'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

Detecção de região saliente em imagens usando dissimilaridade de cor e amostragem por pixeis aleatórios

The purpose of this work is to demonstrate and to assess a simple algorithm for automatic estimation of the most salient region in an image, that have possible application in computer vision. The algorithm uses the connection between color dissimilarities in the image and the image’s most salient region. The algorithm also avoids using image priors. Pixel dissimilarity is an informal function of the distance of a specific pixel’s color to other pixels’ colors in an image. We examine the relation between pixel color dissimilarity and salient region detection on the MSRA1K image dataset. We propose a simple algorithm for salient region detection through random pixel color dissimilarity. We define dissimilarity by accumulating the distance between each pixel and a sample of n other random pixels, in the CIELAB color space. An important result is that random dissimilarity between each pixel and just another pixel (n = 1) is enough to create adequate saliency maps when combined with median filter, with competitive average performance if compared with other related methods in the saliency detection research field. The assessment was performed by means of precision-recall curves. This idea is inspired on the human attention mechanism that is able to choose few specific regions to focus on, a biological system that the computer vision community aims to emulate. We also review some of the history on this topic of selective attention.

Filling in gaps of Drosophila melanogaster urate degradation metabolic pathway using metabolomics approaches: towards the core metabolome of the fruit fly

The primary goal of systems biology is to integrate complex omics data, and data obtained from traditional experimental studies in order to provide a holistic understanding of organismal function. One way of achieving this aim is to generate genome-scale metabolic models (GEMs), which contain information on all metabolites, enzyme-coding genes, and biochemical reactions in a biological system. Drosophila melanogaster GEM has not been reconstructed to date. Constraint-free genome-wide metabolic model of the fruit fly has been reconstructed in our lab, identifying gaps, where no enzyme was identified and metabolites were either only produced or consume. The main focus of the work presented in this thesis was to develop a pipeline for efficient gap filling using metabolomics approaches combined with standard reverse genetics methods, using 5-hydroxyisourate hydrolase (5-HIUH) as an example. 5-HIUH plays a role in urate degradation pathway. Inability to degrade urate can lead to inborn errors of metabolism (IEMs) in humans, including hyperuricemia. Based on sequence analysis Drosophila CG30016 gene was hypothesised to encode 5- HIUH. CG30016 knockout flies were examined to identify Malpighian tubules phenotype, and shortened lifespan might reflect kidney disorders in hyperuricemia in humans. Moreover, LC-MS analysis of mutant tubules revealed that CG30016 is involved in purine metabolism, and specifically urate degradation pathway. However, the exact role of the gene has not been identified, and the complete method for gap filling has not been developed. Nevertheless, thanks to the work presented here, we are a step closer towards the development of a gap-filling pipeline in Drosophila melanogaster GEM. Importantly, the areas that require further optimisation were identified and are the focus of future research. Moreover, LC-MS analysis confirmed that tubules rather than the whole fly were more suitable for metabolomics analysis of purine metabolism. Previously, Dow/Davies lab has generated the most complete tissue-specific transcriptomic atlas for Drosophila – FlyAtlas.org, which provides data on gene expression across multiple tissues of adult fly and larva. FlyAtlas revealed that transcripts of many genes are enriched in specific Drosophila tissues, and that it is possible to deduce the functions of individual tissues within the fly. Based on FlyAtlas data, it has become clear that the fly (like other metazoan species) must be considered as a set of tissues, each 2 with its own distinct transcriptional and functional profile. Moreover, it revealed that for about 30% of the genome, reverse genetic methods (i.e. mutation in an unknown gene followed by observation of phenotype) are only useful if specific tissues are investigated. Based on the FlyAtlas findings, we aimed to build a primary tissue-specific metabolome of the fruit fly, in order to establish whether different Drosophila tissues have different metabolomes and if they correspond to tissue-specific transcriptome of the fruit fly (FlyAtlas.org). Different fly tissues have been dissected and their metabolome elucidated using LC-MS. The results confirmed that tissue metabolomes differ significantly from each other and from the whole fly, and that some of these differences can be correlated to the tissue function. The results illustrate the need to study individual tissues as well as the whole organism. It is clear that some metabolites that play an important role in a given tissue might not be detected in the whole fly sample because their abundance is much lower in comparison to other metabolites present in all tissues, which prevent the detection of the tissue-specific compound.

Plant Migrations Impact on Potential Vegetation and Carbon Redistribution in Northern North America from Climate Change

Forests have a prominent role in carbon storage and sequestration. Anthropogenic forcing has the potential to accelerate climate change and alter the distribution of forests. How forests redistribute spatially and temporally in response to climate change can alter their carbon sequestration potential. The driving question for this research was: How does plant migration from climate change impact vegetation distribution and carbon sequestration potential over continental scales? Large-scale simulation of the equilibrium response of vegetation and carbon from future climate change has shown relatively modest net gains in sequestration potential, but studies of the transient response has been limited to the sub-continent or landscape scale. The transient response depends on fine scale processes such as competition, disturbance, landscape characteristics, dispersal, and other factors, which makes it computational prohibitive at large domain sizes. To address this, this research used an advanced mechanistic model (Ecosystem Demography Model, ED) that is individually based, but pseudo-spatial, that reduces computational intensity while maintaining the fine scale processes that drive the transient response. First, the model was validated against remote sensing data for current plant functional type distribution in northern North America with a current climatology, and then a future climatology was used to predict the potential equilibrium redistribution of vegetation and carbon from future climate change. Next, to enable transient calculations, a method was developed to simulate the spatially explicit process of dispersal in pseudo-spatial modeling frameworks. Finally, the new dispersal sub-model was implemented in the mechanistic ecosystem model, and a model experimental design was designed and completed to estimate the transient response of vegetation and carbon to climate change. The potential equilibrium forest response to future climate change was found to be large, with large gross changes in distribution of plant functional types and comparatively smaller changes in net carbon sequestration potential for the region. However, the transient response was found to be on the order of centuries, and to depend strongly on disturbance rates and dispersal distances. Future work should explore the impact of species-specific disturbance and dispersal rates, landscape fragmentation, and other processes that influence migration rates and have been simulated at the sub-continent scale, but now at continental scales, and explore a range of alternative future climate scenarios as they continue to be developed.

Natural plant polyphenols for alleviating oxidative damage in man: Current status and future perspectives

The balance between oxidation and reduction is important for maintaining a healthy biological system. Oxidative stress results from an imbalance between excessive formation of reactive oxygen species (ROS) and/or reactive nitrogen species (RNS) and limited endogenous defense systems, and this imbalance can adversely alter lipids, proteins and DNA, causing a number of human diseases. Thus, exogenous antioxidants that can neutralize the effect of free radicals are needed to diminish the cumulative effects of oxidative damage over human life span. Current research reveals that phenolic compounds in plants possess high antioxidant activity and free radical scavenging capacity and can prevent the body from oxidative damage over human life span. This review focuses on the present understanding of free radicals and antioxidants and their importance in human health and disease. Information about the chemical features of free radicals as well as their deleterious effects on cell structures is reviewed. The chemical structure and anti-oxidative mechanisms of essential polyphenols and their potential health benefits are presented. In addition, the limitation of natural antioxidants and a perspective on likely future trends in this field are also discussed.

Genetic Algorithms for Parameter Estimation in Circadian Model

This paper proposes an algorithm to estimate two parameter values vs, transcription of frq gene, and vd, maximum rate of FRQ protein degradation for an existing 3rd order Neurospora model in literature. Details of the algorithm with simulation results are shown in this paper.

Methods for kinematic modeling of biological and robotic systems

The main objective is to develop methods that automatically generate kinematic models for the movements of biological and robotic systems. Two methods for the identification of the kinematics are presented. The first method requires the elimination of the displacement variables that cannot be measured while the second method attempts to estimate the changes in these variables. The methods were tested using a planar two-revolute-joint linkage. Results show that the model parameters obtained agree with the actual parameters to within 5%. Moreover, the methods were applied to model head and neck movements in the sagittal plane. The results indicate that these movements are well modeled by a two-revolute-joint system. A spatial three-revolute-joint model was also discussed and tested.

Host-guest system of 4-nerolidylcatechol in 2-hydroxypropyl-beta-cyclodextrin: preparation, characterization and molecular modeling

The interaction of 4-nerolidylcatechol (4-NRC), a potent antioxidant agent, and 2-hydroxypropyl-beta-cyclodextrin (HP-beta-CD) was investigated by the solubility method using Fourier transform infrared (FTIR) methods in addition to UV-Vis, (1)H-nuclear magnetic resonance (NMR) spectroscopy and molecular modeling. The inclusion complexes were prepared using grinding, kneading and freeze-drying methods. According to phase solubility studies in water a B(S)-type diagram was found, displaying a stoichiometry complexation of 2:1 (drug:host) and stability constant of 6494 +/- A 837 M(-1). Stoichiometry was established by the UV spectrophotometer using Job`s plot method and, also confirmed by molecular modeling. Data from (1)H-NMR, and FTIR, experiments also provided formation evidence of an inclusion complex between 4-NRC and HP-beta-CD. 4-NRC complexation indeed led to higher drug solubility and stability which could probably be useful to improve its biological properties and make it available to oral administration and topical formulations.

Host-guest system of 4-nerolidylcatechol in 2-hydroxypropyl-beta-cyclodextrin: preparation, characterization and molecular modeling

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Mathematical modeling and control of population systems: Applications in biological pest control

The aim of this paper is to apply methods from optimal control theory, and from the theory of dynamic systems to the mathematical modeling of biological pest control. The linear feedback control problem for nonlinear systems has been formulated in order to obtain the optimal pest control strategy only through the introduction of natural enemies. Asymptotic stability of the closed-loop nonlinear Kolmogorov system is guaranteed by means of a Lyapunov function which can clearly be seen to be the solution of the Hamilton-Jacobi-Bellman equation, thus guaranteeing both stability and optimality. Numerical simulations for three possible scenarios of biological pest control based on the Lotka-Volterra models are provided to show the effectiveness of this method. (c) 2007 Elsevier B.V. All rights reserved.

Management of vomplex systems: Modeling the biological pest control

The aim of this paper is to study the cropping system as complex one, applying methods from theory of dynamic systems and from the control theory to the mathematical modeling of the biological pest control. The complex system can be described by different mathematical models. Based on three models of the pest control, the various scenarios have been simulated in order to obtain the pest control strategy only through natural enemies' introduction. © 2008 World Scientific Publishing Company.

Distribution of biological, anthropogenic, and volcanic constituents in the San Francisco Bay Coastal System

Although conventional sediment parameters (mean grain size, sorting, and skewness) and provenance have typically been used to infer sediment transport pathways, most freshwater, brackish, and marine environments are also characterized by abundant sediment constituents of biological, and possibly anthropogenic and volcanic, origin that can provide additional insight into local sedimentary processes. The biota will be spatially distributed according to its response to environmental parameters such as water temperature, salinity, dissolved oxygen, organic carbon content, grain size, and intensity of currents and tidal flow, whereas the presence of anthropogenic and volcanic constituents will reflect proximity to source areas and whether they are fluvially- or aerially-transported. Because each of these constituents have a unique environmental signature, they are a more precise proxy for that source area than the conventional sedimentary process indicators. This San Francisco Bay Coastal System study demonstrates that by applying a multi-proxy approach, the primary sites of sediment transport can be identified. Many of these sites are far from where the constituents originated, showing that sediment transport is widespread in the region. Although not often used, identifying and interpreting the distribution of naturally-occurring and allochthonous biologic, anthropogenic, and volcanic sediment constituents is a powerful tool to aid in the investigation of sediment transport pathways in other coastal systems.

Modeling soil system: complexity under your feet

A clear statement in these lines textually cited (Byers et al., 1938) defines the framework of this special issue: “True soil is the product of the action of climate and living organism upon the parent material, as conditioned by the local relief. The length of time during which these forces are operative is of great importance in determining the character of the ultimate product. Drainage conditions are also important and are controlled by local relief, by the nature of the parent material or underlying rock strata, or by the amount of precipitation in relation to rate of percolation and runoff water. There are, therefore, five principal factors of soil formation: Parent material, climate, biological activity, relief and time. These soil forming factors are interdependent, each modifying the effectiveness of the others.” Due to these various processes associated to its formation and genesis soil dynamics reveals high complexity that creates several levels of structure using this term in a broad sense

Host-guest system of 4-nerolidylcatechol in 2-hydroxypropyl-beta-cyclodextrin: preparation, characterization and molecular modeling

The interaction of 4-nerolidylcatechol (4-NRC), a potent antioxidant agent, and 2-hydroxypropyl-beta-cyclodextrin (HP-beta-CD) was investigated by the solubility method using Fourier transform infrared (FTIR) methods in addition to UV-Vis, (1)H-nuclear magnetic resonance (NMR) spectroscopy and molecular modeling. The inclusion complexes were prepared using grinding, kneading and freeze-drying methods. According to phase solubility studies in water a B(S)-type diagram was found, displaying a stoichiometry complexation of 2:1 (drug:host) and stability constant of 6494 +/- A 837 M(-1). Stoichiometry was established by the UV spectrophotometer using Job's plot method and, also confirmed by molecular modeling. Data from (1)H-NMR, and FTIR, experiments also provided formation evidence of an inclusion complex between 4-NRC and HP-beta-CD. 4-NRC complexation indeed led to higher drug solubility and stability which could probably be useful to improve its biological properties and make it available to oral administration and topical formulations.

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 1: Model description and evaluation

We introduce the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). CATT-BRAMS is an on-line transport model fully consistent with the simulated atmospheric dynamics. Emission sources from biomass burning and urban-industrial-vehicular activities for trace gases and from biomass burning aerosol particles are obtained from several published datasets and remote sensing information. The tracer and aerosol mass concentration prognostics include the effects of sub-grid scale turbulence in the planetary boundary layer, convective transport by shallow and deep moist convection, wet and dry deposition, and plume rise associated with vegetation fires in addition to the grid scale transport. The radiation parameterization takes into account the interaction between the simulated biomass burning aerosol particles and short and long wave radiation. The atmospheric model BRAMS is based on the Regional Atmospheric Modeling System (RAMS), with several improvements associated with cumulus convection representation, soil moisture initialization and surface scheme tuned for the tropics, among others. In this paper the CATT-BRAMS model is used to simulate carbon monoxide and particulate material (PM(2.5)) surface fluxes and atmospheric transport during the 2002 LBA field campaigns, conducted during the transition from the dry to wet season in the southwest Amazon Basin. Model evaluation is addressed with comparisons between model results and near surface, radiosondes and airborne measurements performed during the field campaign, as well as remote sensing derived products. We show the matching of emissions strengths to observed carbon monoxide in the LBA campaign. A relatively good comparison to the MOPITT data, in spite of the fact that MOPITT a priori assumptions imply several difficulties, is also obtained.