Development of an Emulation-simulation Thermal Control Model for Space Station Application

Analysis techniques to evaluate the effects of changing thermal loads and the methods utilized to control temperature distributions in the orbital space station are essential. Analysis techniques including a user-friendly computer program, were developed which should prove useful in thermal design and system analysis of the the space station. The program uses a data base and user input to compute costs, sizes, and power requirements for individual components and complete systems. User input consists of selecting mission parameters, selecting thermal acquisition configurations, transport systems and distances, and thermal rejection configurations

A Reference Interpreter for the Graph Programming Language GP 2

GP 2 is an experimental programming language for computing by graph transformation. An initial interpreter for GP 2, written in the functional language Haskell, provides a concise and simply structured reference implementation. Despite its simplicity, the performance of the interpreter is sufficient for the comparative investigation of a range of test programs. It also provides a platform for the development of more sophisticated implementations.Comment: In Proceedings GaM 2015, arXiv:1504.0244

Dementia Education and Training in Hertfordshire and Bedfordshire : An organisational audit commissioned by Health Education England

This audit established the range of dementia education available to NHS staff, social care staff and GPs across the two counties. It reports on current uptake of training, course content, assessment and accreditation of training. Future commissioning for dementia education and training might need to consider i) who in the workforce needs to be targeted, ii) whether or not there should be different sets of competencies for various professional groups, iii) accreditation that leads to recognised steps of progression; iv) joint commissioning of health and social care to deliver dementia education and trainin

Essentials of Programming Languages (third edition) by Daniel P. Friedman and Mitchell Wand, MIT Press, ISBN 978-0-262-06279-4, 2008

Book revie

sGDML: Constructing Accurate and Data Efficient Molecular Force Fields Using Machine Learning

We present an optimized implementation of the recently proposed symmetric gradient domain machine learning (sGDML) model. The sGDML model is able to faithfully reproduce global potential energy surfaces (PES) for molecules with a few dozen atoms from a limited number of user-provided reference molecular conformations and the associated atomic forces. Here, we introduce a Python software package to reconstruct and evaluate custom sGDML force fields (FFs), without requiring in-depth knowledge about the details of the model. A user-friendly command-line interface offers assistance through the complete process of model creation, in an effort to make this novel machine learning approach accessible to broad practitioners. Our paper serves as a documentation, but also includes a practical application example of how to reconstruct and use a PBE0+MBD FF for paracetamol. Finally, we show how to interface sGDML with the FF simulation engines ASE (Larsen et al., J. Phys. Condens. Matter 29, 273002 (2017)) and i-PI (Kapil et al., Comput. Phys. Commun. 236, 214-223 (2019)) to run numerical experiments, including structure optimization, classical and path integral molecular dynamics and nudged elastic band calculations