Cooperation of research groups is nowadays common for the development and execution of biomedical analyses. Multiple partners contribute data in this context, data that is often centralized for processing at some cluster-based or supercomputer-based infrastructure. In contrast, real distributed collaboration that involves processing of data from several partners at different sites is rare. However, such distributed analyses are often very interesting, in particular, for scalability, security and privacy reasons. In this article, we motivate the need for real distributed biomedical analyses in the context of several ongoing projects, including the ICAN project that involves 34 French hospitals and affiliated research groups. We present a set of distributed architectures for such analyses that we have derived from discussions with different medical research groups and a study of related work. These architectures allow for scalability, security/privacy and reproducibility issues to be taken into account. Finally, we illustrate that these architectures can serve as the basis of a development method for biomedical distributed analyses.

Concerns have emerged regarding the expenses associated with integrating virtual reality into the digital transformation of companies, stemming from costs related to 3D software development and procurement of headsets. Despite the acknowledged benefits of experiential learning in military training, education and medicine, industrial adoption of virtual reality remains constrained. This study delves into the distinctive advantages of virtual reality in the elevator industry and proposes a cost-effective and innovative virtual reality (VR) training solution and evaluation model aimed at improving the learning outcomes of engineers in the field, grounded in the critical thinking theory. The proposed model seeks to capitalize on the benefits of VR in projects geared towards digital transformation by identifying "meta-requirements" and "principal designs" through a design science research method focused on problem solving. This approach has potential applications in other domains. Our methodology employs a unique strategy to develop a virtual reality experiential training program that harnesses engineers’ cognitive potential to enhance their critical thinking skills. To evaluate the effectiveness of this approach, we conducted a comparative analysis with a control group trained through traditional digital methods, concentrating on "decision-making and problem-solving" as well as "thinking through hypothesis testing." Engineers undergoing virtual reality training exhibited heightened motivation, emotional engagement, and curiosity levels toward the subject, providing detailed accounts of their experiential training in relation to physical space and time. The "learning by doing" approach resulted in a 15% enhancement in critical thinking among participants, along with a notable 44% improvement in recognition memory.

The proliferation of on-demand internet services delivered over a network of a heterogeneous set of computing devices has created the need for high-performing dynamic systems in real-time. Services such as audio and video streaming, self-driving cars, the Internet of things (IoT), or instant communication on social networks have forced system designers to rethink the architectures and tools for implementing computer systems. Reactive programming has been advocated as a programming paradigm suitable for implementing dynamic applications with complex and heterogeneous architectural needs. However, there is no consensus on the core set of features that a reactive framework must-have. Furthermore, the current set of features proposed in reactive tools seems very restricted to cope with the actual needs for concurrency and distribution in modern systems. In this paper, several alternative semantics for distributed reactive languages are investigated, addressing complex open issues such as glitch avoidance, explicit distribution support, and constructs for explicit time management. First, we propose a reactive event-based programming language with explicit support for distribution, concurrency, and explicit time manipulation (ReactiveXD). Second, we present a reactive event-based semantic framework called Distributed Reactive Rewriting Framework (DRRF). The framework uses rewriting logic to model the components of a distributed base application, observables, and observers, and predicates supporting explicit time manipulation. Finally, to validate the proposal, the paper discusses the specification of the semantics of ReactiveXD and a scenario describing a case of intrusion detection on IoT networks.