An optimal IV technique for identifying continuous-time transfer function model of multiple input systems

An instrumental variable method for continuous-time model identification is proposed for multiple input single output systems where the characteristic polynomials of the transfer functions associated with each input are not constrained to be identical. An associated model order determination procedure is shown to be reasonably successful. Monte Carlo simulation analyses are used to demonstrate the properties and general robustness of the model order selection and parameter estimation schemes. The results obtained to model a winding process and an industrial binary distillation column illustrate the practical applicability of the proposed identification scheme

Very Small Strangelets

We study the stability of small strangelets by employing a simple model of strange matter as a gas of non-interacting fermions confined in a bag. We solve the Dirac equation and populate the energy levels of the bag one quark at a time. Our results show that for system parameters such that strange matter is unbound in bulk, there may still exist strangelets with $A<100$ that are stable and/or metastable. The lifetime of these strangelets may be too small to detect in current accelerator experiments, however.Comment: 13 pages, MIT CTP#217

Dimensionality Reduction, Classification and Reconstruction Problems in Statistical Learning Approaches

Statistical learning theory explores ways of estimating functional dependency from a given collection of data. The specific sub-area of supervised statistical learning covers important models like Perceptron, Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA). In this paper we review the theory of such models and compare their separating hypersurfaces for extracting group-differences between samples. Classification and reconstruction are the main goals of this comparison. We show recent advances in this topic of research illustrating their application on face and medical image databases.Statistical learning theory explores ways of estimating functional dependency from a given collection of data. The specific sub-area of supervised statistical learning covers important models like Perceptron, Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA). In this paper we review the theory of such models and compare their separating hypersurfaces for extracting group-differences between samples. Classification and reconstruction are the main goals of this comparison. We show recent advances in this topic of research illustrating their application on face and medical image databases

Color plasma oscillation in strangelets

The dispersion relation and damping rate of longitudinal color plasmons in finite strange quark matter (strangelets) are evaluated in the limits of weak coupling, low temperature, and long wavelength. The property of the QCD vacuum surrounding a strangelet makes the frequency of the plasmons nearly the same as the color plasma frequency of bulk matter. The plasmons are damped by their coupling with individual excitations of particle-hole pairs of quarks, of which the energy levels are discretized by the boundary. For strangelets of macroscopic size, the lifetime of the plasmons is found to be proportional to the size, as in the case of the usual plasma oscillations in metal nanoparticles.Comment: 9 pages (REVTeX), 2 Postscript figures, to be published in Phys. Rev.

On a discrete Davey-Stewartson system

We propose a differential difference equation in ${\mathcal R}^1\times {\mathcal Z}^2$ and study it by Hirota's bilinear method. This equation has a singular continuum limit into a system which admits the reduction to the Davey-Stewartson equation. The solutions of this discrete DS system are characterized by Casorati and Grammian determinants. Based on the bilinear form of this discrete DS system, we construct the bilinear B\"{a}cklund transformation which enables us to obtain its Lax pair.Comment: 12 pages, 2 figure

Patterns of impact resulting from a 'sit less, move more' web-based program in sedentary office employees.

PURPOSE: Encouraging office workers to 'sit less and move more' encompasses two public health priorities. However, there is little evidence on the effectiveness of workplace interventions for reducing sitting, even less about the longer term effects of such interventions and still less on dual-focused interventions. This study assessed the short and mid-term impacts of a workplace web-based intervention (Walk@WorkSpain, W@WS; 2010-11) on self-reported sitting time, step counts and physical risk factors (waist circumference, BMI, blood pressure) for chronic disease. METHODS: Employees at six Spanish university campuses (n=264; 42±10 years; 171 female) were randomly assigned by worksite and campus to an Intervention (used W@WS; n=129; 87 female) or a Comparison group (maintained normal behavior; n=135; 84 female). This phased, 19-week program aimed to decrease occupational sitting time through increased incidental movement and short walks. A linear mixed model assessed changes in outcome measures between the baseline, ramping (8 weeks), maintenance (11 weeks) and follow-up (two months) phases for Intervention versus Comparison groups. RESULTS: A significant 2 (group) × 2 (program phases) interaction was found for self-reported occupational sitting (F[3]=7.97, p=0.046), daily step counts (F[3]=15.68, p=0.0013) and waist circumference (F[3]=11.67, p=0.0086). The Intervention group decreased minutes of daily occupational sitting while also increasing step counts from baseline (446±126; 8,862±2,475) through ramping (+425±120; 9,345±2,435), maintenance (+422±123; 9,638±3,131) and follow-up (+414±129; 9,786±3,205). In the Comparison group, compared to baseline (404±106), sitting time remained unchanged through ramping and maintenance, but decreased at follow-up (-388±120), while step counts diminished across all phases. The Intervention group significantly reduced waist circumference by 2.1cms from baseline to follow-up while the Comparison group reduced waist circumference by 1.3cms over the same period. CONCLUSIONS: W@WS is a feasible and effective evidence-based intervention that can be successfully deployed with sedentary employees to elicit sustained changes on "sitting less and moving more"

A reduction of the resonant three-wave interaction to the generic sixth Painleve' equation

Among the reductions of the resonant three-wave interaction system to six-dimensional differential systems, one of them has been specifically mentioned as being linked to the generic sixth Painleve' equation P6. We derive this link explicitly, and we establish the connection to a three-degree of freedom Hamiltonian previously considered for P6.Comment: 13 pages, 0 figure, J. Phys. A Special issue "One hundred years of Painleve' VI

Meditation-induced effects on whole-brain structural and effective connectivity

In the past decades, there has been a growing scientific interest in characterizing neural correlates of meditation training. Nonetheless, the mechanisms underlying meditation remain elusive. In the present work, we investigated meditation-related changes in functional dynamics and structural connectivity (SC). For this purpose, we scanned experienced meditators and control (naive) subjects using magnetic resonance imaging (MRI) to acquire structural and functional data during two conditions, resting-state and meditation (focused attention on breathing). In this way, we aimed to characterize and distinguish both short-term and long-term modifications in the brain's structure and function. First, to analyze the fMRI data, we calculated whole-brain effective connectivity (EC) estimates, relying on a dynamical network model to replicate BOLD signals' spatio-temporal structure, akin to functional connectivity (FC) with lagged correlations. We compared the estimated EC, FC, and SC links as features to train classifiers to predict behavioral conditions and group identity. Then, we performed a network-based analysis of anatomical connectivity. We demonstrated through a machine-learning approach that EC features were more informative than FC and SC solely. We showed that the most informative EC links that discriminated between meditators and controls involved several large-scale networks mainly within the left hemisphere. Moreover, we found that differences in the functional domain were reflected to a smaller extent in changes at the anatomical level as well. The network-based analysis of anatomical pathways revealed strengthened connectivity for meditators compared to controls between four areas in the left hemisphere belonging to the somatomotor, dorsal attention, subcortical and visual networks. Overall, the results of our whole-brain model-based approach revealed a mechanism underlying meditation by providing causal relationships at the structure-function level

Thirty Years After Michael E. Porter: What Do We Know About Business Exit?

Although a business exit is an important corporate change initiative, the buyer’s side seems to be more appealing to management researchers than the seller’s because acquisitions imply growth, i.e., success. Yet from an optimistic viewpoint, business exit can effectively create value for the selling company. In this paper we attempt to bring the relevance of the seller’s side back into our consciousness by asking: What do we know about business exit? We start our exploration with Porter (1976), focusing on literature that investigates the antecedents of, barriers to, and outcomes of business exit. We also include studies from related fields such as finance and economics.1 Through this research we determine three clusters of findings: factors promoting business exit, exit barriers, and exit outcomes. Overall, it is the intention of this paper to highlight the importance of business exit for research and practice. Knowing what we know about business exits and their high financial value we should bear in mind that exit need not mean failure but a new beginning for a corporation