1. Albi, G., Artina, M., Foransier, M., Markowich, P.: Biological transportation networks: modeling and simulation. Anal. Appl. 14, 185–206 (2016). https:// doi. org/ 10. 1142/ S0219 53051 54000 59 2. Albi, G., Burger, M., Haskovec, J., Markowich, P., Schlottbom, M.: Continuum Modelling of Biological Network Formation. Active Particles, vol. I: Theory, Models, Applications. Birkhäuser-Springer, Boston (2017) 3. Alcubierre, M., Schutz, B.F.: Time symmetric ADI and casual reconnection. In: International Workshop on Numerical Relativity. Cambridge University Press, Cambridge (1992) 4. Ambrosio, L., Gigli, N., Savaré, G.: Gradient Flows: in Metric Spaces and in the Space of Probability Measures. Springer Sci. Bus. Media, Basel (2005). https:// link. sprin ger. com/ book/ 10. 1007/ b1370 80 5. Astuto, C., Boffi, D., Credali, F.: Finite element discretization of a biological network formation system: a preliminary study. arXiv: 2303. 10625 (2023) 6. Astuto, C., Boffi, D., Haskovec, J., Markowich, P., Russo, G.: Comparison of two aspects of a PDE model for biological network formation. Math. Comput. Appl. 27, 87 (2022). https:// doi. org/ 10. 3390/ mca27 050087 7. Carrillo, J.A., Toscani, G.: Wasserstein metric and large-time asymptotics of nonlinear diffusion equations. In: New Trends in Mathematical Physics: In Honour of the Salvatore Rionero 70th Birthday— Proceedings of the International Meeting (2004). https:// doi. org/ 10. 1142/ 97898 12702 319_ 0022 8. Chen, Q., Jiang, L., Li, C., Hu, D., Bu, J., Cai, D., Du, J.: Haemodynamics-Driven Developmental Pruning of Brain Vasculature in Zebrafish. Public Library of Science, San Francisco (2012). https:// doi. org/ 10. 1371/ journ al. pone. 00476 17 9. Eichmann, A., Le Noble, F., Autiero, M., Carmeliet, P.: Guidance of vascular and neural network formation. Curr. Opin. Neurobiol. 15, 108–115 (2005). https:// doi. org/ 10. 1016/j. conb. 2005. 08. 012 10. Fang, D., Jin, S., Markowich, P., Perthame, B.: Implicit and semi-implicit numerical schemes for the gradient flow of the formation of biological transport networks. SMAI J. Comput. Math. 5, 229–249 (2019). https:// doi. org/ 10. 5802/ smai- jcm. 59 11. Hacking, W.J., Van Bavel, E., Spaan, J.A.: Shear stress is not sufficient to control growth of vascular networks: a model study. Am. J. Physiol. Heart Circ. Physiol. 270, H364–H375 (1996). https:// doi. org/ 10. 1152/ ajphe art. 1996. 270.1. H364 12. Haskovec, J., Markowich, P., Pilli, G.: Tensor PDE model of biological network formation. Commun. Math. Sci. 20, 1173–1191 (2022) 13. Haskovec, J., Markowich, P., Perthame, B.: Mathematical analysis of a PDE system for biological network formation. Comm. Partial Differential Equations 40, 918–956 (2015). https:// doi. org/ 10. 1080/ 03605 302. 2014. 968792 14. Haskovec, J., Markowich, P., Perthame, B., Schlottbom, M.: Notes on a PDE system for biological network formation. Nonlinear Anal. 138, 127–155 (2016). https:// doi. org/ 10. 1016/j. na. 2015. 12. 010 15. Haskovec, J., Markowich, P., Portaro, S.: Emergence of biological transportation networks as a selfregulated process. Discrete Contin. Dyn. Syst. 43, 1499–1515 (2022). https:// doi. org/ 10. 3934/ dcds. 20221 59 16. Hu, D.: Optimization, Adaptation, and Initialization of Biological Transport Networks. Notes from Lecture 1, 3–1 (2013) 17. Hu, D., Cai, D.: Adaptation and optimization of biological transport networks. Phys. Rev. Lett. 111, 138701 (2013). https:// doi. org/ 10. 1103/ PhysR evLett. 110. 138101 18. Hu, D., Cai, D.: An optimization principle for initiation and adaptation of biological transport networks. Commun. Math. Sci. 17, 1427–1436 (2019) 19. Hu, D., Cai, D., Rangan, A.V.: Blood vessel adaptation with fluctuations in capillary flow distribution. PLoS One 7, 45444 (2012). https:// doi. org/ 10. 1371/ journ al. pone. 00447 97 20. Malinowski, R.: Understanding of leaf development—the science of complexity. Plants 2, 396–415 (2013). https:// doi. org/ 10. 3390/ plant s2040 541 21. Michel, O., Biondi, J.: Morphogenesis of neural networks. Neural Process. Lett. 2, 9–12 (1995). https:// doi. org/ 10. 1007/ BF023 09873 22. Otto, F.: Double Degenerate Diffusion Equations as Steepest Descent. Bonn University (1996). https:// books. google. com. sa/ books? id= oxLdG wAACA AJ 23. Otto, F.: The geometry of dissipative evolution equations: the porous medium equation. Comm. Partial Differential Equations 26, 101–174 (2001). https:// doi. org/ 10. 1081/ PDE- 10000 2243 24. Peaceman, D.W., Rachford, H.H., Jr.: The numerical solution of parabolic and elliptic equations. J. Soc. Ind. Appl. Math. 3, 28–41 (1955) 25. Pohl, U., Holtz, J., Busse, R., Bassenge, E.: Crucial role of endothelium in the vasodilator response to increased flow in vivo. Hypertension 8, 37–44 (1986). https:// doi. org/ 10. 1161/ 01. hyp.8. 1. 37 26. Pries, A.R., Secomb, T.W., Gaehtgens, P.: Structural adaptation and stability of microvascular networks: theory and simulations. Am. J. Physiol. Heart Circ. Physiol. 275, H349–H360 (1998). https:// doi. org/ 10. 1152/ ajphe art. 1998. 275.2. H349 27. Raudino, A., Grassi, A., Lombardo, G., Russo, G., Astuto, C., Corti, M.: Anomalous sorption kinetics of self-interacting particles by a spherical trap. Commun. Comput. Phys. 31, 707–738 (2022). https:// doi. org/ 10. 4208/ cicp. OA- 2021- 0101 28. Santambrogio, F.: Euclidean, metric, and Wasserstein gradient flows: an overview. Bull. Math. Sci. 7, 87–154 (2017). https:// doi. org/ 10. 1007/ s13373- 017- 0104-8 29. Sedmera, D.: Function and Form in the Developing Cardiovascular System. Cardiovascular Research. Oxford University Press, Oxford (2011). https:// doi. org/ 10. 1093/ cvr/ cvr228 30. Villani, C.: Topics in Optimal Transportation. American Mathematical Society, Providence (2003) 31. Villani, C.: Optimal Transport: Old and New. Springer, Berlin (2009) 32. Villani, C.: Couplings and changes of variables. In: Optimal Transport. Grundlehren der mathematischen Wissenschaften, vol 338. Springer, Berlin, Heidelberg (2009). https:// doi. org/ 10. 1007/ 978-3- 540- 71050-9_1 |