 Hello everyone. Seems I know most of people are already here, but always happy to meet new one. And today I'm gonna be talking mostly about automation in grants distribution and how we implemented this model within our platform. And because it's tightly aligned with evaluation of scientific research and as Philip, by the way, already mentioned that funders need to screen projects and screening is mostly about evaluation. And if we want to automate this process, if we want to get rid of all these like huge operational costs during this process, we need also to get somehow evaluation more decentralized, more trustworthy. Okay, let me check. Yeah, is it the right presentation? Okay, so it seems it's not possible to distribute grants without involvement from scientists' side because scientific projects are really complex. And if it's the main specific complex project, only scientists who has this expertise within this discipline can and are able to evaluate this and receive and provide for funders for decision makers' information about is it viable, is it feasible, is it good project design, is it worth to fund? So, and actually it's kind of a review and this review, all this review is put inside into funders, into their process and we put trust on them that they do this appropriately, they do this efficiently, that they spend all this operational cost, they're consuming efficiently to determine quality, determine scientific contribution of each research. But really it's kind of a process which can be improved. Obviously everything can be improved but if it could be decentralized and put into open access and results of this evaluation put into open access, then everyone can use it to make a decision on either to fund the research, either to publish this research, either to join to this research group as a junior PhD student. So, let me start a bit from describing a bit our platform and here are our main tokens within our system. There are six type of tokens within our system and first one is the DABE token, it's internal currency. It's the most simple one because it's like store of value and just money, just currency within a system. And another token is the expertise tokens which represents scientific contribution, expertise contribution of each individual within a system. And this is actually the core of the system. These tokens are used also for a relational scientific projects and for governments of all system. Research tokens, I'm not gonna talk a lot about them today but it's also another opportunity to fund a research project because research tokens represents ownership of research and can be used also for investment, for investment into scientific research to receive as investor, by investing into research project, I will be able to receive corresponding part of all future income from IP, from products pinned off from this research project. Research group token is a governments for research group and mostly like voting token, voting shares of research group. Common token is a technical token which allocates throughput within a network and journal token is also very interesting model for journals which will avoid conflict of interest with research projects because currently journals obviously have this conflict of interest. Journals were designed to promote good research and disseminate scientific knowledge but because of conflict of interest and commercial model, now they like more chasing a hype, purchasing like profit and this is definitely not like a good way to promote science, promote quality. And journal token is kind of a venture fund which invest into research token and therefore incentivized to invest into best projects within a system. And portfolio of venture fund is like a journal which shows what this journal have invested in and they will receive also revenue from what they invested in. So that's why now their interest is aligned with the research and then what want to invest into best research, most promising research which will generate most impact in future. Okay, so now let's get back to funding because first of all it's main topic of my today talk. Within our system we have two major classes, two major categories of funding within a system. And first one is external which requires some external funding from government, from private foundations to come to the system and then be distributed within the system. And this external funding involves both investment and grants. And another funding is internal. It's coming from emission of internal currency and represents kind of basic research for basic income for researchers. So every block, every three seconds with our blockchain there is a emission of internal currency which is distributed across research projects, across researchers as a reward for their scientific contribution. It's, and you don't need to trust anyone. So if you've done scientific contribution you will be awarded by protocol and it's all in the algorithm. So you don't need any intermediary for this. And grants also can be automated with this system because the same way we distribute a reward from internal currency, grants can be allocated for specific discipline and distributed to research projects within this discipline. And to distribute this grants, we actually need a quantified index of scientific contribution of each research. And this is what we have done for evaluation of scientific research within our system. We designed mathematical model which produces quantified index of scientific contribution of each research within each discipline. And using this quantified index, smart contract can distribute funds both from internal currency and both from external grants between these research projects. And this also works for basic research. So you can be rewarded even by doing basic research because in our system a part of reward also distributed to references. And if your basic research is referenced a lot from other research projects which earns some revenue within the system, earns some income within the system, your basic research will be rewarded from all research projects which are based on knowledge you created. So, and this is kind of returning back a value for basic research which a bit lost during past 100 years. And by doing basic research you still will be rewarded from everything, every knowledge produced from this basic research. Yeah, so grants distribution as I said can be automated within a system. So let me tell a bit more how it works. Let imagine you have $10 million which you want to distribute across research projects during one year in quantum optics discipline. And you want this money to be distributed to most desorbed project. So within a system there is a smart contract where you can allocate this money and it will be distributed during one year, this money across research projects in this specific discipline accordingly to their index of scientific contribution. And all results of what it was distributed when to what research projects can be audited because it's in public blockchain and you can track why it was distributed to this research, what was proportion, what was ratio of index, scientific contribution index during that period of time. And you can like analyze all history anytime. And actually it also can help us and scientific community enhance the system because after all this happens, all this data can be used to enhance the model of this distribution. Yes, and because all these really rely on results of decentralized assessment, it should be in this scientific contribution index produced by the system. It should be really trustworthy and efficient in terms of how it produced. So it should really reflect real scientific contribution of this research. So that's why I also decided to tell you a bit more about how it's done. So main idea is that we can have, we already have in scientific community, there's already review peer review and this review happens both when you're publishing, when you're applying for a grant, when you just receiving a feedback from scientists from your discipline. And the problem is that this review is not really representative. If you are not an expert, even if you have a review, you don't know what exactly tells about this project. So is it, what is exactly scientific contribution of this research? So we designed a system where scientists can already have incentive within this system, have incentive to assess research projects and results of this assessment are used to produce quantified index of scientific contribution which further can be used by funders, by journals and by society to understand what is the scientific contribution of this research. And our assessment, decentralized assessment process is kind of two level assessment process because we have a review level where scientists can do a review and assign expertise tokens to each review. So it's actually automatically assigned. Once you write a review to research project, the sum of your expertise tokens in the discipline of this research is assigned to review. But also each review can be supported by expertise token holders within the discipline of research. And this information is used to produce index of scientific contribution. So basically our system takes into account what was the order of approving and rejecting review? What was the time delay between each review? What was the expertise of reviewer? How much support each review received? And all this information is used to produce this final index of scientific contribution and research starting getting it even on early stage which can be used for early grants distribution. And then during the enhancement of the scientific project, this index will grow and will let community funders and journals identify, identify good research within the system. And this index is also used to distribute newly created expertise tokens because as you see, expertise tokens is a main governance mechanism within the system and it's also a reputational recognition reward for a scientist. So if I have a expertise token within a quantum optics and means that I did a scientific contribution there and I cannot transfer these tokens, they're not transferable. And they just belong to me and represents my scientific contribution within this discipline. And therefore there is constant emission of expertise tokens as well as internal currency and the size of a mission depends on activity within this discipline. So the more activities, the more expertise tokens emitted and they're distributed to each discipline proportionately to activity within a discipline. And then they're distributed between two pools, research pool and review pool. And proportion is self-balanced, it's automatically balanced depending on proportion of review and research within a system, so within a discipline. So if there is not enough review within a discipline, the more expertise tokens will be allocated to review pool to incentivize more review within this discipline, to incentivize quality. And further, they're distributed to actually researchers and reviewers as recognition reward as a reputational reward. And the same way, almost the same way as the expertise tokens, there is emission of internal currency which is distributed as a financial reward as a basic income for scientists and for reviewers. And what is also very important that wall system, wall infrastructure, because we have developed our own blockchain and we were able to introduce new consensus algorithm which actually governs all the system. And this consensus algorithm ensures that wall system belongs to scientists and only scientific community can come to consensus to change it or update it. So this consensus algorithm, we call it delegated proof of expertise contribution which means that scientists vote for block producer with some of his or her expertise tokens and block producers kind of delegated to maintain the network. But only scientific community can come to consensus to change rules, to change how this index of scientific contribution is produced. And they have all tools to evolve the system because all data is public and we will also open source all tools we created for during development of the system. Actually, one of major tool for this is our agent based simulation model framework to which we're using to create our crypto economy, to create economy of a blockchain. This simulation framework allows us to emulate how this distribution will behave, what will be results of this distribution and tune the model to achieve efficiency. And yeah, so this is a high level model of organizational structure where you can see that grants and investment can be distributed through the platform and we will also create endowment foundation which will initiate grant distribution within the system. Yeah, so there are two sentences which actually represents all why we're working on this and why we're so patient about this. And actually this is two sentences is the end of our white paper and I encourage you to read it and provide the feedback if you want. Thank you.