperatures is investigated numerically in this work. A heat source with 1% of the cavity volume is present in the center of the bottom wall. The cold right wall contains a partial opening occupying 25%, 50% or 75% of the wall. The influence of the temperature gradient between the verticals walls was analyzed for Ra_e = 10³–10⁵, while the influence of the heat source was evaluated through the relation R = Ra_i/Ra_e, investigated at between 400 and 2000. Interesting results were obtained. For a low Rayleigh number, it is found that the isotherm plots are smooth and follow a parabolic shape indicating the dominance of the heat source. But as the Ra_e increases, the flow slowly becomes dominated by the temperature difference between the walls. It is also observed that multiple strong secondary circulations are formed for fluids with a small Ra_e whereas these features are absent at higher Ra_e. The comprehensive analysis is concluded with horizontal air velocity and temperature plots for the opening. The numerical results show a significant influence of the opening on the heat transfer in the cavity.     

Psychic retreats or psychic pits?: Unbearable states of mind and technological addiction.

New technologies are highly interactive. They promote imaginative involvement and allow the experience of different self-states, such as those involving withdrawal or “psychic retreat”. According to Steiner, psychic retreats are areas of the mind populated by imagination and ideas which are poorly aligned with reality. Psychic retreats are not necessarily pathological in themselves—for instance, they can be used positively for counteracting anxiety or enhancing creativeness. However, with technological addiction there is a misuse of psychic retreat: here the total absorption with computer applications serves to hide painful or unbearable states of mind, and to protect the patient from overwhelming feelings through segregating self-states with a disconnection in their representations. Therefore, in clinical work with individuals suffering from technological addiction exploring the use of psychic retreats can serve as an aid to both diagnosis and treatment. Where the dysfunctional use of new technologies constitutes a temporary withdrawal from a specific painful event, this can have the function of protecting the individual from inner conflict; in the most serious cases however, technological addiction is grounded in more chronic and pathological dissociative mechanisms, and serves to prevent the mind from reactivating traumatic states connected to childhood experience of emotional neglect or abuse. While it is likely that the first condition can be positively handled with appropriate identification and treatment, the latter is much more difficult to deal with, particularly where the addictive behavior hides the weakness of the self, and psychic retreats are pervasively used to protect the patient from mental breakdown. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fitting semi‐empirical drying models using a tool based on wavelet neural networks: Modeling a maize drying process

Maize drying is an important process, especially for storage and conservation. For this study, the experimental stage was carried out using a forced convection dryer with air heated at different temperature conditions (306.05–441.85 K) and flow (0.13–0.256 m³/hr), totalizing 15 drying curves. Then the performances of the classic drying kinetics methodology and the approach proposed in this paper, in which the increase in moisture content of the product with time was represented combining exponential models and neural networks based on wavelets, were compared. Good performance was obtained in predictions using the proposed approach. One of the main differentials of the methodology adopted was the obtainment of a model that has a global predictive capacity, within the range of tested operating conditions, which can be used in predicting drying curves for different operating conditions.

Practical applications

The drying process is also one of the most widely used methods for preserving food, and has the advantage of reducing the costs of storage and transport because of the low volume and weight of the end product. During the last years, this topic has attracted a broad industrial interest, resulting in many research studies investigating the drying process. Usually, with regard to the classic approach for modeling of the drying process, the kinetics of drying curves obtained in different operating conditions is affected separately, that is, the parameters are estimated independently, resulting in different regression problems. With the classical approach, in general, it is not possible to obtain a comprehensive prediction model with regards to operating conditions. We have proposed an alternative modeling method. Aiming to obtain a modeling tool with an overall predictive ability, an approach for drying kinetics prediction that combines exponential models and neural networks was proposed. The proposed modeling method was able to predict drying curves for different operating conditions.