Parasites that change predator or prey behaviour can have keystone effects on community composition

Parasites play pivotal roles in structuring communities, often via indirect interactions with non-host species. These effects can be density-mediated (through mortality) or trait-mediated (behavioural, physiological and developmental), and may be crucial to population interactions, including biological invasions. For instance, parasitism can alter intraguild predation (IGP) between native and invasive crustaceans, reversing invasion outcomes. Here, we use mathematical models to examine how parasite-induced trait changes influence the population dynamics of hosts that interact via IGP. We show that trait-mediated indirect interactions impart keystone effects, promoting or inhibiting host coexistence. Parasites can thus have strong ecological impacts, even if they have negligible virulence, underscoring the need to consider trait-mediated effects when predicting effects of parasites on community structure in general and biological invasions in particular.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

In Vitro Release from Reverse Poloxamine/alpha-Cyclodextrin Matrices: Modelling and Comparison of Dissolution Profiles

Gels obtained by complexation of octablock star polyethylene oxide/polypropylene oxide copolymers (Tetronic 90R4) with -cyclodextrin (-CD) were evaluated as matrices for drug release. Both molecules are biocompatible so they can be potentially applied to drug delivery systems. Two different types of matrices of Tetronic 90R4 and -CD were evaluated: gels and tablets. These gels are capable to gelifying in situ and show sustained erosion kinetics in aqueous media. Tablets were prepared by freeze-drying and comprising the gels. Using these two different matrices, the release of two model molecules, L-tryptophan (Trp), and a protein, bovine serum albumin (BSA), was evaluated. The release profiles of these molecules from gels and tablets prove that they are suitable for sustained delivery. Mathematical models were applied to the release curves from tablets to elucidate the drug delivery mechanism. Good correlations were found for the fittings of the release curves to different equations. The results point that the release of Trp from different tablets is always governed by Fickian diffusion, whereas the release of BSA is governed by a combination of diffusion and tablet erosion. 

Release of β-galactosidase from poloxamine/α-cyclodextrin hydrogels

All mammals lose their ability to produce lactase (β-galactosidase), the enzyme that cleaves lactose into galactose and glucose, after weaning. The prevalence of lactase deficiency (LD) spans from 2 to 15% among northern Europeans, to nearly 100% among Asians. Following lactose consumption, people with LD often experience gastrointestinal symptoms such as abdominal pain, bowel distension, cramps and flatulence, or even systemic problems such as headache, loss of concentration and muscle pain. These symptoms vary depending on the amount of lactose ingested, type of food and degree of intolerance. Although those affected can avoid the uptake of dairy products, in doing so, they lose a readily available source of calcium and protein. In this work, gels obtained by complexation of Tetronic 90R4 with α-cyclodextrin loaded with β-galactosidase are proposed as a way to administer the enzyme immediately before or with the lactose-containing meal. Both molecules are biocompatible, can form gels in situ, and show sustained erosion kinetics in aqueous media. The complex was characterized by FTIR that evidenced an inclusion complex between the polyethylene oxide block and α-cyclodextrin. The release profiles of β-galactosidase from two different matrices (gels and tablets) of the in situ hydrogels have been obtained. The influence of the percentage of Tetronic in media of different pH was evaluated. No differences were observed regarding the release rate from the gel matrices at pH 6 (t50 = 105 min). However, in the case of the tablets, the kinetics were faster and they released a greater amount of 90R4 (25%, t50 = 40–50 min). Also, the amount of enzyme released was higher for mixtures with 25% Tetronic. Using suitable mathematical models, the corresponding kinetic parameters have been calculated. In all cases, the release data fit quite well to the Peppas–Sahlin model equation, indicating that the release of β-galactosidase is governed by a combination of diffusion and erosion processes. It has been observed that the diffusion mechanism prevails over erosion during the first 50 minutes, followed by continued release of the enzyme due to the disintegration of the matrix.

A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells

Mathematical models are useful tools for simulation, evaluation, optimal operation and control of solar cells and proton exchange membrane fuel cells (PEMFCs). To identify the model parameters of these two type of cells efficiently, a biogeography-based optimization algorithm with mutation strategies (BBO-M) is proposed. The BBO-M uses the structure of biogeography-based optimization algorithm (BBO), and both the mutation motivated from the differential evolution (DE) algorithm and the chaos theory are incorporated into the BBO structure for improving the global searching capability of the algorithm. Numerical experiments have been conducted on ten benchmark functions with 50 dimensions, and the results show that BBO-M can produce solutions of high quality and has fast convergence rate. Then, the proposed BBO-M is applied to the model parameter estimation of the two type of cells. The experimental results clearly demonstrate the power of the proposed BBO-M in estimating model parameters of both solar and fuel cells.

Whole Genome Sequencing Reveals Local Transmission Patterns of Mycobacterium bovis in Sympatric Cattle and Badger Populations

Whole genome sequencing (WGS) technology holds great promise as a tool for the forensic epidemiology of bacterial pathogens. It is likely to be particularly useful for studying the transmission dynamics of an observed epidemic involving a largely unsampled 'reservoir' host, as for bovine tuberculosis (bTB) in British and Irish cattle and badgers. BTB is caused by Mycobacterium bovis, a member of the M. tuberculosis complex that also includes the aetiological agent for human TB. In this study, we identified a spatio-temporally linked group of 26 cattle and 4 badgers infected with the same Variable Number Tandem Repeat (VNTR) type of M. bovis. Single-nucleotide polymorphisms (SNPs) between sequences identified differences that were consistent with bacterial lineages being persistent on or near farms for several years, despite multiple clear whole herd tests in the interim. Comparing WGS data to mathematical models showed good correlations between genetic divergence and spatial distance, but poor correspondence to the network of cattle movements or within-herd contacts. Badger isolates showed between zero and four SNP differences from the nearest cattle isolate, providing evidence for recent transmissions between the two hosts. This is the first direct genetic evidence of M. bovis persistence on farms over multiple outbreaks with a continued, ongoing interaction with local badgers. However, despite unprecedented resolution, directionality of transmission cannot be inferred at this stage. Despite the often notoriously long timescales between time of infection and time of sampling for TB, our results suggest that WGS data alone can provide insights into TB epidemiology even where detailed contact data are not available, and that more extensive sampling and analysis will allow for quantification of the extent and direction of transmission between cattle and badgers. © 2012 Biek et al.

Nanofluids development and characterization for heat exchanging intensification

A desmaterialização da economia é um dos caminhos para a promoção do desenvolvimento sustentável na medida em que elimina ou reduz a utilização de recursos naturais, fazendo mais com menos. A intensificação dos processos tecnológicos é uma forma de desmaterializar a economia. Sistemas mais compactos e mais eficientes consomem menos recursos. No caso concreto dos sistemas envolvendo processo de troca de calor, a intensificação resulta na redução da área de permuta e da quantidade de fluido de trabalho, o que para além de outra vantagem que possa apresentar decorrentes da miniaturização, é um contributo inegável para a sustentabilidade da sociedade através do desenvolvimento científico e tecnológico. O desenvolvimento de nanofluidos surge no sentido de dar resposta a estes tipo de desafios da sociedade moderna, contribuindo para a inovação de produtos e sistemas, dando resposta a problemas colocados ao nível das ciências de base. A literatura é unânime na identificação do seu potencial como fluidos de permuta, dada a sua elevada condutividade, no entanto a falta de rigor subjacente às técnicas de preparação dos mesmos, assim como de um conhecimento sistemático das suas propriedades físicas suportado por modelos físico-matemáticos devidamente validados levam a que a operacionalização industrial esteja longe de ser concretizável. Neste trabalho, estudou-se de forma sistemática a condutividade térmica de nanofluidos de base aquosa aditivados com nanotubos de carbono, tendo em vista a identificação dos mecanismos físicos responsáveis pela condução de calor no fluido e o desenvolvimento de um modelo geral que permita com segurança determinar esta propriedade com o rigor requerido ao nível da engenharia. Para o efeito apresentam-se métodos para uma preparação rigorosa e reprodutível deste tipo de nanofluido assim como das metodologias consideradas mais importantes para a aferição da sua estabilidade, assegurando deste modo o rigor da técnica da sua produção. A estabilidade coloidal é estabelecida de forma rigorosa tendo em conta parâmetros quantificáveis como a ausência de aglomeração, a separação de fases e a deterioração da morfologia das nanopartículas. Uma vez assegurado o método de preparação dos nanofluídos, realizou-se uma análise paramétrica conducente a uma base de dados obtidos experimentalmente que inclui a visão central e globalizante da influência relativa dos diferentes fatores de controlo com impacto nas propriedades termofísicas. De entre as propriedades termofísicas, este estudo deu particular ênfase à condutividade térmica, sendo os fatores de controlo selecionados os seguintes: fluido base, temperatura, tamanho da partícula e concentração de nanopartículas. Experimentalmente, verificou-se que de entre os fatores de controlo estudados, os que maior influência detêm sobre a condutividade térmica do nanofluido, são o tamanho e concentração das nanopartículas. Com a segurança conferida por uma base de dados sólida e com o conhecimento acerca da contribuição relativa de cada fator de controlo no processo de transferência de calor, desenvolveu-se e validou-se um modelo físico-matemático com um caracter generalista, que permitirá determinar com segurança a condutividade térmica de nanofluidos.

Aplication of a morphodinamic process based model in long-term climate change studies

Climate changes are foreseen to produce a large impact in the morphology of estuaries and coastal systems. The morphology changes will subsequently drive changes in the biologic compartments of the systems and ultimately in their ecosystems. Sea level rise is one of the main factors controlling these changes. Morphologic changes can be better understood with the use of long term morphodynamic mathematical models.

Efeito do sombreamento nos painéis fotovoltaicos

Trabalho Final para obtenção do grau Mestre em Engenharia Electrotécnica

Transformador para fonte de alta-tensão contínua

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Estratégias de investimento em mercados liberalizados de energia elétrica

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Energia

Projeto de um conversor eletrónico para utilização num sistema eólico de produção de energia

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica no Ramo de Automação e Electrónica Industrial

Soil sampling design and sampling techniques for soil properties monitoring – common difficulties related to forest soils

Mathematical models and statistical analysis are key instruments in soil science scientific research as they can describe and/or predict the current state of a soil system. These tools allow us to explore the behavior of soil related processes and properties as well as to generate new hypotheses for future experimentation. A good model and analysis of soil properties variations, that permit us to extract suitable conclusions and estimating spatially correlated variables at unsampled locations, is clearly dependent on the amount and quality of data and of the robustness techniques and estimators. On the other hand, the quality of data is obviously dependent from a competent data collection procedure and from a capable laboratory analytical work. Following the standard soil sampling protocols available, soil samples should be collected according to key points such as a convenient spatial scale, landscape homogeneity (or non-homogeneity), land color, soil texture, land slope, land solar exposition. Obtaining good quality data from forest soils is predictably expensive as it is labor intensive and demands many manpower and equipment both in field work and in laboratory analysis. Also, the sampling collection scheme that should be used on a data collection procedure in forest field is not simple to design as the sampling strategies chosen are strongly dependent on soil taxonomy. In fact, a sampling grid will not be able to be followed if rocks at the predicted collecting depth are found, or no soil at all is found, or large trees bar the soil collection. Considering this, a proficient design of a soil data sampling campaign in forest field is not always a simple process and sometimes represents a truly huge challenge. In this work, we present some difficulties that have occurred during two experiments on forest soil that were conducted in order to study the spatial variation of some soil physical-chemical properties. Two different sampling protocols were considered for monitoring two types of forest soils located in NW Portugal: umbric regosol and lithosol. Two different equipments for sampling collection were also used: a manual auger and a shovel. Both scenarios were analyzed and the results achieved have allowed us to consider that monitoring forest soil in order to do some mathematical and statistical investigations needs a sampling procedure to data collection compatible to established protocols but a pre-defined grid assumption often fail when the variability of the soil property is not uniform in space. In this case, sampling grid should be conveniently adapted from one part of the landscape to another and this fact should be taken into consideration of a mathematical procedure.

Aplicação de um modelo de programação linear inteira mista (PLIM) na expansão da rede de distribuição de energia elétrica em Angola

Em Angola, apenas cerca de 30% da população tem acesso à energia elétrica, nível que decresce para valores inferiores a 10% em zonas rurais mais remotas. Este problema é agravado pelo facto de, na maioria dos casos, as infraestruturas existentes se encontrarem danificadas ou não acompanharem o desenvolvimento da região. Em particular na capital angolana, Luanda que, sendo a menor província de Angola, é a que regista atualmente a maior densidade populacional. Com uma população de cerca de 5 milhões de habitantes, não só há frequentemente problemas relacionados com a falha do fornecimento de energia elétrica como há ainda uma percentagem considerável de municípios onde a rede elétrica ainda nem sequer chegou. O governo de Angola, no seu esforço de crescimento e aproveitamento das suas enormes potencialidades, definiu o setor energético como um dos fatores críticos para o desenvolvimento sustentável do país, tendo assumido que este é um dos eixos prioritários até 2016. Existem objetivos claros quanto à reabilitação e expansão das infraestruturas do setor elétrico, aumentando a capacidade instalada do país e criando uma rede nacional adequada, com o intuito não só de melhorar a qualidade e fiabilidade da rede já existente como de a aumentar. Este trabalho de dissertação consistiu no levantamento de dados reais relativamente à rede de distribuição de energia elétrica de Luanda, na análise e planeamento do que é mais premente fazer relativamente à sua expansão, na escolha dos locais onde é viável localizar novas subestações, na modelação adequada do problema real e na proposta de uma solução ótima para a expansão da rede existente. Depois de analisados diferentes modelos matemáticos aplicados ao problema de expansão de redes de distribuição de energia elétrica encontrados na literatura, optou-se por um modelo de programação linear inteira mista (PLIM) que se mostrou adequado. Desenvolvido o modelo do problema, o mesmo foi resolvido por recurso a software de otimização Analytic Solver e CPLEX. Como forma de validação dos resultados obtidos, foi implementada a solução de rede no simulador PowerWorld 8.0 OPF, software este que permite a simulação da operação do sistema de trânsito de potências.

Effects of treatment, awareness and condom use in a coinfection model for HIV and HCV in MSM

We develop a new a coinfection model for hepatitis C virus (HCV) and the human immunodeficiency virus (HIV). We consider treatment for both diseases, screening, unawareness and awareness of HIV infection, and the use of condoms. We study the local stability of the disease-free equilibria for the full model and for the two submodels (HCV only and HIV only submodels). We sketch bifurcation diagrams for different parameters, such as the probabilities that a contact will result in a HIV or an HCV infection. We present numerical simulations of the full model where the HIV, HCV and double endemic equilibria can be observed. We also show numerically the qualitative changes of the dynamical behavior of the full model for variation of relevant parameters. We extrapolate the results from the model for actual measures that could be implemented in order to reduce the number of infected individuals.