Publications

A Bayesian Non-Stationary Heteroskedastic Time Series Model for Multivariate Critical Care Data
Zayd Omar
David A. Stephens
Alexandra M. Schmidt
David L Buckeridge
2024-07-01
Statistics in Medicine (publié)
doi.org
arxiv.org
Temperature-dependent Spike-ACE2 interaction of Omicron subvariants is associated with viral transmission
Mehdi Benlarbi
Shilei Ding
Étienne Bélanger
Alexandra Tauzin
Raphaël Poujol
Halima Medjahed
Omar El Ferri
Yuxia Bo
Catherine Bourassa
Julie Hussin
Judith Fafard
Marzena Pazgier
Inès Levade
Cameron Abrams
Marceline Côté
Andrés Finzi
The continued evolution of severe acute respiratory syndrome 2 (SARS-CoV-2) requires persistent monitoring of its subvariants. Omicron subva… (voir plus)riants are responsible for the vast majority of SARS-CoV-2 infections worldwide, with XBB and BA.2.86 sublineages representing more than 90% of circulating strains as of January 2024. To better understand parameters involved in viral transmission, we characterized the functional properties of Spike glycoproteins from BA.2.75, CH.1.1, DV.7.1, BA.4/5, BQ.1.1, XBB, XBB.1, XBB.1.16, XBB.1.5, FD.1.1, EG.5.1, HK.3, BA.2.86 and JN.1. We tested their capacity to evade plasma-mediated recognition and neutralization, binding to angiotensin-converting enzyme 2 (ACE2), their susceptibility to cold inactivation, Spike processing, as well as the impact of temperature on Spike-ACE2 interaction. We found that compared to the early wild-type (D614G) strain, most Omicron subvariants' Spike glycoproteins evolved to escape recognition and neutralization by plasma from individuals who received a fifth dose of bivalent (BA.1 or BA.4/5) mRNA vaccine and improve ACE2 binding, particularly at low temperatures. Moreover, BA.2.86 had the best affinity for ACE2 at all temperatures tested. We found that Omicron subvariants’ Spike processing is associated with their susceptibility to cold inactivation. Intriguingly, we found that Spike-ACE2 binding at low temperature was significantly associated with growth rates of Omicron subvariants in humans. Overall, we report that Spikes from newly emerged Omicron subvariants are relatively more stable and resistant to plasma-mediated neutralization, present improved affinity for ACE2 which is associated, particularly at low temperatures, with their growth rates. The persistent evolution of SARS-CoV-2 gave rise to a wide range of variants harboring new mutations in their Spike glycoproteins. Several factors have been associated with viral transmission and fitness such as plasma-neutralization escape and ACE2 interaction. To better understand whether additional factors could be of importance in SARS-CoV-2 variants’ transmission, we characterize the functional properties of Spike glycoproteins from several Omicron subvariants. We found that the Spike glycoprotein of Omicron subvariants presents an improved escape from plasma-mediated recognition and neutralization, Spike processing, and ACE2 binding which was further improved at low temperature. Intriguingly, Spike-ACE2 interaction at low temperature is strongly associated with viral growth rate, as such, low temperatures could represent another parameter affecting viral transmission.
2024-07-01
mBio (publié)
doi.org
089 Levers and limitations of artificial intelligence (AI) to support the assessment and implementation of shared decision making (SDM): perspectives of key stakeholders
Anik Giguère
Adrian Edwards
Denitza Williams
France Légaré
Natalie Joseph-Williams
Samira Abbasgholizadeh-Rahimi
Karina Prévost
Marie-Clare Hunter
Anna Torrens-Burton
Justine Laloux
2024-06-30
International Symposium on Data Mining (publié)
doi.org
169Yb-based high dose rate intensity modulated brachytherapy for focal treatment of prostate cancer
Maude Robitaille
Cynthia Ménard
Gabriel Famulari
Dominic Béliveau-Nadeau
S. Enger
2024-06-30
Brachytherapy (publié)
doi.org
Accelerated Benders Decomposition and Local Branching for Dynamic Maximum Covering Location Problems
Steven Lamontagne
Margarida Carvalho
Ribal Atallah
The maximum covering location problem (MCLP) is a key problem in facility location, with many applications and variants. One such variant is… (voir plus) the dynamic (or multi-period) MCLP, which considers the installation of facilities across multiple time periods. To the best of our knowledge, no exact solution method has been proposed to tackle large-scale instances of this problem. To that end, in this work, we expand upon the current state-of-the-art branch-and-Benders-cut solution method in the static case, by exploring several acceleration techniques. Additionally, we propose a specialised local branching scheme, that uses a novel distance metric in its definition of subproblems and features a new method for efficient and exact solving of the subproblems. These methods are then compared through extensive computational experiments, highlighting the strengths of the proposed methodologies.
2024-06-30
Computers & Operations Research (publié)
doi.org
arxiv.org
Deep learning based vessel arrivals monitoring via autoregressive statistical control charts
Sara El Mekkaoui
Ghait Boukachab
Loubna Benabbou
Abdelaziz Berrado
2024-06-30
WMU Journal of Maritime Affairs (JoMA) (publié)
doi.org
Imagining a Future of Designing with AI: Dynamic Grounding, Constructive Negotiation, and Sustainable Motivation
Priyan Vaithilingam
Ian Arawjo
Elena L. Glassman
2024-06-30
Designing Interactive Systems Conference (publié)
doi.org
arxiv.org
Do LLMs Meet the Needs of Software Tutorial Writers? Opportunities and Design Implications
Avinash Bhat
Disha Shrivastava
Jin L.C. Guo
Creating software tutorials involves developing accurate code examples and explanatory text that engages and informs the reader. Large Langu… (voir plus)age Models (LLMs) demonstrate a strong capacity to generate both text and code, but their potential to assist tutorial writing is unknown. By interviewing and observing seven experienced writers using OpenAI playground as an exploration environment, we uncover design opportunities for leveraging LLMs in software tutorial writing. Our findings reveal background research, resource creation, and maintaining quality standards as critical areas where LLMs could significantly assist writers. We observe how tutorial writers generated tutorial content while exploring LLMs’ capabilities, formulating prompts, verifying LLM outputs, and reflecting on interaction goals and strategies. Our observation highlights that the unpredictability of LLM outputs and unintuitive interface design contributed to skepticism about LLM’s utility. Informed by these results, we contribute recommendations for designing LLM-based tutorial writing tools to mitigate usability challenges and harness LLMs’ full potential.
2024-06-30
Conference on Designing Interactive Systems (publié)
doi.org
A logistics provider’s profit maximization facility location problem with random utility maximizing followers
David Pinzon Ulloa
Emma Frejinger
Bernard Gendron
2024-06-30
Computers & Operations Research (publié)
doi.org
arxiv.org
One-shot Learning for MIPs with SOS1 Constraints
Charly Robinson La Rocca
Jean-François Cordeau
Emma Frejinger
2024-06-30
Operations Research Forum (publié)
doi.org
arxiv.org
Overcoming Boundaries: Interdisciplinary Challenges and Opportunities in Cognitive Neuroscience
Arnaud Brignol
Anita Paas
Luis Sotelo-Castro
David St-Onge
Giovanni Beltrame
Emily B.J. Coffey
2024-06-30
Neuropsychologia (publié)
doi.org
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning
Georg Pichler
Marco Romanelli
Leonardo Rey Vega
Pablo Piantanida
Federated Learning is expected to provide strong privacy guarantees, as only gradients or model parameters but no plain text training data i… (voir plus)s ever exchanged either between the clients or between the clients and the central server. In this paper, we challenge this claim by introducing a simple but still very effective membership inference attack algorithm, which relies only on a single training step. In contrast to the popular honest-but-curious model, we investigate a framework with a dishonest central server. Our strategy is applicable to models with ReLU activations and uses the properties of this activation function to achieve perfect accuracy. Empirical evaluation on visual classification tasks with MNIST, CIFAR10, CIFAR100 and CelebA datasets show that our method provides perfect accuracy in identifying one sample in a training set with thousands of samples. Occasional failures of our method lead us to discover duplicate images in the CIFAR100 and CelebA datasets.
2024-06-30
IEEE Transactions on Dependable and Secure Computing (publié)
doi.org
arxiv.org