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Computational reproducibility is a corner stone for sound and credible research. Especially in complex statistical analyses-such as the analysis of longitudinal data-reproducing results is far from simple, especially if no source code is available. In this work we aimed to reproduce analyses of longitudinal data of 11 articles published in PLOS ONE. Inclusion criteria were the availability of data and author consent. We investigated the types of methods and software used and whether we were able to reproduce the data analysis using open source software. Most articles provided overview tables and simple visualisations. Generalised Estimating Equations (GEEs) were the most popular statistical models among the selected articles. Only one article used open source software and only one published part of the analysis code. Replication was difficult in most cases and required reverse engineering of results or contacting the authors. For three articles we were not able to reproduce the results, for another two only parts of them. For all but two articles we had to contact the authors to be able to reproduce the results. Our main learning is that reproducing papers is difficult if no code is supplied and leads to a high burden for those conducting the reproductions. Open data policies in journals are good, but to truly boost reproducibility we suggest adding open code policies., Competing Interests: The authors have declared that no competing interests exist.

Moisture diffusion in carbon fiber composites changes the mechanical properties of the composite. Therefore, a monitoring method of the actual content of moisture in the composite is important. However, at the moment there are no online methods established. A common method is the measurement of the mass changes due to water uptake. This method is not suitable for online monitoring of a real composite part in service. We demonstrate that miniaturized flexible interdigital sensors are suitable for moisture measurement inside the carbon fiber composite. These sensors are directly integrated inside the composite. It was already demonstrated that these can be successfully used for resin-curing monitoring as a primary application. Here we demonstrate that the same sensors are also suitable for moisture measurement inside the material. In order to do so, we expose samples with and without integrated sensors to hot-wet conditions and measure the dielectric changes with the sensors and the mass gain. The moisture concentration and the measured admittance can be directly correlated to each other. This demonstrates that the sensors can be used for moisture measurement as a secondary application. In addition, it is shown that the sensors have the potential to measure the moisture locally inside the material.