Optoelectronic Reservoir Computing

Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing time dependent data. The basic scheme of reservoir computing consists of a non linear recurrent dynamical system coupled to a single input layer and a single output layer. Within these constraints many implementations are possible. Here we report an opto-electronic implementation of reservoir computing based on a recently proposed architecture consisting of a single non linear node and a delay line. Our implementation is sufficiently fast for real time information processing. We illustrate its performance on tasks of practical importance such as nonlinear channel equalization and speech recognition, and obtain results comparable to state of the art digital implementations.Comment: Contains main paper and two Supplementary Material

Real time noise and wavelength correlations in octave-spanning supercontinuum generation

We use dispersive Fourier transformation to measure shot-to-shot spectral instabilities in femtosecond supercontinuum generation. We study both the onset phase of supercontinuum generation with distinct dispersive wave generation, as well as a highly-unstable supercontinuum regime spanning an octave in bandwidth. Wavelength correlation maps allow interactions between separated spectral components to be identified, even when such interactions are not apparent in shot-to-shot or average measurements. Experimental results are interpreted using numerical simulations. Our results show the clear advantages of dispersive Fourier transformation for studying spectral noise during supercontinuum generation.Comment: 14 pages, 5 figure

Real-time full bandwidth measurement of spectral noise in supercontinuum generation

The ability to measure real-time fluctuations of ultrashort pulses propagating in optical fiber has provided significant insights into fundamental dynamical effects such as modulation instability and the formation of frequency-shifting rogue wave solitons. We report here a detailed study of real-time fluctuations across the full bandwidth of a fiber supercontinuum which directly reveals the significant variation in measured noise statistics across the spectrum, and which allows us to study correlations between widely separated spectral components. For two different propagation distances corresponding to the onset phase of spectral broadening and the fully-developed supercontinuum, we measure real time noise across the supercontinuum bandwidth, and we quantify the supercontinuum noise using statistical higher-order moments and a frequency-dependent intensity correlation map. We identify correlated spectral regions within the supercontinuum associated with simultaneous sideband generation, as well as signatures of pump depletion and soliton-like pump dynamics. Experimental results are in excellent agreement with simulations

Deterministic polarization chaos from a laser diode

Fifty years after the invention of the laser diode and fourty years after the report of the butterfly effect - i.e. the unpredictability of deterministic chaos, it is said that a laser diode behaves like a damped nonlinear oscillator. Hence no chaos can be generated unless with additional forcing or parameter modulation. Here we report the first counter-example of a free-running laser diode generating chaos. The underlying physics is a nonlinear coupling between two elliptically polarized modes in a vertical-cavity surface-emitting laser. We identify chaos in experimental time-series and show theoretically the bifurcations leading to single- and double-scroll attractors with characteristics similar to Lorenz chaos. The reported polarization chaos resembles at first sight a noise-driven mode hopping but shows opposite statistical properties. Our findings open up new research areas that combine the high speed performances of microcavity lasers with controllable and integrated sources of optical chaos.Comment: 13 pages, 5 figure

Elevated soluble Flt1 mediates an anti-angiogenic state in patients with ANCA-associated vasculitis

International audiencen.

The Clinical Variability of Maternally Inherited Diabetes and Deafness Is Associated with the Degree of Heteroplasmy in Blood Leukocytes

Context: Maternally inherited diabetes and deafness (MIDD) is a rare form of diabetes with a matrilineal transmission, sensorineural hearing loss, and macular pattern dystrophy due to an A to G transition at position 3243 of mitochondrial DNA (mtDNA) (m.3243A>G). The phenotypic heterogeneity of MIDD may be the consequence of different levels of mutated mtDNA among mitochondria in a given tissue. Objective: The aim of the present study was thus to ascertain the correlation between the severity of the phenotype in patients with MIDD and the level of heteroplasmy in the blood leukocytes. Participants: The GEDIAM prospective multicenter register was initiated in 1995. Eighty-nine Europid patients from this register, with MIDD and the mtDNA 3243A>G mutation, were included. Patients with MELAS (mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes) or with mitochondrial diabetes related to other mutations or to deletions of mtDNA were excluded. Results: A significant negative correlation was found between levels of heteroplasmy and age of the patients at the time of sampling for molecular analysis, age at the diagnosis of diabetes, and body mass index. After adjustment for age at sampling for molecular study and gender, the correlation between heteroplasmy levels and age at the diagnosis of diabetes was no more significant. The two other correlations remained significant. A significant positive correlation between levels of heteroplasmy and HbA1c was also found and remained significant after adjustment for age at molecular sampling and gender. Conclusions: These results support the hypothesis that heteroplasmy levels are at least one of the determinants of the severity of the phenotype in MIDD. Heteroplasmy levels are at least one of the determinants of the severity of the phenotype of maternally inherited diabetes and deafness

Angiopoietin 2 Alters Pancreatic Vascularization in Diabetic Conditions

Islet vascularization, by controlling beta-cell mass expansion in response to increased insulin demand, is implicated in the progression to glucose intolerance and type 2 diabetes. We investigated how hyperglycaemia impairs expansion and differentiation of the growing pancreas. We have grafted xenogenic (avian) embryonic pancreas in severe combined immuno-deficient (SCID) mouse and analyzed endocrine and endothelial development in hyperglycaemic compared to normoglycaemic conditions. 14 dpi chicken pancreases were grafted under the kidney capsule of normoglycaemic or hyperglycaemic, streptozotocin-induced, SCID mice and analyzed two weeks later. Vascularization was analyzed both quantitatively and qualitatively using either in situ hybridization with both mouse- and chick-specific RNA probes for VEGFR2 or immunohistochemistry with an antibody to nestin, a marker of endothelial cells that is specific for murine cells. To inhibit angiopoietin 2 (Ang2), SCID mice were treated with 4 mg/kg IP L1-10 twice/week. In normoglycaemic condition, chicken-derived endocrine and exocrine cells developed well and intragraft vessels were lined with mouse endothelial cells. When pancreases were grafted in hyperglycaemic mice, growth and differentiation of the graft were altered and we observed endothelial discontinuities, large blood-filled spaces. Vessel density was decreased. These major vascular anomalies were associated with strong over-expression of chick-Ang2. To explore the possibility that Ang2 over-expression could be a key step in vascular disorganization induced by hyperglycaemia, we treated mice with L1-10, an Ang-2 specific inhibitor. Inhibition of Ang2 improved vascularization and beta-cell density. this work highligghted an important role of Ang2 in pancreatic vascular defects induced by hyperglycemia

Chimera-like states in modular neural networks

Chimera states, namely the coexistence of coherent and incoherent behavior, were previously analyzed in complex networks. However, they have not been extensively studied in modular networks. Here, we consider a neural network inspired by the connectome of the C. elegans soil worm, organized into six interconnected communities, where neurons obey chaotic bursting dynamics. Neurons are assumed to be connected with electrical synapses within their communities and with chemical synapses across them. As our numerical simulations reveal, the coaction of these two types of coupling can shape the dynamics in such a way that chimera-like states can happen. They consist of a fraction of synchronized neurons which belong to the larger communities, and a fraction of desynchronized neurons which are part of smaller communities. In addition to the Kuramoto order parameter ?, we also employ other measures of coherence, such as the chimera-like ? and metastability ? indices, which quantify the degree of synchronization among communities and along time, respectively. We perform the same analysis for networks that share common features with the C. elegans neural network. Similar results suggest that under certain assumptions, chimera-like states are prominent phenomena in modular networks, and might provide insight for the behavior of more complex modular networks