Abstract
Following the lack of existing studies about the applications development and use in the event industry, this research aims to analyze the use of applications as a tool to improve event communication. The methodology used includes an exploratory method. This research methodology is based on a review of the literature, a semi-structured interview with the CEO of the company and a case study with participant observation of the French start-up Invent App which provides event applications. The study demonstrate that the event app use allows to ease the event organization, to improve the event communication but also the interactivity and the participant engagement. All of this, increasing the customer experience but also having a part in the customer digital experience improvement. Event applications could be thus considered as amarketing and event communication tool. The research has the limitation to its application within a single company in France. Furthermore, the point of viewadopted is the one of the event organizers and not the event participant one. This research helped to better understand the role that event applications can have in the event industry and particularly in the communication around an event. In addition, this made it possible to understand the perception of market requirements and the characteristics expected of an event application.

Abstract
Phonology is a linguistic discipline that is naturally computational. However, as many researchers are not familiar with the use of digital methods, most of the computation required is still performed by humans. This article presents a training experiment of master's students of the phonology seminar at the University of Porto, bringing the research process directly to the classroom. The experiment was designed to raise students' awareness of the potentialities of combining human and machine computation in phonology. The Centre for Digital Culture and Innovation (CODA) readily embraced this project to showcase the application of digital humanities as humanities in both research and training activities. During this experiment, students were trained to collect and process phonological data using various open-source and free web-based resources. By combining a strict protocol with some individual research freedom, the students were able to make valuable contributions towards Creolistic Studies, while enriching their individual skills. Finally, the interdisciplinary nature of the approach has demonstrated its potential within and beyond the humanities and social sciences fields (e.g., linguistics, archaeology, history, geography, ethnology, sociology, and genetics), by also introducing the students to basic concepts and practices of Open Science and FAIR principles, including Linked Open Data.

Abstract
For decades, the collaborative networks community has studied supply chains, focusing on trust, visibility, collaboration, and innovation, with emergent technologies being a key area of research. The rise of digital technologies has led to extensive studies on supply chain digital transformation. With the surge of AI-based technologies, there is an increasing body of research on AI's human and social impact on Supply Chain Management (SCM). However, while Socio-Technical Systems (STS) thinking has been applied to digital transformations, it has not yet addressed AI-induced changes in supply chains. This paper synthesises recent research on AI integration in SCM and the use of STS thinking in AI systems design. We propose a mapping approach for profiling AI-induced supply chain transformations for strategic design. We also present the Supply Chain Socio-Technical AI (SC-STAI) profiling tool in practice, demonstrating how it maps supply chain participants’ current and desired states regarding AI integration. © IFIP International Federation for Information Processing 2024.

Abstract
Hyper-parameter tuning of machine learning models has become a crucial task in achieving optimal results in terms of performance. Several researchers have explored the optimisation task during the last decades to reach a state-of-the-art method. However, most of them focus on batch or offline learning, where data distributions do not change arbitrarily over time. On the other hand, dealing with data streams and online learning is a challenging problem. In fact, the higher the technology goes, the greater the importance of sophisticated techniques to process these data streams. Thus, improving hyper-parameter self-tuning during online learning of these machine learning models is crucial. To this end, in this paper, we present MESSPT, an evolutionary algorithm for self-hyper-parameter tuning for data streams. We apply Differential Evolution to dynamically-sized samples, requiring a single pass-over of data to train and evaluate models and choose the best configurations. We take care of the number of configurations to be evaluated, which necessarily has to be reduced, thus making this evolutionary approach a micro-evolutionary one. Furthermore, we control how our evolutionary algorithm deals with concept drift. Experiments on different learning tasks and over well-known datasets show that our proposed MESSPT outperforms the state-of-the-art on hyper-parameter tuning for data streams.

Abstract
The trends of the 21st century are challenging the traditional production process due to the reduction in the life cycle of products and the demand for more complex products in greater quantities. Industry 4.0 (I4.0) was introduced in 2011 and it is recognized as the fourth industrial revolution, with the aim of improving manufacturing processes and increasing the competitiveness of industry. I4.0 uses technological concepts such as Cyber-Physical Systems, Internet of Things and Cloud Computing to create services, reduce costs and increase productivity. In addition, concepts such as Smart Factories are emerging, which use context awareness to assist people and optimize tasks based on data from the physical and virtual world. This article explores and applies the capabilities of context-aware applications in industry, with a focus on production lines. In specific, this paper proposes a context-aware application based on a microservices approach, intended for integration into a context-aware information system, with specific application in the area of manufacturing. The manuscript presents a detailed architecture for structuring the application, explaining components, functions and contributions. The discussion covers development technologies, integration and communication between the application and other services, as well as experimental findings, which demonstrate the applicability and advantages of the proposed solution.

Abstract
In an increasingly aging and overweight population, osteoporosis and type 2 diabetes (T2DM) are major public health concerns. T2DM patients experience prejudicial effects on their bone health, affecting their physical capacity. Exercise in hypoxia (EH) and a low-carbohydrate diet (LCD) have been suggested for therapeutic benefits in T2DM, improving bone mineral content (BMC) and glycemic control. This study investigated the effects of EH combined with an LCD on body composition and functional and physiologic capacity in T2DM patients. Older T2DM patients (n = 42) were randomly assigned to the following groups: (1) control group: control diet + exercise in normoxia; (2) EH group: control diet + EH; (3) intervention group: LCD + EH. Cardiopulmonary tests (BRUCE protocol), body composition (DEXA), and functional capacity (6MWT, handgrip strength) were evaluated. Body mass index (kg/m(2)) and body fat (%) decreased in all groups (p < 0.001). BMC (kg) increased in all groups (p < 0.001) and was significantly higher in the EH and EH + LCD groups (p < 0.001). VO2peak improved in all groups (p < 0.001), but more so in the hypoxia groups (p = 0.019). Functional capacity was increased in all groups (p < 0.001), but more so in the EH group in 6MWT (p = 0.030). EH with and without an LCD is a therapeutic strategy for improving bone mass in T2DM, which is associated with cardiorespiratory and functional improvements.