992 resultados para Comparative Modelling


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Background: Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results: The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion: After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

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In this paper we consider the structure of dynamically evolving networks modelling information and activity moving across a large set of vertices. We adopt the communicability concept that generalizes that of centrality which is defined for static networks. We define the primary network structure within the whole as comprising of the most influential vertices (both as senders and receivers of dynamically sequenced activity). We present a methodology based on successive vertex knockouts, up to a very small fraction of the whole primary network,that can characterize the nature of the primary network as being either relatively robust and lattice-like (with redundancies built in) or relatively fragile and tree-like (with sensitivities and few redundancies). We apply these ideas to the analysis of evolving networks derived from fMRI scans of resting human brains. We show that the estimation of performance parameters via the structure tests of the corresponding primary networks is subject to less variability than that observed across a very large population of such scans. Hence the differences within the population are significant.

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The Tropical Rainfall Measuring Mission 3B42 precipitation estimates are widely used in tropical regions for hydrometeorological research. Recently, version 7 of the product was released. Major revisions to the algorithm involve the radar refl ectivity - rainfall rates relationship, surface clutter detection over high terrain, a new reference database for the passive microwave algorithm, and a higher quality gauge analysis product for monthly bias correction. To assess the impacts of the improved algorithm, we compare the version 7 and the older version 6 product with data from 263 rain gauges in and around the northern Peruvian Andes. The region covers humid tropical rainforest, tropical mountains, and arid to humid coastal plains. We and that the version 7 product has a significantly lower bias and an improved representation of the rainfall distribution. We further evaluated the performance of versions 6 and 7 products as forcing data for hydrological modelling, by comparing the simulated and observed daily streamfl ow in 9 nested Amazon river basins. We find that the improvement in the precipitation estimation algorithm translates to an increase in the model Nash-Sutcliffe effciency, and a reduction in the percent bias between the observed and simulated flows by 30 to 95%.

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1. The objective of this study was to determine a metabolisable energy ( ME) requirement model for broiler breeder hens. The influence of temperature on ME requirements for maintenance was determined in experiments conducted in three environmental rooms with temperatures kept constant at 13, 21 and 30 degrees C using a comparative slaughter technique. The energy requirements for weight gain were determined based upon body energy content and efficiency of energy utilisation for weight gain. The energy requirements for egg production were determined on the basis of egg energy content and efficiency of energy deposition in the eggs.2. The following model was developed using these results: ME = kgW(0.75)(806.53 - 26.45T + 0.50T(2)) + 31.90G + 10.04EM, where kgW(0.75) is body weight (kg) raised to the power 0.75, T is temperature (degrees C), G is weight gain (g) and EM is egg mass (g).3. A feeding trial was conducted using 400 Hubbard Hi-Yield broiler breeder hens and 40 Peterson males from 31 to 46 weeks of age in order to compare use of the model with a recommended feeding programme for this strain of bird. The application of the model in breeder hens provided good productive and reproductive performance and better results in feed and energy conversion than in hens fed according to strain recommendation. In conclusion, the model evaluated predicted an ME intake which matched breeder hens' requirements.

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Besnoitia besnoiti is an apicomplexan parasite responsible for bovine besnoitiosis, a disease with a high prevalence in tropical and subtropical regions and re-emerging in Europe. Despite the great economical losses associated with besnoitiosis, this disease has been underestimated and poorly studied, and neither an effective therapy nor an efficacious vaccine is available. Protein disulfide isomerase (PDI) is an essential enzyme for the acquisition of the correct three-dimensional structure of proteins. Current evidence suggests that in Neosporacaninum and Toxoplasmagondii, which are closely related to B. besnoiti, PDI play an important role in host cell invasion, is a relevant target for the host immune response, and represents a promising drug target and/or vaccine candidate. In this work, we present the nucleotide sequence of the B. besnoiti PDI gene. BbPDI belongs to the thioredoxin-like superfamily (cluster 00388) and is included in the PDI_a family (cluster defined cd02961) and the PDI_a_PDI_a'_c subfamily (cd02995). A 3D theoretical model was built by comparative homology using Swiss-Model server, using as a template the crystallographic deduced model of Tapasin-ERp57 (PDB code 3F8U chain C). Analysis of the phylogenetic tree for PDI within the phylum apicomplexa reinforces the close relationship among B. besnoiti, N. caninum and T. gondii. When subjected to a PDI-assay based on the polymerisation of reduced insulin, recombinant BbPDI expressed in E. coli exhibited enzymatic activity, which was inhibited by bacitracin. Antiserum directed against recombinant BbPDI reacted with PDI in Western blots and by immunofluorescence with B. besnoiti tachyzoites and bradyzoites.

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Simulations of forest stand dynamics in a modelling framework including Forest Vegetation Simulator (FVS) are diameter driven, thus the diameter or basal area increment model needs a special attention. This dissertation critically evaluates diameter or basal area increment models and modelling approaches in the context of the Great Lakes region of the United States and Canada. A set of related studies are presented that critically evaluate the sub-model for change in individual tree basal diameter used in the Forest Vegetation Simulator (FVS), a dominant forestry model in the Great Lakes region. Various historical implementations of the STEMS (Stand and Tree Evaluation and Modeling System) family of diameter increment models, including the current public release of the Lake States variant of FVS (LS-FVS), were tested for the 30 most common tree species using data from the Michigan Forest Inventory and Analysis (FIA) program. The results showed that current public release of the LS-FVS diameter increment model over-predicts 10-year diameter increment by 17% on average. Also the study affirms that a simple adjustment factor as a function of a single predictor, dbh (diameter at breast height) used in the past versions, provides an inadequate correction of model prediction bias. In order to re-engineer the basal diameter increment model, the historical, conceptual and philosophical differences among the individual tree increment model families and their modelling approaches were analyzed and discussed. Two underlying conceptual approaches toward diameter or basal area increment modelling have been often used: the potential-modifier (POTMOD) and composite (COMP) approaches, which are exemplified by the STEMS/TWIGS and Prognosis models, respectively. It is argued that both approaches essentially use a similar base function and neither is conceptually different from a biological perspective, even though they look different in their model forms. No matter what modelling approach is used, the base function is the foundation of an increment model. Two base functions – gamma and Box-Lucas – were identified as candidate base functions for forestry applications. The results of a comparative analysis of empirical fits showed that quality of fit is essentially similar, and both are sufficiently detailed and flexible for forestry applications. The choice of either base function in order to model diameter or basal area increment is dependent upon personal preference; however, the gamma base function may be preferred over the Box-Lucas, as it fits the periodic increment data in both a linear and nonlinear composite model form. Finally, the utility of site index as a predictor variable has been criticized, as it has been widely used in models for complex, mixed species forest stands though not well suited for this purpose. An alternative to site index in an increment model was explored, using site index and a combination of climate variables and Forest Ecosystem Classification (FEC) ecosites and data from the Province of Ontario, Canada. The results showed that a combination of climate and FEC ecosites variables can replace site index in the diameter increment model.

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The combustion strategy in a diesel engine has an impact on the emissions, fuel consumption and the exhaust temperatures. The PM mass retained in the CPF is a function of NO2 and PM concentrations in addition to the exhaust temperatures and the flow rates. Thus the engine combustion strategy affects exhaust characteristics which has an impact on the CPF operation and PM mass retained and oxidized. In this report, a process has been developed to simulate the relationship between engine calibration, performance and HC and PM oxidation in the DOC and CPF respectively. Fuel Rail Pressure (FRP) and Start of Injection (SOI) sweeps were carried out at five steady state engine operating conditions. This data, along with data from a previously carried out surrogate HD-FTP cycle [1], was used to create a transfer function model which estimates the engine out emissions, flow rates, temperatures for varied FRP and SOI over a transient cycle. Four different calibrations (test cases) were considered in this study, which were simulated through the transfer function model and the DOC model [1, 2]. The DOC outputs were then input into a model which simulates the NO2 assisted and thermal PM oxidation inside a CPF. Finally, results were analyzed as to how engine calibration impacts the engine fuel consumption, HC oxidation in the DOC and the PM oxidation in the CPF. Also, active regeneration for various test cases was simulated and a comparative analysis of the fuel penalties involved was carried out.

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OBJECTIVE To estimate the cost-effectiveness of prevention of mother-to-child transmission (MTCT) of HIV with lifelong antiretroviral therapy (ART) for pregnant and breastfeeding women ('Option B+') compared with ART during pregnancy or breastfeeding only unless clinically indicated ('Option B'). DESIGN Mathematical modelling study of first and second pregnancy, informed by data from the Malawi Option B+ programme. METHODS Individual-based simulation model. We simulated cohorts of 10 000 women and their infants during two subsequent pregnancies, including the breastfeeding period, with either Option B+ or B. We parameterized the model with data from the literature and by analysing programmatic data. We compared total costs of antenatal and postnatal care, and lifetime costs and disability-adjusted life-years of the infected infants between Option B+ and Option B. RESULTS During the first pregnancy, 15% of the infants born to HIV-infected mothers acquired the infection. With Option B+, 39% of the women were on ART at the beginning of the second pregnancy, compared with 18% with Option B. For second pregnancies, the rates MTCT were 11.3% with Option B+ and 12.3% with Option B. The incremental cost-effectiveness ratio comparing the two options ranged between about US$ 500 and US$ 1300 per DALY averted. CONCLUSION Option B+ prevents more vertical transmissions of HIV than Option B, mainly because more women are already on ART at the beginning of the next pregnancy. Option B+ is a cost-effective strategy for PMTCT if the total future costs and lost lifetime of the infected infants are taken into account.

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Corrosion of a reinforcement bar leads to expansive pressure on the surrounding concrete that provokes internal cracking and, eventually, spalling and delamination. Here, an embedded cohesive crack 2D finite element is applied for simulating the cracking process. In addition, four simplified analytical models are introduced for comparative purposes. Under some assumptions about rust properties, corrosion rate, and particularly, the accommodation of oxide products within the open cracks generated in the process, the proposed FE model is able to estimate time to surface cracking quite accurately. Moreover, emerging cracking patterns are in reasonably good agreement with expectations. As a practical case, a prototype application of the model to an actual bridge deck is reported.

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Innovation studies have been interest of not only the scholars from various fields such as economics, management and sociology but also industrial practitioners and policy makers. In this vast and fruitful field, the theory of diffusion of innovations, which has been driven by a sociological approach, has played a vital role in our understanding of the mechanisms behind industrial change. In this paper, our aim is to give a state of art review of diffusion of innovation models in a structural and conceptual way with special reference to photovoltaic. We argue firstly, as an underlying background, how diffusion of innovations theory differs from other innovation studies. Secondly we give a brief taxonomical review of modelling methodologies together with comparative discussions. And finally we put the wealth of modelling in the context of photovoltaic diffusion and suggest some future directions.

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The new reactor concepts proposed in the Generation IV International Forum (GIF) are conceived to improve the use of natural resources, reduce the amount of high-level radioactive waste and excel in their reliability and safe operation. Among these novel designs sodium fast reactors (SFRs) stand out due to their technological feasibility as demonstrated in several countries during the last decades. As part of the contribution of EURATOM to GIF the CP-ESFR is a collaborative project with the objective, among others, to perform extensive analysis on safety issues involving renewed SFR demonstrator designs. The verification of computational tools able to simulate the plant behaviour under postulated accidental conditions by code-to-code comparison was identified as a key point to ensure reactor safety. In this line, several organizations employed coupled neutronic and thermal-hydraulic system codes able to simulate complex and specific phenomena involving multi-physics studies adapted to this particular fast reactor technology. In the “Introduction” of this paper the framework of this study is discussed, the second section describes the envisaged plant design and the commonly agreed upon modelling guidelines. The third section presents a comparative analysis of the calculations performed by each organisation applying their models and codes to a common agreed transient with the objective to harmonize the models as well as validating the implementation of all relevant physical phenomena in the different system codes.

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Experimental investigations and computer modelling studies have been made on the refrigerant-water counterflow condenser section of a small air to water heat pump. The main object of the investigation was a comparative study between the computer modelling predictions and the experimental observations for a range of operating conditions but other characteristics of a counterflow heat exchanger are also discussed. The counterflow condenser consisted of 15 metres of a thermally coupled pair of copper pipes, one containing the R12 working fluid and the other water flowing in the opposite direction. This condenser was mounted horizontally and folded into 0.5 metre straight sections. Thermocouples were inserted in both pipes at one metre intervals and transducers for pressure and flow measurement were also included. Data acquisition, storage and analysis was carried out by a micro-computer suitably interfaced with the transducers and thermocouples. Many sets of readings were taken under a variety of conditions, with air temperature ranging from 18 to 26 degrees Celsius, water inlet from 13.5 to 21.7 degrees, R12 inlet temperature from 61.2 to 81.7 degrees and water mass flow rate from 6.7 to 32.9 grammes per second. A Fortran computer model of the condenser (originally prepared by Carrington[1]) has been modified to match the information available from experimental work. This program uses iterative segmental integration over the desuperheating, mixed phase and subcooled regions for the R12 working fluid, the water always being in the liquid phase. Methods of estimating the inlet and exit fluid conditions from the available experimental data have been developed for application to the model. Temperature profiles and other parameters have been predicted and compared with experimental values for the condenser for a range of evaporator conditions and have shown that the model gives a satisfactory prediction of the physical behaviour of a simple counterflow heat exchanger in both single phase and two phase regions.

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We investigate an application of the method of fundamental solutions (MFS) to the backward heat conduction problem (BHCP). We extend the MFS in Johansson and Lesnic (2008) [5] and Johansson et al. (in press) [6] proposed for one and two-dimensional direct heat conduction problems, respectively, with the sources placed outside the space domain of interest. Theoretical properties of the method, as well as numerical investigations, are included, showing that accurate and stable results can be obtained efficiently with small computational cost.

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A smart solar photovoltaic grid system is an advent of innovation coherence of information and communications technology (ICT) with power systems control engineering via the internet [1]. This thesis designs and demonstrates a smart solar photovoltaic grid system that is selfhealing, environmental and consumer friendly, but also with the ability to accommodate other renewable sources of energy generation seamlessly, creating a healthy competitive energy industry and optimising energy assets efficiency. This thesis also presents the modelling of an efficient dynamic smart solar photovoltaic power grid system by exploring the maximum power point tracking efficiency, optimisation of the smart solar photovoltaic array through modelling and simulation to improve the quality of design for the solar photovoltaic module. In contrast, over the past decade quite promising results have been published in literature, most of which have not addressed the basis of the research questions in this thesis. The Levenberg-Marquardt and sparse based algorithms have proven to be very effective tools in helping to improve the quality of design for solar photovoltaic modules, minimising the possible relative errors in this thesis. Guided by theoretical and analytical reviews in literature, this research has carefully chosen the MatLab/Simulink software toolbox for modelling and simulation experiments performed on the static smart solar grid system. The auto-correlation coefficient results obtained from the modelling experiments give an accuracy of 99% with negligible mean square error (MSE), root mean square error (RMSE) and standard deviation. This thesis further explores the design and implementation of a robust real-time online solar photovoltaic monitoring system, establishing a comparative study of two solar photovoltaic tracking systems which provide remote access to the harvested energy data. This research made a landmark innovation in designing and implementing a unique approach for online remote access solar photovoltaic monitoring systems providing updated information of the energy produced by the solar photovoltaic module at the site location. In addressing the challenge of online solar photovoltaic monitoring systems, Darfon online data logger device has been systematically integrated into the design for a comparative study of the two solar photovoltaic tracking systems examined in this thesis. The site location for the comparative study of the solar photovoltaic tracking systems is at the National Kaohsiung University of Applied Sciences, Taiwan, R.O.C. The overall comparative energy output efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic monitoring system as observed at the research location site is about 72% based on the total energy produced, estimated money saved and the amount of CO2 reduction achieved. Similarly, in comparing the total amount of energy produced by the two solar photovoltaic tracking systems, the overall daily generated energy for the month of July shows the effectiveness of the azimuthal-altitude tracking systems over the 450 stationary solar photovoltaic system. It was found that the azimuthal-altitude dual-axis tracking systems were about 68.43% efficient compared to the 450 stationary solar photovoltaic systems. Lastly, the overall comparative hourly energy efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic energy system was found to be 74.2% efficient. Results from this research are quite promising and significant in satisfying the purpose of the research objectives and questions posed in the thesis. The new algorithms introduced in this research and the statistical measures applied to the modelling and simulation of a smart static solar photovoltaic grid system performance outperformed other previous works in reviewed literature. Based on this new implementation design of the online data logging systems for solar photovoltaic monitoring, it is possible for the first time to have online on-site information of the energy produced remotely, fault identification and rectification, maintenance and recovery time deployed as fast as possible. The results presented in this research as Internet of things (IoT) on smart solar grid systems are likely to offer real-life experiences especially both to the existing body of knowledge and the future solar photovoltaic energy industry irrespective of the study site location for the comparative solar photovoltaic tracking systems. While the thesis has contributed to the smart solar photovoltaic grid system, it has also highlighted areas of further research and the need to investigate more on improving the choice and quality design for solar photovoltaic modules. Finally, it has also made recommendations for further research in the minimization of the absolute or relative errors in the quality and design of the smart static solar photovoltaic module.

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Power-to-Gas storage systems have the potential to address grid-stability issues that arise when an increasing share of power is generated from sources that have a highly variable output. Although the proof-of-concept of these has been promising, the behaviour of the processes in off-design conditions is not easily predictable. The primary aim of this PhD project was to evaluate the performance of an original Power-to-Gas system, made up of innovative components. To achieve this, a numerical model has been developed to simulate the characteristics and the behaviour of the several components when the whole system is coupled with a renewable source. The developed model has been applied to a large variety of scenarios, evaluating the performance of the considered process and exploiting a limited amount of experimental data. The model has been then used to compare different Power-to-Gas concepts, in a real scenario of functioning. Several goals have been achieved. In the concept phase, the possibility to thermally integrate the high temperature components has been demonstrated. Then, the parameters that affect the energy performance of a Power-to-Gas system coupled with a renewable source have been identified, providing general recommendations on the design of hybrid systems; these parameters are: 1) the ratio between the storage system size and the renewable generator size; 2) the type of coupled renewable source; 3) the related production profile. Finally, from the results of the comparative analysis, it is highlighted that configurations with a highly oversized renewable source with respect to the storage system show the maximum achievable profit.