Abstract:
o gerenciamento de riscos em programas de aventura será analisado de maneira sistemática neste trabalho. Os elementos que conformam os padr es de precau o em atividades comerciais de aventura ser o tratados de forma crítica. V árias quest es relacionadas à polêmica do credenciamento e certifica o de programas comerciais de aventura ser o analisadas. Os principais conceitos relativos à seguran a na concep o, no planejamento, no monitoramento e na execu o de programas turísticos de aventura e eventos na natureza ser o abordados. Após a revis o conceitual, será exposto o resultado do estudo dos elementos de gerenciamento de riscos, introduzidos na legisla o que rege a implementa o da política de desenvolvimento do turismo sustentável no Município de Brotas. Risk management in adventure programs has been systematically analyzed within this work. The elements that integrate the standards of care in commercial adventure programming have been critically approached. Different questions related to the debate on accreditation and certification of adventure programs. The main concepts regarding safety during the conception, planning, monitoring, and execution of adventure tourism programs and events in the wild have been also approached. Following this conceptual revision, the result of the study of risk management topics introduced in the legislation related to the policy of sustainable tourism development in Brotas borough will be displayed.

Abstract:
Bayesian probability theory is used as a framework to develop a formalism for the scientific method based on principles of inductive reasoning. The formalism allows for precise definitions of the key concepts in theories of physics and also leads to a well-defined procedure to select one or more theories among a family of (well-defined) candidates by ranking them according to their posterior probability distributions, which result from Bayes's theorem by incorporating to an initial prior the information extracted from a dataset, ultimately defined by experimental evidence. Examples with different levels of complexity are given and three main applications to basic cosmological questions are analysed: (i) typicality of human observers, (ii) the multiverse hypothesis and, extremely briefly, some few observations about (iii) the anthropic principle. Finally, it is demonstrated that this formulation can address problems that were out of the scope of scientific research until now by presenting the isolated worlds problem and its resolution via the presented framework.

Abstract:
This work introduces a complexity measure which addresses some conflicting issues between existing ones by using a new principle - measuring the average amount of symmetry broken by an object. It attributes low (although different) complexity to either deterministic or random homogeneous densities and higher complexity to the intermediate cases. This new measure is easily computable, breaks the coarse graining paradigm and can be straightforwardly generalised, including to continuous cases and general networks. By applying this measure to a series of objects, it is shown that it can be consistently used for both small scale structures with exact symmetry breaking and large scale patterns, for which, differently from similar measures, it consistently discriminates between repetitive patterns, random configurations and self-similar structures.

Abstract:
Using analytical methods of statistical mechanics, we analyse the typical behaviour of a multiple-input multiple-output (MIMO) Gaussian channel with binary inputs under LDPC network coding and joint decoding. The saddle point equations for the replica symmetric solution are found in particular realizations of this channel, including a small and large number of transmitters and receivers. In particular, we examine the cases of a single transmitter, a single receiver and the symmetric and asymmetric interference channels. Both dynamical and thermodynamical transitions from the ferromagnetic solution of perfect decoding to a non-ferromagnetic solution are identified for the cases considered, marking the practical and theoretical limits of the system under the current coding scheme. Numerical results are provided, showing the typical level of improvement/deterioration achieved with respect to the single transmitter/receiver result, for the various cases.

Abstract:
The typical behaviour of the relay-without-delay channel and its many-units generalisation, termed the relay array, under LDPC coding, is studied using methods of statistical mechanics. A demodulate-and-forward strategy is analytically solved using the replica symmetric ansatz which is exact in the studied system at the Nishimori's temperature. In particular, the typical level of improvement in communication performance by relaying messages is shown in the case of small and large number of relay units.

Abstract:
Using methods of statistical physics, we study the average number and kernel size of general sparse random matrices over GF(q), with a given connectivity profile, in the thermodynamical limit of large matrices. We introduce a mapping of $GF(q)$ matrices onto spin systems using the representation of the cyclic group of order q as the q-th complex roots of unity. This representation facilitates the derivation of the average kernel size of random matrices using the replica approach, under the replica symmetric ansatz, resulting in saddle point equations for general connectivity distributions. Numerical solutions are then obtained for particular cases by population dynamics. Similar techniques also allow us to obtain an expression for the exact and average number of random matrices for any general connectivity profile. We present numerical results for particular distributions.

Abstract:
We present and analyse three online algorithms for learning in discrete Hidden Markov Models (HMMs) and compare them with the Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalisation error we draw learning curves in simplified situations. The performance for learning drifting concepts of one of the presented algorithms is analysed and compared with the Baldi-Chauvin algorithm in the same situations. A brief discussion about learning and symmetry breaking based on our results is also presented.

Abstract:
Understanding a complex network's structure holds the key to understanding its function. The physics community has contributed a multitude of methods and analyses to this cross-disciplinary endeavor. Structural features exist on both the microscopic level, resulting from differences between single node properties, and the mesoscopic level resulting from properties shared by groups of nodes. Disentangling the determinants of network structure on these different scales has remained a major, and so far unsolved, challenge. Here we show how multiscale generative probabilistic exponential random graph models combined with efficient, distributive message-passing inference techniques can be used to achieve this separation of scales, leading to improved detection accuracy of latent classes as demonstrated on benchmark problems. It sheds new light on the statistical significance of motif-distributions in neural networks and improves the link-prediction accuracy as exemplified for gene-disease associations in the highly consequential Online Mendelian Inheritance in Man database.

Abstract:
We investigate a simplified model of two fully connected magnetic systems maintained at different temperatures by virtue of being connected to two independent thermal baths while simultaneously being inter-connected with each other. Using generating functional analysis, commonly used in statistical mechanics, we find exactly soluble expressions for their individual magnetisations that define a two-dimensional non-linear map, the equations of which have the same form as those obtained for densely connected equilibrium systems. Steady states correspond to the fixed points of this map, separating the parameter space into a rich set of non-equilibrium phases that we analyse in asymptotically high and low (non-equilibrium) temperature limits. The theoretical formalism is shown to subvert to the classical non-equilibrium steady state problem for two interacting systems with a non-zero heat transfer between them that catalyses a phase transition between ambient non-equilibrium states.

Abstract:
In this paper we discuss some features of the BCRE model. We show that this model can be understood as a mapping from a two-dimensional to a one-dimensional problem, if some conditions are satisfied. We propose some modifications that (a) guarantee mass conservation in the model (what is not assured in its original form) and (b) correct undesired behaviors that appear when there are irregularities in the surface of the static phase. We also show that a similar model can be deduced both from the principle of mass conservation (first equation) and a simple thermodynamic model (from which the exchange equation can be obtained). Finally, we solve the model numerically, using different velocity profiles and studying the influence of the different parameters present in this model.