Abstract
In online three-dimensional packing problems where items are received one by one and require immediate packing decisions without prior knowledge of upcoming items, considering the static stability constraint is crucial for safely packing each arriving item in real time. Unstable loading patterns can result in risks of potential damage to items, containers, and operators during loading/unloading operations. Nevertheless, static stability constraints have often been neglected or oversimplified in existing online heuristic methods in the literature, undermining the practical implementation of these methods in real-world scenarios. In this study, we analyze how different static stability constraints affect solutions' efficiency and cargo stability, aiming to provide valuable insights and develop heuristic algorithms for real-world online problems, thus increasing the applicability of this research field. To this end, we embedded four distinct static stability constraints in online heuristics, including full-base support, partial-base support, center-of-gravity polygon support, and novel partial-base polygon support. Evaluating the impact of these constraints on the efficiency of a wide range of heuristic methods on real instances showed that regarding the number of used bins, heuristics with polygon- based stabilities have superior performance against those under full-base and partial-base support stabilities. The static mechanical equilibriumapproach offers a necessary and sufficient condition for the cargo static stability, and we employed it as a benchmark in our study to assess the quality of the four studied stability constraints. Knowing the number of stable items under each of these constraints provides valuable managerial insight for decision-making in real-world online packing scenarios.

Abstract
Complex systems, characterised by high interconnectedness and unpredictability, demand structured approaches to support decision-making, system integration, and operational efficiency. This study aims to develop a comprehensive understanding of these systems to facilitate the implementation of Digital Twins (DTs) in Complex Operations Environments (COEs). A Systematic Literature Review (SLR), following PRISMA methodology, is conducted and complemented by a grounded theory approach to identify, organise, and synthesise system characteristics. The result is a hierarchical conceptualisation comprising eight core categories that capture the essential dimensions of complexity, including: Process and System Interoperability, Human Relationships, Behaviour/Nature, Products and Services, Multi-processes, Performance, System Structure, and Management and Skill Requirements. This framework offers a structured foundation for designing and implementing DT-based decision support in COEs.

Abstract
This data-based study aims to understand the progress made by EU countries in recent years on key areas of the circular economy by analyzing some indicators. The data have been collected from the Eurostat database over the period 2013-2021. After a preliminary analysis of the data set, a double principal component analysis has been used. This approach provides insights into the evolution of the countries and correlations between the indicators, highlighting which EU countries are the most (or least) similar to each other. The findings of this study indicate that EU countries collectively have advanced towards a circular economy in various indicators, with certain countries showing more notable progress than others. Some countries are even considered outliers, for positive or negative reasons, in some of the indicators. Overall, the Western EU countries perform better than the Eastern countries on most of the indicators analyzed, especially for resource productivity, municipal waste management, circularity rate, private investment in the circular economy sectors, and gross added value in circular economy sectors. The exceptions are for the generation of municipal waste, percentage of persons employed in circular economy sectors, and greenhouse gas emissions, the ones where the Eastern countries in general perform better. © 2025 Elsevier B.V., All rights reserved.

Abstract
This study reflects the assumption that all links in a supply chain (SC) must share responsibility for socio-environmental issues. One of the main barriers to ensuring the sustainability of an SC is the difficulty in accessing partners' information, especially beyond the first tier. Due to the great geographical dispersion, large number of small companies, and, mainly, the growth of the fast fashion industry, the textile sector is recognised as a priority when it comes to social sustainability issues. Moreover, consumers are increasingly demanding information about the social footprint of products. Thus, this paper aims to contribute to a better understanding of how SC visibility can contribute to increasing the social sustainability of textile SCs. Using a longitudinal perspective and adopting mixed methods integrated into a design science strategy, we evaluate SC visibility in the context of two Portuguese textile supply chains, before and after the development of a technology-based solution.

Abstract

Abstract
Management and reuse of wood waste can be a challenging process due to the frequent presence of hazardous contaminants. Conventional detection methods are often limited by the need for excessive sample preparation and lengthy and expensive analysis. Laser-induced Breakdown Spectroscopy (LIBS) is a rapid and micro- destructive technique that can be a promising alternative, providing in-situ and real-time analysis, with minimal to no sample preparation required. In this study, LIBS imaging was used to analyze wood waste samples to determine the presence of contaminants such as As, Ba, Cd, Cr, Cu, Hg, Pb, Sb, and Ti. For this analysis, a methodology based on detecting three lines per element was developed, offering a screening method that can be easily adapted to perform qualitative analysis in industrial contexts with high throughput operations. For the LIBS experimental lines selection, control and reference samples, and a pilot set of 10 wood wastes were analysed. Results were validated by two different X-ray Fluorescence (XRF) systems, an imaging XRF and a handheld XRF, that provided spatial elemental information and spectral information, respectively. The results obtained highlighted LIBS ability to detect highly contaminated samples and the importance of using a 3-line criteria to mitigate spectral interferences and discard outliers. To increase the dataset, a LIBS large-scale study was performed using 100 samples. These results were only corroborated by the XRF-handheld system, as it provides a faster alternative. In particular cases, ICP-MS analysis was also performed. The success rates achieved, mostly above 88 %, confirm the capability of LIBS to perform this analysis, contributing to more sustainable waste management practices and facilitating the quick identifi- cation and remediation of contaminated materials.