Journal articles: 'Assisted evolution'

1

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

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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 (March 2005): 133–35. http://dx.doi.org/10.1089/end.2005.19.133.

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

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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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Molvar, Christopher, and Mihir Patel. "Evolution of Retrograde Transvenous Obliteration Techniques." Seminars in Interventional Radiology 35, no. 03 (August 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 the benefit of improved hepatic function, but at the expense of increased portal pressure. This article discusses the techniques of RTO, including patient eligibility, as well as technical and clinical outcomes, including adverse events.

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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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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 (November 5, 2015): 565–79. http://dx.doi.org/10.1127/metz/2015/0634.

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

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Miller, Shannon M., Tina Wang, and David R. Liu. "Phage-assisted continuous and non-continuous evolution." Nature Protocols 15, no. 12 (November 16, 2020): 4101–27. http://dx.doi.org/10.1038/s41596-020-00410-3.

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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 (March 11, 2019): 796–806. http://dx.doi.org/10.1021/acssynbio.8b00481.

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

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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 (July 2007): 475–80. http://dx.doi.org/10.1016/j.colsurfa.2007.01.025.

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

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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 (February 2, 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 frequency of storms, all of which can profoundly impact marine ecosystems. Coral reefs are highly diverse ecosystems that have suffered massive declines in health and abundance as a result of these and other direct anthropogenic disturbances. There is great concern that the high rates, magnitudes, and complexity of environmental change are overwhelming the intrinsic capacity of corals to adapt and survive. Although it is important to address the root causes of changing climate, it is also prudent to explore the potential to augment the capacity of reef organisms to tolerate stress and to facilitate recovery after disturbances. Here, we review the risks and benefits of the improvement of natural and commercial stocks in noncoral reef systems and advocate a series of experiments to determine the feasibility of developing coral stocks with enhanced stress tolerance through the acceleration of naturally occurring processes, an approach known as (human)-assisted evolution, while at the same time initiating a public dialogue on the risks and benefits of this approach.

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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 (November 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 (June 1, 2017): 96–110. http://dx.doi.org/10.5507/bo.2017.021.

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18

Le, Minh Nghia, Yew Soon Ong, Stefan Menzel, Yaochu Jin, and Bernhard Sendhoff. "Evolution by Adapting Surrogates." Evolutionary Computation 21, no. 2 (May 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 proposed in the literature with ad hoc approximation/surrogate modeling methodologies considered. Since prior knowledge on the suitability of the data centric approximation methodology to use in surrogate-assisted evolutionary optimization is typically unavailable beforehand, this paper presents a novel evolutionary framework with the evolvability learning of surrogates (EvoLS) operating on multiple diverse approximation methodologies in the search. Further, in contrast to the common use of fitness prediction error as a criterion for the selection of surrogates, the concept of evolvability to indicate the productivity or suitability of an approximation methodology that brings about fitness improvement in the evolutionary search is introduced as the basis for adaptation. The backbone of the proposed EvoLS is a statistical learning scheme to determine the evolvability of each approximation methodology while the search progresses online. For each individual solution, the most productive approximation methodology is inferred, that is, the method with highest evolvability measure. Fitness improving surrogates are subsequently constructed for use within a trust-region enabled local search strategy, leading to the self-configuration of a surrogate-assisted memetic algorithm for solving computationally expensive problems. A numerical study of EvoLS on commonly used benchmark problems and a real-world computationally expensive aerodynamic car rear design problem highlights the efficacy of the proposed EvoLS in attaining reliable, high quality, and efficient performance under a limited computational budget.

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Friedberg, Richard C., and Liron Pantanowitz. "Practice Evolution: Decentralized Computer-Assisted Immunohistochemical Image Analysis." Archives of Pathology & Laboratory Medicine 133, no. 4 (April 1, 2009): 597–600. http://dx.doi.org/10.5858/133.4.597.

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20

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 (June 19, 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 employed to provide selection pressure to enrich tryptophan-producing cells. From the biosensor-assisted ALE, we obtained an evolved population of cells capable of effectively catabolizing galactose to tryptophan and subsequently used the population to obtain the best violacein producer. In addition, whole-genome sequencing of the evolved strain identified point mutations beneficial to the overproduction. Overall, we demonstrated that the biosensor-assisted ALE strategy could be used to rapidly and selectively evolve the producers to yield high violacein production.

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21

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

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22

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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23

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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24

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

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25

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 (August 2005): 133–38. http://dx.doi.org/10.1016/j.colsurfa.2005.04.017.

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26

Smith, Erin, David Pichora, and Randy Ellis. "Computer-Assisted Percutaneous Scaphoid Fixation: Concepts and Evolution." Journal of Wrist Surgery 02, no. 04 (November 8, 2013): 299–305. http://dx.doi.org/10.1055/s-0033-1357760.

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27

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

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28

Lewis, P. "Assisted Dying in France. The Evolution of Assisted Dying in France: A Third Way?" Medical Law Review 14, no. 1 (December 20, 2005): 44–72. http://dx.doi.org/10.1093/medlaw/fwi033.

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29

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 (April 12, 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 finds variants with higher fitness than those found by other directed evolution approaches. We then provide an example application in evolving an enzyme to produce each of the two possible product enantiomers (i.e., stereodivergence) of a new-to-nature carbene Si–H insertion reaction. The approach predicted libraries enriched in functional enzymes and fixed seven mutations in two rounds of evolution to identify variants for selective catalysis with 93% and 79% ee (enantiomeric excess). By greatly increasing throughput with in silico modeling, machine learning enhances the quality and diversity of sequence solutions for a protein engineering problem.

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30

Braun, Jan, Johannes Krettek, Frank Hoffmann, and Torsten Bertram. "Multi-Objective Optimization with Controlled Model Assisted Evolution Strategies." Evolutionary Computation 17, no. 4 (December 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 data based model. The convergence of the evolutionary algorithm is improved as some selection decisions rely on the model rather than to invoke expensive evaluations of the true fitness function. The novelty of our scheme stems from the preselection of solutions based on an instance based fitness model, in which the selection pressure is adjusted to the quality of model. This so-called λ-control adapts the number of true fitness evaluations to the monitored model quality. Our method extends the previous approaches for model assisted scalar optimization to multi-objective problems by a proper redefinition of model quality and preselection pressure control. The analysis on multi-objective benchmark optimization problems not only confirms the superior convergence of the model assisted evolution strategy in comparison with a multi-objective evolution strategy but also the positive effect of regulated preselection in contrast to merely static preselection.

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31

Kleidis, K., and V. K. Oikonomou. "Scalar field assisted f(R) gravity inflation." International Journal of Geometric Methods in Modern Physics 15, no. 08 (June 22, 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 identical to the one corresponding to the ordinary [Formula: see text] gravity, while the scalar-to-tensor ratio is found to be smaller than the [Formula: see text] inflation one consequently, compatibility with both the Planck 2015 and BICEP2/Keck-Array data is achieved.

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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 (June 21, 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 platforms for the hydrogen evolution reaction (HER), in which usually metal nanoparticles (NPs) or metallic compounds (generally Pt-based) act as co-catalysts. The most promising COF-based photocatalytic HER systems will be discussed, and special emphasis will be placed on rationalizing their structure and light-harvesting properties in relation to their catalytic activity and stability under turnover conditions. Finally, the aspects that need to be improved in the coming years will be discussed, such as the degree of dispersibility in water, the global photocatalytic efficiency, and the robustness and stability of the hybrid systems, putting emphasis on both the COF and the metal co-catalyst.

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33

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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34

S., Miruna Joe Amali, and Baskar S. "Surrogate assisted-hybrid differential evolution algorithm using diversity control." Expert Systems 32, no. 4 (March 12, 2015): 531–45. http://dx.doi.org/10.1111/exsy.12105.

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35

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

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36

Dial, K. P. "Wing-Assisted Incline Running and the Evolution of Flight." Science 299, no. 5605 (January 17, 2003): 402–4. http://dx.doi.org/10.1126/science.1078237.

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37

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 (October 2011): 683–86. http://dx.doi.org/10.1016/j.scriptamat.2011.07.006.

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38

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 (January 2018): 89–97. http://dx.doi.org/10.1016/j.jrras.2017.11.005.

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39

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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40

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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41

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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42

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

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43

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

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44

Stanovov, Vladimir, and Eugene Semenkin. "Surrogate-Assisted Automatic Parameter Adaptation Design for Differential Evolution." Mathematics 11, no. 13 (June 30, 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 competition, and the resulting parameter adaptation heuristics are additionally tested on CEC 2022 and SOCO benchmark suites. The results show that the proposed approach is capable of finding efficient adaptation techniques given relatively small computational resources.

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Fung, Allison. "The Rich History and Evolution of Animal-Assisted Therapy." Journal of Alternative, Complementary & Integrative Medicine 10, no. 1 (January 31, 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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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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47

Solomon, Getachew, Raffaello Mazzaro, Vittorio Morandi, Isabella Concina, and Alberto Vomiero. "Microwave-Assisted vs. Conventional Hydrothermal Synthesis of MoS2 Nanosheets: Application towards Hydrogen Evolution Reaction." Crystals 10, no. 11 (November 16, 2020): 1040. http://dx.doi.org/10.3390/cryst10111040.

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Molybdenum sulfide (MoS2) has emerged as a promising catalyst for hydrogen evolution applications. The synthesis method mainly employed is a conventional hydrothermal method. This method requires a longer time compared to other methods such as microwave synthesis methods. There is a lack of comparison of the two synthesis methods in terms of crystal morphology and its electrochemical activities. In this work, MoS2 nanosheets are synthesized using both hydrothermal (HT-MoS2) and advanced microwave methods (MW-MoS2), their crystal morphology, and catalytical efficiency towards hydrogen evolution reaction (HER) were compared. MoS2 nanosheet is obtained using microwave-assisted synthesis in a very short time (30 min) compared to the 24 h hydrothermal synthesis method. Both methods produce thin and aggregated nanosheets. However, the nanosheets synthesized by the microwave method have a less crumpled structure and smoother edges compared to the hydrothermal method. The as-prepared nanosheets are tested and used as a catalyst for hydrogen evolution results in nearly similar electrocatalytic performance. Experimental results showed that: HT-MoS2 displays a current density of 10 mA/cm2 at overpotential (−280 mV) compared to MW-MoS2 which requires −320 mV to produce a similar current density, suggesting that the HT-MoS2 more active towards hydrogen evolutions reaction.

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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 microhardness of the Sn-0.7Cu green compact also decreased as the microwave exposure time is increased.

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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 (August 25, 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 in the material and allows to describe void collapse using the Rayleigh-Plesset equation. The necessary conditions for healing are discussed with use of model results. Particularly, the role of external load during healing, the dependence on liquid viscosity and surface tension are investigated.

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Boistel, Renaud, Anthony Herrel, Gheylen Daghfous, Paul-Antoine Libourel, Elodie Boller, Paul Tafforeau, and Vincent Bels. "Assisted walking in Malagasy dwarf chamaeleons." Biology Letters 6, no. 6 (May 12, 2010): 740–43. http://dx.doi.org/10.1098/rsbl.2010.0322.

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Chamaeleons are well known for their unique suite of morphological adaptations. Whereas most chamaeleons are arboreal and have long tails, which are used during arboreal acrobatic manoeuvres, Malagasy dwarf chamaeleons ( Brookesia ) are small terrestrial lizards with relatively short tails. Like other chamaeleons, Brookesia have grasping feet and use these to hold on to narrow substrates. However, in contrast to other chamaeleons, Brookesia place the tail on the substrate when walking on broad substrates, thus improving stability. Using three-dimensional synchrotron X-ray phase-contrast imaging, we demonstrate a set of unique specializations in the tail associated with the use of the tail during locomotion. Additionally, our imaging demonstrates specializations of the inner ear that may allow these animals to detect small accelerations typical of their slow, terrestrial mode of locomotion. These data suggest that the evolution of a terrestrial lifestyle in Brookesia has gone hand-in-hand with the evolution of a unique mode of locomotion and a suite of morphological adaptations allowing for stable locomotion on a wide array of substrates.

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Journal articles on the topic 'Assisted evolution'

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