Carbono: arte, ciência e as impurezas do tempo

Esta dissertação enfoca uma série de trabalhos artísticos desenvolvidos antes e durante o período do mestrado, como Sumi, Infiltração e Carbono, que utilizam a fotografia, o vídeo, a instalação, o desenho, a frotagem e a escultura como meios de produção. A partir das obras desenvolveu-se uma discussão teórica acerca de algumas das relações possíveis entre a arte e a ciência, enquanto esferas produtoras de conhecimento. O embate entre o homem e a natureza, através da filosofia, da ciência e da arte, é objeto de estudo, além das especificidades do átomo Carbono, em especial suas estruturas macroscópicas os materiais e suas transformações ao longo do tempo. A instabilidade, a entropia, o fluxo, os paradigmas e as diversas concepções de Tempo são alguns dos temas tratados nesta pesquisa, que utilizou como base os escritos e as obras de artistas, cientistas, filósofos e pesquisadores da arte e da ciência

Efeito da anisotropia sobre as propriedades magnetocalóricas de compostos metálicos: um estudo sistemático

O efeito magnetocalórico, i.e., o aquecimento e/ou resfriamento de um material magnético sob variação do campo magnético aplicado é a base da refrigeração magnética.O efeito magnetocalórico é caracterizado pela variação da entropia em um processo isotérmico (O efeito magnetocalórico, i.e., o aquecimento e/ou resfriamento de um material magnético sob variação do campo magnético aplicado é a base da refrigeração magnética. O efeito magnetocalórico é caracterizado pela variação da entropia em um processo isotérmico (ΔSiso) e pela variação da temperatura em um processo adiabático ΔTad.Apesar dos inúmeros trabalhos experimentais e teóricos publicados nessa área, muitos aspectos desse efeito ainda não são bem compreendidos.Nesse trabalho discutimos os efeitos da anisotropia sobre as propriedades magnetocalóricas de um sistema de momentos magnéticos localizados. Para essa finalidade, utilizamos um modelo de spins interagentes com um termo de anisotropia uniaxial do tipo DS2 z , onde D é um parâmetro. Nesse modelo, em que o eixo z é a direção de fácil magnetização, a magnitude do parâmetro de anisotropia e a direção do campo magnético aplicado têm um papel fundamental no comportamento das grandezas magnetocalóricas ΔSiso e ΔTad. Realizamos um estudo sistemático para um sistema com J = 1 aplicando o campo magnético em diferentes direções. Os resultados mostram que, quando o campo magnético é aplicado ao longo da direção z, as grandezas magnetocalóricas apresentam o comportamento normal (valores positivos de ΔTad e valores negativos de ΔSiso para ΔB > 0). Quando o campo magnético é aplicado em uma direção diferente do eixo z, as grandezas magnetocalóricas podem apresentar o comportamento inverso (valores negativos de ΔTad e valores positivos de ΔSiso para ΔB > 0) ou o comportamento anômalo (troca de sinal nas curvas de ΔTad e ΔSiso). Resultados equivalentes também foram obtidos para um sistema com J = 7=2.

O efeito magnetocalórico na série Gd(1-y)Pr(y)Ni2

Em geral, o efeito magnetocalórico (EMC) é caracterizado pela variação adiabática da temperatura (ΔTad) e a variação isotérmica da entropia (ΔST) sob variações do campo magnético. Devido as aplicações tecnológicas do EMC na refrigeração magnética, que não apresentam efeitos perigosos para o meio ambiente e tem o potencial para reduzir o consumo de energia, os estudos sobre o EMC tem crescido ao longo dos anos . Neste trabalho, estudamos as propriedades magnéticas e magnetocalóricos da série Gd (1-Y) Pr (Y) Ni2 com Y = 0; 0,25; 0,5; 0,75 e 1 A série dos compostos RNi2 compostos cristalizam na fase de Laves cúbico C15, o que torna o Campo Elétrico Cristalino cúbico um quadro adequado para descrever a anisotropia magnética sobre estes compostos . Além do modelo hamiltoniano inclui contribuições do efeito Zeeman e as interações de troca indireta entre Gd-Gd, Gd-Pr e íons Pr-Pr. Vale a pena notar que o GdNi2 apresenta um arranjo ferromagnético com temperatura de transição de cerca de 78 K e o composto PrNi2 é paramagnético. Os potenciais magnetocalóricos foram calculados e comparados com os dados experimentais. Além disso, investigamos a influência da direção do campo magnético sobre as quantidades magnéticas e no EMC investigada.

Motor coordination: when two have to act as one.

Trying to pass someone walking toward you in a narrow corridor is a familiar example of a two-person motor game that requires coordination. In this study, we investigate coordination in sensorimotor tasks that correspond to classic coordination games with multiple Nash equilibria, such as "choosing sides," "stag hunt," "chicken," and "battle of sexes". In these tasks, subjects made reaching movements reflecting their continuously evolving "decisions" while they received a continuous payoff in the form of a resistive force counteracting their movements. Successful coordination required two subjects to "choose" the same Nash equilibrium in this force-payoff landscape within a single reach. We found that on the majority of trials coordination was achieved. Compared to the proportion of trials in which miscoordination occurred, successful coordination was characterized by several distinct features: an increased mutual information between the players' movement endpoints, an increased joint entropy during the movements, and by differences in the timing of the players' responses. Moreover, we found that the probability of successful coordination depends on the players' initial distance from the Nash equilibria. Our results suggest that two-person coordination arises naturally in motor interactions and is facilitated by favorable initial positions, stereotypical motor pattern, and differences in response times.

Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii

The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors potentially influence their spatial distribution, including aragonite saturation, alkalinity, pH, currents, water temperature, hard substrate availability and the availability of light at depth. Mesophotic corals and mesophotic coral ecosystems (MCEs) have increasingly been the subject of scientific study because they are being threatened by a growing number of anthropogenic stressors. They are the focus of this spatial modeling effort because the Hawaiian Islands Humpback Whale National Marine Sanctuary (HIHWNMS) is exploring the expansion of its scope—beyond the protection of the North Pacific Humpback Whale (Megaptera novaeangliae)—to include the conservation and management of these ecosystem components. The present study helps to address this need by examining the distribution of mesophotic corals in the Au‘au Channel region. This area is located between the islands of Maui, Lanai, Molokai and Kahoolawe, and includes parts of the Kealaikahiki, Alalākeiki and Kalohi Channels. It is unique, not only in terms of its geology, but also in terms of its physical oceanography and local weather patterns. Several physical conditions make it an ideal place for mesophotic hard corals, including consistently good water quality and clarity because it is flushed by tidal currents semi-diurnally; it has low amounts of rainfall and sediment run-off from the nearby land; and it is largely protected from seasonally strong wind and wave energy. Combined, these oceanographic and weather conditions create patches of comparatively warm, calm, clear waters that remain relatively stable through time. Freely available Maximum Entropy modeling software (MaxEnt 3.3.3e) was used to create four separate maps of predicted habitat suitability for: (1) all mesophotic hard corals combined, (2) Leptoseris, (3) Montipora and (4) Porites genera. MaxEnt works by analyzing the distribution of environmental variables where species are present, so it can find other areas that meet all of the same environmental constraints. Several steps (Figure 0.1) were required to produce and validate four ensemble predictive models (i.e., models with 10 replicates each). Approximately 2,000 georeferenced records containing information about mesophotic coral occurrence and 34 environmental predictors describing the seafloor’s depth, vertical structure, available light, surface temperature, currents and distance from shoreline at three spatial scales were used to train MaxEnt. Fifty percent of the 1,989 records were randomly chosen and set aside to assess each model replicate’s performance using Receiver Operating Characteristic (ROC), Area Under the Curve (AUC) values. An additional 1,646 records were also randomly chosen and set aside to independently assess the predictive accuracy of the four ensemble models. Suitability thresholds for these models (denoting where corals were predicted to be present/absent) were chosen by finding where the maximum number of correctly predicted presence and absence records intersected on each ROC curve. Permutation importance and jackknife analysis were used to quantify the contribution of each environmental variable to the four ensemble models.

The estimation of stochastic context-free grammars using the Inside-Outside algorithm

Using an entropy argument, it is shown that stochastic context-free grammars (SCFG's) can model sources with hidden branching processes more efficiently than stochastic regular grammars (or equivalently HMM's). However, the automatic estimation of SCFG's using the Inside-Outside algorithm is limited in practice by its O(n3) complexity. In this paper, a novel pre-training algorithm is described which can give significant computational savings. Also, the need for controlling the way that non-terminals are allocated to hidden processes is discussed and a solution is presented in the form of a grammar minimization procedure. © 1990.

Vortex Transport and Blade Interactions in High Pressure Turbines

This paper presents a study of the three-dimensional flow field within the blade rows of a high-pressure axial flow steam turbine stage. Half-delta wings were fixed to a rotating hub to simulate an upstream rotor passage vortex. The flow field is investigated in a Low-Speed Research Turbine using pneumatic and hot-wire probes downstream of the blade row. The paper examines the impact of the delta wing vortex transport on the performance of the downstream blade row. Steady and unsteady numerical simulations were performed using structured 3D Navier-Stokes solver to further understand the flow field. The loss measurements at the exit of the stator blade showed an increase in stagnation pressure loss due to the delta wing vortex transport. The increase in loss was 21% of the datum stator loss, demonstrating the importance of this vortex interaction. The transport of the stator viscous flow through the rotor blade row is also described. The rotor exit flow was affected by the interaction between the enhanced stator passage vortex and the rotor blade row. Flow underturning near the hub and overturning towards the mid-span was observed, contrary to the classical model of overturning near the hub and underturning towards the mid-span. The unsteady numerical simulation results were further analysed to identify the entropy producing regions in the unsteady flow field.

Cluster analysis of heterogeneous rank data

Cluster analysis of ranking data, which occurs in consumer questionnaires, voting forms or other inquiries of preferences, attempts to identify typical groups of rank choices. Empirically measured rankings are often incomplete, i.e. different numbers of filled rank positions cause heterogeneity in the data. We propose a mixture approach for clustering of heterogeneous rank data. Rankings of different lengths can be described and compared by means of a single probabilistic model. A maximum entropy approach avoids hidden assumptions about missing rank positions. Parameter estimators and an efficient EM algorithm for unsupervised inference are derived for the ranking mixture model. Experiments on both synthetic data and real-world data demonstrate significantly improved parameter estimates on heterogeneous data when the incomplete rankings are included in the inference process.

The Gaussian mixture MCMC particle algorithm for dynamic cluster tracking

We present a novel filtering algorithm for tracking multiple clusters of coordinated objects. Based on a Markov chain Monte Carlo (MCMC) mechanism, the new algorithm propagates a discrete approximation of the underlying filtering density. A dynamic Gaussian mixture model is utilized for representing the time-varying clustering structure. This involves point process formulations of typical behavioral moves such as birth and death of clusters as well as merging and splitting. For handling complex, possibly large scale scenarios, the sampling efficiency of the basic MCMC scheme is enhanced via the use of a Metropolis within Gibbs particle refinement step. As the proposed methodology essentially involves random set representations, a new type of estimator, termed the probability hypothesis density surface (PHDS), is derived for computing point estimates. It is further proved that this estimator is optimal in the sense of the mean relative entropy. Finally, the algorithm's performance is assessed and demonstrated in both synthetic and realistic tracking scenarios. © 2012 Elsevier Ltd. All rights reserved.

Magnetocaloric and transport study of poly- and nanocrystalline composite manganites La 0.7Ca 0.3MnO 3/La 0.8Sr 0.2MnO 3

Magnetocaloric and transport properties are reported for novel poly- and nanocrystalline double composite manganites, La 0.8Sr 0.2MnO 3/La 0.7Ca 0.3MnO 3, prepared by the sol-gel method. Magnetic field dependence of magnetic entropy change is found to be stronger for the nano- than the polycrystalline composite. The remarkable broadening of the temperature interval, where the magnetocaloric effect occurs in poly- and nanocrystalline composites, causes the relative cooling power (RCP(S)) of the nanocrystalline composite to be reduced by only 10 compared to the Sr based polycrystalline phase. The RCP(S) of the polycrystalline composite becomes remarkably enhanced. The low temperature magnetoresistance is enhanced by 5 for the nanostructured composite. © 2012 American Institute of Physics.

Magnetocaloric effect in La0.75Sr0.25MnO3 manganite

The polycrystalline manganite La0.75Sr0.25MnO 3 prepared by an alternative carbonate precipitation route reveals the rhombohedral perovskite structure. Magnetization isotherms measured up to 2 T are used to determine Curie temperature of 332 K by means of Arrott plot. Maximum of magnetic entropy change is found at Curie temperature. The relative cooling power equal to 64 J/kg for 1.5 T magnetic field, is superior as compared to the manganite with the same chemical composition from the solgel method. © 2010 Elsevier B.V. All rights reserved.

Magnetocaloric effect and magnetic properties of Tb0.9 Sn0.1 MnO3

The magnetocaloric effect in magnetic materials is of great interest nowadays. In this article we present an investigation about the magnetic properties near the magnetic transition in a polycrystalline sample of a manganite Tb0.9 Sn0.1 MnO3. Particularly, we are interested in describing the nature of the magnetic interactions and the magnetocaloric effect in this compound. The temperature dependence of the magnetization was measured to determine the characteristics of the magnetic transition and the magnetic entropy change was calculated from magnetization curves at different temperatures. The magnetic solid is paramagnetic at high temperatures. We observe a dominant antiferromagnetic interaction below Tn =38 K for low applied magnetic fields; the presence of Sn doping in this compound decreases the Ńel temperature of the pure TbMnO3 system. A drastic increase in the magnetization as a function of temperature near the magnetic transition suggests a strong magnetocaloric effect. We found a large magnetic entropy change Δ SM (T) of about -4 J/kg K at H=3 T. We believe that the magnetic entropy change is associated with the magnetic transition and we interpret it as due to the coupling between the magnetic field and the spin ordering. This relatively large value and broad temperature interval (about 35 K) of the magnetocaloric effect make the present compound a promising candidate for magnetic refrigerators at low temperatures. © 2007 American Institute of Physics.

Magneto-transport study of Nb-doped Bi/Pb2223 superconductor

The magneto-transport properties of Bi1.5Pb0.4Nb0.1Sr2Ca2Cu 3O10-x polycrystalline, superconducting ceramic are reported. The material was found to be chemically homogeneous and partially textured. The mixed state properties were investigated by measuring the electrical resistivity, longitudinal and transverse (Nernst effect) thermoelectric power, and thermal conductivity. The magnetization and AC susceptibility measurements were also performed. The variation of these characteristics for magnetic fields up to 5 T are discussed and compared to those of the zero field case. The transport entropy and thermal Hall angle are extracted and quantitatively compared to previously reported data of closely related systems. © 2003 Elsevier Science B.V. All rights reserved.

Bayesian parameter identification for vibro-acoustic models with nonparametric uncertainty

Vibration and acoustic analysis at higher frequencies faces two challenges: computing the response without using an excessive number of degrees of freedom, and quantifying its uncertainty due to small spatial variations in geometry, material properties and boundary conditions. Efficient models make use of the observation that when the response of a decoupled vibro-acoustic subsystem is sufficiently sensitive to uncertainty in such spatial variations, the local statistics of its natural frequencies and mode shapes saturate to universal probability distributions. This holds irrespective of the causes that underly these spatial variations and thus leads to a nonparametric description of uncertainty. This work deals with the identification of uncertain parameters in such models by using experimental data. One of the difficulties is that both experimental errors and modeling errors, due to the nonparametric uncertainty that is inherent to the model type, are present. This is tackled by employing a Bayesian inference strategy. The prior probability distribution of the uncertain parameters is constructed using the maximum entropy principle. The likelihood function that is subsequently computed takes the experimental information, the experimental errors and the modeling errors into account. The posterior probability distribution, which is computed with the Markov Chain Monte Carlo method, provides a full uncertainty quantification of the identified parameters, and indicates how well their uncertainty is reduced, with respect to the prior information, by the experimental data. © 2013 Taylor & Francis Group, London.

Wetness loss prediction for a low pressure steam turbine using computational fluid dynamics

Two-phase computational fluid dynamics modelling is used to investigate the magnitude of different contributions to the wet steam losses in a three-stage model low pressure steam turbine. The thermodynamic losses (due to irreversible heat transfer across a finite temperature difference) and the kinematic relaxation losses (due to the frictional drag of the drops) are evaluated directly from the computational fluid dynamics simulation using a concept based on entropy production rates. The braking losses (due to the impact of large drops on the rotor) are investigated by a separate numerical prediction. The simulations show that in the present case, the dominant effect is the thermodynamic loss that accounts for over 90% of the wetness losses and that both the thermodynamic and the kinematic relaxation losses depend on the droplet diameter. The numerical results are brought into context with the well-known Baumann correlation, and a comparison with available measurement data in the literature is given. The ability of the numerical approach to predict the main wetness losses is confirmed, which permits the use of computational fluid dynamics for further studies on wetness loss correlations. © IMechE 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.