1 June 2018

Research Picks – 1 June 2018

Waste not, want not
Material recirculation – repurposing and recycling waste – is considered a more sustainable approach than running a linear economy where products that are obsolete or redundant are simply disposed of. Conventional recycling of glass, plastics, paper, and other materials is costly and energy intensive and reclaims the waste as new material for further manufacturing. This is perhaps the most well-known approach to material recirculation, but there are other options. “Entirely new products might be fabricated from cleaned, but otherwise unprocessed waste items. Industrial symbiosis and upcycling are two strategies to make new products from discards that can be said to work on both extremes of the volume scale,” report a team from Sweden. They have investigated the state of the art in this area and suggest that the main challenge is a lack of reliable material property data for discarded materials. This hinders well-informed screening and so we need to put in place a way to better understand the processes needed for designing with waste.
Ordoñez, I. and Rexfelt, O. (2017) ‘Designing from the dumpster: experiences of developing products using discards‘, Int. J. Sustainable Design, Vol. 3, No. 2, pp.61-78.

The data age
Data security and privacy protection are constantly in the technology news and with recent scandals associated with social media and election and referendum interference and manipulation they are also become prominent topics in the mainstream news outlets. The issue of privacy and security is perhaps nowhere more critical than in the area of cloud computing where much of the data a user (whether individual, corporate entity, or even government) is entrusted to remote, third-party servers for storage and processing with all the attendant issues of trust and risks of said third party being compromised by yet another party. Cloud computing is an essential part of the modern computing mix. Countless systems would not function at all without it. Researchers in China have now laid bare several of the problems we might face in utilising this paradigm.
Kong, W., Lei, Y. and Ma, J. (2018) ‘Data security and privacy information challenges in cloud computing‘, Int. J. Computational Science and Engineering, Vol. 16, No. 3, pp.215-218.

Flying elephants
Researchers from Brazil have turned to flying elephants to help them model how an object might be coated with spheres of a given size. Such a problem arises in nanotechnology, in understanding the behaviour of living cells and biomacromolecules, pathogens infecting another organism, and perhaps more mundane in packing everyday objects. The question is a global optimisation problem and these normally have a lot of local minima points which requires a lot of calculating to work out an answer. This is where the flying elephants are useful. The flying elephants help smooth a given non-differentiable problem. The elephants represent ways to reach a solution, they can fly anywhere but when they land, they squeeze out many of the less likely minima. The concept is merely a metaphor, but its simple description converted into an algorithmic tool offers a heavyweight answer to the question.
Lubke, D.C., Xavier, V.L., Venceslau, H.M. and Xavier, A.E. (2018) ‘Flying elephants method applied to the problem of covering solid bodies with spheres‘, Int. J. Metaheuristics, Vol. 7, No. 1, pp.30-42.

Networking Alzheimer’s
Alzheimer’s disease was first identified by German psychiatrist and neuropathologist Alois Alzheimer in 1907 and is the most common form of dementia in the elderly. Its causes and effects are complicated and research into understanding the disease and its causes, finding ways to treat it, and perhaps even preventing it from occurring in the first place is wide and far-reaching and represented by lots of different scientific nodes. Researchers in Portugal have used various tools to visualise the scientific research as a network of intellectual endeavours associated with this devastating and fatal disease. Their paper offers a detailed analytical mapping of the research and charts progress with various useful parameters ultimately supplying researchers with new tools and enabling healthcare practitioners to improve their knowledge of trends and developments in Alzheimer’s research.
Pestana, M.H. and Sobral, M.R. (2018) ‘Alzheimer’s disease research: a network science approach‘, Int. J. Multivariate Data Analysis, Vol. 1, No. 3, pp.201-217.

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