14 resultados para whole story model

em Aston University Research Archive


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A nonlinear dynamic model of microbial growth is established based on the theories of the diffusion response of thermodynamics and the chemotactic response of biology. Except for the two traditional variables, i.e. the density of bacteria and the concentration of attractant, the pH value, a crucial influencing factor to the microbial growth, is also considered in this model. The pH effect on the microbial growth is taken as a Gaussian function G0e-(f- fc)2/G1, where G0, G1 and fc are constants, f represents the pH value and fc represents the critical pH value that best fits for microbial growth. To study the effects of the reproduction rate of the bacteria and the pH value on the stability of the system, three parameters a, G0 and G1 are studied in detail, where a denotes the reproduction rate of the bacteria, G0 denotes the impacting intensity of the pH value to microbial growth and G1 denotes the bacterial adaptability to the pH value. When the effect of the pH value of the solution which microorganisms live in is ignored in the governing equations of the model, the microbial system is more stable with larger a. When the effect of the bacterial chemotaxis is ignored, the microbial system is more stable with the larger G1 and more unstable with the larger G0 for f0 > fc. However, the stability of the microbial system is almost unaffected by the variation G0 and G1 and it is always stable for f0 < fc under the assumed conditions in this paper. In the whole system model, it is more unstable with larger G1 and more stable with larger G0 for f0 < fc. The system is more stable with larger G1 and more unstable with larger G0 for f0 > fc. However, the system is more unstable with larger a for f0 < fc and the stability of the system is almost unaffected by a for f0 > fc. The results obtained in this study provide a biophysical insight into the understanding of the growth and stability behavior of microorganisms.

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Background: Activated factor XIII (FXIIIa), a transglutaminase, introduces fibrin-fibrin and fibrin-inhibitor cross-links, resulting in more mechanically stable clots. The impact of cross-linking on resistance to fibrinolysis has proved challenging to evaluate quantitatively. Methods: We used a whole blood model thrombus system to characterize the role of cross-linking in resistance to fibrinolytic degradation. Model thrombi, which mimic arterial thrombi formed in vivo, were prepared with incorporated fluorescently labeled fibrinogen, in order to allow quantification of fibrinolysis as released fluorescence units per minute. Results: A site-specific inhibitor of transglutaminases, added to blood from normal donors, yielded model thrombi that lysed more easily, either spontaneously or by plasminogen activators. This was observed both in the cell/platelet-rich head and fibrin-rich tail. Model thrombi from an FXIII-deficient patient lysed more quickly than normal thrombi; replacement therapy with FXIII concentrate normalized lysis. In vitro addition of purified FXIII to the patient's preprophylaxis blood, but not to normal control blood, resulted in more stable thrombi, indicating no further efficacy of supraphysiologic FXIII. However, addition of tissue transglutaminase, which is synthesized by endothelial cells, generated thrombi that were more resistant to fibrinolysis; this may stabilize mural thrombi in vivo. Conclusions: Model thrombi formed under flow, even those prepared as plasma 'thrombi', reveal the effect of FXIII on fibrinolysis. Although very low levels of FXIII are known to produce mechanical clot stability, and to achieve ?-dimerization, they appear to be suboptimal in conferring full resistance to fibrinolysis.

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The fluid–particle interaction inside a 150 g/h fluidised bed reactor is modelled. The biomass particle is injected into the fluidised bed and the heat, momentum and mass transport from the fluidising gas and fluidised sand is modelled. The Eulerian approach is used to model the bubbling behaviour of the sand, which is treated as a continuum. Heat transfer from the bubbling bed to the discrete biomass particle, as well as biomass reaction kinetics are modelled according to the literature. The particle motion inside the reactor is computed using drag laws, dependent on the local volume fraction of each phase. FLUENT 6.2 has been used as the modelling framework of the simulations with the whole pyrolysis model incorporated in the form of user-defined function (UDF). The study completes the fast pyrolysis modelling in bubbling fluidised bed reactors.

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The fluid–particle interaction and the impact of shrinkage on pyrolysis of biomass inside a 150 g/h fluidised bed reactor is modelled. Two 500 View the MathML sourcem in diameter biomass particles are injected into the fluidised bed with different shrinkage conditions. The two different conditions consist of (1) shrinkage equal to the volume left by the solid devolatilization, and (2) shrinkage parameters equal to approximately half of particle volume. The effect of shrinkage is analysed in terms of heat and momentum transfer as well as product yields, pyrolysis time and particle size considering spherical geometries. The Eulerian approach is used to model the bubbling behaviour of the sand, which is treated as a continuum. Heat transfer from the bubbling bed to the discrete biomass particle, as well as biomass reaction kinetics are modelled according to the literature. The particle motion inside the reactor is computed using drag laws, dependent on the local volume fraction of each phase. FLUENT 6.2 has been used as the modelling framework of the simulations with the whole pyrolysis model incorporated in the form of user defined function (UDF).

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The fluid–particle interaction and the impact of different heat transfer conditions on pyrolysis of biomass inside a 150 g/h fluidised bed reactor are modelled. Two different size biomass particles (350 µm and 550 µm in diameter) are injected into the fluidised bed. The different biomass particle sizes result in different heat transfer conditions. This is due to the fact that the 350 µm diameter particle is smaller than the sand particles of the reactor (440 µm), while the 550 µm one is larger. The bed-to-particle heat transfer for both cases is calculated according to the literature. Conductive heat transfer is assumed for the larger biomass particle (550 µm) inside the bed, while biomass–sand contacts for the smaller biomass particle (350 µm) were considered unimportant. The Eulerian approach is used to model the bubbling behaviour of the sand, which is treated as a continuum. Biomass reaction kinetics is modelled according to the literature using a two-stage, semi-global model which takes into account secondary reactions. The particle motion inside the reactor is computed using drag laws, dependent on the local volume fraction of each phase. FLUENT 6.2 has been used as the modelling framework of the simulations with the whole pyrolysis model incorporated in the form of User Defined Function (UDF).

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Through a lumped parameter modelling approach, a dynamical model, which can reproduce the motion of the muscles of a human body standing in different postures during Whole Body Vibrations (WBVs) treatment, has been developed. The key parameters, associated to the dynamics of the motion of the muscles of the lower limbs, have been identified starting from accelerometer measurements. The developed model can be usefully applied to the optimization of WBVs treatments which can effectively enhance muscle activation. © 2013 IEEE.

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Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.

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This chapter examines the contexts in which people will process more deeply, and therefore be more influenced by, a position that is supported by either a numerical majority or minority. The chapter reviews the major theories of majority and minority influence with reference to which source condition is associated with most message processing (and where relevant, the contexts under which this occurs) and experimental research examining these predictions. The chapter then presents a new theoretical model (the source-context-elaboration model, SCEM) that aims to integrate the disparate research findings. The model specifies the processes underlying majority and minority influence, the contexts under which these processes occur and the consequences for attitudes changed by majority and minority influence. The chapter then describes a series of experiments that address each of the aspects of the theoretical model. Finally, a range of research-related issues are discussed and future issues for the research area as a whole are considered.

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We investigate knowledge exchange among commercial organizations, the rationale behind it, and its effects on the market. Knowledge exchange is known to be beneficial for industry, but in order to explain it, authors have used high-level concepts like network effects, reputation, and trust. We attempt to formalize a plausible and elegant explanation of how and why companies adopt information exchange and why it benefits the market as a whole when this happens. This explanation is based on a multiagent model that simulates a market of software providers. Even though the model does not include any high-level concepts, information exchange naturally emerges during simulations as a successful profitable behavior. The conclusions reached by this agent-based analysis are twofold: 1) a straightforward set of assumptions is enough to give rise to exchange in a software market, and 2) knowledge exchange is shown to increase the efficiency of the market.

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Korea has increasingly adopted design-build for public construction projects in the last few years. There is a much greater awareness of the need to change a system based on ‘Value for Money’ which is high on the government's agenda. A whole life performance bid evaluation model is proposed to aid decision makers in the selection of a design-builder. This is based on the integration of a framework using an analytic hierarchy process as the bid awarding system is being changed from one based on lowest price, to one based on best value over the life-cycle. Key criteria like whole life cost, service life planning and design quality are important through the key stages of evaluation process. The model uses a systematic and holistic approach which enables a public sector to make better decisions in design-builder selection, which will deliver whole life benefits, based on long term cost-effectiveness and whole life.

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Many studies have accounted for whole body vibration effects in the fields of exercise physiology, sport and rehabilitation medicine. Generally, surface EMG is utilized to assess muscular activity during the treatment; however, large motion artifacts appear superimposed to the raw signal, making sEMG recording not suitable before any artifact filtering. Sharp notch filters, centered at vibration frequency and at its superior harmonics, have been used in previous studies, to remove the artifacts. [6, 10] However, to get rid of those artifacts some true EMG signal is lost. The purpose of this study was to reproduce the effect of motor-unit synchronization on a simulated surface EMG during vibratory stimulation. In addition, authors mean to evaluate the EMG power percentage in those bands in which are also typically located motion artifact components. Model characteristics were defined to take into account two main aspect: the muscle MUs discharge behavior and the triggering effects that appear during local vibratory stimulation. [7] Inter-pulse-interval, was characterized by a polimodal distribution related to the MU discharge frequency (IPI 55-80ms, σ=12ms) and to the correlation with the vibration period within the range of ±2 ms due to vibration stimulus. [1, 7] The signals were simulated using different stimulation frequencies from 30 to 70 Hz. The percentage of the total simulated EMG power within narrow bands centered at the stimulation frequency and its superior harmonics (± 1 Hz) resulted on average about 8% (± 2.85) of the total EMG power. However, the artifact in those bands may contain more than 40% of the total power of the total signal. [6] Our preliminary results suggest that the analysis of the muscular activity of muscle based on raw sEMG recordings and RMS evaluation, if not processed during vibratory stimulation may lead to a serious overestimation of muscular response.

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This study aims to reproduce the effect of motor-unit synchronization on surface EMG recordings during vibratory stimulation to highlight vibration evoked muscle activity. The authors intended to evaluate, through numerical simulations, the changes in surface EMG spectrum in muscles undergoing whole body vibration stimulation. In some specific bands, in fact, vibration induced motion artifacts are also typically present. In addition, authors meant to compare the simulated EMGs with respect to real recordings in order to discriminate the effect of synchronization of motor units discharges with vibration frequencies from motion artifacts. Computations were performed using a model derived from previous studies and modified to consider the effect of vibratory stimulus, the motor unit synchronization and the endplates-electrodes relative position on the EMG signal. Results revealed that, in particular conditions, synchronization of MUs' discharge generates visible peaks at stimulation frequency and its harmonics. However, only a part of the total power of surface EMGs might be enclosed within artifacts related bands (±1. Hz centered at the stimulation frequency and its superior harmonics) even in case of strong synchronization of motor units discharges with the vibratory stimulus. © 2013 Elsevier Ireland Ltd.

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This paper presents a new, dynamic feature representation method for high value parts consisting of complex and intersecting features. The method first extracts features from the CAD model of a complex part. Then the dynamic status of each feature is established between various operations to be carried out during the whole manufacturing process. Each manufacturing and verification operation can be planned and optimized using the real conditions of a feature, thus enhancing accuracy, traceability and process control. The dynamic feature representation is complementary to the design models used as underlining basis in current CAD/CAM and decision support systems. © 2012 CIRP.

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Recent changes to the legislation on chemicals and cosmetics testing call for a change in the paradigm regarding the current 'whole animal' approach for identifying chemical hazards, including the assessment of potential neurotoxins. Accordingly, since 2004, we have worked on the development of the integrated co-culture of post-mitotic, human-derived neurons and astrocytes (NT2.N/A), for use as an in vitro functional central nervous system (CNS) model. We have used it successfully to investigate indicators of neurotoxicity. For this purpose, we used NT2.N/A cells to examine the effects of acute exposure to a range of test chemicals on the cellular release of brain-derived neurotrophic factor (BDNF). It was demonstrated that the release of this protective neurotrophin into the culture medium (above that of control levels) occurred consistently in response to sub-cytotoxic levels of known neurotoxic, but not non-neurotoxic, chemicals. These increases in BDNF release were quantifiable, statistically significant, and occurred at concentrations below those at which cell death was measureable, which potentially indicates specific neurotoxicity, as opposed to general cytotoxicity. The fact that the BDNF immunoassay is non-invasive, and that NT2.N/A cells retain their functionality for a period of months, may make this system useful for repeated-dose toxicity testing, which is of particular relevance to cosmetics testing without the use of laboratory animals. In addition, the production of NT2.N/A cells without the use of animal products, such as fetal bovine serum, is being explored, to produce a fully-humanised cellular model.