Abstract
Increasingly social networks are used both in the personal and professional levels, being companies and employees also exposed to the risks posed by them. In this sense, it is relevant to analyze employees’ perception of the risks and vulnerabilities posed by the use of social networks in corporate environments. For this purpose, a questionnaire was developed and distributed to 372 employees of small and medium-sized companies that allowed the characterization and analysis of those risks. The results indicate that the security risks are perceived moderately by employees, emphasizing the risk of defamation and cyberbullying as being the most pertinent. On the other hand, the findings indicate that older employees, the existence of lower academic qualifications, and those working in medium-sized companies are more aware of these risks. © 2022 by IGI Global. All rights reserved.

Abstract
Motion control is an important task in several areas, such as robotics where the angular position and speed should be acquired, usually with encoders. For slow angular speeds, an error is introduced spoiling the measurement. In this paper there will be proposed two new methodologies, that when combined allow to increase the precision whereas reducing the error, even on transient velocities. The two methodologies Variable Acquisition Window and a Quadrature Phase Compensation are addressed and combined simultaneously. A real implementation of the proposed algorithms is performed on a real hardware, with a DC motor and a low resolution encoder based on hall effect. The results validate the proposed approach since the errors are reduced compared with the standard Quadrature Encoder Reading.

Abstract
In the past few years, the first commercially available quantum computers have emerged, in an early stage of development, the so-called Noisy Intermediate-Scale Quantum (NISQ) era. Although these devices are still very prone to errors of different natures, they also have shown to deal successfully with small computational problems. Nowadays, one of the challenges in quantum computation is exactly to be able to show that quantum computers are useful, whereby mitigating the effects of the faulty hardware is pivotal. Recently, a wide range of quantum error mitigation techniques have been proposed and successfully implemented, alternative to quantum error correction codes. Herein, we discuss several types of noise in a quantum computer and techniques available to mitigate them, as well as their limitations and conditions of applicability. We also suggest an hierarchy for them, towards the conception of a layered software framework of error mitigation techniques, and implement some of them in a quantum simulation of the Heisenberg model on an IBM quantum computer, improving the fidelity of the simulation by 2.8x.

Abstract
(1) Background: The repercussions of work environments were widely studied before the pandemic. However, there are still many difficulties to be discovered considering the impact generated by it. Thus, this study aimed to analyse the impact of COVID-19 on nursing practice environments and nurses' job satisfaction. (2) Methods: A correlational study was conducted in a hospital in northern Portugal, with the participation of 416 registered nurses. Data were collected in June 2021 through questionnaires. The study was approved by the Institutional Ethics Committee. (3) Results: COVID-19 had a favourable impact on the structure component of the practice environments; the process component decreased compared to the pre-pandemic period; the outcome component remained moderately favourable to the quality of care. Nurses were not very satisfied or not at all satisfied with their valuation and remuneration; moderately satisfied with the leadership and staffing; and satisfied with the organisation and resources, co-workers and valuation by patients and families. In more favourable environments, nurses' job satisfactions were higher. (4) Conclusions: Identifying the dimensions with the best and worst scores allowed the institution's managers to concentrate efforts on where improvements were needed, thus preparing professional contexts for the recovery of care activities.

Abstract
Spotify is a world class platform for music streaming, and it offers various kinds of services. As with many digital platforms, Spotify uses artificial intelligence to personalize the user experience, also known as a recommender system. This study investigates what role Spotify’s recommender system plays in the use of Spotify and if there are any differences in satisfaction between different ages and gender. Therefore, we conducted a survey about how customers are using Spotify, which was shared in different forums. In total we received 159 answers with respondents from 21 different countries. One of the main findings was that the three services “Make your own playlist”, “Playlist made by Spotify” and “Recommended songs” are the most popular. Also, a correlation was made to investigate the relationship between the satisfaction of “Recommended songs” and if customers add them to their own playlists. The Spearman’s Rank Correlation Coefficient was 0.43 (significant at the 0.01 level), which is a moderate value. This means that almost half of the time the Spotify users place the recommended songs in their playlist. Further, two conclusions were arrived at. Firstly, the recommender system plays a major part in how customers use Spotify. Secondly, we cannot see that age and gender would significantly affect the satisfaction of the recommended songs that Spotify suggest. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
[No abstract available]