The shape of light: how to measure, control and compute complexity?

International audienceWe review a selection of recent results where applications of concepts that harness the “shape of light” in spatial or temporal domain have been applied widely to yield significant advances in areas such as computer-vision sensing with digital holography, spatial shaping of complex laser beams and photonic neural networks.Computer vision is a powerful contact-less measurement tools successfully applied in numerous domains of application, where depth of field and working distances are constrained by the imaging magnification chosen. The use of pseudo-periodic patterns on the target of interest overcomes these usual computer-vision limitations leading to sub-pixel resolutions and making the absolute measurement range independent of the field-of-observation of the imaging system [1]. The approach was also validated using digital holography as imaging method with a tremendous enlargement of the allowed working distance range [2], and seems very well suited to diverse application needs in the micro-robotic and biomedical domains.Principles of digital holography can be used also for spatial shaping of complex laser beams such as Bessel, Airy or arbitrary beams using liquid crystal spatial phase modulators (SLM). Applications in micro&nano-machining by non-diffracting ultrashort laser pulses in various materials have been proposed during recent years [3]. This will also open new perspectives for applications of complex beams for applications in microscopy, optical coherence tomography or ultrafast physics.Photonic systems have revolutionized the hardware implementation of Recurrent Neural Networks and Reservoir Computing, in particular [4]. The fundamental principles of ReservoirComputing strongly facilitate a realization in such complex analog systems. Especially delay systems, which potentially provide large numbers of degrees of freedom even in simple architectures, can efficiently be exploited for information processing. We also demonstrated learning in large-scale neural networks with numerous nonlinear nodes in an architecture using SLM [5]. This last scheme is fully parallel and the passive weights maximize energy efficiency and bandwidth.In high-tech areas such as micro-robotics and photonics, measurement requirements are increasing in terms of high resolution and their controls are based on multi-scale and complex parameters. Increasingly real-time processing remains a big challenge for future applications, where next generation of systems will need to implement new hardware architectures, maybe based on photonic neural networks

Nouvelle-Calédonie

Avec 40000 km2 de récifs et de lagons et plus de 15 000 espèces, la Nouvelle-Calédonie abrite la deuxième plus grande barrière corallienne du monde. À l'heure où les récifs coralliens figurent parmi les écosystèmes les plus menacés de la planète, face aux activités humaines, au réchauffement climatique et à l'acidification des océans, il est devenu impératif de préserver cet exceptionnel héritage environnemental et culturel inscrit au Patrimoine mondial de l'Unesco. Associant des chercheurs de diverses disciplines (sciences de la nature, sciences humaines et sociales) et des acteurs en charge de la gestion des récifs et lagons néo-calédoniens, cet ouvrage présente l'état des connaissances les plus actuelles sur ces espaces. Il permet d'appréhender l'extraordinaire diversité de ces milieux en lien avec l'histoire de l'environnement marin, ainsi que la complexité des relations entre les différents organismes qui les composent. Il accorde également une large place à la manière dont ces écosystèmes offrent aux populations des ressources essentielles et constituent l'un des socles de la culture kanak. Enfin, il interroge la capacité de résilience de ces milieux très vulnérables face aux changements environnementaux globaux et présente les dispositifs mis en place pour leur protection. Rédigé dans un style accessible à tous et très richement illustré, cet ouvrage s'adresse à tout lecteur intéressé par ce patrimoine exceptionnel et, au-delà, il sensibilisera le large public aux enjeux de conservation de la biodiversité, de l'environnement et des cultures

Prognostic value of high-sensitivity measurable residual disease assessment after front-line chemoimmunotherapy in chronic lymphocytic leukemia

International audienceMeasurable residual disease (MRD) status is widely adopted in clinical trials in patients with chronic lymphocytic leukemia (CLL). Findings from FILO group trials (CLL2007FMP, CLL2007SA, CLL2010FMP) enabled investigation of the prognostic value of high-sensitivity (0.7 × 10-5) MRD assessment using flow cytometry, in blood (N = 401) and bone marrow (N = 339), after fludarabine, cyclophosphamide, and rituximab (FCR)-based chemoimmunotherapy in a homogeneous population with long follow-up (median 49.5 months). Addition of low-level positive MRD < 0.01% to MRD ≥ 0.01% increased the proportion of cases with positive MRD in blood by 39% and in bone marrow by 27%. Compared to low-level positive MRD < 0.01%, undetectable MRD was associated with significantly longer progression-free survival (PFS) when using blood (72.2 versus 42.7 months; hazard ratio 0.40, p = 0.0003), but not when using bone marrow. Upon further stratification, positive blood MRD at any level, compared to undetectable blood MRD, was associated with shorter PFS irrespective of clinical complete or partial remission, and a lower 5-year PFS rate irrespective of IGHV-mutated or -unmutated status (all p < 0.05). In conclusion, high-sensitivity (0.0007%) MRD assessment in blood yielded additional prognostic information beyond the current standard sensitivity (0.01%). Our approach provides a model for future determination of the optimal MRD investigative strategy for any regimen