Despite the great empirical success of deep reinforcement learning, its theoretical foundation
is less well understood. In this work, we make the first attempt to theoretically understand …

Alzheimer’s disease (AD) is characterized by the accumulation of the tau protein in neurons,
neurodegeneration and memory loss. However, the role of non-neuronal cells in this chain …

… (or q-) … the q-analogues, which we consider in this article for \(0< q < 1\), can easily (and
possibly trivially) be translated into the corresponding results for the (p, q)-analogues (with \(0< q …

This article summarizes technical advances contained in the fifth major release of the Q-Chem
quantum chemistry program package, covering developments since 2015. A …

… resonances can be achieved with high Q-factors. Surface lattice … resonance to obtain a high-Q
factor, promising for plasmonic … methods for achieving high Q-factor plasmonic resonances …

… In the present study, a UPLC-Q-TOF/MS method was developed for rapid characterization
of chemical constituents in HSBDF. Then, lipopolysaccharide was subsequently used to …

… in Equation 1 learns a Q-function that lower-bounds the true Q-function Qπ, and the evaluation
in Equation 2 provides a tighter lower bound on the expected Q-value of the policy π. For …

… determine how the Q-value can vary with different future outcomes, but how the Q-value can
… (2), but we will aim to estimate the maximum Q-value over actions that are in the support of …

… Q factor in the 1,620–1,650 nm range. The Q factors are shown as a wafer map of the
highest Q factor on each die (top) and as a histogram of Q factors of the 78 resonators (bottom), …

… In this work, we explore the application of f(Q) gravity to the … We demonstrate the effects
of f(Q) by considering the external … of f(Q) by considering a quadratic model of f(Q) = Q + αQ …