micropolar plasticity provides the capability to carry out post-failure simulations of geo-structures due to microstructural considerations and embedded length scale in its formulation. an essential part of the numerical implementation of a micropolar plasticity model is the integration of the rate constitutive equations. efficiency and robustness of the implementation hinge on the type of inte...

In this paper the derivation of the second differentiation of a general yield surface implicit time stepping method along with its consistent elastic-plastic modulus is studied. Moreover, the explicit, trapezoidal implicit and fully implicit time stepping schemes are compared in rate-dependant plasticity. It is shown that implementing fully implicit time stepping scheme in rate-dependant plasti...

Clayey soils are the most common material used for water sealing and undertake an important role in controlling landfill-related pollution. Organic liquids can adversely affect the effectiveness of clay liners by drastically increasing their hydraulic conductivity. The aim of this study is to investigate and compare the permeability in two types of clay with different plasticity, exposed to the...

Fear is a graded central motive state ranging from mild to intense. As threat intensity increases, fear transitions from discriminative to generalized. The circuit mechanisms that process threats of different intensity are not well resolved. Here, we isolate a unique population of locally projecting neurons in the central nucleus of the amygdala (CeA) that produce the neuropeptide corticotropin...

Micropolar plasticity provides the capability to carry out post-failure simulations of geo-structures due to microstructural considerations and embedded length scale in its formulation. An essential part of the numerical implementation of a micropolar plasticity model is the integration of the rate constitutive equations. Efficiency and robustness of the implementation hinge on the type of int...

This talk will introduce the idea that talent development is related to learning where learning is the physiological process of neuro-plastic changes in the brain. To develop talents, individuals must move from novice or beginner’s status to expertise levels of knowledge or skills in a particular domain. Learning depends on maximizing an individual’s potential through the experience...

Abstract The recently proposed network model, Operational Neural Networks (ONNs), can generalize the conventional Convolutional (CNNs) that are homogenous only with a linear neuron model. As heterogenous ONNs based on generalized model encapsulate any set of non-linear operators to boost diversity and learn highly complex multi-modal functions or spaces minimal complexity training data. However...