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Preface to 'Green carbon for the chemical industry of the future'.
Philos Trans A Math Phys Eng Sci
November 2024
Department of Chemistry, Inorganic Chemistry Laboratory, South Parks Road , Oxford OX1 3QR, UK.
Innovative approaches to cardiovascular safety pharmacology assessment.
J Pharmacol Toxicol Methods
July 2024
Cardiovascular Division, King's College London, Rayne Institute, St Thomas' Hospital, London SE17EH, UK.
This editorial prefaces the annual themed issue on safety pharmacology (SP) methods which has been published since 2004 in the Journal of Pharmacological and Toxicological Methods (JPTM). Here we highlight content derived from the 2023 Safety Pharmacology Society (SPS) meeting held in Brussels, Belgium. The meeting generated 138 abstracts, reproduced in the current volume of JPTM.
View Article and Find Full Text PDFA special issue preface: diamond for quantum applications.
Philos Trans A Math Phys Eng Sci
January 2024
Institute for Materials Research (IMO), Hasselt University & IMEC vzw, Diepenbeek, Belgium.
This special issue discusses current progress in the utilization of defect centres in diamond as spin-photon interfaces for quantum applications. This issue is based on the discussions of the Theo Murphy meeting 'Diamond for quantum applications' which covered the recent progress of diamond growth and engineering for the creation and optimization of colour centres, toward the integration of diamond-based qubits in quantum systems. This article is part of the Theo Murphy meeting issue 'Diamond for quantum applications'.
View Article and Find Full Text PDFPreface to the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 2)'.
Philos Trans A Math Phys Eng Sci
January 2024
MOE Key Laboratory of Deep Earth Science and Engineering, College of Architecture and Environment, Sichuan University, Chengdu 610065, People's Republic of China.
As an emerging research field, physics-informed machine learning and its structural integrity applications may bring new opportunities to the intelligent solution of engineering problems. Pure data-driven approaches have some limitations when solving engineering problems due to lack of interpretability and data hungry applications. Therefore, further unlocking the potential of machine learning will be an important research direction in the future.
View Article and Find Full Text PDFA special issue preface: Radiocarbon in the Anthropocene.
Philos Trans A Math Phys Eng Sci
November 2023
Department of Biogeochemical Processes, Max Planck Institute for Biogeochemistry, Jena 07745, Germany.
The Anthropocene is defined by marked acceleration in human-induced perturbations to the Earth system. Anthropogenic emissions of CO and other greenhouse gases to the atmosphere and attendant changes to the global carbon cycle are among the most profound and pervasive of these perturbations. Determining the magnitude, nature and pace of these carbon cycle changes is crucial for understanding the future climate that ecosystems and humanity will experience and need to respond to.
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