Suchergebnisse

Systemic approaches are needed and useful for the study of the very complex issue of cancer. Modeling has a central position in these systemic approaches. Metabolic reprogramming is nowadays acknowledged as an essential hallmark of cancer. Mathematical modeling could contribute to a better understanding of cancer metabolic reprogramming and to identify new potential ways of therapeutic intervention. Herein, I review several alternative approaches to metabolic modeling and their current and future impact in oncology. ; Supported by grants BIO2014-56092-R (MINECO and FEDER), P12-CTS-1507 (Andalusian Government and FEDER) and funds from group BIO-267 (Andalusian Government). The "CIBER de Enfermedades Raras" is an initiative from the ISCIII (Spain). The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.

1. Basic Concepts -- 1.1. Modeling -- 1.2. Classification of Processes -- 1.3. Process Parameters and Variables and their Classification -- 1.4. Classification of Process Models -- Capter 2. Optimizing Models -- 2.1. General Considerations -- 2.2. Objective Function — an Example -- 2.3. Designing the Objective Function -- 2.4. Objective Function as a Function of Time -- 2.5. Constrained and Unconstrained Optima -- 2.6. Objective Function — Example Revisited -- 3. Methods of Optimum Search -- 3.1. Problem Definition -- 3.2. Single Variable Search -- 3.3. Two-dimensional Search (Hill-Climbing) -- 4. Design of Experiments -- 4.1. Replication -- 4.2. Blocking of Experiments -- 4.3. Randomization -- 4.4. Factorial Design -- 4.5. Orthogonality -- 4.6. Confounding -- 4.7. Fractional Factorial Design -- 5. Dynamic Covariance Analysis -- 5.1. Dynamic Models -- 5.2. Linear Dynamic Model — Single Variable -- 5.3. End Conditions -- 5.4. Identification of Linear Model -- 5.5. Linear Dynamic Model — Multiple Variables -- 6. Principal Component Analysis -- 6.1. Reducing Number of Variables -- 6.2. Orthogonal Coordinates in Sample Space -- 6.3. Axes with Stationary Property -- 6.4. Zero-one Normalized Variables -- 6.5. Eigenvalues and Eigenvectors -- 6.6. Orthogonality -- 6.7. Mean-square Distances — Distribution of Variance -- 6.8. Numerical Example -- 6.9. Performance Variables -- 7. Regression Analysis -- 7.1. Principle of Least Squares -- 7.2. Linear Regression -- 7.3. Transformation to Linear Form -- 7.4. Choosing the Form of Model -- 7.5. Stepwise Regression -- 7.6. Non-linear Estimation -- References.

Discusses the physical and mathematical analysis of transport phenomena associated with food processing. This title presents various models that describe many of the important physical and biological transformations that occur in food during processing.

The article outlines and discusses the universal mathematical model created by the author and allowing to predict scenarios for post-Soviet secessions and, more broadly, to forecast secession potentials of any complex subnational regional units. The objects of forecasting are de facto states and different kinds of polities with failed statehood, analyzed through the prism of the "parent state – secession – patron state" triangle. The main research method is quantification of secession factors, which enables a researcher to measure the impacts of objective and subjective conditions on the course and results of secessions through the use of specific variables and indicators. As described in mathematical terms, the model has two extremes: "ideal secession" and "ideal anti-secession".

Intro -- Preface -- Contents -- To Know Without Destroying? -- 1 The MADAR Project: Historical Heritage and Math Towards a Common Path -- 2 Potential and Weaknesses of the Porto Torres (Sardinia) Case Study -- 3 Construction Techniques, Features and Historical Phases of the Complex of Central Baths -- 4 To Know Without Destroying -- References -- Representative Volume Elements for the Analysis of Concrete Like Materials by Computational Homogenization -- 1 Introduction -- 2 Generation of the Geometry of the RVE -- 2.1 Spherical Aggregate Particles -- 2.1.1 Taking Process -- 2.1.2 Placing Process -- 2.2 Polyhedral Aggregate Particles -- 3 Micro-to-Macro Computational Homogenization -- 3.1 Periodic Boundary Conditions -- 4 Numerical Results -- 5 Conclusions -- References -- A New Nonlocal Temperature-Dependent Model for Adhesive Contact -- 1 Introduction -- 1.1 Rate-Independent Models -- 1.2 Rate-Dependent Models -- 1.3 Adhesive Contact with Nonlocal Effects -- 2 The Model and the PDE System -- 2.1 The State and Dissipative Variables -- 2.2 The Free Energy -- 2.3 The Dissipation Potential -- 2.4 The Balance Equations and the Constitutive Laws -- 2.5 The PDE System -- 2.6 Outlook to the Analysis -- References -- Chemomechanical Degradation of Monumental Stones: Preliminary Results -- 1 Introduction -- 2 A Mathematical Model of Marble Sulphation -- 2.1 A Simplified Chemical Reaction -- 2.2 The Hydrodynamical Model -- 3 The Variational Approach to Fracture -- 4 A Chemo-Mechanic Model -- 4.1 Mechanical Properties -- 4.2 Diffusivity -- 4.3 Mathematical Model -- 5 A Numerical Example -- References -- Modelling the Effects of Protective Treatments in Porous Materials -- 1 Introduction -- 2 Materials and Methods -- 3 Modelling of Capillary Imbibition -- 3.1 Boundary Conditions -- 4 Numerical Results and Comparison with Experimental Data.

Intro -- Preface -- Contents -- Round Table of MACH2021 -- 1 Introduction to the Issues Faced in the Round Table -- 2 The Importance of Science and Cultural Aspects and the Impact on Political Strategies on Cultural Heritage -- 3 Critical Issues Emerged in the Management of CH During Covid-19 Pandemic, Arising Opportunities and Problems that Need to Be Faced with New Investments -- References -- Numerical Simulation of the Athens 1999 Earthquake Including Simplified Models of the Acropolis and the Parthenon: Initial Results and Outlook -- 1 Introduction -- 2 Mathematical Model and Its Numerical Discretization -- 3 Computational Setting for the September 7, 1999 Athens Earthquake -- 3.1 Numerical Model of the Seismic Source, Regional Crustal Properties and Geological Setting -- 3.2 Computational Models Setup -- 4 Numerical Results and Comparison with Observed Records -- 4.1 Simulation of the 1999 Athens Earthquake -- 4.2 Seismic Response of the Parthenon -- 5 Conclusions and Future Developments -- References -- Randomness in a Nonlinear Model of Sulphation Phenomena -- 1 Introduction -- 2 The Deterministic Model -- 3 Stochastic Boundary Condition for the S02 Concentration -- 4 A Nonlinear Model with Stochastic Dynamical Boundary Conditions -- 5 Conclusions -- References -- Automatic Description of Rubble Masonry Geometries by Machine Learning Based Approach -- 1 Introduction -- 2 The Data Set Used -- 2.1 Preparation of Geometrical Data -- 3 Basic Concepts About CNN -- 4 Variational Autoencoder (VAE) -- 5 Implementation -- 6 Experimentations -- 7 Closing Remarks -- References -- A Model for Craquelure: Brittle Layers on Elastic Substrates -- 1 A Model for a Brittle Layer on an Elastic Substrate -- 2 Analytical Treatment of the Model -- 3 Analysis of the Results in Terms of Craquelure -- 4 Conclusions -- References.