Introduction Several studies have measured health outcomes in the United States, but none
have provided a comprehensive assessment of patterns of health by state. Objective To use …

We present a new optimization-based approach for robotic motion planning among obstacles.
Like CHOMP (Covariant Hamiltonian Optimization for Motion Planning), our algorithm can …

Deep reinforcement learning (RL) algorithms can learn complex robotic skills from raw
sensory inputs, but have yet to achieve the kind of broad generalization and applicability …

To understand the biology and evolution of ruminants, the cattle genome was sequenced to
about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a …

The suprachiasmatic nucleus (SCN) controls the circadian rhythm of physiological and
behavioural processes in mammals. Here we show that prokineticin 2 (PK2), a cysteine-rich …

We present a novel approach for incorporating collision avoidance into trajectory optimization
as a method of solving robotic motion planning problems. At the core of our approach are (i…

Being able to predict what may happen in the future requires an in-depth understanding of
the physical and causal rules that govern the world. A model that is able to do so has a …

Deep reinforcement learning (RL) algorithms can use high-capacity deep networks to learn
directly from image observations. However, these high-dimensional observation spaces …

Recognition of the multiple roles of Hedgehog signaling in cancer has prompted intensive
efforts to develop targeted pathway inhibitors. Leading inhibitors in clinical development act …

Neurogenesis persists in the olfactory bulb (OB) of the adult mammalian brain. New
interneurons are continually added to the OB from the subventricular zone (SVZ) via the rostral …