Quantum Physics-Informed Neural Networks.

In this study, the PennyLane quantum device simulator was used to investigate quantum and hybrid, quantum/classical physics-informed neural networks (PINNs) for solutions to both transient and steady-state, 1D and 2D partial differential equations. The comparative expressibility of the purely quantum, hybrid and classical neural networks is discussed, and hybrid configurations are explored. The results show that (1) for some applications, quantum PINNs can obtain comparable accuracy with less neural network parameters than classical PINNs, and (2) adding quantum nodes in classical PINNs can increase model accuracy with less total network parameters for noiseless models.

A Variational Quantum Linear Solver Application to Discrete Finite-Element Methods.

Finite-element methods are industry standards for finding numerical solutions to partial differential equations. However, the application scale remains pivotal to the practical use of these methods, even for modern-day supercomputers. Large, multi-scale applications, for example, can be limited by their requirement of prohibitively large linear system solutions.

The Importance of Being RNA-est: considering RNA-mediated ribosome plasticity.

For over 40 years, ribosomes were considered monolithic machines that translate the genetic code indiscriminately. However, over the past two decades, there have been a growing number of studies that suggest ribosomes to have a degree of compositional and functional adaptability in response to tissue type, cell environment and stimuli, cell cycle or development state. In such form, ribosomes themselves take an active part in translation regulation through an intrinsic adaptability provided by evolution, which furnished ribosomes with a dynamic plasticity that confers another layer of gene expression regulation.

Short Report: Evaluating the Effects of Automated Donor Referral Technology on Deceased Donor Referrals.

Unlabelled: Automation of deceased donor referrals with standardized clinical triggers allows organ procurement organizations to be rapidly aware of medically eligible potential donors without the need for manual reporting and subjective decision-making of otherwise very busy hospital staff. In October 2018, 3 Texas hospitals (pilot hospitals) began using an automated referral system; our goal was to evaluate the impact of this system on eligible donor referral.

Methods: We studied ventilated referrals (n = 28 034) in a single organ procurement organization from January 2015 to March 2021.