The use of humanoid robots within the field of neuroscience has gained substantial interest in recent years, specifically as a means to implement and assess biological concepts. This conceptual paper addresses the vital challenge of uncertainty in ...

Spiking neural networks (SNNs) are a large class of neural model distinct from ‘classical’ continuous-valued networks such as multilayer perceptrons (MLPs). With event-driven dynamics and a continuous-time model in contrast to the discrete-time ...

• Tutorial on spiking neural networks (SNNs).
• Recommendations for SNN implementors and researchers.
• Current neural network challenges addressed by SNNs.
• Metrics for evaluating Spiking Neural Network performance.

The article presents a mathematical model that simulates the elastic and plastic behaviour of discrete systems representing isotropic materials. The systems consist of one lattice of nodes connected by edges and a second lattice with nodes placed ...

Numerical methods for delamination analysis, such as the cohesive zone method, require fracture energy as an essential input. Existing formulations rely on a phenomenological relationship that links fracture energy to the mode of fracture based ...

• Discontinuous FE2 is tested for simulating mode-II delamination growth.
• The zone with plastic deformation next to the growing crack is resolved.
• The plastic contribution to the fracture energy is obtained from the FE2 simulations.

Videogames can be persuasive assets in climate communication. However, there is insufficient knowledge on how to employ specific game design aspects to influence attitudes in the context of climate change. We developed a novel conceptual Climate-...

This study aims to achieve the densest possible state of soil for constructing dams and roads. This requires assessing the compaction characteristics, Optimum Moisture Content (OMC), and Maximum Dry Density (MDD) to determine the soil's ...

Stress reconstruction based on experimentally acquired full-field strain measurements is computationally expensive when using conventional implicit stress integration algorithms. The computational burden associated with repetitive stress ...

When modelling discontinuities (interfaces) using the finite element method, the standard approach is to use a conforming finite-element mesh in which the mesh matches the interfaces. However, this natural approach can prove cumbersome if the ...

• Simple approach for improved treatment of weak discontinuities for non-conforming meshes.
• Each finite element that is cut by an interface is treated as a simple laminate.
• Performance is tested through examples employing elastic and ...

This paper presents a numerical model of coupled hydro-mechanical behaviour of partially saturated soils. The model is based on Bishop's effective stress concept and the Cam-Clay model, with the compression stiffness influenced by the effect of ...

• Coupled hydro-mechanical model for partially saturated soils.
• Improvement of the model performance by the algorithmic stiffness matrix for the cutting plane stress algorithm.
• The effect of the wetting collapse can be captured by ...

Numerical modelling of geogrids is a challenging task, with extruded geogrids often presenting complex geometries and nonlinear tensile response even at low strain rates. In this study, three-dimensional (3D) models were developed in ...

• Three-dimensional numerical modelling of geogrids using hyperbolic constitutive models.

A two-dimensional ordinary state-based peridynamic formulation is proposed for the analysis of elastic–plastic plane structures. Selecting appropriate relation for isotropic extension state, the deviatoric strain energy formulation is derived for ...

Adaptive therapy (AT) is an evolution-based treatment strategy that exploits cell–cell competition. Acquired resistance can change the competitive nature of cancer cells in a tumor, impacting AT outcomes. We aimed to determine if adaptive therapy ...

• We extend Ripley’s K-function for the von Neumann neighborhood setting.
• Acquired resistance shapes the distribution of resistance over the tumor.
• A continuous maximum tolerated dose is preferable when acquired resistance is high.

Many solid mechanics problems on complex geometries are conventionally solved using discrete boundary methods. However, such an approach can be cumbersome for problems involving evolving domain boundaries due to the need to track boundaries and ...

In recent years, a lot of progress has been made in the field of material modeling with artificial neural networks (ANNs). However, the following drawbacks persist to this day: ANNs need a large amount of data for the training process. This is not ...

We aim to enhance the stability of finite element models of dynamic structural contact with multiphase granular soils which are described by advanced soil plasticity models that can simulate monotonic and cyclic behaviour of multiphase soils. ...

In the field of nonlinear mechanics, many challenging problems (e.g., plasticity, contact, masonry structures, nonlinear membranes) turn out to be expressible as conic programs. In general, such problems are non-smooth in nature (plasticity ...

Spike-time-dependent plasticity (STDP) represents an essential learning rule found in biological synapses and is recommended for replication in neuromorphic electronic systems. This rule is defined as a process of updating synaptic weight that ...

• Return mapping algorithm for arbitrary constraint stress states considering combined isotropic and kinematic hardening and general yield surfaces;

Structural theories often consider constraints on the stresses, creating a partition into active and fixed components. Sophisticated nonlinear material models are usually described in 3D-continuum form. A reformulation of the material ...

Dopamine plays a critical role in modulating the long-term synaptic plasticity of the hippocampal Schaffer collateral-CA1 pyramidal neuron synapses (SC-CA1), a widely accepted cellular model of learning and memory. Limited results from hippocampal ...

Physiologically based neural field theory (NFT) is extended to encompass cortical plasticity dynamics. An illustrative application is provided which treats the evolution of the connectivity of left- and right-eye visual stimuli to neuronal ...