Aproximação numérica – analítica para a modelagem da conversão termoquímica de combustíveis sólidos

Um algoritmo numérico foi criado para apresentar a solução da conversão termoquímica de um combustível sólido. O mesmo foi criado de forma a ser flexível e dependente do mecanismo de reação a ser representado. Para tanto, um sistema das equações características desse tipo de problema foi resolvido através de um método iterativo unido a matemática simbólica. Em função de não linearidades nas equações e por se tratar de pequenas partículas, será aplicado o método de Newton para reduzir o sistema de equações diferenciais parciais (EDP’s) para um sistema de equações diferenciais ordinárias (EDO’s). Tal processo redução é baseado na união desse método iterativo à diferenciação numérica, pois consegue incorporar nas EDO’s resultantes funções analíticas. O modelo reduzido será solucionado numericamente usando-se a técnica do gradiente bi-conjugado (BCG). Tal modelo promete ter taxa de convergência alta, se utilizando de um número baixo de iterações, além de apresentar alta velocidade na apresentação das soluções do novo sistema linear gerado. Além disso, o algoritmo se mostra independente do tamanho da malha constituidora. Para a validação, a massa normalizada será calculada e comparada com valores experimentais de termogravimetria encontrados na literatura, , e um teste com um mecanismo simplificado de reação será realizado.

Fatores determinantes da política de distribuição de dividendos: Evidência empírica para as empresas não financeiras da Euronext Lisbon

Dividends and their distribution decisions, being a component of the compensation of investors are a constant financial worry within companies, thus revealing one of the themes highlighted in the context of the financial literature. Study will address the factors determining the dividend policy practiced by companies listed in the Portuguese stock market. The latter will be 47 non-financial companies listed on the Euronext Lisbon during 2009 until 2011. The two samples that have been investigated include the representative of the majority of non-financial companies listed on Euronext Lisbon and the other financial companies members of the PSI 20. The methodology adopted is one of the ordinary least squares regression and the amount of dividends per share distributed was used in determining the dependent variable. In relation to the independent variables, six explanatory factors were chosen. These include profitability, stability of dividend policy, size, growth, risk and investment opportunities. The conclusion suggests that the most important factors to explain the amount of dividends distributed are profitability and stability of dividend policy. There after, growth and risk factors, as well as factors that explain the amount of dividends distributed are also relevant. The remaining variables obtained were insufficient evidence pointing to a significant effect in explaining the dividend policy of Portuguese companies in the sample. The conclusion also states that differences exist in the importance of the explanatory factors to the amount of dividends distributed between the study samples, given the differentiation of dividend policies, followed by companies from each group analyzed.

Scheduling of head-dependent cascaded reservoirs considering discharge ramping constraints and start/stop of units

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning head-dependent reservoirs under competitive environment. We propose a novel method, based on mixed-integer nonlinear programming (MINLP), for optimising power generation efficiency. This method considers hydroelectric power generation as a nonlinear function of water discharge and of the head. The main contribution of this paper is that discharge ramping constraints and start/stop of units are also considered, in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve two case studies based on Portuguese cascaded hydro systems, providing a higher profit at an acceptable computation time in comparison with classical optimisation methods based on mixed-integer linear programming (MILP).

Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chain

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to eat her studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement.

Learning dependent sources using mixtures of Dirichlet: applications on hyperspectral unmixing

This paper is an elaboration of the DECA algorithm [1] to blindly unmix hyperspectral data. The underlying mixing model is linear, meaning that each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. The proposed method, as DECA, is tailored to highly mixed mixtures in which the geometric based approaches fail to identify the simplex of minimum volume enclosing the observed spectral vectors. We resort then to a statitistical framework, where the abundance fractions are modeled as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. With respect to DECA, we introduce two improvements: 1) the number of Dirichlet modes are inferred based on the minimum description length (MDL) principle; 2) The generalized expectation maximization (GEM) algorithm we adopt to infer the model parameters is improved by using alternating minimization and augmented Lagrangian methods to compute the mixing matrix. The effectiveness of the proposed algorithm is illustrated with simulated and read data.

Scheduling of head-dependent cascaded hydro systems: Mixed-integer quadratic programming approach

This paper is on the problem of short-term hydro, scheduling, particularly concerning head-dependent cascaded hydro systems. We propose a novel mixed-integer quadratic programming approach, considering not only head-dependency, but also discontinuous operating regions and discharge ramping constraints. Thus, an enhanced short-term hydro scheduling is provided due to the more realistic modeling presented in this paper. Numerical results from two case studies, based on Portuguese cascaded hydro systems, illustrate the proficiency of the proposed approach.

Bias dependent photocurrent collection in p-i-n a-Si : EVSiC : H heterojunction

A series of large area single layers and heterojunction cells in the assembly glass/ZnO:Al/p (SixC1-x:H)/i (Si:H)/n (SixC1-x:H)/Al (0 dependent mainly on minority carriers the diffusion.

Bias-dependent photocurrent collection in p-i-n a-Si : H/SiC : H heterojunction

A series of large area single layers and glass/ZnO:AVp(SixC1-x:H)/i(Si:H)/n(SixC1-x:H)/AI (0 < x < 1) heterojunction cells were produced by plasma-enhanced chemical vapour deposition (PE-CVD) at low temperature. Junction properties, carrier transport and photogeneration are investigated from dark and illuminated current-voltage (J-V) and capacitance-voltage (C-V) characteristics. For the heterojunction cells atypical J-V characteristics under different illumination conditions are observed leading to poor fill factors. High series resistances around 106 Q are also measured. These experimental results were used as a basis for the numerical simulation of the energy band diagram, and the electrical field distribution of the structures. Further comparison with the sensor performance gave satisfactory agreement. Results show that the conduction band offset is the most limiting parameter for the optimal collection of the photogenerated carriers. As the optical gap increases and the conductivity of the doped layers decreases, the transport mechanism changes from a drift to a diffusion-limited process.

Malaria transmission model for different levels of acquired immunity and temperature-dependent parameters (vector)

OBJECTIVE: Describe the overall transmission of malaria through a compartmental model, considering the human host and mosquito vector. METHODS: A mathematical model was developed based on the following parameters: human host immunity, assuming the existence of acquired immunity and immunological memory, which boosts the protective response upon reinfection; mosquito vector, taking into account that the average period of development from egg to adult mosquito and the extrinsic incubation period of parasites (transformation of infected but non-infectious mosquitoes into infectious mosquitoes) are dependent on the ambient temperature. RESULTS: The steady state equilibrium values obtained with the model allowed the calculation of the basic reproduction ratio in terms of the model's parameters. CONCLUSIONS: The model allowed the calculation of the basic reproduction ratio, one of the most important epidemiological variables.

Re-entrant phase behaviour of network fluids: A patchy particle model with temperature-dependent valence

We study a model consisting of particles with dissimilar bonding sites ("patches"), which exhibits self-assembly into chains connected by Y-junctions, and investigate its phase behaviour by both simulations and theory. We show that, as the energy cost epsilon(j) of forming Y-junctions increases, the extent of the liquid-vapour coexistence region at lower temperatures and densities is reduced. The phase diagram thus acquires a characteristic "pinched" shape in which the liquid branch density decreases as the temperature is lowered. To our knowledge, this is the first model in which the predicted topological phase transition between a fluid composed of short chains and a fluid rich in Y-junctions is actually observed. Above a certain threshold for epsilon(j), condensation ceases to exist because the entropy gain of forming Y-junctions can no longer offset their energy cost. We also show that the properties of these phase diagrams can be understood in terms of a temperature-dependent effective valence of the patchy particles. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3605703]

Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

Habitat differentiation between groups of Risso's dolphins as evidence of coastal nursery areas

26th Annual Conference of the European Cetacean Society, Galway, Ireland 26-28 March 2012.

Effects of antihypertensive drugs in the differentiation and activation of human bone cells

O osso é um tecido metabolicamente ativo e a sua remodelação é importante para regular e manter a massa óssea. Esse processo envolve a reabsorção do material ósseo por ação dos osteoclastos e a síntese de novo material ósseo mediado pelos osteoblastos. Vários estudos têm sugerido que a pressão arterial elevada está associada a alterações no metabolismo do cálcio, o que leva ao aumento da perda de cálcio e da remoção de cálcio do osso. Embora as alterações no metabolismo ósseo sejam um efeito adverso associado a alguns fármacos antihipertensores, o conhecimento em relação a este efeito terapêutico ligado com os bloqueadores de canais de cálcio é ainda muito escasso. Uma vez que os possíveis efeitos no osso podem ser atribuídos à ação antihipertensiva dessas moléculas, ou através de um efeito direto nas atividades metabólicas ósseas, torna-se necessário esclarecer este assunto. Devido ao facto de que as alterações no metabolismo ósseo são um efeito adverso associado a alguns fármacos antihipertensores, o objetivo deste trabalho é avaliar o efeito que os bloqueadores dos canais de cálcio exercem sobre as células ósseas humanas, nomeadamente osteoclastos, osteoblastos e co-culturas de ambos os tipos celulares. Verificou-se que os efeitos dos fármacos antihipertensores variaram consoante o fármaco testado e o sistema de cultura usado. Alguns fármacos revelaram a capacidade de estimular a osteoclastogénese e a osteoblastogénese em concentrações baixas. Independentemente da identidade do fármaco, concentrações elevadas revelaram ser prejudiciais para a resposta das células ósseas. Os mecanismos intracelulares através dos quais os efeitos foram exercidos foram igualmente afetados de forma diferencial pelos diferentes fármacos. Em resumo, este trabalho demonstrou que os bloqueadores dos canais de cálcio utilizados possuem a capacidade de afetar direta- e indiretamente a resposta de células ósseas humanas, cultivadas isoladamente ou co-cultivadas. Este tipo de informação é crucial para compreender e prevenir os potenciais efeitos destes fármacos no tecido ósseo, e também para adequar e eventualmente melhorar a terapêutica antihipertensora de cada paciente.

Students' engagement in schools : differentiation and promotion

The objective of this work is to present elements of the project Student engagement in Schools (SES). The team consists of 10 researchers from six Universities. Student engagement in schools is a multidimensional construct that unites affective, behavioural, and cognitive dimensions of student adaptation in the school and has influence on students’outcomes. The team of researchers conceptualized two major studies, a differential study to analyze the relations between SES and contextual factors, personal factors, student’s outcomes, and a quasi-experimental study to analyze the effects on SES of a specific intervention programmes. In study 1, the sample size is around 600 students (150 6th graders, 150 7th graders, 150 9th graders, and 150 10th graders). We shall focus on years of school transition, with rural and urban populations, on different regions of the country, and on students with different family background. We shall conduct questionnaires with national and international scales. The study 2 will involve students in 7th and 9th grade, from four classes, two of the experimental group and two of the control group. Patterns of verbal communication between a teacher and students can influence the classroom environment and SES. This model of communication would result in more effective student management and more time on-task for learning.

Dependent component analysis: a hyperspectral unmixing algorithm

Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.