Dimensionless numbers are important in biomechanics because their constancy can imply
dynamic similarity between systems, despite possible differences in medium or scale 1 . A …

Building robust low and mid-level image representations, beyond edge primitives, is a long-standing
goal in vision. Many existing feature detectors spatially pool edge information which …

Here we provide the first formal quantitative analysis of dynamic stability in a flying animal.
By measuring the longitudinal static stability derivatives and mass distribution of desert …

Convolutional neural networks are capable of learning powerful representational spaces,
which are necessary for tackling complex learning tasks. However, due to the model capacity …

Several years ago Graham Romeyn Taylor, then, as now, one of the editorial staff of The
Survey, visited the various communities which had grown up in the vicinity of the larger cities of …

Background The SARS-CoV-2 delta (B.1.617.2) variant is highly transmissible and spreading
globally, including in populations with high vaccination rates. We aimed to investigate …

We present a hierarchical model that learns image decompositions via alternating layers of
convolutional sparse coding and max pooling. When trained on natural images, the layers of …

We propose a non-linear generative model for human motion data that uses an undirected
model with binary latent variables and real-valued" visible" variables that represent joint …

Epstein-Barr virus (EBV) provides a useful model to study cellular immunity to a genetically
stable, persistent human virus. Different sets of proteins expressed during EBV's lytic and cell …

House dust mite (HDM) allergens are important factors in the increasing prevalence of
asthma. The lung epithelium forms a barrier that allergens must cross before they can cause …