Geodetic Observations of Weak Determinism in Rupture Evolution of Large Earthquakes.

The moment evolution of large earthquakes is a subject of fundamental interest to both basic and applied seismology. Specifically, an open problem is when in the rupture process a large earthquake exhibits features dissimilar from those of a lesser magnitude event. The answer to this question is of importance for rapid, reliable estimation of earthquake magnitude, a major priority of earthquake and tsunami early warning systems. Much effort has been made to test whether earthquakes are deterministic, meaning that observations in the first few seconds of rupture can be used to predict the final rupture extent. However, results have been inconclusive, especially for large earthquakes greater than M w 7. Traditional seismic methods struggle to rapidly distinguish the size of large-magnitude events, in particular near the source, even after rupture completion, making them insufficient to resolve the question of predictive rupture behavior. Displacements derived from Global Navigation Satellite System data can accurately estimate magnitude in real time, even for the largest earthquakes. We employ a combination of seismic and geodetic (Global Navigation Satellite System) data to investigate early rupture metrics, to determine whether observational data support deterministic rupture behavior. We find that while the earliest metrics (~5 s of data) are not enough to infer final earthquake magnitude, accurate estimates are possible within the first tens of seconds, prior to rupture completion, suggesting a weak determinism. We discuss the implications for earthquake source physics and rupture evolution and address recommendations for earthquake and tsunami early warning

Multi-unit Bilateral Trade

We characterise the set of dominant strategy incentive compatible (DSIC), strongly budget balanced (SBB), and ex-post individually rational (IR) mechanisms for the multi-unit bilateral trade setting. In such a setting there is a single buyer and a single seller who holds a finite number k of identical items. The mechanism has to decide how many units of the item are transferred from the seller to the buyer and how much money is transferred from the buyer to the seller. We consider two classes of valuation functions for the buyer and seller: Valuations that are increasing in the number of units in possession, and the more specific class of valuations that are increasing and submodular. Furthermore, we present some approximation results about the performance of certain such mechanisms, in terms of social welfare: For increasing submodular valuation functions, we show the existence of a deterministic 2-approximation mechanism and a randomised e/(1-e) approximation mechanism, matching the best known bounds for the single-item setting

Properties of Nucleon Resonances by means of a Genetic Algorithm

We present an optimization scheme that employs a Genetic Algorithm (GA) to determine the properties of low-lying nucleon excitations within a realistic photo-pion production model based upon an effective Lagrangian. We show that with this modern optimization technique it is possible to reliably assess the parameters of the resonances and the associated error bars as well as to identify weaknesses in the models. To illustrate the problems the optimization process may encounter, we provide results obtained for the nucleon resonances $\Delta$(1230) and $\Delta$(1700). The former can be easily isolated and thus has been studied in depth, while the latter is not as well known experimentally.Comment: 12 pages, 10 figures, 3 tables. Minor correction

Adaptive mutation using statistics mechanism for genetic algorithms

Copyright @ 2004 Springer-Verla

Dominant takeover regimes for genetic algorithms

The genetic algorithm (GA) is a machine-based optimization routine which connects evolutionary learning to natural genetic laws. The present work addresses the problem of obtaining the dominant takeover regimes in the GA dynamics. Estimated GA run times are computed for slow and fast convergence in the limits of high and low fitness ratios. Using Euler's device for obtaining partial sums in closed forms, the result relaxes the previously held requirements for long time limits. Analytical solution reveal that appropriately accelerated regimes can mark the ascendancy of the most fit solution. In virtually all cases, the weak (logarithmic) dependence of convergence time on problem size demonstrates the potential for the GA to solve large N-P complete problems

Thermodynamics of Hidden Sector Gaugino Condensation in the Expanding Universe

This work examines the confining-deconfining phase transition in a hidden Yang Mills sector with scale $\Lambda \sim 10^{14}$ GeV appropriate to dilaton stabilization and SUSY-breaking via formation of a gaugino consensate. If the transition is assumed to take place through homogenous nucleation, then under reasonable assumptions it is found that a critical bubble, formed at a temperature which provides enough supercooling, is not large enough to accommodate an adequate number (\gsim 100) of quanta of the confined phase (`hidden hadrons') to allow a consistent thermodynamic description. Thus, a first order transition in the hidden sector may not be possible in the expanding universe.Comment: 13 pages LaTex, no figure

The dynamics of EU attitudes and their effects on voting

In referendums on issues of European integration, it is often unclear how important attitudes toward Europe are and whether these attitudes change during the campaign. Extant research showing the importance of EU attitudes particularly in salient and contested referendums has often had to rely on static data and limited conceptualizations of EU attitudes. This potentially underestimates the role of (different types of) EU attitudes and hampers the ability to assess the dynamics of them. For the analysis of dynamics in EU attitudes, we mainly rely on pre- and post-waves for the Dutch Ukraine–European Union Association Agreement referendum, which extends a panel study leading back to the EP14 elections. This allows us to assess both long-term changes of EU attitudes since the last EP elections and also during the referendum campaign. We examine the effect of campaign-induced attitude changes for the referendum vote, while controlling for other relevant determinants. Our findings first show significant changes in EU attitudes during the referendum campaign, and second, highlight the relevance of some of these changes for the referendum vote. Both strengthening and especially emotional attitudes play respective significant roles, with the latter being in part dependent on media exposure

CAD of Stacked Patch Antennas Through Multipurpose Admittance Matrices From FEM and Neural Networks

In this work, a novel computer-aided design methodology for probe-fed, cavity-backed, stacked microstrip patch antennas is proposed. The methodology incorporates the rigor of a numerical technique, such as finite element methods, which, in turn, makes use of a newly developed procedure (multipurpose admittance matrices) to carry out a full-wave analysis in a given structure in spite of certain physical shapes and dimensions not yet being established. With the aid of this technique, we form a training set for a neural network, whose output is the desired response of the antenna according to the value of design parameters. Last, taking advantage of this neural network, we perform a global optimization through a genetic algorithm or simulated annealing to obtain a final design. The proposed methodology is validated through a real design whose numerical results are compared with measurements with good agreement