Pliocene-quaternary upwelling in the SoutheasternAtlantic may reflect changes in water mass production

Proceedings of tile 1" R.C.A.N.S. Congress, Lisboa, October 1992

Adaptive learning in agents behaviour: A framework for electricity markets simulation

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

Adaptive Learning in Games: Defining Profiles of Competitor Players

Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

Massive Open Online Course management: learning science and engineering through peer-reviewed projects

Massive Open Online Courses (MOOC) are gaining prominence in transversal teaching-learning strategies. However, there are many issues still debated, namely assessment, recognized largely as a cornerstone in Education. The large number of students involved requires a redefinition of strategies that often use approaches based on tasks or challenging projects. In these conditions and due to this approach, assessment is made through peer-reviewed assignments and quizzes online. The peer-reviewed assignments are often based upon sample answers or topics, which guide the student in the task of evaluating peers. This chapter analyzes the grading and evaluation in MOOCs, especially in science and engineering courses, within the context of education and grading methodologies and discusses possible perspectives to pursue grading quality in massive e-learning courses.

Archaeometallurgical study of pre and protohistoric production remains and artefacts from Southern Portugal

Dissertação para obtenção do Grau de Doutor em Conservação e Restauro, especialidade Ciências da Conservação

Safety function analysis in an industrial production process

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Haptic robot-environment interaction for self-supervised learning in ground mobility

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

Determination of germ tube, phospholipase, and proteinase production by bloodstream isolates of Candida albicans

Introduction Candida albicans is a commensal and opportunistic agent that causes infection in immunocompromised individuals. Several attributes contribute to the virulence and pathogenicity of this yeast, including the production of germ tubes (GTs) and extracellular hydrolytic enzymes, particularly phospholipase and proteinase. This study aimed to investigate GT production and phospholipase and proteinase activities in bloodstream isolates of C. albicans. Methods One hundred fifty-three C. albicans isolates were obtained from blood samples and analyzed for GT, phospholipase, and proteinase production. The assays were performed in duplicate in egg yolk medium containing bovine serum albumin and human serum. Results Detectable amounts of proteinase were produced by 97% of the isolates, and 78% of the isolates produced phospholipase. GTs were produced by 95% of the isolates. A majority of the isolates exhibited low levels of phospholipase production and high levels of proteinase production. Conclusions Bloodstream isolates of C. albicans produce virulence factors such as GT and hydrolytic enzymes that enable them to cause infection under favorable conditions.

Development of a biorefinery–based bioprocess for pigment and lipid production by oleaginous yeasts

Dissertação de mestrado em Bioengenharia

Action of growth regulators on flowering and pod production of soybean cultivar Davis

This research deals with the effects of growth regulators on flowering and pod formation in soybean plant (Glycine max cv. Davis). Under greenhouse conditions, soybean plants were sprayed with 2,3,5-triiodobenzoic acid (TIBA) 20 ppm, Agrostemmin (1g/10 ml/3 l) gibberellic acid (GA) 100 ppm, and (2-chloroethyl) trimethylammonium chloride (CCC) 2,000 ppm. Application of TIBA increased number of flowers. 'Davis' soybean treated with CCC and TIBA presented a tendency to produce a lower number of pods.

Associative learning in wild Anastrepha obliqua females (Diptera, Tephritidae) related to a protein source

The aim of the present study was to determine whether wild adult Anastrepha obliqua (Macquart, 1835) females are able to associate a compound (quinine sulphate - QS) not related to their habitual diet with a protein-enriched food. Females were first fed on diets based on brewer yeast and sucrose containing or not QS. The groups were then allowed to choose between their original diets and a diet with or without QS, depending on the previous treatment, and between a diet based on agar and a diet containing agar and QS. When the nutritional value of the diets was adequate, the females did not show any preference for the diet with or without QS. With respect to the agar diet and the agar + QS diet, females previously fed on a nutritive diet containing QS preferred the diet containing QS, indicating an association between the compound and the nutritional value of the diet. The importance of this behavioral strategy is discussed.

Economic impacts of alternative water policy scenarios in the Spanish production system: an input-output analysis

The objective of this paper is to analyse the economic impacts of alternative water policies implemented in the Spanish production system. The methodology uses two versions of the input-output price model: a competitive formulation and a mark-up formulation. The input-output framework evaluates the impact of water policy measures on production prices, consumption prices, intermediate water demand and private welfare. Our results show that a tax on the water used by sectors considerably reduces the intermediate water demand, and increases the production and consumption prices. On the other hand, according to Jevons' paradox, an improvement in technical efficiency, which leads to a reduction in the water requirements of all sectors and an increase in water production, increases the amount of water consumed. The combination of a tax on water and improved technical efficiency takes the pressure off prices and significantly reduces intermediate water demand. JEL Classification: C67 ; D57 ; Q25. Keywords: Production prices; Consumption prices; Water uses; Water policy; Water taxation.

Influence of local environmental olfactory cues on place learning in rats

The aim of the present study was to assess the influence of local environmental olfactory cues on place learning in rats. We developed a new experimental design allowing the comparison of the use of local olfactory and visual cues in spatial and discrimination learning. We compared the effect of both types of cues on the discrimination of a single food source in an open-field arena. The goal was either in a fixed or in a variable location, and could be indicated by local olfactory and/or visual cues. The local cues enhanced the discrimination of the goal dish, whether it was in a fixed or in a variable location. However, we did not observe any overshadowing of the spatial information by the local olfactory or visual cue. Rats relied primarily on distant visuospatial information to locate the goal, neglecting local information when it was in conflict with the spatial information.

Testing the TASP: An Experimental Investigation of Learning in Games with Unstable Equilibria

We report experiments designed to test between Nash equilibria that are stable and unstable under learning. The “TASP” (Time Average of the Shapley Polygon) gives a precise prediction about what happens when there is divergence from equilibrium under fictitious play like learning processes. We use two 4 x 4 games each with a unique mixed Nash equilibrium; one is stable and one is unstable under learning. Both games are versions of Rock-Paper-Scissors with the addition of a fourth strategy, Dumb. Nash equilibrium places a weight of 1/2 on Dumb in both games, but the TASP places no weight on Dumb when the equilibrium is unstable. We also vary the level of monetary payoffs with higher payoffs predicted to increase instability. We find that the high payoff unstable treatment differs from the others. Frequency of Dumb is lower and play is further from Nash than in the other treatments. That is, we find support for the comparative statics prediction of learning theory, although the frequency of Dumb is substantially greater than zero in the unstable treatments.

When Do We Learn to Cooperate? The Role of Social Learning in Social Dilemmas

In this paper, I look at the interaction between social learning and cooperative behavior. I model this using a social dilemma game with publicly observed sequential actions and asymmetric information about pay offs. I find that some informed agents in this model act, individually and without collusion, to conceal the privately optimal action. Because the privately optimal action is socially costly the behavior of informed agents can lead to a Pareto improvement in a social dilemma. In my model I show that it is possible to get cooperative behavior if information is restricted to a small but non-zero proportion of the population. Moreover, such cooperative behavior occurs in a finite setting where it is public knowledge which agent will act last. The proportion of cooperative agents within the population can be made arbitrarily close to 1 by increasing the finite number of agents playing the game. Finally, I show that under a broad set of conditions that it is a Pareto improvement on a corner value, in the ex-ante welfare sense, for an interior proportion of the population to be informed.