Increases in arterial stiffness and pulse pressure are typical features of the arterial stiffness during aging and are associated with increased risk of cardiovascular complications. Cellular and molecular determinants of arterial stiffness have not been completely elucidated. Clinically, the carotid-femoral pulse wave velocity (PWV) is the gold standard parameter of arterial stiffness. A recent genome-wide scan of the Framingham Heart Study population has shown that arterial stiffness and mean and pulsatile components of blood pressure are heritable and map to separate the genetic loci in humans, suggesting that distinct genes may modulate these two phenotypes. This chapter details the recent knowledge on the influence of genetic determinants and telomere length on the development of age-related phenotypes. Recent genetic studies have revealed specific genes contributing to arterial stiffening. Available data on genome-wide association (GWA) have been initiated on PWV and have identified common genetic variation in specific loci or single-nucleotide polymorphisms (SNP) significantly associated with PWV. Telomere length at birth is strongly determined genetically and is the main determinant of leukocytes’ telomere length (LTL) later in life. Short LTL is associated with increased risk of stiffness and atherosclerosis of the carotid artery, atherosclerotic heart disease, and diminished survival in the elderly.
International audience; Orchestras of Digital Musical Instruments (DMIs) enable new musical collaboration possibilities, extending those of acoustic and electric orchestras. However the creation and development of these orchestras remain constrained. In fact, each new musical collaboration system or orchestra piece relies on a fixed number of musicians, a fixed set of instruments (often only one), and a fixed subset of possible modes of collaboration. In this paper, we describe a unified framework that enables the design of Digital Orchestras with potentially different DMIs and an expand-able set of collaboration modes. It relies on research done on analysis and classification of traditional and digital orchestras, on research in Collaborative Virtual Environments, and on interviews of musicians and composers. The BOEUF framework consists of a classification of modes of collaboration and a set of components for modelling digital orchestras. Integrating this framework into DMIs will enable advanced musical collaboration modes to be used in any digital orchestra, including spontaneous jam sessions.
International audience; We study strategies of approximate pattern matching that exploit bidirectional text indexes, extending and generalizing ideas of . We introduce a formalism, called search schemes, to specify search strate-gies of this type, then develop a probabilistic measure for the efficiency of a search scheme, prove several combinatorial results on efficient search schemes, and finally, provide experimental computations supporting the superiority of our strategies.
Part 2: Infrastructure Protection; International audience; State estimation is vital to the stability of control systems, especially in power systems, which rely heavily on measurement devices installed throughout wide-area power networks. Several researchers have analyzed the problems arising from bad data injection and topology errors, and have proposed protection and mitigation schemes. This chapter employs hierarchical state estimation based on the common weighted-least-squares formulation to study the propagation of faults in intermediate and top-level state estimates as a result of measurement reordering attacks on a single region in the bottom level. Although power grids are equipped with modern defense mechanisms such as those recommended by the ISO/IEC 62351 standard, reordering attacks are still possible. This chapter concentrates on how an inexpensive data swapping attack in one region in the lower level can influence the accuracy of other regions in the same level and upper levels, and force the system towards undesirable states. The results are validated using the IEEE 118-bus test case.
International audience; The use of land cover mappings built using remotely sensed imagery data has become increasingly popular in recent years. However, these mappings are ultimately only models. Consequently, it is vital for one to be able to assess and verify the quality of a mapping and quantify uncertainty for any estimates that are derived from them in a reliable manner.For this, the use of validation sets and error matrices is a long standard practice in land cover mapping applications. In this paper, we review current state of the art methods for quantifying uncertainty for estimates obtained from error matrices in a land cover mapping context. Specifically, we review methods based on their transparency, generalisability, suitability when stratified sampling and suitability in low count situations. This is done with the use of a third-party case study to act as a motivating and demonstrative example throughout the paper.The main finding of this paper is there is a major issue of transparency for methods that quantify uncertainty in terms of confidence intervals (frequentist methods). This is primarily because of the difficulty of analysing nominal coverages in common situations. Effectively, this leaves one without the necessary tools to know when a frequentist method is reliable in all but a few niche situations. The paper then discusses how a Bayesian approach may be better suited as a default method for uncertainty quantification when judged by our criteria.
Genome-wide screens are a powerful technique to dissect the complex network of genes regulating diverse cellular phenotypes. The recent adaptation of the CRISPR-Cas9 system for genome engineering has revolutionized functional genomic screening. Here, we present protocols used to introduce Cas9 into human lymphoma cell lines, produce high-titer lentivirus of a genome-wide sgRNA library, transduce and culture cells during the screen, isolate genomic DNA, and prepare a custom library for next-generation sequencing. These protocols were tailored for loss-of-function CRISPR screens in human lymphoma cell lines but are highly amenable for other experimental purposes.
We discuss the use of parametric phase-diverse phase retrieval to characterize and optimize the transmitted wavefront of a high-contrast apodized pupil coronagraph with and without an apodizer. We apply our method to correct the transmitted wavefront of the HiCAT (High contrast imager for Complex Aperture Telescopes) coronagraphic testbed. This correction requires a series of calibration steps, which we describe. The correction improves the system wavefront from 16 nm RMS to 3.0 nm RMS for the case where a uniform circular aperture is in place. We further measure the wavefront with the apodizer in place to be 11.7 nm RMS. Improvement to the apodized pupil phase retrieval process is necessary before a correction based on this measurement can be applied.
Part 6: Network Modeling; International audience; Mobile Adhoc Networks (MANET) are susceptible to jamming attacks which can inhibit data transmissions. There has been considerable work done in the detection of external jamming attacks. However, detection of insider jamming attack in MANET has not received enough attention. The presence of an insider node that has constantly monitored the network and is privy to the network secrets can acquire sufficient information to cause irreparable damage. In this paper we propose a framework for a novel reputation-based coalition game between multiple players in a MANET to prevent internal attacks caused by an erstwhile legitimate node. A grand coalition is formed which will make a strategic security defense decision by depending on the stored transmission rate and reputation for each individual node in the coalition. Our results show that the simulation of the reputation-based coalition game would help improve the network’s defense strategy while also reducing false positives that results from the incorrect classification of unfortunate legitimate nodes as insider jammers.
International audience; In this paper, we study the effect of smartphone camera exposure on the performance of optical camera communications (OCC) link. The exposure parameters of image sensor sensitivity (ISO), aperture and shutter speed are included. A static OCC link with a 8 × 8 red, green and blue (RGB) LED array employed as the transmitter and a smartphone camera as the receiver is demonstrated to verify the study. Signal-to-noise ratio (SNR) analysis at different ISO values, the effect of aperture and shutter speed on communication link quality is performed. While SNRs of 20.6 dB and 16.9 dB are measured at 1 m and 2 m transmission distance, respectively for a ISO value of 100, they are decreased to 17.4 dB and 13.32 dB for a ISO of 800. The bit error rate (BER) of a 1 m long OCC link with a camera's shutter speed of 1/6000 s is 1.3 × 10 −3 (i.e., below the forward error correction BER limit of 3.8 × 10 −3) and is dropped to 0.0125 at a shutter speed of 1/20 s. This study provides insight of the basic smartphone settings and the exposure adjustment for further complex OCC links.
Wildfire prediction from Earth Observation (EO) data has gained much attention in the past years, through the development of connected sensors and weather satellites. Nowadays, it is possible to extract knowledge from collected EO data and to learn from this knowledge without human intervention to trigger wildfire alerts. However, exploiting knowledge extracted from multiple EO data sources at run-time and predicting wildfire raise multiple challenges. One major challenge is to provide dynamic construction of service composition plans, according to the data obtained from sensors. In this paper, we present a knowledge-driven Machine Learning approach that relies on historical data related to wildfire observations to guide the collection of EO data and to automatically and dynamically compose services for triggering wildfire alerts.