6 papers · ranked by Valyu relevance
Hadeer Kamal, Amira Y. Haikal, Mahmoud M. Saafan
Traffic collisions and congestion represent significant challenges within intelligent transportation systems (ITS). Consequently, a vehicular ad-hoc network (VANET) has been established. Numerous architectures have been incorporated into VANETs to manage the extensive data generated by vehicles. Collaboration with fog…
Justina Stark, Christophe Godin
Biological transport networks range from tree-like to highly reticulated architectures, which have been proposed to reflect different balances between viscous dissipation and metabolic cost. This balance cannot currently be inferred from structure: available descriptors either discard edge width entirely or preserve it…
Xiaoyue Hu, Yuhao Ma, Ruixing Ming, Heping Zhang + 1 more
Identifying essential biomarkers remains a core challenge in elucidating the pathogenic mechanisms and achieving precise diagnosis of complex diseases. Deep neural networks offer immense predictive power, yet their lack of interpretability severely limits downstream biological insight. Here, we introduce DeepVaris, an…
Samuel de la Sablonnière, Samuel Foucher, Yacine Bouroubi, Philippe Vigneault + 1 more
Vegetated riparian buffers play a critical role in maintaining ecological health and water quality, yet efficient characterization and large-scale monitoring remain challenging due to the resource demands of traditional field campaigns. This study, conducted in an agricultural setting, introduces a straightforward…
Filippo Groppi, Jessica Ferrari
Spontaneous population bursts repeatedly expose synapses to correlated spike activity, but it is unclear whether such events reinforce pre-existing synaptic weight differences when precise firing order carries little information. We asked this in a conductance-based model of a bursting neuronal culture: 48 excitatory…
Eliezer Masliah
How transient neural representations become integrated and stable enough to function as internal neural models remains incompletely understood. Grounded in efficient coding, Bayesian and predictive frameworks, recurrent and attractor dynamics, neural state-space models, and systems neuroscience, the Principle of…