Abstract
Container orchestration tools supporting infrastructure-as-code allow new forms of collaboration between developers and operatives. Still, their text-based nature permits naive mistakes and is more difficult to read as complexity increases. We can find few examples of low-code approaches for defining the orchestration of containers, and there seems to be a lack of empirical studies showing the benefits and limitations of such approaches. We hypothesize that a complete visual notation for Docker-based orchestrations could reduce the effort, the error rate, and the development time. Therefore, we developed a tool featuring such a visual notation for Docker Compose configurations, and we empirically evaluated it in a controlled experiment with novice developers. The results show a significant reduction in development time and error-proneness when defining Docker Compose files, supporting our hypothesis. The participants also thought the prototype easier to use and useful, and wanted to use it in the future.

Abstract
Este livro é o resultado do arranjo e compilação de textos didáticos produzidos ou adaptados pelos seus autores para apoio a unidades curriculares dos mestrados em Engenharia Mecânica - Gestão Industrial e Engenharia Eletrotécnica e Computadores – Sistemas de Planeamento Industrial, do Instituto Superior de Engenharia do Politécnico do Porto. Esses textos foram revistos e reorganizados, com vista, não só a manterem a função original de ajuda à formação de estudantes afetos a esta área do conhecimento, como também a constituírem uma referência de conhecimentos para quem deseje iniciar-se nestes temas; procuram ainda ser uma base de consulta e informação para engenheiros ou outros profissionais com funções na gestão da produção. O livro percorre os marcos mais significativos da trajetória histórica da gestão da produção, com particular foco no planeamento e controlo da produção, procurando interpretar e tornar compreensível a sua evolução, e relevando, sempre que oportuno, a influência da tecnologia nos modelos de gestão, e sua interligação. Começa por uma referência à tipologia dos sistemas de produção no capítulo I e aborda, no capítulo II, as principais funções do planeamento, programação e controlo da produção em contexto MRP, normalmente considerada uma visão mais clássica do tema. Outras duas aproximações com expressividade, a Teoria das Restrições e o JIT/Lean, são abordadas nos capítulos III e IV respetivamente. No capítulo V, o livro finaliza o seu conteúdo com uma breve referência a sistemas de informação empresariais, particularmente vocacionados para contextos de produção. Os autores expressam o seu agradecimento a todos os colegas, alunos e editor, que, com os seus contributos, permitiram chegar ao documento que agora disponibilizamos. Esperamos que lhe seja útil, prezado leitor, que suscite em si a mesma satisfação que o seu longo processo de compilação nos proporcionou, e que possa vir a ser, em próxima revisão, enriquecido com as valiosas críticas, sempre bem-vindas, que haja por bem dedicar-lhe.

Abstract
Lung cancer is one of the most common causes of cancer-related mortality, and since the majority of cases are diagnosed when the tumor is in an advanced stage, the 5-year survival rate is dismally low. Nevertheless, the chances of survival can increase if the tumor is identified early on, which can be achieved through screening with computed tomography (CT). The clinical evaluation of CT images is a very time-consuming task and computed-aided diagnosis systems can help reduce this burden. The segmentation of the lungs is usually the first step taken in image analysis automatic models of the thorax. However, this task is very challenging since the lungs present high variability in shape and size. Moreover, the co-occurrence of other respiratory comorbidities alongside lung cancer is frequent, and each pathology can present its own scope of CT imaging appearances. This work investigated the development of a deep learning model, whose architecture consists of the combination of two structures, a U-Net and a ResNet34. The proposed model was designed on a cross-cohort dataset and it achieved a mean dice similarity coefficient (DSC) higher than 0.93 for the 4 different cohorts tested. The segmentation masks were qualitatively evaluated by two experienced radiologists to identify the main limitations of the developed model, despite the good overall performance obtained. The performance per pathology was assessed, and the results confirmed a small degradation for consolidation and pneumocystis pneumonia cases, with a DSC of 0.9015 +/- 0.2140 and 0.8750 +/- 0.1290, respectively. This work represents a relevant assessment of the lung segmentation model, taking into consideration the pathological cases that can be found in the clinical routine, since a global assessment could not detail the fragilities of the model.

Abstract
The human brain can quickly become overwhelmed by the amounts of data computers can process. Consequently, data abstraction is necessary for a user to grasp information and identify valuable patterns. Data is usually abstracted in a pictorial or graphical format. Nowadays, users demand more personalization from the systems they use. This work proposes a user-centered framework that aims to ease creating visualizations for the developers of a platform while offering the end-user a highly customizable experience. The conceptualized solution was prototyped and tested to ensure the information about the data is transmitted to the user in a quick and effective manner. The results of a user study showed that users are pleased with the usability of the prototype and prove that they desire control over the configuration of their visualizations. This work not only confirmed the usefulness of previously explored personalization options for visual representations, but also explored promising new personalization options. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Antarctic deserts, such as the McMurdo Dry Valleys (MDV), represent extremely cold and dry environments. Consequently, MDV are suitable for studying the environment limits on the cycling of key elements that are necessary for life, like nitrogen. The spatial distribution and biogeochemical drivers of nitrogen-cycling pathways remain elusive in the Antarctic deserts because most studies focus on specific nitrogen-cycling genes and/or organisms. In this study, we analyzed metagenome and relevant environmental data of 32 MDV soils to generate a complete picture of the nitrogen-cycling potential in MDV microbial communities and advance our knowledge of the complexity and distribution of nitrogen biogeochemistry in these harsh environments. We found evidence of nitrogen-cycling genes potentially capable of fully oxidizing and reducing molecular nitrogen, despite the inhospitable conditions of MDV. Strong positive correlations were identified between genes involved in nitrogen cycling. Clear relationships between nitrogen-cycling pathways and environmental parameters also indicate abiotic and biotic variables, like pH, water availability, and biological complexity that collectively impose limits on the distribution of nitrogen-cycling genes. Accordingly, the spatial distribution of nitrogen-cycling genes was more concentrated near the lakes and glaciers. Association rules revealed non-linear correlations between complex combinations of environmental variables and nitrogen-cycling genes. Association rules for the presence of denitrification genes presented a distinct combination of environmental variables from the remaining nitrogen-cycling genes. This study contributes to an integrative picture of the nitrogen-cycling potential in MDV.

Abstract
The use of a mobile sink in wireless sensor networks has been a game changing to enable the development of smart cities applications. The mobility feature allows more effective data gathering and energy saving in the network, since the sink can be closer to source nodes, which could activate their radios only when the sink approximates. Doing so, more efficient settings can be achieved when configuring and deploying sensor nodes for a myriad of applications. However, this mobility-centric strategy can generate applications scenarios with large delays when sensor networks are monitoring the environment, which may result in considerable data losses in critical applications. To cope with that, this paper proposes an algorithm to dynamically plan the repositioning of a single mobile sink within distributed sensing applications. The algorithm considers dependability requirements associated with network connectivity, operability, and energy consumption, implicitly minimizing the energy-hole problem and connectivity issues. Simulation results are presented to demonstrate how the can be applied to move the sink through the network meeting dependability requirements. © 2022 IEEE.