Abstract
The United Nations has set Sustainable Development Goals (SDGs) to build a more sustainable future. The SDG analyzes progress to understand major implementation challlenges, define disparities across nations or regions, and propose priorities for action. It has 17 objectives and more than 200 indicators. Cluster analysis was used to categorize the 10 municipalities. It was carried out using IBM SPSS software, which calculated the Euclidean distance and put the investigated regions into clusters with the traits they shared the most in common.

Abstract
The trends of the 21st century are challenging the traditional production process due to the reduction in the life cycle of products and the demand for more complex products in greater quantities. Industry 4.0 (I4.0) was introduced in 2011 and it is recognized as the fourth industrial revolution, with the aim of improving manufacturing processes and increasing the competitiveness of industry. I4.0 uses technological concepts such as Cyber-Physical Systems, Internet of Things and Cloud Computing to create services, reduce costs and increase productivity. In addition, concepts such as Smart Factories are emerging, which use context awareness to assist people and optimize tasks based on data from the physical and virtual world. This article explores and applies the capabilities of context-aware applications in industry, with a focus on production lines. In specific, this paper proposes a context-aware application based on a microservices approach, intended for integration into a context-aware information system, with specific application in the area of manufacturing. The manuscript presents a detailed architecture for structuring the application, explaining components, functions and contributions. The discussion covers development technologies, integration and communication between the application and other services, as well as experimental findings, which demonstrate the applicability and advantages of the proposed solution.

Abstract
Higher education institutions (HEIs) make decisions in several domains, namely strategic and internal management, without using systematized data that support these decisions, which may jeopardize the success of their actions or even their efficiency. Thus, HEIs must define and monitor strategies and policies essential for decision making in their various areas and levels, in which business intelligence (BI) plays a leading role. This study presents a systematic literature review (SLR) aimed at identifying and analyzing primary studies that propose a roadmap for the implementation of a BI system in HEIs. The objectives of the SLR are to identify and characterize (i) the strategic objectives that underlie decision making, activities, processes, and information in HEIs; (ii) the BI systems used in HEIs; (iii) the methods and techniques applied in the design of a BI architecture in HEIs. The results showed that there is space for developing research in this area since it was possible to identify several studies on the use of BI in HEIs, although a roadmap for its implementation was not identified, making it necessary to define a roadmap for the implementation of BI systems that can serve as a reference for HEIs.

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This research revolves around the potential challenges, opportunities, and strategies associated with human-centered generative artificial intelligence (AI) in the music compositional practice, emphasizing the role of metaphorical design in shaping musicians' expectations toward the adoption of generative AI in their everyday creative activities. Through a human-computer interaction (HCI) lens, this paper aims to discuss the cultural implications of the human-AI metaphorical design space for the seamless integration of intelligent algorithmic experiences in a manner that aligns with cultural values and realistic expectations of music creators while promoting informed policies, sociotechnical imaginaries, and culturally sensitive generative AI design strategies with focus on user-friendly interfaces that resonate with diverse music creation groups.

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