 Thanks, Diane. I'm actually here on behalf of more than 50 University of Auckland researchers from the Light Metals Research Center and the Product Accelerator and other programs that we've run over the years. And I've got five points that I want to run through, exemplify to try and show the way step changes in manufacturing can occur. The first one is that you have to be in the data stream. You have to see the problems every day that manufacturers and and I'm including materials, processes of all types. I'm including designers, industrial designers since we have some industrial designers in the room, I think. All of the step changes, any step change can only be made on the basis of inspiration and usually stimuli and stimuli needs data and you need to be in the data stream and unfortunately, although we try and Kather Simpson's new company Engender will help. We need about another hundred or two hundred of them. The university is not in the manufacturing data stream and we struggle with that. I'll give you an example. I guess we were asked by Anne New Zealand to, if we could, produce a new generation of spare parts, because a certain spare part that I probably shouldn't say what it is, but you use it in the facility that Debesh was referring to in the front of the airplane, apparently. It costs eight thousand dollars to produce, takes between six and twelve months to arrive in New Zealand and then Anne New Zealand can install it. We 3D printed them for, I think it was a hundred dollars. They were better, stronger, had a better surface finish and went straight into the aeroplanes. And to do that though, we spent before that about six or seven years working with airframe fit-out specialist designers in New Zealand companies to understand what were the types of issues with these fit-out parts. And then we used a technology for additive manufacturing, digital production to make them at one of the universities not too far from here. So and we've had other many examples where in the construction industry the types of things like this frame here or racking and piping for utilities is the first thing that fails in an earthquake because of the lack of damping in those structures as the building sways and we with that knowledge we were able to design some damping structures and 3D print them by another technique fused deposition modeling with the right modulus so that they damp the vibration. Two stiff structures don't do that. But overseas they made stiff structures using selective laser centering, which didn't work because they didn't have the right modulus, stress-strain relationship. So these things can only be done if you're in the data stream, and I guess that's the first learning that we've had. You need to be out in the laboratories that are in factories. In fact, your laboratory probably will be a factory, not a laboratory in the university, and that's a bit of a cultural thing for the universities to sort of take on board. But it's essential. A practitioner or rather a university researcher like myself might see two or three manufacturing problems a month. A practitioner in a factory sees 20 or so a day. The data stream and they're different data. They're not published data in journals. They're the real problems that nobody knows about and don't get published. So you have to be there. The second point about about step changes in manufacturing and referring to researchers here is is that the big projects are both fundable and achievable within the university. By big, I mean, you know, what we've had in the last 14 years for MB grants about 10 million dollars each. But to get the money, you have to not only say, but you have to actually achieve an outcome which is significant that warrants the investment of the money, which makes, I think, good sense and MB do fund on that basis. But to do that, that means you have to have a team of 10 to 20 people. And the people have to be experienced in various areas, including in the community and especially in the community. So if you're going to bid for that sort of money from MB and if you're going to get a track record where you've actually managed to achieve some of what you said you were going to, it means that you have to manage teams that are larger. You know, one or two people, it's difficult to do. It's difficult. It's not difficult to do some research, but it's difficult to get it applied. And I guess the part, thank you, one minute. The part of this, which is, which is tough is that our research is rather than applied, it's application inspired. So one of the inventions that one of my colleagues over here, Pratish Pratels had a lot to do with is heat exchanges, where we had to take the heat transfer coefficient for heat transfer fluid called air. Anyone, I guess everyone knows, air is a horrible heat transfer fluid. We had to take that heat transfer coefficient from 10 to 100, factor of 10, and we had to do it at very low air flows. So that was the data stream that was in industry that the other researchers around the world couldn't hear. We heard it and we spent a long time in the university working out how to do it and managed to achieve a new technology because of it. Those are two of the points. Next time maybe we'll have another two. Thank you.