Mirzo Sharipov (Bukhara, Uzbekistan)

Precession of magnetic moments with change of their orientations

In the report the precession of the magnetization vector in nano-sized magnets is induced by a femtosecond laser pulse, the frequency of which lies in the transparency region of the magnet material. It will be shown that an alternating magnetic field applied to the XOY plane generates the magnetic equilibrium position vectors and elliptical precession occurs if a constant magnetic field acts along the Z axis. In this case the precession angle changes periodically in time and the precession frequency is determined by the amplitude of the total magnetic field.

Mario R Guarracino (Italy)

Adversarial attacks on graph-level embedding methods: a case study

As the number of graph-level embedding techniques increases at an unprecedented speed, questions arise about their behavior and performance when training data undergo perturbations. This is the case when an external entity maliciously alters training data to invalidate the embedding. The report explores the effects of such attacks on some graph datasets by applying different graph-level embedding techniques. The main attack strategy involves manipulating training data to produce an altered model. In this context, the goal is to go in-depth about methods, resources, experimental settings, and performance results to observe and study all the aspects that derive from the attack stage.

Predrag S. Stanimirovic

New ZNN dynamical systems based on nonlinear optimization methods

A new class of complex-valued recurrent neural networks, known as Zeroing Neural Network (ZNN), was originated in 2001 and has been extensively exploited in solving various time-varying problems.
The design of ZNN dynamical systems arises from the choice of an appropriate matrix-valued error-monitoring function, termed as the Zhang function (ZF). Some new ZFs resulting from nonlinear optimization methods are presented and initiated ZNNs are developed and investigated. The structure and the convergence of ZNN dynamical system which are intended to solving time-varying matrix equations are considered in details.

Mirat Karibaev (Kazakhstan)

Atomistic insight into mobility of hydronium ion for graphene oxide based proton exchange membrane

The Proton Exchange Membrane (PEM) fuel cell emerges as a promising option for electrochemical device applications due to its straightforward design and effective operation at lower temperatures. This study focuses on the utilization of graphene oxides (GO) to tackle the difficulties of chemical instability and proton movement within the under challenging conditions. To address this issue, the research examines how hydronium (H3O) ion move within a GO based PEM using Molecular Dynamics (MD) simulations. Additionally, the study explores the modeling and simulation of the interaction between GO and H3O ions, aiming to imitate the process of H3O ion transportation through the PEM. Noteworthy is the discovery that the diffusion coefficient of H3O ions and water (H2O) molecules is remarkably similar. This similarity is ascribed to the necessity of coordinated diffusion for both types (H2O and H3O ions), known as the vehicular diffusion mechanism, which is particularly evident at hydration level (λ) 3. Interestingly, the research illustrates that as λ rise, there is a consistent upward trend in H3O ion transportation. A comparison between the diffusion of H2O and H3O ions indicates that in the PEM model, their diffusion coefficients are similar due to the requirement for synchronized diffusion of both types in the vehicular diffusion mechanism. In addition, it is suggested that the primary mechanism at work in the GO-based PEM is the Grotthuss mechanism, mainly influenced by the higher diffusion coefficient of H2O molecules compared to H3O ions.