Modelos Teóricos de Difusão Dérmica: abordagens matemáticas e computacionais para terapias transdérmicas da Obesidade

É de senso comum que os nutrientes são fundamentais à vida e que a subnutrição leva à acumulação de gorduras que pode chegar a casos de obesidade, tendo como consequência inúmeras complicações de saúde. Diferentes estruturas neuroanatómicas do cérebro têm um papel essencial no comportamento digestivo. A ação de várias moléculas de sinalização (hormonas, neurotransmissores e neuropéptidos) resulta na regulação da ingestão de alimentos, sendo que, por exemplo, algumas hormonas podem aumentar a sensação de saciedade podendo diminuir o apetite e a ingestão calórica. A descoberta de hormonas envolvidas no balanço energético proporcionou novas oportunidades para desenvolver meios para o tratamento da obesidade. A transferência de medicação antiobesidade por via tópica ou transdérmica é um desafio pois a pele funciona como uma barreira natural e protetora. Sendo uma barreira com uma grande área de superfície e de fácil acessibilidade, a pele tem potencial interesse na libertação de fármacos específicos a cada terapia. Vários métodos têm sido estudados de modo a permitir um aumento da permeabilidade de moléculas terapêuticas para o interior da pele e através da pele. As biotecnologias transdérmicas são um campo de interesse cada vez maior, devido as aplicações dérmicas e farmacêuticas que lhes estão subjacentes. Existem vários modelos computacionais e matemáticos em uso que permite uma visão mais abrangente de puros dados experimentais e até mesmo permite a extrapolação prática de novas metodologias de difusão dérmica. Contudo, eles compreendem uma complexa variedade de teorias e suposições que atribuem a sua utilização para situações específicas. Este trabalho, primeiramente analisa, de forma extensiva, as várias metodologias teóricas para o estudo da difusão dérmica e sistematiza as suas características, realizando depois a fase prévia duma nova abordagem computacional para o estudo da difusão dérmica, que determina características microscópicas de moléculas capazes de provocar a perda de peso, tais como a Leptina e/ou os seus agonistas.

New insights on integer-programming models for the kidney exchange problem

In recent years several countries have set up policies that allow exchange of kidneys between two or more incompatible patient–donor pairs. These policies lead to what is commonly known as kidney exchange programs. The underlying optimization problems can be formulated as integer programming models. Previously proposed models for kidney exchange programs have exponential numbers of constraints or variables, which makes them fairly difficult to solve when the problem size is large. In this work we propose two compact formulations for the problem, explain how these formulations can be adapted to address some problem variants, and provide results on the dominance of some models over others. Finally we present a systematic comparison between our models and two previously proposed ones via thorough computational analysis. Results show that compact formulations have advantages over non-compact ones when the problem size is large.

Supporting leadership development by exposure to role models: two case studies

The idiomatic expression “In Rome be a Roman” can be applied to leadership training and development as well. Leaders who can act as role models inspire other future leaders in their behaviour, attitudes and ways of thinking. Based on two examples of current leaders in the fields of Politics and Public Administration, I support the idea that exposure to role models during their training was decisive for their career paths and current activities as prominent characters in their profession. Issues such as how students should be prepared for community or national leadership as well as cross-cultural engagement are raised here. The hypothesis of transculturalism and cross-cultural commitment as a factor of leadership is presented. Based on current literature on Leadership as well as the presented case studies, I expect to raise a debate focusing on strategies for improving leaders’ training in their cross-cultural awareness.

Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

Computational intelligence applications for future power systems

Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency. The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements. Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation, fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as the most adequate methodologies to address several planning, control and operation problems in power systems. Future power systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires more effective optimization and control techniques techniques so that the involved players can make the most adequate use of existing resources in the new context. The application of computational intelligence methods to deal with several problems of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises of computational intelligence, and illustrate their potentials.

Previsão de vento baseado em técnicas de Data Mining

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Computational analysis of quinoxalines N,N-Dioxide and ITS Derivates

A quinoxalina e seus derivativos são uma importante classe de compostos heterocíclicos, onde os elementos N, S e O substituem átomos de carbono no anel. A fórmula molecular da quinoxalina é C8H6N2, formada por dois anéis aromáticos, benzeno e pirazina. É rara em estado natural, mas a sua síntese é de fácil execução. Modificações na estrutura da quinoxalina proporcionam uma grande variedade de compostos e actividades, tais como actividades antimicrobiana, antiparasitária, antidiabética, antiproliferativa, anti-inflamatória, anticancerígena, antiglaucoma, antidepressiva apresentando antagonismo do receptor AMPA. Estes compostos também são importantes no campo industrial devido, por exemplo, ao seu poder na inibição da corrosão do metal. A química computacional, ramo natural da química teórica é um método bem desenvolvido, utilizado para representar estruturas moleculares, simulando o seu comportamento com as equações da física quântica e clássica. Existe no mercado uma grande variedade de ferramentas informaticas utilizadas na química computacional, que permitem o cálculo de energias, geometrias, frequências vibracionais, estados de transição, vias de reação, estados excitados e uma variedade de propriedades baseadas em várias funções de onda não correlacionadas e correlacionadas. Nesta medida, a sua aplicação ao estudo das quinoxalinas é importante para a determinação das suas características químicas, permitindo uma análise mais completa, em menos tempo, e com menos custos.

Modelling and segmentation of the vocal tract during speech production by using deformable models in magnetic resonance images

The first and second authors would like to thank the support of the PhD grants with references SFRH/BD/28817/2006 and SFRH/PROTEC/49517/2009, respectively, from Fundação para a Ciência e Tecnol ogia (FCT). This work was partially done in the scope of the project “Methodologies to Analyze Organs from Complex Medical Images – Applications to Fema le Pelvic Cavity”, wi th reference PTDC/EEA- CRO/103320/2008, financially supported by FCT.

Analysis of tongue shape and motion in speech production using statistical modeling

The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.

Modelling adhesive joints with cohesive zone models: effect of the cohesive law shape of the adhesive layer

Adhesively-bonded joints are extensively used in several fields of engineering. Cohesive Zone Models (CZM) have been used for the strength prediction of adhesive joints, as an add-in to Finite Element (FE) analyses that allows simulation of damage growth, by consideration of energetic principles. A useful feature of CZM is that different shapes can be developed for the cohesive laws, depending on the nature of the material or interface to be simulated, allowing an accurate strength prediction. This work studies the influence of the CZM shape (triangular, exponential or trapezoidal) used to model a thin adhesive layer in single-lap adhesive joints, for an estimation of its influence on the strength prediction under different material conditions. By performing this study, guidelines are provided on the possibility to use a CZM shape that may not be the most suited for a particular adhesive, but that may be more straightforward to use/implement and have less convergence problems (e.g. triangular shaped CZM), thus attaining the solution faster. The overall results showed that joints bonded with ductile adhesives are highly influenced by the CZM shape, and that the trapezoidal shape fits best the experimental data. Moreover, the smaller is the overlap length (LO), the greater is the influence of the CZM shape. On the other hand, the influence of the CZM shape can be neglected when using brittle adhesives, without compromising too much the accuracy of the strength predictions.

Dermic diffusion and stratum corneum: a state of the art review of mathematical models

Transdermal biotechnologies are an ever increasing field of interest, due to the medical and pharmaceutical applications that they underlie. There are several mathematical models at use that permit a more inclusive vision of pure experimental data and even allow practical extrapolation for new dermal diffusion methodologies. However, they grasp a complex variety of theories and assumptions that allocate their use for specific situations. Models based on Fick's First Law found better use in contexts where scaled particle theory Models would be extensive in time-span but the reciprocal is also true, as context of transdermal diffusion of particular active compounds changes. This article reviews extensively the various theoretical methodologies for studying dermic diffusion in the rate limiting dermic barrier, the stratum corneum, and systematizes its characteristics, their proper context of application, advantages and limitations, as well as future perspectives.

Supporting real-time parallel task models with work-stealing

Dynamic parallel scheduling using work-stealing has gained popularity in academia and industry for its good performance, ease of implementation and theoretical bounds on space and time. Cores treat their own double-ended queues (deques) as a stack, pushing and popping threads from the bottom, but treat the deque of another randomly selected busy core as a queue, stealing threads only from the top, whenever they are idle. However, this standard approach cannot be directly applied to real-time systems, where the importance of parallelising tasks is increasing due to the limitations of multiprocessor scheduling theory regarding parallelism. Using one deque per core is obviously a source of priority inversion since high priority tasks may eventually be enqueued after lower priority tasks, possibly leading to deadline misses as in this case the lower priority tasks are the candidates when a stealing operation occurs. Our proposal is to replace the single non-priority deque of work-stealing with ordered per-processor priority deques of ready threads. The scheduling algorithm starts with a single deque per-core, but unlike traditional work-stealing, the total number of deques in the system may now exceed the number of processors. Instead of stealing randomly, cores steal from the highest priority deque.

Application of integer and fractional models in electrochemical systems

This paper describes the use of integer and fractional electrical elements, for modelling two electrochemical systems. A first type of system consists of botanical elements and a second type is implemented by electrolyte processes with fractal electrodes. Experimental results are analyzed in the frequency domain, and the pros and cons of adopting fractional-order electrical components for modelling these systems are compared.

Hybrid adaptive control of a dragonfly model

Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive (HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive (DA) method in terms of faster and improved tracking and parameter convergence.