A controlled trial of sip-feed supplements in elderly orthopaedic patients

The potential nutritional and clinical benefits of sip-feed supplements were investigated by means of a controlled trial in elderly female patients admitted for orthopaedic surgery. A nutritional risk assessment procedure (Nutritional Risk Questionnaire, NRQ) was used to identify patients who might benefit from supplementation. Patients identified as high risk who did not receive supplements showed significant losses in triceps skinfold thickness (TSF) and mid-upper arm muscle circumference (MUAMC) measurements during hospitalization. Such changes were not observed in high-risk supplemented patients, but significant losses of MUAMC were also recorded in a group of patients who failed to comply with the supplement. No differences in biochemical parameters, muscle function, or clinical outcome were observed between supplemented and unsupplemented and non-compliant patients. The problems of poor compliance to sip-feed supplements and failure to observe clinical benefit in supplemented patients are discussed.

Artificial Intelligence: the basics

Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined, whether machines can 'think', sensory input in machine systems, the nature of consciousness, the controversial culturing of human neurons. Exploring issues at the heart of the subject, this book is suitable for anyone interested in AI, and provides an illuminating and accessible introduction to this fascinating subject.

A combined engineering and statistical model of UK domestic appliance electrical load profiles

The development of a combined engineering and statistical Artificial Neural Network model of UK domestic appliance load profiles is presented. The model uses diary-style appliance use data and a survey questionnaire collected from 51 suburban households and 46 rural households during the summer of 2010 and2011 respectively. It also incorporates measured energy data and is sensitive to socioeconomic, physical dwelling and temperature variables. A prototype model is constructed in MATLAB using a two layer feed forward network with back propagation training which has a 12:10:24 architecture. Model outputs include appliance load profiles which can be applied to the fields of energy planning (microrenewables and smart grids), building simulation tools and energy policy.