Welcome everyone. It's Karen Vissi speaking here. Thank you very much for all coming into this awkward webinar. I'll be presenting on behalf of Natasha Simons, who wasn't able to make it at the last minute today. Today's webinar is sponsored by ANZ, the Australian National Data Service, and called the Council of Australian University Librarians because this is something of joint interest to both organisations. So a bit more about awkward. I'm guessing that since you're here most of you know a little bit about awkward, but I'll just fill in the gaps for a couple of people who may not be aware of the background. Awkward aims to address the problem of unique identification of researchers by giving individuals a globally unique identification number that lasts over time. Some of the world's largest publishers, funders and institutions have adopted awkward and community uptake has dramatically increased over the past year. On the 29th of July this year, ANZ and CORE co-sponsored a national roundtable on awkward to reflect on the progress of awkward internationally, share international perspectives on awkward, discuss international institutional views on awkward adoption and facilitate practical measures that can meet institutional needs. And the presentations for that workshop are on the ANZ website that you can see there on the third link. Today we've got three wonderful presenters who will share their reflections on the roundtable and also present their institution's perspective on the awkward opportunity. Our presenters today are Heather Todd from the University of Queensland, Nathaniel Lewis from the University of Sydney and Simon Porter from the University of Melbourne. Ryan Flarty from the University of Auckland is also ill today, must be a bad day, but his presentation is up on the ANZ website. So our first presenter for today is Heather. Heather Todd is Director of Scholarly Publishing and Digitisation Service at the University of Queensland Library, so we see a campus in Brisbane, which is where we're talking to you from today. I'm just going to hand over to Heather now so that Heather can start her presentation. Okay, well thank you for joining me. It's quite strange for me to present this without actually seeing faces in the room. But anyway, we'll see how you go. So I'm going to talk about the awkward experience at the University of Queensland. So we've been very interested in awkward for a while, and one of our staff members has been appointed as an awkward ambassador, which basically allows her to keep up to date and receive quite a lot of information for awkward. And we do promote awkward whenever possible, for instance in training classes, discussions with researchers. And if anybody sort of emails us and asks us a question about how to sort of what affiliation they should put on their paper, we always take the opportunity to tell them, you know, and whatever you do, don't forget to register for an orchid. And we've just signed up for an institution or subscription because we plan to roll out orchids through the organisation. The library manages the institution or repository, which we call UQE Space, and we do have an identity management aspect of that, but it's rather static because we haven't made use of the API orchid APIs. And users can manage their different identities in a preferences page, which I'll show you in a screen or so. So what we've done is we've allowed academics to put in their online identities, and then with a single URL, they can have all of those identities linked. So I'll just show you a couple of pages. So this screenshot here is our preference page on our repository, and you have to be logged in to do this. And you can see that there's an opportunity to manually enter four author identities, People Australia, Scopus, Orchid, and Google Scholar. You might say, where's researcher ID? Well, because we sort of have a different implementation for that, we automatically add that researcher ID, we automatically add the researcher ID to staff members' profiles. So once staff have actually entered in their author identifiers, they can log in, and if they go to their My Publications, you can actually see on the top right-hand corner for this researcher that they've got all of their online identities listed. So if they click on any of them, they go to their researcher ID account or their Orchid account. So we've made that possible, and we've got about just over 200 Orchids in the system at the moment. One of the things we're asked to talk about was our business drivers, and as I said before, the library does host the institutional repository and we're heavily involved in the Herdick and ERA program. So therefore, you know, it's essential we have good author identification. And just to give you an idea, UQ Publish is about 10,000 publications a year. So it is important that we assign the right paper to the right academic, and we do gather our data through Web of Science and the Scopus API and researcher ID, and we do know there's some under-reporting, and when we implemented the Scopus API last year, we were quite surprised how many new records we were going. We got because although we knew there was under-reporting, we didn't know how much under-reporting. And we also think it's best practice. And we've got a lot of support from the Office of the Deputy Vice-Chancellor of Research, and they're behind the project, but the library will lead the project. And so the university, like many other universities, have various policies on author affiliation on all of the papers. With our workflows, all new academic staff are encouraged to have a researcher ID or to link their existing account to UQ, and we encourage them to clean up their Scopus identities and we provide information to do that. And with our researcher ID program, it's currently managed by administrators only, but we'd like to move to an author-managed process in the future. And for instance, we've just gone out and asked a lot of staff for some information for ERA and we've had over 100 requests for people to link their researcher IDs. So the nuances around the implementation is that UQ researchers, probably like every other researcher, is really resistant to admin work. So we're going to have to try and make it as easy for them as possible. And we do appreciate that while we know that the library is very important, researchers are more likely to take note of the project if they're directed to by the DVCR research or the VC. So there are some things we've got to take into account, and as part of our communication strategy, we want to get the message out from the highest level possible within the university. And then because this involves IT work, we need to prioritize the development with the work to support ERA and Herdick. So our plans for the future is to have an application where UQ academics can manage their online identity really easily. And we just again want to promote the e-space URL where it's possible for UQ academics to have a single URL and link to their online identities and even sort of link that to their email signature for easy access to their identities. So that's what UQ's experience with AllKid is. Thank you. So over to you, Nathaniel, thank you very much. Thank you. Hello all. My name is Nathaniel Lewis. I'm director of research reporting, analysis data and systems at the University of Sydney. Our group manages the Herdsee and ERA submission for the University of Sydney. Among other things, we manage all the research information of our researchers, contracts and grants, and maintain the information systems that hold all that data. Part of the work that we do is to look at other technological initiatives such as AllKid and see what sort of value that could add to, I guess, the management of research information. So today we've been asked to talk a little bit about how we've engaged with AllKid. What are some of the business drivers? What are the fit to services and some integration challenges and any sort of sectoral issues we might want to raise? So for the University, we've identified AllKid as a good opportunity. It's going to work across the research portfolio library, our ICT and ANZ, of course. It's been presented to our senior executive group in the research committee. So all the deans in the ADRs at the University are well aware of AllKid and now it's up to us to think about how do we implement AllKid across Sydney. So we joined AllKid as an institutional member in June this year and so we're now at the planning stage and considering what are the policy implications for AllKid that will lead to some of the implementations as well. Part of those implementation challenges around integrating it with our internal systems we use D-spaces as our main repository for our ERA and HRC submissions. We've got a software platform called ERMA which is our main repository of research information. We also need to integrate with HR and ICT going forward if we're looking at identity management. In terms of the alignment to our research strategy we see AllKid as another tool to enhance the data quality, the accuracy and consistency of information. It allows us to do some triangulation between Scopus and Thompson and various funding bodies as well. And I think one of the biggest challenges we face is around mapping affiliations of researchers. AllKid presents us with an opportunity to enforce persistent identifiers. We've got some researchers with upwards of, I think there's one specific example where they've got over 200 identifiers in Scopus. So this gives us an opportunity to minimise those different researcher IDs and bring some automation to that process. Again, managing duplicates across the different systems and mapping those affiliations and publications, grants, data and also help us with our open access compliance so we can report against AllKid implementation. For us it's about maximising the performance of the university in terms of its research performance to help with the reporting whether it's government compliance reporting and also rankings as well. It's about, again, specter data quality and the accuracy of that data and how well the university is represented. In terms of the fit to services, it's going to impact across a few things and this is in relation to the policy procedures and workflows. We need to think about how it fits with any existing governance arrangements at the university, how it's going to be formulated and how we're going to implement that. We are looking at creating an AllKid identifier for all Sydney researchers so we need to think about how we're going to populate and maintain those records going forward. We see AllKid as supplementing the current Scopus and Thompson publication sweeps that we do to fill in the gaps for the under-reporting piece and we also see AllKid as an opportunity to help manage those non-citation-based disciplines that aren't necessarily as well represented in the major publication and indexing houses. In terms of the technical and policy considerations, we are looking to see how we can minimise researcher burden. In respect to that administration issue, we don't want to enforce another identifier on them. We want to make it as seamless as possible. It should be happening behind the scenes so that's a primary issue for us to consider. There are technical constraints on the AllKid record population policy. We'd like to be able to populate all records in AllKid on behalf of researchers, but there's some issues around AllKid and how that can be set out, but that's more around the philosophy of AllKid and that the researcher owns the record, which is good, but if the researcher owns the record but they don't want to administer the record, how do we go about doing that? So that's something we've got to work through. We do know that the information we collect on behalf of researchers on their research outputs is quality assured. We do the checking, the verification, we make sure we've got a record, we've got an actual publication and a file, and that's populated into a research information system. So we want to leave that to make use of AllKid and make it an effective tool to use. There's some questions around the capacity and service levels of AllKid, but I think at the round table we had the CEO of AllKid there and they reassured everyone they've got plenty of resources and they can scale up their service as well if people do come online in a hurry. We've got, I think, at least 25,000 researcher records we need to manage and over 150,000 publications, so we need to make sure that if we are populating these AllKid records that it can cope. There are also some concerns around the privacy and location of service in the US. Advice from our own legal counsel is that it's not such an issue because it's publicly available information. That would be dependent on your local provisions. There will be the usual issues around integrating the existing ICT and HR systems. It's how far do we want to use AllKid and integrate it into the systems is the next question. Do we make it something that everybody signs up for when they join the university? How do we go about linking the existing AllKid IDs into their university identifiers? And then how do we implement to this at the local faculty level? At the university there are 16 different faculties and they are the ones that run their own show, for example. So we need to provide the advice that enables them to perform an implementation of AllKid at a local level and work with them to do so. In terms of the future of AllKids, we see it as providing a consistent approach for research outputs and records management. I'd like to see it as a good supporting tool for research and mobility. It saves us having to re-enter all their research information again and again. If they've got an AllKid ID and it's well maintained, that will make transferring their research outcomes and outputs into and across universities more easy. We would like to see it as a tool for identifying collaboration opportunities and strategic recruitment. Better alignment to Scopus and Thompson databases. And in terms of sustainability, I think support from publishers of AllKid is key. Thank you. I'm now going to pass over to Simon Porter. So I guess my presentation is somewhat similar to Heather's because it's focusing around... Oh, and if I'm yours because it's focusing around how AllKids primarily facilitate publications collection in the context of collecting publications. Not only for Herd C, but as Heather's indicated increasingly, it's about universities being able to effectively represent online presence of their researchers and comprehensive representations of everything that they do. So I want to put this in the context of... I want to put AllKid in the context of how we've gone about collecting publications over the last 14 years or so. And in 2001, almost all the way through the... 2008, it really was a manual exercise of keying in publications. Along the way, it's become more of an enterprise in harvesting publications from Scopus and Web of Science. To the point now where AllKids evolved into it is now not just harvesting publications, but how do we refine the publications that we can harvest so that we can limit the noise that we get? So that's pretty much the trajectory that I want to talk about.  This graph that you see on the screen is basically all the publications that we've collected for all the departments in the University of Melbourne. The different colours are the different types of publications. So that sort of purpley colour are journal articles. The light blueish colour that you can see in the graph sort of across the top are a conference papers. You can see there's about halfway down there's a chart that looks nothing like the other ones. That's the VCA in Performing Arts. So they're doing lots of different sorts of publications. The purpley colour in the bottom are books and book chapters. So you can see over 14 years we've collected over 150,000 data points of publications. Each of those data points took at least 15 minutes to enter, involved reviewing it by multiple different people. The amount of time that it takes to do all those things quickly adds up. So the context in which Auckland, in which reducing the amount of work it takes to collect these things is really quite a serious enterprise. So I've already talked about the evolution of how we collect the data. For the University of Melbourne, probably up until about 2009, the only way we collected that data was through manual entry. So either it was researchers keying in their publications or publications coordinators on their behalf. Probably we came quite late to this, but we got wise that we could harvest publications from a source like Web of Science or Scopus and then refine them and process them. And we started doing that with just Web of Science in 2010. We got to the end of that process and I quickly realised that whilst it was effective doing it for Web of Science, we didn't have to turn around to it for Scopus and then we'd have to turn around to it for RPEC, then we'd have to do it for Archive and PubMed and every other source that came on, which was really unsustainable. So about 2012 we implemented Simplectic, which enabled us to harvest from multiple sources and basically help us build combined records. So we have a publication record that can say, here's the publication, here's the publication representation of that in Web of Science and Scopus and so on. So over time, publications and interaction has moved from data entry or emailing your publications coordinator to... We think we've found these publications. Can you please confirm whether we've got it right? So this is a screenshot from our UAT instance of Simplectic and you can see that if Jim McCluskey were to log in, he'd see that he has 32 journal articles that he needs to claim and he gets a screen somewhat like this. So he can quickly go down and tick, yes, this is mine. No, that's not. So that works well, provided we don't offer up Jim or other researchers too many false positives. So we don't want to create a situation where a researcher has to wade through hundreds of publications to find the 10 that are actually theirs. So the way Simplectic works for those is that what you do is you go in and you say, okay, for this researcher, these are their search terms and these are their organisation affiliations and it goes off and searches each of the interfaces to try and find publications that match those search terms.  Because we've been collecting publications for 14 years and because we've had Simplectic running in the background for a number of years, we know which publications belong to our researchers for the previous 14 years and their equivalent Web of Science record or their equivalent Scopus record. Because we know that, we can query those records to find out the actual or the search terms that they used on those records and the actual organisational affiliations that they used. So before we roll out Simplectic to our researchers, we can pre-populate all of those search terms in that record and that's helped us to reduce the amount of false positives for some researchers, probably about for an 80% of the researchers, we were able to, by pursuing this strategy, we were able to reduce the amount of false positives that appeared for researchers for some people. So you'll see along the x-axis, you'll see people who used to have a lot of publications pending so for approval, there's a data point at 1500 that's been resourced to zero. But on the other side, you'll see people who used to have fewer publications pending in Simplectic and now have lots of publications. And basically this is because configuring search terms for researchers can only take you so far because some people have such common names and that no matter how far you configure the search terms there really just isn't a way of providing searches that just bring up their search results. And to give you an indication of who they are, if we look at the top 20 or so researchers who are getting lots and lots of false positives, we can see that predominantly they're Asian surnames of some sort and really there is no approach or help for these people in terms of configuring search terms, some researchers just need orchids. So as part of phase two of our Simplectic rollout we'll be targeting these researchers for orchid IDs first because it's these researchers for whom having an orchid ID can help the most.  So that's one use of orchids for our researchers but the real reason we started getting interesting in orchids was not for our researchers but it was actually for our graduate students because with our graduate students we've got a problem of trying to work out what happens to what graduate students have done after they leave the university. So after they left the university we've got no recourse to say hey we think you've done this publication could you please confirm it. So we need to know what have they published based on the research that they conducted before they left. Can we claim that and her to see. We also really want to know where have they gone and what does their academic career look like three years after they left the university for instance. So for these reasons we've now got a university policy which requires graduate students to have an orchid and we will be managing this process through Simplectic. So our idea is to encourage graduate students to have orchids but not just have orchids but actually use that orchid as an active part of their research career. So it's not just having one but it's actually owning it and ensuring that all of their outputs are going to be connected up to it. So really once we've done that we've got a mechanism to glue our knowledge about who our graduate students were to an involving data set of what they're doing in the open world. Our approach for graduate students unlike some other orchid implementations for graduate students we won't be minting orchids for our researchers. The reason for that is we feel that although there are methods where you can create orchids on behalf of your graduate students for all of your researchers the risk is that you end up with orchids that have been created for graduate students which they don't own. So you think you've created an orchid for them but basically they've just ignored the email that came through from orchid once it's been created. There's an orchid out there for them but the first time they go to use an orchid they'll just create a new one because they've completely forgotten that that process has happened. So the risk of creating unknown orchids is too high for us to consider minting them for our graduate students. We will be emailing our graduate students just like orchid does but we will be asking them to go into symplectic and configure their orchid in their symplectic account. The process within symplectic is quite straightforward for this. If users don't have an orchid they can get one as part of the process of configuring their orchid and symplectic and basically it's maybe one or two clicks more than doing it through a minting process but the end result is we now have if we can get students to do that we now have a process where we can track those students that have orchids in our system and we also know that those students have actually undergone some activity which indicates that they might have a better chance of owning that orchid and we've now got a solid practice to track those who haven't engaged with the system with follow-up emails. So we can really track our success of how that flows. That's really the orchid story and I guess reflections on the trajectory of this we've talked about moving from data entry to data glue and we've talked about how we harvest publications how we need to use orchids to glue our knowledge of graduate students to evolving information in the world about them but I guess the reflection is that it's not just publications that we want to glue back to our data sets. Increasingly it's grants not only because we've now got NHMRC requirements that want to track the publications that belong to those grants and ensure that we've got open access publications for them. It's also research data it's also potentially academic history for researchers and we really feel that orchids are key pieces of the puzzle to help us do this in the future. So we were asked also to reflect on the orchid workshop and I guess the biggest takeaway I had from the orchid workshop is that there are multiple levels of orchid subscription you can subscribe as an institution at various different levels and you can also subscribe as a nation which offers discounts. I got the sense from the room that one of the things that we should ask a call about is whether we can pursue a national subscription through the call membership. So that's just my final thought and that's my presentation. So looking forward to seeing you at our next ANS webinar and thank you very much.


Good morning and good afternoon. Hello everyone. My name is Yuri and I'm working here in Norway with tracker implementation. I hope you can hear me well and Scott, do you see my screen? Looks great and here you find. Okay. So I will show you how to move the tracker data to aggregate data sets today. And as Scott mentioned, capturing this individual level data in DHS2 does improve the quality of data that we reports to aggregate HMIS, but it also helps us to get to the analysis of data as regular as often as required. So I first got familiar with this question of how we transfer the data when I was working on the TB case surveillance on the tracker module that has been published now in August. And so my examples that I will share with you will be based on the TB case surveillance. So as you know, for countries that implement tracker, it is recommended that they use two instances for one for aggregate modules and one for tracker. And so by maintaining these separate track and aggregate instances, the performance can be best managed by admins and choosers so that the data can be protected and used as required. So basically, what we do is that when we collect the individual data in tracker, it is being aggregated via program indicators. So when we produce analytics in tracker, sometimes we're lacking those dimensions that the aggregate world allows us to use. And therefore, we need that step of transferring the data from tracker to the aggregate modules. And I'm going to talk about two ways of doing that. One is more user friendly. And this is a solution that has been developed by his Uganda. And I just would like to say thank you to my colleagues in Uganda who shared that information with me and helped me at the beginning. And the other way, the other solution I will talk about is a script approach that requires more tech knowledge. So first, the app that you can all use in DHS2 is called the data import wizard developed by his Uganda. So it has a user friendly interface. It supports various import types and you can save your mappings and edit them and have a good way of controlling them. But the consideration that you need, well, the things that you need to think about as you use that app is that the mapping process is manual and it's best suited for small scale datasets. So basically, if you have to transfer a lot of data from your tracker to the aggregate modules and you have a lot of indicators or data elements to feed, you'll be better off using the other solutions. So how does it work? I'll just say a few words and then I will show it to you on the example of our on the instance. So once you install the app from the app store in DHS2, you have to do it in your aggregate instance and then you can start with a new mapping. So and as you configure it, I will walk you through the steps. Now you will see that it's quite simple. So let me see if you can... I'm trying to make sure that... Scott, did you see that I switched the screen now? Yes, we can see that you're looking at DHS2, the WHO, Hive and Dev. Yeah, okay. So as you see here is my tracker instance with a whole list of program indicators that I have created for my data. And as I said, for each of the data element in the aggregate set, I have to create a program indicator. So I need to create one for the age desegregation for sex and so on and so forth. Here is my aggregate instance with the report forms on the TB. And as you see, this form is empty now. So we'll try to fill it in with some data. So here is the app that I was talking about, the data import wizard. So once I started, it actually serves many purposes. It can help you import dummy data into your instance or data from Excel or whatever. But we are talking about the aggregate. So once I start a new mapping, so basically I will have an overview of the data sets that are present in my instance. And here I will go and take the TB case notification. So I have to create a mapping name and choose the import type. So in this case, I'm going to import DHS2 indicators into a DHS2 aggregate data set. So I go for program indicators. I have to specify the address of my tracker instance, which will be this. So I put it here. And then I have to log in with the system admin password that has access to the instance. See if I get it right this time. Because in the app, you can see the actual password. You don't see the stars. Let's see. So that was right. So now here I have to specify what period of time I want my mapping to work for. So I will take 2020 and I will take the first quarter indicator aggregation level. Okay, so we can do a facility. And then we need to map the facilities on the tracker instance with the facilities or with org units on the aggregate instance. But as you see, if the names are matching, then the mapping happens automatically. I don't need to do much here. Then I can filter my indicators. And these are the indicators that I want to send data to my aggregate modules. And I've been using the prefixing in the indicators that I've created. So I can assign all of that. And then I can move to the next step. Here I have the data sets that you see that I need to manually map. And this is what I mentioned earlier, that for data sets that are included, just a few indicators. This is the way to go with this app. If you have several hundreds or thousands of elements you need to map, this will be a cumbersome process. So let's say here is my agent sex TV form. And here I can select the indicators that I that can feed into it. And so I can also look for for the indicators. Okay, so it's this one. And here it's, I don't know, that was a female, sorry, sorry. Female here. And then I will find the one for female here. And so on. So I proceed like that till I reach the end. And when I click next. So right now I didn't do all of this. But if I did, I would, I would be shown the, I will see the status that all of my indicators in that form were mapped. I guess it takes, it takes so long because of the fact that I have not selected everything here yet. So I will, I will just interrupt this process and I will show you a mapping that I've created earlier. And you will see that it's what it does. So let's say I move on to the next step. So here are my mappings. And here you can see that the import summary of my job that I have updated eight values from my mapping. And I can save it as a JSON file or I can, I can also see, I can, I could also see the report on what has been done. And if I go to my aggregate module now, I will be able to see the data that has been filled in. Okay. So this is how this app works. Basically, what's in the background, there's a JSON file that is generated with a payload. And then it's uploaded to the, to the aggregate module. So the next way of doing, of moving the data to the, to the aggregate modules is the script. And here I'm referring to the script that has been developed by Love Popper. A lot of you might know him. And we are now working on upgrading this script so that it will be more universal in what it's doing and also provide more feedback to the user once, once it's run. So it's a shell executable script that requires some initial setup. And I will walk you through that. And you can also set up automated periodic export of data with that script to, to aggregate with the world by using, let's say, a task schedule. So there's some work that needs to be done for that. And this is where, what I started when I, when I worked on the TB case surveillance. So basically, on the aggregate side, you have the data elements and the category option combinations that need to be coded. So here is an example, as you can see of a data element and a code that it receives. And here's an example of a category option combination with the, with the code. So I will need these codes to map my program indicators in the tracker instance of, in order to, for this transfer to be successful. So on the tracker, we will need, as you see here, I will move to my indicators. As you see here, there is an element or an attribute here called category option combination for aggregate data export. So here I map my category option combinations from the aggregate modules. And I will also need to create a custom attribute, which we call data element for aggregate data export. So we can then map it to the data element in the aggregate package. At this stage, I would, I would just like to point out that there is a bug in the current, in the DHS2 now that prevents the user from creating the custom attribute for program indicators in the maintenance app. We are working on that bug, but when we deliver our generic packages, let's say TBK surveillance, these come with these custom attributes, because these custom attributes can still be injected into the properties of an indicator via API. So if you have any questions on that, or how this can be done, you can, you can get in touch with us and we will help you in this process. But once, once this bug has been resolved, it will be easier for users to actually just enter those mappings here, because this is where it will appear when you create that attribute. So what is done afterwards? So you have a, this is what the script looks like now. So basically, we, we need to edit the list of program indicators that we are going to use to push the data. We have to specify the org unit levels at which we do this transfer, as well as the periods. And then we need to specify the data attribute, UID, and this is the attribute that I was talking about the, for the data elements. And then we need to specify the servers that we're using. So here is our source URL. This is the tracker and our target URL, which is the aggregate package. We make sure that the date format is correct in this field. And then we specify the file name that will be created for transferring the data and the comments that will be added to the database. And basically, then we need to update the user in the password for the servers. And basically, this is it. So we need to, because it's a shell script, we need to make it executable with the C H M O D command. And then we can run it in the, in the shell or in the terminal on the Mac. And then if you need automated data transfer, you can use the a, a scheduler in order to make these transfers periodic. And I think I've forgotten to say, but in the, the his Puganda app, the, the, the import wizard also offers you scheduling for the jobs that you create there. So this is basically what I wanted to show today. And as a, as I said, if you have any questions, please use the, the, the channel on the community of practice to will be happy to answer these questions. And if you need support with the, with the, with the script, or with the transfer from aggregate, please do get in touch with us and we'll guide you further in that process. So thanks. Thanks so much, Yuri. There are a few questions that maybe you can answer right away for us here. There's quite a, actually, there's quite a lot of conversation here. So the, the, so one question that's, one question that's been asked a couple of times, and I think you just answered it is these, using that application, the history of Puganda application, you can schedule jobs. So you, once you set up the mapping, you can schedule it to run periodically, correct? Yes. Yes. Okay. And then what if you have aggregate and tracker data in the same instance, does that app also work for in that situation? Yes, I don't think there's any restriction in regard to that. So you will just have to specify the same instance twice. And then you will be, if the transfer will happen. Great. Then is there, are you able to provide contact details for folks who may need assistance using the app or using the script? Yes, with pleasure. So how do I, do I just paste it in the, in the chat here? Well, I can, if you're fine with me just giving out your email, I can paste it here in the, yeah, in the chat or in our, in our Slack. Yeah. Okay. Is there a step-by-step guide that you have for using the application? We are, I don't have a step-by-step guide right now. So I can, I can, I can copy from the notes that I made for the person over and I can upload it to, or I can either post it on Slack or on the community of practice. And I will also do the same for the, for the script. So the script will be the way it looks now. And so, so basically what we are trying to do is that we're trying to make it more, more user-friendly. So it will give you feedback and it will, you know, on what it's doing basically. So there'll be more kind of validation of the process. But again, you know, the interface requires more time than the actual, you know, script that does the job. Right. Right. Yeah, those would be two very useful resources. Another question is, are we using that same app? Are you able to move data to have interoperability between two DHIS-2 instances that are just having aggregate data? For example, you have aggregate data in one and you want to move that aggregated data to another. Are you also able to use that app for that? I have not tested it for this, but from what I see when I, when I create, when I create a new app. So let me just create a new mapping. So feel free to, you can share your screen again as well. Okay. Let me see. We are here now. Okay. So if I, if I take more, create a new mapping. So these are the options that I have. I have a DHIS-2 to DHIS-2 data set, which I think is the answer to the question. So I can move that from one data set to the other or from indicators. Let's say I could even move the data from the aggregate indicators here to the DHIS-2 data set. Right. Okay. So both ways are possible. Cool. That's great to see. I think we actually have some HIST Uganda folks that are participants. And so they're actually answering some of the questions themselves, which is really cool. And in general, I think it's important to point out that this is a great example of how the DHIS-2 community is able to help each other, right? So we're, what, what Yuri's presenting is not an app made by the University of Oslo. Is an, is it a fantastic app made by the, by HIST Uganda? And it's just made in a generic way so that everyone in the world can use it. But that being said, if you are using this app and you are dependent on this app, I would strongly encourage you to consider supporting HIST Uganda. You know, everything in DHIS-2 is open and free to use, but that doesn't mean that things are sustainable indefinitely. And I just want to strongly say, encourage you that if you start to use this app, appreciate that this app is not developed by the University of Oslo and that there's a development team in Uganda that is working to keep this app alive. And if you are dependent on this app, I would strongly encourage you to get in contact with HIST Uganda. We can provide those contact information and talk to them about how you can support their effort to develop, continue to develop and keep this app alive. There are many apps in DHIS-2 that, you know, the University of Oslo, we only made, we only developed about 30 apps, but there are over 100 apps out there. And so if there's a good chance that you're actually using an app that we didn't develop, and if you want to continue using these apps, I strongly encourage you to figure out who developed them and then to figure out if you can support them. In this case, HIST Uganda, fantastic app. So good that we're supporting it or that we're presenting it here in the academy is kind of one of our default solutions. There is one more question for you, Yuri. Have you, are you aware of the metadata sync app at all? No. Well, is that what is called metadata sync? I think the question's coming from Lisa from WHO. She's asking if we're aware of the metadata sync app and it would be nice if we joined the efforts. I'm not fully aware. Again, there's many apps being developed all the time. I'm finding out about new apps almost on a weekly basis myself. I'm not aware of that app and maybe that app may do something similar, I'm assuming. I have seen this app to be honest. I have not tried it out but it's the metadata sync app. I looked at it briefly when I was preparing for this because I wanted to make sure that I see if there are other apps that serve the same purpose because I'm sure that even with this script that I presented that we might have some community members that have developed their own ways and maybe they're more advanced than what I shared. This is just to emphasize what you said about the power of community. It is great that we can reach out to each other and get each other's support in this but I will definitely look into the metadata sync app and see what it will be. Yeah, it's coming from Lisa Grout and Tina Konjument. I think that they would, maybe we can connect the dots and they can reach out as well. They just posted a link to it. Scott, by the way, can you add me to the Slack channel? Yeah, we'll have Martin do that as well. Thank you. Scott? Yes? There are two questions about using this app to import data from Excel into Tracker on announcements, I think. Have you experienced that, Yuri, or I believe Sam from Histugandas also in the call? Have either of you imported data from Excel into Tracker using this app? I haven't been using this app for that purpose but maybe Sam can answer the other question. Hello. Hello. Hi there, Sam. Hey, how are you? So I was working with the Afghanistan team and specifically this year we used the app to import Tracker data, which was coming through Excel from the professional health laboratory. So it is possible to import it using the Tracker that the team present. Great. I think that's a very clear answer. Thank you so much. And again, example of the power of the communities that Sam just happened to be here and be the right person to answer the question at the right time. So that's fantastic.


Welcome to the closing plenary kind of wrap up session of day two of MIT's computational law course. We just finished our first try at doing breakout sessions completely online and we think it was a success. We were able to get the mechanics working. We had good engagement, interesting questions. We were able to sort of chew gum and and pedal at the same time with, you know, multiple things happening. We also have a... except for the video freeze and there were spills and thrills all around. Here's the team that's here and we're down one. TMA's helping us monitor and facilitate an in-person meeting that's happening downstairs right now. So by way of wrap up you can actually experience all the joys of each of the breakout sessions in the session page. There are now uploaded YouTube archives embedded right in the page and you can follow along with the with the pigeonhole questions and coming up tomorrow looking forward I'm going to do a quick screen share here and we put a couple of updates for you. Boom. Okay, present to everyone. Great. So we'll get started tomorrow at 11 a.m. where we'll ask the as many as possible of the breakout leaders to join us to do a quick round robin of what their sessions are about so that you can be a little bit refreshed and we'll provide a mechanism and we'll also do a bit of a, you know, just a kind of an overview and a synthesis of everything that's happened so far and then at 11 30 to 2 in that period of time we'll have each of the breakout sessions. Some sessions, you know, may be staggered so check the page and more information on the agenda for that for example. I know that Elizabeth Reneres' session for example on the competing legal frameworks for human identity in a data-driven age is going to be starting a little later so that may be something more like one to two, something like that. So one quick update is we've decided that the VAT tax thing is so damn good. So darn good. We're talking about maybe doing a standalone event and having a little more time also to find those people that are really into VAT to engage as opposed to, and we think generally from today's experience having some fewer breakout sessions may actually be more enriching for people. So that's one update. It's also actually not as easy to run multiple breakout sessions as we somehow thought that it might be. So something that you can expect is a kind of a design workshop on valuation and other legal treatments in a bankruptcy setting of tokens like ICO type tokens that that looks like it's going to be very interesting. There's also going to be a much deeper dive on integrating interoperable apps and services with a legal platform. In this case it's the e-discovery context and relativity and the first couple of sessions on that were quite good. Brian, I know facility the first one that was engaging and Diana, you facility the second and it seemed like it was it was pretty deep. Yeah, hopefully it seemed good to me. I popped in from time to time. So that's going to be and they'll be looking at Slack tomorrow, which is so interesting in part because it's an example of how lawyers can work differently. Not necessarily so document centered and serial in the work, but we can kind of have more asynchronous work. We can have multiple people collaborating at one time. This human centered approach of that real time chat as a work method makes available as opposed to the kind of document centered paradigm that's so characteristic of law. We think it's a particularly good example and so we're glad that he's going to be looking at that. As I mentioned Elizabeth Reneres is going to be doing a fascinating session on property legal frameworks and or human rights and civil liberties frameworks of which one is the most appropriate and when does each apply to digital identity of people and personal data. Smart contracts including looking at how it applies to music licensing is going to be terrific as well. Michelle Gitlitz from blank Rome is going to be leading that session and she did just what a terrific overview of the law of smart contracts. So we're very much looking forward to that. And finally what we're calling collectivization of knowledge, the urgency of now. This is a session with Johnny Penn. Let me get back to the stop. Okay here we go back to a human speaking of humans on the video. Well if we haven't have we uploaded Christina's video yet? So possibly so we look for the session page for that we shot a yes so it's not there yet we shot a amazing interview with Christina from Uni Global Unions, the sort of union of unions in a way or umbrella unions taking a serious look at workers and data rights and posing five seminal questions that that discussion group is going to be focusing on. I won't give it away. You can hear her say it in a sort of interview format in the intersession page. So terrific set of breakouts tomorrow and we've got an adequate amount of time at the end of the day like an hour and a half or more where we'll all come together in one big session like we did in the first day and and be able to have a hear about what happened in each of the sessions day two and day three and then basically carry forward in a discussion format with with you in pigeonhole and in telegram and and and in some cases live with us remotely online for the discussion leaders and invited lecturers and some people in the room Brian among all Brian's and so so don't miss that absolutely join us for the for the kind of closing big session tomorrow which is what time anybody the closing session is closing sessions to three three three two to four basically two p.m. to four p.m. Eastern time so with that team on anything else that we should mention oh there's one thing on check your email for all the interesting requests for resources and links and so forth we've fulfilled I think every one of those on some cases where we can have a tracking number and a GitHub issue and we'll give you some of the background topics on identity but for the most part we got links and answers we set up a GitHub directory in our class repository for data playground for those of you that were interested in that so there's a stub at least to kind of get started and let us know if you want to go further with that and read the email for all of our answers to the outstanding questions and let this be a lesson to you among other things that if you have questions ask them ask is the only way you might receive and so please do and you know it's interesting for us to know what you want to know it helps us adjust to know what's relevant and the questions honestly I thought we're good like it was terrific doing the research and half the time I was thinking ah we should have put this on the curriculum so so success and we anything else that we should I'm just happy that everybody's contributing because it makes the course I think it gives the course a way to add value to the students and vice versa as well it makes everybody everybody forward in a meaningful way so I just want to say thank you for everybody who's asking for this stuff that we can provide it and that you know next time that we do this it's all going to be in one place and everybody's going to be able to use it they're here I'm with the promise of distributed systems and the get protocol it could all be in all places I guess so yeah it's true collaborate teamwork makes the dream work so until tomorrow thanks very much and you know do your homework do your do your watching of the videos and and we look forward to hacking the law in a good way again with you tomorrow


Hello person man, I am Dr. Tanjana N from Micromedical College and Research Institute. I would like to thank Indian radiologist for this opportunity. My paper presentation is on the role of magnetic resonance crystallogram in free operative assessment of enorectal fistulas and its correlation with the interoperative findings. Introduction, crystallogram is defined as an abnormal connection between the two structure or the organs or between the organ or between an organ and the surface of the poly. Here is a viewer, it is an abnormal connection between the anal canal and the skin of the perineum. Its prevalence is above 0.01% and it occurs approximately 10 out of 1 that person and it has a main preformalness. Young men are commonly affected, tuberculosis and inflammatory bowel diseases are also associated with the perineal fistulas. Enorectal fistulas can be inter-springtric, trans-pringtric, extra-springtric or supra-springtric. Detailed understanding of the enorectal anatomy is needed for the identification and the management of the enorectal fistulas. Objective, to study the role of myMR fistulogram in free operative assessment of the enorectal fistulas, to identify the fistulas' tracks, internal opening and relationship of the perineal fistulas with the anal-springtric complex to correlate MR findings with interoperative findings. MR appearance in enorectal fistulas and enhanced T1 weighted images provide an excellent anatomic overview of the splinter complex, libator plate and astreorectal posa, fistula strapped inflammation and the apparatus appears as the area of a load to intermediate signal intensity and may not be distinguished from the normal structure such as the ars splinters and elevator in a muscle. At immediate post-op evaluation, the enourage produces high signal intensity on T1 weighted images and thus may be differentiated from the residual tracks. T2 weighted images provide a good contrast between the hyper-intense fluid in the track and the hypo-intense fibrous wall of the fistula and allow the adequate differentiation of the anatomic boundaries between the internal and external printers. Active fistula strapped and extensions have a high signal intensity on T2 weighted images while the sprinters and muscle have a low signal intensity. Conic fistula strapped or the scar appear as an area of load signal intensity on both T1 and T2 weighted images. Abscess also have a high signal intensity on T2 weighted images due to presence of the pus in the central cavity. On a gadolinium-enhanced fat-suppressed T1 weighted images, fistula strapped and the active granulation tissue demonstrate an intense enhancement while the fluid in the track remain hypo-intense. Methodology, the source of data. This is a hospital-based study. The source of the data is from the study will be the patient referred to the department of radiodiagnosis, mycer medical college and research institute mycer. It is a descriptive study and the duration of the study was 18 months. Methodology of study consists of MR-pyschidogram will be performed using a BOLU-coil of 1.5 FyMR, FGE medical systems. Informed and written content is taken from all the patients and the following MR sequences will be acquired. Oblique axial and coronal T1 weighted fast pin echo, T2 weighted fast pin echo, then a pad-suppressed oblique axial and coronal T1 and T2 fast pin echo, coronal and axial steps and contest enhanced oblique axial, coronal, societal, pad-sat, T1 weighted, fast pin echo. The contest was a gallo-denium 0.1 mmol per kg at a rate of 1 ml per second. Inclusion criteria is all the patients with a clinical suspicion of perineal fistula referred to M4 MRI, irrespective of the age and sex. Exclusion criteria, patient having histioprostophobia or histiopo-metallic implant insertion, cardiac pacemaker and metallic foreign body institute, patient in whom intraoperative follow-up could not be done. Then results and study. This is the distribution for age and there were 5 patients below 30 years. There were 10 patients in the age group of 31 to 40, there were 9 patients in the age group of 41 to 50 and there were 5 patients in the age group of 51 to 60 and there were 3 patients aged more than 60 years. Then according to text distribution of total 32 patients included in the study 20 were male and 12 patients were female. And this is the distribution of internal and external opening. External opening number of patients were at 28 with a single external opening and multiple external opening were 4. And internal opening, when analyzing the internal opening it was a single opening in 78.1% of the patients that is 25 out of 32 and multiple in about 5 patients that is 15.6%. Then our secondary tracts. In our study 10 out of 32 patients that is 31.3% had secondary tracts and the abscess in our study the abscess was identified in 7 out of 32 patients which corresponds to 21.9%. According to change in our grading the study that the grade 1 fistula were the commonest which was found in 11 patients that is 34.4%. The second most common is the grade 3 fistulas which was found in 9 patients and grade 2 fistulas were found in 6 patients and grade 4 and grade 5 fistulas were relatively uncommon and were found in 4 patients that is 12.5% under 2 patients that is 6.3% respectively. The sensitivity and specificity of the MRI for grade 1 and grade 5 were in the order of 80 to 100% and for grade 5 was 96.4% and 100% respectively and for the other grades the sensitivity and the specificity was 100%. So this is the image showing high signal intensity between the sphincter which corresponds to grade 1 a simple linear inter sphincter fistula and in the second image we can see a high signal intensity collection in the issuerectal space and a linear high intensity tract between the anal canal and the between the anal canal and the subcutaneous collection which corresponds to grade 2 inter sphincter fistula with abscess and this is the great trans sphincter fistula in which a linear high intensity tract noted by the traversing the sphincter and this is the grade 4 trans sphincter fistula with abscess and secondary tracts and this is grade 5 which is a supra-liberator and trans-liberator this is conclusion perineal fistula though an uncommon problem may be chronic and recurrent it may present different numerous complications like secondary tract, arches, cavities incomplete evaluation of these complications can result in residual and recurrent disease Contestinal MR can identify active information of the tract and rate is also we can also distinguish between the scar and granulation tissue 3D T1 patch that sequence is the best under time trading sequence for imaging of perineal fistulas correct identification of the perineal fistula and proper grading of the fistula are necessary for ensuring optimal surgical outcome these are my references thank you


For the Human Brain Project, and today I would of course add on this, but going a little bit more specific in two technologies. Review at first what are our applications and what they might require and then go into some technology trends. I must apologize, I cannot be very exhaustive in the shortness of the time that I have. I will present some scaling laws and ideas how technology will develop, go into the question of how to increase performances on all, let's say, fields, so this is computing, this is memory and memory bandwidths, and of course increasing it by more parallelism and discussing concurrency levels, discussing some memory developments, going into unconventional architectures where I believe we have a good chance to achieve the goals that we want to achieve in simulation and analytics and maybe comment on the technology development that we go at this time in the Human Brain Project in the ramp up phase and maybe comment also what will come, give an outlook. So my, let's say, CRMs I start with is that first of all the simulations of the Human Brain at scale, so full scale simulations or large simulations will require supercomputers approaching the exascale dimension both in compute capability and of course also in the memory capability there it will be certainly hundreds or hundreds of petabytes to be available for that. On the other hand going for analytics and I have the example of the imaging of the full brain, resolving them, the single neurons and go to the submicrometer level, this will be constrained by the progress of data processing systems. It is very much related but it is of course also different and we have to discuss this. Yesterday I spoke of our code design project. They exactly are intended in some part of their activities to address those questions so to help to build up to some supercomputers and you see the keywords NEST coming up again, the NEST code for simulation of the mouse brain, NEST code also using in the Human Brain, then Neuron for mouse-based cellular cortical and sub-cortical micro-circuit models, then the Atlas structure connectivity and function and visual motor integration, Neuron Brain again, let's say matching top-down with bottom-up top-down theories and ideas with bottom-up simulation and robotics. So this will give us, let's say, the constraints and the requirements of the applications and let's start with some discussion on applications. So the neural network simulations with NEST and Neuron have this main feature that they involve a very high level of concurrency. High level of concurrency means huge parallelism and I know they involve different levels of parallelism. I would call it different levels of concurrency and it is not yet known how to utilize computers if you have programs with different level of concurrency. In fact, all larger programs expose different levels of concurrency but this is something that is only, let's say, taken into account on the node level or on the processor level but not on the level of, let's say, different technologies. Today you have different types of processors. You have multicore, you have Manicore and different directions of those processors and I will show you in this short talk that we also want to address this issue which has not yet been addressed at all, only rudimentary using the CPU-GPU paradigm where you have accelerating type of applications but you do not use today the accelerators as, let's say, a sort of parallel repository maybe for a bunch of CPUs to be useful to carry out highly scalable parts of the code. So we have a very large memory footprint as well and this is an important memory. It seems to become one of the very limiting factors. It's expensive if it is high bandwidths. They have lower arithmetic intensities. It's not completely true. The nest has lower one, the neuron has higher one and the more detailed the knowledge about the neuron becomes and the more detailed physiology and other data are, the more computing intensives the models might become. In so far, I would say this low is only with a grain of salt and we have a global communication pattern so we cannot really go for localization of both data and communication. That's an important issue here. Architectural challenges, we have to provide suitable models of parallelism in order to define those architectures. This holds for the node level, this holds for the aggregation of nodes. We have to provide both high memory capacity and bandwidths with minimal hierarchization. Minimal means in a sense that it's also a question where we do the hierarchies on which level and of course optimize the communication. It's a less good fit what I have sketched now to current roadmaps of technology providers. That's an important issue. Current roadmaps of technology providers go, let's say for combination of CPU, GPU, Xeon Phi type processors or ARM type processors will come. So it's not clear at this stage how this will really fit and we have to do a lot in order to bring in our issues and one of those is interactive supercomputing. It has requirements. So it is data intensive, interactivity and steering should be in analysis and visualization on the fly and given the high amount of local memory, moving of data is just a cost, a power factor. So moving data means investing a lot of energy and we have to avoid it at any means. So the mode of operation is probably also changing. It will be users running multiple jobs concurrently in a single session, large scale simulation jobs together with data analysis jobs together with visualization pipelines maybe on the same or on different type of computers but that are connected as well as a dynamic change of the required resources. So it can be that you at a certain path of the job you will change resources within and those resources available to the session. So this will be a significant change of the operational model. So again a challenge we don't meet yet. Technical aspects. Of course we have to increase the memory footprint. We need a huge memory space. First of all to enable also checkpoint restart type of mechanisms but also in order to do the huge, to cope with the huge memory requirements at all that we have. Maybe new non-volatile memory and VM memory technologies will help. This is our great hope so that we can, let's say, boost the memory footprint by a factor of 10 to 50 which will be required for the full brain simulation so at this time it does just not match to the technology roadmap. Scalable visualization, the same problem. It's constrained by letting the ability to move all data so we will not move. We will only move the visualization data out of the machine and dynamical resource management has to be developed. If we go to the imaging problem, let's take again the imaging of the brain atlas. Here the main features of course a high level of concurrency but the sort of less difficult one where you have of course to exchange data at some stages of the process but many of those processes can be done in, let's not call it trivial parallelism but in parallelism. And again you have architectural challenges. Efficient concurrent update of shared data structures and this is again of course connected to communication. It's one of the problems. We don't have yet an efficient accelerator to accelerator communication. I'll come to this with my proposal again. And the management of pedascale data volumes is required. If you look at what data volumes can be managed in current largest supercomputing centers or computer centers, I don't think that projects that reach up to five pedascale are easy. They would nearly require all the resources such centers have available. This means although here we have to really find ways to work with those environments but we have a good fit to the current technology. We knew how to do it but it comes with a cost and we have made sort of extrapolation. We think that computing cost and the data management cost will dominate everything in this field if one wants to go down to the micrometer level. What are technology trends? Let me present some, the scaling laws of course are well known. Moore's law there came from a cost estimate Moore did in 1965 where the evolution of optimal manufacturing costs for integrated circuits results in an exponential increase of the number of components per circuit finally. So on the left side you have those development of cost in the sweet spot as you see at a minimum and then there comes a line where you see how it has developed. In the recent years it went down a little bit, we know it is stalled. There is a reason for that and it can best be understood by denad scaling. Denad scaling has also been found early by Mr. Denad and I think it was 74 so where the idea is that it can change some parameters given a constant power with increasing or decreasing lengths of the gates. So one thing you can do is to increase the transistor density. This corresponds to Moore's law. Another one is to increase the clock frequency. We know that there was a breaking down so this denad scaling is not followed anymore and you reduce the supply voltage. So you can play with all of this because that is that the trend goes, the trend goes, now it does not appear, towards having more processors on one die and this is, we will have an increase of let's say cores and we have seen already an increase of cores on the system. Another technology trend is expressed by Ren's rule. It's a question of you have a number of logical elements, a number of edge connections and Ren's coefficient. It results in a strategy because it will become difficult to balance the communication and the computation. We come again back to this later. So the trend is that you compute much more than you probably need for some problems. So those that require a very high memory rate are increasingly neglected and that's interesting for all fields of science, especially for physics and chemistry where we believe that the current trend is completely contrary to what we would need, namely very high memory rates at a given let's say high rate of computation. So one potential strategy is a better memory hierarchy to have very large memory on the one hand, maybe through non-volatile type of memory to memory on the network. But essentially this is a very difficult field of research and we'll also touch this in one of the next slides. Concarnancy itself, we have different level of parallelism. We have core level, we have an instruction level parallelism. Each core can, at each of the clock cycles, execute multiple instructions concurrently. As you know, we have data parallel instructions, SIMD instructions that are back to our units, however you call it on those Intel and other chips. We have simultaneous multisetting, so that you can have different sets of instructions executed in a simultaneous manner. On the processor level, we have multiple cores. We have many cores. This is an issue that's interesting if we would have proper multicores which we don't have in my opinion, which are not provided through the vendors, then we could really play with using those in a different level of concurrency. On the node level, we have multiple sockets, we have multiple accelerators. This is a sort of question of economy, maybe also of how to organize the communication on a system. On a system level, we have many nodes, but why don't we have many systems? This means, as I said before, why don't we have systems where you have, let's say, highly evolved vector cores, like, for instance, provided by NEC, then other multi-cores like by Intel, and on top of that, two different variants of cores, those Xeon Phi cores, or the NVIDIA type of cores in separate systems that can, of course, interact through these highly evolved networks, and I think that's one potential important way to go to solve the extra-scale problems that we really have. On the device level, you see that more and more flops can be carried out, especially this is another hint that there is a problem because not in the same manner the data rates go into the devices as flops they can carry out, and a very high level of parallelism you have on such systems. Sometimes, if you have problems that, let's say, for molecular dynamics, where you have not infinite amount of degrees of freedom to compute, of course, you are restricted to a small part of the system, and it is not used at all to have a parallel machine. Maybe you would then better buy an untone system by Shaw or so. All this is somewhat neglected by industry because industry is not at all interested in science. They want to make money through selling systems, and sometime it fits with our scientific needs, so we have to do something here. Memory. The memory question is all important, as I said before. We have the capacity-driven technologies, the DRAMs, density scales, roughly according to Moore's law. We have a very moderate and no increase of bandwidths. We only can increase bandwidth through parallelism again, which is limited because this is very costly, and you see the memory rates of current processor types. If you go to bandwidth-driven technology, where you want to be faster, again, of course, it limits the capacity by the costs. So, in future, to exploit this, we have to go to, let's say, from two-dimensional to three-dimensional stacking technologies, maybe even including processing memory technologies. Again, you have some numbers here. They are not much larger than the numbers before. So, here we are better, but we are still limited, and especially we are limited by a factor of 10 in capacity. Non-volatile memory. This is a third kind of, of course, you have it all in your pocket with your memory sticks, but they are more highly evolved ones. They have a significant higher density, but, of course, their bandwidth is very low. They are packaged as these IO devices as I said before. In the future, there might be a possible replacement of DRAMs. We have to find out. I will just present one example. There are several ones in lack of time. I cannot go into detail here, but you see there are different levels of memory, and the question is how, let's say, are you unconventional future architectures of computers could be, let's say, brought up with those type of memories? So, if you make, again, a sort of model looking at the question what is the capacity or what is the bandwidth of memory, so you see these high bandwidths memories have a low capacity. The DRAM memories have higher ones, and, of course, the non-volatile ones that can be network attached in the future might be a very high one, but if we reverse with the bandwidths and if we then build a ratio of both, it is not a constant that, thanks God, it's different orders of those ratios, and this is actually the guiding parameter to bring together a balanced system. So, you see that you have, for the high bandwidths memory, this ratio is 0.01 for the DRAM, and this is made in this manner, it's 1, and for the non-volatile one, it's 100, and the question is how those numbers in a given code can be, let's say, composed to give an optimal type of performance. And this is a challenge for the programmer how to improve the data locality, how to manage the data transport. Of course, it's not only the programmer, the architecture, the overall architecture has to be formed in this manner. And one of those unconventional architectures is if we focus on the processor as processing in memory technology as by the IBM Active Memory Cube, here we can avoid data movement at all just by having the compute layer below or on top, however you see it, of the 3D memory stacking. And then, of course, you would have a very high memory rate. Certainly, such technologies will be one part of the future solution that we will see. If it is realized as fast as we believe, we have lots of experience. Just one of our people got a price for evaluating this. This remains to be seen, but I'm very, let's say, optimistic that such type of technology on the node will solve part of the problems given such a hierarchy solution. Another one we pursue in our lab, or in my lab, this is the so-called deep projects. Again, an EU-funded project altogether. This is, I think, 30 to 35 million euro funding. It focuses on concurrency and hierarchical memory. So the idea is to match some application scalability patterns that we have in, for instance, also neuron is one part of our test programs. Match those hardware characteristics with these application characteristics with benefits of process or heterogeneity. So you have the Manicor and you have the Maldicor processors. That's the idea. We want to profit from the new memory technologies and so network-attached memory on a special network that can handle network-attached memory. This is the other question. You don't want to have a special node to do that. You want to have the network just plugged in, the memory just plugged in into the network, and the network itself is intelligent enough to handle the memory. That's the idea in an overall efficient loop. Energy envelope. So what you see here is a sketch of how such a system looks. It is, of course, separated in order to give you an idea. You would have a cluster system on the left hand with cluster nodes, and you would have something that, again, is a cluster system. But to distinguish it, we call it a booster system and with a very regular memory, a simple machine, maybe something like the connection machine of the 1990s or something like you had with early parallel computers. It's not SIMD. It is, of course, absolutely SIMD, but it has networks that allow for very fast and much cheaper communication. And Manicor, in this case, it's Xeon Phi. It can finally have any type of Manicor. The major point is that this system will certainly be able, so you see what we have today, will be able to operate, let's say, attributing resources in a dynamical manner. So if on the left hand side the cluster nodes are, let's say, 100 cluster nodes are assigned for a program, they can choose on the right hand side what they need, and an MPI process is spawned over the whole system. This will go on in order to encompass, and you can see it here as a sketch, to encompass the idea of network-attached memory so that we have non-volatile network-attached memory also available on both sides in different, let's say, manners, so directly on the node or off the node. And of course, then you need a way to access those memory, maybe in such a way that you would not even know that it is on the network. That's the idea, the final one. And in order to realize this, you need a programming environment that can spawn those MPI processes as well as can manage the associated network-attached memory question. So you see, we go more and more into virtualization of systems. This also was, in some sense, asked in my keynote from yesterday. I think that technologies, when developed for such type of system, finally we also helped to really realize virtual supercomputing, high-performance computing as a service, like we do today, maybe with a single node or with farming type of applications. So that is one of those unconventional architectures where I believe that those codes that we have in the Human Brain Project really will profit from in one or the other way. I have shown it in two compartments. Of course, such type of technology might also be realizable within one system just for the benefit of explanation here. I've done this. Just one last word of this talk onto the question of what do all the activities that we do in the Human Brain Project? How do they touch these issues? We do pre-commercial procurement and, again, the same questions that I have asked so far are asked to companies. They know the patterns of, let's say, requirements that we have in the Human Brain Project running on pre-exascale, to be run on pre-exascale HPC platforms, and, of course, our mode of operation. We want to procure those R&D services from companies and for that we get them technical goals, dense memory integration, integration of visualization, dynamic resource management. So this is part of the questions I have asked. There is a timeline of this PCP process and we are already now entering phase three. So you see we had five applicants. We have chosen from those five. Not we. Our international panel has chosen three of them. Then our international panel has chosen two finalists. They will both provide prototypes. These prototypes will already give us much more information on the future of technology than we had so far. So this will be finished within the ramp-up phase of the Human Brain Project. And if it is successful and partly I already know today it is, it will certainly define the final procurement of a first stage of a computer for the Human Brain Project that we have a good chance to be funded separately by the European Union. So the status is, as I said, we have a good response to the technological goals. We are just in this phase summary. The technology trends go towards increasing parallelism and deeper memory hierarchies. This sounds like a triviality, but this means something because we are already at a very, very high parallelism if we talk about 500,000 cores, for instance, on our blue gene Q. What we think, the simple road maps of the companies quite well fit with data analytics, but the cost of data analytics will be dominated by computing for sure if you go to very low resolution, high resolution. We need better and faster hierarchical memory concepts and data locality for the simulation that's very clear. So what the vendors offer us is by far not enough new, let's say, memory technologies like computing and memory with the agency of IBM and other technologies like I call cluster booster technologies are very promising. So the booster can easily scale to access scale. Clusters today cannot. These are the heavy-weight computers. They cannot scale in the next 20 years, as you can foresee that. And I guess it is more the other way around today that supercomputing and data analytics as fields as such as technology profit certainly from the guidance by Neuroscience. Thank you. Okay, we've got time for one or two questions. Thomas, I just ask you about the interaction with industry that you described. Is that something you expect will be, you know, like iterative over the life of the HPP, for example? Do you see that this is going to produce the technologies that are more... At least part of it. At least it allows us to... And we have feed already to steer companies. I can name two of them, for instance, for instance, Cray, for instance, IBM, to really look at their roadmap. And I think already this small project I'm talking about has changed the roadmap a little bit towards what is our need. But it is not only within the human brain project. So the idea to, let's say, to support or to really interest other supercomputer centers and technology users to help develop systems, this is really shaping the whole field. And that's the reason why I said finally the technology development profits a lot from the application field like the Neuroscience. That was one of my motivations, really, to go into this field because I can foresee going down to one micrometer, for instance, with imaging questions, or to simulate on a level of, I don't know, 500 petabytes of degrees of freedom that you need for the full brain, that this is something that is unprecedented and I don't see it as necessary in most other fields. They would not know one field except maybe the particle physics they always can go very high up or climatology at a very low resolution but it's unclear to me at this time because many of those inverse problems would not profit from going to more resolution because the unknowns that they have in order to determine them are so high. Okay, would you like to join with me and with Hank Thomas again for his talk? Thank you. It's my pleasure to introduce...


Hi there, my name is Sandy Allnach, I'm an artist and paper crafter here on YouTube. And today I'm going to show you how to do a very simple wet-in-wet watercolor background. I'm going to use the Elfie Selfie Stamp Set from Lawn Fawn that just came out. And I've got it stamped onto some Arches Cold Press paper, it's got a nice texture to it, a nice rag or 100% cotton paper. And I'm painting the water around the area where I'm going to put the background. You could do the background after you paint the images, but I find that if I screw up the background, I might not want to spend the time painting the images. So on something like this, you might want to try it first. I did stamp this in a MISTI so that if I decided I wanted to re-stamp it and start all over, I could do that. The little umbrella is not attached to his nose, I have it stamped above because I'm going to draw that in later to connect it to his little trunk. I'm going to take three different colors of Daniel Smith watercolor paints and drop them into this wet area. I've just painted around everywhere where I want the color. I haven't painted the water right underneath of the umbrella because I want that one, that area under there to be sheltered. So little bird is sheltered by his friend, the elephant. And I'm dropping color in. I want you to note what those edges look like, there's these little tendrils coming out from them. And that's blooming because I had a pool of water that all of this color went out into. And this is one look and I'm going to show you a different way to do it as well in just a moment. But when you have this pool of water, the paint is moving throughout that water color. It's just traveling along and that's what's giving me the blooms. Some people love that look. I'm not a big fan of that look, I want a softer blend to it. So what I'm going to do is take off all that color and all that water and I'm not letting it dry like the amount of time you saw there is almost real time in showing you how long it took. I want to keep the dampness of this paper underneath and then start painting again. Basically do the same thing as I just did, but now I'm painting over damp paper, not on super wet paper. And you'll see the difference in how the color starts to blend when I put a second color in there. My paint is not super puddley at this point. It's wet and there is plenty of moisture in there but it's just not puddley the way it was when I put all that water on there. But look at the difference in how this blend happens. It starts to move a little more carefully, a little more in a blendy, blendy way. Not really sure, there's probably some technical definition for how this color is moving. But I just like the look of this better. It's looking more like the colors are sinking into each other and merging with each other instead of getting those big long tendrils. And this might be a good time to scrub back to that point where the color was mixing and see the difference. And you could put less water or wait for the water to sink all the way into the paper before getting to this step instead of painting and then repainting, but it's always helpful to practice the first time and just see where you want the colors or are the colors the kind that you want. You could change colors in the second painting of this perfectly well. But I just, I like how it looks in the second pass of this and doing that rather than trying to do it all in one fell swoop in the first pass. So I'm adding these colors back in, again being careful not to put the red, blue and yellow in too much proximity over and on top of each other simply because red, blue and yellow when they all mix completely together are going to turn into brown. So you don't want to get too muddy with the color. You want to allow things like that, that blue that I tapped into the yellow will make green because it's only those two colors. If I added it with some red right in there, I'm also going to end up with the possibility of making brown. And that's usually not such a good thing. All of this is painted by the way in real time. So you're getting to see how the colors kind of mix out into each other. You may hit different results if you use different paints because different paints will have different amounts of the ability to lift as well as if you get something that's not as transparent as these Daniel Smith watercolors, you could end up with some mud because of the pigments being a little cloudier. So the reason that I'm getting this really soft light background color is because of some of the properties of Daniel Smith paint.  There's a set of six essentials that's two yellows, two reds and two blues. And I find I can do all kinds of stuff with just those six colors. So if you wanted to try something like that, just to see the difference between them and whatever watercolors you're currently using, that is a interesting way to go to be able to try out some of the colors and see how they compare. So once I have all that background dried, I started painting in with black, my little elephant and I'm doing him in a couple layers and I'm not allowing it to completely dry in between. You're seeing this all in real time. So I'm adding my wet and wet paint right into what I've just painted seconds before. I'll let it dry for just a few seconds so that I don't end up putting puddle after puddle on top of each other and just moving the color around with my brush. I am using a silver brush number eight and the silver brushes I find hold a good amount of water, a good amount of pigment, that sort of thing, but I'm careful here not to be adding straight water. I'm adding pigment mixed with water because if I add just plain water to this, I'm going to end up with a big white spot and it's going to bloom out into my my elephant. So be careful and make sure you mix your paint so that you're painting always with pigment rather than painting with water, unless you're looking to create that kind of a texture and get that to happen deliberately. So now I'm going to finish the umbrella and I did wait to dry those other two colors prior to painting the yellow because I didn't want to mess that up, that would have been a problem. And now I took a pen and I drew the curl of the elephant's nose, his nose, his trunk and finished off my umbrella. So here's my finished card. I just mounted it onto some card stock and kept it really simple but this was fun to do and I hope you'll try it sometime. The supplies are all listed in the doobly-doo down below and if you'd like to subscribe there's a link you can click on my face in order to subscribe to my channel. I put out three videos a week. There's more you can watch here and a watercolor class on my blog if you're interested in that. See you guys later. Take care. Bye-bye.


Hello, everybody. Welcome back to another AI video. In this one, I'm going to show you how to create one click, one prompt, faceless videos. And not only that, you're going to be able to create these videos, and they are monetizable on YouTube because they have great stock videos, stock imagery applied to them, and you have to, if you have zero technical skills or if you're in a time crunch and you're new to YouTube or you just need to get something done, this could be the solution for you. Let me give you an example. Okay, so I've done an example, and one of them here is I just clicked on this. Like, all I did was typed in to this, Battle of Stalingrad, and then I clicked on Generate a Video. Now, it's going to do some analysis and find the correct video, but while it does that, let me show you what it came up with because I've already run one example of this through. This is really remarkable. I'm going to go back to my VLC player here, and I'm going to hit Play and check this out. Have you ever wondered about the turning point of the Second World War? The moment that marked the beginning of the end for the Axis Powers. See how good this is? This is really, really high quality video, and it's footage that is selected and it's intelligently selected. I literally did not select any of this stuff. This was automatically applied. If I move forward a little bit, you'll see here, I'll give you a few more examples. Here's one. This is nice in Russian, but maybe I wouldn't have selected this footage. It's a little bit too saturated and greeny, but you can swap out footage, and I'll show you how to do that in a second. Let's take a little bit of a look more forward and then I'll show you how to do that. Another example here, we've got soldiers running up here with their weapons. A soldier that's been hurt in battle. And then to cap it off, the operation of Uranus, of course. So there we go. This is an example. Let's go back and let me show you what we've got here. So once I've clicked on create it, and I've created generate, it'll ask you a few questions like it does here. I'm creating this for history enthusiasts. I want it to be dramatic. I want it to be for YouTube. I'll click continue. And then that's it. It is now literally generating the video that you just saw. It's now in the process of generating. That said, it does take a few minutes sometimes to create this. So if you have other tasks you need to do, go attend to those and then come back in a couple of minutes and this should be cooked up and ready to go. I will come back when it's ready and show you the next step. All right, welcome back. So here is the first kick at the can here. From literally, remember, all I did was type in the battle of Stalingrad. Let's see what it gave us in this example. I'll hit play. I'll turn the volume down. Watch this. A single city could change the course of history. Welcome to the tale of the Battle of Stalingrad, the summer of 1942. Okay, so I was skipping through it. So a couple of comments. One, the accent doesn't quite work, as you can imagine, but the video and the stock footage that it selected is very good in my opinion. I'll just zoom forward here, a little bit of the stuff that I showed you earlier. But literally, if you want to export this as is, all you gotta do literally right here is click on export, export video. If you want to edit it, in this case, I do want to edit it and you wanna swap out some scenes, you can just type in what you want. So I could be like a change accent of voice to deep mail, something like that. Click generate. It's going to go ahead and process this. This is amazing. I'm gonna come back when it's done. It's regenerating the voiceover and it has nine things to go through. When it's done, I'll show you what it came back with. All right, it's done apparently. That was only took like 10 seconds. Let's see what it came with. Have you ever wondered how a single city could change the course of history? Look at that. That is fantastic. Unbelievable. If you wanna go in and go a little more, I just clicked on the edit media button and look at that, I can swap out some of these things. So here is the second scene doesn't really work for me, so I'll select the second scene and then what do I wanna do? I don't know, maybe I wanna swap it out. I can just go down here and I can replace it with something I upload or I can search for something like war and then hit enter and see what I find here and it will load up some different stock media so you're not forced to take whatever they give you. You can go ahead and swap it out. So I like this one here. It looks kind of like a cool little war shot so I'll hit replace and press though. It's gone ahead and put it over top of the old one and if I want to apply it, I just click on apply and literally it just does this and literally you have to have no technical skills and you're off to the races. Let me show you what this has done and then we'll go through the export process and then that'll be wrap it up. All right, so that only took a few seconds and if I scroll through the timeline here, let's just take a look right there. There's the first shot. Look at that, the second shot is replaced. It was literally done. I didn't have to touch a single button other than just do it. So I'm previewing it in 400 AP. If you want to go ahead and export it, let's go to that process. So for exporting it, if you like it, you can just click on this little export button right here and it says export video. You get a few options. If you want a free option and you're okay with the watermarks and if you're just getting started or you're just learning, you could possibly want to keep the branding and the watermarks.  If you want to remove the watermarks and remove some of the branding, which I understand if you've got a few bucks and that's your thing, you can just click on upgrade and then you can purchase it for, I believe, what's that, say $20 a month and you get 60 exports per month. 50 minutes of AI generation, which is not bad, but nothing great, but there you go. These are your options, but there is a free option and you can get it with watermarks and get used to creating videos on YouTube just like that. That's all there is for this video. Thanks for watching.


Hello and welcome to the session I am Deepika here. Let's discuss a question which says two concentric circles are of radii 5 centimeter and 3 centimeter, find the length of the cord of the larger circle which touches the smaller circle. Let us first recall the definition of concentric circles. Concentric circles are the circles which have the same center point. So this is a key idea behind the question. We will take the help of this key idea to solve the above question. So let's start the solution. Now we are given concentric circles C1 and C2 with center O and radii 5 centimeter and 3 centimeter respectively. That is O B is 3 centimeter and O B is 5 centimeter. We want to find the length of the cord of the larger circle that is C1 which touches the smaller circle that is C2 at the point D that is we want to find length of AB which touches the smaller circle G. A tangent is a line which touches the circle at only one point AB of larger circle touches the smaller circle at the point D the point of contact. Therefore T degree because the tangent at of a circle radius to the point of contact AB is equal to AB plus VD because the perpendicular of a circle we can say AB is equal to twice VD triangle ODB. So in right triangle AB we have by Pythagoras theorem VD is equal to O B square minus OD square or VD is equal to O B is 5 centimeter. So this is 5 square minus OD 3 centimeter 3 square VD is equal to the root of 25 minus and this is equal to root 16 and this is equal to 4. Hence VD is equal to 4 centimeter this implies AB is equal to 2 into 4 centimeter is equal to 8 centimeter because AB is equal to twice VD. Hence the length of the cord of the larger circle which touches a smaller circle is 8 centimeter. Hence the answer for the AB of question is 8 centimeter. I hope the solution is clear to you. Bye and take care.


What's going on everybody got Kyle and Shawn here relating sports cards from one box This is gonna be for Brandon T and be one box of 2023 Bowman's Best University football. This is breakers delights I do I am delighted to be ripping these that is true breakers delights Do enjoy these good luck here mr. Brandon saw dude shorts at the bar yesterday cheese People are crazy, man. There's a studio stars Joe Milton out of Tennessee studio stars We have to 25 that one's going to be Eli Holstein out of Bama Holstein We have a refractor that one's going to be Jordan Travis. Go nose Fracture base we have golds of 50 mankind lemon for usc To 150 is tray Benson out of fs you go nose God's a 75 another Eli Holstein to 100 is Dorian singer on the fuchsia lava auto And our first refractor auto is going to be Troy Franklin. Nice one there It was a bow Nick's favorite target at Oregon On the refractor base auto And another nice one we had to 50 that one's going to be um riley Leonard Elements of the game auto very nice. That's going to be Notre Dame's new qb Very nice riley there out of duke someone is a got a 50 on the elements of the game Very nice goal out of there and on the back another nice one is a um Drake may on the prospect patch auto There we go. Very nice box there again for mr. Brainin Drake may and we got a um And we got another nice out of there um player warren on the memorabilia Or unz very nice All right, he got riley and Drake there very nice one there for mr. Brainin get that right out to you sir. Thank you