Abstract
Background Engaging in advance care planning can be emotionally challenging, but gamification and technology are suggested as a potential solution.Objective Present the development stages of a mobile app prototype to improve quality of life for patients in palliative care.Design The study started with a comprehensive literature review to establish a foundation. Subsequently, interviews were conducted to validate the proposed features of the mobile application. Following the development phase, usability tests were conducted to evaluate the overall usability of the mobile application. Furthermore, an oral questionnaire was administered to understand user satisfaction about the implemented features.Results A three-phase testing approach was employed based on the chosen user-centred design methodology to obtain the results. Three iterations were conducted, with improvements being made based on feedback and tested in subsequent phases. Despite the added complexity arising from the health status of patients in palliative care, the usability tests and implemented features received positive feedback from both patients and healthcare providers.Conclusion The research findings have demonstrated the potential of digitisation in enhancing the quality of life for patients in palliative care. This was achieved through the implementation of patient-centred design, personalised care, the inclusion of social chatrooms and facilitating end-of-life discussions.

Abstract
Road network studies attracted unprecedented and overwhelming interest in recent years due to the clear relationship between human existence and city evolution. Current studies cover many aspects of a road network, for example, road feature extraction from video/image data, road map generalisation, traffic simulation, optimisation of optimal route finding problems, and traffic state prediction. However, analysing road networks as a complex graph is a field to explore. This study presents comparative studies on the Porto, in Portugal, road network sections, mainly of Matosinhos, Paranhos, and Maia municipalities, regarding degree distributions, clustering coefficients, centrality measures, connected components, k-nearest neighbours, and shortest paths. Further insights into the networks took into account the community structures, page rank, and small-world analysis. The results show that the information exchange efficiency of Matosinhos is 0.8, which is 10 and 12.8% more significant than that of the Maia and Paranhos networks, respectively. Other findings stated are: (1) the studied road networks are very accessible and densely linked; (2) they are small-world in nature, with an average length of the shortest pathways between any two roads of 29.17 units, which as found in the scenario of the Maia road network; and (3) the most critical intersections of the studied network are 'Avenida da Boavista, 4100-119 Porto (latitude: 41.157944, longitude: - 8.629105)', and 'Autoestrada do Norte, Porto (latitude: 41.1687869, longitude: - 8.6400656)', based on the analysis of centrality measures.

Abstract
Car rental and car sharing are two established mobility concepts which traditionally have been offered by specialized providers. Presumably to increase utilization and profitability, most recently, car rental providers began to offer car sharing in addition, and vice versa. To assess and quantify benefits and drawbacks of combining both into a single mobility concept with one common fleet, we consider such combined systems on an aggregate level, replicating demand patterns and rentals throughout a typical week. Our systematic approach reflects that, depending on a provider's status quo, different business practices exist, for example with regard to the applied revenue management approaches. Methodologically, our analyses base on mathematical optimization. We propose several models that consider the different business practices and degrees to which the respective new mobility concept is offered. To support mobility providers in their strategic decision-making, we derive managerial insights based on numerical studies that use real-life data.

Abstract
In the energy production sector, increasing the quantity and efficiency of renewable energies, such as hydropower plants, is crucial to mitigate climate change. This paper proposes a new and flexible model for optimising operational decisions in watershed systems with interconnected dams. We propose a systematic representation of watersheds by a network of different connection points, which is the basis for an efficient Mixed-Integer Linear Programming model. The model is designed to be adaptable to different connections between dams in both main and tributary rivers. It supports decisions on power generation, pumping and water discharge, maximising profit, and considering realistic constraints on water use and factors such as future energy prices and weather conditions. A relax-and-fix heuristic is proposed to solve the model, along with two heuristic variants to accommodate different watershed structures and sizes. Methodological tests with simulated instances validate their performance, with both variants achieving results within 1% of the optimal solution faster than the model for the tested instances. To evaluate the performance of the approaches in a real-world scenario, we analyse the case study of the C & aacute;vado watershed (Portugal), providing relevant insights for managing dam operations. The model generally follows the actual decisions made in typical situations and flood scenarios. However, in the case of droughts, it tends to be more conservative, saving water unless necessary or profitable. The model can be used in a decision-support system to provide decision-makers with an integrated view of the entire watershed and optimised solutions to the operational problem at hand.

Abstract
Warehouses and distribution centres play a key role in any Supply Chain, particularly in the retail sector, where a network of stores needs to be replenished in a highly dynamic and increasingly uncertain context. In this regard, companies need to improve their intralogistics systems daily to ensure long-term competitiveness and sustainable growth. This is especially true in picking-by-line systems where many time-consuming and manual tasks are usually involved. This study introduces a new decision support tool based on simulation methods to aid the decision-making process in a picking-by-Line system, aimed to improve the overall picking operations efficiency, through human-centric perspective. A Discrete-Event-Simulation model is proposed to assess a set of parameters under several scenarios, driving a more informed decision-making process towards cost-effective strategies. The proposed approach was validated through an empirical case study showing its effectiveness in assisting operational planning decisions related to capacity and resource allocation. The system demonstrates promising versatility for application across varied warehouse environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract
In this work a hybrid simulation-optimization approach is presented to support decision-making towards improved resiliency and sustainability in pharmaceutical supply chain (PSC) operations. In a first step, a simulation model is used to assess the PSC performance under a set of disruptive scenarios to select the best inventory-based strategy for enhanced resiliency. Disruptions addressed in this work are mainly related to unpredicted medium-term production stoppages due to unexpected high-impact events such as accidents in production and transportation, or natural disasters. In a second step, a multi-objective mixed integer linear programming (MO-MILP) model is developed to optimize the selected inventory-based strategy regarding the economic, social, and environmental dimensions. In particular, the social and environmental aspects are introduced by anticipating the expected waste generation of close to expire medicines, redirecting them into a donation scheme. The proposed approach is applied to a representative PSC, with preliminary results showing the relevance of this tool for decision-makers to assess the trade-offs associated to the economic and social dimensions, as well as their impacts on waste generation.