Abstract
Recently, multi-carrier energy systems (MCESs) have been rapidly developed as flexible multi-generation systems aiming to satisfy load demands by purchasing, converting, and storing different energy carriers. This study specifically focuses on the optimal and robust large-scale coordination of interconnected energy hubs (IEHs) in an iterative consensus-based procedure considering distribution network losses. Furthermore, a new robustbased hybrid IGDT/consensus algorithm is introduced to achieve risk-averse optimal energy management in IEHs under uncertainty. The fast convergence, needless to collect the total information from all hubs, minimal computational burden, and more robust communication system are the most important features of the proposed distributed consensus algorithm in this study. The effectiveness of the proposed consensus algorithm is verified by simulation results considering various energy trading structures in IEHs at different scales. The obtained results highlight the scalability capability of the proposed method. Regarding an IEHS of 30 energy hubs, the computation burden is lightened by 0.53 (s) and 0.1917 (s), respectively with and without uncertainty. Considering distribution network losses, the total purchasing costs can be increased by 8%. The simulation results also reveal an increase of 11% in the total power trading under the uncertainty.

Abstract
In the health sector, the implementation of qualitative data research is very important to improve overall services. However, the use of these methods remains relatively unexplored when compared to quantitative analyses. This article describes the qualitative data analysis process that is based on the description, analysis and interpretation of data. It also describes a practical case study and the use of NVivo software to assist in the development of a theory-based qualitative analysis process. This article intends to be a step forward in the use of qualitatively based methodologies in future research in the health sector.

Abstract
The European Project Semester (EPS) at Instituto Superior de Engenharia do Porto (ISEP) is a capstone engineering design programme in which students, organised in multidisciplinary and multicultural teams, develop a solution for a proposed problem, taking into account sustainability, ethical and market concerns. This paper describes a research project aimed at raising awareness and changing behaviour in relation to waste disposal, carried out by a team of EPS@ISEP students during spring 2023. BinIt, as the project is named, targets young adults who want to live in a cleaner city. Unlike other campaigns, it simplifies and stimulates proper waste disposal and recycling, tackling the root of the problem and creating a new social norm. BinIt includes a campaign, a web app and the Garbage Gladiator bin. The app consists of a city map where users can pin and check bin locations, and an educational platform with information on waste disposal and recycling issues. Gamification is incorporated through a ranking system. The Garbage Gladiator is a physical container for urban public spaces specially designed to encourage people to dispose of their waste correctly. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Abstract
This review is an analysis of the literature on public transport and mobile ticketing systems and their gamification. The review is divided into three main topics: (i) Behavioral Change in relation to Public Transport, (ii) Gamification, and (iii) Gamification in Public Transport and Mobile Ticketing. This study shows the diversity of the theme of gamification applied to the transport sector and demonstrates its potential to attract and retain more customers for more sustainable means of transport.

Abstract

Abstract
Traditionally, scheduling literature has focused mainly on solving problems related to processing jobs with non- assembly operations. Despite the growing interest in the assembly literature in recent years, knowledge of the problem is still in its early stages in many aspects. In this regard, we are not aware of any previous contributions that address the assembly scheduling problem with just-in-time objectives. To fill this gap, this paper studies the 2-stage assembly scheduling problem minimising the sum of total earliness and total tardiness. We first analyse the relationship between the decision problem and the generation of the due dates of the jobs, and identify the equivalences with different related decision problems depending on the instances. The properties and conclusions obtained in the analysis are applied to design two constructive heuristics and a composite heuristic. To evaluate our proposals, different heuristics from the state-of-the-art of related scheduling problems are adapted, and a computational evaluation is carried out. The excellent behaviour of the proposed algorithms is demonstrated by an extensive computational evaluation.