Naturally fractured reservoirs are generally extremely complex. The aim of characterisation and modelling of such reservoirs is to construct numerical models of rock and fractures, preparing input data for reliable stimulation and fluid flow simulation analyses. This requires the knowledge of different fracture heterogeneities and their correlations at well locations and inter-well regions. This study addresses the issues of how to integrate different information from various field data sources and construct comprehensive discrete fracture networks for naturally fractured reservoir. The methodology combines several mathematical and artificial intelligent techniques, which include statistics, geostatistics, fuzzy neural network, stochastic simulation and simulated annealing global optimisation. The study has contributed to knowledge in characterisation and modelling of naturally fractured reservoirs in several ways. It has developed: .An effective and data-dependant fracture characterisation procedure. It examines all the conventional reservoir data sources and their roles towards characterisation of different fracture properties. The procedure has the advantage of being both comprehensive and flexible. It is able to integrate all multi-scaled and diverse fracture information from the different data sources. .An improved hybrid stochastic generation algorithm for modelling discrete fracture networks. The stochastic simulation is able to utilise both discrete and continuum fracture information. It could simulate not only complicated distributions for fracture properties (e.g. multimodal circular statistics and non-parametric distributions) but also their correlations. In addition, with the incorporation of artificial fuzzy neural simulation, discrete multifractal geometry of fracture size and fracture density distribution map could be evaluated and modelled. Compared to most of the previous fracture modelling approach, this model is more flexible and comprehensive. .An improved conditional global optimisation model for modelling discrete fracture networks. The hybrid model takes full advantages of the advanced fracture characterisation using geostatistical and fuzzy neural analyses. Discrete fractures are treated individually and yet continuum information could be modelled. Compared to the stochastic simulation approach, this model produces more representative fracture networks. Compared to the conventional optimisation programs, this model is more versatile and contains superior objective function.

Hvordan kan en omkostningskalkulationsmodel udformes under moderne og fleksible produktionsforudsætninger, og hvordan påvirker stokastikken fra produktionen en given kalkulationsmodel, når der tages højde for samtlige indsatte ressourcer fra produktionen? Disse forhold er diskuteret med udgangspunkt i den existerende kalkulationsteori på området og i relation till to konkrete case-virksomheder. For at kunne gøre konkrete beregninger af stokastikkens virkninger, er der udformet en model baseret på et FMS-system, som har været testet via stokastisk simulering. Resultatet heraf viste, at variationer i processerne, transport og leadtid kan have relativ stor effekt på stykomkostningerne sammenliget med det deterministiske tilfælde. Med en stokastisk omkostningsmodel er der også mulighed for, at estimere effekten fra Design For Manufacturability (DFM) via standardafvigelsen. Dermed bliver det muligt att søge efter at minimere stokastikken og variationen fra produktionen. / Diss. Stockholm : Handelshögskolan

Caspases are important players in programmed cell death. Normal activities of caspases are critical for the cell life cycle and dysfunction of caspases may lead to the development of cancer and neurodegenerative diseases. They have become a popular target for drug design against abnormal cell death. In this study, the recognition of P5 position in substrates by caspase-3, -6 and -7 has been investigated by kinetics, modeling and crystallography. Crystal structures of caspase-3 and -7 in complexes with substrate analog inhibitor Ac-LDESD-CHO have been determined at resolutions of 1.61 and 2.45 Å, respectively, while a model of caspase-6/LDESD is constructed. Enzymatic study and structural analysis have revealed that Caspase-3 and -6 recognize P5 in pentapeptides, while caspase-7 lacks P5-binding residues. D-arginine dehydrogenase catalyzes the flavin-dependent oxidative deamination of D-amino acids to the corresponding imino acids and ammonia. The X-ray crystal structures of DADH and its complexes with several imino acids were determined at 1.03-1.30 Å resolution. The DADH crystal structure comprises a product-free conformation and a product-bound conformation. A flexible loop near the active site forms an “active site lid” and may play an essential role in substrate recognition. The DADH Glu87 forms an ionic interaction with the side chain of iminoarginine, suggesting its importance for DADH preference of positively charged D-amino acids. Comparison of the kinetic data of DADH activity on different D-amino acids and the crystal structures demonstrated that this enzyme is characterized by relatively broad substrate specificity, being able to oxidize positively charged and large hydrophobic D-amino acids bound within a flask-like cavity. Understanding biology at the system level has gained much more attention recently due to the rapid development in genome sequencing and high-throughput measurements. Current simulation methods include deterministic method and stochastic method. Both have their own advantages and disadvantages. Our group has developed a deterministic-stochastic crossover algorithm for simulating biochemical networks. Simulation studies have been performed on biological systems like auto-regulatory gene network and glycolysis system. The new system retains the high efficiency of deterministic method while still reflects the random fluctuations at lower concentration.

Simulation of animal disease spread is essential for understanding and controlling the outbreak of disease among herds of livestock (in particular cattle and poultry). Using a computerized system or simulator, animal health professionals or epidemiologists often spend many hours determining the set of input parameters that most accurately represent a disease spread or an outbreak scenario. A parameter can be a simple boolean value, or a scientific or often hypothetically derived range of real numbers. Many times, an epidemiologist chooses a value provisionally in a random fashion and repeats the simulation until a viable solution is achieved. This tedious process is inefficient and lengthy. To assist and improve this laborious practice in a concise and timely manner, a Genetic Algorithm is employed to determine a population based solution consisting of input parameters using the North American Animal Disease Spread Model (NAADSM).

Closed depressions, low elevation features in a landscape with no outlet point, play an important role in both surface and subsurface hydrology. These depressions, which are common in hummocky morainal landscapes, pool incoming surface flow, promoting infiltration and facilitating leaching of surface pollutants into vital groundwater resources. Due to the cost of ground based identification in large areas and difficulties with the identification of irregular depressions, remote identification using digital elevation models (DEMs) stands as a practical and effective tool for the mapping of these closed depressions. A modified stochastic depression identification algorithm was used in this study to characterize depressions in the Waterloo and Paris-Galt-Guelph moraines of Southwestern Ontario. The simulation output was a map of depressions in the study area. Depressions were corroborated using GRCA Wetlands data, Google Street View imagery, SWOOP 2006 orthophotos and field validation. Depression corroboration showed that the algorithm was able to accurately identify the location of closed depressions containing wetlands and closed depressions that are dry (largely due to wetland draining) in the hummocky topography of the study site. This research has implications for depression mapping in the field of digital terrain analysis as it enables the identification of real depressions in large study areas with a moderate resolution DEM. Providing a means of efficiently mapping closed depressions is important because of the role closed depressions play in the recharge of important groundwater stores. / Natural Resources Canada

The overall goal of this research is to understand roles of gut microbiota metabolites and adipocyte transcription factor (TF) network in health and disease by developing systematic analysis methods. As microbiota can perform diverse biotransformation reactions, the spectrum of metabolites present in the gastrointestinal (GI) tract is extremely complex but only a handful of bioactive microbiota metabolites have been identified. We developed a metabolomics workflow that integrates in silico discovery with targeted mass spectrometry. A computational pathway analysis where microbiota metabolisms are modeled as a single metabolic network is utilized to predict a focused set of targets for multiple reaction monitoring (MRM) analysis. We validated our methodology by predicting, quantifying in murine cecum and feces and characterizing tryptophan (TRP)-derived metabolites as ligands for the aryl hydrocarbon receptor. The adipocyte process of lipid droplet accumulation and differentiation is regulated by multiple TFs that function together in a network. Although individual TF activation is previously reported, construction of an integrated network has been limited due to different measurement conditions. We developed an integrated network model of key TFs - PPAR, C/EBP, CREB, NFAT, FoxO1, and SREBP-1c - underlying adipocyte differentiation. A hypothetic model was determined based on literature, and stochastic simulation algorithm (SSA) was applied to simulate TF dynamics. TF activation profiles at different stages of differentiation were measured using 3T3-L1 reporter cell lines where binding of a TF to its DNA binding element drives expression of the Gaussia luciferase gene. Reaction trajectories calculated by SSA showed good agreement with experimental measurement. The TF model was further validated by perturbing dynamics of CREB using forskolin, and comparing the predicted response with experimental data. We studied the molecular recognition mechanism underlying anti-inflammatory function of a bacterial metabolite, indole in DC2.4 cells. The indole treatment attenuated the fraction of cells that were producing the pro-inflammatory cytokine, TNFα and knockdown of nuclear receptor related 1 (Nurr1; NR4A2) resulted in less indole-derived suppression of TNFα production. The first discovery of NR4A2 as a molecular mediator of the endogenous metabolite, indole is expected to provide a new strategy for treatment of inflammatory disorders.

This dissertation comprises theoretical and empirical models to manage watersupply risk in irrigated agriculture. While irrigation is by itself a strategy to regulate thesupply of water for farm use, water systems that depend on surface water sources are stillsubject to the random inflows that feed their reservoirs. Depending on the size of thereservoir, the demand for irrigation, and the seasonal distribution of inflows, wateravailability may decrease to levels that severely constraint agricultural production. Thisdissertation begins with a theoretical examination of on-farm cropping decisions underwater endowment risk. However, the analysis is extended to the use of a risk-sharinginnovation to transfer the water availability risk outside an irrigation district. Specifically,the design, use, and economic feasibility of an inflow-based derivative are studied for theRio Mayo irrigation district, located in Northwestern Mexico.On the theoretical front, the analysis consists of modeling the on-farm economicsof hedging against uncertain irrigation endowments. The basic model starts by analyzingthe role of crop diversification. As expected, the firm responds to higher degrees of risk,as measured by the variance in the supply of water, by allocating less land towards thewater-intensive crops. The underlying motivation in these strategies is the need to avoidthe relatively larger reductions in productivity sustained by water-intensive cropportfolios. However, crop diversification comes at the cost of reduced profits. As analterative to crop diversification, the model is modified to study the role of an institutionthat transfers water contingent on the states of nature. The extension shows that, undercertain conditions, enrolling in such a scheme produces the same profit as undercertainty.In the empirical component of the dissertation, the economics of an inflow-basedderivative are examined. The modeling strategy consists of simulating the economicenvironment and hydrological profile of the Adolfo Ruiz Cortinez Reservoir on the RioMayo irrigation district. Specifically, a stochastic dynamic simulation model is developedthat captures the intra and inter seasonal risk aspects associated with water risk and wateruse for irrigated agriculture. The results indicate that the inflow-based derivative is aviable instrument in the terms of affordability (i.e. premiums) and yield effective incomeprotection (i.e. risk reduction).

In this study, stochastic simulation based risk analysis is applied to the government domestic debt stock in Turkey with the motivation to identify the cost and risk characteristics of alternative debt financing strategies. Future path of interest rates is simulated by using the yield curve forecasting framework in Diebold and Li (2002), which is founded on the Nelson-Siegel yield curve model. Yield curve simulation is based on the estimated term structure of interest rates for the period June 2001-July 2004. Simulated yield curves are generally upward sloped and concave. Contrary to the common observation, long-term yields are more volatile compared to short-term yields. Under each financing strategy, debt is rolled over on top of simulated term structure of interest rates. Alternative financing strategies are compared with respect to absolute Cost-at-Risk, relative Cost-at-Risk and relative risk measures computed from the simulated cost distributions. Results of the risk analysis are influenced by the characteristics of the simulated term structure of interest rates and the additional yield imposed on the coupon bonds, which is assumed to reflect risk perception of investors for increased maturity.

Se manipulado de forma eficiente, o crescimento compensatório pode ser uma alternativa para reduzir o custo com a alimentação. No presente trabalho objetivou-se analisar o efeito bioeconômico do crescimento compensatório sobre sistemas intensivos de recria e terminação de bovinos de corte. Por meio de simulação, em um Sistema de Apoio a Decisão, a produtividade (Pr) e a resposta econômica foram avaliadas em quatro sistemas. Caracterizados por diferentes períodos de restrição alimentar (sem restrição, CONT; 90 dias de restrição, COMP90; 120 dias de restrição, COMP120 e 150 dias de restrição, COMP150) no período pós-desmama. Além disso, foram realizadas análises de risco e de sensibilidade, por meio de simulação de Monte Carlo. Os sistemas com regime alimentar restrito necessitaram de maior período de engorda (14, 21 e 35 dias para COMP90, COMP120 e COMP150, respectivamente) que CONT. O sistema COMP90 teve Pr (434,2 kg/ha/ano) similar ao CONT (434,0 kg/ha/ano) e ambos maiores que COMP120 (395,0 kg/ha/ano) e COMP150 (394,0 kg/ha/ano). A margem bruta/ha foi de 608,98; 493,5; 366,96 e 304,23 R$/ha/ano para os sistemas COMP90, CONT, COMP120 e COMP150, respectivamente. Entretanto, na análise de risco o sistema menos estável economicamente foi o CONT e o com menor risco foi COMP90. A análise de sensibilidade demonstrou que as variáveis com maior efeito sobre a margem bruta foram o preço do boi gordo, do bezerro e do milho usado no confinamento. O uso do crescimento compensatório pode ser uma ferramenta para redução de custos com a alimentação em sistemas de recria e engorda de bovinos de corte, mas a sua eficácia é influenciada pelo período de restrição. / When used efficiently the compensatory growth can be an option to reduce feeding cost. The aim was to analyze the bioeconomic effect of compensatory growth on intensive growing and fattening beef cattle systems. By simulation using a Decision Support System the productivity and the economic return were evaluated in four different systems, characterized by different periods of feeding restriction (no restriction, CONT; 90 days restriction, COMP90; 120 days restriction, COMP120 and 150 days restriction, COMP150). Besides, the risk analysis and sensitivity analysis were performed using Monte Carlo simulation. The systems with restriction of feeding required longer fattening periods (14, 21 e 35 days for COMP90, COMP120 e COMP150 respectively) than the CONT system. The COM90 obtained higher productivity (434,2 kg/ha/year) close of CONT system (434kg/ ha/ year) and both were higher than COMP120 (395 kg/ha/year) and COMP150 (394 kg/ha/year). The highest gross margin/ha was obtained in COMP90 (608,98 R$/ha/year) that was more than CONT (493,5 R$/ha/year), COMP120 (366,96 R$/ha/year) and COMP150 (304,23 R$/ha/ year). However, the risk analysis resulted in a highest risk using CONT system and lowest risk with COMP90. The sensitivity analysis demonstrated that the variables with the most effect on gross margin are beef, calf and corn prices. The use of compensatory growth can be a tool to reduce feeding costs in beef cattle systems however its effectiveness is influenced by the restriction period.

Se manipulado de forma eficiente, o crescimento compensatório pode ser uma alternativa para reduzir o custo com a alimentação. No presente trabalho objetivou-se analisar o efeito bioeconômico do crescimento compensatório sobre sistemas intensivos de recria e terminação de bovinos de corte. Por meio de simulação, em um Sistema de Apoio a Decisão, a produtividade (Pr) e a resposta econômica foram avaliadas em quatro sistemas. Caracterizados por diferentes períodos de restrição alimentar (sem restrição, CONT; 90 dias de restrição, COMP90; 120 dias de restrição, COMP120 e 150 dias de restrição, COMP150) no período pós-desmama. Além disso, foram realizadas análises de risco e de sensibilidade, por meio de simulação de Monte Carlo. Os sistemas com regime alimentar restrito necessitaram de maior período de engorda (14, 21 e 35 dias para COMP90, COMP120 e COMP150, respectivamente) que CONT. O sistema COMP90 teve Pr (434,2 kg/ha/ano) similar ao CONT (434,0 kg/ha/ano) e ambos maiores que COMP120 (395,0 kg/ha/ano) e COMP150 (394,0 kg/ha/ano). A margem bruta/ha foi de 608,98; 493,5; 366,96 e 304,23 R$/ha/ano para os sistemas COMP90, CONT, COMP120 e COMP150, respectivamente. Entretanto, na análise de risco o sistema menos estável economicamente foi o CONT e o com menor risco foi COMP90. A análise de sensibilidade demonstrou que as variáveis com maior efeito sobre a margem bruta foram o preço do boi gordo, do bezerro e do milho usado no confinamento. O uso do crescimento compensatório pode ser uma ferramenta para redução de custos com a alimentação em sistemas de recria e engorda de bovinos de corte, mas a sua eficácia é influenciada pelo período de restrição. / When used efficiently the compensatory growth can be an option to reduce feeding cost. The aim was to analyze the bioeconomic effect of compensatory growth on intensive growing and fattening beef cattle systems. By simulation using a Decision Support System the productivity and the economic return were evaluated in four different systems, characterized by different periods of feeding restriction (no restriction, CONT; 90 days restriction, COMP90; 120 days restriction, COMP120 and 150 days restriction, COMP150). Besides, the risk analysis and sensitivity analysis were performed using Monte Carlo simulation. The systems with restriction of feeding required longer fattening periods (14, 21 e 35 days for COMP90, COMP120 e COMP150 respectively) than the CONT system. The COM90 obtained higher productivity (434,2 kg/ha/year) close of CONT system (434kg/ ha/ year) and both were higher than COMP120 (395 kg/ha/year) and COMP150 (394 kg/ha/year). The highest gross margin/ha was obtained in COMP90 (608,98 R$/ha/year) that was more than CONT (493,5 R$/ha/year), COMP120 (366,96 R$/ha/year) and COMP150 (304,23 R$/ha/ year). However, the risk analysis resulted in a highest risk using CONT system and lowest risk with COMP90. The sensitivity analysis demonstrated that the variables with the most effect on gross margin are beef, calf and corn prices. The use of compensatory growth can be a tool to reduce feeding costs in beef cattle systems however its effectiveness is influenced by the restriction period.