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SSRN 2023年

作者： Karditsa, Katerina A. Niavis, Spyros Paramana, Theodora Monioudi, Isavela Poulos, Serafeim Hatzaki, Maria Department of Ports Management and Shipping National and Kapodistrian University of Athens Evripos Campus Greece Department of Planning and Regional Development University of Thessaly Volos Greece Laboratory of Environmental Chemistry Department of Chemistry National and Kapodistrian University of Athens Greece Department of Marine Sciences University of the Aegean Mytilene Greece Laboratory of Physical Geography Section of Geography and Climatology Department of Geology and Geoenvironment National and Kapodistrian University of Athens Greece Laboratory of Climatology and Atmospheric Environment Section of Geography and Climatology Department of Geology and Geoenvironment National and Kapodistrian University of Athens Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology-Hellas Heraklion70013 Greece

Beaches are among the most common areas for tourism activity constituting valuable economic resources. However, due to their location in the coastal zone they are particularly exposed to the impacts of Climate Change (CC), which is expected to have broad implications for the development prospects of the economy and human welfare, as a result of, amongst other, extreme events and sea-level rise. Looking beyond 2050, it is considerably important for beach tourism managers to have developed proper adaptation strategies. The main scope of the paper is to support tourism adaptation planning, in response to sea level rise impacts on beach zones at a regional scale, and in specific in the touristic beaches of Ionian Islands (Greece). The methodology follows the AR6 (IPCC, 2022) approach for Risk Assessment along with the concept of the Impact Chain according to which Risk is expressed as a function of factors (i) Hazard (H), (ii) Vulnerability (V) (sensitivity and adaptive capacity) and (iii) Exposure (E). Adaptation prospects consider both physico-geographical and tourism information to respond to climatic risk and highlight the priorities to indicate case-by-case proper adaptation measures. © 2023, The Authors. All rights reserved.

关键词： Beaches

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Dynamics and rheology of polymer melts via hierarchical atomistic, coarse-grained, and slip-spring simulations

arXiv

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arXiv 2021年

作者： Behbahani, Alireza Foroozani Schneider, Ludwig Rissanou, Anastassia Chazirakis, Anthony Bačová, Petra Jana, Pritam Kumar Li, Wei Doxastakis, Manolis Polińska, Patrycja Burkhart, Craig Müller, Marcus Harmandaris, Vagelis A. Institute of Applied and Computational Mathematics Foundation for Research and Technology - Hellas HeraklionGR-71110 Greece Institute for Theoretical Physics Georg-August University Göttingen Germany Department of Chemical and Biomolecular Engineering University of Tennessee KnoxvilleTN37996 United States Goodyear S.A. Avenue Gordon Smith Colmar-BergL-7750 Luxembourg The Goodyear Tire and Rubber Company 142 Goodyear Blvd. AkronOH44305 United States Department of Mathematics and Applied Mathematics University of Crete HeraklionGR-71110 Greece Computation-based Science and Technology Research Center The Cyprus Institute Nicosia2121 Cyprus

A hierarchical (triple scale) simulation methodology is presented for the prediction of the dynamical and rheological properties of high molecular weight entangled polymer melts. The methodology consists of atomistic, moderately coarse-grained (mCG), and highly coarse-grained slip-spring (SLSP) simulations. At the mCG level, a few chemically bonded atoms are lumped into one coarse-grained bead. At this level, the chemical identity of the underlying atomistic system, and the interchain topological constraints (entanglements) are preserved. The mCG interaction potentials are derived by matching local structural distributions of the mCG model to those of the atomistic model through iterative Boltzmann inversion. For matching mCG and atomistic dynamics, the mCG time is scaled by a time scaling factor, which compensates for the lower monomeric friction coefficient of the mCG model than that of the atomistic one. At the SLSP level, multiple Kuhn segments of a polymer chain are represented by one coarse-grained bead. The very soft nonbonded interactions between beads do not prevent chain crossing and, hence, can not capture entanglements. The topological constraints are represented by slip-springs, restricting the lateral motion of polymer chains. A compensating pair potential is used in the SLSP model, to keep the static macromolecular properties unaltered upon the introduction of slip-springs. The static and kinetic parameters of the SLSP model are determined based on the lower level simulation models. Particularly, matching the orientational autocorrelation of the end-to-end vector, we determine the number of slip-springs and calibrate the timescale of the SLSP model. As the test case, the hierarchical methodology is applied to cis-1,4-polybutadiene (cPB) at 413 K. Dynamical single-chain and linear viscoelastic properties of cPB melts are calculated for a broad range of molecular weights, ranging from unentangled to well-entangled chains. The calculations are compared,

关键词： Polymer melts

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A posteriori error estimate for the IPDGFEM of a Kirchhoff-Love bending plate

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AIP Conference Proceedings 2022年第1期2611卷

作者： Konstantinos G. Eptaimeros Institute of Applied and Computational Mathematics Foundation for Research and Technology 100 N. Plastira Str. Vassilika Vouton Heraklion Crete GR 70013

This research objective revolves around a posteriori error analysis for the symmetric interior penalty discontinu- ous Galerkin finite element method (IPDGFEM) of a Kirchhoff-Love bending plate. To be more specific, a reliable a posteriori error estimate of residual type in the energy seminorm for the IPDG method of a Kirchhoff-Love bending plate model is established.

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The inverse-deformation approach to fracture

arXiv

引用

arXiv 2020年

作者： Rosakis, Phoebus Healey, Timothy J. Alyanak, Ugur Department of Mathematics and Applied Mathematics University of Crete Heraklion Crete70013 Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology-Hellas Voutes Crete70013 Greece Department of Mathematics Cornell University IthacaNY14853 United States Field of Theoretical and Applied Mechanics Cornell University IthacaNY14853 United States

We propose a one-dimensional, nonconvex elastic constitutive model with higher gradients that can predict spontaneous fracture at a critical load via a bifurcation analysis. It overcomes the problem of discontinuous deformations without additional field variables, such as damage or phase-field variables, and without a priori specified surface energy. Our main tool is the use of the inverse deformation, which can be extended to be a piecewise smooth mapping even when the original deformation has discontinuities describing cracks opening. We exploit this via the inverse-deformation formulation of finite elasticity due to Shield and Carlson, including higher gradients in the energy. The problem is amenable to a rigorous global bifurcation analysis in the presence of a unilateral constraint. Fracture under hard loading occurs on a bifurcating solution branch at a critical applied stretch level and fractured solutions are found to have surface energy arising from higher gradient effects. Copyright © 2020, The Authors. All rights reserved.

关键词： Bifurcation (mathematics)

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Deep operator network models for predicting post-burn contraction

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Clinical Biomechanics 2025年

作者： Selma Husanovic Ginger Egberts Alexander Heinlein Fred Vermolen Delft Institute of Applied Mathematics (DIAM) Faculty of Electrical Engineering Mathematics & Computer Science Delft University of Technology Mekelweg 4 2628 CD Delft the Netherlands Research Group Computational Mathematics (CMAT) Department of Mathematics and Statistics University of Hasselt Hasselt Belgium Department of Plastic Reconstructive & Hand Surgery Amsterdam UMC Amsterdam the Netherlands Dutch Burns Foundation Beverwijk the Netherlands

Background Burn injuries present a significant global health challenge. Among the most severe long-term consequences are contractures , which can lead to functional impairments and disfigurement. Understanding and predicting the evolution of post-burn wounds is essential for developing effective treatment strategies. Traditional mathematical models, while accurate, are often computationally expensive and time-consuming, limiting their practical application. Recent advancements in machine learning, particularly in deep learning, offer promising alternatives for accelerating these predictions. Methods This study explores the use of a deep operator network , a type of neural operator, as a surrogate model for finite element simulations aimed at predicting post-burn contraction across multiple wound shapes. A deep operator network was trained on three distinct initial wound shapes, with enhancements made to the architecture by incorporating initial wound shape information and applying sine augmentation to enforce boundary conditions. Findings The performance of the trained deep operator network was evaluated on a test set including finite element simulations based on convex combinations of the three basic wound shapes. The model achieved an R 2 score of 0.99 , indicating strong predictive accuracy and generalization. Moreover, the model provided reliable predictions over an extended period of up to one year, with speedups of up to 128-fold on the Central Processing Unit and 235-fold on the Graphical Processing Unit, compared to the numerical model. Interpretation These findings suggest that deep operator networks can effectively serve as a surrogate for traditional finite element methods in simulating post-burn wound evolution, with potential applications in medical treatment planning.

关键词： Operator learning Neural networks Surrogate model Wound modeling

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Asymptotics for the Phase Space Schrödinger Equation

arXiv

引用

arXiv 2020年

作者： Karageorge, Panos D. Makrakis, George N. Department of Mathematics and Applied Mathematics University of Crete Voutes Campus Heraklion700 13 Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology 100 Nikolaou Plastira St Vassilika Vouton Heraklion700 13 Greece

We consider semi-classical time evolution for the phase space Schrödinger equation. We construct a semi-classical phase space propagator in terms of semi-classical wave packets by the Anisotropic Gaussian Approximation, related to the Nearby Orbit Approximation. We deduce the canonical system in double phase space, related to the Berezin-Shubin-Marinov canonical system and construct a semi-classical asymptotic solution of the Cauchy problem for the phase space Schrödinger equation for initial WKB states. We illustrate the method for sub-quadratic potentials in *** Codes 35Q40, 81S30, 81Q20 Copyright © 2020, The Authors. All rights reserved.

关键词： Wave packets

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Structure Of Biomolecules Through Molecular Dynamics Simulations

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Procedia Computer Science 2019年 156卷 69-78页

作者： Maria Arnittali Anastassia N. Rissanou Vagelis Harmandaris Institute of Applied and Computational Mathematics Foundation for Research and Technology Hellas Heraklion Crete GR-70013 Greece Department of Mathematics and Applied Mathematics University of Crete Voutes Campus Heraklion Crete GR-70013 Greece

Proteins are complex biological macromolecules performing a great variety of functions in the living systems. In order to get insight into the atomic structures and the time evolution of proteins, besides experimental techniques, mathematical and computational modeling approaches can be also used. Nowadays, Molecular Dynamics (MD) simulations constitute a powerful technique for understanding the physical basis of the structure of proteins, since via MD simulations someone can obtain information about proteins at the microscopic level and express it in macroscopic properties. In the current work, we present a detailed simulation approach concerning the modeling of two proteins in the native state, through all-atom Molecular Dynamics simulations under specific (physiological) conditions. The homodimeric Rop protein, that is a paradigm of a canonical 4-a-helical bundle, and its loopless mutation (RM6) are studied in aqueous solution. Their structural, conformational properties, as well as their hydrogen bond network, are characterized in atomic detail. Our findings reveal that both Rop and RM6 proteins have stable native states. The stability of the secondary conformation can be attributed to the formation of hydrogen bonds. The calculation of the root mean square deviation (RMSD) verifies that the system is in an equilibrated structure, validating at the same time, our model. Furthermore, the stereochemical quality of our protein models is demonstrated through the calculation of the Ramachandran plot. Finally, the thermal stability of RM6 protein is studied, and the results show that it is a hyperthermostable protein.

关键词： Proteins ROP RM6 Molecular Dynamics Simulations Native State Protein Stability

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Renyi divergence and non-deterministic subsampling in Rigid Image Registration

Renyi divergence and non-deterministic subsampling in Rigid ...

引用

IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： C. Spanakis E. Mathioudakis N. Kampanis N. Tsiknakis K. Marias Computational BioMedicine Lab (CBML) Institute of Computer Science Foundation for Research and Technology-Hellas School of Mineral Resources Engineering Technical University of Crete Institute of Applied and Computational Mathematics Foundation for Research and Technology-Hellas Hellenic Mediterranean University

ISBN: (数字)9781728138688

ISBN: (纸本)9781728138695

The successful application and reported robustness of Mutual Information both in rigid and nonrigid image registration over the last decades gave rise to an ongoing research on other information based similarity metrics emanating from Renyi Divergence. To the best of our knowledge however, this is the first paper studying the effects of Renyi parameter in combination with a subsampling factor in image registration accuracy. To this end, a series of experiments are presented with respect to the effect of Renyi's parameter and the subsampling factor in registration accuracy. Our results show that the increase of the Renyi parameter and the percentage of the pixels used leads, on average, to the reduction of the registration error.

关键词： Image registration Mutual information Random variables Biomedical imaging Biomedical measurement Robustness Entropy

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(f, Γ)-divergences: Interpolating between f-divergences and integral probability metrics

arXiv

引用

arXiv 2020年

作者： Birrell, Jeremiah Dupuis, Paul Katsoulakis, Markos A. Pantazis, Yannis Rey-Bellet, Luc TRIPODS Institute for Theoretical Foundations of Data Science University of Massachusetts Amherst AmherstMA01003 United States Division of Applied Mathematics Brown University ProvidenceRI02912 United States Department of Mathematics and Statistics University of Massachusetts Amherst AmherstMA01003 United States Institute of Applied and Computational Mathematics Foundation for Research and Technology - Hellas HeraklionGR-70013 Greece

We develop a rigorous and general framework for constructing information-theoretic divergences that subsume both f-divergences and integral probability metrics (IPMs), such as the 1-Wasserstein distance. We prove under which assumptions these divergences, hereafter referred to as (f, Γ)- divergences, provide a notion of 'distance' between probability measures and show that they can be expressed as a two-stage mass-redistribution/mass-transport process. The (f, Γ)-divergences inherit features from IPMs, such as the ability to compare distributions which are not absolutely continuous, as well as from f-divergences, namely the strict concavity of their variational representations and the ability to control heavy-tailed distributions for particular choices of f. When combined, these features establish a divergence with improved properties for estimation, statistical learning, and uncertainty quantification applications. Using statistical learning as an example, we demonstrate their advantage in training generative adversarial networks (GANs) for heavy-tailed, not-absolutely continuous sample distributions. We also show improved performance and stability over gradientpenalizedWasserstein GAN in image generation. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

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The Deterministic and Stochastic Shallow Lake Problem 1

引用

Conference in Honor of the 75th Birthday of S.R.S. Varadhan, 2016

作者： Kossioris, G.T. Loulakis, M. Souganidis, P.E. Department of Mathematics and Applied Mathematics Voutes Campus University of Crete Heraklion700 13 Greece School of Applied Mathematical and Physical Sciences National Technical University of Athens Athens157 80 Greece Institute of Applied and Computational Mathematics-Foundation of Research and Technology Hellas Heraklion700 13 Greece Department of Mathematics University of Chicago 5734 S. University Avenue ChicagoIL60637 United States

ISBN: (数字)9783030153380

ISBN: (纸本)9783030153373

We study the welfare function of the deterministic and stochastic shallow lake problem. We show that the welfare function is the viscosity solution of the associated Bellman equation, we establish several properties including its asymptotic behaviour at infinity and we present a convergent monotone numerical scheme. © Springer Nature Switzerland AG 2019.

关键词： Stochastic systems

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