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Journal articles on the topic 'Assisted evolution'

Author: Grafiati

Published: 14 September 2024

Last updated: 31 July 2025

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1

Qiu, Yuchi, Jian Hu, and Guo-Wei Wei. "Cluster learning-assisted directed evolution." Nature Computational Science 1, no. 12 (2021): 809–18. http://dx.doi.org/10.1038/s43588-021-00168-y.

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2

Boland, James P., Roberto E. Kusminsky, E. H. Tiley, and J. P. Tierney. "Evolution of Hand-Assisted Laparoscopic Surgery." Journal of Endourology 19, no. 2 (2005): 133–35. http://dx.doi.org/10.1089/end.2005.19.133.

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3

Orvieto, M. A., and V. R. Patel. "Evolution of Robot-Assisted Radical Prostatectomy." Scandinavian Journal of Surgery 98, no. 2 (2009): 76–88. http://dx.doi.org/10.1177/145749690909800203.

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4

Jewel, Delilah, Quan Pham, and Abhishek Chatterjee. "Virus-assisted directed evolution of biomolecules." Current Opinion in Chemical Biology 76 (October 2023): 102375. http://dx.doi.org/10.1016/j.cbpa.2023.102375.

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5

Yu, Laiqi, Zhenyu Meng, Lingping Kong, Vaclav Snasel, and Jeng-Shyang Pan. "Surrogate-assisted differential evolution: A survey." Swarm and Evolutionary Computation 94 (April 2025): 101879. https://doi.org/10.1016/j.swevo.2025.101879.

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6

Molvar, Christopher, and Mihir Patel. "Evolution of Retrograde Transvenous Obliteration Techniques." Seminars in Interventional Radiology 35, no. 03 (2018): 185–93. http://dx.doi.org/10.1055/s-0038-1660796.

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AbstractGastric variceal hemorrhage is a life-threatening complication of portal hypertension with a poorer prognosis compared with esophageal variceal hemorrhage. The presence of an infradiaphragmatic portosystemic shunt, often a gastrorenal shunt, allows for treatment with retrograde transvenous obliteration (RTO). RTO is an evolving treatment strategy, which includes balloon-assisted RTO, plug-assisted RTO, and coil-assisted RTO, for both gastric variceal hemorrhage and hepatic encephalopathy. RTO techniques are less invasive than transjugular intrahepatic portosystemic shunt creation, with

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7

Chen, Lisong, and Jianlin Shi. "Chemical-assisted hydrogen electrocatalytic evolution reaction (CAHER)." Journal of Materials Chemistry A 6, no. 28 (2018): 13538–48. http://dx.doi.org/10.1039/c8ta03741h.

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8

Cai, Yiqiao, Chi Shao, Huizhen Zhang, Shunkai Fu, Hui Tian, and Yonghong Chen. "A Neighborhood-Assisted Framework for Differential Evolution." IEEE Access 7 (2019): 44338–58. http://dx.doi.org/10.1109/access.2019.2908660.

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9

Trevathan, Wenda R. "The Evolution of Bipedalism and Assisted Birth." Medical Anthropology Quarterly 10, no. 2 (1996): 287–90. http://dx.doi.org/10.1525/maq.1996.10.2.02a00100.

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10

Miller, Shannon M., Tina Wang, and David R. Liu. "Phage-assisted continuous and non-continuous evolution." Nature Protocols 15, no. 12 (2020): 4101–27. http://dx.doi.org/10.1038/s41596-020-00410-3.

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11

Roth, Timothy B., Benjamin M. Woolston, Gregory Stephanopoulos, and David R. Liu. "Phage-Assisted Evolution ofBacillus methanolicusMethanol Dehydrogenase 2." ACS Synthetic Biology 8, no. 4 (2019): 796–806. http://dx.doi.org/10.1021/acssynbio.8b00481.

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12

Joseph, Merin, and Suja Haridas. "Recent progresses in porphyrin assisted hydrogen evolution." International Journal of Hydrogen Energy 45, no. 21 (2020): 11954–75. http://dx.doi.org/10.1016/j.ijhydene.2020.02.103.

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13

Chaudhari, Vijay R., Santosh K. Haram, S. K. Kulshreshtha, J. R. Bellare, and P. A. Hassan. "Micelle assisted morphological evolution of silver nanoparticles." Colloids and Surfaces A: Physicochemical and Engineering Aspects 301, no. 1-3 (2007): 475–80. http://dx.doi.org/10.1016/j.colsurfa.2007.01.025.

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14

Zhou, Xiao-Gen, and Gui-Jun Zhang. "Abstract Convex Underestimation Assisted Multistage Differential Evolution." IEEE Transactions on Cybernetics 47, no. 9 (2017): 2730–41. http://dx.doi.org/10.1109/tcyb.2017.2710626.

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15

van Oppen, Madeleine J. H., James K. Oliver, Hollie M. Putnam, and Ruth D. Gates. "Building coral reef resilience through assisted evolution." Proceedings of the National Academy of Sciences 112, no. 8 (2015): 2307–13. http://dx.doi.org/10.1073/pnas.1422301112.

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The genetic enhancement of wild animals and plants for characteristics that benefit human populations has been practiced for thousands of years, resulting in impressive improvements in commercially valuable species. Despite these benefits, genetic manipulations are rarely considered for noncommercial purposes, such as conservation and restoration initiatives. Over the last century, humans have driven global climate change through industrialization and the release of increasing amounts of CO2, resulting in shifts in ocean temperature, ocean chemistry, and sea level, as well as increasing freque

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16

Londos, C. A., M. S. Potsidi, J. Bak-Misiuk, A. Misiuk, and V. V. Emtsev. "Pressure assisted evolution of defects in silicon." Crystal Research and Technology 38, no. 12 (2003): 1058–62. http://dx.doi.org/10.1002/crat.200310136.

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17

Hořejší, Michal. "Krajina (Landscape) - lexical evolution assisted discourse analysis." Bohemica Olomucensia 9, no. 2 (2017): 96–110. http://dx.doi.org/10.5507/bo.2017.021.

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18

Pham, Martin H., and Nolan J. Brown. "Evolution of Robotic Spine Surgery Technologies." Neurosurgery 96, no. 3S (2025): S75—S83. https://doi.org/10.1227/neu.0000000000003351.

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Robotic-assisted spine surgery has significantly advanced surgical precision and safety. This is particularly pertinent in minimally invasive spine surgeries that rely on imaging and technologies for visualization and the ability to accomplish surgical goals through smaller surgical corridors. The ability to preoperatively plan and then place pedicle screws across a wide range of applications has reduced the difficulty of even complex surgeries that once may have been considered prohibitive for minimally invasive approaches. While challenges and limitations remain, ongoing research and develop

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19

Schlipf, David, Florian Haizmann, Nicolai Cosack, Tom Siebers, and Po Wen Cheng. "Detection of Wind Evolution and Lidar Trajectory Optimization for Lidar-Assisted Wind Turbine Control." Meteorologische Zeitschrift 24, no. 6 (2015): 565–79. http://dx.doi.org/10.1127/metz/2015/0634.

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20

Le, Minh Nghia, Yew Soon Ong, Stefan Menzel, Yaochu Jin, and Bernhard Sendhoff. "Evolution by Adapting Surrogates." Evolutionary Computation 21, no. 2 (2013): 313–40. http://dx.doi.org/10.1162/evco_a_00079.

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To deal with complex optimization problems plagued with computationally expensive fitness functions, the use of surrogates to replace the original functions within the evolutionary framework is becoming a common practice. However, the appropriate datacentric approximation methodology to use for the construction of surrogate model would depend largely on the nature of the problem of interest, which varies from fitness landscape and state of the evolutionary search, to the characteristics of search algorithm used. This has given rise to the plethora of surrogate-assisted evolutionary frameworks

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21

Friedberg, Richard C., and Liron Pantanowitz. "Practice Evolution: Decentralized Computer-Assisted Immunohistochemical Image Analysis." Archives of Pathology & Laboratory Medicine 133, no. 4 (2009): 597–600. http://dx.doi.org/10.5858/133.4.597.

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22

Gwon, Da-ae, Joo Yeon Seok, Gyoo Yeol Jung, and Jeong Wook Lee. "Biosensor-Assisted Adaptive Laboratory Evolution for Violacein Production." International Journal of Molecular Sciences 22, no. 12 (2021): 6594. http://dx.doi.org/10.3390/ijms22126594.

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Violacein is a naturally occurring purple pigment, widely used in cosmetics and has potent antibacterial and antiviral properties. Violacein can be produced from tryptophan, consequently sufficient tryptophan biosynthesis is the key to violacein production. However, the complicated biosynthetic pathways and regulatory mechanisms often make the tryptophan overproduction challenging in Escherichia coli. In this study, we used the adaptive laboratory evolution (ALE) strategy to improve violacein production using galactose as a carbon source. During the ALE, a tryptophan-responsive biosensor was e

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23

Vargas, H. "Hand-Assisted Laparoscopic Colectomy: Rational Evolution for Diverticulitis." Clinics in Colon and Rectal Surgery 19, no. 1 (2006): 019–25. http://dx.doi.org/10.1055/s-2006-939527.

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24

Broe, Mark P., James Ryan, Barry McGuire, Diarmaid Moran, and David Mulvin. "Evolution in technique of robotic-assisted laparoscopic prostatectomy." European Urology Open Science 20 (September 2020): S28. http://dx.doi.org/10.1016/s2666-1683(20)35286-1.

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25

Tanaka, Y., T. Yanagisawa, and T. Nishio. "Fluctuation-assisted gap evolution in frustrated multiband superconductors." Physica C: Superconductivity 483 (December 2012): 86–90. http://dx.doi.org/10.1016/j.physc.2012.07.012.

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26

Benway, Brian M., and Sam B. Bhayani. "Robot-assisted partial nephrectomy: evolution and recent advances." Current Opinion in Urology 20, no. 2 (2010): 119–24. http://dx.doi.org/10.1097/mou.0b013e3283362563.

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27

Panigrahi, Sudipa, Subrata Kundu, Sujit Kumar Ghosh, Sudip Nath, and Tarasankar Pal. "Sugar assisted evolution of mono- and bimetallic nanoparticles." Colloids and Surfaces A: Physicochemical and Engineering Aspects 264, no. 1-3 (2005): 133–38. http://dx.doi.org/10.1016/j.colsurfa.2005.04.017.

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28

Smith, Erin, David Pichora, and Randy Ellis. "Computer-Assisted Percutaneous Scaphoid Fixation: Concepts and Evolution." Journal of Wrist Surgery 02, no. 04 (2013): 299–305. http://dx.doi.org/10.1055/s-0033-1357760.

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29

Beavis, Ronald C. "Matrix-assisted ultraviolet laser desorption: Evolution and principles." Organic Mass Spectrometry 27, no. 6 (1992): 653–59. http://dx.doi.org/10.1002/oms.1210270602.

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30

Lewis, P. "Assisted Dying in France. The Evolution of Assisted Dying in France: A Third Way?" Medical Law Review 14, no. 1 (2005): 44–72. http://dx.doi.org/10.1093/medlaw/fwi033.

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31

Wu, Zachary, S. B. Jennifer Kan, Russell D. Lewis, Bruce J. Wittmann, and Frances H. Arnold. "Machine learning-assisted directed protein evolution with combinatorial libraries." Proceedings of the National Academy of Sciences 116, no. 18 (2019): 8852–58. http://dx.doi.org/10.1073/pnas.1901979116.

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To reduce experimental effort associated with directed protein evolution and to explore the sequence space encoded by mutating multiple positions simultaneously, we incorporate machine learning into the directed evolution workflow. Combinatorial sequence space can be quite expensive to sample experimentally, but machine-learning models trained on tested variants provide a fast method for testing sequence space computationally. We validated this approach on a large published empirical fitness landscape for human GB1 binding protein, demonstrating that machine learning-guided directed evolution

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32

Kleidis, K., and V. K. Oikonomou. "Scalar field assisted f(R) gravity inflation." International Journal of Geometric Methods in Modern Physics 15, no. 08 (2018): 1850137. http://dx.doi.org/10.1142/s0219887818501372.

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In this paper, we investigate the inflationary dynamics of an [Formula: see text] gravity in the presence of a canonical scalar field. We specifically choose the cosmological evolution to be a quasi-de Sitter evolution and also the [Formula: see text] gravity is assumed to be a modified version of the [Formula: see text] gravity. We investigate which scalar field potential can produce the quasi-de Sitter evolution for the choice of the [Formula: see text] gravity we made, and also we study in detail the inflationary dynamics of the resulting theory. As we demonstrate, the spectral index is ide

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33

Braun, Jan, Johannes Krettek, Frank Hoffmann, and Torsten Bertram. "Multi-Objective Optimization with Controlled Model Assisted Evolution Strategies." Evolutionary Computation 17, no. 4 (2009): 577–93. http://dx.doi.org/10.1162/evco.2009.17.4.17408.

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Evolutionary algorithms perform robust search in complex and high dimensional search spaces, but require a large number of fitness evaluations to approximate optimal solutions. These characteristics limit their potential for hardware in the loop optimization and problems that require extensive simulations and calculations. Evolutionary algorithms do not maintain their knowledge about the fitness function as they only store solutions of the current generation. In contrast, model assisted evolutionary algorithms utilize the information contained in previously evaluated solutions in terms of a da

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34

Somidin, Flora, Norainiza Saud, and Mohd Arif Anuar Mohd Salleh. "The Microstructure Evolutions of Sn-0.7Cu Solder Using Microwave-Assisted Sintering Method at Various Exposure Times." Advanced Materials Research 1107 (June 2015): 582–86. http://dx.doi.org/10.4028/www.scientific.net/amr.1107.582.

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This study investigates the effect of microwave-assisted sintering on microstructure evolution and microhardness of Sn-0.7Cu green compact solder. Results showed that microwave-assisted sintering has shortened the sintering duration compared to conventional process. Microstructural characterization revealed that the 800W (2.45GHz) microwave power combined with SiC microwave susceptor heating showed rapid particle grain evolution within 120 seconds. In order to get similar grain evolution, 2 hours of sintering duration was needed for conventional sintering. Results were also revealed that the m

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35

Siroky, Georg, Elke Kraker, Dietmar Kieslinger, Ernst Kozeschnik, and Werner Ecker. "Micromechanics-based damage model for liquid-assisted healing." International Journal of Damage Mechanics 30, no. 1 (2020): 123–44. http://dx.doi.org/10.1177/1056789520948561.

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This work presents a damage evolution framework including liquid-assisted healing. The model incorporates contributions from void size, void pressure, surface tension and liquid pressure. Experimental motivation for the damage-healing model is provided with in-situ melting experiments, where the evolution of the void distribution under monotonic tension is illustrated. The damage evolution is based on nucleation and growth of voids, which are modeled in a unified creep and plasticity framework. The proposed damage formulation introduces a void collective, which computes the void distribution i

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36

Romero, Nuria, Roger Bofill, Laia Francàs, Jordi García-Antón, and Xavier Sala. "Light-Driven Hydrogen Evolution Assisted by Covalent Organic Frameworks." Catalysts 11, no. 6 (2021): 754. http://dx.doi.org/10.3390/catal11060754.

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Covalent organic frameworks (COFs) are crystalline porous organic polymers built from covalent organic blocks that can be photochemically active when incorporating organic semiconducting units, such as triazine rings or diacetylene bridges. The bandgap, charge separation capacity, porosity, wettability, and chemical stability of COFs can be tuned by properly choosing their constitutive building blocks, by extension of conjugation, by adjustment of the size and crystallinity of the pores, and by synthetic post-functionalization. This review focuses on the recent uses of COFs as photoactive plat

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37

Guo, Wei, Jie Xiang, Su Yang, and Hecheng Li. "Video-assisted thoracic surgery for esophagectomy: evolution and prosperity." Video-Assisted Thoracic Surgery 2 (January 6, 2017): 2. http://dx.doi.org/10.21037/vats.2016.12.03.

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38

S., Miruna Joe Amali, and Baskar S. "Surrogate assisted-hybrid differential evolution algorithm using diversity control." Expert Systems 32, no. 4 (2015): 531–45. http://dx.doi.org/10.1111/exsy.12105.

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39

Martynenko, Yu V., and G. Carter. "Stress evolution in ion assisted thin metal film deposition." Radiation Effects and Defects in Solids 132, no. 2 (1994): 103–18. http://dx.doi.org/10.1080/10420159408224301.

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40

Dial, K. P. "Wing-Assisted Incline Running and the Evolution of Flight." Science 299, no. 5605 (2003): 402–4. http://dx.doi.org/10.1126/science.1078237.

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41

Araújo, Aluizio F. R., Lucas R. C. Farias, and Antônio R. C. Gonçalves. "Self-organizing surrogate-assisted non-dominated sorting differential evolution." Swarm and Evolutionary Computation 91 (December 2024): 101703. http://dx.doi.org/10.1016/j.swevo.2024.101703.

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42

Demirskyi, D., H. Borodianska, S. Grasso, Y. Sakka, and O. Vasylkiv. "Microstructure evolution during field-assisted sintering of zirconia spheres." Scripta Materialia 65, no. 8 (2011): 683–86. http://dx.doi.org/10.1016/j.scriptamat.2011.07.006.

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43

Mahmoud, Mustafa Z., Mohammed Aslam, Mohammed Alsaadi, Maram A. Fagiri, and Batil Alonazi. "Evolution of Robot-assisted ultrasound-guided breast biopsy systems." Journal of Radiation Research and Applied Sciences 11, no. 1 (2018): 89–97. http://dx.doi.org/10.1016/j.jrras.2017.11.005.

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44

Sehdev, Neeru, Rohit Medwal, and Annapooni S. "Ag assisted evolution of ordered L10 CoPt alloy nanoparticles." Journal of Alloys and Compounds 522 (May 2012): 85–89. http://dx.doi.org/10.1016/j.jallcom.2012.01.090.

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45

Smith, Alan, Ian Ramnarine, and Patrice Pinkney. "Evolution of Video Assisted Thoracoscopic Surgery in the Caribbean." International Journal of Surgery 72 (December 2019): 19–22. http://dx.doi.org/10.1016/j.ijsu.2019.05.012.

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46

Balaji, G., R. Balamurugan, and L. Lakshminarasimman. "Mathematical approach assisted differential evolution for generator maintenance scheduling." International Journal of Electrical Power & Energy Systems 82 (November 2016): 508–18. http://dx.doi.org/10.1016/j.ijepes.2016.04.033.

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47

Hartley, D. M., and P. J. Rous. "Lifetime evolution in resonance-assisted desorption of adsorbed molecules." Chemical Physics 201, no. 2-3 (1995): 427–32. http://dx.doi.org/10.1016/0301-0104(95)00342-8.

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48

Kelly, Patrick J., Stephan J. Goerss, and Bruce A. Kall. "Evolution of contemporary instrumentation for computer-assisted stereotactic surgery." Surgical Neurology 30, no. 3 (1988): 204–15. http://dx.doi.org/10.1016/0090-3019(88)90273-x.

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49

Stanovov, Vladimir, and Eugene Semenkin. "Surrogate-Assisted Automatic Parameter Adaptation Design for Differential Evolution." Mathematics 11, no. 13 (2023): 2937. http://dx.doi.org/10.3390/math11132937.

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In this study, parameter adaptation methods for differential evolution are automatically designed using a surrogate approach. In particular, Taylor series are applied to model the searched dependence between the algorithm’s parameters and values, describing the current algorithm state. To find the best-performing adaptation technique, efficient global optimization, a surrogate-assisted optimization technique, is applied. Three parameters are considered: scaling factor, crossover rate and population decrease rate. The learning phase is performed on a set of benchmark problems from the CEC 2017

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50

Fung, Allison. "The Rich History and Evolution of Animal-Assisted Therapy." Journal of Alternative, Complementary & Integrative Medicine 10, no. 1 (2024): 1–6. http://dx.doi.org/10.24966/acim-7562/100443.

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Animal-Assisted Therapy (AAT) has a long and rich history of complementing traditional medicine in the treatment of many types of conditions. This type of therapy however may be poorly understood resulting in underutilization and bias. We explore the early foundations of AAT and why it should remain an important tool to be applied in patient treatment strategies.

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