Garlic powder and wheat bran as fillers: Their effect on the physicochemical properties of edible biocomposites

Biocomposites with two different fillers, garlic and wheat bran, were studied. They were based on cassava starch and contained glycerol as a plasticizer and potassium sorbate as an antimicrobial agent and were characterized by scanning electron microscopy (SEM), differential scanning calorimetry (DSC) and infrared spectroscopy (IR). The mechanical performance at room and lower temperatures was also studied. SEM micrographies of fractured surfaces of the wheat bran composite films showed some ruptured particles of fiber while fibrils of garlic on the order of nanometers were observed when garlic composite films were studied. Mechanical tests, at room temperature, showed that the addition of wheat bran led to an increment in the storage modulus (E`) and hardening and a decrease in Tan delta, while the garlic composite showed a diminishing in the E` and hardening and did not produce significant changes in Tan delta values when compared with systems without fillers (matrix). In the range between -90 degrees C and 20 degrees C. all the materials studied presented two peaks in the Tan delta curve. In the case of the wheat bran composite, both relaxation peaks shifted slightly to higher temperatures, broadened and diminished their intensity when compared with those of the matrix; however garlic composite showed a similar behavior to the matrix. DSC thermograms of aqueous systems showed a slight shift of gelatinization temperature (T(gelatinization)) to higher values when the fillers were present. Thermograms of films showed that both, garlic and wheat bran composites, had a lower melting point than the matrix. IR data indicated that interaction between starch and fillers determined an increase in the availability of hydroxyl groups to be involved in a dynamic exchange with water. (C) 2010 Elsevier B.V. All rights reserved.

Results of Joint Experiments and other IAEA activities on research using small tokamaks

This paper presents an overview of the results obtained during the Joint Experiments organized in the framework of the IAEA Coordinated Research Project on `Joint Research Using Small Tokamaks` that have been carried out on the tokamaks CASTOR at IPP Prague, Czech Republic (2005), T-10 at RRC `Kurchatov Institute`, Moscow, Russia (2006), and the most recent one at ISTTOK at IST, Lisbon, Portugal, in 2007. Experimental programmes were aimed at diagnosing and characterizing the core and the edge plasma turbulence in a tokamak in order to investigate correlations between the occurrence of transport barriers, improved confinement, electric fields and electrostatic turbulence using advanced diagnostics with high spatial and temporal resolution. On CASTOR and ISTTOK, electric fields were generated by biasing an electrode inserted into the edge plasma and an improvement of the global particle confinement induced by the electrode positive biasing has been observed. Geodesic acoustic modes were studied using heavy ion beam diagnostics on T-10 and ISTTOK and correlation reflectometry on T-10. ISTTOK is equipped with a gallium jet injector and the technical feasibility of gallium jets interacting with plasmas has been investigated in pulsed and ac operation. The first Joint Experiments have clearly demonstrated that small tokamaks are suitable for broad international cooperation to conduct dedicated joint research programmes. Other activities within the IAEA Coordinated Research Project on Joint Research Using Small Tokamaks are also overviewed.

Cathepsin X cleaves the beta 2 cytoplasmic tail of LFA-1 inducing the intermediate affinity form of LFA-1 and alpha-actinin-1 binding

The motility of T cells depends on the dynamic spatial regulation of integrin-mediated adhesion and de-adhesion. Cathepsin X, a cysteine protease, has been shown to regulate T-cell migration by interaction with lymphocyte function associated antigen-1 (LFA-1). LFA-1 adhesion to the ICAM-1 is controlled by the association of actin-binding proteins with the cytoplasmic tail of the beta(2) chain of LFA-1. Cleavage by cathepsin X of the amino acid residues S(769), E(768) and A(767) from the C-terminal of the beta(2) cytoplasmic tail of LFA-1 is shown to promote binding of the actin-binding protein alpha-actinin-1. Furthermore, cathepsin X overexpression reduced LFA-1 clustering and induced an intermediate affinity LFA-1 conformation that is known to associate with a-actinin-1. increased levels of intermediate affinity LFA-1 resulted in augmented cell spreading due to reduced attachment of T cells to the ICAM-1-coated surface. Gradual cleavage of LFA-1 by cathepsin X enables the transition between intermediate and high affinity LFA-1, an event that is crucial for effective T-cell migration.

Structural matching of 2D electrophoresis gels using deformed graphs

2D electrophoresis is a well-known method for protein separation which is extremely useful in the field of proteomics. Each spot in the image represents a protein accumulation and the goal is to perform a differential analysis between pairs of images to study changes in protein content. It is thus necessary to register two images by finding spot correspondences. Although it may seem a simple task, generally, the manual processing of this kind of images is very cumbersome, especially when strong variations between corresponding sets of spots are expected (e.g. strong non-linear deformations and outliers). In order to solve this problem, this paper proposes a new quadratic assignment formulation together with a correspondence estimation algorithm based on graph matching which takes into account the structural information between the detected spots. Each image is represented by a graph and the task is to find a maximum common subgraph. Successful experimental results using real data are presented, including an extensive comparative performance evaluation with ground-truth data. (C) 2010 Elsevier B.V. All rights reserved.

Indoor and outdoor atmospheric fungal spores in the So Paulo metropolitan area (Brazil): species and numeric concentrations

The aim of this study was to estimate the indoor and outdoor concentrations of fungal spores in the Metropolitan Area of Sao Paulo (MASP), collected at different sites in winter/spring and summer seasons. The techniques adopted included cultivation (samples collected with impactors) and microscopic enumeration (samples collected with impingers). The overall results showed total concentrations of fungal spores as high as 36,000 per cubic meter, with a large proportion of non culturable spores (around 91% of the total). Penicillium sp. and Aspergillus sp. were the dominant species both indoors and outdoors, in all seasons tested, occurring in more than 30% of homes at very high concentrations of culturable airborne fungi [colony forming units(CFU) m(-3)]. There was no significant difference between indoor and outdoor concentrations. The total fungal spore concentration found in winter was 19% higher than that in summer. Heat and humidity were the main factors affecting fungal growth; however, a non-linear response to these factors was found. Thus, temperatures below 16A degrees C and above 25A degrees C caused a reduction in the concentration (CFU m(-3)) of airborne fungi, which fits with MASP climatalogy. The same pattern was observed for humidity, although not as clearly as with temperature given the usual high relative humidity (above 70%) in the study area. These results are relevant for public health interventions that aim to reduce respiratory morbidity among susceptible populations.

Image indexing and retrieval using an ART-2A neural network architecture

Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.