STUDY ON STRUCTURE-ACTIVITY-RELATIONSHIPS OF ORGANIC-COMPOUNDS - 3 NEW TOPOLOGICAL INDEXES AND THEIR APPLICATIONS

In this paper, three new topological indices, A(x1), A(x2), and A(x3), have been developed for use in multivariate analysis in structure-property relationship (SPR) and structure-activity relationship (SAR) studies. Good results have been obtained by using them to predict the physical and chemical properties and biological activities of some organic compounds.

Miniaturization of electromagnetic band gap structures for mobile applications

It is well known that interference of the human body affects the performance of the antennas in mobile phone handsets. In this contribution, we investigate the use of miniaturized metallodielectric electromagnetic band gap (MEBG) structures embedded in the case of a mobile handset as a means of decoupling the antenna from the user's hand. The closely coupled MEBG concept is employed to achieve miniaturization of the order of 15:1. Full wave dispersion relations for planar closely coupled MEBG arrays are presented and are validated experimentally. The performance of a prototype handset with an embedded conformal MEBG is assessed experimentally and is compared to a similar prototype without the MEBG. Reduction in the detuning of the antenna because of the human hand by virtue of the MEBG is demonstrated. Moreover, the efficiency of the handset when loaded with a human hand model is shown to improve when the MEBG is in place. The improvements are attributed to the decoupling of the antenna from the user's hand, which is achieved by means of suppressing the fields in the locality of the hand.

Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow applications with security constraints in distributed data-intensive computing environments and present a novel security constraint model. Several meta-heuristic adaptations to the particle swarm optimization algorithm are introduced to deal with the formulation of efficient schedules. A variable neighborhood particle swarm optimization algorithm is compared with a multi-start particle swarm optimization and multi-start genetic algorithm. Experimental results illustrate that population based meta-heuristics approaches usually provide a good balance between global exploration and local exploitation and their feasibility and effectiveness for scheduling work-flow applications. © 2010 Elsevier Inc. All rights reserved.

Surface Modification of Photoresist SU-8 for Low Autofluorescence and Bioanalytical Applications

This paper reports a surface modification of epoxy-based negative photoresist SU-8 for reducing its autofluorescence while enhancing its biofunctionality. By covalently depositing a thin layer of 20 nm Au nanoparticles (AuNPs) onto the SU-8 surface, we found that the AuNPs-coated SU-8 surface is much less fluorescent than the untreated SU-8. Moreover, DNA probes can easily be immobilized on the Au surface and are thermally stable over a wide range of temperature. These improvements will benefit bioanalytical applications such as DNA hybridization and solid-phase PCR (SP-PCR).

Service composition for biomedical applications

A exigente inovação na área das aplicações biomédicas tem guiado a evolução das tecnologias de informação nas últimas décadas. Os desafios associados a uma gestão, integração, análise e interpretação eficientes dos dados provenientes das mais modernas tecnologias de hardware e software requerem um esforço concertado. Desde hardware para sequenciação de genes a registos electrónicos de paciente, passando por pesquisa de fármacos, a possibilidade de explorar com precisão os dados destes ambientes é vital para a compreensão da saúde humana. Esta tese engloba a discussão e o desenvolvimento de melhores estratégias informáticas para ultrapassar estes desafios, principalmente no contexto da composição de serviços, incluindo técnicas flexíveis de integração de dados, como warehousing ou federação, e técnicas avançadas de interoperabilidade, como serviços web ou LinkedData. A composição de serviços é apresentada como um ideal genérico, direcionado para a integração de dados e para a interoperabilidade de software. Relativamente a esta última, esta investigação debruçou-se sobre o campo da farmacovigilância, no contexto do projeto Europeu EU-ADR. As contribuições para este projeto, um novo standard de interoperabilidade e um motor de execução de workflows, sustentam a sucesso da EU-ADR Web Platform, uma plataforma para realizar estudos avançados de farmacovigilância. No contexto do projeto Europeu GEN2PHEN, esta investigação visou ultrapassar os desafios associados à integração de dados distribuídos e heterogéneos no campo do varíoma humano. Foi criada uma nova solução, WAVe - Web Analyses of the Variome, que fornece uma coleção rica de dados de variação genética através de uma interface Web inovadora e de uma API avançada. O desenvolvimento destas estratégias evidenciou duas oportunidades claras na área de software biomédico: melhorar o processo de implementação de software através do recurso a técnicas de desenvolvimento rápidas e aperfeiçoar a qualidade e disponibilidade dos dados através da adopção do paradigma de web semântica. A plataforma COEUS atravessa as fronteiras de integração e interoperabilidade, fornecendo metodologias para a aquisição e tradução flexíveis de dados, bem como uma camada de serviços interoperáveis para explorar semanticamente os dados agregados. Combinando as técnicas de desenvolvimento rápidas com a riqueza da perspectiva "Semantic Web in a box", a plataforma COEUS é uma aproximação pioneira, permitindo o desenvolvimento da próxima geração de aplicações biomédicas.

Synthesis in the human evolutionary behavioural sciences

Over the last three decades, the application of evolutionary theory to the human sciences has shown remarkable growth. This growth has also been characterised by a ‘splitting’ process, with the emergence of distinct sub-disciplines, most notably: Human Behavioural Ecology (HBE), Evolutionary Psychology (EP) and studies of Cultural Evolution (CE). Multiple applications of evolutionary ideas to the human sciences are undoubtedly a good thing, demonstrating the usefulness of this approach to human affairs. However, this fracture has been associated with considerable tension, a lack of integration, and sometimes outright conflict between researchers. In recent years however, there have been clear signs of hope that a synthesis of the human evolutionary behavioural sciences is underway. Here, we briefly review the history of the debate, both its theoretical and practical causes; then provide evidence that the field is currently becoming more integrated, as the traditional boundaries between sub-disciplines become blurred. This article constitutes the first paper under the new editorship of the Journal of Evolutionary Psychology, which aims to further this integration by explicitly providing a forum for integrated work.

Downstream processing development of enveloped viruses for clinical applications: innovative tools for rational process optimization

Dissertation presented to obtain a Ph.D. degree in Engineering and Technology Sciences, Biotechnology at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

Quantum dots: synthesis, functionalization and bioconjugation for biological applications

Dissertation presented to obtain the Ph.D degree in Engineering Sciences and Technology

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.