Representations of gender in the writings of St. Francis Xavier: an interdisciplinary approach

Francis Xavier’s Letters and Writings are eloquent narratives of a journey that absorbed the Saint’s entire life. His experiences and idiosyncrasies, values and categorizations are presented in a clear literate discourse. The missionary is rarely neutral in his opinions as he sustains his unmistakable and omnipresent objective: the conversion of peoples and the expansion of the Society of Jesus. Parallel with this objective, the reader is introduced to the individuals that Xavier meets or that he summons in his epistolary discourse. Letters and Writings presents us with a structured narrative peopled by all those who are subject to and objects of Xavier’s apostolic mission, by helpful and unhelpful persons of influence, and by leading and secondary actors. What is then the position of women, in the collective sense as well as in the individual sense, in the travels and goals that are the centre of Xavier’s Letters and Writings? What is the role of women, that secondary and suppressed term in the man/woman binomial, a dichotomy similar to the civilized/savage and European/native binomials that punctuate Xavier’s narratives and the historic context of his letters? Women are not absent from his writings, but it would be naïve to argue in favour of the author’s misogyny as much as of his “profound knowledge of the female heart”, to quote from Paulo Durão in "Women in the Letters of Saint Francis Xavier" (1952), the only paper on this subject published so far. We denote four great categories of women in the Letters and Writings: European Women, Converted Women, Women Who Profess another Religion, and Women as the Agents and Objects of Sin, the latter of which traverses the other three categories. They all depend on the context, circumstances and judgements of value that the author chooses to highlight and articulate.

Folk culture and political power: practices and representations of moliceiro culture in Portugal, cultural sociology

This article analyses the painted panels of the moliceiro boat, a traditional working boat of the Ria de Aveiro region of Portugal. The article examines how the painted panels have been invented and reinvented over time. The boat and its panels are contextualized both within the changing socio-economic conditions of the Ria de Aveiro region, and the changing socio-political conditions of Portugal throughout the 20th century and until the present day. The article historically analyses the social significance of ‘moliceiro culture’, examining in particular the power relations it expresses and its ambiguous past and present relationships with the political and the economic powers of the Portuguese state. The article unpacks some of the complexity of the relations that have pertained between public and private, local and national, folk culture and ‘art’, and popular and institutional in the Ria de Aveiro region in particular, and Portugal more generally.

A Lady's visit to Manilla and Japan: intercultural representations on a journey to the east

Numa primeira abordagem a A Lady’s Visit to Manilla and Japan (1863), de Anna D’Almeida, os leitores não deverão esperar encontrar a narrativa de uma experiência que poderia ter sido produzida por um desses “Etonnants voyageurs! Quelles nobles histoires / Nous lisons dans vos yeux profonds comme les mers!”, citando o último poema de Les Fleurs du Mal de Baudelaire. Nem deverão esperar ser confrontados com o relato superficial de uma turista indolente sobre a diversão convencional ou o previsível choque moral experimentados durante as várias etapas do seu grand tour pessoal, tão em voga, e que são característicos deste tipo de literatura, particularmente popular no campo emergente do turismo do final do século xix. Neste artigo, proponho-me analisar a escrita feminina occidental no contexto dos encontros culturais, mais precisamente, as imagens que uma viajante ocidental do século xix cria a partir da sua breve exposição a vários espaços e práticas da Ásia. A família D’Almeida viajou pelo Extremo Oriente entre Março e Julho de 1862. O título A Lady’s Visit to Manilla and Japan induz em erro, pois a narrativa começa em Singapura e termina em Hong Kong, mas a família visitou também Macau, Xangai, Nagasáqui, Yokohama, Xiamen (Hokkien) e Cantão, entre outros lugares, atestando assim o profundo desejo dos D’Almeida de explorar in loco todas as potencialidades dos países visitados Neste estudo tenciono demonstrar as complexidades que existem dentro de / entre as histórias, experiências e actividades interculturais de mulheres, e como estas alargam o âmbito do estudo dos sistemas sociais e culturais. Ao examinar as diferenças e semelhanças de género, podemos elaborar construções teóricas que analisam as variações entre mulheres; como elas são influenciadas pela classe, raça, etnia e religião; e como estas moldam a forma como entendemos a posição da mulher na cultura e na sociedade. O preconceito de classe da elite ocidental considera a mulher não-ocidental como sendo ‘a outra’, alguém que representa aquilo que o escritor ocasional não é. A questão da representação feminina das suas congéneres como ‘mulheres-outras’, com base numa ampla variedade de diferenças, é definitivamente um desafio para os estudos interculturais e de género.

Dynamic artificial neural network for electricity market prices forecast

This paper presents an artificial neural network applied to the forecasting of electricity market prices, with the special feature of being dynamic. The dynamism is verified at two different levels. The first level is characterized as a re-training of the network in every iteration, so that the artificial neural network can able to consider the most recent data at all times, and constantly adapt itself to the most recent happenings. The second level considers the adaptation of the neural network’s execution time depending on the circumstances of its use. The execution time adaptation is performed through the automatic adjustment of the amount of data considered for training the network. This is an advantageous and indispensable feature for this neural network’s integration in ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to the market negotiating players of MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

Representations of Portugal in Herman Hesse

The aim of my research is to answer the question: How is Portugal seen by non-Portuguese fictionists? The main reason why I chose this research line is the following: Portuguese essayists like Eduardo Lourenço and José Gil (2005) focus their attention on the image or representation of Portugal as conceived by the Portuguese; indeed there is a tendency in Portuguese cultural studies (and, to a certain extent, also in Portuguese philosophical studies) to focus on studying the so-called ‗portugalidade‘ (portugueseness), i.e., the essence of being Portuguese. In my view, the problem with the studies I have been referring to is that everything is self-referential, and if ‗portugueseness‘ is an issue, then it might be useful, when dealing with it, to separate subject from object of observation. That is the reason why we, in the CEI (Centro de Estudos Interculturais), decided to start this research line, which is an inversion in the current tendency of the studies about ‗portugueseness‘: instead of studying the image or representation of Portugal by the Portuguese, my task is to study the image or representation of Portugal by the non-Portuguese, in this case, in non-Portuguese fiction. For the present paper I selected three writers of the 20th century: the German Hermann Hesse and the North-Americans Philip Roth and Paul Auster

On the issue of representations

This paper aims at revisiting the concept of ‗representation‘, in order to discuss matters like truth value and the cultural and ideological importance of representations.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Neural networks for condition monitoring of wind turbines gearbox

Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Multilayer Perceptron Neural Networks Training Through Charged System Search and its Application for Non-Technical Losses Detection

The non-technical loss is not a problem with trivial solution or regional character and its minimization represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. In this paper, we show how to improve the training phase of a neural network-based classifier using a recently proposed meta-heuristic technique called Charged System Search, which is based on the interactions between electrically charged particles. The experiments were carried out in the context of non-technical loss in power distribution systems in a dataset obtained from a Brazilian electrical power company, and have demonstrated the robustness of the proposed technique against with several others natureinspired optimization techniques for training neural networks. Thus, it is possible to improve some applications on Smart Grids.

Metalearner based on Dynamic Neural Network for Strategic Bidding in electricity Markets

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.

Solar Intensity Forecasting using Artificial Neural Networks and Support Vector Machines

This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.