 Right, ladies and gentlemen, indeed, yet another concrete bridge. So I'll try to tell you about our goal and focus for this concrete case. In doing that, I would like to give some context. Within here now, we are now working with a multi-year research program, a so-called early research program. And we are assessing existing reinforced concrete structures and accounting for multiple sources of uncertainties. Quite familiar to all of you, I guess. And next to material properties and loads and modeling uncertainties, we are focusing to one specific deterioration process, corrosion. A nice scheme, but I will not go into that. People can have a look at it later. But the idea is indeed assessment and predictions. Next to this early research program, also in the Netherlands, people are making up their minds and doing some studies about how to deal with information and come to rationale for reasoning for decisions based on information. So we have recently some guidelines for existing structures on a national level, so for the national road authorities and highway bridges. And currently, there are also studies coming on for recommendations for local bridges, for local authorities like municipalities. So this might be something that we can take into account for the case study proposed. The real subject of the case study that I would like to propose is a typical sensor. We call it a multi-sensor data fusion. And the idea is that we derive a sensor that simultaneously measures multiple physical quantities. And we also derive an interpretation model for the assessment of the corrosion state, whether or not there is corrosion and what the corrosion rate is. So instead of, for instance, measuring only one physical quantity, like potential current density, the idea is to measure a total of eight physical properties with one combined sensor. And I already mentioned the interpretation model. It's based on a VAsian network that is trained, so to speak, with a lot of data from the past. And the outcome of this interpretation model is, let's say, the probabilities or distribution functions of the corrosion state, so yes or no corrosion. And next to that, also the corrosion rate, so the number of corrosion loss per year at the time. Now our proposal for the actual case study in terms of value of information, we would like to investigate the added value of this multi-sensor data fusion node or measurements compared to the more traditional measurement of sensors, where, for instance, only one or two physical quantities are measured. Possible structures that might be relevant for this is, for instance, the bridge of the river list that was already introduced by Louis. In fact, this bridge is also used within this aforementioned early research program where we take where we profit from all the data that we obtain from Louis. The other possible structures are city bridges in Amsterdam or, for instance, in Rotterdam. The value of information approach, we are thinking of using again BHG networks or dynamic BHG networks. Well, a few examples here from authors that you all are familiar with, I guess. And, for instance, on the left side, we see an example from Jürgen Hackel and Jochen Kohler where you see already the impact of reducing uncertainties in the case of measuring the potential based on half-cell potential method. So that might be a stepping stone towards a value of information study for our sensor. So in a nutshell, a concrete bridge, the origin of free enforcement, we would like to compare the added value of this multi-sensor data fusion measurements to more traditional sensors. The method and tools that we envisage are dynamic belief nets and influence diagrams. Maybe to be combined also with some reasoning with respect to the decision to be made based on information. And finally, but also very important, we are very open to team up with other case studies. Thank you.