ParisTech

About: ParisTech is a education organization based out in Paris, France. It is known for research contribution in the topics: Finite element method & Residual stress. The organization has 1888 authors who have published 1965 publications receiving 55532 citations. The organization is also known as: Paris Institute of Technology & ParisTech Développement.

Accounting for biological variability and sampling scale: a multi-scale approach to building epidemic models

Abstract: When one considers the fine-scale spread of an epidemic, one usually knows the sources of biological variability and their qualitative effect on the epidemic process. The force of infection on a susceptible unit depends on the locations and the strengths of the infectious units, and on the environmental and intrinsic factors affecting infectivity and/or susceptibility. The infection probability for the susceptible unit can then be modelled as a function of these factors. Thus, one can build a conceptual model at the fine scale. However, the epidemic is generally observed at a larger scale and one has to build a model adapted to this larger scale. But how can the sources of variation identified at the fine scale be integrated into the model at the larger scale? To answer this question, we present, in the context of plant epidemiology, a multi-scale approach which consists of defining a base model built at the fine scale and upscaling it to match the scale of the sampling and the data. This approach will enable comparing experiments involving different observational processes.

Functional and high-resolution retinal imaging monitoring photoreceptor damage in acute macular neuroretinopathy

Abstract: Background: To report functional and high-resolution retinal imaging abnormalities, including adaptive optics (AO) throughout the course of acute macular neuroretinopathy (AMNR). Methods: Two female patients (four eyes) with a diagnosis of AMNR were observed at the Clinical Investigation Center, CHNO des Quinze-Vingts, Paris, France. The patients underwent detailed ophthalmic examination including best-corrected visual acuity, slit-lamp examination, kinetic and static perimetry, full-field and multifocal electroretinogram, infrared reflectance, autofluorescence imaging and spectral-domain optical coherence tomography (SD-OCT) and AO fundus imaging at presentation and during follow-up. Results: Both cases showed concomitant loss of integrity of the outer retinal structures on SD-OCT, and marked abnormalities on AO imaging with disruption of the visibility of the cone mosaic. In the first case, photoreceptor damage was seen to progress during several weeks before healing. In both cases, there were persistent morphological abnormalities of photoreceptors 1 year after onset. Conclusion: This study further highlights the value of AO fundus imaging to facilitate detection, mapping, and monitoring of damage to the cone outer segments during AMNR. In particular, residual damage to the cone mosaic can be precisely documented.

HIP Tags Privacy Architecture

Abstract: This paper describes an innovative and highly secure networking architecture, dedicated to the Internet of things (IoT). We propose an infrastructure that works with a new type of tags, supporting the recently standardized host identity protocol (HIP). Our main concern is to ensure RFID tags privacy, while enabling things to things communications.

Volterra-Based Nonlinear Compensation in 400 Gb/s WDM Multiband Coherent Optical OFDM Systems

Abstract: We apply a 3rd-order inverse Volterra series nonlinear equalizer to a 400 Gb/s WDM multiband PM-16QAM OFDM signal. IVSTF-NLE provides a 0.6 dB Q-factor improvement and 1 dB nonlinear threshold increase compared to linear equalization.

Multi-temporal SAR classification according to change detection operators

Abstract: Multitemporal SAR images are a very useful source of information for geophysicists, especially for change monitoring. In this paper, a new SAR change detection and monitoring approach is proposed through the analysis of a time series of SAR images covering the same region. The first contribution of this work is the SAR filtering preprocessing step using an extension of the spatial NL-means filter to the temporal domain. Then, the Rayleigh Kullback Leibler measure is used to detect the changes between a reference image and each SAR image. This leads to the second contribution which consists on a temporal classification based on changes images and describing the temporal behaviour of the changing regions.