Analysis and Calibration of Loran-C Signals in the Lower St. Lawrence Area Using GPS

Loran-C signals along and in the Lower St. Lawrence River, namely between Québec City and the Gaspesia Peninsula on the south shore, between Québec City and Havre-Saint-Pierre on the North Shore, and between Québec City and Anticosti Island in the river, were analyzed using a mobile Loran-C coverage validation and calibration system consisting of analog and digital Loran-C receivers, differential GPS and data logging systems. The road measurements were made successively during February-March and July-August 1991 to analyse seasonal effects. The signals received from the East Coast Canada Chain (5930M, X, Y, Z) and the Northeast U.S. Chain (9960M, W, X) are discussed herein. The Field Strength and Signal to Noise Ratio measurements are compared with predicted values using various models for conductivity and atmospheric noise. The Time Difference (TD) measurements are first compared between forward and reverse runs along the road profiles to ascertain the quality and reliability of the system utilized. The differences between Winter and Summer TD measurements are then analyzed. A relatively small but significant seasonal effect is found. The GPS-derived TD distortions are compared with those derived using various models for the combined effect of the primary, secondary and additional secondary phase lags. The differences between measured and modeled distortions reaches several jis. The effect of these differences on Loran-C positions is found to reach several hundred metres in many cases. Conclusions related to the results presented herein are made, together with recommendations pertaining to the use of these results and future investigations

Uncovering the topology of configuration space networks

The configuration space network (CSN) of a dynamical system is an effective approach to represent the ensemble of configurations sampled during a simulation and their dynamic connectivity. To elucidate the connection between the CSN topology and the underlying free-energy landscape governing the system dynamics and thermodynamics, an analytical soluti on is provided to explain the heavy tail of the degree distribution, neighbor co nnectivity and clustering coefficient. This derivation allows to understand the universal CSN network topology observed in systems ranging from a simple quadratic well to the native state of the beta3s peptide and a 2D lattice heteropolymer. Moreover CSN are shown to fall in the general class of complex networks describe d by the fitness model.Comment: 6 figure

Brane Bremsstrahlung in DBI Inflation

We consider the effect of trapped branes on the evolution of a test brane whose motion generates DBI inflation along a warped throat. The coupling between the inflationary brane and a trapped brane leads to the radiation of non-thermal particles on the trapped brane. We calculate the Gaussian spectrum of the radiated particles and their backreaction on the DBI motion of the inflationary brane. Radiation occurs for momenta lower than the speed of the test brane when crossing the trapped brane. The slowing down effect is either due to a parametric resonance when the interaction time is small compared to the Hubble time or a tachyonic resonance when the interaction time is large. In both cases the motion of the inflationary brane after the interaction is governed by a chameleonic potential,which tends to slow it down. We find that a single trapped brane can hardly slow down a DBI inflaton whose fluctuations lead to the Cosmic Microwave Background spectrum. A more drastic effect is obtained when the DBI brane encounters a tightly spaced stack of trapped branes.Comment: 20 pages, 1 figur

Exploring the use of a participative design in the early development of a predictive test : the importance of physician involvement

In this study, we contribute to the personalized medicine and health care management literature by developing and testing a new participative design approach. We propose that involving gastroenterologists in the development of a predictive test to assist them in their clinical decision-making process for the treatment of inflammatory bowel diseases will increase the likelihood of their acceptance of the innovation. Based on data obtained from 6 focus groups across Canada from a total of 28 physicians, analyses reveal that current tools do not enable discriminating between treatment options to find the best fit for each patient. Physicians expect a new predictive tool to have the capability of showing clear reliability and significant benefits for the patient, while being accessible in a timely manner that facilitates clinical decisions. Physicians also insist on their key role in the implementation process, hence confirming the relevance and importance of participative designs in personalized medicine

Patients’ perception of their involvement in shared treatment decision making : key factors in the treatment of inflammatory bowel disease

Objectives This study aims to characterize the relationships between the quality of the information given by the physician, the involvement of the patient in shared decision making (SDM), and outcomes in terms of satisfaction and anxiety pertaining to the treatment of inflammatory bowel disease (IBD). Methods A Web survey was conducted among 200 Canadian patients affected with IBD. The theoretical model of SDM was adjusted using path analysis. SAS software was used for all statistical analyses. Results The quality of the knowledge transfer between the physician and the patient is significantly associated with the components of SDM: information comprehension, patient involvement and decision certainty about the chosen treatment. In return, patient involvement in SDM is significantly associated with higher satisfaction and, as a result, lower anxiety as regards treatment selection. Conclusions This study demonstrates the importance of involving patients in shared treatment decision making in the context of IBD. Practice implications Understanding shared decision making may motivate patients to be more active in understanding the relevant information for treatment selection, as it is related to their level of satisfaction, anxiety and adherence to treatment. This relationship should encourage physicians to promote shared decision making

On the criticality of inferred models

Advanced inference techniques allow one to reconstruct the pattern of interaction from high dimensional data sets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to a phase transition. On one side, we show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher Information) is directly related to the model's susceptibility. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. On the other, this region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time-scales naturally yield models which are close to criticality.Comment: 6 pages, 2 figures, version to appear in JSTA

Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior

Despite the availability of very detailed data on financial market, agent-based modeling is hindered by the lack of information about real trader behavior. This makes it impossible to validate agent-based models, which are thus reverse-engineering attempts. This work is a contribution to the building of a set of stylized facts about the traders themselves. Using the client database of Swissquote Bank SA, the largest on-line Swiss broker, we find empirical relationships between turnover, account values and the number of assets in which a trader is invested. A theory based on simple mean-variance portfolio optimization that crucially includes variable transaction costs is able to reproduce faithfully the observed behaviors. We finally argue that our results bring into light the collective ability of a population to construct a mean-variance portfolio that takes into account the structure of transaction costsComment: 26 pages, 9 figures, Fig. 8 fixe

A simple mean field model for social interactions: dynamics, fluctuations, criticality

We study the dynamics of a spin-flip model with a mean field interaction. The system is non reversible, spacially inhomogeneous, and it is designed to model social interactions. We obtain the limiting behavior of the empirical averages in the limit of infinitely many interacting individuals, and show that phase transition occurs. Then, after having obtained the dynamics of normal fluctuations around this limit, we analize long time fluctuations for critical values of the parameters. We show that random inhomogeneities produce critical fluctuations at a shorter time scale compared to the homogeneous system.Comment: 37 pages, 2 figure

Beyond inverse Ising model: structure of the analytical solution for a class of inverse problems

I consider the problem of deriving couplings of a statistical model from measured correlations, a task which generalizes the well-known inverse Ising problem. After reminding that such problem can be mapped on the one of expressing the entropy of a system as a function of its corresponding observables, I show the conditions under which this can be done without resorting to iterative algorithms. I find that inverse problems are local (the inverse Fisher information is sparse) whenever the corresponding models have a factorized form, and the entropy can be split in a sum of small cluster contributions. I illustrate these ideas through two examples (the Ising model on a tree and the one-dimensional periodic chain with arbitrary order interaction) and support the results with numerical simulations. The extension of these methods to more general scenarios is finally discussed.Comment: 15 pages, 6 figure

A Semi-Lagrangian scheme for a modified version of the Hughes model for pedestrian flow

In this paper we present a Semi-Lagrangian scheme for a regularized version of the Hughes model for pedestrian flow. Hughes originally proposed a coupled nonlinear PDE system describing the evolution of a large pedestrian group trying to exit a domain as fast as possible. The original model corresponds to a system of a conservation law for the pedestrian density and an Eikonal equation to determine the weighted distance to the exit. We consider this model in presence of small diffusion and discuss the numerical analysis of the proposed Semi-Lagrangian scheme. Furthermore we illustrate the effect of small diffusion on the exit time with various numerical experiments