40 resultados para Hyperbaric oxygen, Optimal protocol, Chronic wound, Mathematical modelling, Diabetes
Resumo:
The increasing intensity of global competition has led organizations to utilize various types of performance measurement tools for improving the quality of their products and services. Data envelopment analysis (DEA) is a methodology for evaluating and measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. All the data in the conventional DEA with input and/or output ratios assumes the form of crisp numbers. However, the observed values of data in real-world problems are sometimes expressed as interval ratios. In this paper, we propose two new models: general and multiplicative non-parametric ratio models for DEA problems with interval data. The contributions of this paper are fourfold: (1) we consider input and output data expressed as interval ratios in DEA; (2) we address the gap in DEA literature for problems not suitable or difficult to model with crisp values; (3) we propose two new DEA models for evaluating the relative efficiencies of DMUs with interval ratios, and (4) we present a case study involving 20 banks with three interval ratios to demonstrate the applicability and efficacy of the proposed models where the traditional indicators are mostly financial ratios. © 2011 Elsevier Inc.
Resumo:
Conventional DEA models assume deterministic, precise and non-negative data for input and output observations. However, real applications may be characterized by observations that are given in form of intervals and include negative numbers. For instance, the consumption of electricity in decentralized energy resources may be either negative or positive, depending on the heat consumption. Likewise, the heat losses in distribution networks may be within a certain range, depending on e.g. external temperature and real-time outtake. Complementing earlier work separately addressing the two problems; interval data and negative data; we propose a comprehensive evaluation process for measuring the relative efficiencies of a set of DMUs in DEA. In our general formulation, the intervals may contain upper or lower bounds with different signs. The proposed method determines upper and lower bounds for the technical efficiency through the limits of the intervals after decomposition. Based on the interval scores, DMUs are then classified into three classes, namely, the strictly efficient, weakly efficient and inefficient. An intuitive ranking approach is presented for the respective classes. The approach is demonstrated through an application to the evaluation of bank branches. © 2013.
Resumo:
Introduction: Serum concentrations of polyclonal free light chains (FLC) represent the activity of the adaptive immune system. This study assessed the relationship between polyclonal FLC and the established marker of innate immunity, C-reactive protein (CRP), in chronic and acute disease. Methods: We utilized four cross-sectional chronic disease patient cohorts: chronic kidney disease (CKD), diabetes, vasculitis and kidney transplantation; and a longitudinal intensive care case series to assess the kinetics of production in acute disease. Results: There was a weak association between polyclonal FLC and high-sensitivity CRP (hs-CRP) in the study cohorts. A longitudinal assessment in acute disease showed a gradual increase in FLC concentrations over time, often when CRP levels were falling, demonstrating clear differences in the response kinetics of CRP and FLC in this setting. Conclusion: Polyclonal FLC and hs-CRP provide independent information as to inflammatory status. Prospective studies are now required to assess the utility of hs-CRP and polyclonal FLC in combination for risk stratification in disease populations. © 2013 John Wiley & Sons Ltd.
Resumo:
Genetic experiments over the last few decades have identified many regulatory proteins critical for DNA transcription. The dynamics of their transcriptional activities shape the differential expression of the genes they control. Here we describe a simple method, based on the secreted luciferase, to measure the activities of two transcription factors NF?B and HIF. This technique can effectively monitor dynamics of transcriptional events in a population of cells and be up-scaled for high-throughput screening and promoter analysis, making it ideal for data-demanding applications such as mathematical modelling.
Resumo:
Microfluidics has recently emerged as a new method of manufacturing liposomes, which allows for reproducible mixing in miliseconds on the nanoliter scale. Here we investigate microfluidics-based manufacturing of liposomes. The aim of these studies was to assess the parameters in a microfluidic process by varying the total flow rate (TFR) and the flow rate ratio (FRR) of the solvent and aqueous phases. Design of experiment and multivariate data analysis were used for increased process understanding and development of predictive and correlative models. High FRR lead to the bottom-up synthesis of liposomes, with a strong correlation with vesicle size, demonstrating the ability to in-process control liposomes size; the resulting liposome size correlated with the FRR in the microfluidics process, with liposomes of 50 nm being reproducibly manufactured. Furthermore, we demonstrate the potential of a high throughput manufacturing of liposomes using microfluidics with a four-fold increase in the volumetric flow rate, maintaining liposome characteristics. The efficacy of these liposomes was demonstrated in transfection studies and was modelled using predictive modeling. Mathematical modelling identified FRR as the key variable in the microfluidic process, with the highest impact on liposome size, polydispersity and transfection efficiency. This study demonstrates microfluidics as a robust and high-throughput method for the scalable and highly reproducible manufacture of size-controlled liposomes. Furthermore, the application of statistically based process control increases understanding and allows for the generation of a design-space for controlled particle characteristics.
Resumo:
Projects exposed to an uncertain environment must be adapted to deal with the effective integration of various planning elements and the optimization of project parameters. Time, cost, and quality are the prime objectives of a project that need to be optimized to fulfill the owner's goal. In an uncertain environment, there exist many other conflicting objectives that may also need to be optimized. These objectives are characterized by varying degrees of conflict. Moreover, an uncertain environment also causes several changes in the project plan throughout its life, demanding that the project plan be totally flexible. Goal programming (GP), a multiple criteria decision making technique, offers a good solution for this project planning problem. There the planning problem is considered from the owner's perspective, which leads to classifying the project up to the activity level. GP is applied separately at each level, and the formulated models are integrated through information flow. The flexibility and adaptability of the models lies in the ease of updating the model parameters at the required level through changing priorities and/or constraints and transmitting the information to other levels. The hierarchical model automatically provides integration among various element of planning. The proposed methodology is applied in this paper to plan a petroleum pipeline construction project, and its effectiveness is demonstrated.
Resumo:
This work is an initial study of a numerical method for identifying multiple leak zones in saturated unsteady flow. Using the conventional saturated groundwater flow equation, the leak identification problem is modelled as a Cauchy problem for the heat equation and the aim is to find the regions on the boundary of the solution domain where the solution vanishes, since leak zones correspond to null pressure values. This problem is ill-posed and to reconstruct the solution in a stable way, we therefore modify and employ an iterative regularizing method proposed in [1] and [2]. In this method, mixed well-posed problems obtained by changing the boundary conditions are solved for the heat operator as well as for its adjoint, to get a sequence of approximations to the original Cauchy problem. The mixed problems are solved using a Finite element method (FEM), and the numerical results indicate that the leak zones can be identified with the proposed method.
Resumo:
A landfill represents a complex and dynamically evolving structure that can be stochastically perturbed by exogenous factors. Both thermodynamic (equilibrium) and time varying (non-steady state) properties of a landfill are affected by spatially heterogenous and nonlinear subprocesses that combine with constraining initial and boundary conditions arising from the associated surroundings. While multiple approaches have been made to model landfill statistics by incorporating spatially dependent parameters on the one hand (data based approach) and continuum dynamical mass-balance equations on the other (equation based modelling), practically no attempt has been made to amalgamate these two approaches while also incorporating inherent stochastically induced fluctuations affecting the process overall. In this article, we will implement a minimalist scheme of modelling the time evolution of a realistic three dimensional landfill through a reaction-diffusion based approach, focusing on the coupled interactions of four key variables - solid mass density, hydrolysed mass density, acetogenic mass density and methanogenic mass density, that themselves are stochastically affected by fluctuations, coupled with diffusive relaxation of the individual densities, in ambient surroundings. Our results indicate that close to the linearly stable limit, the large time steady state properties, arising out of a series of complex coupled interactions between the stochastically driven variables, are scarcely affected by the biochemical growth-decay statistics. Our results clearly show that an equilibrium landfill structure is primarily determined by the solid and hydrolysed mass densities only rendering the other variables as statistically "irrelevant" in this (large time) asymptotic limit. The other major implication of incorporation of stochasticity in the landfill evolution dynamics is in the hugely reduced production times of the plants that are now approximately 20-30 years instead of the previous deterministic model predictions of 50 years and above. The predictions from this stochastic model are in conformity with available experimental observations.
Resumo:
This thesis presents theoretical investigation of three topics concerned with nonlinear optical pulse propagation in optical fibres. The techniques used are mathematical analysis and numerical modelling. Firstly, dispersion-managed (DM) solitons in fibre lines employing a weak dispersion map are analysed by means of a perturbation approach. In the case of small dispersion map strengths the average pulse dynamics is described by a perturbation approach (NLS) equation. Applying a perturbation theory, based on the Inverse Scattering Transform method, an analytic expression for the envelope of the DM soliton is derived. This expression correctly predicts the power enhancement arising from the dispersion management.Secondly, autosoliton transmission in DM fibre systems with periodical in-line deployment of nonlinear optical loop mirrors (NOLMs) is investigated. The use of in-line NOLMs is addressed as a general technique for all-optical passive 2R regeneration of return-to-zero data in high speed transmission system with strong dispersion management. By system optimisation, the feasibility of ultra-long single-channel and wavelength-division multiplexed data transmission at bit-rates ³ 40 Gbit s-1 in standard fibre-based systems is demonstrated. The tolerance limits of the results are defined.Thirdly, solutions of the NLS equation with gain and normal dispersion, that describes optical pulse propagation in an amplifying medium, are examined. A self-similar parabolic solution in the energy-containing core of the pulse is matched through Painlevé functions to the linear low-amplitude tails. The analysis provides a full description of the features of high-power pulses generated in an amplifying medium.
Resumo:
Activated sludge basins (ASBs) are a key-step in wastewater treatment processes that are used to eliminate biodegradable pollution from the water discharged to the natural environment. Bacteria found in the activated sludge consume and assimilate nutrients such as carbon, nitrogen and phosphorous under specific environmental conditions. However, applying the appropriate agitation and aeration regimes to supply the environmental conditions to promote the growth of the bacteria is not easy. The agitation and aeration regimes that are applied to activated sludge basins have a strong influence on the efficacy of wastewater treatment processes. The major aims of agitation by submersible mixers are to improve the contact between biomass and wastewater and the prevention of biomass settling. They induce a horizontal flow in the oxidation ditch, which can be quantified by the mean horizontal velocity. Mean values of 0.3-0.35 m s-1 are recommended as a design criteria to ensure best conditions for mixing and aeration (Da Silva, 1994). To give circulation velocities of this order of magnitude, the positioning and types of mixers are chosen from the plant constructors' experience and the suppliers' data for the impellers. Some case studies of existing plants have shown that measured velocities were not in the range that was specified in the plant design. This illustrates that there is still a need for design and diagnosis approach to improve process reliability by eliminating or reducing the number of short circuits, dead zones, zones of inefficient mixing and poor aeration. The objective of the aeration is to facilitate the quick degradation of pollutants by bacterial growth. To achieve these objectives a wastewater treatment plant must be adequately aerated; thus resulting in 60-80% of all energetic consummation being dedicated to the aeration alone (Juspin and Vasel, 2000). An earlier study (Gillot et al., 1997) has illustrated the influence that hydrodynamics have on the aeration performance as measure by the oxygen transfer coefficient. Therefore, optimising the agitation and aeration systems can enhance the oxygen transfer coefficient and consequently reduce the operating costs of the wastewater treatment plant. It is critically important to correctly estimate the mass transfer coefficient as any errors could result in the simulations of biological activity not being physically representative. Therefore, the transfer process was rigorously examined in several different types of process equipment to determine the impact that different hydrodynamic regimes and liquid-side film transfer coefficients have on the gas phase and the mass transfer of oxygen. To model the biological activity occurring in ASBs, several generic biochemical reaction models have been developed to characterise different biochemical reaction processes that are known as Activated Sludge Models, ASM (Henze et al., 2000). The ASM1 protocol was selected to characterise the impact of aeration on the bacteria consuming and assimilating ammonia and nitrate in the wastewater. However, one drawback of ASM protocols is that the hydrodynamics are assumed to be uniform by the use of perfectly mixed, plug flow reactors or as a number of perfectly mixed reactors in series. This makes it very difficult to identify the influence of mixing and aeration on oxygen mass transfer and biological activity. Therefore, to account for the impact of local gas-liquid mixing regime on the biochemical activity Computational Fluid Dynamics (CFD) was used by applying the individual ASM1 reaction equations as the source terms to a number of scalar equations. Thus, the application of ASM1 to CFD (FLUENT) enabled the investigation of the oxygen transfer efficiency and the carbon & nitrogen biological removal in pilot (7.5 cubic metres) and plant scale (6000 cubic metres) ASBs. Both studies have been used to validate the effect that the hydrodynamic regime has on oxygen mass transfer (the circulation velocity and mass transfer coefficient) and the effect that this had on the biological activity on pollutants such as ammonia and nitrate (Cartland Glover et al., 2005). The work presented here is one part to of an overall approach for improving the understanding of ASBs and the impact that they have in terms of the hydraulic and biological performance on the overall wastewater treatment process. References CARTLAND GLOVER G., PRINTEMPS C., ESSEMIANI K., MEINHOLD J., (2005) Modelling of wastewater treatment plants ? How far shall we go with sophisticated modelling tools? 3rd IWA Leading-Edge Conference & Exhibition on Water and Wastewater Treatment Technologies, 6-8 June 2005, Sapporo, Japan DA SILVA G. (1994). Eléments d'optimisation du transfert d'oxygène par fines bulles et agitateur séparé en chenal d'oxydation. PhD Thesis. CEMAGREF Antony ? France. GILLOT S., DERONZIER G., HEDUIT A. (1997). Oxygen transfer under process conditions in an oxidation ditch equipped with fine bubble diffusers and slow speed mixers. WEFTEC, Chicago, USA. HENZE M., GUJER W., MINO T., van LOOSDRECHT M., (2000). Activated Sludge Models ASM1, ASM2, ASM2D and ASM3, Scientific and Technical Report No. 9. IWA Publishing, London, UK. JUSPIN H., VASEL J.-L. (2000). Influence of hydrodynamics on oxygen transfer in the activated sludge process. IWA, Paris - France.