Machine Learning Mapping Approach for Computing Spin Relaxation Dynamics.

In this work, a machine learning mapping approach for predicting the properties of atomistic systems is reported. Within this approach, the atomic orbital overlap, density, or Kohn-Sham (KS) Fock matrix elements obtained at a low level of theory such as extended tight-binding have been used as input features to predict the electric field gradient (EFG) tensors at a higher level of theory such as those obtained with hybrid functionals. It is shown that the machine-learning-predicted EFG tensors can be used to compute spin relaxation rates of several ions in aqueous solutions.

A mechanistic understanding of human magnetoreception validates the phenomenon of electromagnetic hypersensitivity (EHS).

Background: Human electromagnetic hypersensitivity (EHS) or electrosensitivity (ES) symptoms in response to anthropogenic electromagnetic fields (EMFs) at levels below current international safety standards are generally considered to be nocebo effects by conventional medical science. In the wider field of magnetoreception in biology, our understanding of mechanisms and processes of magnetic field (MF) interactions is more advanced.

Methods: We consulted a range of publication databases to identify the key advances in understanding of magnetoreception across the wide animal kingdom of life.

The Case for the Role of Primary Care in Patient Blood Management.

Patient blood management (PBM) is a patient-centered evidence-based strategy designed to preserve a patient's own blood and improve health outcomes. The effectiveness of PBM programs is now well-established globally within tertiary and secondary sectors, with demonstrable outcome benefits and cost savings. However, the role of primary care and the general practitioner in PBM is poorly understood.