Theoretical and experimental approaches towards the determination of solute effective diffusivities in foods

The aim of this review paper is to present experimental methodologies and the mathematical approaches used to determine effective diffusivities of solutes in food materials. The paper commences by describing the diffusion phenomena related to solute mass transfer in foods and effective diffusivities. It then focuses on the mathematical formulation for the calculation of effective diffusivities considering different diffusion models based on Fick's second law of diffusion. Finally, experimental considerations for effective diffusivity determination are elucidated primarily based on the acquirement of a series of solute content versus time curves appropriate to the equation model chosen. Different factors contributing to the determination of the effective diffusivities such as the structure of food material, temperature, diffusion solvent, agitation, sampling, concentration and different techniques used are considered. (c) 2005 Elsevier Inc. All rights reserved.

Post-genomics approaches towards monitoring changes within the microbial ecology of the gut

The human gut microbiota, comprising many hundreds of different microbial species, has closely co-evolved with its human host over the millennia. Diet has been a major driver of this co-evolution, in particular dietary non-digestible carbohydrates. This dietary fraction reaches the colon and becomes available for microbial fermentation, and it is in the colon that the great diversity of gut microorganisms resides. For the vast majority of our evolutionary history humans followed hunter-gatherer life-styles and consumed diets with many times more non-digestible carbohydrates, fiber and whole plant polyphenol rich foods than typical Western style diets today.

Microbiology of the human intestinal tract and approaches for its dietary modulation

Gut bacteria can be categorised as being either beneficial or potentially pathogenic due to their metabolic activities and fermentation end-products. Health-promoting effects of the microflora may include immunostimulation, improved digestion and absorption, vitamin synthesis, inhibition of the growth of potential pathogens and lowering of gas distension. Detrimental effects are carcinogen production, intestinal putrefaction, toxin production, diarrhoea/constipation and intestinal infections. Certain indigenous bacteria such as bifidobacteria and lactobacilli are considered to be examples of health-promoting constituents of the microflora. They may aid digestion of lactose in lactose-intolerant individuals, reduce diarrhoea, help resist infections and assist in inflammatory conditions. Probiotics, prebiotics and synbiotics are functional foods that fortify the lactate producing microflora of the human or animal gut.

HAWAIIAN SKIRT: an F-box gene that regulates organ fusion and growth in arabidopsis

A fast neutron-mutagenized population of Arabidopsis ( Arabidopsis thaliana) Columbia-0 wild-type plants was screened for floral phenotypes and a novel mutant, termed hawaiian skirt ( hws), was identified that failed to shed its reproductive organs. The mutation is the consequence of a 28 bp deletion that introduces a premature amber termination codon into the open reading frame of a putative F-box protein ( At3g61590). The most striking anatomical characteristic of hws plants is seen in flowers where individual sepals are fused along the lower part of their margins. Crossing of the abscission marker, Pro(PGAZAT):beta-glucuronidase, into the mutant reveals that while floral organs are retained it is not the consequence of a failure of abscission zone cells to differentiate. Anatomical analysis indicates that the fusion of sepal margins precludes shedding even though abscission, albeit delayed, does occur. Spatial and temporal characterization, using Pro(HWS):beta-glucuronidase or Pro(HWS):green fluorescent protein fusions, has identified HWS expression to be restricted to the stele and lateral root cap, cotyledonary margins, tip of the stigma, pollen, abscission zones, and developing seeds. Comparative phenotypic analyses performed on the hws mutant, Columbia-0 wild type, and Pro(35S):HWS ectopically expressing lines has revealed that loss of HWS results in greater growth of both aerial and below-ground organs while overexpressing the gene brings about a converse effect. These observations are consistent with HWS playing an important role in regulating plant growth and development.

Results of applying sensor fusion to a control system using optic flow

The results from applying a sensor fusion process to an adaptive controller used to balance all inverted pendulum axe presented. The goal of the sensor fusion process was to replace some of the four mechanical measurements, which are known to be sufficient inputs for a linear state feedback controller to balance the system, with optic flow variables. Results from research into the psychology of the sense of balance in humans were the motivation for the investigation of this new type of controller input. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described. The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training till-le for the adaptive controller and reduced performance (measured as the time the pendulum remains upright)

Intelligent cores and intelligent agents: two approaches to achieve autonomy in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing systems? How can autonomic computing approaches be extended towards building reliable systems? How can existing technologies be merged to provide a solution for self-managing systems? The work reported in this paper aims to answer these questions by proposing Swarm-Array Computing, a novel technique inspired from swarm robotics and built on the foundations of autonomic and parallel computing paradigms. Two approaches based on intelligent cores and intelligent agents are proposed to achieve autonomy in parallel computing systems. The feasibility of the proposed approaches is validated on a multi-agent simulator.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Functional verification: approaches and challenges

It's a fact that functional verification (FV) is paramount within the hardware's design cycle. With so many new techniques available today to help with FV, which techniques should we really use? The answer is not straightforward and is often confusing and costly. The tools and techniques to be used in a project have to be decided upon early in the design cycle to get the best value for these new verification methods. This paper gives a quick survey in the form of an overview on FV, establishes the difference between verification and validation, describes the bottlenecks that appear in the verification process, examines the challenges in FV and exposes the current FV technologies and trends.

Image restoration for a rectangular poor-pixels detector

This paper presents a unique two-stage image restoration framework especially for further application of a novel rectangular poor-pixels detector, which, with properties of miniature size, light weight and low power consumption, has great value in the micro vision system. To meet the demand of fast processing, only a few measured images shifted up to subpixel level are needed to join the fusion operation, fewer than those required in traditional approaches. By maximum likelihood estimation with a least squares method, a preliminary restored image is linearly interpolated. After noise removal via Canny operator based level set evolution, the final high-quality restored image is achieved. Experimental results demonstrate effectiveness of the proposed framework. It is a sensible step towards subsequent image understanding and object identification.