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Mutations in the hotspot ligand-binding domain of the estrogen receptor (ER) gene ESR1 have recently been recognized as mechanisms of endocrine resistance in endocrine receptor-positive metastatic breast cancer (MBC). Accumulating data suggest these mutations develop under the selective pressure of endocrine treatments, and are infrequent in untreated ER-positive breast cancers. In vitro studies show that these mutations confer ligand-independent activity, resistance to estrogen deprivation, and relative resistance to tamoxifen and fulvestrant. Post-hoc retrospective and prospective analyses of ESR1 mutations in patients with MBC have consistently found that these mutations are markers of poor prognosis and predict resistance to aromatase inhibitors (AIs). These results warrant further investigation and prospective validation in dedicated studies. Moreover, studies are ongoing to clarify the activity of novel drugs in the context of metastatic endocrine resistant luminal breast cancer harboring ESR1 mutations. In this review, we summarize the pre-clinical and clinical findings defining the characteristics of ESR1 mutant breast cancer, and highlight the potential clinical developments in this field.

Nos anos 1960 e no início dos anos 1970, Portugal testemunhou um dos maiores movimentos populacionais de saída do país. Cerca de 700 000 portugueses chegaram a França nesses anos[1]. Nos anos onde esse fluxo foi mais intenso, mais de dois terços dessas pessoas saíram do país clandestinamente, cuja viagem ficou conhecida pelo nome o “Salto”, perigo do trajeto e pelas más condições de alojamento nos bidonvilles às portas de Paris. Ainda assim a inserção no mercado de trabalho francês nesse período foi facilitada pela conjuntura socioeconómica favorável da França, encontrávamo-nos então no auge dos chamados “Trinta Gloriosos”. Segundo alguns testemunhos de emigrantes chegados a França nesses anos [2], recrutadores com propostas de trabalho esperavam os portugueses na fronteira logo que estes pisavam território francês. info:eu-repo/semantics/publishedVersion

In this paper, we propose an improved version of descent direction-based multiobjective algorithm (DDMOA2). Significant modifications are introduced comparing with the originally proposed algorithm (DDMOA). DDMOA2 does not rely on the concept of Pareto dominance instead a scalarizing fitness assignment is used. Now, all population members have a probability of creating offspring. We define the concept of search matrix and population leaders for which local search is used to find descent directions. Moreover to improve efficiency, descent directions are found only for two randomly chosen objectives. The experimental study shows that the proposed approach outperforms the previous version of the algorithm with respect to the convergence to the Pareto optimal front and the diversity among obtained solutions, especially on three-objective test problems. At the same time, it provides highly competitive results with respect to other state-ofthe- art multiobjective optimizers.

Hybridization of local search based algorithms with evolutionary algorithms is still an under-explored research area in multiobjective optimization. In this paper, we propose a new multiobjective algorithm based on a local search method. The main idea is to generate new non-dominated solutions by adding to a parent solution a linear combination of descent directions of the objective functions. Additionally, a strategy based on subpopulations is implemented to avoid the direct computation of descent directions for the entire population. The evaluation of the proposed algorithm is performed on a set of benchmark test problems allowing a comparison with the most representative stateof- the-art multiobjective algorithms. The results show that the proposed approach is highly competitive in terms of the quality of non-dominated solutions, robustness and the computational efficiency.

In general, parameters in multi-objective optimization are assumed as deterministic with no uncertainty. However, uncertainty in the parameters can affect both variable and objective spaces. The corresponding Pareto optimal fronts, resulting from the disturbed problem, define a cloud of curves. In this work, the main objective is to study the resulting cloud of curves in order to identify regions of more robustness and, therefore, to assist the decision making process. Preliminary results, for a very limited set of problems, show that the resulting cloud of curves exhibits regions of less variation, which are, therefore, more robust to parameter uncertainty., The authors would like to thank FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) that supported in part this work.

Background: The significance of the association between the human papillomavirus (HPV) and other sexually transmitted infections in the development of cervical, penile or anal neoplasias has been investigated, and the more consistent data have pointed to an association with Chlamydia trachomatis. In Portugal, the lack of information on STI precludes any knowledge on this subject. Objective: To determine CT infection in a group of individuals selected for HPV detection in the major Portuguese STD clinic. Methods: This opportunistic screening comprehended 177 outpatients (148 women, 29 men; age: 16-61 years) suspected of HPV infection (warts, abnormal histology) between 2008 and 2010. Demographic and sexual behaviour data and a full medical history were obtained at enrolment. Genital samples (cervical, vulvar, vaginal, penile or anal) were collected from all the subjects. HPV DNA was detected by CLART HPV2 assay, which allowed the detection of 35 genotypes. CT DNA was detected by Cobas 4800. Results and Discussion: Overall, 84.5% of the individuals had at least one of the infections. Evidencing an excellent correlation with clinical signs, HPV infection was detected in 68.2% of the women and in 75.9% of the men, where CT positivity was 10.1% and 13.8%, respectively. Coinfection was observed in 8.9% of the women and in 13.8% of the men. No correlation with HPV or CT genotypes could be established. HPV infection was more frequent in CT negative (87.1%) than in CT positive women (13.8%), and the same was observed for men (81.8% versus 18.2%). Full results will be presented and discussed. Conclusions: No correlation between HPV-CT coinfection, and clinical signs was observed. However, further long-term studies are needed to elucidate the effects of HPV-CT coinfection in the clinical history of the infected patient, which would greatly contribute towards a better management of patients.

This paper presents a pattern search algorithm and its hybridization with a random descent search for solving bound constrained minimax problems. The herein proposed heuristic pattern search method combines the Hooke and Jeeves (HJ) pattern and exploratory moves with a randomly generated approxi- mate descent direction. Two versions of the heuristic algorithm have been applied to several benchmark minimax problems and compared with the original HJ pat- tern search algorithm.

When modeling an activated sludge system of a wastewater treatment plant (WWTP), several conflicting objectives may arise. The proposed formulation is a highly constrained bi-objective problem where the minimization of the investment and operation costs and the maximization of the quality of the effluent are simultaneously optimized. These two conflicting objectives give rise to a set of Pareto optimal solutions, reflecting different compromises between the objectives. Population based algorithms are particularly suitable to tackle multi-objective problems since they can, in principle, find multiple widely different approximations to the Pareto-optimal solutions in a single run. In this work, the formulated problem is solved through an elitist multi-objective genetic algorithm coupled with a constrained tournament technique. Several trade-offs between objectives are obtained through the optimization process. The direct visualization of the trade-offs through a Pareto curve assists the decision maker in the selection of crucial design and operation variables. The experimental results are promising, with physical meaning and highlight the advantages of using a multi-objective approach.

An augmented Lagrangian algorithm is presented to solve a global optimization problem that arises when modeling the activated sludge system in a Wastewater Treatment Plant, attempting to minimize both investment and operation costs. It is a heuristic-based algorithm that uses a genetic algorithm to explore the search space for a global optimum and a pattern search method for the local search refinement. The obtained results have physical meaning and show the effectiveness of the proposed method.

This paper describes a derivative-free method that aims to solve an optimization problem arising from the mathematical formulation of an activated sludge system in which the objective is to minimize the investment and operation costs. The method relies on an augmented Lagrangian technique that uses a pattern search for solving bound constrained subproblems.

Tese de Doutoramento em Engenharia de Produção de Sistemas, área de Métodos Númericos e Estatísticos, Uma das grandes preocupações actuais prende-se com a preservação do meio ambiente. Em particular, no caso do tratamento de efluentes líquidos domésticos e/ou industriais, cujo impacto ambiental é muito significativo, é conveniente fazer-se uma análise detalhada aos efluentes em causa e aos processos de tratamento disponíveis, bem como proceder-se a um estudo económico, de modo a que os custos, à partida muito elevados, possam ser minimizados. Assim, o objectivo desta tese é determinar o desenho óptimo de uma estação de tratamento de águas residuais (ETAR), de tal forma que os custos de investimento e operação sejam minimizados. Os processos envolvidos, em particular os relacionados com o tratamento secundário - um sistema de lamas activadas, foram modelados de modo a serem determinadas as equações matemáticas que correspondem ao problema de optimização. Foram obtidas algumas funções custo a partir de dados reais fornecidos por uma empresa construtora de ETARs em Portugal. O processo de modelação centrou-se no tanque arejador e no sedimentador secundário, tendo este sido objecto de um estudo mais detalhado. Para além das normas ATV e do modelo da dupla exponencial (DE), foi analisado um modelo combinado destes dois e testado numa ETAR real que está a ser instalada no norte interior de Portugal. Os resultados obtidos são encorajadores, tendo-se verificado que este modelo não só origina um desenho equilibrado como é mais robusto que os outros dois, se usados em separado, quando testados por simulação. Para além do sistema de lamas activadas, incluiu-se ainda no procedimento de optimização o tratamento e deposição final das lamas em excesso. Foi analisada a contribuição deste tratamento para o custo total da ETAR. Na presença de funções não diferenciáveis, que foram encontradas nas equações matemáticas do modelo DE, é mais adequado usar-se uma técnica de optimização que não requer o uso de derivadas. Por este motivo implementou-se e testou-se um algoritmo de pesquisa em padrão generalizada. Este algoritmo é baseado numa função Lagrangeana aumentada de modo a obter-se uma solução que satisfaça as restrições de igualdade e desigualdade do problema. Os resultados experimentais são bastante animadores e originam desenhos de ETARs bastante atractivos em termos económicos. Nesta tese conduz-se um procedimento de optimização, que é pouco comum no desenho de ETARs. Este procedimento inclui uma função objectivo - a função custo obtida através de dados reais - e restrições provenientes da modelação do sistema de lamas activadas. Propõe-se um modelo inovador para o sedimentador secundário que permite ultrapassar as limitações dos modelos tradicionais ATV e DE. No entanto, devido à presença de funções não diferenciáveis provenientes do modelo DE, desenvolveu-se um novo algoritmo de optimização de pesquisa em padrão, adaptado a problemas com todo o tipo de restrições, que não recorre a derivadas. Este algoritmo foi codificado na linguagem de programação C e deu origem a um solver que inclui uma interface de ligação ao AMPL., One of the main concerns nowadays is environmental preservation. In particular, for domestic and/or industrial wastewater treatment, with significant environmental impact, a careful analysis on the corresponding effluents and of the available treatment processes, as well as an economic study should be conducted, so that the associated high costs can be minimized. Thus, the aim of this thesis is to determine the optimal design of a wastewater treatment plant (WWTP) in a way that the investment and operational costs are minimized. The involved processes, in particular those related with the secondary treatment - an activated sludge system - were modelled in order to obtain the mathematical equations of the corresponding optimization problem. Some cost functions were obtained using real data collected from a WWTP company builder in Portugal. The modelling process took into account the aeration tank and the secondary settler, being the latter subject to a detailed study. Besides the ATV design procedure and the double exponentional model (DE), a combination of these two models was analized and tested in a real WWTP being installed in the interior north of Portugal. The obtained results are encouraging, and it was observed that this model not only gives an equilibrated design, as it is more robust than the other two used separately, when tested by simulation. Besides the activated sludge system, the treatment and final disposal of the wasted sludge was also included in the optimization procedure. Its contribution to the WWTP total cost was analized. In the presence of non-differentiable functions as encountered in the mathematical equations involved in the DE model, a derivative-free optimization technique is the most appropriate. So, a generalized pattern search algorithm was implemented and tested. This algorithm relies on an augmented Lagrangian function in order to obtain a solution that satisfies the equality and inequality constraints of the problem. The experimental results are very stimulating and give economically attractive WWTP designs. In this thesis an optimization procedure, which is not very common in WWTP designs is conducted. This procedure includes an objective function - the cost function obtained with real data - and constraints originating from the activated sludge system modelling. An innovative model for the secondary settler that is able to overcome the disadvantages of the two traditional models ATV and DE is proposed. However, due to the non-differentiable equations present in the DE model, a new pattern search optimization algorithm, adapted to all types of constraints, which does not require any derivative information, is developed. This algorithm was coded in the C programming language and originated a solver that includes an interface to AMPL.

This paper aims to analyze the cost contribution of a simple wasted sludge process in the WWTP design total cost. The plant design relies on a combined ATV and double exponential model to describe the secondary settler as well as on a simple sludge treatment based on dewatering followed by deposition in landfills. The experiments carried out with three small WWTPs in design show that the chosen wasted biosolids treatment is responsible for 10 to 14% of the total costs. However significantly higher values are obtained when the secondary settler is described by an ATV model., (undefined)

This paper describes a derivative-free method to solve a non-linear constrained optimization problem that arises from the mathematical formulation of an activated sludge system of a wastewater treatment plant (WWTP), in which the objective is to minimize the investment and operation costs. The method relies on an augmented Lagrangian function to penalize infeasible solutions and uses the original Hooke and Jeeves pattern search method for solving bound constrained subproblems. The experimental results are very promising and give economically attractive WWTP designs.

In the sequence of the work done with a combined ATV and double exponential model to describe the secondary settler concerning the optimal design of a wastewater treatment plant (WWTP), a simple sludge treatment based on dewatering followed by deposition in landfills is now included in the system. Power consumption, transport and deposition of the sludge are involved in the operation cost of the sludge treatment. This work aims to evaluate the contribution of this cost in the WWTP design total cost. The experiments carried out with three WWTPs in design show that the considered wasted biosolids treatment does not affect the design although is responsible for 10 to 14% of the total costs.

The aim of this paper is to assess the goodness of the solutions obtained when minimizing the investment and operation costs of a wastewater treatment plant considering three secondary settler models. The obtained optimal designs are introduced in the GPS-X simulator and stress conditions are imposed in order to evaluate the robustness of the solutions. Only the model that combines the ATV design procedure with the double exponential model is able to support the imposed adverse conditions in the sense that the quality of the treated effluent is not compromised., (undefined)

This work focus on the accomplishing of the best model to a secondary settler to use in a minimum cost optimization procedure concerning the construction and operation of a wastewater treatment plant (WWTP). Two traditional models are tested as well as a new model that results from the combination of the other two. The obtained optimal designs are then simulated in order to evaluate the model that provides the best performance.

The aim of this paper is to determine the optimal design and operation of an activated sludge system that is being installed in a small town in the north of Portugal. This process design takes into consideration real data in order to define the objective cost function which includes both investment and operation costs. The collected data were also used to characterize the wastewater in that region. To define the constraints of the optimization problem, we consider very well established models for the aeration tank and the secondary settler, together with the system balances and some system definitions. The highly nonlinear optimization problem was solved through the internet by the SNOPT solver provided by the NEOS Server. We found, for the minimum cost, the optimal design/operation for the above mentioned system in terms of the volume of the aeration tank, air flow needed for the biological sludge, the sedimentation area and the secondary settler depth, to name a few of the involved variables.

Neste artigo apresenta-se um problema de optimização relacionado com um processo biológico de tratamento de águas residuais. Neste problema pretende-se minimizar uma função custo de um sistema de lamas activadas, constituído por um tanque arejador e um sedimentador secundário. A função foi obtida a partir de dados reais e os modelos utilizados foram o ASM1 para as lamas activadas e um ponto de separação simples sem clarificação perfeita para a sedimentação. Utilizou-se o pacote de software LOQO como ferramenta de optimização e o AMPL como linguagem de codificação do problema.

En este trabajo usamos el paquete de software LOQO para optimización de procesos de tratamiento de aguas residuales. Se minimizó una función costo, el volumen del reactor y el caudal de agua para diferentes valores de demanda química de oxígeno y nitrógeno en el efluente., Factor Ambiente

On-line detectors of biofilm - platinum electrodes - were calibrated and validated in the laboratory under defined conditions, using a bacterium known as a good biofilm producer, Pseudomonas fluorescens. The electrochemical technique used was cyclic voltammetry., Instituto de Biotecnologia e Química Fina (IBQF)., Fundação para a Ciência e a Tecnologia (FCT) - PRAXIS XXI/BD/11211/97.