Architectural aspects of self-aware and self-expressive computing systems:from psychology to engineering

Work on human self-Awareness is the basis for a framework to develop computational systems that can adaptively manage complex dynamic tradeoffs at runtime. An architectural case study in cloud computing illustrates the framework's potential benefits.

Toward a scalable and consistent manufacturing process for the production of human MSCs

The development of novel, affordable and efficacious therapeutics will be necessary to ensure the continued progression in the standard of global healthcare. With the potential to address previously unmet patient needs as well as tackling the social and economic effects of chronic and age-related conditions, cell therapies will lead the new generation of healthcare products set to improve health and wealth across the globe. However, if many of the small to medium enterprises (SMEs) engaged in much of the commercialization efforts are to successfully traverse the ‘Valley of Death’ as they progress through clinical trials, there are a number of challenges that must be overcome. No longer do the challenges remain biological but rather a series of engineering and manufacturing issues must also be considered and addressed.

Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction:a review

Support Vector Machines (SVMs) are widely used classifiers for detecting physiological patterns in Human-Computer Interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the application of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables, and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.

Mixing theory for culture and harvest in bioreactors of human mesenchymal stem cells on microcarriers

The use of human mesenchymal stem cells (hMSCs) in regenerative medicine is a potential major advance for the treatment of many medical conditions, especially with the use of allogeneic therapies where the cells from a single donor can be used to treat ailments in many patients. Such cells must be grown attached to surfaces and for large scale production, it is shown that stirred bioreactors containing ~200 μm particles (microcarriers) can provide such a surface. It is also shown that the just suspended condition, agitator speed NJS, provides a satisfactory condition for cell growth by minimizing the specific energy dissipation rate, εT, in the bioreactor whilst still meeting the oxygen demand of the cells. For the cells to be used for therapeutic purposes, they must be detached from the microcarriers before being cryopreserved. A strategy based on a short period (~7 min) of very high εT, based on theories of secondary nucleation, is effective at removing >99% cells. Once removed, the cells are smaller than the Kolmogorov scale of turbulence and hence not damaged. This approach is shown to be successful for culture and detachment in 4 types of stirred bioreactors from 15 mL to 5 L.