Abstract
Canvas have for long been embraced as a popular design tool. Initially aimed towards, business model development, the model of a one page, visual and collaborative tool has spread to the design of many different artifacts. Digital platforms, with its conjugation of business, technical, and social facets have benefited from the canvas model for its design practices, from both scholars and practitioners. Nonetheless, the recent push for more industry-specific and holistic digital platform research agenda is bound to have an impact in the tools used for platform design. In this paper, we apply a literature review method to examine existing canvas, inspired by the Business Model Canvas, as tools for the design of digital platforms. Using conceptual platform design research as a frame of reference, we review eight canvas specific for digital platform design, highlighting four critical limitations in their application regarding (1) adopted broad platform conceptualizations; (2) a restricted focus on business elements; (3) a lack of focus on platform evolution; and (4) a lack of guidance in the translation of canvas to explicit platform design propositions and requirements. By addressing these limitations, we set a path for the evolution of canvas as collaborative tools that can better support the more comprehensive and nuanced approaches required for the design of digital platforms acting in an evermore non-linear, volatile, uncertain, complex, and ambiguous environments.

Abstract
While a wide range of resources is available on orchestration techniques and best practices for containerized software systems, many are not documented clearly or in detail. This complicates the process of selecting the most suitable methods for various usage scenarios. To address this gap, we documented a set of orchestration patterns. This paper reports the results of a focus group conducted during the EuroPLoP 2024 conference, where we aimed to obtain feedback on that group of patterns and on a wider pattern map we outlined. We also aimed to identify container orchestration patterns that have not yet been documented. We found that participants knew most of the patterns we included on the pattern map. Additionally, one of the practices mentioned by the participants (Node Balancing) was previously documented as a pattern by us with the name of Service Balancing. Finally, we found important insights into container orchestration patterns, expanding our pattern map to include eight new proto-patterns.

Abstract
To facilitate easy prediction and estimation of Adaptive Optics performance, we have created a fast algorithm named TipTop. This algorithm generates the expected AO Point Spread Function (PSF) for any existing AO observing mode (SCAO, LTAO, MCAO, GLAO) and any set of atmospheric conditions. Developed in Python, TipTop is based on an analytical approach, with simulations performed in the Fourier domain, enabling very fast computation times (less than a second per PSF) and efficient exploration of the extensive parameter space. TipTop can be used for several applications, from assisting in the observation preparation with the Exposure Time Calculator (ETC), to providing PSF models for post-processing. TipTop can also be used to help users in selecting the best NGSs asterism and optimizing their observation. Over the past years, the code has been intensively tested against different other simulation tools, showing very good agreements. TipTop is also currently deployed for VLT instruments, as proof of concepts in preparation of the ELT. The code is available here: https://tiptop.readthedocs.io/en/main/, and we encourage all future observers of the ELT to test it and provide feedback !

Abstract
Urban retrofitting has emerged as a key strategy in the transition towards sustainable cities, with Positive Energy Districts (PEDs) serving as a model for achieving energy-positive urban environments. This paper explores the potential for urban retrofitting to achieve a positive energy balance through a case study of four existing districts in European Municipalities: Settimo Torinese (Italy), Großschönau (Austria), Amsterdam (Netherlands), and Resita (Romania). The analysis leverages energy balance simulations, considering various retrofitting scenarios, including building insulation, photovoltaic (PV) installations, and the adoption of flexible grid usage. The findings indicate that while achieving a PED is challenging, it is attainable through a combination of aggressive retrofitting measures, renewable energy integration, and smart energy management. The study highlights the importance of context-specific strategies, as climatic and urban characteristics significantly influence the outcomes. It aims to add to the ongoing discourse on sustainable urban development by providing empirical insights into the pathways and challenges of achieving PEDs through urban retrofitting. © 2024 IEEE.

Abstract
Some of the fundamental activities of the software development process relate to the discipline of Requirements Engineering. Their objectives are to discover, analyze, document, verify and manage the requirements that will be part of the software. The requirements are the system's characteristics, which are identified based on information provided by users or experts in the field. The effective management of this information is essential to ensure that the system meets the needs of those who will use it. Considering that the requirements are information, we carried out research to propose a framework contemplating a set of tools used by the information management to assist the requirements management process's activities. This article aims to present the FIRMa - Framework based on Information Management to Requirements Management, and the results of an evaluation carried out by a group of eighteen specialists in Requirements Engineering, who gave their opinion about the tools contemplated by the framework, as well as defined steps and the guidelines elaborated for its use. The evaluation results showed that FIRMa could contribute to the requirements management process's activities and increase the project's chances of success.

Abstract
This article presents the development of a vision system designed to enhance the autonomous navigation capabilities of robots in complex forest environments. Leveraging RGBD and thermic cameras, specifically the Intel RealSense 435i and FLIR ADK, the system integrates diverse visual sensors with advanced image processing algorithms. This integration enables robots to make real-time decisions, recognize obstacles, and dynamically adjust their trajectories during operation. The article focuses on the architectural aspects of the system, emphasizing the role of sensors and the formulation of algorithms crucial for ensuring safety during robot navigation in challenging forest terrains. Additionally, the article discusses the training of two datasets specifically tailored to forest environments, aiming to evaluate their impact on autonomous navigation. Tests conducted in real forest conditions affirm the effectiveness of the developed vision system. The results underscore the system's pivotal contribution to the autonomous navigation of robots in forest environments.