Cleft Team Clinicians' Perspectives on the Process of Patient Transition from Childhood to Adulthood in New Zealand.

Objective: This study sought to understand cleft team clinician experiences of transitioning patients from pediatric to adult cleft care services in New Zealand.

Design: The qualitative study conducted 4 interviews and 4 focus groups with Cleft Team clinicians either in person or over Zoom. Data were analyzed using inductive thematic analysis to identify themes.

Fast-food consumption and asthma-related emergency room visits in California.

Introduction: Asthma is common, affecting up to 8% of adults in the United States. Several studies have shown an association between poorer diet and asthma. Despite the prevalence of fast-food consumption in the Western diet, research examining fast food consumption and asthma is limited.

An Improved Penalty-Based Excited-State Variational Monte Carlo Approach with Deep-Learning Ansatzes.

We introduce several improvements to the penalty-based variational quantum Monte Carlo (VMC) algorithm for computing electronic excited states of Entwistle et al. [Nat. Commun.

Electronic excited states in deep variational Monte Carlo.

Obtaining accurate ground and low-lying excited states of electronic systems is crucial in a multitude of important applications. One ab initio method for solving the Schrödinger equation that scales favorably for large systems is variational quantum Monte Carlo (QMC). The recently introduced deep QMC approach uses ansatzes represented by deep neural networks and generates nearly exact ground-state solutions for molecules containing up to a few dozen electrons, with the potential to scale to much larger systems where other highly accurate methods are not feasible.