921 resultados para Two-state Potts model


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Part I. Proton Magnetic Resonance of Polynucleotides and Transfer RNA.

Proton magnetic resonance was used to follow the temperature dependent intramolecular stacking of the bases in the polynucleotides of adenine and cytosine. Analysis of the results on the basis of a two state stacked-unstacked model yielded values of -4.5 kcal/mole and -9.5 kcal/mole for the enthalpies of stacking in polyadenylic and polycytidylic acid, respectively.

The interaction of purine with these molecules was also studied by pmr. Analysis of these results and the comparison of the thermal unstacking of polynucleotides and short chain nucleotides indicates that the bases contained in stacks within the long chain poly nucleotides are, on the average, closer together than the bases contained in stacks in the short chain nucleotides.

Temperature and purine studies were also carried out with an aqueous solution of formylmethionine transfer ribonucleic acid. Comparison of these results with the results of similar experiments with the homopolynucleotides of adenine, cytosine and uracil indicate that the purine is probably intercalating into loop regions of the molecule.

The solvent denaturation of phenylalanine transfer ribonucleic acid was followed by pmr. In a solvent mixture containing 83 volume per cent dimethylsulf oxide and 17 per cent deuterium oxide, the tRNA molecule is rendered quite flexible. It is possible to resolve resonances of protons on the common bases and on certain modified bases.

Part II. Electron Spin Relaxation Studies of Manganese (II) Complexes in Acetonitrile.

The electron paramagnetic resonance spectra of three Mn+2 complexes, [Mn(CH3CN)6]+2, [MnCl4]-2, and [MnBr4]-2, in acetonitrile were studied in detail. The objective of this study was to relate changes in the effective spin Hamiltonian parameters and the resonance line widths to the structure of these molecular complexes as well as to dynamical processes in solution.

Of the three systems studied, the results obtained from the [Mn(CH3CN)6]+2 system were the most straight-forward to interpret. Resonance broadening attributable to manganese spin-spin dipolar interactions was observed as the manganese concentration was increased.

In the [MnCl4]-2 system, solvent fluctuations and dynamical ion-pairing appear to be significant in determining electron spin relaxation.

In the [MnBr4]-2 system, solvent fluctuations, ion-pairing, and Br- ligand exchange provide the principal means of electron spin relaxation. It was also found that the spin relaxation in this system is dependent upon the field strength and is directly related to the manganese concentration. A relaxation theory based on a two state collisional model was developed to account for the observed behavior.

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The imminent inability of silicon-based memory devices to satisfy Moore's Law is approaching rapidly. Controllable nanodomains of ferroic systems are anticipated to enable future high-density nonvolatile memory and novel electronic devices. We find via piezoresponse force microscopy (PFM) studies on lead zirconate titanate (PZT) films an unexpected nanostructuring of ferroelectric-ferroelastic domains. These consist of c-nanodomains within a-nanodomains in proximity to a-nanodomains within c-domains. These structures are created and annihilated as pairs, controllably. We treat these as a new kind of vertex-antivertex pair and consider them in terms of the Srolovitz-Scott 4-state Potts model, which results in pairwise domain vertex instabilities that resemble the vortex-antivortex mechanism in ferromagnetism, as well as dislocation pairs (or disclination pairs) that are well-known in nematic liquid crystals. Finally, we show that these nanopairs can be scaled up to form arrays that are engineered at will, paving the way toward facilitating them to real technologies.

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When a grating is recorded in a bacteriorhodopsin film by two linear parallel polarized beams together with anauxiliary violet light, the diffraction efficiency has a dependence on the polarization orientation of the violet light as well as its intensity. A method for calculating the diffraction efficiency of gratings in bacteriorhodopsin is proposed based on the two-state photochromic model, considering the saturation effect and the polarization status of all the involved lights. It is found that the polarization orientation of the violet light produces an approximate-cosine and an approximate-sine modulation on the steady-state diffraction efficiency separately at low and high intensities, respectively. The parallel polarized violet light can improve the steady-state diffraction efficiency to a larger degree than the perpendicularly polarized violet light when both are at their optimal intensities. The optimal intensity for the parallel polarized violet light is lower than that of the perpendicular polarized one. Thus, the improvement of the steady-state diffraction efficiency is less sensitive to the intensity of perpendicular polarized violet light than to that of parallel polarized violet light. (C) 2008 Optical Society of America.

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Biophysical Chemistry 110 (2004) 83–92

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Der Haupt-Lichtsammelkomplex (LHCII) des Photosyntheseapparates höherer Pflanzen gehört zu den häufigsten Membranproteinen der Erde. Seine Kristallstruktur ist bekannt. Das Apoprotein kann rekombinant in Escherichia coli überexprimiert und somit molekularbiologisch vielfältig verändert werden. In Detergenzlösung besitzt das denaturierte Protein die erstaunliche Fähigkeit, sich spontan zu funktionalen Protein-Pigment-Komplexen zu organisieren, welche strukturell nahezu identisch sind mit nativem LHCII. Der Faltungsprozess findet in vitro im Zeitbereich von Sekunden bis Minuten statt und ist abhängig von der Bindung der Cofaktoren Chlorophyll a und b sowie verschiedenen Carotinoiden.rn Diese Eigenschaften machen LHCII besonders geeignet für Strukturuntersuchungen mittels der elektronenparamagnetischen Resonanz (EPR)-Spektrokopie. Diese setzt eine punktspezifische Spinmarkierung des LHCII voraus, die in dieser Arbeit zunächst optimiert wurde. Einschließlich der Beiträge Anderer stand eine breite Auswahl von über 40 spinmarkierten Mutanten des LHCII bereit, einen N-terminalen „Cys walk“ eingeschlossen. Weder der hierfür notwendige Austausch einzelner Aminosäuren noch die Anknüpfung des Spinmarkers beeinträchtigten die Funktion des LHCII. Zudem konnte ein Protokoll zur Präparation heterogen spinmarkierter LHCII-Trimere entwickelt werden, also von Trimeren, die jeweils nur ein Monomer mit einer Spinmarkierung enthalten.rn Spinmarkierte Proben des Detergenz-solubilisierten LHCII wurden unter Verwendung verschiedener EPR-Techniken strukturell analysiert. Als besonders aussagekräftig erwies sich die Messung der Wasserzugänglichkeit einzelner Aminosäurepositionen anhand der Electron Spin Echo Envelope Modulation (ESEEM). In Kombination mit der etablierten Double Electron-Electron Resonance (DEER)-Technik zur Detektion von Abständen zwischen zwei Spinmarkern wurde der membranständige Kernbereich des LHCII in Lösung eingehend untersucht und strukturell der Kristallstruktur für sehr ähnlich befunden. Die Vermessung kristallographisch nicht erfasster Bereiche nahe dem N-Terminus offenbarte die schon früher detektierte Strukturdynamik der Domäne in Abhängigkeit des Oligomerisierungsgrades. Der neue, noch zu vervollständigende Datensatz aus Abstandsverteilungen und ESEEM-Wasserzugänglichkeiten monomerer wie trimerer Proben sollte in naher Zukunft die sehr genaue Modellierung der N-terminalen Domäne des LHCII ermöglichen.rn In einem weiteren Abschnitt der Arbeit wurde die Faltung des LHCII-Apoproteins bei der LHCII-Assemblierung in vitro untersucht. Vorausgegangene fluoreszenzspektroskopi-sche Arbeiten hatten gezeigt, dass die Bindung von Chlorophyll a und b in aufeinanderfolgenden Schritten im Zeitbereich von weniger als einer Minute bzw. mehreren Minuten erfolgten. Sowohl die Wasserzugänglichkeit einzelner Aminosäurepositionen als auch Spin-Spin-Abstände änderten sich in ähnlichen Zeitbereichen. Die Daten deuten darauf hin, dass die Ausbildung der mittleren Transmembran-Helix mit der schnelleren Chlorophyll-a-Bindung einhergeht, während sich die Superhelix aus den beiden anderen Transmembranhelices erst im langsameren Schritt, zusammen mit der Chlorophyll-b-Bindung, ausbildet.rn

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UV-melting experiments were performed on 9-mer duplexes containing a pair of synthetic nucleobases P·Z, two members of Expanded Genetic Information System (AEGIS), or P, Z containing mismatches. Enthalpy, entropy and free energy change were derived from simulation using two-state transition model. Nearest neighbor thermodynamic parameters of trimers or tetramers containing P·Z pair or P, Z containing mismatches were derived based on known nearest neighbor parameters. Proposed structures based on thermodynamic parameters are discussed. An application using P·Z pair as reverse selection tool of desired nucleic acid secondary structure is described.

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A rare example of a two-dimensional Heisenberg model with an exact dimerized ground state is presented. This model, which can be regarded as a variation on the kagome' lattice, has several features of interest: it has a highly (but not macroscopically) degenerate ground state; it is closely related to spin chains studied by earlier authors; in particular, it exhibits domain-wall-like "kink" excitations normally associated only with one-dimensional systems. In some limits it decouples into noninteracting chains; unusually, this happens in the limit of strong, rather than weak, interchain coupling. [S0163-1829(99)50338-X].

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Ground-state properties of the two-dimensional Hubbard model with point-defect disorder are investigated numerically in the Hartree-Fock approximation. The phase diagram in the p(point defect concentration)-delta(deviation from half filling) plane exhibits antiferromagnetic, spin-density-wave, paramagnetic, and spin-glass-like phases. The disorder stabilizes the antiferromagnetic phase relative to the spin-density-wave phase. The presence of U strongly enhances the localization in the antiferromagnetic phase. The spin-density-wave and spin-glass-like phases are weakly localized.

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We interpret the recent discovery of a 125 GeV Higgs-like state in the context of a two-Higgs-doublet model with a heavy fourth sequential generation of fermions, in which one Higgs doublet couples only to the fourth-generation fermions, while the second doublet couples to the lighter fermions of the first three families. This model is designed to accommodate the apparent heaviness of the fourth-generation fermions and to effectively address the low-energy phenomenology of a dynamical electroweak-symmetry-breaking scenario. The physical Higgs states of the model are, therefore, viewed as composites primarily of the fourth-generation fermions. We find that the lightest Higgs, h, is a good candidate for the recently discovered 125 GeV spin-zero particle, when tan beta similar to O(1), for typical fourth-generation fermion masses of M-4G = 400-600 GeV, and with a large t-t' mixing in the right-handed quark sector. This, in turn, leads to BR(t' -> th) similar to O(1), which drastically changes the t' decay pattern. We also find that, based on the current Higgs data, this two-Higgs-doublet model generically predicts an enhanced production rate (compared to the Standard Model) in the pp -> h -> tau tau channel, and reduced rates in the VV -> h -> gamma gamma and p (p) over bar /pp -> V -> hV -> Vbb channels. Finally, the heavier CP-even Higgs is excluded by the current data up to m(H) similar to 500 GeV, while the pseudoscalar state, A, can be as light as 130 GeV. These heavier Higgs states and the expected deviations from the Standard Model din some of the Higgs production channels can be further excluded or discovered with more data.

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Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p, r, t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p, r, t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t -> infinity. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.

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We introduce a dynamic directional model (DDM) for studying brain effective connectivity based on intracranial electrocorticographic (ECoG) time series. The DDM consists of two parts: a set of differential equations describing neuronal activity of brain components (state equations), and observation equations linking the underlying neuronal states to observed data. When applied to functional MRI or EEG data, DDMs usually have complex formulations and thus can accommodate only a few regions, due to limitations in spatial resolution and/or temporal resolution of these imaging modalities. In contrast, we formulate our model in the context of ECoG data. The combined high temporal and spatial resolution of ECoG data result in a much simpler DDM, allowing investigation of complex connections between many regions. To identify functionally segregated sub-networks, a form of biologically economical brain networks, we propose the Potts model for the DDM parameters. The neuronal states of brain components are represented by cubic spline bases and the parameters are estimated by minimizing a log-likelihood criterion that combines the state and observation equations. The Potts model is converted to the Potts penalty in the penalized regression approach to achieve sparsity in parameter estimation, for which a fast iterative algorithm is developed. The methods are applied to an auditory ECoG dataset.

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Lithium-ion batteries have been widely adopted in electric vehicles (EVs), and accurate state of charge (SOC) estimation is of paramount importance for the EV battery management system. Though a number of methods have been proposed, the SOC estimation for Lithium-ion batteries, such as LiFePo4 battery, however, faces two key challenges: the flat open circuit voltage (OCV) vs SOC relationship for some SOC ranges and the hysteresis effect. To address these problems, an integrated approach for real-time model-based SOC estimation of Lithium-ion batteries is proposed in this paper. Firstly, an auto-regression model is adopted to reproduce the battery terminal behaviour, combined with a non-linear complementary model to capture the hysteresis effect. The model parameters, including linear parameters and non-linear parameters, are optimized off-line using a hybrid optimization method that combines a meta-heuristic method (i.e., the teaching learning based optimization method) and the least square method. Secondly, using the trained model, two real-time model-based SOC estimation methods are presented, one based on the real-time battery OCV regression model achieved through weighted recursive least square method, and the other based on the state estimation using the extended Kalman filter method (EKF). To tackle the problem caused by the flat OCV-vs-SOC segments when the OCV-based SOC estimation method is adopted, a method combining the coulombic counting and the OCV-based method is proposed. Finally, modelling results and SOC estimation results are presented and analysed using the data collected from LiFePo4 battery cell. The results confirmed the effectiveness of the proposed approach, in particular the joint-EKF method.

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The problem of state estimation occurs in many applications of fluid flow. For example, to produce a reliable weather forecast it is essential to find the best possible estimate of the true state of the atmosphere. To find this best estimate a nonlinear least squares problem has to be solved subject to dynamical system constraints. Usually this is solved iteratively by an approximate Gauss–Newton method where the underlying discrete linear system is in general unstable. In this paper we propose a new method for deriving low order approximations to the problem based on a recently developed model reduction method for unstable systems. To illustrate the theoretical results, numerical experiments are performed using a two-dimensional Eady model – a simple model of baroclinic instability, which is the dominant mechanism for the growth of storms at mid-latitudes. It is a suitable test model to show the benefit that may be obtained by using model reduction techniques to approximate unstable systems within the state estimation problem.

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We characterize optimal policy in a two-sector growth model with xed coeÆcients and with no discounting. The model is a specialization to a single type of machine of a general vintage capital model originally formulated by Robinson, Solow and Srinivasan, and its simplicity is not mirrored in its rich dynamics, and which seem to have been missed in earlier work. Our results are obtained by viewing the model as a specific instance of the general theory of resource allocation as initiated originally by Ramsey and von Neumann and brought to completion by McKenzie. In addition to the more recent literature on chaotic dynamics, we relate our results to the older literature on optimal growth with one state variable: speci cally, to the one-sector setting of Ramsey, Cass and Koopmans, as well as to the two-sector setting of Srinivasan and Uzawa. The analysis is purely geometric, and from a methodological point of view, our work can be seen as an argument, at least in part, for the rehabilitation of geometric methods as an engine of analysis.

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The main properties of realistic models for manganites are studied using analytic mean-field approximations and computational numerical methods, focusing on the two-orbital model with electrons interacting through Jahn-Teller (JT) phonons and/or Coulombic repulsions. Analyzing the model including both interactions by the combination of the mean-field approximation and the exact diagonalization method, it is argued that the spin-charge-orbital structure in the insulating phase of the purely JT-phononic model with a large Hund couphng J(H) is not qualitatively changed by the inclusion of the Coulomb interactions. As an important application of the present mean-held approximation, the CE-type antiferromagnetic state, the charge-stacked structure along the z axis, and (3x(2) - r(2))/(3y(2) - r(2))-type orbital ordering are successfully reproduced based on the JT-phononic model with large JH for the half-doped manganite, in agreement with recent Monte Carlo simulation results. Topological arguments and the relevance of the Heisenberg exchange among localized t(2g) spins explains why the inclusion of the nearest-neighbor Coulomb interaction does not destroy the charge stacking structure. It is also verified that the phase-separation tendency is observed both in purely JT-phononic (large JH) and purely Coulombic models in the vicinity of the hole undoped region, as long as realistic hopping matrices are used. This highlights the qualitative similarities of both approaches and the relevance of mixed-phase tendencies in the context of manganites. In addition, the rich and complex phase diagram of the two-orbital Coulombic model in one dimension is presented. Our results provide robust evidence that Coulombic and JT-phononic approaches to manganites are not qualitatively different ways to carry out theoretical calculations, but they share a variety of common features.