Density-Profile Processes Describing Biological Signaling Networks: Almost Sure Convergence to Deterministic Trajectories

We introduce jump processes in R(k), called density-profile processes, to model biological signaling networks. Our modeling setup describes the macroscopic evolution of a finite-size spin-flip model with k types of spins with arbitrary number of internal states interacting through a non-reversible stochastic dynamics. We are mostly interested on the multi-dimensional empirical-magnetization vector in the thermodynamic limit, and prove that, within arbitrary finite time-intervals, its path converges almost surely to a deterministic trajectory determined by a first-order (non-linear) differential equation with explicit bounds on the distance between the stochastic and deterministic trajectories. As parameters of the spin-flip dynamics change, the associated dynamical system may go through bifurcations, associated to phase transitions in the statistical mechanical setting. We present a simple example of spin-flip stochastic model, associated to a synthetic biology model known as repressilator, which leads to a dynamical system with Hopf and pitchfork bifurcations. Depending on the parameter values, the magnetization random path can either converge to a unique stable fixed point, converge to one of a pair of stable fixed points, or asymptotically evolve close to a deterministic orbit in Rk. We also discuss a simple signaling pathway related to cancer research, called p53 module.

Open Issues in Control ofAutomotive R744 Air-ConditioningSystems

In this thesis, one of the current control algorithms for the R744 cycle, which tries tooptimize the performance of the system by two SISO control loops, is compared to acost-effective system with just one actuator. The operation of a key component of thissystem, a two stage orifice expansion valve is examined in a range of typical climateconditions. One alternative control loop for this system, which has been proposed byBehr group, is also scrutinized.The simulation results affirm the preference of using two control-loops instead of oneloop, but refute advantages of the Behr alternate control approach against one-loopcontrol. As far as the economic considerations of the A/C unit are concerned, usinga two-stage orifice expansion valve is desired by the automotive industry, thus basedon the experiment results, an improved logic for control of this system is proposed.In the second part, it is investigated whether the one-actuator control approach isapplicable to a system consisting of two parallel evaporators to allow passengers tocontrol different climate zones. The simulation results show that in the case of usinga two-stage orifice valve for the front evaporator and a fixed expansion valve forthe rear one, a proper distribution of the cooling power between the front and rearcompartment is possible for a broad range of climate conditions.

Applicatiion of Almost ideal demand system for a pharmaceutical

This thesis is an application of the Almost Ideal Demand System approach of Deaton and Muellbauer,1980, for a particular pharmaceutical, Citalopram, in which GORMAN´s (1971) multi-stage budgeting approach is applied basically since it is one of the most useful approach in estimating demand for differentiated products. Citalopram is an antidepressant drug that is used in the treatment of major depression. As for most other pharmaceuticals whose the patent has expired, there exist branded and generic versions of Citalopram. This paper is aimed to define its demand system with two stage models for the branded version and five generic versions, and to show whether generic versions are able to compete with the branded version. I calculated the own price elasticities, and it made me possible to compare and make a conclusion about the consumers’ choices over the brand and generic drugs. Even though the models need for being developed with some additional variables, estimation results of models and uncompensated price elasticities indicated that the branded version has still power in the market, and generics are able to compete with lower prices. One important point that has to be taken into consideration is that the Swedish pharmaceutical market faced a reform on October 1, 2002, that aims to make consumer better informed about the price and decrease the overall expenditures for pharmaceuticals. Since there were not significantly enough generic sales to take into calculation before the reform, my paper covers sales after the reform.

Spanning Tree Approach On The Snow Cleaning Problem

Snow cleaning is one of the important tasks in the winter time in Sweden. Every year government spends huge amount money for snow cleaning purpose. In this thesis we generate a shortest road network of the city and put the depots in different place of the city for snow cleaning. We generate shortest road network using minimum spanning tree algorithm and find the depots position using greedy heuristic. When snow is falling, vehicles start work from the depots and clean the snow all the road network of the city. We generate two types of model. Models are economic model and efficient model. Economic model provide good economical solution of the problem and it use less number of vehicles. Efficient model generate good efficient solution and it take less amount of time to clean the entire road network.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.

Parameterization Of Turbulence Models Using 3DVAR Data Assimilation

In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ε model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ε model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. 3DVAR allows also to identify and quantify shortcomings of the numerical model. Such comprehensive analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows.

Estudo clínico de fase II e farmacocinético para o uso de Talidomida em pacientes com câncer colorretal metastático

O objetivo deste estudo foi avaliar a eficácia, a segurança e a farmacocinética da talidomida nos pacientes com câncer colorretal metastático. Dezessete pacientes com adenocarcinoma colorretal metastático, previamente tratados com pelo menos um regime de quimioterapia, foram incluídos no estudo. Os pacientes eram inicialmente tratados com talidomida 200 mg/dia, com um aumento de dose de 200mg a cada duas semanas, até atingir a dose máxima de 800 mg/dia. Os pacientes eram reavaliados a cada duas semanas para toxicidade e a cada 8 semanas para taxa de resposta através de exames de imagem. A farmacocinética foi caracterizada em quatro pacientes no nível de dose de 200 mg/dia.Todos os dezessete pacientes incluídos foram avaliados no perfil de toxicidade e quatorze pacientes nos critérios de taxa de resposta. A talidomida foi bem tolerada, sendo os principais efeitos colaterais a sonolência, a tontura, a xerostomia e a constipação. Não houve nenhuma resposta objetiva ou doença estável após oito semanas de tratamento. A sobrevida global mediana foi de 3,6 meses. A talidomida é bem tolerada como agente único de tratamento, mas não demonstrou nenhuma atividade antitumoral em pacientes com câncer colorretal metastático, já tratados previamente com outro regime de quimioterapia. Apesar disto, futuros estudos com este agente em estágios iniciais desta neoplasia devem ser considerados, quando as propriedades antiangiogênicas desta droga poderão ser mais relevantes para a progressão da doença.

Respostas dinâmicas em sistemas distribuídos e decomposição forçada da superfície livre para um modelo acoplado Oceano-Atmosfera

O objetivo deste trabalho é a introdução e desenvolvimento de uma metodologia analítico-simbólica para a obtenção de respostas dinâmicas e forçadas (soluções homogêneas e não homogêneas) de sistemas distribuídos, em domínios ilimitados e limitados, através do uso da base dinâmica gerada a partir da resposta impulso. Em domínios limitados, a resposta impulso foi formulada pelo método espectral. Foram considerados sistemas com condições de contorno homogêneas e não homogêneas. Para sistemas de natureza estável, a resposta forçada é decomposta na soma de uma resposta particular e de uma resposta livre induzida pelos valores iniciais da resposta particular. As respostas particulares, para entradas oscilatórias no tempo, foram calculadas com o uso da fun»c~ao de Green espacial. A teoria é desenvolvida de maneira geral permitindo que diferentes sis- temas evolutivos de ordem arbitrária possam ser tratados sistematicamente de uma forma compacta e simples. Realizou-se simulações simbólicas para a obtenção de respostas dinâmicas e respostas for»cadas com equações do tipo parabólico e hiperbólico em 1D,2D e 3D. O cálculo das respostas forçadas foi realizado com a determinação das respostas livres transientes em termos dos valores iniciais das respostas permanentes. Foi simulada a decomposição da resposta forçada da superfície livre de um modelo acoplado oceano-atmosfera bidimensional, através da resolução de uma equação de Klein-Gordon 2D com termo não-homogêneo de natureza dinâmica, devido a tensão de cisalhamento na superfície do oceano pela ação do vento.

Forecasting electricity demand using generalized long memory

This paper studies the electricity hourly load demand in the area covered by a utility situated in the southeast of Brazil. We propose a stochastic model which employs generalized long memory (by means of Gegenbauer processes) to model the seasonal behavior of the load. The model is proposed for sectional data, that is, each hour’s load is studied separately as a single series. This approach avoids modeling the intricate intra-day pattern (load profile) displayed by the load, which varies throughout days of the week and seasons. The forecasting performance of the model is compared with a SARIMA benchmark using the years of 1999 and 2000 as the out-of-sample. The model clearly outperforms the benchmark. We conclude for general long memory in the series.

Inflation and overbanking

This paper argues that monetary models can and usually present the phenomenon of over-banking; that is, the market solution of the model presents a size of the banking sector which is higher than the social optima. Applying a two sector monetary model of capital accumulation in presence of a banking sector, which supplies liquidity services, it is shown that the rise of a tax that disincentives the acquisition of the banking service presents the following impacts on welfare. If the technology is the same among the sectors, the tax increases welfare; otherwise, steady-state utility increase if the banking sector is labor-intensive compared to the real sector. Additionally, it is proved that the elevation of inflation has the following impact on the economy's equilibrium: the share on the product of the banking sector increases; the product and the stock of capital increases or reduces whether the banking sector is capital-intensive or laborintensive; and, the steady-state utility reduces. The results were derived under a quite general set up - standard hypothesis regarding concavity of preference, convexity of technology, and normality of goods - were required.

How does foreign capital participation affect brazilian companies' performance?: investigation of foreign direct investment's impact on host country

In this dissertation, we investigate the effect of foreign capital participations in Brazilians companies’ performance. To carry out this analysis, we constructed two sets of model based on EBITDA margin and return on equity. Panel data analysis is used to examine the relationship between foreign capital ownership and Brazilian firms’ performance. We construct a cross-section time-series sample of companies listed on the BOVESPA index from 2006 to 2010. Empirical results led us to validate two hypotheses. First, foreign capital participations improve companies’ performance up to a certain level of participation. Then, joint controlled or strategic partnership between a Brazilian company and a foreign investor provide high operating performance.

Estimating the effect of discretionary spending on corruption: evidence from Brazilian municipalities

O presente artigo estuda a relação entre corrupção e discricionariedade do gasto público ao responder a seguinte pergunta: regras de licitação mais rígidas, uma proxy para discricionariedade, resultam em menor prevalência de corrupção nos municípios brasileiros? A estratégia empírica é uma aproximação de regressões em dois estágios (2SLS) estimadas localmente em cada transição de regras de licitação, cuja fonte de dados de corrupção é o Programa de Fiscalização por Sorteio da CGU e os dados sobre discricionariedade são derivados da Lei 8.666/93, responsável por regular os processos de compras e construção civil em todas as esferas de governo. Os resultados mostram, entretanto, que menor discricionariedade está relacionada com maior corrupção para quase todos os cortes impostos pela lei de licitações.

Wald tests for IV regression with weak instruments

This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).

Generic-branded drug competition and the price for pharmaceuticals in procurement auctions

This paper studies the effects of generic drug’s entry on bidding behavior of drug suppliers in procurement auctions for pharmaceuticals, and the consequences on procurer’s price paid for drugs. Using an unique data set on procurement auctions for off-patent drugs organized by Brazilian public bodies, we surprisingly find no statistically difference between bids and prices paid for generic and branded drugs. On the other hand, some branded drug suppliers leave auctions in which there exists a supplier of generics, whereas the remaining ones lower their bidding price. These findings explain why we find that the presence of any supplier of generic drugs in a procurement auction reduces the price paid for pharmaceuticals by 7 percent. To overcome potential estimation bias due to generic’s entry endogeneity, we exploit variation in the number of days between drug’s patent expiration date and the tendering session. The two-stage estimations document the same pattern as the generalized least square estimations find. This evidence indicates that generic competition affects branded supplier’s behavior in public procurement auctions differently from other markets.

Previsão da estrutura a termo de taxa de juros aplicando o Filtro de Kalman ao modelo Vasicek: o caso brasileiro

Este trabalho tem o objetivo de testar a qualidade preditiva do Modelo Vasicek de dois fatores acoplado ao Filtro de Kalman. Aplicado a uma estratégia de investimento, incluímos um critério de Stop Loss nos períodos que o modelo não responde de forma satisfatória ao movimento das taxas de juros. Utilizando contratos futuros de DI disponíveis na BMFBovespa entre 01 de março de 2007 a 30 de maio de 2014, as simulações foram realizadas em diferentes momentos de mercado, verificando qual a melhor janela para obtenção dos parâmetros dos modelos, e por quanto tempo esses parâmetros estimam de maneira ótima o comportamento das taxas de juros. Os resultados foram comparados com os obtidos pelo Modelo Vetor-auto regressivo de ordem 1, e constatou-se que o Filtro de Kalman aplicado ao Modelo Vasicek de dois fatores não é o mais indicado para estudos relacionados a previsão das taxas de juros. As limitações desse modelo o restringe em conseguir estimar toda a curva de juros de uma só vez denegrindo seus resultados.