Iron Fortification Strategies for the Control of Childhood Anemia in Brazil

This article presents data on the fortification of foods, necessary as an important public health approach for the success in reducing anemia. The use of food vehicles, iron salts and their costs, as well as recent work on iron fortification of foods in Brazil are reviewed. Recent research serves as a cornerstone for countries that attempt to implement permanent, long-lasting iron fortification programs aimed at the prevention of anemia considering cultural habits, type of iron salts and at-risk groups.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

A Dynamical Modeling to Study the Adaptive Immune System and the Influence of Antibodies in the Immune Memory

Immunological systems have been an abundant inspiration to contemporary computer scientists. Problem solving strategies, stemming from known immune system phenomena, have been successfully applied to chall enging problems of modem computing. Simulation systems and mathematical modeling are also beginning use to answer more complex immunological questions as immune memory process and duration of vaccines, where the regulation mechanisms are not still known sufficiently (Lundegaard, Lund, Kesmir, Brunak, Nielsen, 2007). In this article we studied in machina a approach to simulate the process of antigenic mutation and its implications for the process of memory. Our results have suggested that the durability of the immune memory is affected by the process of antigenic mutation.and by populations of soluble antibodies in the blood. The results also strongly suggest that the decrease of the production of antibodies favors the global maintenance of immune memory.

Asymmetric page split generalized index search trees for formal concept analysis

Formal Concept Analysis is an unsupervised machine learning technique that has successfully been applied to document organisation by considering documents as objects and keywords as attributes. The basic algorithms of Formal Concept Analysis then allow an intelligent information retrieval system to cluster documents according to keyword views. This paper investigates the scalability of this idea. In particular we present the results of applying spatial data structures to large datasets in formal concept analysis. Our experiments are motivated by the application of the Formal Concept Analysis idea of a virtual filesystem [11,17,15]. In particular the libferris [1] Semantic File System. This paper presents customizations to an RD-Tree Generalized Index Search Tree based index structure to better support the application of Formal Concept Analysis to large data sources.

Analysis of the Ontogenetic Variation in the Venom Proteome/Peptidome of Bothrops jararaca Reveals Different Strategies to Deal with Prey

Previous studies have demonstrated that the pharmacological activities displayed by Bothrops jararaca venom undergo a significant ontogenetic shift. Variation in the venom proteome is a well-documented phenomenon; however, variation in the venom peptidome is poorly understood. We report a comparative proteomic and peptidomic analysis of venoms from newborn and adult specimens of B. jararaca and correlate it with the evaluation of important venom features. We demonstrate that newborn and adult venoms have similar hemorrhagic activities, while the adult venom has a slightly higher lethal activity in mice; however, the newborn venom is extremely more potent to kill chicks. The coagulant activity of newborn venom upon human plasma is 10 times higher than that of adult venom. These differences were clearly reflected in their different profiles of SDS-PAGE, gelatin zimography, immunostaining using specific antibodies, glycosylation pattern, and concanavalin A-binding proteins. Furthermore, we report for the first time the analysis of the peptide fraction of newborn and adult venoms by MALDI-TOF mass spectrometry and LC-MS/MS, which revealed different contents of peptides, while the bradykinin potentiating peptides (BPPs) showed rather similar profiles and were detected in the venoms showing their canonical sequences and also novel sequences corresponding to BPPs processed from their precursor protein at sites so far not described. As a result of these studies, we demonstrated that the ontogenetic shift in diet, from ectothermic prey in early life to endothermic prey in adulthood, and in animal size are associated with changes in the venom proteome in B. jararaca species.

Regional investment strategies (RIS) and coastal catchment initiative (CCI) project alignmnet to Great Barrier Reef Water Quality Protection Plan

The Great Barrier Reef Water Quality Protection Plan (the Reef Plan) is a joint initiative of the Australian and Queensland Governments. The Reef Plan aims to progress an integrated approach to natural resource management planning by building on the existing partnerships between the different levels of government, industry groups, the community and research providers within the Reef catchments, principally through partnerships with the regional natural resource management (NRM) bodies.

Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.