Non-linear analysis of geomagnetic time series from Etna volcano

International audienceAn intensive nonlinear analysis of geomagnetic time series from the magnetic network on Etna volcano was carried out to investigate the dynamical behavior of magnetic anomalies in volcanic areas. The short-term predictability of the geomagnetic time series was evaluated to establish a possible low-dimensional deterministic dynamics. We estimated the predictive ability of both a nonlinear forecasting technique and a global autoregressive model by comparing the prediction errors. Our findings highlight that volcanomagnetic signals are the result of complex processes that cannot easily be predicted. There is slight evidence based on nonlinear predictions, that the geomagnetic time series are to be governed by many variables, whose time evolution could be better regarded as arising from complex high dimensional processes

Three-Loop Results in QCD with Wilson Fermions

We calculate the third coefficient of the lattice beta function in QCD with Wilson fermions, extending the pure gauge results of Luescher and Weisz; we show how this coefficient modifies the scaling function on the lattice. We also calculate the three-loop average plaquette in the presence of Wilson fermions. This allows us to compute the lattice scaling function both in the standard and energy schemes.Comment: 3 pages, LaTeX (fleqn.sty, espcrc2.sty), contribution to Lattice'97. Table caption corrected. The longer write-ups are in hep-lat/9801007 (beta function) and hep-lat/9801003 (plaquette

University Centers Programs: Creative Solutions For Serving Remote Populations

University Centers programs are designed to provide University level classes to students at remote locations and to facilitate a transition from local two-year institutions to regional four-year institutions.  Although similar in concept to satellite campuses and often using technologies associated with distance learning, University Centers programs also have unique characteristics that bring additional issues and concerns that need to be addressed.  In this paper we introduce the University Centers concept and review related administrative arrangements and uses of technology.   We then explore the unique issues and concerns of University Centers, drawing upon the experiences of one university’s involvement with University Centers for examples of both opportunities and solutions.  Guidelines will be presented for universities that are considering becoming involved in a University Centers program

Lava flow susceptibility map of mt etna based on numerical simulations

We constructed maps of probability of lava inundation using computer simulations considering the past eruptive behaviour of the Mt. Etna volcano and data deriving from monitoring networks. The basic a priori assumption is that new volcanoes will not form far from existing ones and that such a distribution can be performed using a Cauchy kernel. Geophysical data are useful to update or fine tune the initial Cauchy kernel to better reflect the distribution of future volcanism. In order to obtain a final susceptibility map, a statistical analysis permits a classification of Etna’s flank eruptions into twelve types. The simulation method consists of creating a probability surface of the location of future eruption vents and segmenting the region according to the most likely historical eruption on which to base the simulation. The paths of lava flows were calculated using the MAGFLOW Cellular Automata (CA) model, allowing us to simulate the discharge rate dependent spread of lava as a function of time

Modelling lava flows by Cellular Nonlinear Networks (CNN): preliminary results

International audienceThe forecasting of lava flow paths is a complex problem in which temperature, rheology and flux-rate all vary with space and time. The problem is more difficult to solve when lava runs down a real topography, considering that the relations between characteristic parameters of flow are typically nonlinear. An alternative approach to this problem that does not use standard differential equation methods is Cellular Nonlinear Networks (CNNs). The CNN paradigm is a natural and flexible framework for describing locally interconnected, simple, dynamic systems that have a lattice-like structure. They consist of arrays of essentially simple, nonlinearly coupled dynamic circuits containing linear and non-linear elements able to process large amounts of information in real time. Two different approaches have been implemented in simulating some lava flows. Firstly, a typical technique of the CNNs to analyze spatio-temporal phenomena (as Autowaves) in 2-D and in 3-D has been utilized. Secondly, the CNNs have been used as solvers of partial differential equations of the Navier-Stokes treatment of Newtonian flow

Assessment and modeling of lava flow hazard on Etna volcano

A methodology for constructing a probability map of lava inundation by considering the past eruptive behavior of the Mt Etna volcano is described. The basic a priori assumption is that new vents will not form far from existing ones and that such a distribution can be performed using a Gaussian kernel. The methodology is based on several steps: computation of susceptibility map that provides the spatial probability of vent opening; evaluation of the temporal probability for the occurrence of the hazard during the considered time interval; characterization of the expected eruptions; numerical simulations of lava flow paths, and elaboration of the hazard map. The application of MAGFLOW code, a physical-mathematical model, for simulating the lava flow paths represents the central part of this methodology for the hazard assessment at Etna. The simulation approach, to assess lava flow hazard, provides a more robust and locally accurate analysis than a simple probabilistic approach and accounts for the influence of the actual topography on the path of future lava flows

Assessment and modeling of lava flow hazard on Mt. Etna volcano

A methodology for constructing a probability map of lava inundation by considering the past eruptive behavior of the Mt. Etna volcano is described. The basic a priori assumption is that new vents will not form far from existing ones and that such a distribution can be performed using a Gaussian kernel. The methodology follows several steps: computation of a susceptibility map that provides the spatial probability of vent opening; evaluation of the temporal probability for the occurrence of the hazard during the considered time interval; characterization of the expected eruptions; numerical simulations of lava flow paths and elaboration of the hazard map. The application of MAGFLOW code, a physical-mathematical model, for simulating the lava flow paths represents the central part of this methodology for the hazard assessment at Mt. Etna. The simulation approach, to assess lava flow hazard, provides a more robust and locally accurate analysis than a simple probabilistic approach and accounts for the influence of the actual topography on the path of future lava flows

Tree biomass equations from terrestrial LiDAR : a case study in Guyana

Large uncertainties in tree and forest carbon estimates weaken national efforts to accurately estimate aboveground biomass (AGB) for their national monitoring, measurement, reporting and verification system. Allometric equations to estimate biomass have improved, but remain limited. They rely on destructive sampling; large trees are under-represented in the data used to create them; and they cannot always be applied to different regions. These factors lead to uncertainties and systematic errors in biomass estimations. We developed allometric models to estimate tree AGB in Guyana. These models were based on tree attributes (diameter, height, crown diameter) obtained from terrestrial laser scanning (TLS) point clouds from 72 tropical trees and wood density. We validated our methods and models with data from 26 additional destructively harvested trees. We found that our best TLS-derived allometric models included crown diameter, provided more accurate AGB estimates (R-2 = 0.92-0.93) than traditional pantropical models (R-2 = 0.85-0.89), and were especially accurate for large trees (diameter > 70 cm). The assessed pantropical models underestimated AGB by 4 to 13%. Nevertheless, one pantropical model (Chave et al. 2005 without height) consistently performed best among the pantropical models tested (R-2 = 0.89) and predicted AGB accurately across all size classes-which but for this could not be known without destructive or TLS-derived validation data. Our methods also demonstrate that tree height is difficult to measure in situ, and the inclusion of height in allometric models consistently worsened AGB estimates. We determined that TLS-derived AGB estimates were unbiased. Our approach advances methods to be able to develop, test, and choose allometric models without the need to harvest trees

Improving the topological charge density operator on the lattice

We analyze the properties of a class of improved lattice topological charge density operators, constructed by a smearing-like procedure. By optimizing the choice of the parameters introduced in their definition, we find operators having (i) a much better statistical behavior as estimators of the topological charge density on the lattice, i.e. much less noisy; (ii) a multiplicative renormalization much closer to one; (iii) a large suppression of the perturbative tail in the corresponding lattice topological susceptibility.Comment: 4 pages, to be published in the Proceedings of Lattice 95, uuencoded postscript fil

Finite-size scaling in two-dimensional Ising spin glass models

We study the finite-size behavior of two-dimensional spin-glass models. We consider the +-J model for two different values of the probability of the antiferromagnetic bonds and the model with Gaussian distributed couplings. The analysis of renormalization-group invariant quantities, the overlap susceptibility, and the two-point correlation function confirms that they belong to the same universality class. We analyze in detail the standard finite-size scaling limit in terms of TL^(1/nu) in the +-J model. We find that it holds asymptotically. This result is consistent with the low-temperature crossover scenario in which the crossover temperature, which separates the universal high-temperature region from the discrete low-temperature regime, scales as T_c(L) ~ L^(-theta_S) with theta_S \approx 0.5.Comment: v2: added fig. 9b; 16 pages, 20 fig