The Charter of the French Language and its regulations govern the consultation of English-language content.
Professeur titulaire, Faculté des sciences et de génie, Université Laval
Chercheur, CERVO
Axe de recherche:
Neurosciences cellulaires et moléculaires
Conception optique (design, théorie des aberrations, optomécanique)
Métrologie optique (interférométrie, CGH, aphérique)
Optique adaptative (simulation, miroir déformable)
Optique en environnement extrême (conception, métrologie, cryogénique, spatial)
Éclairage extérieur longue durée (DEL, modèle de vieillissement, norme, gestion thermique, optique)
Marc Picheral; Camille Catalano; Denis Brousseau; Hervé Claustre; Laurent Coppola; Edouard Leymarie; Jérôme Coindat; Fabio Dias; Sylvain Fevre; Lionel Guidi; Jean Olivier Irisson; Louis Legendre; Fabien Lombard; Laurent Mortier; Christophe Penkerch; Andreas Rogge; Catherine Schmechtig; Simon Thibault; Thierry Tixier; Anya Waite; Lars Stemmann
The Underwater Vision Profiler 6: an imaging sensor of particle size spectra and plankton, for autonomous and cabled platforms Article de journal
Dans: Limnol Oceanogr Methods, vol. 20, no 2, p. 115–129, 2022, ISSN: 1541-5856.
@article{pmid35909413,
title = {The Underwater Vision Profiler 6: an imaging sensor of particle size spectra and plankton, for autonomous and cabled platforms},
author = {Marc Picheral and Camille Catalano and Denis Brousseau and Hervé Claustre and Laurent Coppola and Edouard Leymarie and Jérôme Coindat and Fabio Dias and Sylvain Fevre and Lionel Guidi and Jean Olivier Irisson and Louis Legendre and Fabien Lombard and Laurent Mortier and Christophe Penkerch and Andreas Rogge and Catherine Schmechtig and Simon Thibault and Thierry Tixier and Anya Waite and Lars Stemmann},
doi = {10.1002/lom3.10475},
issn = {1541-5856},
year = {2022},
date = {2022-02-01},
journal = {Limnol Oceanogr Methods},
volume = {20},
number = {2},
pages = {115--129},
abstract = {Autonomous and cabled platforms are revolutionizing our understanding of ocean systems by providing 4D monitoring of the water column, thus going beyond the reach of ship-based surveys and increasing the depth of remotely sensed observations. However, very few commercially available sensors for such platforms are capable of monitoring large particulate matter (100-2000 m) and plankton despite their important roles in the biological carbon pump and as trophic links from phytoplankton to fish. Here, we provide details of a new, commercially available scientific camera-based particle counter, specifically designed to be deployed on autonomous and cabled platforms: the Underwater Vision Profiler 6 (UVP6). Indeed, the UVP6 camera-and-lighting and processing system, while small in size and requiring low power, provides data of quality comparable to that of previous much larger UVPs deployed from ships. We detail the UVP6 camera settings, its performance when acquiring data on aquatic particles and plankton, their quality control, analysis of its recordings, and streaming from in situ acquisition to users. In addition, we explain how the UVP6 has already been integrated into platforms such as BGC-Argo floats, gliders and long-term mooring systems (autonomous platforms). Finally, we use results from actual deployments to illustrate how UVP6 data can contribute to addressing longstanding questions in marine science, and also suggest new avenues that can be explored using UVP6-equipped autonomous platforms.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mishal Ashraf; Sharika Mohanan; Byu Ri Sim; Anthony Tam; Kiamehr Rahemipour; Denis Brousseau; Simon Thibault; Alexander D Corbett; Gil Bub
Random access parallel microscopy Article de journal
Dans: Elife, vol. 10, 2021, ISSN: 2050-084X.
@article{pmid33432922,
title = {Random access parallel microscopy},
author = {Mishal Ashraf and Sharika Mohanan and Byu Ri Sim and Anthony Tam and Kiamehr Rahemipour and Denis Brousseau and Simon Thibault and Alexander D Corbett and Gil Bub},
doi = {10.7554/eLife.56426},
issn = {2050-084X},
year = {2021},
date = {2021-01-01},
journal = {Elife},
volume = {10},
abstract = {We introduce a random-access parallel (RAP) imaging modality that uses a novel design inspired by a Newtonian telescope to image multiple spatially separated samples without moving parts or robotics. This scheme enables near-simultaneous image capture of multiple petri dishes and random-access imaging with sub-millisecond switching times at the full resolution of the camera. This enables the RAP system to capture long-duration records from different samples in parallel, which is not possible using conventional automated microscopes. The system is demonstrated by continuously imaging multiple cardiac monolayer and preparations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Madison Rilling; Guillaume Allain; Simon Thibault; Louis Archambault
Tomographic-based 3D scintillation dosimetry using a three-view plenoptic imaging system Article de journal
Dans: Med Phys, vol. 47, no 8, p. 3636–3646, 2020, ISSN: 2473-4209.
@article{pmid32445200,
title = {Tomographic-based 3D scintillation dosimetry using a three-view plenoptic imaging system},
author = {Madison Rilling and Guillaume Allain and Simon Thibault and Louis Archambault},
doi = {10.1002/mp.14213},
issn = {2473-4209},
year = {2020},
date = {2020-08-01},
journal = {Med Phys},
volume = {47},
number = {8},
pages = {3636--3646},
abstract = {PURPOSE: To demonstrate the feasibility of a three-plenoptic camera projection, scintillation-based dosimetry system for measuring three-dimensional (3D) dose distributions of static photon radiation fields.nnMETHODS: Static x-ray photon beams were delivered to a cubic plastic scintillator volume embedded within acrylic blocks. For each beam, three orthogonal projections of the scintillating light emission were recorded using a multifocus plenoptic camera. Experimental 3D reconstructions of the light distribution were obtained using an iterative maximum likelihood-expectation maximization (ML-EM) algorithm. For this purpose, the elements of the system matrix representing the contribution of the scintillator volume voxels to the camera sensor pixels were calculated using optical design software. A reconstruction-specific correction was applied to light reconstructions to account for scintillating light imaged by the camera but not directly resulting from dose deposition. Cross beam profiles (CBPs) and percentage depth dose (PDD) curves were compared to treatment planning system data for square fields. Three-dimensional and 3D gamma analyses were performed for concave-shaped dose distributions and the Pearson correlation coefficient and reconstruction error were employed to assess the quality of the measured relative 3D dose distributions.nnRESULTS: A full and accurate model of the plenoptic camera-based scintillation dosimetry system was implemented using the light ray tracing capabilities of optical design software. With this model, light distributions were successfully reconstructed over a volume of 60 × 60 × 60 mm at a resolution of 2 mm. For relative 3D measurements of square radiation fields of , and compared with treatment planning system reference distributions, the maximum root-mean-square error of the CBPs evaluated at two different depths was of 3.2%, 1.2%, and 1.1%, respectively; as for the corresponding linearly fitted PDDs of the square fields, the slopes of the reconstructed dose distributions overestimated those of the reference distributions by at most 0.2%/ cm. The 2D gamma passing rate with a criterion of 2%/2 mm for the concave-shaped photon field was of 61.6%, 66.1%, and 76.4% using one, two, and three plenoptic projections; the respective success rates become 77.1%, 87.5%, and 94.9% using a criterion of 3%/3 mm. The 3D correlation coefficient for the corresponding reconstructions was of 0.688, 0.905, and 0.976, respectively.nnCONCLUSIONS: Three-dimensional light distributions emitted from within a plastic scintillator volume were successfully recovered using optical design software to establish a complete tomographic model of a plenoptic camera-based prototype. The tomographic model can equivalently extend to dynamic dose delivery measurements, providing temporal resolution limited by the camera's exposure time. This feasibility study enables a simplified design-to-implementation process for volumetric scintillation dosimetry prototypes toward fully meeting the clinical needs of 3D dose measurements for static and dynamic delivery techniques.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Joel Lehman; Jeff Clune; Dusan Misevic; Christoph Adami; Lee Altenberg; Julie Beaulieu; Peter J Bentley; Samuel Bernard; Guillaume Beslon; David M Bryson; Nick Cheney; Patryk Chrabaszcz; Antoine Cully; Stephane Doncieux; Fred C Dyer; Kai Olav Ellefsen; Robert Feldt; Stephan Fischer; Stephanie Forrest; Antoine Fŕenoy; Christian Gagńe; Leni Le Goff; Laura M Grabowski; Babak Hodjat; Frank Hutter; Laurent Keller; Carole Knibbe; Peter Krcah; Richard E Lenski; Hod Lipson; Robert MacCurdy; Carlos Maestre; Risto Miikkulainen; Sara Mitri; David E Moriarty; Jean-Baptiste Mouret; Anh Nguyen; Charles Ofria; Marc Parizeau; David Parsons; Robert T Pennock; William F Punch; Thomas S Ray; Marc Schoenauer; Eric Schulte; Karl Sims; Kenneth O Stanley; François Taddei; Danesh Tarapore; Simon Thibault; Richard Watson; Westley Weimer; Jason Yosinski
The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities Article de journal
Dans: Artif Life, vol. 26, no 2, p. 274–306, 2020, ISSN: 1530-9185.
@article{pmid32271631,
title = {The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities},
author = {Joel Lehman and Jeff Clune and Dusan Misevic and Christoph Adami and Lee Altenberg and Julie Beaulieu and Peter J Bentley and Samuel Bernard and Guillaume Beslon and David M Bryson and Nick Cheney and Patryk Chrabaszcz and Antoine Cully and Stephane Doncieux and Fred C Dyer and Kai Olav Ellefsen and Robert Feldt and Stephan Fischer and Stephanie Forrest and Antoine Fŕenoy and Christian Gagńe and Leni Le Goff and Laura M Grabowski and Babak Hodjat and Frank Hutter and Laurent Keller and Carole Knibbe and Peter Krcah and Richard E Lenski and Hod Lipson and Robert MacCurdy and Carlos Maestre and Risto Miikkulainen and Sara Mitri and David E Moriarty and Jean-Baptiste Mouret and Anh Nguyen and Charles Ofria and Marc Parizeau and David Parsons and Robert T Pennock and William F Punch and Thomas S Ray and Marc Schoenauer and Eric Schulte and Karl Sims and Kenneth O Stanley and François Taddei and Danesh Tarapore and Simon Thibault and Richard Watson and Westley Weimer and Jason Yosinski},
doi = {10.1162/artl_a_00319},
issn = {1530-9185},
year = {2020},
date = {2020-01-01},
journal = {Artif Life},
volume = {26},
number = {2},
pages = {274--306},
abstract = {Evolution provides a creative fount of complex and subtle adaptations that often surprise the scientists who discover them. However, the creativity of evolution is not limited to the natural world: Artificial organisms evolving in computational environments have also elicited surprise and wonder from the researchers studying them. The process of evolution is an process that transcends the substrate in which it occurs. Indeed, many researchers in the field of digital evolution can provide examples of how their evolving algorithms and organisms have creatively subverted their expectations or intentions, exposed unrecognized bugs in their code, produced unexpectedly adaptations, or engaged in behaviors and outcomes, uncannily convergent with ones found in nature. Such stories routinely reveal surprise and creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. Bugs are fixed, experiments are refocused, and one-off surprises are collapsed into a single data point. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This article is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
