Computational modelling of multi-physics and multi-scale processes in parallel

This paper provides an overview of the developing needs for simulation software technologies for the computational modelling of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and space scales. Computational modelling of such problems requires software tech1nologies that enable the mathematical description of the interacting physical phenomena together with the solution of the resulting suites of equations in a numerically consistent and compatible manner. This functionality requires the structuring of simulation modules for specific physical phenomena so that the coupling can be effectively represented. These multi-physics and multi-scale computations are very compute intensive and the simulation software must operate effectively in parallel if it is to be used in this context. An approach to these classes of multi-disciplinary simulation in parallel is described, with some key examples of application to2 challenging engineering problems.

State defining experiment in chemical kinetics. Primary characterization of catalyst activity in a TAP experiment

This paper presents a new strategy, “state-by-state transient screening”, for kinetic characterization of states of a multicomponent catalyst as applied to TAP pulse-response experiments. The key idea is to perform an insignificant chemical perturbation of the catalytic system so that the known essential characteristics of the catalyst (e.g. oxidation degree) do not change during the experiment. Two types of catalytic substances can be distinguished: catalyst state substances, which determine the catalyst state, and catalyst dynamic substances, which are created by the perturbation. The general methodological and theoretical framework for multi-pulse TAP experiments is developed, and the general model for a one-pulse TAP experiment is solved. The primary kinetic characteristics, basic kinetic coefficients, are extracted from diffusion–reaction data and calculated as functions of experimentally measured exit-flow moments without assumptions regarding the detailed kinetic mechanism. The new strategy presented in this paper provides essential information, which can be a basis for developing a detailed reaction mechanism. The theoretical results are illustrated using furan oxidation over a VPO catalyst.

Do smokers with chronic obstructive pulmonary disease report their smoking status reliably?:A comparison of self-report and bio-chemical validation

Chronic obstructive pulmonary disease (COPD) is predominantly caused by cigarette smoking and is considered a worldwide preventable chronic illness. Smoking cessation is considered the primary intervention for disease management and nurses should play a major role in assisting patients to stop smoking. Currently there is a lack of professional consensus on how cessation interventions should be evaluated. The vast array of biochemical markers reported in the literature can be confusing and can make the comparisons of results difficult.

Chemical kinetics and reactive species in atmospheric pressure helium-oxygen plasmas with humid-air impurities

In most applications helium-based plasma jets operate in an open-air environment. The presence of humid air in the plasma jet will influence the plasma chemistry and can lead to the production of a broader range of reactive species. We explore the influence of humid air on the reactive species in radio frequency (rf)-driven atmospheric-pressure helium-oxygen mixture plasmas (He-O, helium with 5000 ppm admixture of oxygen) for wide air impurity levels of 0-500 ppm with relative humidities of from 0% to 100% using a zero-dimensional, time-dependent global model. Comparisons are made with experimental measurements in an rf-driven micro-scale atmospheric pressure plasma jet and with one-dimensional semi-kinetic simulations of the same plasma jet. These suggest that the plausible air impurity level is not more than hundreds of ppm in such systems. The evolution of species concentration is described for reactive oxygen species, metastable species, radical species and positively and negatively charged ions (and their clusters). Effects of the air impurity containing water humidity on electronegativity and overall plasma reactivity are clarified with particular emphasis on reactive oxygen species. © 2013 IOP Publishing Ltd.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

Bio-chemical changes associated with processing of shell fishes and flavour constituents of body meat and claw meat'of crab

In this thesis all these aspects are taken into consideration. Extensive studies were conducted on all aspects of processing of crabs, mussels and clams. The species taken for studies are commercially used ones namely Scylla sereta, perna viridis, and villorita cyprinoids. In Chapter 4.1 with regard to crab) the following aspects on their handling and processing are reported seasonal variation of chemical constituents, changes taking place during ice storage, freezing, canning etc. In Chapter 4._2 with regard to mussel, the relation between age (size) and chemical constituents, changes taking place during ice storage, freezing, canning etc. are reported and in Chapter 4.3 the changes taking place in clam muscle during icing and freezing are reported and the ame rebility of ice stored clams for canning purpose is reported.The interference of high concentration of glycogen in mussel and clam muscles during the colour development of ribose (Me-jbaum's method) is observed and remedial step are taken to minimise the interference.

Spatial and Temporal Variation of Microbial Population in the Grassland Soils of Tropical Montane Forest: Influence of Soil Physico-Chemical Characteristics and Nutrients

Present study is focused on the spatiotemporal variation of the microbial population (bacteria, fungus and actinomycetes) in the grassland soils of tropical montane forest and its relation with important soil physico-chemical characteristics and nutrients. Different physico-chemical properties of the soil such as temperature, moisture content, organic carbon, available nitrogen, available phosphorous and available potassium have been studied. Results of the present study revealed that both microbial load and soil characteristics showed spatiotemporal variation. Microbial population of the grassland soils were characterized by high load of bacteria followed by fungus and actinomycetes. Microbial load was high during pre monsoon season, followed by post monsoon and monsoon. The microbial load varied with important soil physico-chemical properties and nutrients. Organic carbon content, available nitrogen and available phosphorous were positively correlated with bacterial load and the correlation is significant at 0.05 and 0.01 levels respectively. Available nitrogen and available phosphorous were positively correlated with fungus at 0.05 level significance. Moisture content was negatively correlated with actinomycetes at 0.01 level of significance. Organic carbon negatively correlated with actinomycetes load at 0.05 level of significance

Stochastic modelling of rainfall from satellite data

Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.

Human exposure modelling for chemical risk assessment: a review of current approaches and research and policy implications

A wide variety of exposure models are currently employed for health risk assessments. Individual models have been developed to meet the chemical exposure assessment needs of Government, industry and academia. These existing exposure models can be broadly categorised according to the following types of exposure source: environmental, dietary, consumer product, occupational, and aggregate and cumulative. Aggregate exposure models consider multiple exposure pathways, while cumulative models consider multiple chemicals. In this paper each of these basic types of exposure model are briefly described, along with any inherent strengths or weaknesses, with the UK as a case study. Examples are given of specific exposure models that are currently used, or that have the potential for future use, and key differences in modelling approaches adopted are discussed. The use of exposure models is currently fragmentary in nature. Specific organisations with exposure assessment responsibilities tend to use a limited range of models. The modelling techniques adopted in current exposure models have evolved along distinct lines for the various types of source. In fact different organisations may be using different models for very similar exposure assessment situations. This lack of consistency between exposure modelling practices can make understanding the exposure assessment process more complex, can lead to inconsistency between organisations in how critical modelling issues are addressed (e.g. variability and uncertainty), and has the potential to communicate mixed messages to the general public. Further work should be conducted to integrate the various approaches and models, where possible and regulatory remits allow, to get a coherent and consistent exposure modelling process. We recommend the development of an overall framework for exposure and risk assessment with common approaches and methodology, a screening tool for exposure assessment, collection of better input data, probabilistic modelling, validation of model input and output and a closer working relationship between scientists and policy makers and staff from different Government departments. A much increased effort is required is required in the UK to address these issues. The result will be a more robust, transparent, valid and more comparable exposure and risk assessment process. (C) 2006 Elsevier Ltd. All rights reserved.