The focus of the article is on utilizing neural networks, a form of artificial intelligence, to address the task of categorizing mechanical characteristics of diverse materials. Brinell hardness was chosen as the considered characteristics of materials for the study, the choice of this property was justified. The study simulates a finite element model of the impact of an indenter on a two-layer structure in an Ansys environment. The difference in the properties of the construction materials is determined by the application of a strengthening coating or the accumulation of multiple defects in the surface layer. Using the model, a set of data for training a neural network was obtained. As part of the experimental part, the structure of the neural network was developed, its hyperparameters were adjusted. A comparative analysis is presented that examines two different methods for neural network calculations based on the nature of the input impact.

Patterned stimulation of the locus coeruleus (LC, 100 Hz), in conjunction with test‐pulse stimulation of hippocampal afferents, results in input‐specific long‐term depression (LTD) of synaptic plasticity in the hippocampus. Effects are long‐lasting and have been described in Schaffer‐collateral–CA1 and perforant path‐dentate gyrus synapses in behaving rats. To what extent LC‐mediated hippocampal LTD (LC‐LTD) is frequency‐dependent is unclear. Here, we report that LC‐LTD can be triggered by LC stimulation with 2 and 5 Hz akin to tonic activity, 10 Hz equivalent to phasic activity, and 100 Hz akin to high‐phasic activity in the dentate gyrus (DG) of freely behaving rats. LC‐LTD at both 2 and 100 Hz can be significantly prevented by an NMDA receptor antagonist. The LC releases both noradrenaline (NA) and dopamine (DA) from its hippocampal terminals and may also trigger hippocampal DA release by activating the ventral tegmental area (VTA). Unclear is whether both neurotransmitters contribute equally to hippocampal LTD triggered by LC stimulation (LC‐LTD). Both DA D1/D5 receptors (D1/D5R) and beta‐adrenergic receptors (β‐AR) are critically required for hippocampal LTD that is induced by patterned stimulation of hippocampal afferents, or is facilitated by spatial learning. We, therefore, explored to what extent these receptor subtypes mediate frequency‐dependent hippocampal LC‐LTD. LC‐LTD elicited by 2, 5, and 10 Hz stimulation was unaffected by antagonism of β‐AR with propranolol, whereas LC‐LTD induced by these frequencies was prevented by D1/D5R‐antagonism using SCH23390. By contrast, LC‐LTD evoked at 100 Hz was prevented by β‐AR‐antagonism and only mildly affected by D1/D5R‐antagonism. Taken together, these findings support that LC‐LTD can be triggered by LC activity at a wide range of frequencies. Furthermore, the contribution of D1/D5R and β‐AR to hippocampal LTD that is triggered by LC activity is frequency‐dependent and suggests that D1/D5R may be involved in LC‐mediated hippocampal tonus.