REPCAN: Guideline for REporting Population-based CANcer Registry Data

Background: The objective of this study was to develop a guideline on how to report result of a population-based cancer registry. Methods: The guideline's development involved a core working committee and a scientific committee comprising experts from diverse domains. The process comprised three steps: 1) a comprehensive review of existing tools and guidelines and the development of the initial draft of the guideline based on a review of literature, 2) refinement items through several rounds of focus group discussion among the core group, and development initial draft, and 3) Evaluation of the initial draft by scientific committee members. Items in the guideline were organized to accommodate reports of population-based cancer registries as a scientific manuscript. Results: The core committee developed 47 items distributed in the major heading of a scientific manuscript presented as a checklist. The evaluation of the scientific committee led to a consensus on the majority of the items included in the checklist. Among 10 committee members, 7 provided unreserved approval, validating each item's necessity, applicability, and comprehensibility in the checklist. Feedback from the remaining 3 members was carefully analyzed and integrated to enhance the guideline's robustness. Incorporating feedback, a first final draft was presented in a meeting of scientific and core working committee members. Collaborative discussion ensured clarity of expression for each items and a final checklist was developed. Conclusion: The guideline abbreviated as REPCAN offers a standardized framework for reporting population-based cancer registry, fostering transparency, comparability, and comprehensive data presentation. The guideline encourages flexibility while promoting comprehensive and robust reporting practices.

Information Distribution in Multi-Robot Systems: Generic, Utility-Aware Optimization Middleware

This work addresses the problem of what information is worth sending in a multi-robot system under generic constraints, e.g., limited throughput or energy. Our decision method is based on Monte Carlo Tree Search. It is designed as a transparent middleware that can be integrated into existing systems to optimize communication among robots. Furthermore, we introduce techniques to reduce the decision space of this problem to further improve the performance. We evaluate our approach using a simulation study and demonstrate its feasibility in a real-world environment by realizing a proof of concept in ROS 2 on mobile robots.

An Evaluation Model for Information Distribution in Multi-Robot Systems

This work addresses the problem of information distribution in multi-robot systems, with an emphasis on multi-UAV (unmanned aerial vehicle) applications. We present an analytical model that helps evaluate and compare different information distribution schemes in a robotic mission. It serves as a unified framework to represent the usefulness (utility) of each message exchanged by the robots. It can be used either on its own in order to assess the information distribution efficacy or as a building block of solutions aimed at optimizing information distribution. Moreover, we present multiple examples of instantiating the model for specific missions. They illustrate various approaches to defining the utility of different information types. Finally, we introduce a proof of concept showing the applicability of the model in a robotic system by implementing it in Robot Operating System 2 (ROS 2) and performing a simple simulated mission using a network emulator. We believe the introduced model can serve as a basis for further research on generic solutions for assessing or optimizing information distribution.