Abstract
The ionosphere is a fundamental component of the Earth's atmosphere, impacting human activities such as communication transmissions, navigation systems, satellite functions, power network systems, and natural gas pipelines, even endangering human life or health. As technology moves forward, understanding the impact of the ionosphere on our daily lives becomes increasingly important. CubeSats are a promising way to increase understanding of this important atmospheric layer. This paper reviews the state of the art of CubeSat missions designed for ionospheric studies. Their main instrumentation payload and orbits are also analyzed from the point of view of their importance for the missions. It also focuses on the importance of data and metadata, and makes an approach to the aspects that need to be improved.

Abstract
This article reports on the development of a Web platform for the study of Adverse Drug Events (ADEs). The platform is able to import ADE episodes from official Web sites, like OpenFDA, analyse the chemistry of the drugs involved, together with patient data, and produce a potential explanation based on the drugs interactions. Each study uses chemical knowledge to enrich the information on the molecules involved in the episodes. Data Mining is then used to construct models that can help in the explanation of the ADE occurrence and to predict future events. This paper reports on the Web portal developed and the Data Mining experiments conducted to evaluate the quality, and potential explanations of the forecasted adverse reactions, using real reports of drug administration and the subsequent adverse events. The results showed that it was possible to predict the outcomes of ADEs based on the structure of the molecules of the drugs involved and the data collected from real reports of drug administration up to an accuracy of 79%, while also predicting, with high accuracy, the severity of events where the outcome is the death of the patient (with a precision of 98.9%). The platform provides a less expensive and more accurate way of predicting adverse drug reactions compared to traditional methods. This study highlights the importance of understanding drug interactions at a molecular level and the usefulness of utilising Data Mining techniques in predicting ADEs.

Abstract
Variational quantum circuits are being used as versatile quantum machine learning models. Some empirical results exhibit an advantage in supervised and generative learning tasks. However, when applied to reinforcement learning, less is known. In this work, we considered a variational quantum circuit composed of a low-depth hardware-efficient ansatz as the parameterized policy of a reinforcement learning agent. We show that an epsilon-approximation of the policy gradient can be obtained using a logarithmic number of samples concerning the total number of parameters. We empirically verify that such quantum models behave similarly to typical classical neural networks used in standard benchmarking environments and quantum control, using only a fraction of the parameters. Moreover, we study the barren plateau phenomenon in quantum policy gradients using the Fisher information matrix spectrum.

Abstract

Abstract
This article proposes the use of social representation theory to validate the structural model of structural equation modeling, thereby enhancing the understanding of the research object. To achieve this, it was employed action research to construct, implement, and confirm the practical feasibility of the metho-dological procedures described herein. This was accomplished through their practical application in a case analysis. It was possible to validate the structural model used in structural equation modeling by applying the proposed methodological procedures to a case involving the governance system construct. This validation opens the possibility for future research to use these procedures in conjunction to validate theoretical models and the causal relationships between their constructs. Therefore, the primary theoretical contribution of this paper is the proposition of a research methodology that combines social representation theory with structural equation modeling to validate the structural model. This approach reduces the risk of using the statistical method to confirm or refute a theoretical model whose causal relationships may not represent a reality supported by practice.

Abstract
The 5th International Conference on Production Economics and Project Evaluation ICOPEV 2022 held on 29th – 30th of September 2022 in Castelo Branco, Portugal, continues the series of annual events shaping the future of Project Evaluation and Selection. Projects compete for scarce resources and choosing the best allocation of these resources is a complex and challenging task that decision makers face every day. The conference has covered a broad range of important and timely issues related to business intelligence, innovation & technology, project management, knowledge & technology trans-fer, energy issues, decision support systems, cost management, sustainability, innovation, and entrepreneurship. ICOPEV 2022 also featured keynote sessions and round tables. Our deepest appreciation goes to all that put in a lot of hard work of all who are involved in making this conference a success, including the organizing staff at Polytechnic Institute of Castelo Branco and the sponsors. In this conference participated authors from ten countries, namely Brazil, China, Chile, Colombia, Mexico, Poland, Portugal, Spain, and United Kingdom. The technical program is the result of the dedication and efforts of 56 members of the Scientific Committee as well as 37 reviewers, who have greatly contributed to the success of the ICOPEV 2022 paper review process, with an acceptance rate of 80%. The 2022 edition is the 5th conference since the inaugural event held in Guimarães, Portugal in 2011. The ICOPEV conferences follow a tradition of a high scientific quality and an informal atmosphere that fosters innovative and open discussions between academia and industry. Based on the many high-quality contributions in the technical program and interesting discussions during the conference, we are sure that this year edition in Castelo Branco was a worthy successor of the previous ICOPEV events.