Long-range automaton models of earthquakes: Power-law accelerations, correlation evolution, and mode-switching

We introduce a conceptual model for the in-plane physics of an earthquake fault. The model employs cellular automaton techniques to simulate tectonic loading, earthquake rupture, and strain redistribution. The impact of a hypothetical crustal elastodynamic Green's function is approximated by a long-range strain redistribution law with a r(-p) dependance. We investigate the influence of the effective elastodynamic interaction range upon the dynamical behaviour of the model by conducting experiments with different values of the exponent (p). The results indicate that this model has two distinct, stable modes of behaviour. The first mode produces a characteristic earthquake distribution with moderate to large events preceeded by an interval of time in which the rate of energy release accelerates. A correlation function analysis reveals that accelerating sequences are associated with a systematic, global evolution of strain energy correlations within the system. The second stable mode produces Gutenberg-Richter statistics, with near-linear energy release and no significant global correlation evolution. A model with effectively short-range interactions preferentially displays Gutenberg-Richter behaviour. However, models with long-range interactions appear to switch between the characteristic and GR modes. As the range of elastodynamic interactions is increased, characteristic behaviour begins to dominate GR behaviour. These models demonstrate that evolution of strain energy correlations may occur within systems with a fixed elastodynamic interaction range. Supposing that similar mode-switching dynamical behaviour occurs within earthquake faults then intermediate-term forecasting of large earthquakes may be feasible for some earthquakes but not for others, in alignment with certain empirical seismological observations. Further numerical investigation of dynamical models of this type may lead to advances in earthquake forecasting research and theoretical seismology.

Long range forecasts of the numbers of Helicoverpa punctigera and H-armigera (Lepidoptera : Noctuidae) in Australia using the Southern Oscillation Index and the Sea Surface Temperature

The use of long-term forecasts of pest pressure is central to better pest management. We relate the Southern Oscillation Index (SOI) and the Sea Surface Temperature (SST) to long-term light-trap catches of the two key moth pests of Australian agriculture, Helicoverpa punctigera (Wallengren) and H. armigera (Hubner), at Narrabri, New South Wales over 11 years, and for H. punctigera only at Turretfield, South Australia over 22 years. At Narrabri, the size of the first spring generation of both species was significantly correlated with the SOI in certain months, sometimes up to 15 months before the date of trapping. Differences in the SOI and SST between significant months were used to build composite variables in multiple regressions which gave fitted values of the trap catches to less than 25% of the observed values. The regressions suggested that useful forecasts of both species could be made 6-15 months ahead. The influence of the two weather variables on trap catches of H. punctigera at Turretfield were not as strong as at Narrabri, probably because the SOI was not as strongly related to rainfall in southern Australia as it is in eastern Australia. The best fits were again given by multiple regressions with SOI plus SST variables, to within 40% of the observed values. The reliability of both variables as predictors of moth numbers may be limited by the lack of stability in the SOI-rainfall correlation over the historical record. As no other data set is available to test the regressions, they can only be tested by future use. The use of long-term forecasts in pest management is discussed, and preliminary analyses of other long sets of insect numbers suggest that the Southern Oscillation Index may be a useful predictor of insect numbers in other parts of the world.

Off-diagonal long-range order in a supersymmetric integrable model of correlated electrons

A new model for correlated electrons is presented which is integrable in one-dimension. The symmetry algebra of the model is the Lie superalgebra gl(2\1) which depends on a continuous free parameter. This symmetry algebra contains the eta pairing algebra as a subalgebra which is used to show that the model exhibits Off-Diagonal Long-Range Order in any number of dimensions.

New integrable model of correlated electrons with off-diagonal long-range order from so(5) symmetry

We present a new integrable model for correlated electrons which is based on so(5) symmetry. By using an eta-pairing realization we construct eigenstates of the Hamiltonian with off-diagonal long-range order. It is also shown that these states lie in the ground state sector. We exactly solve the model on a one-dimensional lattice by the Bethe ansatz.

Integrability and exact solution of an electronic model with long range interactions

We present an electronic model with long range interactions. Through the quantum inverse scattering method, integrability of the model is established using a one-parameter family of typical irreducible representations of gl(211). The eigenvalues of the conserved operators are derived in terms of the Bethe ansatz, from which the energy eigenvalues of the Hamiltonian are obtained.

Accelerating precursory activity within a class of earthquake analogue automata

A statistical fractal automaton model is described which displays two modes of dynamical behaviour. The first mode, termed recurrent criticality, is characterised by quasi-periodic, characteristic events that are preceded by accelerating precursory activity. The second mode is more reminiscent of SOC automata in which large events are not preceded by an acceleration in activity. Extending upon previous studies of statistical fractal automata, a redistribution law is introduced which incorporates two model parameters: a dissipation factor and a stress transfer ratio. Results from a parameter space investigation indicate that a straight line through parameter space marks a transition from recurrent criticality to unpredictable dynamics. Recurrent criticality only occurs for models within one corner of the parameter space. The location of the transition displays a simple dependence upon the fractal correlation dimension of the cell strength distribution. Analysis of stress field evolution indicates that recurrent criticality occurs in models with significant long-range stress correlations. A constant rate of activity is associated with a decorrelated stress field.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Quantum noise in optical fibers. I. Stochastic equations

We analyze the quantum dynamics of radiation propagating in a single-mode optical fiber with dispersion, nonlinearity, and Raman coupling to thermal phonons. We start from a fundamental Hamiltonian that includes the principal known nonlinear effects and quantum-noise sources, including linear gain and loss. Both Markovian and frequency-dependent, non-Markovian reservoirs are treated. This treatment allows quantum Langevin equations, which have a classical form except for additional quantum-noise terms, to be calculated. In practical calculations, it is more useful to transform to Wigner or 1P quasi-probability operator representations. These transformations result in stochastic equations that can be analyzed by use of perturbation theory or exact numerical techniques. The results have applications to fiber-optics communications, networking, and sensor technology.

Conformations of platypus venom C-type natriuretic peptide in aqueous solution and sodium dodecyl sulfate micelles

Nuclear magnetic resonance spectroscopy was used to investigate the conformations of the platypus venom C-type natriuretic peptide A (OvCNPa) in aqueous solutions and in solutions containing sodium dodecyl sulfate (SDS) micelles. The chemically synthesized OvCNPa showed a substantial decrease in flexibility in aqueous solution at 10 degreesC, allowing the observation of medium- and long-range nuclear Overhauser enhancement (NOE) connectivities. Three-dimensional structures calculated using these data showed flexible and reasonably well-defined regions, the locations of which were similar in the two solvents. In aqueous solution, the linear part that spans residues 3-14 was basically an extended conformation while the cyclic portion, defined by residues 23-39, contained a series of beta-turns. The overall shape of the cyclic portion was similar to that observed for an atrial natriuretic peptide (ANP) variant in aqueous solution. OvCNPa adopted a different conformation in SDS micelles wherein the N-terminal region, defined by residues 2-10, was more compact, characterised by turns and a helix, while the cyclic region had turns and an overall shape that was fundamentally different from those structures observed in aqueous solution. The hydrophobic cluster, situated at the centre of the ring of the structure in aqueous solution, was absent in the structure in the presence of SDS micelles. Thus, OvCNPa interacts with SDS micelles and can possibly form ion-channels in cell membranes. (C) 2002 Elsevier Science Ltd. All rights reserved.

Quantum noise limits to terabaud communications

From a general model of fiber optics, we investigate the physical limits of soliton-based terabaud communication systems. In particular we consider Raman and initial quantum noise effects which are often neglected in fiber communications. Simulations of the position diffusion in dark and bright solitons show that these effects become increasingly important at short pulse durations, even over kilometer-scale distances. We also obtain an approximate analytic theory in agreement with numerical simulations, which shows that the Raman effects exceed the Gordon-Haus jitter for sub-picosecond pulses. (C) 1997 Elsevier Science B.V.

The structures of Langmuir-Blodgett films of fatty acids and their salts

Recent advances in several experimental techniques have enabled detailed structural information to be obtained for floating (Langmuir) monolayers and Langmuir-Blodgett films. These techniques are described briefly and their application to the study of films of fatty acids and their salts is discussed. Floating monolayers on aqueous subphases have been shown to possess a complex polymorphism with phases whose structures may be compared to those of smectic mesophases. However, only those phases that exist at high surface pressures are normally used in Langmuir-Blodgett (LB) deposition. In single LB monolayers of fatty acids and fatty acid salts the acyl chains are in the all-cans conformation with their long axes normal to the substrate. The in-plane molecular packing is hexagonal with long-range bond orientational order and short-range positional order: known as the hexatic-B structure. This structure is found irrespective of the phase of the parent floating monolayer. The structures of multilayer LB films are similar to the structures of their bulk crystals, consisting of stacked bilayer lamellae. Each lamella is formed from two monolayers of fatty acid molecules or ions arranged head to head and held together by hydrogen bonding between pairs of acids or ionic bonding through the divalent cations. With acids the acyl chains are tilted with respect to the substrate normal and have a monoclinic structure, whereas the salts with divalent cations may have the chains normal to the substrate or tilted. The in-plane structures are usually centred rectangular with the chains in the trans conformation and packed in a herringbone pattern, Multilayer films of the acids show only a single-step order-disorder transition at the malting point, This temperature tends to rise as the number of layers increases. Complex changes occur when multilayer films of the salts are heated. Disorder of the chains begins at low temperatures but the arrangement of the head groups does not alter until the melting temperature is reached, Slow heating to a temperature just below the melting temperature gives, with some salts, a radical change in phase. The lamellar structure disappears and a new phase consisting of cylindrical rods lying parallel to the substrate surface and stacked in a hexagonal pattern is formed, In each rod the cations are aligned along the central axis surrounded by the disordered acyl chains. (C) 2001 Elsevier Science B,V. All rights reserved.

Electric-field-induced Mott insulating states in organic field-effect transistors

We consider the possibility that the electrons injected into organic field-effect transistors are strongly correlated. A single layer of acenes can be modeled by a Hubbard Hamiltonian similar to that used for the κ-(BEDT-TTF)2X family of organic superconductors. The injected electrons do not necessarily undergo a transition to a Mott insulator state as they would in bulk crystals when the system is half-filled. We calculate the fillings needed for obtaining insulating states in the framework of the slave-boson theory and in the limit of large Hubbard repulsion U. We also suggest that these Mott states are unstable above some critical interlayer coupling or long-range Coulomb interaction.

Axon navigation in the mammalian primary olfactory pathway: Where to next?

The process of establishing long-range neuronal connections can be divided into at least three discrete steps. First, axons need to be stimulated to grow and this growth must be towards appropriate targets. Second, after arriving at their target, axons need to be directed to their topographically appropriate position and in some cases, such as in cortical structures, they must grow radially to reach the correct laminar layer Third, axons then arborize and form synaptic connections with only a defined subpopulation of potential post-synaptic partners. Attempts to understand these mechanisms in the visual system have been ongoing since pioneer studies in the 1940s highlighted the specificity of neuronal connections in the retino-tectal pathway. These classical systems-based approaches culminated in the 1990s with the discovery that Eph-ephrin repulsive interactions were involved in topographical mapping. In marked contrast, it was the cloning of the odorant receptor family that quickly led to a better understanding of axon targeting in the olfactory system. The last 10 years have seen the olfactory pathway rise in prominence as a model system for axon guidance. Once considered to be experimentally intractable, it is now providing a wealth of information on all aspects of axon guidance and targeting with implications not only for our understanding of these mechanisms in the olfactory system but also in other regions of the nervous system.