So I hope you can hear me, right? No, you cannot hear me. Okay, so that's better. I can go away. Have you ever imagined how to use Linux in mission-critical systems like air traffic control? Imagine you're sitting in a plane looking outside and probably you're wondering, are these guys doing their job? And maybe my code is used somewhere in the plane, in the core systems for air traffic control. My name is Geroff Zingheim. I'm responsible at DFS for the operating system development and hardware standardizations. And in the next 50 minutes, I will try to introduce you into the world of air traffic control and Linux software development in air traffic control. The second microphone? Okay, so that's bad. You have another one? So I'll try to improvise while they find the technical solution, whatever. So let's go ahead. It doesn't matter. So we can improvise. We're actually writing to the topic the integration of hardware and software is very important to us. This talk is a memory of my former boss and mentor who happened to pass away just two weeks ago. So the title of my talk, using air traffic, using Linux in air traffic control, hardware and software platforms. The agenda for today is quite packed, so I try to catch up. At first, we start off with air traffic control for dummies. Of course, we need to know what's the world I'm living in, what are my perspectives on Linux, the history of Linux in DFS, how long do we use it, what did we learn on the way. And then I want to show you what are the current challenges and what are the dos and don'ts we learned in the past 10 years using Linux for our core systems. Finally, I show you how the structure of our modular platforms look like today. And finally, I try to show you what will come next, what's the view for the future. So ATC for dummies. The domain I'm living in is quite different from anything else you know probably. I'm living in a world where radar systems are 30 years old, where we have floppy disks still running the software for radar systems and they still run fine and are in good shape. We have departments taking care on these parts and they actually can desolder chips and exchange them with FPGAs and stuff like that. So this is the world I'm living in. What is air traffic control by the way? What is our core business? Probably you'll think of these guys sitting around doing some gestures, showing the plane where to go. Yes, this is air traffic control too, but our systems look more like that.  He's seeing lots of planes. He's seeing information on these planes and he's talking to the pilots and giving him commands where to go. Sounds easy. These people are always working in pairs. One is the controller who is actually doing the talking to the pilot and the other one is organizing all the interfaces to other air blocks, to other air traffic centers, etc., etc. And as you can see, there are lots of systems behind and our job is of course to provide these systems, to build these systems and nowadays most of them run under Linux. If you take a look in the sky for one day, you can see, sorry, over Germany, but you can see roughly 10,000 flights per day going up and down, flying around and in order to understand this big mess, a short introduction in air blocks. We have roughly two different kinds of air blocks. We have upper airspace. This is everything flying around over countries and we have the lower airspace. This is everything starting and descending. Sounds easy. Why should you separate these two kinds of systems? Because the speeds and the movements the planes make are quite different. As you can imagine, if a plane is flying over a country, it will not so often change its direction but will go with a very high speed in contrast if it's starting or landing. Sounds easy. So what are the systems behind? The systems behind are core infrastructure, are safety critical infrastructure and one important aspect just in advance. We are not into security. Safety is the topic. Safety is more important. Safety means our systems have more or less direct impact on the lives of others. So we have to take care that the safety of the systems is guaranteed. In case of doubt, we have no problem if the system fails but it should be a determined fail in contrast to security topics. So we have special requirements. For example, some of our integration requirements, we could not take a microphone like this, this is bad. Imagine you want to talk to a pilot and your microphone stops working, this is bad. So we need application support for the whole life cycle of the system. Okay, sounds easy. What's the life cycle of the system? The life cycle of a system is easily between updates, eight years. Example, the current system for Europe, which is developed in cooperation with DFS, is in development since 15 years and it will go live end of this year. So this is what I'm talking about by application support for the whole life cycle. Of course, we have high quality standards. We will jump into them later on. And we need proofs that actual the systems work, paperwork alone, a certificate or a document, yes, yes, we can fulfill this is not enough. We actually do tests, even if there's enough paperwork and certificates, existence and reality shows that we are right. We discover failures. What these failures are, I will show you some small examples. Of course, you can bet, we don't need any single point of failure and we need fallback systems or system architectures are, we have redundant systems of course and these redundant systems have fallback systems. So if the primary system will go down, we have a fallback system which will take over. This has implications for the architecture of the systems. If you want to have a fallback system, you should have the most, you should have something which is completely dissimilar to the primary system. Means we use different CPU architectures, we use different operating systems, we use different applications and even different requirements and engineers developing these applications in order to avoid any systematic failures. What kind of environment are we operating in? Maybe this is also interesting. Of course, air traffic control is something controlled by the governments because if you control the air spaces over a country, clearly this is a governmental task. But it has been regulated by the European Union that private companies nowadays, DFS is a private company, can take over these tasks. And we have a lot of abbreviations here. Welcome to my world in DFS. We have a lot of abbreviations. I will try to explain them to you. Farbeck means one aspect of cost saving, of increasing the efficiency in airspace is organizing the air blocks in a more efficient way. In the old times, air traffic control was governmental and if a plane flies from here to the United States, you will cross different countries and every time a different center will take over, this is not efficient. It is better to create the air blocks in a manner that they follow the roots of the actual airplanes. This is what Farbeck nearly means. We have other programs and regulations like CSAR stating that please guys, sit together and know it's more like a command, sit together and find a way to create homogeneous systems, develop them together, create system-wide information management, don't create your own solutions. We have a free market nowadays. We can take over air spaces in different countries and other aeronautical service providers also can take over air blocks in Germany. And of course, last but not least, we have coast regulation by the European Union and this has a strong impact on our daily work. In the last one and a half years, we were able at DFS to reduce the cost for the customers by 23%. And Linux is one important point. The Linux platforms, how we achieved to save this money. So what about the history of Linux and DFS now? We started using Linux in a time where the systems currently in development were still developed for systems with Alpha and True64. When I started at DFS in 2010, we had the last big go live of a big primary system running on Alpha, True64. At that time, you couldn't even buy the machines anymore. We had stocks of machines and this is the time we are living in. But even five years before DFS thought about that, we have to think how we create the systems after Alpha doesn't exist anymore in this architecture. What can we do? And at that time, the Linux Competence Center has been formed and the idea was to provide centralized knowledge for Linux and Linux related topics, hardware, and so on and so on, centralized in DFS. At that time, we also established a partnership with both big enterprise providers, Rathat and Susan. Why Enterprise Linux? It's quite simple. I will explain to you later in the talk what exactly we need from these enterprise distributors. Because, okay, if you first think, yeah, okay, it's a big company, safety is something, yeah, okay, enterprise is great, but what can we really get in reality considering these life cycles, these development life cycles, you can already imagine that if we go live with the systems, it's out of support. So we have something else from these distributors. What that is, I will explain it later. In 2008, the first systems started growing and we thought, okay, we should create a unified solution, the so-called DFS Unix. DFS Linux, the idea was to implement the requirements of our customers for the various products we have in use to implement these requirements only once. Of course, the operational processes for all of the products are the same, so we should implement the requirements only once. In 2010, the idea was to extend this first solution to a platform with the main goal to harmonize the configurations. At that time, we had roughly 1,500 systems in our corpus running on the Linux and it was already foreseeable that the amount will increase tremendously in the upcoming years and the question was how to react on that. And at that point, it was, I think, a very farsight solution to set on this puppet stuff and to say, we are going to use this kind of concept and enable the users to write their own configurations. Besides this standard we created, we thought about how to get our hardware. The systems before, they were bought as appliances. So appliance means we buy the alpha hardware with the operating system together. This is not possible anymore, so we have to provide something here and the solution was create a hardware standard and make sure that these systems in the standard can run on the Linux. Sounds easy. In 2015, the number increased, the number of systems, the complexity increased and the cost pressure increased and this forced us to think in different ways. So we extended this hardware standard to the hardware platform. What that means, I will show you by end of the talk. Finally, in the last year, we cracked the mark 10,000 operative systems running under the Linux platform at DFS and all of them are using our modular hardware standard and this is why it's something away. This means 100 systems, we buy a factor 10 more systems for testing, development and so on. This is why for one platform instance, we easily buy 1,000 systems. So what did we learn on our way? Do's and don'ts. In the following slides, I present you some examples and I try to explain them as detailed as possible but I think it will not be possible to dive into every detail and if you have questions, please write them down, come back to me later, we can talk about that. CT1, what does it mean? Welcome to the world of DFS. We introduce abbreviations for everything. Challenge technical number one. So you have the real DFS feeling. The first technical challenge, a Wacom driver. Well, okay, that's easy, a Wacom tablet.  It's used everywhere and so also we use it in DFS easy but the use case in DFS is quite different. This is where I have a problem with a microphone but it doesn't matter. I will show it to you. An artist makes a movement like this and DFS will make a movement like this. So this is a problem. This is a problem when you consider that both the driver and the firmware is, of course, optimized for the usage of the general purpose. What happened is we had a major observation three years ago, no four years ago already, where some of the air traffic controllers found the bug and the bug was if you place the pen in a specific angle at a specific point, a press event was released in the middle of the screen. Nobody found this. Why should you do that? And as you know, the people who are working as air traffic controllers under high stress and once you detect one of these failures, they show up everywhere. So this is high critical. We have to fix it. Don't wonder if your standard driver and the standard firmware doesn't work. Luckily, we didn't wonder. We have customer tests for this and, of course, this past the customer test, the bug arise later. But we planned ahead for the support. In a case like that, if you don't have established connections to your providers and can ask them what's the problem with this firmware? What's the problem with this driver? Can you please come over? You're in deep trouble. The solution here was actually fixing both something in the driver and something in the firmware and we had to update, we had firmware update, roughly 240 of these Wacom displays in the night. What makes it different? What makes it complicated to update something like that in a mission critical system? You cannot just take down the screens. There are fixed intervals, which are harmonized worldwide where it is allowed to play in updates and you have to synchronize with that and this increases the cost even more. Second example of a technical challenge. Intel IMT. Maybe better known under the name of Vipro. This is a technology probably existing in all of your clients and it provides remote accessibility to your client systems. A very nice feature and there's also Linux support. And the Linux support is a part of a Windows tool written in a bad programming language and it's ported and it's rotting around. So we bought the hardware in 2014. We want to go live. This is actually the system we built for the future. We want to go live by the end of this year. And in 2016, Intel told us, okay, the support is dropped. There's nobody anymore. We sack the people. Oh, that's bad. So don't rely, maybe this is obvious. Don't rely on binary drivers even if they are provided for free. Just don't do it. When you end up with a door, it's closed. There's nothing behind anymore. What you want to do is you want to use open source tools. You want to have established connections again with your providers so they have a real chance providing your solution. You want to assert the lifecycle for the complete lifecycle of the application. Of course, this did fail in that case. And you want to have alternatives. Luckily, we had alternatives so we could figure out a workaround using a different technology so we can go live. A small blocker, but this is a very serious topic. Imagine we have everything ready for go live and we cannot access the machines remotely. This is bad. Third technical challenge. Deployment solution. Of course, obviously, if we have 10,000 systems, we need some kind of deployment. Okay, that's nice deployment. That's easy. If you consider that we have two very different cultures in air traffic control. One of them is the guys living in a tower system. This is what you see at all the airports. And the other guys are sitting in the center doing the control of this lower and upper airspace. The systems, obviously, are completely different. Tower systems are decentralized and center systems, it's already in the name, they're centralized. The deployment solution look the same. It doesn't work. So the challenge here is we need a deployment solution and we have a lot of legacy code. Where does this legacy code from? Very easy. All of you know DevOps. DFS does exactly this, not. We do it completely different. We do the development. We test and test and test and when it's finished, it goes live. The people working in first and second level support have kind of driver's licenses. For all of their actions, they take in the systems. For each system, there's a driver's license. And obviously, finally, they are personally responsible if something goes wrong. So this is a source of tools, of course. If these guys are responsible, they start writing their own tools in the years. Now these tools exist and you provide them a new solution. The challenge is we know the better way. We know state of the art technologies. We know how it's really done and the customer has their own solution. So don't use puppet master. Don't use live reconfiguration, even though it's possible and very nice. Don't use it. Don't use all the nice features existing. It doesn't make sense. If the person wants a chessboard, you can write an application on an iPad. It's nice and expensive, but it doesn't work. If the user wants to stick with this old ladder, don't provide him a Porsche. Very easy. So what you really want to do is he wants to go to the people who are responsible for the first and second level support with a completely different mindset than any developer because they're personal responsible and they feel that way. You want to go to them, ask them what you really need and just implement that. This means focus on the real customer value. The real customer value is, in our case, of course, the people who are doing the operations. And understand that even though you have all these nice ideas, which is very nice and of course they are better, but we only create costs. We create no value. And we did take a wrong path in the beginning. We tried to force the system management to use a different way of deployment. And of course it was better, but it didn't work out because of cultural problems. Interestingly, interestingly, as soon as we started providing them the solutions they needed, they asked, can you please provide us a better solution? Okay, it was two years' work and then take over at the old point. Now let's start diving into the real challenges. The first real challenge, you can see, C1, no technical challenge anymore. The real challenge, there's a gap in the delivery. What kind of gap could this be? As I mentioned earlier, our job is to do the integration of the operating system and the hardware. Challenges? The hardware is delivered by somebody else than the operating system. So we have to take care on the integration somehow. Okay, that's fine, easy. What's in the gap? What do we have to consider for a specific Linux version? Linux versions, in my terms, is something like REL7, not a kernel version, an enterprise Linux version. For a specific Linux version, we have a hardware and driver, hardware and firmware version for every hardware component. Can this work together? Obviously this is difficult because the operating system has been released in an earlier date in the firmware later. Who will test it? Drivers and modules. You've seen an example, vacuum driver. And obviously also tools you need for the hardware functionality, like IMT. These tools and these problems with hardware revisions are in kind of a gap. How does this gap feel for DFS? And this is where we jump into the development processes. A short introduction into my world. So structured software development obviously uses some kind of model, like the V-Model. And you start off with a high-level requirement and you say, there's a hardware unit, it's named X, and it shall boot. And it's provided by some independent hardware vendor. Somebody has produced it, fine. And it shall boot with Linux Y. Okay, that's very easy to understand. And then it should work, shouldn't it? Okay, and we know some more details. We know the low-level requirements. The low-level requirement would be, okay, we have a driver Z for this module included somehow in this hardware unit. And this shall boot with Linux Y. Easy. This is the world of DFS. We write the requirements, we say what we want. And then any distributor will say, okay, fine. The driver is included. And it is included for Linux X because it's newer. Nice. But we need it for the old version. Okay, we can make a backport, fine, okay. We take the backport, we try it out, and maybe there's a bug. We ask them, by the way, how did you test them? Or we did only compile it. What do you mean by test? This is the test. We did do it. Well, okay, we mean something like you use the actual hardware and find out whether the driver really works. Ah, no, this is not our responsibility. This is, of course, we don't have every hardware. This is where the independent hardware vendors come into the game. They should do it. Okay, fine. We have support contracts. We ask them, okay, yes, okay, we test it. And our specific problem is not tested. Yeah, because there's no business case. You have to do it yourself. So you end up with something like this. This is visualization of a Lawrence attractor. The people laughing are probably also physicists. It's a chaotic system. And everybody moves around in a chaotic way. Everybody points in all directions and there's no solution coming. So this is where the gap is. How can we fix something like this? Actually, what you don't want to do is you don't want to blindly blue-eyed. You don't want to rely on what the contractors say. You're talking in different languages. It's not bad will, it's just different languages. You have to somehow make the languages compatible. At first, what you want to create is, you want to create specific customer tests and provide them, provide these test cases to your manufacturers. So they have a good chance to understand what you really need. And the best way where to put this is obviously in frame contracts. So they can even see in advance, do I want to take this bit or maybe I'm the wrong partner? Maybe I won't do it. The second thing you want to do is, you want to create an internal document for the company, an ICD interface control document, writing down all the hardware components you have and all the operating systems you have and test them using your acceptance tests and make a matrix what works, what doesn't work. And if you do that in a modular way, you can save in a tremendous amount of costs. The third thing you want to do is, obviously to steer and control the support. If you want to escape this Lawrence extractor, somewhere you have to manage to talk to your providers and help them understand what you really want. And the last point, obviously, you need developers in-house and external ones who do the actual work. What's really the point here? The point here is that results are only there if you can understand them. Even though the technical solution may exist and may work out perfectly, if there is no understanding and customer side, what this means, the solution doesn't exist. And in order to make the solution visible to a company like DFS, we need these test documents. We need these requirements. Anywhere else, it's not there. Second challenge, lifecycle. Okay, I told you about that before. We have eight years of application lifecycle and we buy hardware, we buy operating systems and we need support. And once we go live with the systems, the operating systems are out of support. Okay, that's bad. And we have lots of safety requirements hindering us, even if there's a patch and even if all the documentation is there, we have to safely approve the system and this will take at least half a year. So that's a problem. We have servers level one and two with these driver's licenses. And how can we deal with something like this? Obviously, you cannot rely on manufacturer support. Even if they understand what you want to do, they will put a price tag that's incredible, ridiculous. It doesn't work. So you have to find another way to make sure that the lifecycle works. So what do we do in DFS to get a grip on that? At first, we need revision control down to the firmware levels. We need it in order to reduce the complexity. If we don't have control about what hardware is in use, and this means hardware, the revision number on the PCB and the exact number of the firmware version, we are in deep problems. A real example, we bought 90 network cards and we do a test for switch over and two of them don't work properly. They have a different time interval for takeover. So what was the problem here? We found out that the two network cards were manufactured in a different country, Taiwan versus China. This was the only difference. And obviously, you want to know that in advance. The second thing you really want to do is create a modular standard. What that means, I will show you in the next part of the talk. And this includes also the repairs. What means repairs? If you know that you buy hardware and for example, but could be anything else, NVIDIA cards and you know that the diodes of the NVIDIA cards at the graphics port, they break regularly. It's better to take all of the graphics cards, solder them out and replace them with better ones. So this is the level we have the knowledge about the systems and what we do.  Third challenge, the regulations. And this is really a big one. Easy to solve, but it's a big one. In DFS we have lots of regulations considering the software. For example, we have ASR 6 and ED1 whatever and ISO and blah. And of course, we also use the state of the art processes. What does it really boil to? Please make your software structured and write the requirements document and stuff like that and write good acceptance tests and so on and so on. Okay, that's fine. And finally, we have the DFS core processes. Nobody can know them. Only us can know them. And somehow we have to make this compatible with the outside world. We look like this. So quick introduction for dummies and if you can take one thing home, this would be the thing. How does a software development process look like for safety critical systems? You remember this V-Model? On the left-hand side, you have the requirements down to the code. On the right-hand side, you have the test cases. If you start linking the requirements to the test cases, high-level tests and high-level requirements, you have software assurance level 4. If you can link down to the lower level requirements and link them to the test, you have software assurance level 3 and you link it down to the code, then you have assurance level 1. To the code means every code part has its requirement. Every requirement has its code. And this is how the open source community looks like from our perspective. What to do? There's no common development process. How can we accept the results? The technical solutions are there, but we cannot take them. What to do? Don't underestimate, and this is very important, don't underestimate the differences in cultures and development processes which it has on your results. The solution is quite easy. We just agree on the deliverables. That's easy. And once we agree on the deliverables, we can use our distributors, Rated and Sousa, we can ask them to shield us against these open source community by telling us how do you develop, how do you test. We write down the interfaces, how we interact with them, and we are fine. This is the trick. The fourth challenge is customer acceptance. When you think of a platform, obviously you think at first, of course. The problem here is, we don't own the production line because we have separated the first second level support from the development. So in the end, the guys responsible, they have to like our solution. So if we build a standard in a manner that we say, we know the better way, we end up with something like this. Obviously not what we want. If we want the customers to build something like this, we need to provide them the right modules. We need to provide them the results that they can do their work. How do we do it? We built a flexible modular standard, and this is what I will show you now, how it looks like. We have to document it, we have to keep it simple, and we have to empower our users and our customers to use the standard. Last but not least, challenge testing. We just talked about this in the beginning of the talk. Yes, you can automate. And if you automate everything, you have great tests, but never forget what your test coverage should be. If you don't test what the customer wants to have, this is a problem. And if you know your customer test too good, you end up with something like this. This is maybe not so good. So how do the modular platforms look like today? We have, on the one hand side, we have a hardware platform which includes all the server systems, the client systems, displays, KVM monitors, et cetera, et cetera. We have shared common requirements we agree upon in a board, and we provide service for the frame contracts. We have different persons, not only us, but different persons in product management who take over responsibility for these frame contracts and help if there's a support case. On the other side, we have the Linux platform, of course. It uses this enterprise Linux and implements specific ATC requirements. I won't go into details here if you have questions, ask me later. The point here is we have to provide the same modularity here on that level as we have for the hardware because the hardware drives the operating system. And obviously, our job in the Linux platform is to make sure the integration works. All of these standards are agreed upon in an architecture board, and I think this is unique for a big company like DFS. We have an architecture board where we sit together in every month and discuss what's coming on in the architectures in the near future, and we agree upon our standards and we talk about exceptions and why these exceptions should be accepted. So actually, how does the system architecture look like? What means modular? Modular means if we consider, if we keep in mind that in the end everything together should work, including firmware and so on and so on, obviously a hardware system includes the hardware unit and the concrete adaptation, like firmware, liver, biosettings, and so on and so on. And in order to reduce the cost and make it a platform and not single towers, which don't interact with other people in DFS, we have components inside the modules. A component could be a monitor. A module could be a graphics card, network cards. If we have once approved it, if we have once certified it, you can plug it into any solution. The same holds true, obviously, for the Linux platform. It should not be something like a legacy code. It should be very modular and if there are two different kind of deployment solutions, okay, that's fine. We provide the modules, the customer can use it, or he can leave it. Okay, maybe I'll skip that considering the time. So actually, what is inside? The core components of our Linux platform. The first thing is, in the core components, we have to provide the basic functionality. The basic functionality would be we have to have a Stage 1. We want to boot and install the system, obviously. Then we want to configure the system. Okay, that's fine. We can use Puppet, but not everywhere. If some customers in some tower systems don't like to use Puppet because they have a real reason for that. They have non-unix systems, window systems running. And they cannot use our Puppet deployment and our Puppet configuration for doing their job. Okay, we provide them something else. And two years later, they see, oh, there's other tower. He starts using Puppet and he's going better. I want to have a two. So we provide this flexibility on that level. And last but not least, we have an operational mode where we can do stuff like reconfiguration of the systems and where we can do something like monitoring and so on and so on. These are the core components which are coming every time with the platform. And then we have some kind of optional stuff which you can use, but you are not forced to use. It is one thing to create a platform and say, okay, if I want to have something like, I want to boot SUSE and Red Hat, so I write my own boot loader, I write my own code. Yes, you can do it. But in the end, you cannot make a better job with limited manpower. You cannot make a better job than the distributors. It's better to rely on the distributors' solution and write your own binary code which comes after that. And then we can provide these modules. So what are the technologies we have inside? This would be a completely different talk. We use Puppet. And over the long term, maybe two words on that, over the long term, there are big pitfalls if you use Puppet. If you start using Puppet and consider that the idea of Puppet is you write the nice configuration and afterwards it's very portable. Okay, nice. A life cycle of eight years is not too long. You should consider that maybe you expect that everything works the same with the new distribution. You just make an update, but the configuration, in fact, stays the same. It is not. So what we did now is we reduced the allowed command set to the basic stuff with what we really can control which will not change and the things like template stuff and so on and so on. We create our own solutions because over the long term they are more stable when it comes to the interfaces. So finally, one different view on these platforms, how can you make this platform and it's on the one hand side, it is safety and on the other hand side, it is flexible. You have to use the language of your customer and the language of the customer is like that. We use requirements documents and test documents but here I show the requirements documents. If you want to make it modular, you describe the hardware standard in one set of requirements, the blue ones here. You describe the Linux platform part in another set of requirements, high-level, low-level design document and so on, the green ones and the customer brings his own configuration, his own requirements and says, okay, I'm compatible with this platform and I use these interfaces. What's the big difference here? We only have to agree with our roughly 70 customers, 70 different products. We only have to agree upon these interfaces and we can create all requirements very stable and they are not touched even if the customer comes up with some fancy requirements. So what's next? The next steps for us are when it comes to platform, we continue to shrink the core platform even more. We have reached the number of 10,000 systems and we have such a good user acceptance of our puppet configurations that we were able to give the configurations away to the product management and to the first and second level support. So we can take a step back and redesign our platform, focus it on the core concepts when it comes to hardware platform. What is the next step? Obviously we want to include more modules. There are a lot of legacy systems and they continue to be replaced and all the new hardware we want to include in our standard obviously. When it comes to technologies, we are currently developing the first ATC application using container technology, in that case it is Docker and it is the core component for networking. So quite important technology and of course we will also include this in our platform and when it really comes to software development the biggest challenge for us currently is the security requirements. So far everything I told all the problems we solved are safety requirements. In the world we are living now, security becomes more important and we are rated as a critical infrastructure. This means we have completely different requirements demanding security and the problem here is that security and safety are completely different things. This is a completely different thing to say I want to create a safe system, I lower failure and it is somehow encapsulated in a box and nobody can access it then if you say I want to secure my system, I want to have secure software, I want to do for example live patching, I want to include software updates. Half a year rate is not enough. So hold on, solve that. This is really a big challenge for us. So to sum it up, what did we achieve in the last ten years? We successfully built this platform and it is widely accepted in our business and not even in DFS we are currently providing the operating systems for the European system for ICAS and this is relevant for the whole European Union. We have shown successfully that it is possible to create mission critical systems and fulfill these safety requirements with Linux, it works and in the end we achieved the results and we had a lot of fun on our way. So what is my main point? My main point is here, if I really understand the core, the core processes and the core results I want to achieve both internally of my customer and if I understand the community, that means you, you are actually contributing to our stuff. If I understand that it is possible to use Linux in a mission critical system. Thank you.


What's up everybody, Jason here with Jasper's Case Breaks.com 2019-20 Pinuni Obsidian Basketball Pikachu number four sold out 12 box case And this round of number block we're doing here is just for the pelicans So again Round of number block for the pelicans all numbered cards are atomized in one lot at the end of the break So everybody's gonna have a shot at that and again every spot gets a zero every spot gets a round of number from zero through Nine nice example if you get number three randomized to you with three being the first number next to the dash on the left side of the dash That would be your hit so for example we pull a Zion or a pelicans hit two forty three at two ninety nine That'll be yours for number three Thirsty out of ninety nine three out of twenty five forty three out of forty nine Etc. Etc. The number three block will get that hit our redemption cards go to spot zero even if we know it's a one-on-one It'll still go to spot zero and then of course any non-numbered cards are atomized to the group So this is just for the pelicans. Good luck. Let's roll it one and a five six times one two three four five and six Steven down a nick one two three four five and six Five down to zero Steven five four three eight seven six nine Matthew would one any one of ones will be yours Steven with two and Nick you have zero so any of our redemptions So they go guys, this is just the randomizing part one more randomizer for seven other teams random number blocks out And then we'll start the break guys appreciate it


Hi everyone, my name is Dr. Jabron Shake. I'm the Chief Resident of the Department of Dermatology here at the University of Maryland. I wanted to tell you a little bit more today about the program and the city of Baltimore, and I think it's a great opportunity that we have this opportunity virtually to discuss it, but I think that obviously we wish that you could be here in person. So Baltimore is a fantastic city. If you have an opportunity to come and visit it, you'll know that it's a city full of charming neighborhoods. We've got the Inner Harbor and Federal Hill, Fells Point, lots of fantastic neighborhoods, and the University of Maryland Medical Center is right there in the center of it, so it's really convenient to live in any of the nearby neighborhoods, and you'll be close to the medical center. And then the city itself is really closely adjacent to Philadelphia and New York City and Washington, so it's great for conferences and weekend trips alike if you want to get out and see those cities. And the cost of living is pretty low, which I think is a huge perk during residency, because you'll have plenty of money to spend even after your rent and everything like that. The program itself, it's an excellent program. I'm coming to the end of my training here, so I can tell you that everything that I wanted to get out of my dermatology training, I think I really got it here at the University of Maryland. You'll get really fantastic surgical training, both at the VA and with our Moe surgeon, Dr. Maxoumi. Because it's a small program, you'll have an opportunity to work with her a lot one-on-one and do some pretty advanced cases, which I think is, again, a real strength of our program. We serve a really diverse population here in Baltimore. It's predominantly an inner city population, but then we also have the suburbs that we rotate at in Columbia and Millishville, so you get a mix of suburban and urban care. And at the VA, you see a lot of patients who are coming in pretty rural areas. You see a mix of white and skin of color, and that's, I think, a really fantastic opportunity to see the broad spectrum of dermatologic illness. So I think our faculty is incredibly supportive. Whatever your long-term career interests, whether you want to pursue fellowship, whether you want to go into academic or private practice, you'll be well supported. If you're interested in doing research, either clinical research or basic science research, during residency, you'll find plenty of opportunities. Our chairman, Dr. Horniac, is actively engaged in basic science research, and there's always opportunities to get involved with his work and, of course, quality improvement projects within the department. So, yeah, I think it's a fantastic opportunity to learn dermatology in a cool city. I think you will learn more about our department on the website and other places, but I really hope you have an opportunity to see it and get a sense of what we're all about here at University of Maryland. Thank you. Hi, everyone. I'm Dr. Max Weddington. I'm one of the senior residents at the University of Maryland Department of Dermatology. So I just wanted to give you a little information about our program, and the aspect that I'd like to talk with you about is the culture of our program as well as the culture of our institution. So I'm originally from Oklahoma, Oklahoma City, and I did my medicine years at Loyola University Medical Center outside Chicago. And when I was applying for residency, both for my preliminary year as well as dermatology, the thing I was really looking for was what is a good fit for me in terms of the program, the way that I interact with my faculty and the way that I'm treated. So our program director, Dr. Marcia Doriscoll, is incredibly supportive. Our chair, Dr. Tom Horniak, is very interested in research, clinical research in addition to basic science research and resident wellness, and he really wants to make all of the opportunities that he can available to you to pursue the dermatology practice that you want in the future. And then all of our other faculty have been incredibly supportive the whole time that I've been at the program, and Betsy Satoski is our program support, really. She's kind of our mom of all of the residents. She always puts little treats for us in the refrigerator, has fresh cold drinks for us to refresh ourselves on these hot summer days here in Baltimore. So they've always made me feel welcome, even though I'm not originally from the East Coast. This is my first time living here, but for me that was really important and looking for a program was a place where I felt like I was part of, not just a collegial culture, but a family. And that's the way they've made me feel over the past year that I've been here.


Hello and welcome to the concluding lecture of this course on Introduction to Launch Vehicles, Analysis and Design. In this final lecture, we will attempt to take an overview of the course that we have gone through and we will also look at possibilities of future reading in this very important area. So, let us begin. So, I am sure you would recall this slide which I had put in my very first lecture as the introduction to the course when we started. We have now completed our journey of eight weeks starting February 15th and during this period we have looked at many aspects of launch vehicles, the analysis of their trajectory and the design aspects as well as the design of the configuration of multi-stage vehicles. What I would like to do is to kind of take a look at what we actually had started off as our overall plan and to see if we have been able to reasonably adhere to it and provide the information that was intended. So, let us begin our final journey of this course through closing remarks. If you recall, the broad course objectives with which we started was to understand fundamental principles governing ascent mission design including configuration design of launch system and the trajectory design. With this objective in mind, we had put the following contents in front of us which we intended to cover during these eight weeks that is ascent trajectory analysis and design containing mathematical models, various trajectories, real system effects such as drag, gravity etc. Then in the context of multi-stage rocket configuration, our intention was to look at the staging solution, its sensitivity, series and parallel staging, optimal staging. This is all what we had intended to cover. The point is how did we do? Did we fare well? Let us look at it. So, what has been achieved? If you just recall the material that we have covered, we have created a set of simplified tools and methodologies to set up a space mission configuration and trajectories. So, the first objective has been reasonably served. We have also provided methodologies for design of multi-stage rockets and established basis for optimal procedures. So, we have done that as well which was also the second objective. In addition, we did something more than what we had intended or what we had planned for. In terms of introducing a few special physical effects such as jet therapy, we also looked at some special current concepts in the form of air-bithing rockets, photonic rockets and we also introduced ideas of fast transfers, launch window and the reentry missions. So, this was something which we did not explicitly intended but as many of these in some way were related to the basic launcher configuration, I thought it appropriate to include this as part of our course. Question is, is that all? Is there anything more that we can do? Here, I would like to say that yes, in a course which spans only 8 weeks, we can only touch upon some aspects and we have chosen the ideas that we have presented in this course. There are many aspects that are typically part of any practical space mission design. I will only list couple of them but there are many more that you can think of. So, there is a ballistic missile trajectory solutions. If you recall, I did introduce the basic idea of ballistic missile concept, left it at the conceptual level in terms of what it intends but did not give a detailed trajectory solution. So, one could look at those detailed trajectory solution and to some extent relate to the ballistic reentry trajectory solutions that we have seen as part of this course. Another aspect that we have not touched upon and it is an extremely important and critical aspect is the separation maneuver. The separation maneuver is the backbone of all space missions that use multi-stage rockets and hence needs a separate study of the separation dynamics, the various mechanisms and the associated solutions as well as safety measures which are part of such design procedures. Another aspect that we have not looked at explicitly are the attitude dynamics and control of launch vehicles which is again an essential ingredient of the ascent mission trajectory design because during atmosphere motion there will be disturbances and in order to hold the trajectory as per requirement, you need to provide some amount of control. You would also have realized that we made an assumption of zero angle of attack during the ascent mission. One of the ways in which that would be ensured would be through a closed loop attitude control and then of course there are other aspects of launch pad dynamics, the lift-off mechanisms, the other issues of modeling the atmosphere, the recovery of payloads through different reusable technologies, greater emphasis is on development of propulsion for future, the propellants for future. So, there is a whole lot of material that can be looked at. So, I hope that this short course of 8 weeks has given you sufficient background material but more importantly I hope it has also given you a lasting interest in this area of launch vehicle analysis and design and that you would be able to sustain this interest with additional material, reading and be able to practice some of the things and contribute to this important discipline that all of us feel is going to be the future of the mankind. So, with this let me wish you all the best for the exams and bye for now. Thank you.


An elevated Los Angeles freeway closed for more than a week because of an arson fire is expected to reopen ahead of Monday morning's commute. A day earlier than previously announced and weeks ahead of the original estimate, California Governor Gavin Newsom said Sunday, the November 11 blaze, fed by flammable materials stored under the roadway in violation of a company's lease, shot a mile-long stretch of Interstate 10 near downtown, snarling traffic as repair crews worked around the clock. Newsom had said last week that all lanes were expected to reopen by Tuesday, but moved it up to Monday after significant progress in Newsom said recent safety inspections showed the span was safe to start reopening Sunday evening and that the freeway would be fully operational before Monday's rush hour aerial video from CapTV slash ABC7 Los Angeles showed some traffic already on the freeway on Sunday night.


so the ravens they've added yet another running back to the mix and his name is tyson williams now as we all know the ravens they have a stable of running backs they have a plethora of running backs they have this long list of running backs that are currently on the team and the list just keeps on growing of course there's mark ingram there's gus edwards there's jk dobbins there's just as hill there's kenyon barna and now there's tyson meadows as well and and it's interesting because i know a lot of people whoa what's tyson meadow what's he gonna do why the ravens sign him first off who is that well he's an undrafted rookie free agent uh from brigham young the ravens signed him yesterday yesterday was friday today when i'm recording this is saturday when you see it hey who knows because you know stuff be coming up anyway and real quick i appreciate y'all for helping the channel get to 29 000 subscribers that's i appreciate that a lot man because that's that that don't happen without y'all y'all know that already that does not happen without y'all so i appreciate y'all man thank you thank you thank you um but with ravens they they got a lot of running backs and a lot of people may question why so many running backs for what what's the point why why they bringing on this undrafted rookie free agent running back well because mark ingram he's good gus edwards he's good jk dobbins he's good justice hill little banged up kian barna little banged up so you cannot just have your top three the guaranteed top three they can't be the only ones taking reps and the at the time that i'm recording this is before they have their scrimmage tonight on saturday evening i think it's at five p.m but i'm recording this at uh two p.m so they're gonna have their scrimmage in a few hours from now um but right now they're a little banged up at the running back position and again like we said when they signed uh johnny townsen had to say hey did sam cook's job is not in jeopardy not in jeopardy at all because a lot of people um when teams make depth signings throughout training camp it can scare some people it can frighten some people they could be like oh my goodness what do they sign this person for what do they bring it does this mean something for the guy in front of them are they gonna lose their spot and sometimes depending on the case it is possible but enough times teams will bring in guys for depth depth depth depth depth even if it's just training camp depth because training camp is exactly that is training so you don't want to overwork your starters you don't want to overwork your guys who are like sort of guarantees to make the roster because they got to be ready for a season that's coming up very shortly like raven season starts in 15 days from today from saturday so tomorrow sunday we will be exactly two weeks from the start of raven season oh man that like that gave me chills saying that out loud man we will be exactly two weeks from the start of raven season and with us being closer and closer to the start of the raven season it is an exciting time for us fans it's a fun time for us fans but it's also a frightening time for players reason that it's such a frightening time is because it's almost cut down time man it's almost cut down time it is literally right around the corner because we have like about a week left before before they have to get to either 53 or 55 man i always forget what it is this year but cut down time is literally right around the corner because this time next week i believe is within this within this week maybe i got a double check on that because when there'll be a week a week heading into the game heading into their first regular season game the week prior before their regular their first regular season game they're in regular season mode so they currently have 80 people on the roster tyson williams was the 80th spot so with them currently having 80 people on the roster they have to get down to the 53 or 55 so they have to get rid of either 25 or 27 people who's trying to do some quick math right there that was a little scary so there's some people that may be obvious cuts like the extra punner the extra kicker that they have uh and at least one quarterback who that is it's obviously gonna be between and even though sometimes strange things happens but i don't expect them to at the quarterback position but that last spot is up for grabs between trace and tyler and we'll see who ends up getting the nod i know who i think is gonna get it but we can talk about that another time so one of those is going they're gonna go they're gonna be cutting at least one and then another one is again the obvious positions the obvious extra punner the obvious extra kicker because they're not gonna keep two kickers they're not gonna keep two punners but then stuff on all these other positions as far as uh running backs as far as receivers tight ends offense defensive linemen linebackers corner backs safety debt all that stuff that's where it gets tricky there's nothing that's really obvious there it's nothing that's obvious because you obviously you i mean there's some obvious because you obviously got your guys that are locks to make the roster in some of those spots but then you have some guys where it's like hmm i don't know but so we're probably about a week out from cut downtime so i'm not sure what their schedule is gonna be like this week if they have any more scrimmages or anything but this is it so like i was saying this is a very uh as the season approaches this is a very scary time for guys who are on a roster bubble guys who sort of don't know their fate guys who don't know what that next move is going to be and there can be some guys right now and you feel bad for them but some guys just almost feel like you gotta feel like they know what's coming and one of those guys uh that a lot of reporters spoke about was jaleel scott somebody asked me um what percent chance do i give jaleel scott on making this ravens roster this year and i i think i told him maybe a 10 percent chance um that's not because i don't think he got ability that's not because i don't think he would be able to make it uh in the nfl as a wide receiver i just think the the numbers don't play in his favor they just they really don't play in his favor uh they i know jeff zrebek talked about it james and hensley talked about it how this camp he's he's almost made so many plays he's been close to making a lot of plays but just been coming up just a little bit short a little bit short and with him not being one of eric de casas picks at receiver i i just don't think his spot is safe man and they said the other day that he he he ended up tossing his helmet he just tossed it because he was just that frustrated to where he just tossed it he chuck clocked his helmet well chuck clocked tossed it he threw it down they said uh uh jaleel scott tossed it so there's that clear frustration you don't just toss your helmet for nothing like like we spoke about with chuck clock when he threw his helmet down you could tell that was a built up pent up level of frustration that just kept rising over time rising over time and he must have been continually being agitated over time and then with jaleel scott it just seems like with him he's this is this is his third year on the ravens roster but yeah first year he was stashed last year he was carried on the active roster and he played his first and only game in week 17 and yeah this is his third year this is his third year and to watch the ravens moves to watch them draft the hollywood and boiken bringing um seth robbers they still keep really sneak of course and you just you're inactive and then the follow oh actually that was uh that was last year but the year before that you got stashed so you couldn't do anything about that but they they did show that they wanted to keep you around but to just be sitting in the background and watching and waiting for your opportunity and hoping for your opportunity but you can't do anything it's like man and then if you having this training camp where you're just coming up short it can be super frustrating so I can understand why he just thrown his helmet because his chances are slim they're very slim but it's a lot of other people like that currently on a roster too different situations but they probably got it on their mind right now because this is their job this is their livelihood and to not know what your next move is going to be that's scary man that's scary I don't care how old or young you are it can be scary so you got a feel for these guys man so this is going to be a very uh interesting week uh as it every week really is but we're getting things are going to ramp up because we're getting that much closer um so team keep it clean appreciate y'all like riding this out with us this season is going to be crazy uh it's going to be different than any other season has ever been I mean you can say that about every single season but because no season is the same but no this season is going to be like way different than it's ever been before so I appreciate y'all being a part of it I appreciate y'all riding out I love y'all so much team keep it clean and we'll see how things end up turning out I love y'all are we out


Despite eight rounds of talks with the farmers regarding this farm, we've got right now right to the ninth round of talks as we know. How do you see this impact? Farmers are not in a position to understand the government or the government is not able to understand the position of the farmers. Farmers are planning for a massive rally, tractor rally on 26th January. See, I do not know exactly what is it that is really upsetting the farmers of Punjab and Haryana. The policy doesn't seem to disturb the farming community here. I've spoken to many of them, they don't feel that way. So what I feel is there may be specific concerns in different areas of the nation or different states of the nation. So it is important, I feel, because it's come this far and unnecessarily the farmers are sitting on the street causing great inconvenience to rest of the citizens and a lot of torture to themselves. And the government is also not able to function properly because of these protests going on endlessly. So I think it is best that these laws are made as a recommendation for the nation. And every state, it is best that they try to explain to the state leadership what is the significance of this loss, what sort of investment it will bring into the state, what kind of development and infrastructure will happen, the cold chains and the value addition infrastructure that could come out of this. And if the states wants to regulate, if they have fear of corporations or corporates taking over agriculture, the states can have amendments to control those aspects. In each state, the concerns may be different because agriculture itself is different. So I feel that would be the way forward, but right now it's unfortunate that so many people are unnecessarily suffering. I feel it's a large scale misunderstanding. I'm not saying on any one party, I think somewhere they didn't read it right and these people didn't understand what they are saying. And now Supreme Court has entered and unfortunately we are kind of making all major institutions, which matter for this nation, kind of insignificant with this kind of debates and discussions going on everywhere and everybody having a potshot at it. I feel it's time that the government makes this law into a recommendation. And every state can make their own amendments as they want. Consulting their farmers according to their requirements, I see this as a way forward.


This always works for me. OK, good morning. I'd like to thank the organizers first for having me here. Great pleasure. So today, I'll be talking about cooperative transport in ANTS. And I guess this conference is all about the collective phenomenon in biology. And we know that there's many, many examples. We've seen some wonderful ones here where we have many similar, more or less similar entities interacting to produce some whole, which does more, gives more than the parts new kind of phenomenon. So we have many examples of this in nature, but the theoretical language by which we should describe this if it even exists, it's not too clear what it is. And one field in which we have some tools for describing large systems of similar particles is physics. So we have some decent tools that were developed over the years. And the question arises is, can we take these tools or these phenomena that we know from physics and try to use them to understand these collective biological groups? And so it's interesting how far we can get, but it's also interesting perhaps when we'll stop. What is the limits of this approach? Because when we look at these systems, we have a tendency to call them cognitive. Well, these physical systems are indifferent. And the question is, where does this arise? If we could just describe all these systems by very simple physical laws. So where does this at least intuitive difference, if it even exists, arrive from? So this is the approach that I'll be trying to convey in this talk. And I study ants. And to approach this question that I just talked about, you need two necessary things. One of them is because we want to look at the relations between the individual and the group. So it's good if, experimentally, you can track each individual and all individual ants in our cases. So there's one thing. And the second thing, since we're interested in this indifferent versus a cognitive, we better give the animals some kind of a goal, a clear collective goal. And these two things are typically not that simple to achieve in many biological systems. And luckily, the ants, it's a bit simpler. So actually, all that we have to do is go to the nearest grocery shop, get a box of Cheerios, take one of them, and then go outside to the field near our building, put the Cheerio near the ant nest. And now we get all this for free or for the price of a Cheerio. Because first, we've provided the ants with a very clear goal. They want to get this Cheerio from where it is to the nest as fast as possible, well-defined. We know exactly what they're trying to do. So there's one thing. And the second thing, another thing is this is a collective behavior. So no ant can move it on its own. It's very heavy for a single ant, very big.  Another thing, everything is just confined to this small area. We can easily see everything, track everything, each ant and all ants. So this is what it looks like after it's tracked. You can see the numbers here. So this is in the field. We don't have to tag them or anything. The ants' legs are pretty spread. So it's easy to differentiate between them. And they're going towards the nest. And the bonus is cooperative transport is a very physical kind of phenomenon. There's forces. There's motion. So these are the things we're used to deal with with physical tools. So pretty easy, maybe straightforward interpretations that we can use here. So again, we're trying to take our approach. We're going to try to look at the ants as particles and see how far we can go. So first thing you need to do when you move a large object is you need some kind of consensus in the application of forces. Because if you carry something big together and each person, each ant pulls in a different direction, you're not going to get too far. You're not going to be too efficient. And here we're going to see some microscopic evidence for this. So this is a side view. You can see that this kind of slant of the object, it's tilted in this direction. These ants here are pulling. Well, those in the back are lifting. So there is some kind of consensus. The ants are not just pulling randomly everywhere, but some kind of order in the system. You can think of two possible explanations for this. One is that we have smart and independent ants. OK, I'll discuss them in the next slide. And the second is very simple ants, like particles, but coupled. So let's look at the, sorry. And before we compare the two models, which I didn't describe yet, actually, the experimental evidence, which I'm going to pit them against, is the trajectory smoothness and speed as the dependent group size. So in the lab, we can prepare these artificial objects. So these are not cheerios. So we can cheerios are very uniform in size of different sizes. And check the characteristics of the motion. So we can see that the very large object, the blue here, go in very smooth lines. Well, the smaller objects, they wander around much more. So this is one thing. And second thing, the large objects move faster than the smaller ones. So these are two observations. First observations that I want you to remember. So now let's look at our other two models. First is smart and independent ants. So the single ant rule is, you're smart. You know where the nest is, grab the object, and pull in that direction independently of others. You don't care what the others are doing. Act as if you were alone. And then that's what all the ants are doing. And then we can calculate the forces, et cetera. And the collective motion is just overdammed motion. Of course, the ants are applying force, but it doesn't mean they're accelerating forever. So actually, the speed is proportional to the total force of all ants. And the consequence of this is wisdom of the crowds. So what is the total force that we get on the objects? It's just the sum of all forces. So it's just like averaging many, many forces. And the more ants we have, if each of them has some notion of where home is, but there is some noise in this, if each of them is making a mistake, then the more ants we have, we get a better and better estimate. Or the total force is a better and better estimate of the correct direction to the nest. So this is like the wisdom of the crowds, like the large numbers, if you want. The more you average, the more accurate you get. But you get the same kind of mean. So the mean stays the same. You get smaller and smaller fluctuations, but the mean stays the same. So this means that if we look at larger items, where more ants are needed to carry it, we expect to have same mean speed and smaller fluctuations. So this fits with one of our observations. We did get smaller fluctuations for larger objects, but they were also faster. We didn't get the same mean speed. Okay, so now let's look at the second model. So here the ants are simpler. They don't really know where home is. So the single ant rule is you're lost. You don't know where to go. Just feel the current direction. Feel the force at your point of attachment. And just go with the flow. So if you're in the front and it's coming towards you, so you pull also, you help the group. If you're in the back, lift. Okay, so we can capture it by this transition rate rules that ants measure the force once every few seconds and decide if they want to pull or lift, switch between pulling and lifting. Okay, so again, they tend to be lift pullers on the leading edge and lifters on the back edge, on the trailing edge. And the collective motion is again over-damped. So what do we expect to get here? So, okay, one more detail here. Sorry, I forgot to say. So what they actually do in our model is they take the force that they feel and if this force is over, okay, so this is the total force that they feel at the point of attachment, if this force is over some force that they have measured the scale that they have in their head, F independence, F end here. So if the force is over, stronger than this, then they will tend to align. If the force is very weak, compared to the scale that they have in their head, they will just act randomly and they can pull in the front, lift in the back, et cetera. Okay, so the consequence of this is that if the forces that an ant feel is much or independence, it's much smaller than total force, then all the ants will tend to align. Okay, so there's this force which is much stronger than independence. All the ants will tend to align and we get high speed and smooth trajectories. On the other hand, if the independence of the ant is very large, so they have a very, very high independence parameter in their head, it's very difficult to convince them, then each ant will pull in different direction, we will get low speed and irregular trajectories. Okay, so actually we can achieve these two inequalities either by playing with the independence level, the scale that each ant, that the ants have in their head, which is very difficult to do, but we can also play with the total force just by increasing the object's size. So it's like playing with the social pressure. So very large object, there'll be a large social pressure, all the ants will tend to align and here there's a small social pressure because the total force doesn't pass this scale. Okay, so we expect to get high speed, smooth trajectories for the large load and low speed irregular trajectories for the small load. Okay, so this fits better with this observations, first observations that I showed you. Okay, so just a quick summary here.  Okay, so this is actually the same species of ants in different behavior, the ant entrance, we just put like a toilet paper roll around it, they can go, they can escape easily, they can go back, do whatever they want, but they're trapped in this collective state where they go around and around and this maintained itself for 10 days, I think, during which no ant died, because if an ant got tired, she just went back to the nest, another replaced her, but it's really a collective state. Okay, so now that we saw that we can describe, okay, we can hope to describe the ants as simple particles, let's go to this next stage where we actually show that ants are important as individuals. So we have two puzzles that are actually left by this model that I just described. First, it doesn't count at all for directionality, so it just says that wherever the object is moving, the ants will try to keep moving in the same direction, go with the flow, but this will not really bring them anywhere or to the nest. And second, the path that we measure are quite convoluted and this was very strange for us the first time, we saw it because we used to see ant trails that are so straight and nice and so we know that ants as a species and also these species have the propensity to make very straighter eyes, but here the trail has a lot of sinuosity and this was very strange for us. Why don't they take the straight line if a single ant can do so? And I think there is some explanation that kind of what I'll describe now kind of provides the same answer for these two questions. Okay, so how do the ants find their way home? So here we'll show a short movie, so the ants are carrying the stereo, they're lost and they're all trying to just go the flow, pull in the same direction, but they're going up instead of to the right. So because the path is convoluted, it happens a lot. So they have to somehow be corrected and let's see how it happens. So now they're going up, the nest is to the left and soon you see the rescuer, she's coming from the outside, well oriented, ants like any other insects navigate very well when they're doing free motion. She looks for a place to attach, attaches, and when she attaches you see a very sharp turn to the left. So now they're going very much to the left almost 90 degree turn, which is very strange because it's one ant pulling to the left and the rest are cooperating and going up, you would expect maybe a very, very wide turn. How could she turn them so sharply? Okay, so to try and understand what is happening here, how we got this sharp turn, we went back to the model I described before and we simulated it, okay? So we took these ants on a circular object and they attached all around and they follow these rules that I told you before over deciding whether to pull in the back, lift in the front, measuring forces, et cetera. So it's a very detailed model, but finally you actually have, it includes four free parameters, okay? So most parameters you can measure, like the friction or the size of the Cheerio, the mass of the Cheerio, et cetera, you can measure, you're left with four free parameters and because we have so many trajectories, we have many, by today many kilometers of such trajectories, you can get four different features and many more actually from the trajectories, okay? Like the speed as a function of the number of ants, the correlation distance of the trajectory, et cetera. So there's more than four features, so we can fit it pretty reliably. And what do we see when we fit the parameters to the natural motion, okay? So we fit them for a single size object on which we did most of the experiments and what we saw is that the fitted parameters actually places naturally sized loads, okay, which are about one, two centimeters, that's what they carry in nature, large insects, at the transition between a random walk and persistent motion. So very large loads go in very smooth trajectories. Okay, what we see here is actually the projection of the speed on the X axis, for example. So very large load, they have a persistent motion, ballistic, which you can see by these two peaks here, small objects have just something like a random walk, because none of the ants are cooperating, and natural sized objects are in the middle, okay? So they're not deeply in this area and not deeply in this area, somehow between two different modes of motion. Okay, we can compare this to the experiment, so we can see here that the curvature of the trails in the experiment for different load sizes and in this simulation, okay?  Okay, so what does this tell us? So transitions, we know them from physics, and we try to look in this direction, and to get this into a more physically understandable model, instead of looking at a circular load, we look just at this kind of rectangular load where the ant can attach just in the front and just in the back, to make things simpler so we don't have all the angles, and the ants can then choose if to be a puller or a lifter, according to the exact same rules as I told you before. Okay, so just a simpler model, and here they just move along a single dimension, so they can just move front or back. Okay, so just a simplified version of the previous model, and actually, even though this thing is moving, since there's translational invariance, it's actually mapped to a fully connected, Ising model at a thermal equilibrium, we can even write a Hamiltonian for it, which is something a physicist likes to do, like to do, and as we know for Ising models, you get this transition between order and disorder. So to get really the Ising model, what you have to do is take the number of particles to infinity, which is the kind of systems we deal with in physics, very, very large systems, and we can see that we take the number of particles to infinity of ants, and then we also have to raise this independence parameter at the same time in their heads, so we take them both to infinity together, and then we get an exact mapping to this mean field solution of the Ising model, where you get ordered states here, where the ants are not so independent, and they go to the group, and you get a disordered state here, and no speed, okay, so the order parameter is the speed here that you get. So this is for very large system sizes, it's clearly not what we have with the ants, we don't have a number of ants, but we can, using simulations, we can see also with the ants going as low as 10 ants, I can't even read it from here, you can see that we get the same behavior even for very, very low number of ants. So we get this transition between ordered state, where you get a collective speed, collective motion, and a disordered state where the thing moves very, very slowly, okay, and as we said, the ants are positioned, the real system is positioned somewhere in the middle, okay, not deeply in the ordered state, and not deeply in the disordered state, okay, so what could be the advantage of being there? So this kind of a criticality was observed in many other systems, in bird flocks and fish, and the idea here is that the system may have very strong responsiveness, okay, so we know that in physical systems, near the transition here, you have strong susceptibility to external fields, so if you apply a small external field on the Ising magnet, it will respond very strongly when you are here, okay, so what is the external field, how can it be here? External field is just a constant force that you add to the system, okay, so this constant force, how can you get it? You can get it by having a single ant, which is not following the rules, she's an informed ant, she's just pulling in a constant direction, she knows this to be the direction to the nest, she just pulls there, she acts as an external field, and we expect to have a maximal response to her since the system is sitting here, okay, so this ant doesn't have to communicate anything to the group to be able to get control like this, she might get the control just by the group being placed at this critical position and near this critical position, okay, so we add informed ants to the model and informed ants are ants that just attached to the load, so they came from the outside, they're well oriented, just attached to the load, and the rule is you know best, others don't know, so ignore them, just attach and pull to the nest, okay, and after about 10 seconds, you consider yourself lost also, okay, so this comes from experimental measurements, and then you become a regular carrier and go on to follow the rules before, okay, so you have the ant had its time of it's a five minutes of fame, 10 seconds of fame, and then she becomes a regular carrier, okay, so what does this give us? So in the simplified model, this is just an Ising model, if you take an end to infinity, you really get a divergence of the response, it's a red line here for small numbers or for a finite times, you still get a peak here, and the full model, we get the same kind of peak, and this is what we think we see here, so this ant is actually not interacting with these ants there, she's just looking for a place to attach, and once she attaches, because the other ants are placed at this critical position, she can get control of the whole system, okay, so experimental evidence that there is an optimal group size, okay, so if we have a very small load, the social pressure or the total force is not enough to impress the ants, and one ant actually does much better when the second ant attaches, they start to fight each other, they go right, left, right, left, and they can't seem to coordinate, if you have a large load, as we saw before, it goes in very straight lines, so very smooth, this will be the best, but the problem, if we confront it with an obstacle, so similar to the obstacles that Odre just showed, except this one's a bit more confusing because there is a small hole in here in the center, it will stay here for 20, 30 minutes, it cannot get the new information, okay, so the ants are very, very well coordinated with each other, all the carriers, but they're not open to external information that will tell them how to pass, and this natural size load, size of an insect, it walks in lines that are kind of convoluted, okay, so it doesn't walk in the straightest line possible, but when it hits the same obstacle, quickly gets information of how to pass it, we'll talk about this later, and they pass, okay, so I think this is a nice result here, actually what we see is transient leadership, so the object is moving towards home, each time a new ant comes, she has influence, she leads for about 10 seconds, but then she stops to lead, the object gets lost again, and then another ant picks up, and then another each color here is a new leader, and slowly the cheerio goes towards home, okay, so when you look at an ant system and you ask yourself, okay, is it a distributed system, is it hierarchical, is somebody in control, it depends on the time scale here, so if you look at a single, five second period, there will be somebody that is leading the entire group, but there's somebody, there's nothing too special about it, if you look at this whole period, there are many leaders, okay, so the leaders are democratically changing between them, and at a longer time period, it actually looks much more distributed in the non-hierarchical system, okay, so now we saw something kind of funny, that first I described the ants as particles, very simple particles that follow simple rules, but actually what this did is transfer the control to a single ant that was very knowledgeable and she knows how to get home, so actually by describing the ants as a physical system, we move the control to, okay, like particles very simple, we move the control to this single ant, which we can't really describe by physics, how she navigates and what she remembers, okay, this is a bit less like physical laws, but still maybe we still have a chance, because all these ants that are coming and in most of the examples we saw, they just want to pull to the nest and the nest is always to the west, to the east, maybe it's still simple, okay, so if you just model them as a simple particles that have some attraction to the east, maybe that'll be enough, so let's see how far we can still go and use this physics language, so what we did is use the invisible constraint and the invisible constraint, it's different than the constraint I showed before, which were walls, this is a piece of hair which is tethered here and tied to the load, okay, the movie was not supposed to begin, and what happens is that the ants go towards the nest and then when the hair becomes taut, they start this pendulum-like motion, okay, so we're going to look at the system, it's a different system than we saw before, it will help us test our model as well, okay, so we want to test our model on a different system, and we're going to use this one as a test to the model we developed on moving in open space, okay, so and the reason that we use this invisible constraint is we don't want the ants to have any other information than the nest is in this direction, okay, so we want the leader ants to be as simple as possible just to pull towards the south, okay, and this is what we get, okay, so first let's try to see if this really supports our model, okay, so this is, we have these two different alternatives, the smart independent with the averaging and the coupled particles, so in free motion that the puller ants in the front could be there for two reasons, either they're going with the direction because or they're going towards the nest, typically these two are more or less aligned, okay, so the trajectory is wavy but more or less goes towards home, so these are aligned, so it's really different, difficult to tell between these two, but when we look at this constraint motion, the direction of transport is different from the direction of the nest, right, they're doing this pendulum, the nest could be there and they're moving to the right, so here we could see are the pulling ants in the direction of the nest because they're all nowhere it is or are in the direction of the leading edge, okay, what we can see actually is the slant is towards the direction of transport and not towards the direction of the nest, okay, so again this is microscopic support for this coupled particles model, that's the answer, just going with the flow, okay, second kind of support is just to take our model as is, okay, so this is what we measured experimentally, these kind of shark fin oscillations, so we took take our model as is and we just add this piece of hair as a Lagrange multiplier that restricts it to go on the circle, so what happens when we do this for our coupled model we get very similar kind of oscillations and for the uncoupled model all the ants are trying to pull to the nest, so it actually stays near the center, okay, so they're just trying to pull there just so the more they are, the more they'll stay near the center, okay, and actually doing this we can get very, very nice fit, so this is the experimental data in blue and this is this simulation in red, very similar and also this is an analytical kind of a model that I will show you next, also fits very, very well, okay, which is another piece of evidence that our model seems to be correct and these oscillations are happening just do, not because any ants is realizing what is happening, okay, the ants are just following the same rules that they did in open space, okay, this is just a collective phenomenon, okay, or emergent phenomenon that gives rise to these oscillations, okay, so let's just try to give us very small physical intuition for the oscillations, so here again we take the simpler model, we have an object that has two sides, front and the back and it moves along this circle, so we can vary theta and we can write a very simple equation for this, so we have the informed ants, they just come in as a force towards the nest, so we g here like gravity and with the uninformed ants kind of give the object its momentum, so they keep on going left and right, so we can capture it by these equations, I won't go into it of course, and we can linearize it, so if we linearize it, we get an equation of the speed change according to the speed and we can see that if here, if this thing here is negative, so the speed that change varies negatively with the speed and this can give us, okay, so this happens with a, for a small number of ants, the number of ants here is n, for a small number of ants we can get a fixed point at zero zero, okay, so this is negative, if you get a speed in the right direction, it will pull you back to the left, so for a small number of ants, we expect it to be stuck at zero, but what happens if the number of ants becomes larger and then the ant starts actually to fill each other, the social pressure they start to cooperate, so what happens when the number of ants goes over this, so when the number of ants becomes higher, we get these, this is what we think, we get these oscillations in the experiment, so you can see in the oscillations, the speed is practically, okay, it decreases here but almost constant for the entire range of motion and then there's a brap flipped and it goes to the other side and then against almost constant, so the change in the speed is almost zero, okay, so if we write the change of the speed as a derivative of this energy function, okay, so we just took the formula we had here, change of the speed and we write this as a derivative of an energy function, so this is like a Lando energy, we can write this energy, so this is just the same formula as before but now we can plot this energy at different locations along the trajectory and this will give us intuition for the oscillations, so what happens when the object is at the center, the force of the spooler ants is just totally canceled by the string so that we can forget about them and what we have is just the lift, just the other ants, the uninformed ants just trying to cooperate with each other so they want to move together, they have two alternatives either left or right and the two alternatives are equally probable and you can really see it in this W function, in this Lando energy, you have these two valleys and you spontaneously fall into one of them, so now you got the system got a positive speed, it starts to move to the right, when it starts to move to the right, now the informed ants that are coming and pulling towards the nest, this gravity, now they have an effect, okay, because they're not totally canceled by the string and their effect is in the opposite direction, so actually what happens if you plot this function, you see that the peak here, the valley here, becomes smaller and then becomes even smaller until at some point it loses stability and the system has to fall to the other side, okay, so. So actually this will tell us the different load sizes, will give us different collective modes, the larger the load size, the larger the oscillations and this we can see in the experiment and in theory and in this modeling, this physics like modeling even predicted a third kind of, which doesn't work, doesn't work, sorry, a third kind of regime, which I had the movie here but somehow it skips it, where actually the object can do full rotations around its axis, so my time is completely over. Okay, so I'll go into, so what we saw here, okay, so unfortunately there's not the experimental evidence but it fits quite well, so what we saw here, again we can describe the system very nicely as a physical system, as they describe the ants as very simple particles, which we can track using physical tools, okay, so this was in a very simple system as well, with this invisible kind of constraint, okay, but now when we go to more natural systems, then we see that the ants actually profit from both the individual and the group, okay, so it's not one or the other, we need both the collective effects and the intelligence of the individual ants, okay, so natural environments look more like this, so this is a natural movie, which was not staged at all, so there's a leaf here and the ants are carrying this seed, so the ants easily pass from left to right but the seed can't and then they have to go and find a way where the seed can actually pass, so we kind of simulated this here, we bring the ants an obstacle, here the ants can pass easily, it's the fastest way to the nest, but the theory cannot pass, okay, and what happens, so it's a confusing kind of obstacle, they think they could go here but the real solution is from the side and actually we see that they solve this in linear time, okay, so how do the ants do this, so for this we have to add a new kind of information to the system, which is the scent marks that the ants employ, so the ants actually employ scent marks while they're carrying the loads and the scent marks you can see the ants here, she's touching the end of her gaster to the floor, she's applying a scent mark and the nice thing is you can see this behavior from the top, so it's a very stereotypical behavior, she walks a bit backwards, you can see it from the top, you don't need the side view, which means that even when you look at a single ant from the top, you can infer just from the movie where exactly she laid those scent marks, which we add here in animation, and these scent marks also appear during the co-op of the transport, so here the cheer is moving and we plot, this is a real experiment, we plot the scent marks that the ants have laid and the cheer are moving on top of them and we see that cheer lost the scent marks and a new trail formed here, cheer is moving on it, loses it again and a third trail forms here, so the trail is always deforming according to the location of the cheerio, so the trail is more finger and leading the cheerio at the same time, both leading each other. Okay, and the nice thing here, when we follow the scent marks, we learned that the individuals cannot solve these kind of problems alone, so when the individuals see these kind of obstacles, they actually mark towards the shortest route to the nest, which here is under the sleeve, where the object can't pass, so even if you take many such animals and you average all of them together, okay, even if a few animals will see, a few ants will see the way around, the average will be towards the center, okay, so doing this kind of wisdom of the crowds doesn't work here at all, the wisdom of the crowds is telling you to go forward while the answer is to the side, okay, so individuals and averaging individuals doesn't work at all, they have misguided information which is on the wrong scale, okay, the group also cannot solve the problem at all, if we remove knowledgeable individuals by blocking the ways from the side, we can see that instead of solving these obstacles linearly, it takes them at the group exponential time, so the group also can't solve it alone, okay, so both of them are not suffice, so how do the ants actually manage to quickly circumvent the obstacle, so I don't know if to give the answer or not? No, please give us the answer. Okay, so to understand this, we looked at all the scent marks that the ants lay near the obstacle, and what we found that the scent marks here near this opening, they're actually like a road sign that's pointing up, so these are wrong, but the scent marks, if you go here, more to the side or here, they're all to the right, so here the scent marks that are far from this entrance are to the right, okay, so the ants are marking the ants, know their way around, and they give these possible solutions, and this stays constant over time, so we have this error here, it's constant over time, it's always an error, but it's also confined in space, okay, so we have areas, the representation is wrong, but it's quenched in time, confined in space, okay, so when you have this, I'm trying to speed up, when you have this kind of rules, or road signs that are sometimes wrong, typically correct, sometimes wrong, what do you do? How can you use them to get to your destination? And what we find is the ants use this by applying this locally-bladed trail, which is, they apply each ant when it marks, it doesn't mark all the way to the nest, it just lays a small 10 pheromone droplets, for example, 10 centimeters, and goes back, so it's like a little arrow telling you, telling the object where to go next, okay, so the trajectory is not fully planned in advance, okay, just the next step each time, so this is one part of it, and the other, the group follow these trails, but not religiously, okay, so the group tends to go along these scent marks, but often loses them as we saw in the movie before, okay, so this is a different kind of trail than the one we typically know, which is very, very well defined and constant over time mostly, okay, so now why does this algorithm work? Okay, so here we want to get from A to B, so a very simplified version, mostly we have the correct instructions, but sometimes we have the wrong instructions, okay, so there can be few possible approaches, first, you trust, you say, okay, most instructions are correct, I'll follow them, the person who put them there wants my best, but if you do this, you'll get stuck here forever, so this is infinite time, second is disillusioned, so there's sometimes wrong, I'll just forget about them all together and just do a random walk, so this will get you to B, but in quadratic time, and third thing, which is kind of what the ants do, is follow with probability, you typically follow, but not always the next arrow, and on stretches of good advice, this gives you biased random walk, which is linear, on stretches of bad advice, it gives you exponentially long, because you're doing a biased random walk against the bias, but these stretches are rare, because usually the advice is for you, so together, you can analyze it, you get linear time, okay, so this is the reason why people have this dice in cars, okay, and actually when you follow, so I won't go into it because my time is out, I guess, but when you follow what the ants are doing, this is really what they're doing, so the reason that they're not stuck here and near the center is sometimes they don't follow advice and they go elsewhere, and then they pay for it, okay, so the ants here paid for it because here, they could have followed the advice and escaped, but still here, they chose not to follow it, and they go against their interest and back, but the price you pay here is minimal when compared to the price you gain here, and you get this linear time, so what I wanted to summarize or looking at the future is to try to say that ingredients for this collective cognition that we say we have cognitive systems is you can use this collective phenomenon in physics, can get you very far, but it will not give you cognition, at least for the ants, and for this, you have to add these navigational, competent, goal-oriented individuals, and you need information to transfer between these two all the time, okay, so in physical system, usually you can forget about the microscopical details, here, no, here, yeah, keep on being important even when you go to the group level, and then we want to understand, take this for the future and try to understand, okay, what can this give us? What is the class of problems that the ants can solve using this? And we try all kinds of different measures, so here you can see the ants trying to go through this rock field, the ants can easily walk straight, but what they're carrying has to take a very different kind of path, and we're trying to understand theoretically, okay, do we expect the ants to solve this? Don't we, what kind of puzzles do we expect them to solve and what we don't? So you can follow the trajectory of what they're doing until success, okay, so thank you very much, sorry for being over time.