I will basically be short and introduce you to a part of a session that focused on advanced methods in ground and excited state computations and Professor Nice's expertise is in quantum chemistry and particular wave function based methods and he's been doing some very exciting calculations at the frontier of using couple cluster methods, sort of higher level gold standard quantum chemistry, wave function quantum chemistry on systems in the solid state in the condensed phase. And so this is a very exciting area in our community for both validation of say plain wave density functional theory advanced methods but also opening up new avenues for exploring the phenomena of complex materials. So I'll let Frank tell you more about it. Frank please floor is yours and I'll give you a warning at five minutes about 25 minute talk. Thank you very much for the kind invitation to come here and I'm very sorry for the confusion that I caused it was a family tragedy this morning and I have to add out. But I nevertheless want to embrace the opportunity to tell us a little bit what we did in the field of solids and surfaces and I do it from the perspective of molecular quantum chemistry if I come across a bit amateurishly during the talk that's the truth. So let's look at a molecule or molecular system or maybe also solid through the eyes of physicists and it's nothing else but a collection of positively charged nuclei assumed at rest and the moving electrons and what I always find of hypnotic attraction in that field is that a single physical law named the Coulomb's law should be able to account for all of the complexity of the material world or nearly all of the complexity of the material world. And of course as we all know since Newton's days the many body problem is a hard one in classical physics and it's even harder in quantum mechanics and when we talk about first principle wave function approaches we approach that typically in two stages and first solving the mean field Hartree-Fock equations that give about 99.8% of the correct energy and introducing the idea of each electron moving in the average field of the other electron and the nuclei and what's missing from that is just 0.2% of the total energy it's frustrating that 99.8% isn't good enough but basically the last 80 years of molecular quantum chemistry has been an uphill battle against the missing 0.2% of the energy and that is so-called dynamic electron correlation basically the instantaneous interaction between electrons when they bump into each other they come in two flavors the same spin correlation or Fermi correlation and the opposite spin correlation namely the Coulomb correlation and the Fermi correlation is relatively easy because part of it is in the Hartree-Fock and what's really hard is to treat the Coulomb correlation correctly. And how to do that and how to do that without introducing screening functions or u-parameters and all of these things that is the subject of Appianichal quantum chemistry and what has been found to be the most successful method here originated in nuclear physics where it is less successful than in chemistry and that is a couple cluster and that's where the wave function is written as an exponential of an operator T acting on the Hartree-Fock reference wave function and the operator T comes in terms of excitation classes and these excitations are promoting 1, 2, 3, 4 particles at a time from occupied Hartree-Fock orbitals into virtual orbitals and it is very fortunate by construction it is size consistent at any level of truncation of the cluster operator and in chemistry we are very lucky that we can essentially truncate the cluster excitation operator after the second or most the third term. Now if you expand the exponential of course then you get the linear terms here in those operators and then you get products of these excitation operators and they describe disconnected excitations meaning statistically uncorrelated events in electron correlation. The couple cluster calculation method is not variational but it is solved by a projection technique that leads to non-linear equation set that is not hard to solve and contains up to the fourth power of the excitation amplitudes and it is a gold standard method where CCSD parenthesis T where parenthesis T accounts in a perturbative way for the triple excitations and that has been tested at Libertum in molecular quantum chemistry and has been found to be a really very accurate method and if you capitalize on couple cluster theory you can go crazy accurate in these calculations. This is calculation a method, a compound method of my colleague Jan Martin and it is based on couple cluster theory and he shows in that was more than 10 years ago that relative to the most accurate thermochemical data available, gas phase thermochemical data available, he reaches an accuracy of 0.1 kilocalories per mole and this is an absolute accuracy. There is no rolling dice here, there is no fitting there, no parametres, this is just simply natural constants and the Schrödinger equation and this is what couple cluster theory then gives you, it gives you a systematic way to really solve the many particle Schrödinger equation to an accuracy of about 0.1 ppm parts per million and that is amazing. For very small system you can go even more accurate but like couple cluster theory it is about really solving the Schrödinger equation to that accuracy with no strings attached. Now what's wrong of course about couple cluster theory and you all know that is that it scales very unfavorably with system size namely CCSD parenthesis t scales as n to the seventh meaning if you want to treat a system that's twice as large you have to invest 128 times the computational resource in terms of CPU time, disk and memory and that of course many people, I'm very surprised always how many people give this answer to that problem. Computers, computers, computers and more computers but with an n power seven scaling this in my opinion clearly is a losing proposition and supercomputers don't solve the problem but instead I always felt very strongly that what one should do is to invent intelligent approximations that like bring down the computational effort so that these calculations become feasible and it is surprisingly hard to do that without spoiling the accuracy of the parent method so there have been many many many many approximations to the couple cluster equations but many of them were of a kind that they introduced errors that were far too large to be tolerable and then couple cluster theory is lost. So essentially there are three things to be exploited here. The first thing to be exploited is sparsity and in the self-consistent field there is sparsity and by Kuhn's conjecture the density matrix is falling off exponentially however very slowly stop and in the correlation energy there is a lot of sparsity and so here you look at pair correlation energy so these are increments of the correlation energy brought in by pairs of electrons and you can always write the exact correlation energy as a sum of pair correlation energies and they fall off extremely quickly with distance so after about two bonds like the energy contribution is zero then there is a wonder valve tail and then and then you forget it so there is very quickly a linear scaling number of significant electron pairs that contribute to the correlation energy and that is of course the basis for local correlation theory and that alone is not enough however and that is where we come in that the next thing you need to do is to compress data unfortunately I don't have time to go into much detail but rather the idea is rather than to operate on large matrices that are densely filled with small numbers you invent a transformation that gives you a small block of the matrix with large numbers that is densely filled and the rest is zero and then you truncate so it's basically kind of G-zip operation on the quantum chemical information content and these are the three principles that we have utilized and we have invented a method that's so called DLP and O CCSD parenthesis T and the DLP and O stands for domain-based local pair natural orbital theory and if I would explain that to you the entire talk would be about that but I want to go to the applications and what it gives you is linear scaling with respect to system size so that would be the canonical couple classroom method that is the system size here is the number of atoms and that is the computational effort of DLP and O CCSD parenthesis scales linearly with system size and with a small pre-factor and so that means instead of being able to treat 10 atoms you're able to treat hundreds of atoms with that method and it is now probably the most accurate method that you can apply routinely to molecules and we have worked on this with an entire group for about 10 years this was the first paper and since then the citations here are exponentially rising and it's on a good way to become one of the really substantially used quantum chemical methods in computational chemistry and it's easy to use it's black box just in the same way that DFT is oops sorry you can treat ginormous molecules with that that was from 2013 was the first time an entire protein has been treated with couple cluster theory so that was an all electron CCSD parenthesis T level calculation on an entire protein we didn't really learn anything from it other than that we were able to finish the calculation but it shows that that these calculations can be done that had been 640 atoms and 12,000 basis functions that was the first calculation on a molecule over a thousand atoms and the last thing we did last year was a big drug that contained 22,000 basis functions and 2,400 atoms so basically the curse of the bad scaling has definitively been overcome with that development and if you subject that now to the standard quantum chemistry test set so in quantum chemistry the culture is that you have a laboratory test set containing like hundreds or thousands of data points of high accuracy thermo chemical or other data that people run their methods through in order to get error statistics and if you if you see how how we're doing that so DLP and all CCSD T in these tests do with an average error of about 1 k cal per mole and so that is chemical accuracy and this is not by chance this is by construction and all DFT and these are don't rule us own test set so right I'm not cheating then is these are don't rule us on test set and it outperforms now how can we do solids and surfaces with that of course the proper way to do that would be to go to full periodic implementation of that and that is scary then as I've witnessed I've I've seen I've observed people doing couple cluster theory on solids and it scares me and and so what we're doing is I think the pedestrian way we treat them the retreat the solid or the surface just like a large molecule and since we're able to do a few hundred atoms we can go to very large embedded cluster models so what we do then is to take the solid or surface and then we cut out a quantum region and that quantum region can be pretty large it can be like a few hundred atoms then we kept that with capping ECPs it's all standard technology and then we embedded in the field of a couple of tens of thousands of point charges and so basically we it's very similar to doing a calculator QMM calculation on an enzyme so basically that is the way we do it now of course you tell me that such an embedded cluster is not a solid and I understand that and and I know that there are limitations but there are things you can do with it and in order to convince ourselves that we're not doing nonsense what we typically do is the following we do periodic DFT calculation on the system and then we vary the cluster size and we do we use the same functional as in the periodic DFT calculation and then we observe that the cluster embedded cluster results converge towards the periodic DFT results using the same functional right and if that is the case and typically it is a case in the overwhelming majority of cases that we studied we really were able to converge the cluster calculation towards the tube periodic result at the DFT level and then we feel entitled to use that converged cluster and apply couple clusters theory to it and the first study we have done there is a couple of years ago together with colleagues from the TUM Munich from cast and Reuter and we have studied small molecule binding to TI02 surfaces and my colleague Robert Schlügel tells me that the experimental data on these systems isn't very reliable but it's the only thing that we found and so it's it's what we what we connect to and so there is data for water for methanol for CO2 for ammonia and for and for methane and for all of these the binding energies cup calculated with the DLP and OCC STT is within 1 k cal of the experiment so that is the best comparison we can offer and the same is obviously not true for DFT that is varying all over the place here for example here in the water molecule so that is the experimental result here is the DLP and OCC STT and then depending on the functional dispersion corrected or not you can get all kinds of results from 10 k cal error to relatively close here that would be be to peel up a double hybrid functional that is not really cheaper than the DLP and OCC STT so so I guess PB0 D3 would be more something that that is known to that community and that has an error of about 4 k cal or so so it's it's it's quite significant for the case of the CO2 adduct I think it's it's well known that DFT always wants the tilted conformation to be lost in energy but the experiment shows that the parallel conformation is lower than energy and that is also what the DLP and O gives you so it's it's in substantial agreement with experiment so going through a list of functional there were always a few functions that were relatively close to the DLP and OCC STT for one system but then not for the next or second next system so there was not one functional that uniformly performed good now one nice thing about the couple cluster energy that that I cannot get from the DFT is I can understand it I can break it down in digestible chunks and one thing that we have come up with here so-called local energy decomposition and the local energy decomposition what that gives you is say you have an interaction between two two systems whether that's a solid as surface or an enzyme and a risk and an effector or a drug it doesn't matter and so you have these contact points between these two interacting systems and now the total interaction energy is then our total binding energy is then just the sum of the interaction energy as these contact points and the local energy decomposition allows you at each of these points to decompose it into electrostatic contributions dispersion energy contributions and exchange contributions and that is very very powerful we've been using it in molecular chemistry all the time and in terms of the surfaces you can see that and that is certainly not surprising if you bind water to the TIO two surface then the binding is predominantly electrostatic and if you bind methane to the TIO two surface the binding is predominantly dispersion controlled and quite typically DFT does relatively well if the binding energy is is electrostatic and it varies all over the map if it's dispersion even if you include the grimmer dispersion correction then then you see here for the dispersion like the results are very variable in electrostatics is better but also you have some really bad results for example here with PBE so that is the story on on binding energies and just to give you an idea of course you pay for it it's not for free on one point of the largest cluster we've been treating the PBE calculation takes 30 minutes the PBE zero calculation takes five hours the double hybrid calculation takes 12 hours and the DLP and O calculation takes four days it is more expensive there is no doubt about it but it's still efficient enough to do it in production mode you just wait a bit longer but you're rewarded with a systematically accurate result now we've been trying to extend that whole scheme to excited states and that was a was a very substantial struggle I think we've made quite some progress along the way and I want to show you here for the first time what we've very stand with respect to band gaps so the band gap is defined as the difference between the ionization potential and the electron affinity and an alternative definition is the first optical excitation energy and of course these things are related and for semiconductors the band gap and the optical band gap they are fairly similar now I can wrap my head around an excitation energy fairly well as a molecular chemist and and then many of the things you guys are talking about is a bit beyond me but of course we can approach it this way now here's one thing that always confused me and and that is very many times you see in that literature that people equate band gives with orbital energy differences right from the corn charm orbital energy differences and then they are happy if like they add hard to fork exchange and it gets larger but I don't really know what that means and look at this here this is interesting and I have the PBE functional that doesn't have hard to fork exchange and the orbital energy difference between the Homo and the Lumo is 2.06 electron volts and if I do a delta SCF calculation by moving an electron and reconverging I get practically the same and if I calculate to use TDDFT and calculate the first singlet and triplet and then take the average I also get practically the same so things are completely fine here and then it's absolutely okay to use these orbital energy differences as a measure for that for that excitation however as soon as you add hard to fork exchange that's no longer true here then the orbital energy difference is 3.5 electron volts and the delta SCF is totally different and it's and it's the same as the average between the singlet and the triplet excitation energy and that's okay because in the TDDFT response equation there is that term here the fractional hard to fork exchange CHF times that integral IAA which is not small five minutes fine and of course if you don't take that into account that is not a physical number here right this is a physical number this is a physical number the most physical numbers are singlet and triplet excitation energies so one really should look at the states and not at the orbitals and that's why I would never call an orbital state then the state is many particle object and orbitals one particle object and it's it's absolutely the same as true for for solid so if you look at things sulphide here or lithium chloride and that is the difference between the orbital excite the orbital energy difference and the excitation energy and it's several electron volts large and of course that is exactly the way it should be so now couple just a theory for excited states that is a complicated subject it's the equation of motion couple cluster in the interest of time I don't go into it and there are technical challenges that we needed to overcome and we ended up with a scheme that's a so-called similarity transformed equation of motion couple cluster that's an ingenious invention by Marcel Noyan and what Marcel has shown if you apply a second similarity transformation to the similarity transformed Hamiltonian and get the amplitudes from the separate equation of motion IP and EA problems you can eliminate the the singles doubles block of the transformed Hamiltonian and then you only have to solve a CI singles basically a particle whole dimension problem in order to get a fully correlated results and that is absolutely beautiful and it's a very accurate method that has an average error and excitation energy molecular test set of about 0.1 electron volts and we've been able to implement that in a near linear scaling fashion and so we now can apply that to a whole range of semiconductors here and so you see that is our range and this is a range of of band gaps that has been calculated for them and again we do the cluster thing and we see that in the majority of the cases our calculations really our DFT calculations are converging to the periodic result and the couple cluster calculations are converging to the experimental result and that is quite beautiful so if you look at it so here is our for the range of systems these are the Hartree-Fock meaning CI singles results they have a big error of more than one electron volts then we do the stem couple cluster that goes point two to point three and once we had the spin orbit coupling we go go to an error of below point two electron volts and compared to DFT it's it's way more accurate than DFT that depending on the functional the DGA functions have errors of more than one electron volt hybrid functionals 0.5 electron volts double hybrids are a bit better but the couple cluster is by far the most accurate so that is all I had to say I hope you found it a bit interesting and what I've talked about is it correlated ab initio quantum chemistry can now be applied to systems containing hundreds of atoms and that allows us to treat large cluster systems and the results of these couple cluster calculations so far I think have been quite encouraging and they do outperform DFT I'm aware that the cluster models do not solve all the problems in solid state and materials chemistry but I think there's a lot you can do with it thank you


Hey, good afternoon, good to be here and it is a lovely to see the fantastic interesting people in the Hyperledger Global Forum and today I'm taking this opportunity to talk about few use cases and applications that Krupsi has developed for some of our clients globally and also how our blockchain as a service is covering these use cases both at the time of deployment to managing the scaling. So I have few use cases and also I'm going to talk about our Krupsi blockchain as a service platform and probably around it may take about 20 to 20 minutes and towards the end if there are any questions I would like to take it up as well and feel free to just put your questions in the chat box it'll help me to understand what kind of clarifications are needed. So as you know blockchain has been evolving quite some time right from 2015 and enterprise great blockchains are you know becoming more mainstream nowadays. Our experience when we started in 2015 blockchain was a pretty much an unknown subject in the technology world when we were talking to enterprises but in 2016-2017 we did some very interesting projects so this one what we are talking about here is a liquid asset trading between banks it's a marketplace providing a lot of trust and also certain you know ability to make the assets available for all the participants to see and then buy and sell. So just to any use case unless it is backed by a significant business case it's going to be you know a dead use case all of us we have seen there are many POCs that did not take off because of the underlying business case was not strong enough in this case it's about 3.1 trillion market size so if you see here there are four major participant groups there are banks who are selling assets there are banks who are buying the assets there are importers and exporters who are you know handling the underlying business transaction so these business transactions are you know spins off an asset an instrument that originating bank they are holding it is called a liquid asset because the life of the asset is you know probably around 30 to 120 days it's not long term but within the time the bank who you know bought you know originated asset for liquidity purpose they may have to sell this to another bank who is looking for such assets with high liquidity so now across the globe if you are talking about 3.1 trillion there are millions of transactions happening so it's tough for any banks to understand where these assets are without a proper platform and it is probably higher too it was dominated by a lot of intermediaries so that's where this trade asset is the company's name on the right hand side top you will see this is Dubai based bankers they wanted to put up this platform in 2017 we started right now there are about 60 plus banks are onboarded and there are transactions happening across and all the banks are comfortable in seeing the benefit accruing to them and at a peak we had about 15 nodes deployed across the globe and now the number of nodes are less a trade asset side but there are nodes like selling banks and buying banks they can always opt for a node and connect to the system so this is one now use case that we did in 2017 and then right after that in 2019 2018 we did the finance against remittance platform this is again with a very strong business case supporting because if you see typically there are migrant labourers from different locations their corridors and they work in a normal scenario if you are working in our own country probably we have a choice to go to the bank of formal lending institution to get loan for various things at home it could be improvement at home or buying assets education multiple things but in this scenario the migrant labourer he's working in different country so the banks in his native country it's very difficult for them to understand what is the his income capability and what is the his affordability and all those stuff and at the same time the local regulation prohibit the banking regulation prohibits to give money without all these information so it is supported by united nations or there is a startup in in India and Dubai they wanted to set up this platform facilitating the migrant labourers coming through the forex agencies through whom they are remitting money back to their native country and the lenders in native country connecting them and putting a network so that the there is a visibility to the migrant labourers ability to pay and also the lenders can extend load to the beneficiaries that is migrant labourer's relatives so this one was done in a corridor between Nepal and Dubai and again this is one of the united nation SDG program about the financial inclusion for the certain people of certain levels of economic levels so this is one project that is you know we are we are planning to expand this the client is planning to expand this to multiple corridors just before pandemic this went live and post pandemic they are going to take it to multiple regions like Africa and other parts of UAE and Middle East connecting to Philippines, India and other countries as well so this is really solving certain critical problems and we hope to see this network expanding to multiple X levels in the next couple of years time and then again another project this we did in 2017 as well this is a micro lending project micro lending typically you know it's not a big size a set because average ticket size could be maybe thousand dollars or 1200 dollars here you know there are multiple participants and the time sensitive you know because if you see typical micro lending it takes about two to three weeks but after sitting it up or this platform in high quality fabric now it is taking maybe couple of days or less than that that means the borrowers when they need the money they were able to get the money and because there is no they are going through the formal lending or a formal lending institution process the cost of interest or a cost of finance is extremely low again when you talk about the micro lending this is for the people that are economic level where their affordability is very very less so that interest component and the time time component is very very important and also now there are multiple participants in the system because this being a micro lending at a rural level there are agents who interact with these borrowers and once they interact they connect to the system they feed in the information and we use external APIs for getting the credit score and background check everything now the information is available in the system for lenders to decide what how much and you know what interest rate that they have to provide for this loan and then the borrowers can access the loan immediately and on top of that insurance companies comes in and they also make sure that the borrowers are certain in a rural areas they are enjoying the insurance benefit as well so this is another use case we did in again 2017 and this one was in 2020 a use case where there is a supply chain platform for mining industry it is set up by a company called Mine Hub and the mining industry is a very very unique because it is in bulk and it takes a lot of time and the quality of the output is also a very important factor and that are certain ethical side of mining has to be maintained and all these things should be visible to the participant whether it is a bank or an insurance or a buyer or a logistics company everybody should know about all these aspects and the supply chain in terms of finance in terms of compliance in terms of the operational side all these three layers very very very critical and hitherto they were managing this in a very simple standalone system but there are a lot of delays and disputes and reconcilations and other challenges so this we this went into production in November and a lot of large-scale mining companies have already come on board and we are seeing this ecosystem also growing rapidly right after this lockdown is released we are already seeing a lot of traction to this mine hub ecosystem so next one is a very recent one it's in POC state pilot state again the business case is very attractive because if you see the education or student loan that's somewhere you know it requires a lot of liquidity because it's just within the hands of few players who are continuously lending to students through universities and the size of the education loan is kind of a snowballing because it's a average time it takes for a percent to complete his education so throughout the next you know for example five or six years the loan has to be continuously given to him so it's snowballing right so because of that the liquidity becomes a big challenge because if there is one institution lender if he's giving loan taking this to the secondary market whose of bigger than the lender or the equal size it's always tough because they have to you know deal with the wholesale the size of the loan but what the client who's you know a CFO of a university in the US they wanted to put this because they understood the liquidity and also the risk related disability challenges in the student loan portfolio and then for them just we have deployed a pilot now they're running the pilot where that thousands of loans are being put into the system it creates a lot of liquidity for example a high net worth individual with certain you know SCC criteria they can come and then participate now the the originator need not sell this loan to one single party they can sell this to probably 30 40 50 people who are interested to you know come and participate in this system now they can for example if a if a lender if I'm holding a hundred million dollar worth of portfolio no probably I can sell it to 70 people with you know average maybe 150,000 dollars you know or 1.5 million whatever it comes to so this way the the liquidity becomes of you know much more than the the current scenario and also the information relating to the student and their education and their status is also continuously available in the system so when these things are available now probably the risk visibility is very high because it's not like I'm giving the loan I don't know about the student now all these things are made available in the in the HLF ecosystem at the same time the no compromise relating to this the data and the confidentiality are also you know extremely critical though the we designed the system in such a way that without compromising the security without compromising the confidentiality and the data privacy the lenders and investors they are able to transact the loans and they can also see the risk coercion of the particular asset so that's what this education load project is about then comes up you know all these projects if you see you know it took average about three to maximum four months for us to put a production you know a production grade system in you know fully deployed on in any cloud you know it's clouded domestic blockchain as a service platform we have and it's also domain agnostic now you have seen supply chain and a banking and a microlending and we have done you know a retail application we have done multiple applications across multiple domains so blockchain's service platform was a backbone and that drives all these programs so why do we need a blockchain as a service platform in the first place if you see the blockchain adoption in the initial stages we are going through a lot of challenges you know starting from availability of talent pool because a person who's coming in and then trying to build a system for a for an enterprise he should know about cryptography he should know about blockchain how it is working he should know the full stack development capabilities and he should know the you know sudden you know legal aspects of it there are multiple challenges so it's not easy to get at that you know set of talent with all these experiences and capability and then continues evolving because if you see hyper ledger started from dot six we're buying two dot x now so it's it's kind of you know to that to that extent it's dynamic you know we are seeing a lot of improvements a lot of upgrades happening so that is also certain you know the technology challenge because if you are in one dot four if you have to move to two dot two you need to understand that the dynamics of the the protocol upgrades and advancement and then again the any you know most of the projects that we have done it's all connecting to certain put another technology as well it could be iot it could be ai it could be ml so if there are ancillary technologies maybe it is development related or it is also giving some value added services for the use case so those things are also very very critical and important and the conceptual understanding of blockchain by itself is a big challenge because you know there were situations where blockchain technology was put as a force fit for a use case you know maybe that's not a the best case because you know ultimately the ROI will go for a task and the enterprises will will look at like okay why am I running this program and the partners are not coming on board so there are other challenges always and the business value has to be clearly identified only then conceptually you know the blockchain will make sense for the use case so that's also another challenge challenge that enterprises are going through and then blockchain is not an IT topic for an enterprise it's a service design for example if you're talking about a trades and track program or if you're talking with a sustainability program so you have to you have to talk about the ecosystem and there are certain compliances that you may have to think about there are certain partner onboarding processes you may have to think about i think it's not just an IT topic and taking all these challenges into consideration we build this blockchain as a service platform which is almost like you know you take each other you you decide that this is a use case you don't have to do anything else the corporate blockchain as a service platform helps right from deploy development deployment management and scale all through it is a UI UI driven uh it's a GUI driven so you don't have to worry about going to the console and then uh patching in code and understanding goulang understanding uh hyperliterals smart contract how it is working how the crypto side of the identity working probably all those things are not acquired so we have done 50 plus POS is so far in this platform 10 plus of them are in production rate already so when you when you see the stack you know it is you know we have created multiple layers starting from bottom if you see it's a you know the smart contract layer where anything relating to the data i think we are managing in that uh that layer which is a blockchain node and peer layer and then comes your middle back a lot of communication related boxes you are seeing all these things are included in your blockchain as a service platform and we also have a conceptual data lake because we make sure that the reporting and query is happening directly from the data lake we meaningfully take the information from the block into the data lake so that the the business uh information that anybody wants to get from the blockchain network it is easy for them to get from the data lake rather than understanding or coming into the block and trying to take the data and you know trying to understand the logic behind the data that's what the data lake does and then we have got the deployment side you know anything relating to any cloud irrespective of the cloud we have got all the services that is available including the health check and network management and your cloud resource management all the artifacts whatever is required connecting to the cloud infrastructure is done in our deployment tool in fact we have also deployed an on template for hlf 2.2 in azure now it's free of cost any enterprise wants to deploy they can use that on template and then you boom you have the 2.2 within about you know a few clicks so that's what we have done and on top is an excellent part you know a feature called process modeling so if you know a full sheet of what exactly you are use case who the participants are what the data set is what the business rule probably you can come and just map what you want then your application is ready with certain ui it's not a you know all that uh exciting ui but the very basic ui for you to test the application and then move it iteratively iteratively to the production grid now it generates api it generates ui it generates chain code and also it generates a data lake now all these things generated then you can have a look at your application and then improvise it as you want to move towards production more partners coming in they may have their own requirements you can modify it it's not a because it's just a you know you may have to change the data structure and you may have to change it and rules whatever you want to change you don't have to get into deeper coding it's a low code environment probably about 95 percent you don't have to code still you may have to code about four to five percent it's just a scripting if the business rule is going to be so complicated we have seen in any use case the business rule complication is by default so that's why we are saying about four to five percent of coding is essential so with that process modeling it is easy for you to you know number one deploy and then do your process modeling your application is ready now your middleware and other blockchain uh pure management systems what you are saying on the bottom two layers with that you'll be able to manage and then scale your application and you want to scale your application more members coming in more organization coming in new channels you want to set up more peers you want to set up all those things you can do just through a GUI driven uh you know screens and we also provide managed services even enterprise ones just to take care of the entire services we will take that responsibility with our own eyeball monitoring your nodes and uh whenever whatever services are required on the reactive mode we will do those things as well so end to end any life cycle of a hyper ledger program Crip core bus it does without much need for manual and time consuming effort and it is since it is time-tested it's uh you know probably uh the close to zero uh error I would say so that this is about the course stack when we put that into a customer application the architecture works on the left hand side is our uh Crip core and always there is a question about who wants IP how it was and all those stuff we have given a very clear uh demarcation of what to code on the right hand side what the box you are talking about is a client application tomorrow if they don't want to code they want to run their own services they can take this uh their their sort of you know the application and they can take it put it on any bars or any services that they may develop on that this is a kind of a flexible you know approach that we have given I think with that all these 50 plus projects in uh you know some of them are in production like 10 plus are in production and we are also seeing a lot of demand um after uh certain products in the market were taken out and after certain services were taken out I think there are a lot of demand for uh the boss services that Cripsy is providing so that's all I have today this is uh you know about Cripsy we are serial entrepreneurs we come from a very strong uh uh cryptography background and this is uh all of us are working to that from you know from 2006 and from 2006 Cripsy is in existence prior to that we are working in our other startup in our you know winters and we are present across the globe our corporate old who is in the US we have an operating entity in Seattle and in Netherlands the Hague and in Bangalore we have a strong team of research and developers sitting in Bangalore that's our background I'm is I'm Ravi Chaganathan and you know I have about 30 plus years of business experience globally I was in our corporate world and I started my first venture in 2008 that is relating to the trust authority system in India called E-Mudra then I set up a tax filing portal the first tax filing authority here in India and then we started blockchain in 2016 so feel free if you have any questions I'm happy to take the questions yeah there is a question from Karthik is asking this demand for HLF or for any other protocol we the blockchain as a service layer what we have it works only for it's it works only for HLF we don't support any other protocols but we work in Hedera protocol as well that is more to do with the public if you have any close-loop enterprise system driving use case in hyper ledger and if that is a need for it's you know extending this information to a public network then we have what a type to Hedera and Hedera being cost effective and also times in effective and green efficient we use the Hedera and that information are available through the consensus service of Hedera that's available in a public mode. Hi Ravi there's also a question from Yaku a little bit more about life financial services applications not the POC just things that are actually live and happening which which application sorry live financial services live financial services yeah I think the the the one I was talking about the bank marketplace where illiquid assets are being traded it's live it's a production there are 60 plus banks have onboarded what they do is there there are illiquid assets for example if I'm talking about I have lend for my client it could be a trade finance asset and this asset I'm holding and if I want to sell to another bank now it's very difficult for me to understand which bank is interested and because it's across the globe I may be sitting in Bangladesh Dhaka and there may be a buying bank sitting in London if they want to buy they don't know me I don't know them so this is a very typical problem and also even if they know they may not be able to put some trust on me and my asset so what we have is we have this platform setup this platform is a completely smart contract driven and also it is a you know it gives a lot of visibility to the asset and now the bank in London they know that there is an asset available and also they know the complete trace and track of the asset because that's how it is captured now they can bid for the asset and then they can buy and everybody knows this asset moves to move to another bank and that bank when they want to sell to another bank for example now the trace and track of the asset is available until the bank who's holding that asset so that is how that was architected so that's one live use case it's in production that's great thank you we still have two minutes so I would go through the follow-up questions from Katharik which is what about application upgrades say Hyperledger Fabric moves from 2.x to 3 or be seamless or will the application sitting on top be impacted yeah being a member of Hyperledger Fabric and contributors of Hyperledger Fabric we closely work with Hyperledger and community we understand the future versions and what functions the future which you know versions are bringing in for example 2.2 when it came alongside within a week from 2.2 announcement our trip core was ready for 2.2 because we closely worked with the Hyperledger community to understand the future versions and we upgrade our Hyperledger our trip core was to make sure that the upgraded versions are available as quick as possible so we support we started supporting dot 6 and we have matured up to 2.x now so we are already I think 2.3 dot something I think that's a version which we are currently supporting last one last question from Yakubis what is the pricing model for Cryptsy yeah we have a couple of there are three layers number one if you want application development consulting services that comes in the completely consulting services mode we have a red card and ours is a time and cost sensitive time and effort sensitive so at a very least possible time we will be able to give you an application the second one is you have a team of Hyperledger or a blockchain specialist or a technical specialist you can take our boss on a licensed basis it's a we charge either per transaction or a periodical you know annual license you can take that and then you can run your managed services or if you want us to do the managed services we do end to end that is that goes by per node per hour basis and also we have a charges at our subscription they may have to pay for using our blockchain as a service layer this on top of that we add the underlying infrastructure cost directly whatever cloud you want to have it's back to back we'll take that cost and any eyeball is required if you want some support from our our technical team that is also will be charged on top of that on an hourly basis or a daily basis wonderful thank you well I guess Jakob you will have to follow up with Ravi separately because we ran out of time we're actually one minute over so thank you everyone for participating go ahead and catch the last session of this blog and then I'll see you in afternoon thank you Jakob I we support Hedera blockchain that I have already told please let us get back connect back and then see how we can work together thank you appreciate it bye bye


कुवेंपू तो इवारे कलबुर्गी मैं पादर दो और प्रनिच्छन्त क्रिटिक्स अफ जागाहर्लानेरु, अफ आद्राणार्दी, अफ राजीव्गार्दी, बत लिए में से बत रान्णोफ तैंब, अव वो विश्खल अग्टाट, वेख्लों देख्च्च्च्च्च मeme saying thatrayone who criticize tag India will die in drugs debt. बेँलोर conjunctionpably पट् ממקकार गारी लंकेष की बवो ब शिन्काँट रो costingत है. पंत्तर कार कही लंकेच ठीते कोगेagh Apa vita pa этихon ? बेक्लोर thanagalore matters the same. तो बयाभी पुछ cad 바 slogan kaupi pappu chitach Basic करनात की जाली मान पत्त्र कार गोरी लंकीश की भीतिराज रत्यल कर दीगDAY अगरकान मैं बाना हुट, नहीं सीश वारी बेशी कुई उन थोंसे आपने लोगी रहे है, भी सीश्गान मैं करनात की पहत्र भू मैं,enge raha main, अदियलाजकल कमित्मन्त अमोशनल कन्विक्ष्यन तुद खाजस ची एस पोज्ज वस सो रेडियेंद, सो रेडियेटिंग, सो ट्रन्स्परेंट। अदिक तुद गव्रीज मर्डव, विछ at the personal level is, you know, both shocking and tragic. But I do think it is, it goes beyond an attack on an individual, independent minded journalist. And it is actually an attack on freedom of expression and I think that is something which we all need to understand. One thing that she stood for about everything else was a rational outlook, questioning caste, questioning exclusion and believing that this country is the country of the questioner, the shravana. Pluralism and secularism is not a foreign construct, it is a construct deep into the soils of this country and nobody, no majoritarian fascist can take that away. And she used to say, if truth is biased, journalism should also be biased. If the truth is one-sided, it should take sides. She never believed in a kind of so-called objective, non-partisan kind of journalism. It cannot exist like that, it will take its time. So activism was blended into her kind of journalism. So this is gauri actually. She was the voice for the voiceless. So that is what she stood for, I think. And though she has been silenced now, what I feel is after she has passed away, so many people are translating on their own and putting it into the social media. Now Diana publishers have come from Kerala to say that they have published in English and now Telugu, they are releasing it in Telugu, the book which was done by Chandan, got a good friend of hers and a journalist as well, columnist as well. So people are being translated into so many languages. I think many-many gauris will be born because of this. We have lost many to such cowards' bullets. But all that have gone, including gauri, have been brave shining stars, spoken truth to power, gone against the wind, personally and politically. She stood apart. All of us have a lot to learn from her. Nothing else, the clarity, the grace, the conviction that exclusions and deprivals of all kinds meet to unite and we can't afford to be sectarian under our individual flags. We must dedicate gauri's death to a renewal of a cohesive resistance. We cannot let her go in vain. They killed gauri because she was alive.


For the last 29 days, I have been floating along in the breeze of consumerism. Just eating and shopping and consuming, like so many of us are used to. The catch?  So, I'm up to about 68 pounds of trash, and I'm really starting to feel the weight and the burden of consumerism. And you can really see it.


T F N N headline news update Good afternoon everybody. I'm Tommy O'Brien coming alive from T F N N headquarters in St. Petersburg, Florida 1 p.m. Eastern time on Thursday three hours left to go on the trading day and we got markets pretty close to flat territory after volatility in both directions S&P's up one point trading at 2812 Nasdaq currently up 13 points treating it 276.56 and the Dow up 20 points during a 25,645 quite a day for the dollar index up 482 ticks trading at 96 765 gold contract off more than $21 trading at 1295 40 notes and bonds slightly lower price and higher yield 10-year note negative 7 ticks 124 15 30-year bond negative 2 ticks trading at 150 on the dot. We'll start things off Let's jump over to the futures markets and we'll start it off with the S&P's So quite a roller coaster as we just stated markets pretty close to flat slightly in the positive across the board But the S&P is at one point. We're up there at 2823. You trade all the way down to 2802 so you're talking about 21 S&P points from just 10 30 this morning to just after noon and from there We're up a bit 2812 in the June S&P contract Nasdaq 100 much the same highs this morning just after 10 a.m. Of 73 71 We trade all the way down to 7301 So you're talking about 70 points almost a full percent in the Nasdaq 100 But from there we're right back in the middle of the trading range for the day trading at 7341 and climbing higher as we speak Dow 30 much the same as well currently trading 25,666 right in the middle of that volatility for the day Gold contract trading lower from most of the session Check out that run even since about 2 a.m. This morning training at 1317 and from there We just made lows within the last half hour 12 93 37 the price of gold Natural gas we got EIA volatility this morning at 10 30. We're trading about 272 We're within about a half a penny from that level those levels EIA inventories seeing a decrease of about 36 billion cubic feet pretty much in line with estimates and crude oil back above $59 you have crude trading at 5903 Terms of what else you have happening in the market in terms of the dollar Let's check it out because quite a day for the dollar There we go. We'll pull it up Come on Come on. There we go Up one more IGPO keep up with me Bloomberg There's your acceleration. We reach a high of above 97 8 trading at 96 8 96 7 15 Stay tuned folks Steve Rhodes coming up right now with the trader's edge. Have a great thursday


Everyone shiver 1,000 here today.  I'm just using my pocket knife here Now this one has got hex heads in it Which they're 930 seconds, but they originally should have if yours has never been out probably they've got a Phillips head sometimes they've got Torx But I know these shivers they usually have They usually have Phillips head on them and I got one don't want to come out here. All right.  All right now on the back here.  I know the lighting is bad, but we're outside So there's not a lot we can do about it. There's your bulb There's your side marker light. This thing should just turn a quarter turn counterclockwise And pull it out and there's your bulb. Okay, so Pull this out. Check it make sure because these do get really hot Check in there make sure it's not, you know, anything's melted or anything like that Because this is almost a 12 year old vehicle. This is this I think it's the same on 2009 to 2014 ish so I mean if you got this style tail light you'll know but You know, this is the basics. They're all pretty much the same There's no right or wrong way to put this bulb in you just Stick it in like that when you go to put it back in Just reverse it. It's going to go in you just turn it till it pops in and then A quarter turn clockwise now you're done. Now let's have monkey go and put her foot on the brake pedal And we'll see We'll see if it comes on And we'll see if it comes on Your foot's on the brake pedal well so much for one cut Okay, she just went got the keys so There it is All right, let off left turn signal Okay, there you go. That was our issue and you'll see these things they get there's two filaments in there You can see that one's real black so it's blown. I can actually see it right there All right, so there you go now. Let's put this back in There's a little Right there. That's going to go into this hole right back here Now I got these wires yours may not have it. I got these on here because the trailer lights So we're just going to put this back in here and line that little tab up with that hole Push it in then we're going to put our screws back in and you're done real simple But these are all pretty much the same just look for hidden screws These ones are pretty easy because it's only got two Well now it's only got one Okay, let's wiggle them around they'll get started They don't have to be super tight guys. Just give it a little bit of just turn like that That's all there is to that Then put your little caps And there there's a little tab here And a little like a little notch there. That's how you're going to want them to go Just like that Nothing to it, but to do it Takes about 30 seconds Maybe a little longer All right guys, so there you go. That's uh That's on a a traverse is about the same or well. This is a traverse equinox about the same thing So you know you got something like this but all these plastic tail lights, you know if you got to remove them You know, that's the basics just look for screws take them out Yours may be a different bulb now this one if you do have one of these traverses This one is the 7443 There's the number right there. That's what your traverse will take And we got an extra one because the other side will probably blow so All right guys. Thanks for watching appreciate it. J. Bertha met the man alleged and gone for now Stay tuned for more videos guys. We'll see you soon. Bye. Bye


Hello and welcome back to The Craft Box. My name is Sprint and today we're an episode number 103 of the Wizard101 Death Walkthrough Last Episode. If you haven't checked it already, we continued on in Zemunda and we found out that there was a traitor. But yeah, today we're talking to the Queen. Hello, young wizard. We need your help. I have heard of you, young wizard. I hope we can help each other. Tell me, the king's magician. Sitsi's snake tail. Said he was also looking for a herd of wizards for nefarious purposes, no doubt. Sitsi has somehow broken the spirit of the great Shaka Zebu. Here, use this key to enter the palace. You'll find Shaka in the King's Court. Perhaps your magic can cure him. Okay. Use this key to enter the palace. You will find Shaka Zebu in the King's Court. Hello, wizard! As you can see, one of the key... I cut... you'll find the longdreamer shamans in the Zemunda outskirts. That one. Once you retrieve them, I'll teach you how to read the Star Obelisk. Okay. Yeah, let's not do that now. We are going to enter here. Let's go into the King's Court and see what there's to see in there. Mm-hmm. And we will see who we need to defeat now. It is a... Okay, interesting. Shaka Zebu. Guys, reveal that he is under a dark spell. You sense a dire link to this corrupted Baobab tree. Which looks like it is being strangled by that vine. Mm, oh no. That's not good. No, not good. Not very good yet. Not very good. Well, let us find out what she thinks the problem is. Doop-doop-doop-doop-doop. Hello there. Yes, our King is under an evil shadow. News of Shaka Zebu's condition has blown to the city like a foul wind. Some of the younger hot-headed stallions are using it as an excuse to riot. They threaten to tear the city down from inside. I need you to show them how foolish they are and how little they know. It is a time to stand strong, not run wild. Please defeat the rioting impirators so that we have time to find a way to heal Shaka Zebu. Okay, I'll be back once I've defeated five of these. Okay, I am back. Just finished off defeating them. You reigned them in. Well done. While you were dealing with the upstart impirators, my daughter Mandisa was keeping an eye out for Zizi. She has found the magician. Quick, go and talk to Princess Mandisa Autumn Rain and find out what she saw. Then track Zizi down and bring him here. It is an honor to meet you. I saw Zizi skulking about the city. I trailed him to his hut. If you hurry, you can catch him there. Okay, let us head on over to Zizi's hut. Or the magician hut, whatever it's called. The door was locked earlier, but it's open now. Okay then, let's charge on in here then. And get him. Five, four, three, two, one. That's not the magician. Uh-oh, bamboo's all again. Okay, let us put two of you. Two of you. One of you. Two of you. One of you. Three of you and two of you. And that should be fine, hopefully. Well, if it isn't, that's unlucky because we got pulled on. So, we're going. We're going. Let's see. Well, we'll do this. Okay, Storm Lord off the bat. That is fun.  That's great. And Skeletal Pirate, okay then. Okay, okay, I see how it is. I see how it is, man. I see how it is. Let us try again. Unlucky. Yay, convert. Um, we also need a blade. You can't do anything too bad, so that's fine. Unless you have feebles, but I don't think you can. Also, I don't think he cheats, which is good. Um, didn't cheat coming, so who knows. Um, what else do we have? We don't need you again, because you definitely did already. Um, we'll do you. Wraith, hello. Okay, and, okay. And what do we got? We got a blade. We got a blade. We got blades. We got them blades, boys. Two blades. Three blades. Dun-dun-dun-dun-dun-dun. Unlucky. Kraken, unlucky. Resist, unlucky. 412, unlucky. Three blades. Spicy. Uh, what else do we have? We have finally have space to draw again. For a, not you. For you, yes. Four blades. Okay, you really want your health, eh? Wraith. Vampire. Kinda silly. Because you have like, you're not even dead yet. But that's fine. Four blades. Passing. What's this, another Kraken? Nope, a Fizzle, that's unlucky. Faint. Sure, why not. Let's do some other Kraken. Oh, okay. This could kill us. Okay, didn't kill us, but it could have. Uh, uh, uh, uh, uh, uh. Faint, faint. Kind of worried now. Um, that he's going to do something big. Another blade, five blades. Okay, I'm really worried now. We could die here. We could die here, man. And we still don't have a good hit. At least that's taken away. Um, hopefully doesn't do 600 damage. He's got lots of pubs, he could do 600. Um, yeah. Okay, five blades. And a hit. We have to hit. We have to hit. Because we're dead either way. We have to hit, we're dead. So we're just going to hit the boss and hope he doesn't kill us. Which he won. And the other guy, I don't think he can do anything. So that's what's good. Yeah, no, not quite kill. Okay, what are you doing? Okay, that's fine. We're getting health back. We need health. Need health. Three, four, five. Faint, you're definitely dead, boyo. Bye. Yup, bye. Yum. There we go, full health, yay. Now we have that. Okay, that's fine. We actually need a blade. So... Yeah, we will just use this one. Sure, why not? Need a little bit more substance. Because he's kind of got a bit of health. Um, just a bit. Look, now we get asked, here it goes. Okay, game. Okay, let's do that. And the prism should be good, even though he does have a... Even though he's got his fortify up. Should still be able to kill. In fact, we'll even go like that. Just so we definitely kill. And skip now. Unlucky. He did not even test to death. Kind of annoying. Just as well, we have other things left. Like a, um... A blade. And things and stuff. Yeah. This could be bad. This could be bad. Probably will be bad. Might have to reshuffle. Which I'm not against doing. Mainly because I've actually never used reshuffle on this character before. So it'll be a new experience, you know. How much health do you have? 900. Okay. Well, we're gonna try. See what happens. And if not, we will reshuffle and try again.  So that's always good. He says at nearly quarter of an hour. Done already. Um, okay. Let's see if this works. Okay, he's dead by. Yay, we did it. We did it. After defeating the bug, you see there's someone in the shadows. A student from Wizard City. Tied up. Whoa! That was it. Thitsy captured me right before I got to Zamunda. He snuck me in and said he was keeping me for his Dark Queen. Thitsy just left. He said he was going to the Tomb of the Zebra Kings. Sounds awful. Thanks for saving me. I'm outta here. Good. Three left. Okay. Um, monkey is here. Hello monkey. Monkey. There we go. Kind of a cheeky place for the monkey in a dungeon. You wouldn't expect that one. Or in a boss battle. Wouldn't expect that one. But that's where they did it. So let us head on over and talk to the Queen again. And find out what she wants us to do now. We might have to go on to the Tomb. I think we do have to go on to the Tomb from memory. Thitsy is going to the Tomb of the Zebra Kings. You must stop him. Luckily the Tomb of the Zebra Kings is guarded by powerful spells. There is no way Thitsy could get him. Go speak with the Tomb's guard, Temper True Stride. The two of you need to catch Thitsy before he causes more mischief. Okay. We don't want this quest just like before. And let us head on over to the King's Tomb. Which is over this way. Doop-a-doop-a-doop-a-doop-a-doop. Doop-a-doop-a-doop-a-doop. Oh, hello. Long dream is shaman. Okay then. Doop-a-doop-a-doop-a-doop. Doop-a-doop-a-doop-a-doop. Doop-a-doop-a-doop-a-doop. By the ancestors, please help. I'm caught in this infernal web. Praise your ancestors. The chief's magician Thitsy attacked me then went into the tomb. I never saw it coming. I can't even open the tomb. Thitsy used a magic powder he got from the long dreamer shamans. Defeat some shamans, then use the magic powder to make the braziers burn like a zebra stripes.  Explore the tomb to find out what Thitsy wants. Then tell Queen Autumn Rain what you discovered. Okay, I am back. Got them. We need to use the braziers now. The black one. And the white one. With a groan, the doors open, leading into a yawning darkness. This tomb must date back to when Baobab was young. Okay, I had to skip that because I didn't want to get pulled. Just as well, it was only one thing. So yeah, let us... Wizard, you trespassing days. Hello, I charge you with finding my grave goods. First, return to me the sword of the duelist taken by Jackal Bandit. Okay, let's not do that then. Let us head on in here. And see what we have to do. Five, four, three, two, one. Okay. Well, I'll be back. And just a sec. Once I've defeated these guys. Okay, just defeated them. Oh, there's more. My fearsome arachnid servants. Destroy this interloper. He's got a spider mask now. Okay. We get it, you're a man of many talents. Okay, jeez. I'll be back once I've defeated these. Okay, we have just defeated them. Apparently we're too late or something. I don't know what that means. I don't know what that's meant to mean. Because we're never too late. We always won. So, yeah, we don't take owls. Which is unfortunate for you.  Oh, that's cute. I have stolen the essence of Zonga Zebo. I am now as powerful as any zebra king. Now to steal Zamunda's greatest prize. You trespass in the halls of the Zebra kings of old. You treacherous jackal.   Kind of interesting. Yeah, let's do this. I'm suspecting a couple of tower shields. But you know what I don't really care? Let's just go for it. At least we don't have to have prisms. Which is fantastic. Prisms are really annoying sometimes. Okay, we're just getting all the blades that we don't like. But that's fine. Oh, hello. Hello there. Yeah. Phew, 444. Boop, boop, boop. Blade number one. Yeah, boy.  I didn't put feints in. Oh, well. We should be able to kill this one. Blade number two. Yeah, boy. Okay. And he's probably going to shield. And that's fine. Blade number three. Oh, he's stunning. Okay, that's cool as well. Blade number three does not exist yet. We will get that next round. Blade number three. Really, that stun was pretty useless. Like usually you would follow up with something, but you didn't see a bad. Blade number four. And after this one, one more for greatness. Boop. No. Okay, not too much damage. Blade four. Yay. And that's it. Blade four. Yay. And Blade five. Are you there? No, you're not. Okay, that's embarrassing. We have a pass then. Don't want to discard all my wand hits in case he shields. Oh, okay. Just trying to stun me. That's cool. I see how it is. Just give me a blade. Jeez. All I need is a blade. No. Okay, that did like nothing. And we still didn't get a blade. This is embarrassing. We're going to get an enchantment. Oh no, we got a blade. That's fantastic, finally. Okay, blade number five. Blade five. There we go. And we are going to hit with one of you. Okay, that's a lot. Oh, we fizzled. Okay, game. I see how it is. Stop fizzling, please. I need accuracy. Boom, boom, boom. Neum. Here we go. One, two, three, four, five. Let's see how much damage this does. Won't kill. No, not quite. Not quite a kill. We can follow up with a vampire. So that's fine. We're full health though, so that's what's good. Always good, man. Yeah, we can just... Yeah, we'll just do it, you know. Let's just do it. YOLO. And here we go. Neum. Yay. You're dead. You're dead. You're dead. You're dead. You're dead. 8-8-3. Okay, that took long. Didn't think it would do that much. I have lots of damage. I forget that. Okay, let us get the quagga blade. Okay. And let us go and go back and talk to the queen. And I'll be back when I'm there. Okay, I just activated the star school trainer here. Berserk and Mint. Nothing good. But yeah, we'll just finish off this quiz. There we go, smxp, yay. And this one here. Yay, level up. Okay, so next episode we will wrap up this and defeat the evil spirit. So yeah, thank you for watching. Remember to leave a like and subscribe and if you haven't already subscribed, press the little bell so you know exactly when I post another video. And remember, craft outside the box.


So thank you. Can you hear me? Yes? So first I would like to thank the organizers for setting up such a nice meeting. So my name is Martin Castell-Nouveau. I'm from France in Lyon and today I would like to present you some recent works that we performed in our group over the last two years and so they all deal about viral self-assembly and I will have two parts. One part will be more specialized on a single object, namely following the self-assembly of a single capsule and try to understand some specific features giving rise to specific shape of viruses. And in the second part I will try to speak about some collective effects, so how a pool of proteins will self-assemble and what is the dynamics associated to this. So as you after two days of workshop you you all know this kind of structures for icosahedral viruses so they are icosahedral because they have some set of different symmetries. You can observe for example in this in these reconstructions here that they range from different sizes from 20 nanometers to more than 60 nanometers and an idealized view of these structures will be this one which is an assembly of let's say triangles where you can identify very easily some hexamers where are six proteins back together and you can also identify some pentramers where you have only five proteins at specific locations. So I don't know if somebody explained it but roughly the t-numbers that are used to classify the icosahedral viruses are measuring basically the distance between two pentramers on a particular lattice okay the lattice of the hexagonal path but not all viruses have this shape some viruses have more irregular shaped and especially elongated shapes this is the case for example for some retro viruses like HIV here with this famous conical core shape RSV which is another retrovirus which has this funny coffin-like shape with something that looks flat here and kind of apex at the other side. This one is a bacteriophage but it looks like a icosahedron that has been stretched so it's just like elongated cylinder and this one among our cure virus is called a lemon-shaped virus which has this very weird shape and so basically if we try to understand what is the difference between the shaped in these viruses we are led to the following conclusions so indeed in all these structures either regular or irregular you can identify hexamers and pentramers and from topological rule if you have a surface that you want to close you must have at least 12 or maximum 12 net pentramers in the structure so for the regular one you would say that the the typical feature is that the pentramers have an equal distance between each other's right why here they are kind of face separated here for example you you have seven pentramers here you have five pentramers this is the same here and this one well this is not a virus this comes from carbon phases this is a double nano cone where you have three on top three at the bottom and six at the waist but you have a total of 12 pentramers but these pentramers are irregularly placed so the question I'm asking today is can we identify what is the property at the level of a single protein that give rise to this particular shape how a protein will know that it will end up into a icosahedron or into a elongated structure to do that we are trying to to understand the elasticity of these objects I'm making the link between the elasticity and the capsid shape and I have some specific discussion about HIV so this problem has been already attacked by numerical simulations in particular in some groups for example in group of boy as Andy and the simplest way to address this these questions of shape is to have this minimal model where in which in fact the building blocks are triangles that are deformable those triangles wants to share some edge to have some adhesion and you must be able to compute some elastic energy for your system and you try to see for example if the the minimization of elastic energy is able to to reproduce the shape you observe so this is not what I'm going to do today and I will try to to to provide some analytical arguments in order to understand the shape that you observe in such simulations but so basically with this model the elasticity will be composed of two parts basically you will have an in-plane stress in in-plane stretching or compression of the protein in their own plane and you will have an out-of-plane curvature as well which tells you about the bending the local bending of the surface so in the in the in the discrete model the bending arise with a potential a kind of quadratic potential around a preferred angle and this is an important parameter we introduce some preferred angle assuming that in fact the protein is by by itself if itself assembled with us some other proteins you want to have some local curvature okay but at the scale of two proteins this this is an angle between the two proteins and the other potential is just the stretching of the bones the stretching of the triangle edges and this just reflects the fact that maybe upon the assembly you will have some compression or stretching okay so given that you have some spontaneous curvature to your surface at the at the beginning of the self-assembly you expect to have some kind of isotropy growth so you will have a kind of sphere covered by triangles but if you do that with just triangles and preserving the the isotropy then you you you see that in fact the triangles that sit on the edge but starts to be compressed okay well I'm going to explain in a minute why but this is exactly the same case if you take a sphere and try to cover the sphere with a flat sheet if you want to to cover this the the sphere you will have to include some folds or wrinkles in the structure okay and this this this tells you that you have a too much too large amount of material to cover the sphere in fact okay so we can estimate we can estimate roughly the the cost due to this this this growth along the sphere if you take a disk for example and you try to put this disk on the top of the sphere following the sphere then the the rim here we have a reduced value and you can evaluate for the whole structure you can evaluate the cost of confining this disk onto the surface and you see that this is a strong scaling low because it goes as R to the power of 6 so it's a large value and the radius of the sphere comes with R to power of 4 so it means that at the very beginning of the the the growth there is a huge mechanical stress that is rising up due to the spontaneous erosion so you have to find ways to reduce this this stress this mechanical stress well you can find you can find some strategies to reduce this stress by looking at the equations describing the internal stress or the in-plane stress so this equation this is one of the equation one of the focal form of common equation it is related to the so the stress tensor which tells you the state of stress inside the thin shell you introduce some specific function here which measure which measure the stress and this this classical equation is written here this is one of the two focal form of common equations giving the the equilibrium solutions for the shape of plates for example and it has two source terms okay and these are very important in fact so this green source term is the defect density by defects we mean topological defects but if we if we try to understand this in terms of our discrete model it means that we have some panchambers so the topological defects from continue theory are just disclinations or panchambers inside the structure and the second term is the Gaussian curvature for the Gaussian curvature it's just the product of the two principle curvature of a surface that you can define at any point and you see that well if there were no such terms in fact the stress will be minimal okay so in a sense you by just writing this question you identify two strategies in order to relax the stress the first one is that well if you have Gaussian curvature then you have to induce defects in order to compensate so to have a minimal state of stress that's one strategy and that that will be the strategy called the defect inclusion or panchamber inclusion through the assembly again the other strategy is to have no defects and no Gaussian curvature but still you want to have some curvature but you can have such a curvature by taking a cylinder or cone for example we have vanishing Gaussian curvature and you want to end up with some cylinders cylinder that has been seen in simulations in a group of Royazandi for example simulations very similar to this the model I described before can we estimate the cost of defect inclusion and to see how is it better than just having this isotropic growth so in fact including a defects or panchamber in the solution amounts to perform such an operation here you have a network of hexagons and you will cut out a wedge of 60 degrees and then you try to glue the thing you try to glue the both parts if you do that if you stay flat well you expect to have to pay a strong stretching price right but if you go to 3d in fact very easily you are able to to form a cone in fact and so the different cost here so here if you stay flat you don't have the bending energy but you have the stretching which goes like the the area of the the disc you are considering now if you perform buckling and have a cone then you see that you just have a logarithmic growth which is much more affordable in terms of mechanical stress so pay attention this is a zero spontaneous curvature calculation that you can make for non-zero spontaneous curvature but it's more complicated so with one defect indeed we can reduce the state of stress but if you keep on going the growth you expect to have to maybe include more defects and we will come up to this point in a minute if you include more defects or more panchambers in fact you see that you will curve more and more your structure okay more precisely for example here you have one defect two three four five and why from a geometric argument is it favorable to have multiple defects in order to to to have a less a less amount of stress well recall that in fact by going from the disc to the sphere the rim was reduced the rim land was reduced but if you just include one defect you are performing such as thing you are reducing the rim land because you removed this part okay so you can compute the number the the length that you remove from the system in order to cover up the sphere okay by adding by adding more defects and so in fact this land for reduction is easier in order to follow the curvature of the sphere so for the other for the other possibility of a strategy to reduce the mechanical stress well just have to pay bending energy because here don't have any stretching if I take a flat sheet of paper I can roll it without any tearing stretching or compressing and you see that it goes like the the area of the other surface and you have also the radius of spontaneous curvature that that comes up so more or less what we have is that if we start from this if we start from this structure with isotropic growth on only hexagons if you are at high spontaneous curvature you would expect to have at first one pantamers but then you have a cascade of pantamers in your end up with an icosahedron and if you are on the other side that for the weak spontaneous curvature then you expect to have a cylinder that will growth indefinitely and you don't have to include any defects so that this is a problem for a virus because it needs to be closed we'll see we'll comment about that in a minute so more precisely for example you can compute for example in the high spontaneous curvature scheme you can compute for example the energy without any defects this is this blue curve and with the 12 defects this is this red curve and in between you see that there is a cascade that the more you add defects the better it is in order to follow the structure okay and you reach eventually icosahedral symmetry on the other side if you have a small curvature and you compare for example this is the energy with the 12 defects you compare with cylinders you see that depending on the radius of the cylinders sometimes you have a smaller energy by going to the cylinders instead of having the defects and so you observe these uncapped cylinders and in between and we we identify some typical scaling for the typical radius of spontaneous curvature you expect to have intermediate shapes that are strongly dependent on the way you self-assemble so indeed with this continuous calculation you you you are able to explain why in the simulations of Roya for example for small radius of small radius of spontaneous curvature you expect to have this icosahedron and on the other side you have the cylinders so I'm I'm just trying to comment now on the special case of HIV so some experiments have been performed quite a long time ago into the self-assembly of just ca which is the part which is the protein that makes up the conical core in HIV and depending on the presence of the genome or not cylinders were quite often observed right now if you look at cones inside particles that are produced inside cells well you make an interesting correlation as well most of the time you observe some cones but sometimes you observe some cylinders but the genome is outside here a cylinder here the genome is outside okay so this raised the possibility that in fact in order to answer the question how would you close your surface if you have an infinite cylinders maybe this is the interaction with the genome that induces the defects so we started to to make some simulations and this is an ongoing work but indeed if you take a surface that wants to grow separately without any interactions with something else if it wants to grow just like a cylinder if you perform the growth in the presence of an attractive sphere then you are able to induce the presence of punch embers so you change the way the surface wants to grow and so we started to to have kind of face diagram but this is very rough basically with the addition energy and the ratio between the spheres and the spontaneous curvature and you expect to have some phases where you don't have any addition some phases where you have complete covering and in some phases you observe some some cones for example so this this will end my first part about the single objects and the main conclusion is that at the level of a single protein this is really the spontaneous curvature so at the very local scale this is the spontaneous curvature that will determine the shape you will end up if you would have rather icosahedron or or more elongated shape and importantly it seems that for the case of HIV but maybe for other viruses as well the interaction of the growing protein surface with something else it could be the genome or it could be the outer membrane for HIV for example is susceptible to give rise to punch embers in order to close the structure so now I move to the to the second part we are going to look at many intermediates now not just one particle and we are going to to focus to focus specifically on one type of self-assembly that is found for HIV again which is what we call the open self-assembly so it means that in fact you have a self-assembly scheme where you have some proteins that wants to minimize their overall energy by associating but there is a source of monomer and there is an outflux of complete particle okay so this is not a closed self-assembly we would be just this case right but here you have an entry and an exit in your system the fact that you have an entry and an exit will all you allow you to reach eventually some stationary state okay so we we try to to to understand the dynamics of such a self-assembly scheme and so the idea to do that is to write down the kinetic equations and so basically we have a pool of monomer which is fed externally by constant flux we have the self-assembly and the pool of monomer couples to all these reactions because you we consider a monomer addition model and the last step is irreversible because you you you lose the the complete particle so the interesting quantity to consider in order to understand what is going on is the local flux which tells you if locally you are going forward or backward and you have also the detail balance and the interesting so there is another also an interesting phenomena is that you expect to have some line tension in your system because you grow your system there there is a border between the particle that is growing and the rest of the membrane for example you expect to have some barrier energetic barrier and this energetic barrier in fact is the net effect of this energetic barrier is coupled to the monomer populations this is this graph here this is the height of the energy barrier this is the number the size of the intermediate two compute and you see that depending on the monomer population you are able to modulate the height and the width of the of the of this barrier and this will have some strong consequences on the on the assembly on the dynamics so if you solve numerically the equations I just showed you will end up with a profile like this so these are different profiles so this is the size distribution as function for different time and you see that in fact you have some assembly waves with with some some parts of intermediates which are relatively well localized okay so you have a propagation of kind of front and in fact sorry it's well it's hidden more or less in the in the effective in the effective parameters the bending energy will will come up in this in this epsilon this is the net energy you gain by forming the by forming the intermediate and if you have bending energy for the membrane you lower this net energy this is an energy gain okay so if you if you bend you you expect to to loss to lose something so the gain will be small we can discuss this afterwards sure so the interesting point is that well the monomers that you have in the solution they have they are used by two two two processes the first process is to nucleate an intermediate right we call this nucleation and there is an elongation which is which amounts to grow the intermediate you just nucleated and the monomers how have to share between classes that will nucleate or elongate and here for example if you compute along the time so these are rescaled units but if you compute on the time you compare for example the elongation current here which is roughly constant but there's a slight drop here to the nucleation current you see that nucleation current is strongly localized so you nucleate a whole bunch of intermediates but then you stop nucleating and then the things travels and that's why you observe this assembly weight here for example if you look at the outcome this is the flux outside so you expect to have as an outcome as if you measure the number of particles that emitted by by the this cell for example you expect to have some can what what we call viral burst it means that for some time you have a strong production of full particles but then you have a lower production then a stronger production then a lower production before reaching eventually some stationary state where you you have this kind of production so we don't have really experimental evidence as precise as the these predictions but if you look for example at cells that are producing producing that are infected and producing HIV for example you see sometimes you see a real like this where you seem to have all the particles in the same state here you don't have particles with few few proteins you see mainly particles with many proteins that are almost closed okay so that that goes to that that fits well at least qualitatively with this kind of prediction but we expect to have more more exponential data so this is really related to the to the presence of of of the barrier here in fact this barrier depends the the the height of the barrier depends on the monomer population and so as the monomer are are divided between monomers that will nucleate and will grow eventually you see that here the elongation is almost constant but this is the nucleation which is highly localized meaning that here for example if I look at an intermediate time let's say 400 which is the violet here you see that well you have something which is localized because you you stopped nucleating you just you use almost all the monomers to propagate because you have a high barrier you cannot create anymore and these these are on the other side of the barrier and they will propagate and you have also an interesting comparison if you want to compare the what what I define as the open self-assembly with a one-shot self-assembly so what is a one-shot self-assembly so suppose you perform the open self-assembly for a certain time and remember you we have an influx of monomer so if you count the total number of monomers you fed in your system you could try the following experiments take this number and plug all the monomers at the same time zero and then you stop putting monomers and you see that the dynamics are very different in fact so this is again the color hate gives you the size distribution you have the time you have the size here and you see that in fact if you all monomers are probably in one shot then you have a large number of nuclei but you have no more monomers to propagate them so you have to disassemble or wait for disassembled or to recycle in order to propagate so if you make a quantitative comparison between the two kind of self-assembly so let's say for example that we are going to compare the two self-assembly at time ten thousand okay so with a flux one at time ten thousand it means that I can plug at the very beginning ten thousand effective monomers because these are reduced units and so if you compare the black curve and the red curve you see that in the experiments where you provided all the monomers at once you have at the given time you have a much less efficient production if you provide the monomers by constant flux but small flux then you have you are able to go faster than if you provide all the monomers together that that's an interesting prediction and again the reason is that you have to recycle for the one-shot self-assembly you have to recycle because you created so many nuclei that you don't have any more monomer to propagate them so you have to disassemble some nuclei in order to make some of them progress and this makes you the process this process which has been called in literature kind of kinetic trap is indeed smaller so I arrived to the to the conclusion to this part and just in order to summarize so for this open self assembly problem the presence of an energetic barrier is very important because it gives you this particular dynamics in the form of assembly waves and if you look at just the out the the output of virus production you expect to have some burst okay not continuous production but some burst before reaching eventually some stationary state and the interesting prediction as well might be that well if you want to perform an experiment of self assembly by using the standard physical chemist way you put all the monomers together maybe if you try to to put some flux of monomers you might enhance the the the speed of the reaction and so with this I would like to thank you for your attention and yes I would like to thank some collaborators in particular thank you