Abstract
The main objective of the present work was to review the current knowledge about the factors that influence the different phases of the natural regeneration of maritime pine (Pinus pinaster Aiton) and propose scientifically based management schedules. The review focused on the natural regeneration of maritime pine within its most representative areas (Portugal, Spain, and France). First, a brief characterisation of the main phases of the natural regeneration of maritime pine is described. Next, information on the factors affecting the natural regeneration of the species is provided, highlighting its positive and negative effects. Finally, management proposals are presented to promote the natural regeneration of maritime pine species. Numerous factors influencing the natural regeneration of maritime pine were identified. Fires and climatic factors can intervene in all three regeneration phases (seeding, germination, and seedling survival and development). The natural regeneration failure of maritime pine species can be aggravated in drier scenarios. Forest management plays an important role as it can promote the natural regeneration of the species.

Abstract
Background: E-commerce has emerged as a good response to the pandemic of COVID-19. However, the costs of providing a service, which includes a driver and a vehicle, in a regular vehicle that can transport goods that need positive cold (0 & DEG; to 5 & DEG;C) are very high. Objectives: This paper aims to investigate how a big Portuguese retailer company can reduce its dependence on refrigerated vehicles, simplifying operations and reducing the costs of transporting positive and negative cold food. Methods/Approach: This research was carried out in a food retailer Portuguese company, more precisely in a Dark Store dedicated to the online channel. The study was developed based on the AS-IS/TO-BE process analysis methodology, starting with the analysis of the current situation, giving rise to the so-called AS-IS model. Results: It was possible to reduce costs associated with transporting positive cold goods. As a result, there are 30% fewer costs associated with order transportation. With an additional 10% in space optimization with the gain of space within the galley of each vehicle. Conclusions: The costs of transporting positive and negative cold foods were decreased, and substituting vehicles with room temperature transport reduced the need for refrigerated vehicles.

Abstract
Traditionally, serious games have been used in the development of hard skills, particularly in technical areas such as health, engineering, defence or the environment. However, they can also be applied in the assessment and development of soft skills, which are increasingly key competencies for an individual in the twenty-first century. In this sense, this study proposes the adoption of the FLIGBY serious game in a higher education institution to evaluate and develop students' skills in this field. The findings indicate a large correspondence between the soft skills fundamental to the twenty-first century and the assessment dimensions recorded by the game. Furthermore, the findings reveal that FLIGBY can be used primarily to develop skills in dimensions such as leadership, conflict management, diplomacy and emotional intelligence. These findings are relevant for higher education institutions that intend to include and foster the development of soft skills competencies in their curricula.

Abstract
<p>Flying networks, composed of Unmanned Aerial Vehicles (UAVs) acting as mobile Base Stations and Access Points, have emerged to provide on-demand wireless connectivity, especially due to their positioning capability. Still, existing solutions are focused on improving aggregate network performance using a best-effort approach. This may compromise the use of multiple services with different performance requirements. Network slicing has emerged in 5G networks to address the problem, allowing to meet different Quality of Service (QoS) levels on top of a shared physical network infrastructure. However, Mobile Network Operators typically use fixed Base Stations to satisfy the requirements of different network slices, which may not be feasible due to limited resources and the dynamism of some scenarios.</p> <p>We propose an algorithm for enabling the joint placement and allocation of communications resources in Slicing-aware Flying Access and Backhaul networks – SurFABle. SurFABle allows the computation of the amount of communications resources needed, namely the number of UAVs acting as Flying Access Points and Flying Gateways, and their placement. The performance evaluation carried out by means of ns-3 simulations and an experimental testbed shows that SurFABle makes it possible to meet heterogeneous QoS levels of multiple network slices using the minimum number of UAVs.</p>

Abstract
The use of Generative Adversarial Networks is almost traditional in creating synthetic images for medical purposes. They are probably the best use of GANs until now, as their results can easily be checked by the eye of specialists. In fake news detection models, we have seen lately that neural models (and deep learning) can provide a considerable improvement from standard classifiers. Yet, the most problematic problem still is the lack of data, mostly fake news data to feed these models. In this paper, we address that by proposing the use of a GAN. Results show a better capacity to generalize when used for training an extended dataset based on synthetic samples created by this GAN.

Abstract
Natural language processing (NLP) refers to the field of study that focuses on the interactions between human language and computers. It has recently gained much attention for analyzing human language computationally and has spread its applications for various tasks such as machine translation, information extraction, summarization, question answering, and others. With the rapid growth of cloud computing services, merging NLP in the cloud is a significant benefit. It allows researchers to conduct NLP-related experiments on large amounts of data handled by big data techniques while harnessing the cloud's vast, on-demand computing power. However, it has not sufficiently spread its tools and applications as a service in the cloud and there is little literature available that discusses the scope of interdisciplinary work. NLP, cloud Computing, and big data are vast domains and contain their challenges and potentials. By overcoming those challenges and integrating these fields, great potential for NLP and its applications can be unleashed. This paper presents a survey of NLP in cloud computing with a key focus on the comparison of cloud-based NLP services, challenges of NLP and big data while emphasizing the necessity of viable cloud-based NLP services. In the first part of this paper, an overview of NLP is presented by discussing different levels of NLP and components of natural language generation (NLG), followed by the applications of NLP. In the second part, the concept of cloud computing is discussed that highlights the architectural layers and deployment models of cloud computing and cloud-hosted NLP services. In the third part, the field of big data in the cloud is discussed with an emphasis on NLP. Furthermore, information extraction via NLP techniques within big data is introduced.