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Featured Application This review highlights interoperability, automation, and decision-making as critical requirements for context-aware systems in the manufacturing domain that integrate the principles of Industry 4.0. It discusses relevant patterns and technologies, identifies context gaps, emphasises ontologies' importance, and proposes directions for future research.Abstract Technological evolution has driven the integration of computing devices in various domains, giving rise to heterogeneous and dynamic intelligent environments; together with market pressure, these pose challenges in formulating an architecture that takes advantage of contextual knowledge. In terms of architectural design, we are witnessing a transition from a centralised, monolithic view of systems to a decentralised view that incorporates the vertical and horizontal dimensions of the production environment. Therefore, this review aimed to (i) identify the requirements, (ii) find out about the representation models and context inference techniques, and (iii) identify architectural technologies, norms, models, and standards. The results observed in 25 articles made it possible to identify interoperability, automation, and decision-making as convergence points and observe the adoption of ontologies as a research area for context representation. In contrast, the discussion of context inference techniques remains open. Finally, this study presents recommendations for the design of a context-aware systems architecture that incorporates the principles of Industry 4.0 and facilitates the development of applications.

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Mobile devices have become integral to our everyday lives, yet their utility hinges on their battery life. In Android apps, resource leaks caused by inefficient resource management are a significant contributor to battery drain and poor user experience. Our work introduces Alpakka, a source-to-source compiler for Android's Smali syntax. To showcase Alpakka's capabilities, we developed an Alpakka library capable of detecting and automatically correcting resource leaks in Android APK files. We demonstrate Alpakka's effectiveness through empirical testing on 124 APK files from 31 real-world Android apps in the DroidLeaks [12] dataset. In our analysis, Alpakka identified 93 unique resource leaks, of which we estimate 15% are false positives. From these, we successfully applied automatic corrections to 45 of the detected resource leaks.

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The rapid rise of Renewable Energy Communities (REC) offers unique opportunities for decentralizing and decarbonizing energy systems but also brings challenges in designing fair mechanisms for distributing the benefits of collective self-consumption. This paper evaluates three approaches for benefit-sharing based on the Shapley value, direct marginal contributions, and system marginal cost. A case study compares these methodologies in terms of practicality, fairness, and impact on financial returns. Additionally, this paper proves that settling local transactions using system marginal costs ensures that all REC participants incur equal or lower costs compared to operating independently.

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The food industry faces growing challenges due to evolving consumer demands, requiring digital technologies to enhance sensory analysis. Innovations such as eye tracking, FaceReader, virtual reality (VR), augmented reality (AR), and artificial intelligence (AI) are transforming consumer behavior research by providing deeper insights into sensory experiences. For instance, FaceReader captures emotional responses to food by analyzing facial expressions, offering valuable data on consumer preferences for taste, texture, and aroma. Together, these technologies provide a comprehensive understanding of the sensory experience, aiding product development and branding. Electronic nose, tongue, and eye technologies also replicate human sensory capabilities, enabling objective and efficient assessment of aroma, taste, and color. The electronic nose (E-nose) detects volatile compounds for aroma evaluation, while the electronic tongue (E-tongue) evaluates taste through electrochemical sensors, ensuring accuracy and consistency in sensory analysis. The electronic eye (E-eye) analyzes food color, supporting quality control processes. These advancements offer rapid, non-invasive, reproducible assessments, benefiting research and industrial applications. By improving the precision and efficiency of sensory analysis, digital tools help enhance product quality and consumer satisfaction in the competitive food industry. This review explores the latest digital methods shaping food sensory research and innovation.

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