Avaliação do desempenho de fundos de investimento de ouro nos EUA: influência dos diferentes regimes de mercado na seletividade e market-timing

Dissertação de mestrado em Finanças

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

Kinematic constraint equations

This chapter presents a general methodology for the formulation of the kinematic constraint equations at position, velocity and acceleration levels. Also a brief characterization of the different type of constraints is offered, namely the holonomic and nonholonomic constraints. The kinematic constraints described here are formulated using generalized coordinates. The chapter ends with a general approach to deal with the kinematic analysis of multibody systems.

Childhood history of abuse and child abuse potential: the role of parent’s gender and timing of childhood abuse

It has been suggested that being physically abused leads to someone becoming a perpetrator of abuse which could be associated to parents' gender, timing of the physical abuse and specific socio-demographic variables. This study aims to investigate the role the parents' gender, timing of childhood abuse and socio-demographic variables on the relationship between parents' history of childhood physical abuse and current risk for children. The sample consisted of 920 parents (414 fathers, 506 mothers) from the Portuguese National Representative Study of Psychosocial Context of Child Abuse and Neglect who completed the Childhood History Questionnaire and the Child Abuse Potential Inventory. The results showed that fathers had lower current potential risk of becoming physical abuse perpetrators with their children than mothers although they did not differed in their physical victimization history. Moreover, the risk was higher in parents (both genders) with continuous history of victimization than in parents without victimization. Prediction models showed that for fathers and mothers separately similar socio-demographic variables (family income, number of children at home, employment status and marital status) predicted the potential risk of becoming physical abuses perpetrators. Nevertheless, the timing of victimization was different for fathers (before 13 years old) and mothers (after 13 years old). Then our study targets specific variables (timing of physical abuse, parents' gender and specific socio-demographic variables), which may enable professionals to select groups of parents at greater need of participating in abuse prevention programs.