Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

Food access and diet quality are associated with quality of life outcomes among HIV-infected individuals in Uganda.

BACKGROUND: Food insecurity is associated with poor nutritional and clinical outcomes among people living with HIV/AIDS. Few studies investigate the link between food insecurity, dietary diversity and health-related quality of life among people living with HIV/AIDS. OBJECTIVE: We investigated whether household food access and individual dietary diversity are associated with health-related quality of life among people living with HIV/AIDS in Uganda. METHODS: We surveyed 902 people living with HIV/AIDS and their households from two clinics in Northern Uganda. Health-related quality of life outcomes were assessed using the Medical Outcomes Study (MOS)-HIV Survey. We performed multivariate regressions to investigate the relationship between health-related quality of life, household food insecurity and individual dietary diversity. RESULTS: People living with HIV/AIDS from severe food insecurity households have mean mental health status scores that are 1.7 points lower (p<.001) and physical health status scores that are 1.5 points lower (p<.01). Individuals with high dietary diversity have mean mental health status scores that were 3.6 points higher (p<.001) and physical health status scores that were 2.8 points higher (p<.05). CONCLUSIONS: Food access and diet quality are associated with health-related quality of life and may be considered as part of comprehensive interventions designed to mitigate psychosocial consequences of HIV

Tipping Point for Expansion of Layered Aluminosilicates in Weakly Polar Solvents: Supercritical CO2

Layered aluminosilicates play a dominant role in the mechanical and gas storage properties of the subsurface, are used in diverse industrial applications, and serve as model materials for understanding solvent-ion-support systems. Although expansion in the presence of H2O is well-known to be systematically correlated with the hydration free energy of the interlayer cation, particularly in environments dominated by nonpolar solvents (i.e., CO2), uptake into the interlayer is not well-understood. Using novel high-pressure capabilities, we investigated the interaction of dry supercritical CO2 with Na-, NH4-, and Cs-saturated montmorillonite, comparing results with predictions from molecular dynamics simulations. Despite the known trend in H2O and that cation solvation energies in CO2 suggest a stronger interaction with Na, both the NH4- and Cs-clays readily absorbed CO2 and expanded, while the Na-clay did not. The apparent inertness of the Na-clay was not due to kinetics, as experiments seeking a stable expanded state showed that none exists. Molecular dynamics simulations revealed a large endothermicity to CO2 intercalation in the Na-clay but little or no energy barrier for the NH4- and Cs-clays. Indeed, the combination of experiment and theory clearly demonstrate that CO2 intercalation of Na-montmorillonite clays is prohibited in the absence of H2O. Consequently, we have shown for the first time that in the presence of a low dielectric constant, gas swelling depends more on the strength of the interaction between the interlayer cation and aluminosilicate sheets and less on that with solvent. The finding suggests a distinct regime in layered aluminosilicate swelling behavior triggered by low solvent polarizability, with important implications in geomechanics, storage, and retention of volatile gases, and across industrial uses in gelling, decoloring, heterogeneous catalysis, and semipermeable reactive barriers

A statistical framework for genetic association studies of power curves in bird flight

How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution

Natural computation meta-heuristics for the in silico optimization of microbial strains

<p>Abstract</p> <p>Background</p> <p>One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metabolic phenotype which typically means having a high yield/productivity. This challenge is not only due to the inherent complexity of the metabolic and regulatory networks, but also to the lack of appropriate modelling and optimization tools. To this end, Evolutionary Algorithms (EAs) have been proposed for <it>in silico </it>metabolic engineering, for example, to identify sets of gene deletions towards maximization of a desired physiological objective function. In this approach, each mutant strain is evaluated by resorting to the simulation of its phenotype using the Flux-Balance Analysis (FBA) approach, together with the premise that microorganisms have maximized their growth along natural evolution.</p> <p>Results</p> <p>This work reports on improved EAs, as well as novel Simulated Annealing (SA) algorithms to address the task of <it>in silico </it>metabolic engineering. Both approaches use a variable size set-based representation, thereby allowing the automatic finding of the best number of gene deletions necessary for achieving a given productivity goal. The work presents extensive computational experiments, involving four case studies that consider the production of succinic and lactic acid as the targets, by using <it>S. cerevisiae </it>and <it>E. coli </it>as model organisms. The proposed algorithms are able to reach optimal/near-optimal solutions regarding the production of the desired compounds and presenting low variability among the several runs.</p> <p>Conclusion</p> <p>The results show that the proposed SA and EA both perform well in the optimization task. A comparison between them is favourable to the SA in terms of consistency in obtaining optimal solutions and faster convergence. In both cases, the use of variable size representations allows the automatic discovery of the approximate number of gene deletions, without compromising the optimality of the solutions.</p

Functional Mapping of Dynamic Traits with Robust t-Distribution

Functional mapping has been a powerful tool in mapping quantitative trait loci (QTL) underlying dynamic traits of agricultural or biomedical interest. In functional mapping, multivariate normality is often assumed for the underlying data distribution, partially due to the ease of parameter estimation. The normality assumption however could be easily violated in real applications due to various reasons such as heavy tails or extreme observations. Departure from normality has negative effect on testing power and inference for QTL identification. In this work, we relax the normality assumption and propose a robust multivariate -distribution mapping framework for QTL identification in functional mapping. Simulation studies show increased mapping power and precision with the distribution than that of a normal distribution. The utility of the method is demonstrated through a real data analysis

A Comparison of Online versus On-site Training in Health Research Methodology: A Randomized Study

<p>Abstract</p> <p>Background</p> <p>Distance learning may be useful for building health research capacity. However, evidence that it can improve knowledge and skills in health research, particularly in resource-poor settings, is limited. We compared the impact and acceptability of teaching two distinct content areas, Biostatistics and Research Ethics, through either on-line distance learning format or traditional on-site training, in a randomized study in India. Our objective was to determine whether on-line courses in Biostatistics and Research Ethics could achieve similar improvements in knowledge, as traditional on-site, classroom-based courses.</p> <p>Methods</p> <p><it>Subjects: </it>Volunteer Indian scientists were randomly assigned to one of two arms.</p> <p><it>Intervention: </it>Students in Arm 1 attended a 3.5-day on-site course in Biostatistics and completed a 3.5-week on-line course in Research Ethics. Students in Arm 2 attended a 3.5-week on-line course in Biostatistics and 3.5-day on-site course in Research Ethics. For the two course formats, learning objectives, course contents and knowledge tests were identical.</p> <p><it>Main Outcome Measures: </it>Improvement in knowledge immediately and 3-months after course completion, compared to baseline.</p> <p>Results</p> <p>Baseline characteristics were similar in both arms (n = 29 each). Median knowledge score for Biostatistics increased from a baseline of 49% to 64% (p < 0.001) 3 months after the on-site course, and from 48% to 63% (p = 0.009) after the on-line course. For the on-site Research Ethics course, median score increased from 69% to 83% (p = 0.005), and for the on-line Research Ethics course from 62% to 80% (p < 0.001). Three months after the course, median gains in knowledge scores remained similar for the on-site and on-line platforms for both Biostatistics (16% vs. 12%; p = 0.59) and Research Ethics (17% vs. 13%; p = 0.14).</p> <p>Conclusion</p> <p>On-line and on-site training formats led to marked and similar improvements of knowledge in Biostatistics and Research Ethics. This, combined with logistical and cost advantages of on-line training, may make on-line courses particularly useful for expanding health research capacity in resource-limited settings.</p

A survey of canine tick-borne diseases in India

Background: There are few published reports on canine Babesia, Ehrlichia, Anaplasma, Hepatozoon and haemotropic Mycoplasma infections in India and most describe clinical disease in individual dogs, diagnosed by morphological observation of the microorganisms in stained blood smears. This study investigated the occurrence and distribution of canine tick-borne disease (TBD) pathogens using a combination of conventional and molecular diagnostic techniques in four cities in India. Results: On microscopy examination, only Hepatozoon gamonts were observed in twelve out of 525 (2.3%; 95% CI: 1.2, 4) blood smears. Using polymerase chain reaction (PCR), a total of 261 from 525 dogs (49.7%; 95% CI: 45.4, 54.1) in this study were infected with one or more canine tick-borne pathogen. Hepatozoon canis (30%; 95% CI: 26.0, 34.0) was the most common TBD pathogen found infecting dogs in India followed by Ehrlichia canis (20.6%; 95% CI: 17.2, 24.3), Mycoplasma haemocanis (12.2%; 95% CI: 9.5, 15.3), Anaplasma platys (6.5%; 95% CI: 4.5, 8.9), Babesia vogeli (5.5%, 95% CI: 3.7, 7.8) and Babesia gibsoni (0.2%, 95% CI: 0.01, 1.06). Concurrent infection with more than one TBD pathogen occurred in 39% of cases. Potential tick vectors, Rhipicephalus (most commonly) and/or Haemaphysalis ticks were found on 278 (53%) of dogs examined. Conclusions: At least 6 species of canine tick-borne pathogens are present in India. Hepatozoon canis was the most common pathogen and ticks belonging to the genus Rhipicephalus were encountered most frequently. Polymerase chain reaction was more sensitive in detecting circulating pathogens compared with peripheral blood smear examination. As co-infections with canine TBD pathogens were common, Indian veterinary practitioners should be cognisant that the discovery of one such pathogen raises the potential for multiple infections which may warrant different clinical management strategies

Observing Exoplanets with the James Webb Space Telescope

The census of exoplanets has revealed an enormous variety of planets or- biting stars of all ages and spectral types: planets in orbits of less than a day to frigid worlds in orbits over 100 AU; planets with masses 10 times that of Jupiter to planets with masses less than that of Earth; searingly hot planets to temperate planets in the Habitable Zone. The challenge of the coming decade is to move from demography to physical characterization. The James Webb Space Telescope (JWST) is poised to open a revolutionary new phase in our understanding of exoplanets with transit spectroscopy of relatively short period planets and coronagraphic imaging of ones with wide separations from their host stars. This article discusses the wide variety of exoplanet opportunities enabled by JWSTs sensitivity and stability, its high angular resolution, and its suite of powerful instruments. These capabilities will advance our understanding of planet formation, brown dwarfs, and the atmospheres of young to mature planets