Abstract
Objective: This study aims to present the developmental stages of a Mobile App Prototype designed to enhance patient participation in the rehabilitation process after hip replacement. Methods: To ensure effective interaction between the system and the end user, a User-Centered Design methodology was followed, encompassing three phases: Requirements gathering, Prototyping, and Evaluation. Usability tests were conducted to assess the usability of the developed system. Results: The RehabApp for mobile devices was created, and the testing results were positive. Users expressed satisfaction with the outcome, deeming it a valuable tool for their recovery. This outcome demonstrates the high receptiveness of these technologies in the healthcare sector, making it a project that can readily be expanded into other areas of rehabilitation. Conclusion: This study demonstrated the potential of the RehabApp in the rehabilitation process after hip replacement surgery. This accomplishment was realized by ensuring the active participation of patients, potential users, and healthcare professionals throughout the app's development. Innovation: The RehabApp is a mobile application to provide users with all the necessary knowledge, enabling them to undergo a smoother and safer rehabilitation. Feedback from both patients and healthcare professionals played a crucial role in refining the app's features and addressing usability concerns.

Abstract
Objective: The study aimed to demonstrate the development of a mobile app prototype, BarrierBeGone, a system that identifies potential barriers for individuals with mobility disabilities and promotes accessibility using gamification strategies. The main goal is to raise awareness about mobility and accessibility difficulties, especially for wheelchair users, and to promote more responsible behaviours. Method: The User-Centred Design methodology was employed, going through three phases: requirements gathering, design and development, and evaluation. Additionally, interviews with five individuals with mobility disabilities helped define the initial system requirements. The development of the barrier identification system was followed by usability tests with nine representative users. Results: The results of the usability tests of the "BarrierBeGone" barrier identification system were extremely positive. Stakeholders recognized the utility and simplicity of the platform, considering it a motivating factor for future use. Conclusion: The results support the effectiveness of the proposed educational tool in increasing awareness about accessibility and social inclusion in smart cities. This study makes a significant contribution to the field of urban planning and inclusive design. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

Abstract
The purpose of this scoping review was to identify and summarize how technology can promote patient participation in the rehabilitation process in hip replacement. We conducted a scoping review following the steps outlined by the Joanna Briggs Institute. The PRISMA Checklist (Preferred Reporting Items for Systematic reviews and Meta-Analyses) was utilized to systematically organize the gathered information. A thorough search of articles was performed on PubMed, Scopus, and CINAHL databases for all publications up to December 2022. Twenty articles were included in this study. Various technologies, such as mobile applications, Web sites, and platforms, offer interactive approaches to facilitate total hip replacement rehabilitation. The analyzed studies were based on the rehabilitation of total hip arthroplasty, which in most of them was developed in mobile applications and Web sites. The studies identified reflect trends in the application of digital health technologies to promote patient engagement in the rehabilitation process and provide risk monitoring and patient education.

Abstract
This study explores the prediction and mitigation of pallet collapse during transportation within the glass packaging industry, employing a machine learning approach to reduce cargo loss and enhance logistics efficiency. Using the CRoss-Industry Standard Process for Data Mining (CRISP-DM) framework, data were systematically collected from a leading glass manufacturer and analysed. A comparative analysis between the Decision Tree and Random Forest machine learning algorithms, evaluated using performance metrics such as F1-score, revealed that the latter is more effective at predicting pallet collapse. This study is pioneering in identifying new critical predictive variables, particularly geometry-related and temperature-related features, which significantly influence the stability of pallets. Based on these findings, several strategies to prevent pallet collapse are proposed, including optimizing pallet stacking patterns, enhancing packaging materials, implementing temperature control measures, and developing more robust handling protocols. These insights demonstrate the utility of machine learning in generating actionable recommendations to optimize supply chain operations and offer a foundation for further academic and practical advancements in cargo handling within the glass industry.

Abstract
Public transport systems worldwide experienced significant declines in usage during the COVID-19 pandemic due to lockdowns and work-from-home mandates. While numerous studies have examined these phenomena, there is still a need for empirical evidence that not only documents what occurred but also provides actionable insights for future transport planning. This study aims to enhance understanding of public transport passengers' mobility behaviors during different stages of the pandemic, using the Metropolitan Area of Porto, Portugal, as a case study. Automated Fare Collection data from 2020 were analyzed and compared with data from the pre-pandemic year of 2019. The analysis included temporal, spatial, spatio-temporal, and sociodemographic dimensions. Key patterns and trends identified include a rapid recovery of ridership post-restriction easing, homogenized daily travel patterns, varied impacts on different transport modes, and significant shifts in demographic travel behaviors. These findings highlight the resilience of public transport demand and suggest that adaptive scheduling, enhanced safety measures, targeted support for vulnerable groups, promotion of off-peak travel, investment in bus infrastructure, and encouragement of multi-modal transport are essential strategies. Implementing these strategies can help improve public transport planning and mitigate the adverse effects of future crises.

Abstract
Effective traffic management is crucial in addressing the growing complexities of urban mobility, and variable message signs (VMSs) play a vital role in delivering real-time information to road users. Despite their widespread application, there is limited comprehensive understanding of how VMS influence user behavior and optimize traffic flow. This systematic literature review aims to address this gap by examining the effectiveness of VMS in shaping user interactions and enhancing traffic management systems. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology, a thorough analysis of relevant studies was conducted to identify key factors influencing VMS impact, including message content and characteristics, complementary sources of information, user demographics, VMS location, and users' reliance on these signs. Additionally, the review explores the implications of displaying non-critical information on VMS and introduces virtual dynamic message signs (VDMSs) as an innovative approach for delivering public traveler information. The study identifies several research gaps, such as the integration of VMS with vehicle-to-everything (V2X) technologies, navigation systems, the need for validation in real-world scenarios, and understanding behavioral responses to non-critical information on VMS. This review highlights the importance of optimizing VMS for improved user engagement and traffic management, providing valuable insights and directions for future research in this evolving field.