Bacteria and bees
Algorithms that mimic the behavior of living things are an important route into optimizing data mining and countless other applications. For instance, there are algorithms that emulate the way in which the workers from a hive of bees will seek out flowers with abundant nectar supplies. Similarly, another approach to algorithms copies the cultured foraging behavior of bacteria. Now, an international team based in Iran and the USA have combined the behavior of bees and bacteria in a novel multi-objective algorithm. Their approach pools the benefits of the artificial bee colony and bacterial foraging models in a single algorithm that is very flexible has fewer setting parameters and yet outperforms three of the most well-known multi-objective tools.
Mahmoodabadi, M.J., Taherkhorsandi, M., Maafi, R.A. and Castillo-Villar, K.K. (2015) ‘A novel multi-objective optimisation algorithm: artificial bee colony in conjunction with bacterial foraging’, Int. J. Intelligent Engineering Informatics, Vol. 3, No. 4, pp.369–386.
(I can’t get no) satisfaction
Customers satisfaction, trust and brand image are important factors in business and marketing, not least in the world of telecommunications with its multitude of suppliers of both services and devices such as smart phones. In rapidly developing nations there are major implications for business and marketing to better understand the behavior of customers and potential clients in this sector. New work from Ghana suggests that fundamentally, the same rules apply there as they do in the more established technological markets of “the West”, namely that “marketing managers need to develop marketing and loyalty strategies that result in better customer satisfaction, induce more trust in the brand and project the image of the brand high to build a stable customer base.”
Yeboah-Asiamah, E., Nimako, S.G., Quaye, D.M. and Buame, S. (2016) ‘Implicit and explicit loyalty: the role of satisfaction, trust and brand image in mobile telecommunication industry’, Int. J. Business and Emerging Markets, Vol. 8, No. 1, pp.94–115
Protein complexes abound across all life on Earth. A new US computational study of how such complex are interconnected suggests that in humans and yeast alike these interconnections of protein complexes are evolutionarily conserved. The discovery that for a given inter-complex hub in one species, human or yeast, there exists an equivalent hub in the other. This has important implications for understanding the protein networks and their implications for medicine, biotechnology and other areas. There are also implications for understanding the transfer of information between species a critical phenomenon in the emergence of new diseases and in the development of drug resistance in old ones.
Guerra, C. (2015) ‘On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks’, Int. J. Bioinformatics Research and Applications, Vol. 11, No. 6, pp.483–502.
Teatime for HIV
Natural chemicals, such as gallic Acid (GA) a polyphenol, found in tea leaves, gallnuts, oak bark and other plant parts could lead to new anti-HIV drugs that block the viral protease enzymes as effectively as current drugs including darunavir and amprenavir, according to research from India. HIV-1 Protease enzymes are critical to the assembly and maturation of infectious HIV retroviruses and so blocking their activity with drugs is the focus of much research and development to treat the virus that causes AIDS. The current work builds on earlier studies that have shown how derivatives of gallic acid are active against these enzymes and used computer modeling to design better analogs that could one day be used in a potent antiviral medication against HIV. The current lead compound in the work has the chemical name [(3S)-octahydrobenzofuran- 3-yl ((2S, 3R)-3-hydroxy-1-phenyl-4-(3,4,5-trihydroxy-N-isobutylphenylsulfonamido) butan-2-yl)carbamate]. It will most likely have a much shorter name should it or its chemical cousins be marketed as drugs.
Singh, A. and Pal, T.K. (2015) ‘Docking analysis of gallic acid derivatives as HIV-1 protease inhibitors’, Int. J. Bioinformatics Research and Applications, Vol. 11, No. 6, pp.540–546.