Statistical early-warning indicators based on Auto-Regressive Moving-Average processes

We address the problem of defining early warning indicators of critical transition. To this purpose, we fit the relevant time series through a class of linear models, known as Auto-Regressive Moving-Average (ARMA(p,q)) models. We define two indicators representing the total order and the total persistence of the process, linked, respectively, to the shape and to the characteristic decay time of the autocorrelation function of the process. We successfully test the method to detect transitions in a Langevin model and a 2D Ising model with nearest-neighbour interaction. We then apply the method to complex systems, namely for dynamo thresholds and financial crisis detection.Comment: 5 pages, 4 figure

Probing turbulence intermittency via Auto-Regressive Moving-Average models

We suggest a new approach to probing intermittency corrections to the Kolmogorov law in turbulent flows based on the Auto-Regressive Moving-Average modeling of turbulent time series. We introduce a new index $\Upsilon$ that measures the distance from a Kolmogorov-Obukhov model in the Auto-Regressive Moving-Average models space. Applying our analysis to Particle Image Velocimetry and Laser Doppler Velocimetry measurements in a von K\'arm\'an swirling flow, we show that $\Upsilon$ is proportional to the traditional intermittency correction computed from the structure function. Therefore it provides the same information, using much shorter time series. We conclude that $\Upsilon$ is a suitable index to reconstruct the spatial intermittency of the dissipation in both numerical and experimental turbulent fields.Comment: 5 page

Statistical Analysis of a Close Von Karman Flow

This thesis addresses the statistical modeling of turbulence, focusing on three main aspects: the critical transition from laminarity to turbulence, the effects of the so-called intermittency and the energy dynamics of a turbulent flow. The central part of the thesis consists of six papers, divided into two parts. In Part I we develop two new indices to quantify the proximity to critical transitions in stochastic dynamical systems, with particular attention to the transition from laminarity to turbulence in fluids (Paper A). The two indices are tested on two toy models and then applied to the detection of critical events in a magnetised fluid and in financial time series. We define a third index Y, which quantifies the effects of intermittency and does not require very long time series. This index turns out to be effective in recovering the structure of the turbulent flow (Papers B, C). In Paper D we show that Y is also sensitive to the turbulent behavior of financial markets, providing a possible early warning indicator of the proximity to critical events. In Part II we introduce a new local observable as the arrival times of tracer particles at a particular point in the fluid as a proxy of the turbulent velocity field. We model the universal self-organising structure of this observable in an effective and parsimonious way. In the second paper of Part II, we model the continuous-time dynamics of the energy budget of the turbulent field. We show that this observable can be characterised as the exponential of a stochastic integral on a Lévy basis, under the assumption that the energy transmission across time scales is a multiplicative cascade process

Differential Effects of Brain Disorders on Structural and Functional Connectivity

Different measures of brain connectivity can be defined based on neuroimaging read-outs, including structural and functional connectivity. Neurological and psychiatric conditions are often associated with abnormal connectivity, but comparing the effects of the disease on different types of connectivity remains a challenge. In this paper, we address the problem of quantifying the relative effects of brain disease on structural and functional connectivity at a group level. Within the framework of a graph representation of connectivity, we introduce a kernel two-sample test as an effective method to assess the difference between the patients and control group. Moreover, we propose a common representation space for structural and functional connectivity networks, and a novel test statistics to quantitatively assess differential effects of the disease on different types of connectivity. We apply this approach to a dataset from BTBR mice, a murine model of Agenesis of the Corpus Callosum (ACC), a congenital disorder characterized by the absence of the main bundle of fibers connecting the two hemispheres. We used normo-callosal mice (B6) as a comparator. The application of the proposed methods to this data-set shows that the two types of connectivity can be successfully used to discriminate between BTBR and B6, meaning that both types of connectivity are affected by ACC. However, our novel test statistics shows that structural connectivity is significantly more affected than functional connectivity, consistent with the idea that functional connectivity has a robust topology that can tolerate substantial alterations in its structural connectivity substrate

Compound Climate Events and Extremes in the Midlatitudes: Dynamics, Simulation, and Statistical Characterization

The workshop, conducted virtually due to travel restrictions related to COVID-19, gathered scientists from six countries and focused on the mechanistic understanding, statistical characterization, and modeling of societally relevant compound climate events and extremes in the midlatitudes. These ranged from co-occurring hot–humid or wet–windy extremes, to spatially compounding wet and dry extremes, to temporally compounding hot–wet events and more. The aim was to bring together selected experts studying a diverse range of compound climate events and extremes to present their ongoing work and outline challenges and future developments in this societally relevant field of research

Modelling and analysis of turbulent datasets using Auto Regressive Moving Average processes

International audienceWe introduce a novel way to extract information from turbulent datasets by applying an Auto Regressive Moving Average (ARMA) statistical analysis. Such analysis goes well beyond the analysis of the mean flow and of the fluctuations and links the behavior of the recorded time series to a discrete version of a stochastic differential equation which is able to describe the correlation structure in the dataset. We introduce a new index ϒ that measures the difference between the resulting analysis and the Obukhov model of turbulence, the simplest stochastic model reproducing both Richardson law and the Kolmogorov spectrum. We test the method on datasets measured in a von Kármán swirling flow experiment. We found that the ARMA analysis is well correlated with spatial structures of the flow, and can discriminate between two different flows with comparable mean velocities, obtained by changing the forcing. Moreover, we show that the ϒ is highest in regions where shear layer vortices are present, thereby establishing a link between deviations from the Kolmogorov model and coherent structures. These deviations are consistent with the ones observed by computing the Hurst exponents for the same time series. We show that some salient features of the analysis are preserved when considering global instead of local observables. Finally, we analyze flow configurations with multistability features where the ARMA technique is efficient in discriminating different stability branches of the system

Principal components analysis based control of a multi-dof underactuated prosthetic hand

<p>Abstract</p> <p>Background</p> <p>Functionality, controllability and cosmetics are the key issues to be addressed in order to accomplish a successful functional substitution of the human hand by means of a prosthesis. Not only the prosthesis should duplicate the human hand in shape, functionality, sensorization, perception and sense of body-belonging, but it should also be controlled as the natural one, in the most intuitive and undemanding way. At present, prosthetic hands are controlled by means of non-invasive interfaces based on electromyography (EMG). Driving a multi degrees of freedom (DoF) hand for achieving hand dexterity implies to selectively modulate many different EMG signals in order to make each joint move independently, and this could require significant cognitive effort to the user.</p> <p>Methods</p> <p>A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoFs underactuated prosthetic hand prototype (called CyberHand) with a two dimensional control input, in order to perform the three prehensile forms mostly used in Activities of Daily Living (ADLs). Such Principal Components set has been derived directly from the artificial hand by collecting its sensory data while performing 50 different grasps, and subsequently used for control.</p> <p>Results</p> <p>Trials have shown that two independent input signals can be successfully used to control the posture of a real robotic hand and that correct grasps (in terms of involved fingers, stability and posture) may be achieved.</p> <p>Conclusions</p> <p>This work demonstrates the effectiveness of a bio-inspired system successfully conjugating the advantages of an underactuated, anthropomorphic hand with a PCA-based control strategy, and opens up promising possibilities for the development of an intuitively controllable hand prosthesis.</p

Grecs et indigènes de la Catalogne à la mer Noire

Le programme de travail qui aboutit à ce livre s’inscrit dans le cadre du réseau d’excellence européen Ramses2, initié par la Maison méditerranéenne des sciences de l’homme. Une demi-douzaine de tables rondes ont réuni entre 2006 et 2008, d’un bout à l’autre de la Méditerranée (à Empúries, Aix-en-Provence, Palerme, Naples, Athènes), quelque soixante-dix chercheurs essentiellement français, italiens et espagnols, mais aussi anglais, grecs, bulgares, roumains, canadiens et russes. Il s’agissait d’étudier les rapports d’acculturation entre colons grecs et populations indigènes, en tenant compte des différences géographiques et chronologiques mais aussi de l’historiographie et des habitudes de recherche des diverses institutions. Les nombreuses communications qui ont jalonné les six tables rondes sont ici la plupart du temps précédées de textes introductifs. Une première partie, consacrée aux approches régionales, permet d’illustrer l’état de la recherche dans quelques régions choisies (autour d’Empuries, d’Himère, de Marseille, de Vélia, en Thrace et en mer Noire). La seconde partie, thématique, aborde un certain nombre de thèmes de recherche dans les régions précédentes, mais aussi dans d’autres régions du monde de la colonisation grecque. Le point de vue adopté dans ce livre est d’abord celui de la culture matérielle ; l’approche en est essentiellement archéologique. On se demandera par exemple quels sont les indices archéologiques qui permettent de dire si un site est habité par des Grecs, par des indigènes ou par une population “mixte”, et comment ces indices ont été appréciés selon les périodes et selon les régions. Beaucoup de communications présentent des synthèses régionales ou thématiques, mais une large place est faite également à des sites inédits, pour lesquels on n’a pas hésité à livrer une abondante documentation (plans, matériel de fouille). C’est en effet par le renouvellement de la documentation archéologique que nous pouvons espérer avancer dans la compréhension des rapports d’acculturation entre les colons grecs et les populations locales

Epigenetics in atherosclerosis and inflammation

Introduction Epigenetics explained Epigenetic alterations are reversible Atherosclerosis Epigenetics and association with atherosclerosis Epigenetic regulation of cell activity T cells Monocytes Endothelial cells Smooth muscle cells Chemokines, their receptors and other genes involved in inflammation eNOS iNOS CCL11 (eotaxin) CCR5 Epigenetics in (vascular) inflammation KDM6B Oestrogen receptor COX2 Transcriptional regulation of MHC molecules - the role of CIITA Non-histone targets MicroRNAs Conclusions Atherosclerosis is a multifactorial disease with a severe burden on western society. Recent insights into the pathogenesis of atherosclerosis underscore the importance of chronic inflammation in both the initiation and progression of vascular remodelling. Expression of immunoregulatory molecules by vascular wall components within the atherosclerotic lesions is accordingly thought to contribute to the ongoing inflammatory process. Besides gene regulatory proteins (transcription factors), epigenetic mechanisms also play an essential and fundamental role in the transcriptional control of gene expression. These epigenetic mechanisms change the accessibility of chromatin by DNA methylation and histone modifications. Epigenetic modulators are thus critically involved in the regulation of vascular, immune and tissue-specific gene expression within the atherosclerotic lesion. Importantly, epigenetic processes are reversible and may provide an excellent therapeutic target. The concept of epigenetic regulation is gradually being recognized as an important factor in the pathogenesis of atherosclerosis. Recent research provides an essential link between inflammation and reprogramming of the epigenome. In this review we therefore discuss the basis of epigenetic regulation - and the contribution thereof in the regulation of inflammatory processes in general and during atherosclerosis in particular. Moreover we highlight potential therapeutic interventions based on epigenetic mechanisms.Stemcel biology/Regenerative medicine (incl. bloodtransfusion