Differential Models, Numerical Simulations and Applications |
Autore | Bretti Gabriella |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
Descrizione fisica | 1 electronic resource (240 p.) |
Soggetto topico |
Research & information: general
Mathematics & science |
Soggetto non controllato |
conservation laws
feedback stabilization input-to-state stability numerical approximations nonlocal velocity macroscopic models traffic data gap analysis multi-phase models Volterra integral equations asymptotic-preserving numerical stability Cellular Potts model cell migration nucleus deformation microchannel device regularization theory multivariate stochastic processes cross-power spectrum magnetoencephalography MEG functional connectivity spectral complexity soil organic carbon RothC non-standard integrators Exponential Rosenbrock–Euler langevin equation Mean Field Games system kinetic Fokker–Planck equation hypoelliptic operators Caputo fractional derivative Allee effect existence and stability Hopf bifurcation implicit schemes optimal design soft tissue mechanics mutual information biaxial experiment inverse problems information theory LWR model follow-the-leader model phase transition creeping seepage fundamental diagram lane discipline networks aggregation equation relaxation limit scalar conservation law finite volume scheme differential equations mathematical biology microfluidic chip applied mathematics numerical methods computational mathematics differential and integro-differential models |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557897703321 |
Bretti Gabriella
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Mathematical Modeling in Cultural Heritage [[electronic resource] ] : MACH2021 / / edited by Gabriella Bretti, Cecilia Cavaterra, Margherita Solci, Michela Spagnuolo |
Autore | Bretti Gabriella |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (230 pages) |
Disciplina | 363.69015118 |
Altri autori (Persone) |
CavaterraCecilia
SolciMargherita SpagnuoloMichela |
Collana | Springer INdAM Series |
Soggetto topico |
Differential equations
Mathematics Differential Equations Applications of Mathematics |
ISBN | 981-9936-79-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 1: Round Table The impact of Covid-19 pandemic on cultural heritage: from fruition to conservation practises -- Chapter 2: Numerical simulation of the Athens 1999 earthquake including simplified models of the Acropolis and the Parthenon: initial results and outlook -- Chapter 3: Randomness in a nonlinear model of sulphation phenomena -- Chapter 4: Automatic description of rubble masonry geometries by machine learning based approach -- Chapter 5: Themes and reflections upon structural analysis in the field of archaeology -- Chapter 6: A model for craquelure: brittle layers on elastic substrates -- Chapter 7: From point clouds to 3D simulations of marble sulfation -- Chapter 8: A semi-analytical approach to approximate chattering time of rocking structures -- Chapter 9: Numerical modelling of historical masonry structures with the finite element code NOSA-ITACA -- Chapter 10: Mathematical Methods for the Shape Analysis and Indexing of Tangible CH artefacts -- Chapter 11: Multiscale carbonation models – a review -- Chapter 12: Forecasting damage and consolidation: mathematical models of reacting flows in porous media -- Chapter 13: Models and mathematical issues in color film restorations. |
Record Nr. | UNINA-9910736996603321 |
Bretti Gabriella
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
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Lo trovi qui: Univ. Federico II | ||
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Mathematical Models and Computer Simulations for Biomedical Applications / / edited by Gabriella Bretti, Roberto Natalini, Pasquale Palumbo, Luigi Preziosi |
Autore | Bretti Gabriella |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (261 pages) |
Disciplina | 511.8 |
Altri autori (Persone) |
NataliniRoberto
PalumboPasquale PreziosiLuigi |
Collana | SEMA SIMAI Springer Series |
Soggetto topico |
Mathematics
Mathematics - Data processing Applications of Mathematics Computational Mathematics and Numerical Analysis Enginyeria biomèdica Simulació (Ciències de la salut) Models matemàtics Aplicacions industrials |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-031-35715-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Contents -- An Application of the Grünwald-Letinkov Fractional Derivative to a Study of Drug Diffusion in Pharmacokinetic CompartmentalModels -- 1 Introduction -- 2 Pharmacokinetic Two Compartmental Model -- 2.1 Grünwald-Letinkov Approximation for Bicompartmental Model (14) -- 2.2 Non-standard Discretization of Bicompartmental Model (14) -- 2.3 Fractional Bicompartmental Model -- 3 Bicompartmental Model with NPs Infusion -- 4 Applications of Fractional Calculus to Model Drug Diffusion in a Three Compartmental Pharmacokinetic Model -- 5 Discussion -- References -- Merging On-chip and In-silico Modelling for Improved Understanding of Complex Biological Systems -- 1 Introduction -- 2 The Organs-on-Chip Technology -- 2.1 Setting of the Laboratory Experiments -- 3 Mathematical Modeling of OoC -- 3.1 Macroscopic Model for CoC Experiment BBN -- 3.1.1 Interface Between 2D-1D Models in (1)-(4) -- 3.2 Hybrid Macro-Micro Model for CoC Experiment BDNPR -- 3.2.1 Function F1: Chemotactic Term -- 3.2.2 Function F2: ICs/TCs Repulsion -- 3.2.3 Function F3: ICs Adhesion/Repulsion -- 3.2.4 Friction -- 3.2.5 Function F4: Production of Chemical Signal -- 3.2.6 Initial Conditions -- 3.2.7 Boundary Conditions -- 3.2.8 Stochastic Model -- 3.3 Future Directions: Mean-Field Limits and Nonlocal Models NP2022 -- 4 Numerical Approximation -- 4.1 Numerical Schemes for the Approximation of the Models (1)-(4) -- 4.1.1 Stability at Interfaces -- 4.2 Numerical Schemes for the Approximation of the Model (7)-(8) -- 4.2.1 Discretization of the PDE (Eq.(7)) -- 4.2.2 Boundary Conditions -- 4.2.3 Discretization of the ODE (8) -- 4.3 Discretization of the SDE (20) -- 5 Simulation Results -- 5.1 Simulation Results Obtained by Macroscopic Model -- 5.1.1 Time Evolution of Macroscopic Densities -- 5.2 Simulation Results Obtained by Hybrid Macro-Micro Model.
5.2.1 Scenario 1: Deterministic Motion -- 5.2.2 Scenario 2: Deterministic Motion Including Cell Death -- 5.2.3 Scenario 3: Stochastic Motion -- 6 Conclusions -- References -- A Particle Model to Reproduce Collective Migrationand Aggregation of Cells with Different Phenotypes -- 1 Introduction -- 2 Mathematical Framework and Representative Simulations -- 2.1 Cell Proliferation -- 2.2 Cell Movement -- 2.2.1 Cell Repulsive Behavior and Random Movement -- 2.2.2 Phenotypic-Related Cell Behavior -- 3 Model Application: Wound Healing Assay -- 4 Conclusions -- References -- Modelling HIF-PHD Dynamics and Related Downstream Pathways -- 1 Introduction -- 2 HIFs and PHDs -- 2.1 Equilibrium States -- 2.2 The Limit ζ0 -- 2.3 The Anoxic Limit -- 2.4 HIF-PHD Dynamics -- 3 Hypoxia and Inflammation -- 3.1 HIF-Alarmin-NFkB Dynamics -- 3.2 HIF-Interleukine Dynamics -- 4 Modelling Other HIF-Related Downstream Pathways -- 4.1 HIF and Metabolism -- 4.2 HIF and pH -- 4.3 HIF and Cell Cycle -- 4.4 HIF and ECM-Stiffening -- 4.5 HIF and VEGF -- 4.6 HIF and High Altitude -- References -- An Imaging-Informed Mechanical Framework to Providea Quantitative Description of Brain Tumour Growthand the Subsequent Deformation of White Matter Tracts -- 1 Introduction -- 2 A Multiphase Model for Brain Tumour Growth -- 2.1 Eulerian Formulation -- 2.1.1 Balance Equations -- 2.1.2 Stress Tensor and Constitutive Equations -- 2.1.3 Nutrients -- 2.1.4 Diffusion Tensor D and Preferential Directions Tensor A -- 2.1.5 Interface Conditions at the Boundary Between the Tumour and the Healthy Tissue -- 2.2 Lagrangian Formulation of the Model -- 3 Numerical Implementation -- 3.1 Weak Formulation of the Lagrangian Model -- 3.2 Discrete Formulation of the Continuous Variational Problems -- 3.3 Parameters Estimation -- 3.4 Mesh Preparation -- 4 Numerical Simulations in the Brain. 5 Conclusions and Future Developments -- References -- A Multi-Scale Immune System Simulator for the Onset of Type2 Diabetes -- 1 Introduction -- 2 Mathematical Models -- 2.1 The Model of Metabolism -- 2.2 The Hormonal Glucagon/Insulin Model -- 2.3 The Model of the Physical Exercise -- 2.4 The Model of Food Intake, Stomach Emptying and Macronutrient Absorption -- 2.5 Modeling Total Daily Energy Balance and Body Weight -- 2.6 Modeling the Effect of a Calorie Excess on the Adipocytes -- 2.7 The Model of IL-6 Release -- 2.8 The Model of Inflammation -- 3 Results -- 3.1 Setting the Parameters for the Glucagon/Insulin Model -- 3.2 Simulating Different Lifestyle Scenarios -- 4 Discussion and Conclusions -- References -- Molecular Fingerprint Based and Machine Learning Driven QSAR for Bioconcentration Pathways Determination -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Processing -- 2.2 Machine Learning Models -- 2.2.1 Extreme Gradient Boosting -- 2.2.2 Support Vector Machines -- 2.2.3 Neural Networks -- 2.2.4 Spiking Neural Networks -- 3 Results -- 4 Discussion -- 5 Conclusions -- Appendix -- Author contributions -- References -- Advanced Models for COVID-19 Variant Dynamicsand Pandemic Waves -- 1 Introduction -- 2 Description of Data -- 3 Drivers of Case Count -- 4 Data Analysis -- 4.1 Computation of ``Switching Time'' -- 4.2 Days Between Variants Dominance and Cases Peak -- 4.3 Comparing the Trend of Variant Progression with Cases Progression -- 5 Modeling a Virus with Mutation -- 5.1 Epidemiological Modeling -- 5.2 Definition of MC-ODE System -- 5.3 Simulations -- 6 Discussion -- References -- Multifractal Spectrum Based Classification for Breast Cancer -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Patient-Based Breast Cancer Identification -- 4.1 Image Processing -- 4.2 Fractal Dimension -- 4.3 Multifractal Spectrum. 5 Experiments and Results -- 5.1 The Extended Dataset: Structure and Preprocessing -- 5.2 Classification Results -- 5.3 Discussion -- 6 Conclusions -- References. |
Record Nr. | UNINA-9910739416303321 |
Bretti Gabriella
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
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Lo trovi qui: Univ. Federico II | ||
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