The assumption was verified that for patients suffering from cancer levels of anxiety and self-esteem differ compared to other patients before surgery. 120 patients of urology were assigned to subgroups according to diagnosis (cancer vs. non-cancer) and the duration of hospitalization (5 days vs. 1 day). Patients suffering from cancer declared higher anxiety than other patients. Longer hospitalization was connected to higher anxiety. A threat-congruent difference in explicit self-esteem was revealed only between two groups: 1. cancer and long hospitalization and 2. non-cancer and short hospitalization. For implicit self-esteem the phenomenon of implicit compensation of self-esteem was predicted and confirmed: among cancer-sufferers the Name Letter Effect was greater than among other patients. Also, in the cancerpatients group, the result of Rudman et al. (2007) was replicated: increasing anxiety was connected with increasing implicit self-esteem.

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In order to develop reliable safety standards for 5G sensor networks (SN) and the Internet of Things, appropriate verification tools are needed, including those offering the ability to perform automated symbolic analysis process. The Tamarin prover is one of such software-based solutions. It allows to formally prove security protocols. This paper shows the modus operandi of the tool in question. Its application has been illustrated using an example of an exchange of messages between two agents, with asynchronous encryption. The scheme may be implemented, for instance, in the TLS/DTLS protocol to create a secure cryptographic key exchange mechanism. The aim of the publication is to demonstrate that automated symbolic analysis may be relied upon to model 5G sensor networks security protocols. Also, a use case in which the process of modeling the DTLS 1.2 handshake protocol enriched with the TCP SYN Cookies mechanism, used to preventing DoS attacks, is presented