scholarly journals On path-dependent SDEs involving distributional drifts

2021 ◽  
pp. 1-23
Author(s):  
Alberto Ohashi ◽  
Francesco Russo ◽  
Alan Teixeira
Keyword(s):  
Path Dependent

Moral reasoning is the process of asking moral questions and answering them

2019 ◽  
Vol 42 ◽  
Author(s):  
Mark Alfano
Keyword(s):  
Moral Reasoning ◽  
Dependent Process ◽  
Asking Questions ◽  
Path Dependent ◽  
Path Dependent Process ◽  
Moral Questions

Abstract Reasoning is the iterative, path-dependent process of asking questions and answering them. Moral reasoning is a species of such reasoning, so it is a matter of asking and answering moral questions, which requires both creativity and curiosity. As such, interventions and practices that help people ask more and better moral questions promise to improve moral reasoning.

Stress Path Dependent Hydromechanical Properties of Carbonates - Impact of Heterogeneities and use of Effective Medium Theory for Critical State Scaling

2009 ◽  
Author(s):  
Nicolas F. Gland ◽  
Jeremie Dautriat ◽  
Olga Vizika ◽  
Alexandre Dimanov ◽  
Jean L. Raphanel
Keyword(s):  
Critical State ◽  
Effective Medium Theory ◽  
Stress Path ◽  
Effective Medium ◽  
Medium Theory ◽  
Path Dependent

The singular points binominal method for pricing American path-dependent options

2010 ◽  
Vol 14 (1) ◽  
pp. 29-56 ◽  
Author(s):  
Marcellino Gaudenzi ◽  
Antonino Zanette ◽  
Maria Antonietta Lepellere
Keyword(s):  
Singular Points ◽  
Path Dependent

Speculation in a Path Dependent World

2016 ◽  
Author(s):  
Nakul Nayyar
Keyword(s):  
Path Dependent

Path-Dependent Backward Stochastic Volterra Integral Equations with Jumps

2016 ◽  
Author(s):  
Ludger Overbeck ◽  
Jasmin A.L. RRder
Keyword(s):  
Integral Equations ◽  
Volterra Integral Equations ◽  
Path Dependent

Trading with Path-Dependent Effect: A Continuous-Time Cointegration Perspective

2020 ◽  
Author(s):  
Tingjin Yan ◽  
Hoi Ying Wong
Keyword(s):  
Continuous Time ◽  
Dependent Effect ◽  
Path Dependent

Is Government Growth Inevitable?

2019 ◽  
pp. 587-604
Author(s):  
Randall G. Holcombe
Keyword(s):  
Twentieth Century ◽  
Size Of Government ◽  
Equilibrium Conditions ◽  
Government Growth ◽  
Equilibrium Size ◽  
Path Dependent ◽  
The U.S

Despite massive worldwide growth of government in the twentieth century, there have been periods in the U.S. and other countries when growth has slowed or reversed. Government growth is not inevitable. Explanations of government growth fall into three major categories. Path-dependent theories emphasize factors that continually push the size of government up, so the current size is in part a function of its past size. Theories about the equilibrium size of government explain why government is big, but not why government grows. If equilibrium conditions change, that can produce government growth. Theories also describe ideological shifts that cause people to want, or at least accept, bigger governments. All these explanations could have an effect on government growth. However, none appears to be persuasive enough to explain all the growth that occurred.

scholarly journals A computational framework to establish data-driven constitutive models for time- or path-dependent heterogeneous solids

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Weijian Ge ◽  
Vito L. Tagarielli
Keyword(s):  
Constitutive Models ◽  
Computational Procedure ◽  
Data Driven ◽  
Dissipated Energy ◽  
Computational Framework ◽  
Heterogeneous Solids ◽  
Non Linear ◽  
Recorded Data ◽  
Path Dependent ◽  
Computational Homogenisation

AbstractWe propose and implement a computational procedure to establish data-driven surrogate constitutive models for heterogeneous materials. We study the multiaxial response of non-linear n-phase composites via Finite Element (FE) simulations and computational homogenisation. Pseudo-random, multiaxial, non-proportional histories of macroscopic strain are imposed on volume elements of n-phase composites, subject to periodic boundary conditions, and the corresponding histories of macroscopic stresses and plastically dissipated energy are recorded. The recorded data is used to train surrogate, phenomenological constitutive models based on neural networks (NNs), and the accuracy of these models is assessed and discussed. We analyse heterogeneous composites with hyperelastic, viscoelastic or elastic–plastic local constitutive descriptions. In each of these three cases, we propose and assess optimal choices of inputs and outputs for the surrogate models and strategies for their training. We find that the proposed computational procedure can capture accurately and effectively the response of non-linear n-phase composites subject to arbitrary mechanical loading.

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