Casamentos entre Católicos Romanos e Judeus: desafios de conviver com diferentes tradições religiosas e o de orientar os filhos na sua formação espiritual.

Esta pesquisa tem como objetivo observar o casamento inter-religioso. O encontro de duas culturas religiosas pode e, provavelmente, constituirá fonte de conflito. Os conflitos emergentes podem ocorrer, não por uma visão diferente de mundo, mas essencialmente porque o outro, por ser diferente, ameaça a identidade do indivíduo. Frente à ameaça, é necessário fortalecer a própria identidade. A partir de entrevistas com seis casais em casamentos inter-religiosos, mais especificamente, entre cristãos e judeus, e com filhos com idade entre zero e cinco anos e entre quatorze e vinte e quatro anos de idade, residentes em São Paulo, Capital, pretendi analisar como os casais lidam com os desafios que surgem quando um cônjuge pertence a uma tradição religiosa diferente da do outro. Dentre os desafios, está o de lidar com a educação religiosa ou a formação espiritual de seus filhos. Utilizando-se como referencial a Terapia Sistêmica Familiar, principalmente o trabalho de Paul Watzlawick sobre a comunicação e o de Murray Bowen sobre o funcionamento humano dentro dos sistemas familiares, além de outros referenciais auxiliares para trabalhar a questão intercultural no casamento, pretendi discutir as implicações para a práxis religiosa e oferecer contribuições à clínica psicológica e às ciências da religião. A psicologia necessita repensar sua prática, deixando o preconceito em relação à religião de lado e incluindo essa em seus estudos, de modo a aproximar o discurso e a prática do terapeuta, uma vez que pode tomar consciência de seus próprios valores religiosos quando buscar compreender a religião e a espiritualidade de sua clientela. Por sua vez, as instituições religiosas necessitam refletir sobre sua práxis, de modo a alcançar as famílias que se encontram na periferia das religiões. Famílias que solicitam uma orientação, uma formação religiosa, mas que, sendo inter-religiosas, necessitam ser reconhecidas e respeitadas como tal. Portanto, as igrejas precisam abrir-se, deixar de olhar para dentro de si mesmas e servir ao mundo, mesmo que parte desse mundo nunca venha a se tornar formalmente membro da comunidade.(AU)

Stimuli of varying spatial scale induce gamma activity with distinct temporal characteristics in human visual cortex

Gamma activity to stationary grating stimuli was studied non-invasively using MEG recordings in humans. Using a spatial filtering technique, we localized gamma activity to primary visual cortex. We tested the hypothesis that spatial frequency properties of visual stimuli may be related to the temporal frequency characteristics of the associated cortical responses. We devised a method to assess temporal frequency differences between stimulus-related responses that typically exhibit complex spectral shapes. We applied this methodology to either single-trial (induced) or time-averaged (evoked) responses in four frequency ranges (0-40, 20-60, 40-80 and 60-100 Hz) and two time windows (either the entire duration of stimulus presentation or the first second following stimulus onset). Our results suggest that stimuli of varying spatial frequency induce responses that exhibit significantly different temporal frequency characteristics. These effects were particularly accentuated for induced responses in the classical gamma frequency band (20-60 Hz) analyzed over the entire duration of stimulus presentation. Strikingly, examining the first second of the responses following stimulus onset resulted in significant loss in stimulus specificity, suggesting that late signal components contain functionally relevant information. These findings advocate a functional role of gamma activity in sensory representation. We suggest that stimulus specific frequency characteristics of MEG signals can be mapped to processes of neuronal synchronization within the framework of coupled dynamical systems.

Dynamics of learning with restricted training sets

The dynamics of supervised learning in layered neural networks were studied in the regime where the size of the training set is proportional to the number of inputs. The evolution of macroscopic observables, including the two relevant performance measures can be predicted by using the dynamical replica theory. Three approximation schemes aimed at eliminating the need to solve a functional saddle-point equation at each time step have been derived.

Amplitude response of a unilaterally constrained nonlinear micromechanical resonator

Dynamical systems that involve impacts frequently arise in engineering. This Letter reports a study of such a system at microscale that consists of a nonlinear resonator operating with an unilateral impact. The microresonators were fabricated on silicon-on-insulator wafers by using a one-mask process and then characterised by using the capacitively driving and sensing method. Numerical results concerning the dynamics of this vibro-impact system were verified by the experiments. Bifurcation analysis was used to provide a qualitative scenario of the system steady-state solutions as a function of both the amplitude and the frequency of the external driving sinusoidal voltage. The results show that the amplitude of resonant peak is levelled off owing to the impact effect and that the bandwidth of impacting is dependent upon the nonlinearity and the operating conditions.

Bayesian online algorithms for learning in discrete Hidden Markov Models

We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.

Variational inference for diffusion processes

Diffusion processes are a family of continuous-time continuous-state stochastic processes that are in general only partially observed. The joint estimation of the forcing parameters and the system noise (volatility) in these dynamical systems is a crucial, but non-trivial task, especially when the system is nonlinear and multimodal. We propose a variational treatment of diffusion processes, which allows us to compute type II maximum likelihood estimates of the parameters by simple gradient techniques and which is computationally less demanding than most MCMC approaches. We also show how a cheap estimate of the posterior over the parameters can be constructed based on the variational free energy.

Before and after modelling:risk knowledge management is required

Risk and knowledge are two concepts and components of business management which have so far been studied almost independently. This is especially true where risk management is conceived mainly in financial terms, as, for example, in the banking sector. The banking sector has sophisticated methodologies for managing risk, such as mathematical risk modeling. However. the methodologies for analyzing risk do not explicitly include knowledge management for risk knowledge creation and risk knowledge transfer. Banks are affected by internal and external changes with the consequent accommodation to new business models new regulations and the competition of big players around the world. Thus, banks have different levels of risk appetite and policies in risk management. This paper takes into consideration that business models are changing and that management is looking across the organization to identify the influence of strategic planning, information systems theory, risk management and knowledge management. These disciplines can handle the risks affecting banking that arise from different areas, but only if they work together. This creates a need to view them in an integrated way. This article sees enterprise risk management as a specific application of knowledge in order to control deviation from strategic objectives, shareholders' values and stakeholders' relationships. Before and after a modeling process it necessary to find insights into how the application of knowledge management processes can improve the understanding of risk and the implementation of enterprise risk management. The article presents a propose methodology to contribute to providing a guide for developing risk modeling knowledge and a reduction of knowledge silos, in order to improve the quality and quantity of solutions related to risk inquiries across the organization.