University College Cork

About: University College Cork is a education organization based out in Cork, Ireland. It is known for research contribution in the topics: Population & Context (language use). The organization has 12056 authors who have published 28452 publications receiving 958414 citations. The organization is also known as: Coláiste na hOllscoile Corcaigh & National University of Ireland, Cork.

The clustering of health behaviours in Ireland and their relationship with mental health, self-rated health and quality of life

Abstract: Health behaviours do not occur in isolation. Rather they cluster together. It is important to examine patterns of health behaviours to inform a more holistic approach to health in both health promotion and illness prevention strategies. Examination of patterns is also important because of the increased risk of mortality, morbidity and synergistic effects of health behaviours. This study examines the clustering of health behaviours in a nationally representative sample of Irish adults and explores the association of these clusters with mental health, self-rated health and quality of life.

Power-Factor-Corrected Single-Stage Inductive Charger for Electric Vehicle Batteries

Abstract: A novel power-factor-corrected single-stage alternating current/direct current converter for inductive charging of electric vehicle batteries is introduced. The resonant converter uses the current-source characteristic of the series-parallel topology to provide power-factor correction over a wide output power range from zero to full load. Some design guidelines for this converter are outlined. An approximate small-signal model of the converter is also presented. Experimental results verify the operation of the new converter

Towards a Universal SMILES representation - A standard method to generate canonical SMILES based on the InChI

Abstract: There are two line notations of chemical structures that have established themselves in the field: the SMILES string and the InChI string. The InChI aims to provide a unique, or canonical, identifier for chemical structures, while SMILES strings are widely used for storage and interchange of chemical structures, but no standard exists to generate a canonical SMILES string. I describe how to use the InChI canonicalisation to derive a canonical SMILES string in a straightforward way, either incorporating the InChI normalisations (Inchified SMILES) or not (Universal SMILES). This is the first description of a method to generate canonical SMILES that takes stereochemistry into account. When tested on the 1.1 m compounds in the ChEMBL database, and a 1 m compound subset of the PubChem Substance database, no canonicalisation failures were found with Inchified SMILES. Using Universal SMILES, 99.79% of the ChEMBL database was canonicalised successfully and 99.77% of the PubChem subset. The InChI canonicalisation algorithm can successfully be used as the basis for a common standard for canonical SMILES. While challenges remain – such as the development of a standard aromatic model for SMILES – the ability to create the same SMILES using different toolkits will mean that for the first time it will be possible to easily compare the chemical models used by different toolkits.