982 resultados para Interacting particle systems


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The origin of M32, the closest compact elliptical galaxy (cE), is a long-standing puzzle of galaxy fort-nation in the Local Group. Our N-body/smoothed particle hydrodynamics simulations suggest a new scenario in which the strong tidal field of M31 can transform a spiral galaxy into a compact elliptical galaxy. As a low-luminosity spiral galaxy plunges into the central region of M31, most of the outer stellar and gaseous components of its disk are dramatically stripped as a result of M31's tidal field. The central bulge component, on the other hand, is just weakly influenced by the tidal field, owing to its compact configuration, and retains its morphology. M31's strong tidal field also induces rapid gas transfer to the central region, triggers a nuclear starburst, and consequently forms the central high-density and more metal-rich stellar populations with relatively young ages. Thus, in this scenario, M32 was previously the bulge of a spiral galaxy tidally interacting with M31 several gigayears ago. Furthermore, we suggest that cE's like M32 are rare, the result of both the rather narrow parameter space for tidal interactions that morphologically transform spiral galaxies into cE's and the very short timescale (less than a few times 10(9) yr) for cE's to be swallowed by their giant host galaxies (via dynamical friction) after their formation.

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Multipartite nucleic acid-containing virus-like particles, known as polydnaviruses, are special structures produced by female parasitoid wasps to deliver wasp components into the body of their host at oviposition. The particles confer protection for the developing parasitoid by passive and active means. Although several genes expressed from the circular DNA of these particles have been identified from various host-parasitoid systems, there is not much known about the structural proteins of these particles. Here we report on two genes encoding Cotesia rubecula particle proteins with similarities to molecular chaperones, calreticulin and heat-shock protein 70.

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There are practical and academic situations that justify the study of calcium carbonate crystallization and especially of systems that are associated with organic matrices and a confined medium. Despite the fact that many different matrices have been studied, the use of well-behaved, thin organic films may provide new knowledge about this system. In this work, we have studied the growth of calcium carbonate particles on well-defined organic matrices that were formed by layer-by-layer (LbL) polyelectrolyte films deposited on phospholipid Langmuir-Blodgett films (LB). We were able to change the surface electrical charge density of the LB films by changing the proportions of a negatively charged lipid, the sodium salt of dimyristoyl-sn-glycero-phosphatidyl acid (DMPA), and a zwitterionic lipid. dimyristoyl-sn-glycero-phosphatidylethanolamine (DMPE). This affects the subsequent polyelectrolyte LbL film deposition, which also changes the the nature of the bonding (electrostatic interaction or hydrogen bonding). This approach allowed for the formation of calcium carbonate particles of different final shapes, roughnesses, and sizes. The masses of deposited lipids, polyelectrolytes, and calcium cabonate were quantified by the quartz crystal microbalance technique. The structures of obtained particles were analyzed by scanning electron microscopy.

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We outline a scheme to accomplish measurements of a solid state double well system (DWS) with both one and two electrons in nonlocalized bases. We show that, for a single particle, measuring the local charge distribution at the midpoint of a DWS using a SET as a sensitive electrometer amounts to performing a projective measurement in the parity (symmetric/antisymmetric) eigenbasis. For two-electrons in a DWS, a similar configuration of SET results in close-to-projective measurement in the singlet/triplet basis. We analyze the sensitivity of the scheme to asymmetry in the SET position for some experimentally relevant parameter, and show that it is experimentally realizable.

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Many peptides containing tryptophan have therapeutic uses and can be studied by their fluorescent properties. The biological activity of these peptides involves interactions with many cellular components and micelles can function as carriers inside organisms. We report results from the interaction of small peptides containing tryptophan with several microheterogeneous systems: sodium dodecyl sulphate (SDS) micelles; sodium dodecyl sulphate-poly(ethylene oxide) (SDS-PEO) aggregates; and neutral polymeric micelles. We observed that specific parameters, such as wavelength of maximum emission and fluorescence anisotropy, could be used to ascertain the occurrence of interactions. Affinity constants were determined from changes in the intensity of emission while structural modifications in rotameric conformations were verified from time-resolved measurements. Information about the location and diffusion of peptides in the microheterogeneous systems were obtained from tryptophan emission quenching experiments using N-alkylpyridinium ions. The results show the importance of electrostatic and hydrophobic effects, and of the ionization state of charged residues, in the presence of anionic and amphiphilic SDS in the microheterogeneous systems. Conformational stability of peptides is best preserved in the interaction with the neutral polymeric micelles. (C) 2009 Elsevier B.V. All rights reserved.

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Classical dynamics is formulated as a Hamiltonian flow in phase space, while quantum mechanics is formulated as unitary dynamics in Hilbert space. These different formulations have made it difficult to directly compare quantum and classical nonlinear dynamics. Previous solutions have focused on computing quantities associated with a statistical ensemble such as variance or entropy. However a more diner comparison would compare classical predictions to the quantum predictions for continuous simultaneous measurement of position and momentum of a single system, in this paper we give a theory of such measurement and show that chaotic behavior in classical systems fan be reproduced by continuously measured quantum systems.

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We extend a recent construction for an integrable model describing Josephson tunneling between identical BCS systems to the case where the BCS systems have different single particle energy levels. The exact solution of this generalized model is obtained through the Bethe ansatz.

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We study a model consisting of particles with dissimilar bonding sites ("patches"), which exhibits self-assembly into chains connected by Y-junctions, and investigate its phase behaviour by both simulations and theory. We show that, as the energy cost epsilon(j) of forming Y-junctions increases, the extent of the liquid-vapour coexistence region at lower temperatures and densities is reduced. The phase diagram thus acquires a characteristic "pinched" shape in which the liquid branch density decreases as the temperature is lowered. To our knowledge, this is the first model in which the predicted topological phase transition between a fluid composed of short chains and a fluid rich in Y-junctions is actually observed. Above a certain threshold for epsilon(j), condensation ceases to exist because the entropy gain of forming Y-junctions can no longer offset their energy cost. We also show that the properties of these phase diagrams can be understood in terms of a temperature-dependent effective valence of the patchy particles. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3605703]

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This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

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Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

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The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

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We investigate the phase behaviour of 2D mixtures of bi-functional and three-functional patchy particles and 3D mixtures of bi-functional and tetra-functional patchy particles by means of Monte Carlo simulations and Wertheim theory. We start by computing the critical points of the pure systems and then we investigate how the critical parameters change upon lowering the temperature. We extend the successive umbrella sampling method to mixtures to make it possible to extract information about the phase behaviour of the system at a fixed temperature for the whole range of densities and compositions of interest. (C) 2013 AIP Publishing LLC.

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We present a study of the effects of nanoconfinement on a system of hard Gaussian overlap particles interacting with planar substrates through the hard-needle-wall potential, extending earlier work by two of us [D. J. Cleaver and P. I. C. Teixeira, Chem. Phys. Lett. 338, 1 (2001)]. Here, we consider the case of hybrid films, where one of the substrates induces strongly homeotropic anchoring, while the other favors either weakly homeotropic or planar anchoring. These systems are investigated using both Monte Carlo simulation and density-functional theory, the latter implemented at the level of Onsager's second-virial approximation with Parsons-Lee rescaling. The orientational structure is found to change either continuously or discontinuously depending on substrate separation, in agreement with earlier predictions by others. The theory is seen to perform well in spite of its simplicity, predicting the positional and orientational structure seen in simulations even for small particle elongations.

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This manuscript analyses the data generated by a Zero Length Column (ZLC) diffusion experimental set-up, for 1,3 Di-isopropyl benzene in a 100% alumina matrix with variable particle size. The time evolution of the phenomena resembles those of fractional order systems, namely those with a fast initial transient followed by long and slow tails. The experimental measurements are best fitted with the Harris model revealing a power law behavior.