This review focuses on the characteristics of tennis players during match play and provides a greater insight into the energy demands of tennis. A tennis match often lasts longer than an hour and in some cases more than five hours. During a match there is a combination of periods of maximal or near maximal work and longer periods of moderate and low intensity activity. Match intensity varies considerably depending on the players' level, style, and sex. It is also influenced by factors such as court surface and ball type. This has important implications for the training of tennis players, which should resemble match intensity and include interval training with appropriate work to rest ratios.

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The new unified monitoring architecture (MONIT) for the CERN Data Centres and for the WLCG Infrastructure is based on established open source technologies to collect, stream, store and access monitoring data. The previous solutions, based on in-house development and commercial software, have been replaced with widely- recognized technologies such as Collectd, Kafka, Spark, Elasticsearch, InfluxDB, Grafana and others. The monitoring infrastructure, fully based on CERN cloud resources, covers the whole workflow of the monitoring data: from collecting and validating metrics and logs to making them available for dashboards, reports and alarms. The deployment in production of this new DC and WLCG monitoring is well under way and this contribution provides a summary of the progress, hurdles met and lessons learned in using these open source technologies. It also focuses on the choices made to achieve the required levels of stability, scalability and performance of the MONIT monitoring service.

Abstract. The latest policy developments require immediate action for data preservation, as well as reproducible and Open Science. To address this, an unprecedented digital library service is presented to enable the High-Energy Physics community to preserve and share their research objects (such as data, code, documentation, notes) throughout their research process. While facing the challenges of a "big data" community, the internal service builds on existing internal databases to make the process as easy and intrinsic as possible for researchers. Given the "work in progress" nature of the objects preserved, versioning is supported. It is expected that the service will not only facilitate better preservation techniques in the community, but will foremost make collaborative research easier as detailed metadata and novel retrieval functionality provide better access to ongoing works. This new type of e-infrastructure, fully integrated into the research workflow, could help in fostering Open Science practices across disciplines.