Edinburgh Napier University

About: Edinburgh Napier University is a education organization based out in Edinburgh, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 2665 authors who have published 6859 publications receiving 175272 citations.

Inflammation caused by particles and fibers.

Abstract: (2002) INFLAMMATION CAUSED BY PARTICLES AND FIBERS Inhalation Toxicology: Vol 14, No 1, pp 5-27

Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment

Abstract: COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spread in 212 countries and territories and increasing numbers of infected cases and death tolls mounting to 5,212,172 and 334,915 (as of May 22 2020), it remains a real threat to the public health system. This paper renders a response to combat the virus through Artificial Intelligence (AI). Some Deep Learning (DL) methods have been illustrated to reach this goal, including Generative Adversarial Networks (GANs), Extreme Learning Machine (ELM), and Long/Short Term Memory (LSTM). It delineates an integrated bioinformatics approach in which different aspects of information from a continuum of structured and unstructured data sources are put together to form the user-friendly platforms for physicians and researchers. The main advantage of these AI-based platforms is to accelerate the process of diagnosis and treatment of the COVID-19 disease. The most recent related publications and medical reports were investigated with the purpose of choosing inputs and targets of the network that could facilitate reaching a reliable Artificial Neural Network-based tool for challenges associated with COVID-19. Furthermore, there are some specific inputs for each platform, including various forms of the data, such as clinical data and medical imaging which can improve the performance of the introduced approaches toward the best responses in practical applications.

The water vapor sorption behavior of natural fibers.

Abstract: The water vapor sorption behavior of a range of natural fibers (jute, flax, coir, cotton, hemp, Sitka spruce) has been studied. The data were analyzed using the Hailwood Horrobin model for isotherm fitting and determi- nation of monolayer moisture content. The Hailwood Hor- robin model was found to provide good fits to the experimental data. The extent of hysteresis exhibited between the adsorption and desorption isotherms was de- pendent on fiber type studied and was larger with high lig- nin compared with low lignin content fibers. The area bounded by the hysteresis loop decreased as the isotherms were performed at progressively higher temperatures. This behavior is consistent with sorption interactions occurring with a glassy solid below the glass transition temperature. V C 2009 Wiley Periodicals, Inc. J Appl Polym Sci 112: 1524-1537, 2009

Application areas of AIS: The past, the present and the future

Abstract: After a decade of research into the area of artificial immune systems, it is worthwhile to take a step back and reflect on the contributions that the paradigm has brought to the application areas to which it has been applied. Undeniably, there have been a lot of successful stories-however, if the field is to advance in the future and really carve out its own distinctive niche, then it is necessary to be able to illustrate that there are clear benefits to be obtained by applying this paradigm rather than others. This paper attempts to take stock of the application areas that have been tackled in the past, and ask the difficult question ''was it worth it ?''. We then attempt to suggest a set of problem features that we believe will allow the true potential of the immunological system to be exploited in computational systems, and define a unique niche for AIS.