Abstract
Purpose: This paper intends to evaluate the impact of Toyota Way (TW) focused activities on operational performance and its connection to sustainability and longterm success. Methodology/Approach: Three theoretical-practical activities were implemented in a real pickup assembly plant. Performance was assessed through the recording of standard documentation before and after implementation, direct observation at the gemba, and anonymous qualitative surveys of those involved. Findings: Results show how TW enhances workers' skills alongside TPS through experiential learning, fostering continuous improvement with minimal or no financial investment and creating value iteratively and exponentially. However, it had a limited impact on environmental factors. TW emerges as a critical link between short-term operational performance and long-term sustainable growth. Research Limitations/Implications: The sample is restricted to a single assembly plant in Portugal. The surveys involved between 5 and 13 respondents per activity. Originality/Value of paper: In contrast to TPS and lean manufacturing, current literature on TW is limited, often outdated, and lacks clarity regarding its Japanese and American interpretations. Furthermore, few studies emphasise the human element as a driver of company growth-a factor often overlooked by companies. Category: Case study

Abstract
The Machine Learning Data Market (MLDM), which relies on multi-agent systems, necessitates robust negotiation strategies to ensure efficient and fair transactions. The Contract Net Protocol (CNP), a well-established negotiation strategy within Multi-Agent Systems (MAS), offers a promising solution. This paper explores the integration of CNP into MLDM, proposing the CNP-MLDM model to facilitate data exchanges. Characterized by its task announcement and bidding process, CNP enhances negotiation efficiency in MLDM. This paper describes CNP tailored for MLDM, detailing the proposed protocol following experimental results.

Abstract
Accurate dynamics modelling of Unmanned Under-water Vehicles (UUV s) is critical for optimizing mission planning, minimizing collision risks, and ensuring the successful execution of tasks in diverse underwater environments. This paper presents a structured approach to estimating the hydrodynamic coeffi-cients of UUV s. Initially, it follows a detailed methodology for estimating hydrodynamic coefficients using simple geometries, a sphere and a spheroid, using the Computational Fluid Dy-namics (CFD) software OpenFoam, and comparing the results to analytical solutions, enabling the validation of the simulations approach. Following this, the paper provides an in-depth analysis of the damping and added mass coefficients for the Raya UUV, offering valuable insights into its hydrodynamic behaviour. © 2024 IEEE.

Abstract
Spectral imaging is a technique that captures spectral information from a scene and maps it onto a 2D image, featuring the potential to reveal hidden features and properties of objects that are invisible to the human eye, such as elemental and molecular compositions. Augmented reality (AR), on the other hand, is a technology that enhances the perception of reality by superimposing digital information on the physical world. While these technologies have different purposes, they can be considered one and the same in terms of providing an user-centric extension of reality. Spectral imaging provides the information that can reveal the underlying nature of objects, while AR provides the method of visualization that can display the information in an intuitive and interactive way. In this work, we present a novel Unity toolkit that combines spectral imaging and a HoloLens 2 AR device to create an interactive and immersive experience for the user. The toolkit enables the interactive visualization of various elemental maps of a 3D rock model in AR using a simple and intuitive interface. With this technique, the user can select a sample model and an elemental map from a preloaded asset library and then see the map projected onto the rock model in AR, using simple interactions such as zoom adjustment, rotation, and pan of the models to explore features and properties in detail. The toolkit offers several advantages, including better contextual interpretation of the spectral data by placing it in relation to the shape and texture of the rock, increased user engagement and curiosity through the creation of a realistic and immersive experience, and ease of decision-making through the provision of comparative tools. In short, by combining spectral imaging and AR, we present an innovative approach that can enrich the user experience and expand the user knowledge of the environment.

Abstract
The Web of Things (WoT) is an essential component within the Internet of Things (IoT) domain, offering a standardized method for describing, consuming, and orchestrating the functions of IoT devices. WoT plays a crucial role in promoting interoperability and streamlining the development of applications for IoT solutions. Recent research focusing on IoT solutions for ambient assisted living (AAL) has highlighted WoT as a key framework for integrating diverse smart devices and services to enhance the quality of life for older adults and individuals with specific health conditions. However, a closer look at recent literature reviews reveals a deficiency in comprehensive research regarding the interplay between WoT, AAL, and the health and wellbeing of older adults. To address this question, a comprehensive mapping review is performed to delve into the existing literature and pinpoint the most pertinent themes and topics within WoT. This analysis aims to uncover evidence of the correlation between WoT, AAL, and active and healthy aging (AHA) to support future research in this area.

Abstract
BackgroundHereditary transthyretin amyloidosis (ATTRv amyloidosis) is an inherited disease, where the study of family history holds importance. This study evaluates the changes of age-of-onset (AOO) and other age-related clinical factors within and among families affected by ATTRv amyloidosis.MethodsWe analysed information from 934 trees, focusing on family, parents, probands and siblings relationships. We focused on 1494 female and 1712 male symptomatic ATTRV30M patients. Results are presented alongside a comparison of current with historical records. Clinical and genealogical indicators identify major changes.ResultsOverall, analysis of familial data shows the existence of families with both early and late patients (1/6). It identifies long familial follow-up times since patient families tend to be diagnosed over several years. Finally, results show a large difference between parent-child and proband-patient relationships (20-30 years).ConclusionsThis study reveals that there has been a shift in patient profile, with a recent increase in male elderly cases, especially regarding probands. It shows that symptomatic patients exhibit less variability towards siblings, when compared to other family members, namely the transmitting ancestors' age of onset. This can influence genetic counselling guidelines.