Identification of a coupled dynamical system

An identification problem for a coupled dynamical system is addressed. More specifically, the system, known from measurements of a scalar quantity, is governed by a set of Langevin equations coupled to a deterministic forcing evolving in a much slower fashion. A statistical method is presented which identifies the deterministic forcing without assuming any parameterization for both sub-systems. This procedure, which is based on a proper orthogonal decomposition applied on probability density functions, works when measurement sampling times remain much smaller than the characteristic time of the forcing. Several test cases are performed

Gravitational Waves from Rotating Proto-Neutron Stars

We study the effects of rotation on the quasi normal modes (QNMs) of a newly born proto neutron star (PNS) at different evolutionary stages, until it becomes a cold neutron star (NS). We use the Cowling approximation, neglecting spacetime perturbations, and consider different models of evolving PNS. The frequencies of the modes of a PNS are considerably lower than those of a cold NS, and are further lowered by rotation; consequently, if QNMs were excited in a sufficiently energetic process, they would radiate waves that could be more easily detectable by resonant-mass and interferometric detectors than those emitted by a cold NS. We find that for high rotation rates, some of the g-modes become unstable via the CFS instability; however, this instability is likely to be suppressed by competing mechanisms before emitting a significant amount of gravitational waves.Comment: 5 pages, proceedings of the 5th Edoardo Amaldi Conference On Gravitational Wave

Credit Default Swaps Drawup Networks: Too Tied To Be Stable?

We analyse time series of CDS spreads for a set of major US and European institutions on a pe- riod overlapping the recent financial crisis. We extend the existing methodology of {\epsilon}-drawdowns to the one of joint {\epsilon}-drawups, in order to estimate the conditional probabilities of abrupt co-movements among spreads. We correct for randomness and for finite size effects and we find significant prob- ability of joint drawups for certain pairs of CDS. We also find significant probability of trend rein- forcement, i.e. drawups in a given CDS followed by drawups in the same CDS. Finally, we take the matrix of probability of joint drawups as an estimate of the network of financial dependencies among institutions. We then carry out a network analysis that provides insights into the role of systemically important financial institutions.Comment: 15 pages, 5 figures, Supplementary informatio

Sufficientness postulates for Gibbs-type priors and hierarchical generalizations

A fundamental problem in Bayesian nonparametrics consists of selecting a prior distribution by assuming that the corresponding predictive probabilities obey certain properties. An early discussion of such a problem, although in a parametric framework, dates back to the seminal work by English philosopher W. E. Johnson, who introduced a noteworthy characterization for the predictive probabilities of the symmetric Dirichlet prior distribution. This is typically referred to as Johnson’s “sufficientness” postulate. In this paper we review some nonparametric generalizations of Johnson’s postulate for a class of nonparametric priors known as species sampling models. In particular we revisit and discuss the “sufficientness” postulate for the two parameter Poisson-Dirichlet prior within the more general framework of Gibbs-type priors and their hierarchical generalizations.. Stefano Favaro is supported by the European Research Council through StG N-BNP 306406. Marco Battiston’s research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) ERC grant agreement number 617071

Multi-echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla

MRI; Multi-echo QSM; Quantitative susceptibility mappingImágen por resonancia magnética; QSM de ecos múltiples; Mapeo cuantitativo de susceptibilidadImatge per ressonància magnètica; QSM de ressò múltiple; Mapeig quantitatiu de susceptibilitatPurpose To compare different multi-echo combination methods for MRI QSM. Given the current lack of consensus, we aimed to elucidate how to optimally combine multi-echo gradient-recalled echo signal phase information, either before or after applying Laplacian-base methods (LBMs) for phase unwrapping or background field removal. Methods Multi-echo gradient-recalled echo data were simulated in a numerical head phantom, and multi-echo gradient-recalled echo images were acquired at 3 Tesla in 10 healthy volunteers. To enable image-based estimation of gradient-recalled echo signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: 1 applied nonlinear phase fitting over TEs before LBMs; 2 applied LBMs to the TE-dependent phase and then combined multiple TEs via either TE-weighted or SNR-weighted averaging; and 2 calculated TE-dependent susceptibility maps via either multi-step or single-step QSM and then combined multiple TEs via magnitude-weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland–Altman) and regional differences between the means (nonparametric tests). Results Nonlinearly fitting the multi-echo phase over TEs before applying LBMs provided the highest regional accuracy of and the lowest phase noise propagation compared to averaging the LBM-processed TE-dependent phase. This result was especially pertinent in high-susceptibility venous regions. Conclusion For multi-echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs.Supported by the UK Engineering and Physical Sciences Research Council (EPSRC), award number: 1489882 (e.b.); by the EPSRC-funded UCL Centre for Doctoral Training in Medical Imaging, grant EP/L016478/1 (a.k.), and the Department of Health's National Institute for Health Research funded Biomedical Research Centre at University College London Hospitals (a.k.); by the UCL Leonard Wolfson Experimental Neurology Centre, grant PR/ylr/18575 (d.l.t) The Queen Square MS Centre, where part of the MRI scans for this work were performed, is supported by grants from the UK MS Society and by the National Institute for Health Research University College London Hospitals Biomedical Research Centre (UCLH/BRC). F. Grussu was supported by PREdICT, a study at the Vall d'Hebron Institute of Oncology in Barcelona funded by AstraZeneca (f.g.), and funding from the postdoctoral fellowships program Beatriu de Pinós (2020 BP 00117), funded by the Secretary of Universities and Research, Government of Catalonia (f.g.

Evolution equations for slowly rotating stars

We present a hyperbolic formulation of the evolution equations describing non-radial perturbations of slowly rotating relativistic stars in the Regge--Wheeler gauge. We demonstrate the stability preperties of the new evolution set of equations and compute the polar w-modes for slowly rotating stars.Comment: 27 pages, 2 figure

Views of Mental Health Professionals on Positive Changes in Service Practices and Staff-User Relationships After One Year of Covid-19 Pandemic in Italy

Abstract This study explored views of mental health services (MHS) professionals regarding positive changes in service practices and organizations, and staff-user relationships after one year of COVID19 in Italy. Professionals from a community-oriented MHS completed online the Questionnaire on MHS Transformations during the COVID-19 pandemic, a 30-item tool developed by a participatory approach and validated. Of the 184 participants, 91.8% felt it was ‘‘true/definitely true’’ that during the pandemic they had informed users on procedures to reduce contagion risks, and 82.1% stated that they had increased telephone contact with users. Sixty-nine percent of professionals reported that staff revised treatment plans according to new needs of care and 78.6% stated that they had been able to mediate between user needs and safe working procedures. Moreover, 79.4% of respondents stated that they had rediscovered the importance of gestures and habits, and 65% that they had gained strength among colleagues to face fear. Fifty-four percent of participants admitted that they had discovered unexpected personal resources in users. Overall, 59.6% of participants stated that they found some positives in the COVID-19 experience. Perceived positive changes was greater among professionals from community facilities vs. those from hospital and residential facilities. In community-oriented MHS, the pandemic offered an opportunity to change practices and rethink the meaning of relationships between people. This data may be useful in generating a more balanced understanding of COVID-19’s impact on MHS and for MHS planning in the pandemic era

Systemic Risk in a Unifying Framework for Cascading Processes on Networks

We introduce a general framework for models of cascade and contagion processes on networks, to identify their commonalities and differences. In particular, models of social and financial cascades, as well as the fiber bundle model, the voter model, and models of epidemic spreading are recovered as special cases. To unify their description, we define the net fragility of a node, which is the difference between its fragility and the threshold that determines its failure. Nodes fail if their net fragility grows above zero and their failure increases the fragility of neighbouring nodes, thus possibly triggering a cascade. In this framework, we identify three classes depending on the way the fragility of a node is increased by the failure of a neighbour. At the microscopic level, we illustrate with specific examples how the failure spreading pattern varies with the node triggering the cascade, depending on its position in the network and its degree. At the macroscopic level, systemic risk is measured as the final fraction of failed nodes, $X^\ast$, and for each of the three classes we derive a recursive equation to compute its value. The phase diagram of $X^\ast$ as a function of the initial conditions, thus allows for a prediction of the systemic risk as well as a comparison of the three different model classes. We could identify which model class lead to a first-order phase transition in systemic risk, i.e. situations where small changes in the initial conditions may lead to a global failure. Eventually, we generalize our framework to encompass stochastic contagion models. This indicates the potential for further generalizations.Comment: 43 pages, 16 multipart figure

Layered social influence promotes multiculturality in the Axelrod model

9 pages, 4 figures, was "Robust multiculturality emerges from layered social influence". In press in Scientific Report