Syntgen: A system to generate temporal networks with user specified topology

Network representations can help reveal the behavior of complex systems. Useful information can be derived from the network properties and invariants, such as components, clusters or cliques, as well as from their changes over time. The evolution of clusters of nodes (or communities) is one of the major focus of research. However, the time dimension increases complexity, introducing new constructs and requiring novel and enhanced algorithms. In spite of recent improvements, the relative scarcity of timestamped representations of empiric networks, with known ground truth, hinders algorithm validation. A few approaches have been proposed to generate synthetic temporal networks that conform to static topological specifications while in general adopting an ad-hoc approach to temporal evolution. We believe there is still a need for a principled synthetic network generator that conforms to problem domain topological specifications from a static as well as temporal perspective. Here we present such a system. The unique attributes of our system include accepting arbitrary node degree and cluster size distributions and temporal evolution under user control, while supporting tunable joint distribution and temporal correlation of node degrees. Theoretical contributions include the analysis of conditions for "graphability" of sequences of inter and intra cluster node degrees and cluster sizes and the development of a heuristic to search for the cluster membership of nodes that minimizes the shared information distance between clusterings. Our work shows that this system is capable of generating networks under user controlled topology with up to thousands of nodes and hundreds of clusters with strong topology adherence. Much larger networks are possible with relaxed requirements. The generated networks support algorithm validation as well as problem domain analysis

Implementation of the Medical Response to Major Incidents Course in Madeira, Portugal

Background. The Medical Response to Major Incidents (MRMI) course was created in response to the need to train people from multi-agencies on major incidents management. In Madeira, a group of physicians and nurses from SESARAM attended this course and “Madeira International Disaster Training Center” (MIDTC) was created with the objective of providing training in the areas of emergency, trauma and catastrophe. Since its implementation, the MRMI course has been offered in Portugal twice a year in Madeira, Mainland Portugal and Azores. Objectives. To describe the method of implementation and functioning of the MRMI course and, additionally, to study the degree of satisfaction of the trainees. Material and methods. A quantitative study was performed during our last courses, using a satisfaction scale with the simulated clinical experience composed of 17 items with a Likert-type scale, punctuated from one (lowest level of satisfaction) to ten (highest level of satisfaction), in terms of practical, cognitive and realism dimensions. Data analysis was performed using the SPSS Statistic software, v. 25. A p-value of < 0.05 was used as the significance threshold. Results. Twenty-one Portuguese MRMI courses were attended by 1,556 trainees from different professional areas (physicians, nurses, emergency and security technicians, social workers, command and control professionals). One hundred sixty-three surveys submitted by the trainees were available for analysis. A total of 60.7% of the respondents were men aged 30–49 years (71.8%). The overall satisfaction average score was 9.06. The practical dimension attained the highest score (9.12), followed by realism (9.05) and finally the cognitive aspect (8.90). Non-medical trainees’ scores were slightly lower when compared to the scores provided by the medical trainees. Conclusions. Demand for the MRMI course in Portugal has been high, with the number of students increasing since its first implementation. This makes the MRMI course a practical doctrine to implement in Portugal by the national authorities.info:eu-repo/semantics/publishedVersio

The Soccer Game, bit by bit: An information-theoretic analysis

We modeled the dynamics of a soccer match based on a network representation where players are nodes discretely clustered into homogeneous groups. Players were grouped by physical proximity, supported by the intuitive notion that competing and same-team players use relative position as a key tactical tool to contribute to the team's objectives. The model was applied to a set of matches from a major European national football league, with players' coordinates sampled at 10Hz, resulting in approx. 60,000 network samples per match. We took an information theoretic approach to measuring distance between samples and used it as a proxy for the game dynamics. Significant correlations were found between measurements and key match events that are empirically known to result in players jostling for position, such as when striving to get unmarked or to mark. These events increase the information distance, while breaks in game play have the opposite effect. By analyzing the frequency spectrum of players' cluster transitions and their corresponding information distance, it is possible to build a comprehensive view of player's interactions, useful for training and strategy development. This analysis can be drilled down to the level of individual players by quantifying their contribution to cluster breakup and emergence, building an overall multi-level map that provides insights into the game dynamics, from the individual player, to the clusters of interacting players, all the way to the teams and their matches.Comment: 18 pages, 9 figure