Exponential evolution mechanism for in vivo computation

Swarm and Evolutionary Computation - Tập 65 - Trang 100931 - 2021
Shaolong Shi1,2, Yifan Chen2,3, Xin Yao4, Qiang Liu1,5
1Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, 324000, China
2School of Life Science and Technology, the University of Electronic Science and Technology of China, Chengdu 611731, China
3Division of Health, Engineering, Computing and Science, the University of Waikato, Hamilton 3240, New Zealand
4Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
5School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Tài liệu tham khảo

Jemal, 2011, Global cancer statistics, CA, 61, 69 Bharath, 2008, Introductory medical imaging, Synth. Lec. Biomed. Eng., 3, 1 Pepe, 2001, Phases of biomarker development for early detection of cancer, J. Nat. Cancer Inst., 93, 1054, 10.1093/jnci/93.14.1054 Kingsley, 2006, Nanotechnology: a focus on nanoparticles as a drug delivery system, J. Neuroimmune Pharmacol, 1, 340, 10.1007/s11481-006-9032-4 Maeda, 2000, Tumor vascular permeability and the EPR effect in macromolecular therapeutics: a review, J. Control. Rel., 65, 271, 10.1016/S0168-3659(99)00248-5 Wilhelm, 2016, Analysis of nanoparticle delivery to tumours, Nat. Rev. Mater., 1, 16014, 10.1038/natrevmats.2016.14 Yu, 2019, Reversible swelling and shrinking of paramagnetic nanoparticle swarms in biofluids with high ionic strength, IEEE/ASME Trans. Mechatron., 24, 154, 10.1109/TMECH.2018.2876617 Arruebo, 2007, Magnetic nanoparticles for drug delivery, Nano today, 2, 22, 10.1016/S1748-0132(07)70084-1 Shi, 2020, Microrobots based in vivo evolutionary computation in two-dimensional microchannel network, IEEE Trans. Nanotechnol., 19, 71, 10.1109/TNANO.2019.2960126 Rahul, 2017, A brief review on nanorobots, SSRG-IJME, 4, 15, 10.14445/23488360/IJME-V4I8P104 Sitti, 2009, Miniature devices: voyage of the microrobots, Nature, 458, 1121, 10.1038/4581121a Servant, 2015, Controlled in vivo swimming of a swarm of bacteria-like microrobotic flagella, Adv. Mater., 27, 2981, 10.1002/adma.201404444 Felfoul, 2016, Magneto-aerotactic bacteria deliver drug-containing nanoliposomes to tumour hypoxic regions, Nat. Nanotechnol., 11, 941, 10.1038/nnano.2016.137 Li, 2017, Micro/nanorobots for biomedicine: delivery, surgery, sensing, and detoxification, Sci. Robot., 2, eaam6431, 10.1126/scirobotics.aam6431 Chen, 2016, Green touchable nanorobotic sensor networks, IEEE Commun. Mag., 54, 136, 10.1109/MCOM.2016.1500626CM Yu, 2017, On-demand probabilistic polling for nanonetworks under dynamic IoT backhaul network conditions, IEEE Internet Things J., 4, 2217, 10.1109/JIOT.2017.2751524 H. Yu, B. Ng, W.K. Seah, Pulse arrival scheduling for nanonetworks under limited IoT access bandwidth, 2017 IEEE 42nd Conference on Local Computer Networks (LCN) (2017b) 18–26. Bui, 2009 Shi, 2019, Perspective: computational nanobiosensing., IEEE Trans. Nanobiosci., 19, 267, 10.1109/TNB.2019.2956470 Chen, 2017, Touchable computing: computing-inspired bio-detection, IEEE Trans. Nanobiosci., 16, 810, 10.1109/TNB.2017.2769162 Chen, 2019, Biosensing-by-learning direct targeting strategy for enhanced tumor sensitization, IEEE Trans. Nanobiosci., 18, 498, 10.1109/TNB.2019.2919132 Shi, 2020, In vivo computing strategies for tumor sensitization and targeting, IEEE Trans. Cybern., 1 Shi, 2020, NGA-inspired nanorobots-assisted detection of multifocal cancer, IEEE Trans. Cybern., 1 Shi, 2020, Nanorobots-assisted natural computation for multifocal tumor sensitization and targeting, IEEE Trans. NanoBiosci. Shi, 2019, Experimental verification of guidance and search strategy of nanobots under magnetic field control in grid network, 526 Ali, 2016, Fabrication and magnetic control of alginate-based rolling microrobots, AIP Adv., 6, 125205, 10.1063/1.4971277 Yan, 2017, Multifunctional biohybrid magnetite microrobots for imaging-guided therapy, Sci. Robot., 2, eaaq1155, 10.1126/scirobotics.aaq1155 Kim, 2016, Fabrication and manipulation of ciliary microrobots with non-reciprocal magnetic actuation, Sci. Rep., 6, 30713, 10.1038/srep30713 Chen, 2016, Green touchable nanorobotic sensor networks, IEEE Commun. Mag., 54, 136, 10.1109/MCOM.2016.1500626CM Sefidgar, 2015, Numerical modeling of drug delivery in a dynamic solid tumor microvasculature, Microvasc. Res., 99, 43, 10.1016/j.mvr.2015.02.007 Cheang, 2015, Self-assembly of robotic micro-and nanoswimmers using magnetic nanoparticles, J. Nanopart. Res., 17, 145, 10.1007/s11051-014-2737-z Shi, 2019, Lightweight evolution strategies for nanoswimmers-oriented in vivo computation, 866 Cheang, 2017, Feedback control of an achiral robotic microswimmer, J. Biol. Eng., 14, 245 Wong, 1999, Direct force measurements of the streptavidin–biotin interaction, Biomol. Eng., 16, 45, 10.1016/S1050-3862(99)00035-2 Kei Cheang, 2014, Multiple-robot drug delivery strategy through coordinated teams of microswimmers, Appl. Phys. Lett., 105, 083705, 10.1063/1.4893695 Lorthois, 2010, Fractal analysis of vascular networks: insights from morphogenesis, J. Theor. Biol., 262, 614, 10.1016/j.jtbi.2009.10.037 Gazit, 1997, Fractal characteristics of tumor vascular architecture during tumor growth and regression, Microcirculation, 4, 395, 10.3109/10739689709146803 Holash, 1999, Vessel cooption, regression, and growth in tumors mediated by angiopoietins and VEGF, Science, 284, 1994, 10.1126/science.284.5422.1994 Carmeliet, 2000, Angiogenesis in cancer and other diseases, Nature, 407, 249, 10.1038/35025220 Baish, 2000, Fractals and cancer, Cancer Res., 60, 3683 Rieger, 2015, Integrative models of vascular remodeling during tumor growth, Wil. Interdisci. Rev., 7, 113 Baish, 1996, Role of tumor vascular architecture in nutrient and drug delivery: an invasion percolation-based network model, Microvasc. Res., 51, 327, 10.1006/mvre.1996.0031 Sutherland, 1988, Cell and environment interactions in tumor microregions: the multicell spheroid model, Science, 240, 177, 10.1126/science.2451290 Chen, 2019, Direct targeting strategy for smart cancer detection as natural computing, 1 Rashedi, 2009, GSA: a gravitational search algorithm, Inform. Sci., 179, 2232, 10.1016/j.ins.2009.03.004 Kennedy, 1995, Particle swarm optimization, 4, 1942 Zhang, 2008, A task scheduling algorithm based on PSO for grid computing, Int. J. Comput. Intell. Res., 4, 37 Shi, 2001, Particle swarm optimization: developments, applications and resources, 1, 81 Sengupta, 2019, Particle swarm optimization: a survey of historical and recent developments with hybridization perspectives, Mach. Learn. Knowl. Extr., 1, 157, 10.3390/make1010010 Tong, 2018, A PSO optimization scale-transformation stochastic-resonance algorithm with stability mutation operator, IEEE Access, 6, 1167, 10.1109/ACCESS.2017.2778022