Scale Dependence of Polarized DIS Asymmetries

We compare the $Q^{2}$ dependence of the polarized deep inelastic scattering proton asymmetry, driven by the leading order Altarelli Parisi evolution equations, to those arising from fixed order $\alpha_{s}$ and $\alpha_{s}^{2}$ approximations. It is shown that the evolution effects associated with gluons, which are not properly taken into account by the leading order approximation, cannot be neglected in the analysis of the most recent experimental data.Comment: Latex file, (9 figures in postcript available from [email protected]

Fashion showcases design: perceptions of the showcase in the brazilian popular market

The present work aims to present the showcase, its relation with the building, with fashion and with the observer. The importance of this exhibition space extends from the aesthetic and communication functions to be part of a wide textile and clothing chain. This role integrates the whole cycle of creation, textiles, clothing and fashion accessories. For this article we used bibliographical references of design and fashion, as well as methodologies of photographic and ethnographic documentation, with application of focus groups. From the focus groups were identified descriptors related to emotional design. Such descriptors point to the emotions arising from memories, tastes and attitudes. These factors can lead to decisions and assist the wider knowledge of the target audience.- This work is supported by CNPq funding on the Programa Ciencias Sem Fronteiras - CSF by national funds within the scope of the project Processo no 203068/2014-9.info:eu-repo/semantics/publishedVersio

Physics of the Riemann Hypothesis

Physicists become acquainted with special functions early in their studies. Consider our perennial model, the harmonic oscillator, for which we need Hermite functions, or the Laguerre functions in quantum mechanics. Here we choose a particular number theoretical function, the Riemann zeta function and examine its influence in the realm of physics and also how physics may be suggestive for the resolution of one of mathematics' most famous unconfirmed conjectures, the Riemann Hypothesis. Does physics hold an essential key to the solution for this more than hundred-year-old problem? In this work we examine numerous models from different branches of physics, from classical mechanics to statistical physics, where this function plays an integral role. We also see how this function is related to quantum chaos and how its pole-structure encodes when particles can undergo Bose-Einstein condensation at low temperature. Throughout these examinations we highlight how physics can perhaps shed light on the Riemann Hypothesis. Naturally, our aim could not be to be comprehensive, rather we focus on the major models and aim to give an informed starting point for the interested Reader.Comment: 27 pages, 9 figure

A quantum mechanical model of the Riemann zeros

In 1999 Berry and Keating showed that a regularization of the 1D classical Hamiltonian H = xp gives semiclassically the smooth counting function of the Riemann zeros. In this paper we first generalize this result by considering a phase space delimited by two boundary functions in position and momenta, which induce a fluctuation term in the counting of energy levels. We next quantize the xp Hamiltonian, adding an interaction term that depends on two wave functions associated to the classical boundaries in phase space. The general model is solved exactly, obtaining a continuum spectrum with discrete bound states embbeded in it. We find the boundary wave functions, associated to the Berry-Keating regularization, for which the average Riemann zeros become resonances. A spectral realization of the Riemann zeros is achieved exploiting the symmetry of the model under the exchange of position and momenta which is related to the duality symmetry of the zeta function. The boundary wave functions, giving rise to the Riemann zeros, are found using the Riemann-Siegel formula of the zeta function. Other Dirichlet L-functions are shown to find a natural realization in the model.Comment: 42 pages, 12 figure

Uncertainty in perception and the Hierarchical Gaussian Filter

In its full sense, perception rests on an agent's model of how its sensory input comes about and the inferences it draws based on this model. These inferences are necessarily uncertain. Here, we illustrate how the Hierarchical Gaussian Filter (HGF) offers a principled and generic way to deal with the several forms that uncertainty in perception takes. The HGF is a recent derivation of one-step update equations from Bayesian principles that rests on a hierarchical generative model of the environment and its (in)stability. It is computationally highly efficient, allows for online estimates of hidden states, and has found numerous applications to experimental data from human subjects. In this paper, we generalize previous descriptions of the HGF and its account of perceptual uncertainty. First, we explicitly formulate the extension of the HGF's hierarchy to any number of levels; second, we discuss how various forms of uncertainty are accommodated by the minimization of variational free energy as encoded in the update equations; third, we combine the HGF with decision models and demonstrate the inversion of this combination; finally, we report a simulation study that compared four optimization methods for inverting the HGF/decision model combination at different noise levels. These four methods (Nelder-Mead simplex algorithm, Gaussian process-based global optimization, variational Bayes and Markov chain Monte Carlo sampling) all performed well even under considerable noise, with variational Bayes offering the best combination of efficiency and informativeness of inference. Our results demonstrate that the HGF provides a principled, flexible, and efficient-but at the same time intuitive-framework for the resolution of perceptual uncertainty in behaving agents

Strong, bold, and kind : Self-control and cooperation in social dilemmas

Financial support from the Swedish Research Council (Vetenskapsrådet), from Formas through the program Human Cooperation to Manage Natural Resources (COMMONS), and the Ideenfonds of the University of Munich is gratefully acknowledged.We develop a model that relates self-control to cooperation patterns in social dilemmas, and we test the model in a laboratory public goods experiment. As predicted, we find a robust association between stronger self-control and higher levels of cooperation, and the association is at its strongest when the decision maker’s risk aversion is low and the cooperation levels of others high. We interpret the pattern as evidence for the notion that individuals may experience an impulse to act in self-interest—and that cooperative behavior benefits from self-control. Free-riders differ from other contributor types only in their tendency not to have identified a self-control conflict in the first place.PostprintPeer reviewe

Motives and comprehension in a public goods game with induced emotions

This study analyses the sensitivity of public goods contributions through the lens of psychological motives. We report the results of a public goods experiment in which subjects were induced with the motives of care and anger through autobiographical recall. Subjects' preferences, beliefs, and perceptions under each motive are compared with those of subjects experiencing a neutral autobiographical recall control condition. We find, but only for those subjects with the highest comprehension of the game, that care elicits significantly higher contributions than anger, with the control treatment in between. This positive influence of the care motive on unconditional giving is accounted for partly by preferences for giving and partly by the beliefs concerning greater contributions by others. Anger also affects attention to own and other's payoffs (using mouse tracking) and perceptions of the game's incentive structure (cooperative or competitive)

Optimal Capital Income Taxation with Tax Evasion

The paper discusses the applicability of optimal taxation theory to source-based capital incomes when significant tax evasion is observed. Without tax evasion a modified Ramsey Rule may reduce distortions brought by international capital mobility, leading to levying differentiated tax rates in domestic sectors inversely proportioned to observed elasticities in terms of capital mobility. The introduction of tax evasion brings additional complexity. The viability of optimal tax rates à la Ramsey is explored, and additional requirement (namely that tax evasion is either very low or very homogeneous) are shown to be necessary in order to allow policy-makers to obtain the tax rates minimizing total excess burden. Results are also provided to solve the optimal taxation objective when tax evasion is a relevant phenomenon and is not homogeneous throughout domestic sectors

The Human Affectome

Over the last decades, the interdisciplinary field of the affective sciences has seen proliferation rather than integration of theoretical perspectives. This is due to differences in metaphysical and mechanistic assumptions about human affective phenomena (what they are and how they work) which, shaped by academic motivations and values, have determined the affective constructs and operationalizations. An assumption on the purpose of affective phenomena can be used as a teleological principle to guide the construction of a common set of metaphysical and mechanistic assumptions—a framework for human affective research. In this capstone paper for the special issue “Towards an Integrated Understanding of the Human Affectome”, we gather the tiered purpose of human affective phenomena to synthesize assumptions that account for human affective phenomena collectively. This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research

Getting warmer: predictive processing and the nature of emotion

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