Live from Vancouver, Canada, it's theCUBE at OpenStack Summit Vancouver 2015. Brought to you by headline sponsors EMC and jointly by Red Hat and Cisco with additional sponsorship by Brocade and HP. And now your hosts, John Furrier and Stu Miniman. Okay, hello everyone, welcome back to the day three of live coverage here at the OpenStack Summit. This is Silicon Angles theCUBE, this is our flagship program. We go out to the events and extract the civil noise. Talk to the expert, talk to the entrepreneurs, talk to VC, talk to whoever has data to share. We share that with you. I'm John Furrier, my co-host Stu Miniman. Our next guest is Brian Redbeard, Principal Architect Coro West, welcome to theCUBE. Hello, thank you, thank you, I'm glad to be here. Love the look, it's great. Redbeard, it's beautiful, very, very hipster, OpenStack looking, we love it. But a lot of action here and I want to get your thoughts before we get into some specific questions around the vibe and around the people here.  This is a telltale sign that there's real building going on. People are actually acquiring information. This is on the path to maturity, as we were saying in the intro. What's your take on that, what's your view of that? What's your big picture take on all this learning? It's active community, but a lot of change going on. Absolutely, you know, there's, when it comes to what we're doing, like we have a clear vision for where we want to take infrastructure and it just, it happens to be that there's a lot of outstanding questions at the community level and that's what folks are here to actually kind of solve and work through and it's nice to actually go where our users are and work collaboratively to figure stuff out together. So what's your take on the overall core OS mission, obviously, you gave a talk on OpenStack with Kubernetes, obviously Google is involved with you guys from a funding standpoint. What's the progress? What's going on? What's the state of the union? What's the landscape look like for you guys? Well, the big things for us right now are really targeting Kubernetes, kind of pushing adoption of AppC and then greater use of Rocket itself and really trying to continue with the overarching mission of changing how infrastructure is done and driving greater security on the server side of things on the internet. Yeah, so, so, so, Redbeard, one of the big discussions we're having at this show is, you know, what are the business models for open source? You're the first guest that we've actually had on from Core West, so I've had the chance to talk to you a few times, talk to Alex Pulvy, talk about kind of the Core West's mentality as to how you build, you know, projects and tools and, you know, how to put them out in the marketplace. So very much we are an open source company, we are an open company in general, like when right from the start we are present on IRC, we're very active on GitHub, you know, we try to be as present as we can to our actual users, you know, we do a lot of like community meetups and stuff, but what it means is that all of our development happens in the open, folks can really track what we're doing and we make ourselves available so that when folks want to kind of see where our vision is going, they can do a little reading of the tea leaves when they actually watch our Git repositories and get a good sense of what's coming next and that's why when it came to some of the stuff with like Kubernetes and Rocket, folks start looking at seeing, oh, I see that there's some commit changes happening on Rocket, this is where it's going to go and, you know, from a marketing perspective, it means that there's also just a little bit less that we need to do on that, because folks do have an overall sense of like where our infrastructure is going. All right, can you speak a little bit about the CoreOS involvement in OpenStack then, which projects are you guys heavily involved in and what are you seeing, because, I mean, Magnum is pretty new, Kala's there, you know, other pieces, there's the keynote, the discussion of Kubernetes and how that's expanding into OpenStack. Yeah, so just under the wire, I was able to get some commits in on the OpenStack marketplace, the Mirantis just rolled out, so, you know, we've been involved with that. For a long time, we were working with the folks over at Rackspace and HP on Ironic, Ironic utilizes the CoreOS image to get a lot of things done on that front, and, you know, we've been talking both internally and with the folks on the Magnum team about how CoreOS gets involved, like there's already been a few kind of proof of concepts where you can use both Project Atomic and CoreOS inside of Magnum today, so we're really trying to make sure that where it makes sense, we're present and active in these projects. You guys are optimizing on many levels, but can you share with where your focus on optimization is in terms of the efforts and the coding? Is it the secure cloud? Is it container delivery? If you guys had to optimize, and where are you guys focusing all your guns on? I mean, obviously there's a lot of stuff going on across the board with Linux, you know, the distribution piece of it, but what is that focus? What do you guys organize around to optimize first? Well, so, like a lot of open source projects, we have federated teams inside of CoreOS that work on specific things, so, you know, in the same way that you'll see a lot of interaction between like the Apache and the HA proxy teams at the open source level, internally, we have them separated, so like the rocket team is doing things and the tectonic team is doing things and then, you know, they do a sync up. So it's been continuing on the focus of security, like we've got Matthew Garrett from our team who's done a lot of work recently on Secure Boot and UEFI, and it's where we're trying to bring the overall security of the stack from being able to verify the bootloader to the image itself and eventually securing the containers as well and being able to validate that. Still at the community, what's the big reaction? I mean, obviously this is growing fast. There's a lot of traction across the board. Where are you guys seeing the collaboration coming in around CoreOS? What are some highlights? Can you share some data around where the collaboration is? Absolutely, so we just had CoreOS Fest, which was our open source kind of, you know, whereas some other companies have like their big commercial event, we wanted to have a big open source event. And it was a great opportunity because folks from data.com over at Salesforce came out and gave their story about how they're using the open source components. Intel and Supermicro came out. And that really also gives a view into where we're working with other companies and trying to contribute things upstream for folks to work on. Like the folks, the work that Intel did around optimizing SED to work on the silicon, much better was just out of this world. Like seeing the 10X performance increase and they're promising another 10X soon, so we'll see that. So, so Redbeard, you know, I think back to like how long it took Intel to optimize for virtualization. It took many years. How did this happen so fast with Intel? I was hoping Nick Weaver was supposed to come on. I think he's actually flying in today. And I know he was involved, but you know, how's CoreOS and Intel working so fast? Well, a lot of it just comes down to standing on the shoulder of the giants that is the Linux kernel team. Like the work that Linus Torvalds, Chris Wright, Greg Crow Hartman, and then all of the folks kind of also involved, they're really focused on working with hardware vendors to get hardware support in as quickly as possible. And it's just because we use an up-to-date kernel, we get all of these features really as soon as they're available to the kernel. You know, whereas other distros, they lag behind a little bit because part of their actual sales model is like having a more, I wouldn't necessarily say stable, but you know, having a kernel that lags behind so that they can control the feature set a lot more tightly, whereas we want to bring the features that are in the stable kernel to folks as fast as possible, because it is the stable kernel. And you know, having that strict contract around the API and the ABI, like that binary interface, means that your workloads are going to continue to work even when you use that newer software. So I got to ask you last year at Atlanta when we were doing theCUBE, I mean, all the rage was containers, Docker. And so Docker kind of slid in through the mind share and on the conversation cycles, you know, and so that buzz was rocking. I'll say Docker's got 95 million bucks and the container story's kind of been kicked around, but we're not hearing a lot about containers. It's not dominating the conversation. It seems to be a subtext, if you will. Kubernetes certainly has risen up as well. You mentioned that earlier. Why is that? Why is it because it's more established, more recognized containers and delivery with orchestration and with Kubernetes is now hot? Or is there a bigger messaging and or conversation going on on top of it? Can you talk about that as an architectural thing? Is it more of a systems architecture, services architecture? What is, why isn't it dominating? Does it already establish sub-element? Share your thoughts. I think that there's two key things to identify there. One is that if you look at the patterns of social media networks, there's a lot to be into it there. And also if you look at like the development of the iPhone, really it all comes down to content. Today, there's not a lot of open source upstream applications which are designed to run natively in containers. And that inherently has a slight limitation to organizations that are looking to do green field applications. They want to do that new development and so they know and they recognize that containers make sense for that. But until we see open source applications in the upstream that just, they treat containers as a first class citizen, it's going to be how do we then shoehorn this into containers. So that's why I make that comparison to social networks because it really comes down to having the network effect. Yeah, and some critical mass, some tipping point if you will. So you got to have some ubiquity. So people are recognizing, so I break that down, they're recognizing the importance of containers. But the native apps are not out there. So it's now being architected. So we are in that kind of pre-architectural figuring out for the apps. Yeah. So how many plays are there at Core West today? There's about 40. Yeah, so am I right? You guys have about 90 projects up on GitHub right now. You know, I had a great conversation last year on theCUBE with John Ankees from Rackspace. And he said, we hire great people and we let them work on whatever they want. And it was like, wow, how do we make that turn into a business? So the question I have for you, Core West, I mean, you know, SCD, Rocket, Fleet, Flannel, a whole lot more up on your Git page. How do you guys focus on that? How much of it are you guys driving? How do you bring the community in? And then we'll talk about Tectonic when we're done with that. Well, a lot of it comes down to our employees, we try to make sure that they're empowered to be able to work on the things that are interesting and really kind of feel out all the threads to see what makes the most sense. So that's why you do see so many repositories up there because we have an idea, we take it, we run with it, and then we see what makes sense in the long run. When it comes to that, you know, it just is a natural progression where, you know, I have an idea and I start looking at that. You know, the one that I kind of started a while ago was called Mayday because we wanted to see a good mechanism for, from a support perspective, users to be able to send telemetry data back, but that really just captures it in a way where they can unpack it and see where that goes. And you know, today that's modeled after some other patterns like sauce report and things, but it's just one example of where we take these little ideas and we, in the true UNIX model, try to have small tools that do that one thing well and then see where they go from a ubiquity perspective. All right, so then can we talk about the CoreOS of the business? Because in addition to making all these pieces, you guys are building a platform, tectonic, huge discussion at the CoreOS Fest.  Where are you with customer deployments of stuff that they might actually pay for? Yeah, so right now we have a closed beta going on. It's very, very high touch. You know, we've specifically kept it to a small group of people, a small group of companies, so that I can interact with them on a weekly basis, and make sure that they're, that it's operating exactly the way that they expect it to. Because anytime you build software, there is that gap between what we thought would be useful and what the customer finds useful. So I'm there kind of as the reconciler to make sure that those actually converge on a central point. And it's really promising because we've got a really diverse group of customers in that beta program between financial, media companies, large data aggregation. So we tried to make sure that we had a good cross-section of folks with large workloads to be able to test out and ensure that this would be really good for those companies from a commercial perspective. What's your advice to folks out there that are getting in? Because a lot of in-migration coming into the community, which is great, you see some fresh blood come in. And it's not tire kickers either, these are real people, engineers. What's your advice then as they come in and gratiate into the community? Obviously the communities will open to your community and open stack in general. How would you advise them on the navigation, like where to get started, there's so much to jump into. So how does someone just get in, what's your advice? I mean you've been doing a lot of cool stuff so obviously that's going to attract some intoxication effect with developers. So what's your advice for the newbies out there coming in, serious players? You know, what I would say is in similar to where I said earlier that the Linux kernel is what is enabling this, there's been a very large pattern over the past 15 years with the kernel of folks coming into Linux but just treating it like it's Unix and it really does short shrift for Linux where if you're just coming in and expecting to be able to treat this like Linux, you're not really getting into some of the next generation features that are there. Like when we look at this, Google contributed a lot of the code in coordination with IBM back in 2005 that really laid the groundwork for containers. And 10 years on we're just getting around to doing that. So for the new folks and the folks who like have a strong architectural sense where they want to be able to work on that next generation, it's that you want to actually look at the kernel and understand what differentiates the Linux kernel from some of the more traditional Unix models because that is what's going to unlock these features for next generation. So really the creative pieces and the exercises to come in and understand where the leverage points are for the next generation apps. Exactly. And because it does take a little bit of time and the second thing I tease out of that is that, and this is always something we always talk about in theCUBE, is that it's a systems architecture kind of concept right now. There's a lot of really great work and the affinity from the developer engineer is a architectural issue, right? There's a lot of architecture going on right now. Yeah, it's something where the folks who are architects at large scale media companies or at large scale companies in general, they're going to be able to have the vision for where they want to get to. And by having an understanding of the individual pieces, they're really able to, like an engineer, kind of build that up one piece at a time and make sure that they're all going to interoperate in the way they need to. So one of the questions I have for you is if you look at kind of the whole cloud conversation in general, if I take something like OpenStack, where is the line where below this line, you might not want to do it yourself. You want to kind of go to the rack space, go to HP Helion, go to somebody else and let them do it. We've said on theCUBE many times, friends don't let friends build new data centers. So what can IT get rid of? But containers are one of those things that, whether you're really small or big, it might make sense for you. Developers are loving the containers in general. You guys work at like massive scales, one of the things you work on. So where's kind of your natural fit and where's that kind of, is there a low watermark or where's that look go?  The answer is it depends, but there is a bit more insight that we can get to on that. Because for each organization, you have the target of how technical you want to be with specific components.  And at that point, just starting from like the core OS pieces and working up makes a lot of sense.  You don't want to be building out like your own set of APIs. And like it probably doesn't even make sense to be doing development on the OpenStack components themselves. So it does, like knowing where your core competencies are really kind of help get alignment on that. All right, so CoreOS is still relatively young as a company. What, as industry watchers and people watching you, what milestone should we look for? What are some of the kind of the goals and success factors that we can say kind of the end of 2015, you know, core OS is moving in the right direction, making money, you know, things like that. Well, so our major commercial flagship that we're launching, which is Tectonic, we're targeting for the second half of this year. And realistically, it's going to be hopefully early on that, but it means that when we hit the end of 2015, Tectonic will be the thing that folks will look at and go, okay, that has demonstrated that Kubernetes is a viable product for the enterprise and that core OS makes sense. That core OS really is solving real world problems that companies have today. Brian, thanks so much. Brian Redby, you're inside theCUBE. Thanks for sharing your insight and just your take on this year's summit of Vancouver. What's the vibe, folks that aren't here? Give a little taste and color of what's going on, just around the show. Share some color and insight. Well, when it comes to OpenStack Summit, it's one of those things where each time it gets a little bit bigger, each time it's moving from its infancy into adolescence, and it's going to be grown up here pretty soon. When you see companies coming in like Ericsson and Alcatel Lucent and all these real big players in the networking and large-scale computing space, it shows that it's proving itself as a technology that everybody wants to use. And more use cases on stage from customers doing live demos. So you're seeing kind of growing out of this POC. Exactly. Yeah, it is 100% real deal. And when you see all of the various companies that are investing in OpenStack, like a lot of open-source projects, you start it, you work through it, and it goes from the stage of getting things done to doing the things elegantly. And there are a lot of naysayers around OpenStack, but I think it's just natural to the fact that we're making that transition from components that just got the job done to now components that are maintainable in the long term. It's hard for folks to get their arms around the complexity of what OpenStack is, because it's such a broad, ranging, and diverse use cases. You got telcos to enterprises, the developers all kind of mashed in, so it's hard to put it into a little box and saying, you know, are these three layers when you have a service architecture model going on where people are actually creating their own blueprints, if you will. Exactly. That seems to be our takeaway from this week is that, you know, it's growing, but people really don't understand the animal that is OpenStack. What is this going to look like? The lion is the tiger, is the cat a dog? I mean, it's kind of crazy in a good way. So opportunities are there. Yes, it definitely is. So I got to ask you, the final question is, you mentioned reading the tea leaves, and so how would, how do people, you know, if you could share your secret sauce on reading the tea leaves, whether it's in Git or in the projects, how should someone coming in who's going to jump in for the first time and do or is immersing into the community, how do they read the tea leaves? What's your secret sauce? What's your, what's your technique? The easiest one, and this is going to be a little bit of a giveaway for the analysts and folks out there who are trying to get in on it, but it's less the Git repositories themselves and more watching the issues in the repositories, because when you are seeing the issues that folks are raising or the feature requests that are being done, and then actually watching the comments on those and seeing what gets closed out, it really gives you a clear vision for where a project's going and what folks are asking for from the project. It's great metadata. Yeah, actually engagement there, you know, right, if you're not finding problems, there's probably not really getting used to any real environment. Exactly. So that's a great one. Brian, Redbeard inside theCUBE sharing his wisdom, talking about CoreOS and all the traction, all the opportunities out there. Great time to jump into OpenStack if you're an architect, you're an engineer. A lot of build out going on, it's exciting times. This is theCUBE, of course, sharing that data with you. We'll be right back after this short break with more guests here. Day three coverage here at OpenStack Summit in Vancouver, British Columbia. We'll be right back.


I normally do on my television show, a rapid fire round. When you fire, I also fire, all right? No, but... Today, everyone wants heart operations, at least. Is it for romantic reasons or...? I want to know whether you're scared of something and I would also like to know whether you have attachments. Let me finish this. This is not news hour, okay? When I'm telling you an answer, you can't ask me another question. How was it when you were a child, were you put into a school to go the systematic way? Do I look educated?  So yesterday, I put a tweet out saying, I'm meeting Sadhguruji tomorrow. What should I ask him? What is the purpose of life? What is the purpose of life? What is the purpose of life? I was like, guys, just come up with something else. Essentially, you're asking what is the use of life? There is no use, even if you're not born, everything would be fine, believe me? Actually, it would be better. If you could be invisible for a day, what would you do? You wouldn't know. At least there should be texts on the third child. Two children should be okay, but third one should have texts. I don't say that because I'm the fourth among the siblings.


just put a couple slides before we get into the notebook. So this is a project that I've been working with as part of a larger project looking at landscape evolution in the Colorado Front Range. And this is a little aspect that's developed out of that of thinking about what happens when you start thinking about feedbacks between the hydrology and the geomorphology which produce a heterogeneous surface where you have exposed bedrock in some places and soils, relatively thin soils in other places. And this is like I said in collaboration with Greg and Suzanne and Bob. And I want to just, you know, Greg kind of already went through this but from the kind of geomorphic view that one of the simplest visions we have is this kind of characteristic parabolic form to hill slopes. This is just a view out of my my brother and his house in his backyard, right? And so when we start thinking about simple models, there's two simple models that we can bring in right into land lab or components in land lab that basically are just solving for mass balance between the flux downslope and the conversion of bedrock to soil. And so one of those is the kind of creep model that Greg had in his notebook and it's just saying that, you know, there's a linear dependence with slope in the sediment flocks and that's what gives us our parabolic form. And then oftentimes, and this is based partially on observations, it's partially on empirical measurements of soil production rates, we fit something like this is an exponential soil production function. Sometimes people argue for a humped one where it goes down to zero with that zero bedrock. But these are basically two core components that a geomorphologist, if they have soil and they have the surface might include. But what happens when you go to hillsides like this, so this is just the image I took near Gold Hill, Colorado up in the four mile watershed. It's actually in the scar of the four mile wildfire. And you can see it's very heterogeneous. There's in the background, you see steep bedrock cliffs. In the foreground, you see some bedrock tours. And you see relatively thin soils that are kind of dispersed in between. And so the goal that I have is can we replace this kind of general soil production, generic soil production function with something that is more process specific. And in particular, I've been experimenting with processes that might be conducive towards an agent based model. I'm going to think about trees. I'm going to share with you a little bit of my thoughts on trees. There's lots of things we might consider with trees when it comes to soil production. This is just a conceptual figure from a paper and review paper in 2013. I'm really only going to focus on kind of what the biomechanical weathering component of tree roots might have on producing soil, right? So we might think that roots grow to a certain depth, they grow to a certain rate. So we can actually relate that tree property to a soil production rate in an actual landscape. And this is really kind of building off the backs of other kinds of models that are similar in spirit, albeit not using an agent based model. So these papers back in the mud and roaring at all, including Jill here who's here with us today. And I just want to give you a brief, instead of the net locale model is there for you that I developed, or I should say a simple version of the one I developed is there for you in the repository. But I thought I'd just give you a conceptual model of what's actually going on in this agent based model. Our agents are trees. They're basically borne by seeds. So they have some seed production. They have some seed fertility. They have some seed dispersal properties. And then there's some, when they live, they have an area. So the red domain here is basically the patches on this kind of cartoon grid where they might have resource competition. So you can imagine that their growth rate shouldn't just be some simple plant functional type function, but it has to have some sort of resource competition associated with it. So there's a neighborhood that matters. And this is where the agent based modeling is well suited to it. And this is quantified through this term that I use. It's just a resource stress term that allows the resource stress can alter the growth rate. It can alter the fertility. It can alter the death rate. And then the idea here is that the only mechanism to produce soil in this model is through trees interacting, getting their roots down to the bedrock soil interface. So if trees start growing in places where there's already soil, then they just grow happily in that soil. But as soon as their roots come in contact with the interface of bedrock and soil, then they can start converting bedrock into soil. And so this is only, like I said at the beginning, only one potential role trees play, but it could be a potentially important one. I'm interested to see how these dynamics may play out with our more simpler models of soil production.  And I'm going to use land lab to simulate the erosion and sediment transport. So there's both the kind of vertical loss of soil and that then being spread out across the landscape. So we might expect different results if we actually have a proper transport model. And to give you, for those of you who are familiar with net logo, I've kind of listed out all the variables that are in the model on the right-hand side. You can kind of just look at the left-hand side. There's basically three basic categories of things going on in the model. There's the trees, the individual tree, the forest dynamics. Those are in turtle in the net logo parlance. Those are the turtles in my model. And then there's the patches in my model, which are carrying states like soil depth, elevation, things like that. And those patches are what I'm going to actually use to link with my land lab model, which is modeling the soil erosion transport, with a variety of potential feedbacks. In fact, the version that you guys have is a simpler version. So some of these feedbacks are going to disappear. But you can imagine, we can add as many of these feedbacks as we might want. And all the bolded text that I put on that right-hand side, those are just inputs. So those are things that we can now start playing with, you know, what is the dispersal distance, characteristic dispersal distance of trees? What is the maximum rooting depth of a given plant functional type? So we can start evaluating the sensitivity of these different things. And then the key thing is that I'm using Pinet logo to link the two, as opposed to building it all on a Python environment. Before you get started, I just want to ask a technical question. My Pinet logo doesn't load because I don't have something called Jpyte. JPYPE. Does that ring a bell to anybody out there? I ran into the same problem. It's whether you... So in the documentation, it'll take you to how to install the Java stuff, but I still ran into problems with what directory the Java was in. But that's what it's referring to. And it's one more step in the installation instruction. Yeah. So it is in the Pinet logo documentation and the Java issues are real. And also the version of NetLogo you have is real. So if you have the latest version of NetLogo, it will not work. Oh. Well, that fixes that. So I do. Yeah. So in the notebook, I have some comments to that effect. Basically, it works with 6.0 and not 6.1. So hopefully, I had to learn that the hard way myself as I was learning this. And then the documentation proved and said, oh, we don't support 6.1 yet. So be forewarned. Oh, that makes you do so much better. Yeah. No, I struggled through that myself. I was like, I think I'm doing everything right. But it turns out that it's just not supporting the newest version. So any of the versions of 5, NetLogo 5, it will work with. And 6.0, it will work with. And hopefully, they're working towards getting to work with 6.1. The final little, sorry, is there any other questions that popped up? Sorry. Thank you. No, no problem. The final piece is that I have a bunch of these slides. I'm not going to show them. I don't think I'm going to show them until the end. I want to get to the notebook first. But one instinct or insight that can be gleaned right away before going out and trying to link a landscape evolution model with this forest dynamics model is that simply adding some lost term like erosion means that this interesting question from the geomorphology community is that we can actually produce steady state landscapes that have a heterogeneous bedrock to soil cover ratio. And so this is all done in NetLogo. I did here is just I'm plotting up soil fraction as the function of time for a given set of input parameters and showing you that it does obtain a steady state soil fraction scenario for different values of erosion rate. If I only allow erosion to happen in the soil. And so I have a few other like sensitivity plots I might show to you guys at the end. But this was what gave me pause and say, OK, now we need to stick an actual proper sediment transport model because how robust are these kinds of results that I'm kind of hacking into a NetLogo model? All right. I'm going to switch now to the notebook. Let's see. I'll share that at the right one. All right. Do you guys all see my notebook? Yeah. Yes. Yes. All right. Perfect. So there's the model. I'm going to leave that as a black box right now. It's a little model I developed with all those components in it. And now I'm just going to show you how we can couple something simple like the linear diffusion style model that Greg was showing to iterate through letting the forest evolve and then diffusing the landscape. A couple of things about this notebook, if you're trying to write it here, it says right at the beginning, you need 6.0, not 6.1 is that first thing. You need this model, obviously. So this is how you would call any sort of model if you want to start bringing it in. In this case, you just keep it in the local directory. I am using the Seaborn library for data visualization here. So and I've also added this thing where there's a CSV file. I'm sorry, I didn't update this. Or you can use an Excel file. This is a weight. So in that logo, it's very easy to see the random number of agents. This takes, you can just impose where you put agents in R in the model so that when you're running it, you always have the same initial condition. So it's not required to run this notebook. But if you want to compare plots as we go through, it'll be easier. Just look at kind of apples to apples. So at the beginning here, we're just going to import all the packages we need from LandLab and from Matplotlib. One thing to note, and I'll say this below, but Pinet logo basically brings in grids as pandas data frames. So you need to deal with converting them over from pandas data frames into the grids that are used in LandLab. So let me just run this. I'm going to open NetLogo here. I strongly encourage you to set this GUI flag to false. Things run tremendously faster if you're not actually using, doing all your visualization in Python is really, really handy. And then here, I just have a check for the version just to make sure you meet that condition of having an acceptable version for Pinet logo. I've stuck this figure in that is just like the figure I showed in the PowerPoint, only it's showing you which elements of complexity I've removed, right? So I've got strike-throughs on all the pieces that I took out of this simpler version of that logo, right? So we've gotten rid of some of the potential feedbacks, but it'll at least illustrate to us how we can pass grids back and forth and we still get some pretty interesting dynamics out of it. So one of the nice things about using Pinet logo is that you can take your knowledge of the syntax of NetLogo and you basically just stick it into these command prompts.  So in this case, I'm just setting up, I'm loading the model and I'm setting up all of these parameters that are important, like the initial number of trees, the tree root max, the tree age max, seed max, the seed dispersal, and the seed decontinue. And then once I do that, I can set up the model, right? Take a second. And then this is this optional cell I was telling you about. So this is just the piece where if you want to stick in a CSV file or an Excel file that has the initial position of all your agents, this is, it's really simple. You can just bring it in as a PANAS data frame and you can, you know, you can check it out. We'll map it out real quickly. I set the initial coordinates of four trees that are equally spaced apart from each other throughout the model domain. And so we can go ahead and map that out. So we're going to, the first part here, we're going to report where all those trees are from NetLogo. And then we're going to also get this NetLogo.report. We're going to pull some of the constants that are buried within the NetLogo model because I want to show you some relationships that are implied by using this model. And then we're just going to make a figure. And this figure on the left-hand side, I'm going to go ahead and run it. On the left-hand side, I'm just going to show you where the initial tree locations are. And on the right-hand side, I'm going to show you what my root function actually looks like in the model. So it's just telling you that in this version of the model, I've specified the age of the trees. They have a lifespan. I don't have them dying before the end of their lifespan. So another version I do. So in this case, I'll live to 100 years and that they, their roots will grow initially very fast, which is based on the published literature around root growth dynamics. And it reaches some maximum value at the end of its life and it slows down. So the root growth slows down with age. Now, I also have this term, this is this resource availability term that is in my case encapsulating resource competition from neighbors. But you could imagine using it also to capture variable climate, variable rock soils types. So you could use this resource term to actually affect the dynamics a lot. And what you're seeing is that if I have a value of this weight of one that I grow on my maximum trajectory and then anything less than that, I grow at a slower rate. The actual trajectory of trees doesn't look like these simple curves because during their lifespan, there are new trees that are being born and old trees that are dying. So their trajectories are jumping on and off of different versions of these curves. And so like before, we're going to use this patch report. So this is another function. There's only less than a dozen functions really within PyNet logo, but they're all very powerful because they allow you to basically either get information from that logo or modify things that are in that logo. So in this case, we're going to report all the elevations. I set it up so that I actually in dealing with elevation, the initial condition in that logo, you could do it either way. So here I'm going to report my elevations, I'm going to report my initial soil depths, and then I'm just going to plot them up. So here we go. So I'm starting from the initial condition where there's zero soil depth. So this right hand side is good. It means it worked. There's no soil anywhere. When I start the model, I set up a ramp of around 36 degrees, basically going from the north to the south, pretty similar to the setup that Greg had in his example. And now we can go ahead and run the model. So when we run the model, you have to give it some time, number of time steps to go through. So this is something in, we talked about earlier, you have to think very carefully about, especially as we start coupling them, because you want to make sure those time steps make sense. And we're going to report back the locations of all the new trees that are produced in the model. So the second bundle is telling us. And then we're going to report back all the resultant soil depths and plot them up. So let's go ahead, run it. It shouldn't take too long. And unsurprisingly, I set them up so they're equally apart. So we have these four little clusters of trees. Notice that the original trees are gone. And so the legacy of those other trees is in the soils, not in the current locations of trees. One of the very important parameters in this model is the dispersal distance. So if you have a very short dispersal distance, then you can set, in this particular model, the forest can go extinct. It can die because they can't get outside the resource competition. If you set the dispersal distance very wide, it's like having random seed generation all across the landscape. So I have a pretty tight dispersal distance here. So you're going to see these clusters, makes it easier for us to see these clusters as they grow through time. And then the other thing we can look about is we can, we can use Pinot logo to start looking at attributes about our agents and then using all the power of the statistical packages and plotting packages in Python to interpret them. So it's really nice because in this particular example I'm going to show you, I'm going to report back the age of the trees. I'm going to report back the soil depths and report back the soil fraction and then just plot them up as histograms. And so, you know, we didn't run our model for very long. In general, this distribution of tree ages, if I don't put a resource depth on these trees, it basically will bounce around where you see equal distribution at all ages, right? So there's just as many trees dying at any given time as they're born at any time. Now, we ran it for a pretty short time. So we're really sensitive to the initial conditions that we have. And then we can also plot up. We see we got to have a distribution of soil depths. I just want to point out, in this particular version, I have a maximum soil depth of three meters. It is very rare to produce an actual soil of three meters because they're all competing with each other. And so there's being scales of the rare tree that gets outside the patches that can grow for its entire life at that maximum rate. So you're seeing most of our trees in this particular example, I should say most of our trees had grown only to soil depths of around half a meter, right? So we get this very skewed distribution. And again, that's because we have this resource competition. And so this is just, this first example was just meant to show that you can drive everything in NetLogo within a Python interface. And there's some really, I should stop here and say there's some really nice tutorials on PinetLogo where they do a nice job of showing how you might do a sensitivity analysis. So if you wanted to paralyze your NetLogo runs so that you have a bunch of different runs and you want to do the statistics on it, it's a way more efficient way to do that than trying to work within NetLogo itself. Or at least I should say you have the full advantage of all the Python packages that exist to do those things. So running a headless version of NetLogo pretty straightforward. There's just a couple different kinds of commands you would use, these report commands and these set commands in order to do that. So in the second example, I'm just going to, I have basically three parts. The second part, I'm simply going to do one time step at a time, one bulk time step at a time. I'm going to run NetLogo. I'm going to run LandLab.  And the final example is actually just bundling all it up into a for loop to see what that might do over longer timescales. So let's talk about passing variables between NetLogo and LandLab. I'll stop right here for any questions or comments. So this works very much like our NetLogo as far as I can tell. I don't know if you've used that or not, but where you have our primitives that you just plug in within your R script to do stuff. In fact, I think in the documentation of PinetLogo, they've taken their inspiration from our NetLogo. So it's exactly, I think you're exactly right. It has the same Java problems that our NetLogo does too. Okay. So linear diffusion or soil creep is actually a relatively straightforward thing to implement in NetLogo. So if I were only doing that, I actually think it would be just as easy for me to do that in NetLogo. I think the real advantage of bringing it into LandLab at this stage is that there's four different possibilities we might want to use for our diffuser. We might have a linear diffusion model, a nonlinear diffusion model, a depth dependent diffusion model, right? We have all these components that are already packaged and ready to go for being in the LandLab interface. And so really that's where the power of it comes. And so that's what this is all with an eye towards. We're going to basically do our sensitivity analysis on all these different variants of alternative hill slope sediment transport models. Today, I'm just going to show you the simple case using linear diffusion. So in this first cell, I'm going to reinitialize the model. So because I've already set up all my inputs, and you could set this up with the text file too, I'm just going to reset it up to that initial condition. And the second patch here is just telling me I want to read it in from that CSV file for the initial conditions again. The one new thing that I'm doing here is now I will also want to set up my LandLab grid at the same time so that it matches, right? We need these grids to conform to each other. So the sizes and the dimensionality of the grids need to be the same. And like I was saying before, PinetLogo brings these things as pandas data frames.  So this time I'm going to run a thousand ticks, which my functions are kind of set for a yearly time. So that represents like a thousand years. And then I have to set this similar to the way Greg dealt with diffusion, having this depth-dependent diffusion so that you didn't have production of soil on very thin soils that wasn't due to the processes we care about. So I'm going to set that characteristic depth of diffusion. And then this is just setting up my initial LandLab grid with its boundary conditions. And very similar to what Greg showed before. So I should forget if I ran this. It doesn't matter. I can rerun this as many times I want because we're starting from scratch here. And then I'm going to add some fields. So in this case I'm going to add a topographic elevation field, a past elevation field, a soil cover field, and a soil depth field. And I really should rename the soil cover field. It's actually my diffusion coefficient field because I'm using it to modify the diffusivity as a function of soil depth. Okay, so that's very straightforward. Let's run NetLogo and send the values to LandLab. So we have to give NetLogo a command it recognizes. And in this case I've just said it kind of so that I can have any time I will just send it to this go command. And then I just send NetLogo command go. And then I have to when I report the elevations and pass them to LandLab, I need to convert them to the size that LandLab is expecting. So that's what all these little things are doing. I'm just reporting the elevation passing the LandLab by reshaping it. Same with the soil depths. And then I'm calculating this diffusion coefficient field based upon the depths. Now this is exactly like what Greg showed. He had one minus this exponential. I put 1.0001. And it's because if I have a zero diffusion coefficient, it raises lots of errors in your linear diffuser. So basically this is effectively like saying I have a diffusion coefficient that's 10,000 times slower than the maximum value I'm using for places that have soil. So it's a very, very slow. It's actually an extra source term for sediment in the way that I'm doing the model. But it's very small with respect to the soil depth. And then I'm also going to print out the mean depth for comparison later. So this will tell us how much soil is being produced. And it also tell us, kind of help us keep track as we redistribute soil. Are we doing anything weird by moving soil around by the way we've set our diffusion model itself? So let's run it pretty fast. 1,000 years runs pretty good. We're going to see when we do. Go ahead.  You've set it up. Then you're just going to run NetLogo for 1,000 years. But it was not without anything. So I was wondering if maybe you're going to do this later. I thought maybe you'd want to step, you know, one year through NetLogo and then do LandLab and step through NetLogo. Yeah. So in the for loop, I'm going to put steps in. So I just want to show that we can pass these variables back and forth. That's going to be really important, right? This gets us sensitive. What are the right time steps to choose? Because do I want to do NetLogo at an annual time step? Because that's going to be really computationally expensive. Or in the example I show, I do the half-life of a tree. So every 50 years I run NetLogo and I re-diffuse the landscape. So I'll show that in the for loop. Okay. So we've run it in NetLogo and so we're ready to redistribute the soil. So much like Greg showed, I'm just going to initialize the diffusion component. And then all I'm doing is I'm going to keep my elevations from this step. And I'm going to record them in what I'm calling this ZP, which is the prior Z. And then I'm going to diffuse the landscape and then I'm going to recalculate the soil. So that's all I'm doing here. So let's go ahead and do that. And now we can make the same figures we made with the initial conditions, exactly the same plotting functions here. And we can look what we get. So we now have this kind of patchy soil that is inherited the initial condition. And you can see we get this droopy diffusive landscape, right? So there's lots of these little kind of droops that are correlated with where we've actually had trees. So it looks very linear, like we would expect for linear diffusion in the places where the trees haven't made it to yet. So that makes good sense with what we're thinking. And we look at our mean depth, 0.052 because we had 0.052 before. So we're not like doing anything weird with the soil depths here. We're preserving the soil. We're just moving it around. And then the other thing I want to show you is I'm just going to do another figure that shows how the elevations have changed with respect to the initial condition. So I just run that. And the initial condition is this red line. And you can see I have places where I've accumulated soil. I have places where I've eroded soil. And in this particular case, because of the way I set up that initial condition, it's concentrated kind of in these two quarters of the, you know, in the middle of the landscape, it looks just like the initial condition. But you can see stuff is marching its way downhill. And I'm going to go real fast to this part because there's not much new here. The only thing that's new is I now have to take that elevation data and send it back to net logos. It means I need to put it back into a data, pandas data frame. And I'm going to do that using pandas. And I'm going to then use the pie net logo dot patch set to reset that the elevations in the depths. I'm going to go ahead and run it quick moment. Okay. And just plot it up again. Now, this is just a check for me. In this version of my net logo model, I don't have any feedback between the elevation and it's only a one way feedback, right? So elevation is getting modified in land lab, but not net logo. So my elevation should look exactly the same because I haven't sent it back to land lab. But if we compare our soil depth, we can see we produced a lot more soil now. So you can just see this is the style of step we would run. And then I'm almost done here. I guess the only thing I'll say here is this is exactly what Michael's bringing up.  And then defusal landscape, we would want to set some time step that makes sense. So I've set the land lab time step here to be 50 years, which in this case is half of the average lifespan of a tree. I'm going to run it for much longer. Everything else is the same. That's just setting up the initial conditions. And this is everything I had in the previous parts. Just highlight this, except I've just bundled it up into a for loop. So we're just going to run it for the range of time and see what we get. Now, it'll take a few minutes to run. So I guess it would be a good time to bring any questions out. So you're playing with an oak command on this, unless you've defined go. I mean, normally go is a loop in NetLogo. But you can also do a one shot. I guess you're just running go once, right? Yeah. And this is, to be clear, this go that the variable go, perhaps I should rename it, it's not the same as the go command in NetLogo. I've defined the whole string as go. So I set what that time step is by defining the string up above. So in this case, by me putting my dt of equal to 50, it's running go for 50 time step. Got it. Got it. Okay. Yeah. And just constructing that string dynamically so I can monkey around with it. Okay. Any other questions while we're waiting for this? So I have a question. So what do you think? What do you think is going to happen if we run? So if we go back to what it looked like after this was after 1000 years, but not iterated, we're now going to run it. We're now running it in 4000 years, but it's iterating over much shorter time steps. So I'm curious, what do you think is going to happen to the topography? How's it going to look different? Or will it look different? I'm excited to see some clustering. You see some clustering? Okay. Thanks for sharing this stuff. Yeah, of course. Much appreciated. Other ideas? How are we doing? Will there be net erosion over that time? Well, so the way, so this is really important how you set your boundary conditions and, you know, in this case, I'm not uplifting the landscape, but I have a closed boundary condition at the top of the model domain. So it means that there's no input from the top. So stuff is just trundling downhill.  And there's no accident at the bottom? Well, it is. The bottom is held constant. So it's effectively like having an open boundary condition at the bottom. Yeah, I thought there was. So that's why I was thinking it would overall, there would be some degradation. Right. So if I add uplift, you might expect that it could evolve towards some steady state. In this case, we might expect, if we're just doing diffusion, it would start relaxing down because I'm just holding this at a constant elevation. That's what I meant. So it would decrease. There would be some net loss. Yeah, exactly. Okay, so you would expect that. Okay. Yeah, exactly. Yeah, and we're only running this for 4,000 years. So let's run it. Let's plot up what we see. It's okay. So one thing I'll point out is, and it's a little hard to see, it's hard to find good color ramps to show this, but you get these little pockets of, I would call them Torah-like features where they're kind of, they get abandoned and there still seem to be on the landscape. But because we ran it for a long time and because we iterated through shorter time steps, we get a much smoother landscape, looks a lot more like a diffusive landscape. And of course, we've allowed more soil formation to happen. We started with no soil, allowed more time. So it means that more of the landscape has been covered. But even after 4,000 years, there's a lot of places with zero soil depth. So it's telling us that it takes a long time for this particular mechanism, given this particular configuration to actually produce soil all across the landscape. And so maybe an easier way to show this is to plot up that same initial condition versus the current condition. And hopefully the thing you see with this is that I printed out the mean elevation. So this is to Mary's point. We've actually got net erosion, which is good. So it's behaving in a way that makes good sense. It used to be 142. Our initial condition was like 142. And we see the same kind of like bouncing around that initial condition, but it's getting a lot tighter. And it's getting a lot tighter around that initial condition, because places that are have bedrock exposed are trapping soil from uphill. And therefore, you're smoothing out the landscape. But at the top of the landscape, we're getting something that looks more like our parabolic top, right? But notice, and it's again, very hard to see, even on this parabolic top, there are these places, these individual patches that are getting abandoned. Because if they can't get, if they can't stay contiguous with the soil that's fluxing downhill, then they will get abandoned because they never have, if there's nothing flowing into them, they're never going to get new soil until you randomly get a plant up there. So they can stick around for a very long time, even though you're smoothing out the landscape. And then finally, we can get a cleaner, a cleaner look at the distributions that we looked at at the beginning. So we now get cleaner distribution is look at, yeah, we get something like equal chance of all elevations and again, a very skewed soil depth distribution. But even if we run for a long time, we don't get very deep soils. And that's because we have resource competition going on here. So I'll stop there because I've talked a lot. But I thought I'd open up for comments and questions. There's not very many feedbacks that we've included in this one, but it's still quite interesting. Now, one thing I think is really interesting about this is that you get very smooth terrain, but really bumpy depth to bedrock, your soil depth is very heterogeneous. It doesn't get smoothed out. That's right. And that's because, and part of this is the paired thing to do with the start with the initial condition of some soil that could be lost as opposed to starting with zero soil. So it takes a long time. I'll just show one other thing very quickly. Let's stop here. This is just back to that PowerPoint. Sorry, I should have advanced this. So this time scale of which, even if you had no erosion, so that's what these plots are showing is there's no erosion. This is just a net logo model looking at the kinds of time scales and their sensitivity to these different input parameters is pretty long. So for me to cover the entire landscape with just this mechanism of soil production, it's taking on order thousands to tens of thousands of years depending upon the input parameters I put for the tree dynamics. So I'll just stop there, but that's why you're still preserving these little nubbins. It takes a long time just to randomly occupy those places where you preserved a little tour. That's awesome. Second, that's super cool. And I have to say that your end results from the model with, as Greg was pointing out, even though you have a relatively smooth surface topography, that the soil depths are really variable, that's what we see with GPRs that we see. I've seen with a lot of field digging in similar locations. So that's great. This is awesome output. I'm curious and this is just kind of from my own personal interest. In the more complex stuff you're running, have you played around at all with where you have trees, having higher diffusion rates, or you always applying a uniform diffusion rate? So that's something I didn't talk about, but we can imagine there's two feedbacks that I'm actually explicitly trying to link to the model. One is using the density of trees to set the diffusivity constant itself. So that's a link to not only soil production, but it's a link into the diffusion. And also, in parallel, think about using that as setting the cohesion. So you can think about that from a mass placing perspective too. So if you have high root density, potentially that could stabilize these soils depending upon, again, your initial conditions, your boundary conditions, all these things. The interesting thing that I didn't show in this example is that when you add resource depth, so when you say trees don't just live for 100 years or they don't just live for 200 years, what happens is you get this selection process, this feedback in the agent-based model that enables deeper soils. So if you just looked at the soil cover over time, it looks very similar to not having that variable lifespan. But if you look at the actual soil depth distribution, it alters it quite a bit. And so there's actually some really interesting dynamics in thinking about, well, do we actually know what these functional relationships should be so that we could make a prediction of soil production that is based upon plant properties?


This is covering the spread part of the Fandall podcast network Big night across the NBA and the NHL forward tonight with nine games in the NBA and five in the NHL as well We're gonna break down all that today with Tom Vecchio picking his brain on Traditional market bets and player props across both leagues to get you ready for should be a fun Wednesday night This is covering the spread right here on the Fandall podcast network and Fandall research My name is Jim Sonnis. I am a managing editor of digital media for Fandall research joined here as mentioned by Tom Vecchio You can find him on Twitter at Tom underscore Vecchio one and Tom pretty fun night of sports coming up. How you doing today? I'm doing good. Yeah, really really interesting night across the NBA specifically. There are a lot of high-over undergames There's also a number of injury situations, which could change things massively for some game lines But I do think there's some really good spots to attack Yeah, and we'll talk about those spots We'll talk about traditional market bets where you're talking about the impact of those guys potentially sitting and much more to get you ready for Wednesday in just one second a first-day reminder to make sure you are subscribed to covering the spread wherever you get your podcast later on today Tom is back with you once again. We talking about a thriller Thursday night between Easton stick and Aiden O'Connell You're gonna need some action to have some fun with that one You know if you are so inclined But that'll be up on the covering the spread podcast feed later on today and also up on Fanduul TV plus I gave my first look at NFL week number 15 spreads moneylons and totals my models like that is up on the Covering the spread podcast feed the Fanduul YouTube page and Fanduul TV plus as well Score early this NFL season with Fanduul America's number one sports book right now new customers get $150 and bonus bets with any winning $5 moneyline bet That's 150 bucks if your team wins if you've been thinking about joining Fanduul There is no better time to get in on the action. 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Let's dig in now to the NBA Tom and talk about last week we saw the in-season tournament and Seen like a lot of fun honestly wrapped up on Saturday Lakers taking down the Pacers and I want to talk to you about takeaways from the tourney I think mostly from like a team level perspective from a betting perspective You know, what were the big things that stood out to you or was this format too unique to have any major takeaways going forward? I Think there's if we have to take I think there's some minor things we can take away potentially to move forward with One the Pacers are a very fun exciting team I mentioned last week that they're playing you know all these games to the over but they actually are a solid team And it's like they got a little bit of a taste of what postseason ish basketball is like sure And that is a building block for them. So a part of me Likes to take the Pacers to win the central with their plus 650 right now to win the central The cabs are at plus 290 and the bucks are minus 240 So the Pacers are showing that they can kind of hang with some of these top teams So I like them at plus 650. They're sitting in a playoff spot right now there are only a few games behind the box and I Almost just want to take this position as a spot to hold in the portfolio Waiting for a cash out and just cash out at plus money I still think the bucks are the best team in this division The cabs I'm dealing with some injuries. I if it was a seven-game series. I would take the cabs over the Pacers But I think they all can make the playoffs But just holding that ticket if it gets later in the season you could just cash out So the Pacers got that taste of postseason. I think they're for real They're here to stay and you can probably use that as some leverage going forward where they play all these games to the overs They're not amazing on defense And I think they'll still be underdogs as they are tonight And I think you could just continue to take them get them with the points is a situation We think the market has been a bit slow to react to the Pacers. Do you think what they're doing is sustainable? What's your read on where the market sits on them right now? So the I think the market reacted Appropriately especially with Tyrus Halbert into an MVP. I think was that like 30 to 1 to an MVP things around 16 to 1 right now We have to double-check that 15 to 1 16 to 1 for Halbert into an MVP somewhere around there Yeah, 60 or 15 to 1 right now 15 to 1 so like it he moved and it's like okay He has this like these big performances prime time and people are like buying into that so the hype is real around Haliburton and there are a lot of encouraging reports From Adrian Wojnowski that Haliburton is trying to do what a tentacumbo did in Milwaukee and instead of you know Moving somewhere else. He wants to bring people into the Pacers. Yeah so at the trade deadline There's a lot of rumors that they're going to be very aggressive at the trade deadline and that could just be another thing that bolsters They're they're central to vision odds Okay So we got a little taste of the Pacers being a fun basketball team in the in-season tournaments got to see them You know make a really good run didn't get the win there But some potential takeaways about ways to get exposure to them going forward again 15 to 1 for Halbert and to win MVP And then they are plus 650 to win the division and Tom as we talked about before I'm not the most in tune with the NBA. So I want to ask you about the division stuff Is the benefit of winning the division great enough where we'd see the bucks like fully fully pushed during the regular season in order to win that division because we know that like they're a team that has you know They have NBA finals aspirations We've seen teams like that not push a hundred percent during the regular season if it's tight late in the year will they actually go all out to kind of maybe negate a run from the Pacers or calves or Does it not matter to it to the extent where they care a ton? So the division the division definitely Matters less because at a certain point They're gonna be worried about the one or the two seed against the 76ers of the Celtics It's not about the division so okay They're gonna be pushing to keep the one seed rather than keep the division if that makes sense So like having home court against the the Celtics is more important than having home court and winning the division over the calves Okay, that does make a lot of sense and I appreciate that explainer Let's shift now and talk about the games in the NBA for tonight nine separate games Let's begin things off with the traditional market bets You mentioned a lot of things up in the air as far as injuries go Where is he in value right now in the traditional markets at fangirl sports? Let's go to two of the late games and I'll be starting off with the Brooklyn Nets plus two and a half Against the Phoenix Suns the Suns are on the second night of the back-to-back the Suns are dealing with a number of injuries so last night Kevin Durant did not play for the Suns and You know will he play tonight against this former team? Not not sure yet Bradley Biel for the Suns returned to the lineup last night It was his first game since November 12th and Given his injury situation the fact that he this was his fourth game this season So given his injury situation, I'm not entirely sure that they're gonna push him out there on the second I have a back-to-back Josh a Koji also is not expected to play for the Suns tonight So their lineup is completely in flux tonight and are gonna be shorthanded in some capacity The Nets are playing solid ball. They're 16 5 and 1 against the spread this year. They didn't play last night They're coming off a full rest and they match up well Against the Suns from like a size perspective So when we add all this together And maybe do the Nets want to get some a little bit of revenge knowing that Durant's on the other side They traded him like all these sorts of things maybe But it really does make sense for the Nets who have been playing really good ball against the team that their lineup is Shorthanded they're on the second back-to-back There's a lot going on combined the fact that yeah, the Suns are struggling a little bit on defense this year Yeah reporting was a KD should be good to go tonight Beal though had a minutes restriction on him last night So I kind of assume the same as you were less likely to go for him and a Kogi or Koji getting getting hurt in that game Last night a lot of ambiguity for the Suns so the Nets plus two and a half Minus 1 14 right now for that game mention another game out west in the later slots Which one are you looking at there? That would be the Knicks minus six against Utah The Nicks are actually playing really solid basketball as of late looking at their Recent performances. You know you see these two losses. They lost against the Celtics and they lost against the Bucks I don't consider those bad losses. They're really good teams and more importantly the jazz are extremely injured especially when it comes to their big men between Walker Kessler and Kelly Olenek should be good to go large marketing is questionable Jordan Clarkson is out And John Collins is also questionable for the Utah Jazz So this is a really straightforward spot for the Knicks they've been playing good ball despite some actual losses in terms of the win-loss column and Julius Randall being at like peak form right now their powerful He really should be able to dominate down low given the lack of depth that the jazz haven't big men So Knicks they and they're also getting like a tough break because like oh They have to play the Celtics and the Bucks X amount more time because the in-season toward them in and they're kind of I don't want to say complaining about that But that's kind of the vibe that I've gotten from some of these reports where it's true Like they have to play against the best teams extra times just because the in-season tournament This is a chance for them to write the ship get back going like in an easy matchup And it's also a big pace-up spot for them because they're dead last and leading pace So literally anyone they play is gonna be a pace-up spot and the pace-up spot matters here because they are laying You're laying six points and you want them to be able to get a larger total when you're laying that much In a game so I think that does make a lot of sense Mitchell Robinson out for the Knicks kind of a bummer there But something they've got the depth to cover up for that in the interim. What about player props Tom What stands out to you there across the NBA for tonight? Let's go to Hawks and Raptors. This game has a One-and-a-half point spread has a two forty-and-a-half over under Massive total super close spread fantastic for player production This is also a pace-up spot for the Raptors. They're 19th in the league. The Hawks are sitting at fourth So let's go to the PRA that points rebounds assist combined for Scotty Barnes for the Toronto Raptors over 36 and a half PRA sitting a minus 111. He's averaging About 33 and a half 34 and it depending if you want to round up or not But the double double slash triple double potential from him is there every single night The shot volume is there from him the usages there You know, can you look I mean the steals and assists of the steels and blocks don't matter too much for PRA but he's all over the place in terms of filling up the stat sheet and defensively this game is not gonna have much of it as the 240 over under would indicate and a One-and-a-half point spread means theoretically, this is probably one of the best games on the slate that has overtime potential So if we look at Barnes and his production when he can already go for 30 plus real points I love this game environment from a fancy perspective. I spoke heavily about Scotty Barnes on the daily iso I love him for PRA bet. I'm not worried about the Hawks defense Everything every box is possibly checked for the Raptors tonight. Okay, so Scotty Barnes across the board Not just for betting but also in DFS Forts and I check out the daily ISO on the number fire daily fantasy podcast feed for that But then Scotty Barnes the PRA bet over 36 and a half Minus 111 right now at Fandall Sportsbook for that one any other player props your eye in for tonight, Tom I don't believe any Lakers props are posted They played last night and the report after the game was that both LeBron and Anthony Davis Their status is quote-unquote uncertain So I'm not sure if there were are their Laker props but points props for the Lakers posted yet But if there are or once there are D'Angelo Russell, they're starting point guard could be the new primary Ball not just a primary ballhander, but the primary usage player if LeBron and AD are out tonight and the Spurs are terrible this year Like despite the hype around women down and they're terrible their defense is terrible They play super fast bull teams top 10 leading offense base close spread high over under D'Angelo Russell could be the player for the Lakers tonight if LeBron and AD are out How high would that number need to be for Russell to scare you off? Just in case, you know, we do see major adjustments for injuries and stuff like that How high would it have to be for you to like maybe not? It's probably gonna be in the low 20s. Okay, so anything under If it gets to 24 and a half, I don't know if it'll get that high I don't know what is normal normal points prop is but like a 22 20 22 and a half 23 and a half. I think it's fine Probably talk about this a lot on the the NFL shows But is Russell a guy where you'd look at alternate markets to try to take advantage of potential variants Or is he not that kind of player even when those guys are out? No, he's he's been known to go for 30 plus. So that's I Mean given the matchup which I already love to begin with okay I mean that that's actually a pretty good slant that I didn't really think about okay So check out the end of Russell props once they're up for the Lakers and Spurs game 24 and a half is where Tom gets a little bit hesitant for the regular market, but also could potentially dig into Some alternate markets for Russell depending on what those numbers look like for that one Let's talk now about the NHL Tom got some pretty fun games going on over there works night a total five games slate In the NHL side of things. Let's begin things with the traditional markets there as well What stands out to you in the NHL when looking at sides and totals the Bruins and the devils over six and a half. It's a plus 104 For the Bruins, it's expected that their top defenseman Charlie McAvoy is going to be out tonight the Bruins Got off to another super hot start They've taken a slight dip in production as of late defensive defensive, you know consistency as of late The devils got off to a slower start. They got healthy and their offense has really picked up and The Bruins also have an often awesome offense to begin with so these teams don't need help score Also, on the other side for the devils, their top defenseman Dougie Hamilton has been out for about a week at this point So they have like all these teams have all this offense lackluster on defense simply due to injuries and it really should just present a very wide open game for both teams tonight and if this game ends Five to four four to three in either side I won't be surprised that like it could be a it's a toss of game as the money line kind of indicate So I'm I'm in for the over not the winner Yeah money line for devils Bruins devils are minus 130 Bruins plus one away total as Tom mentioned is six and a half Plus one oh four on the over for that one any other traditional markets you're eyeing here Tom That would be the Kings in regulation their three-way money line, which is minus 125 Minus 180 for them on the money line. I think is appropriate Minus 125 for the regulation bet is what I prefer. They are back at home. They're coming off of a two game losing streak I'm not sure if I told you said specifically, but I've said it on other shows where the Kings are awesome And I'm not sure if a lot of people are particularly paying attention to that simply do the fact that they don't necessarily have a superstar and They're just like their start to the season was incredibly strong but there were so many other storylines where Vegas is strong and Vancouver strong and the Oilers were horrible and they fire their coach and like There's all these storylines going on and they got overlooked and the Kings are super strong because they play great defense They're super deep down the middle at center, which is an extremely important thing to have especially when it comes to the playoffs And they're coming off of two losses They're back at home They're going up against the Jets who are on the second night of a back-to-back They traveled from San Jose last night Also was announced yesterday for the Jets that their best player Kyle Connor is out for six to eight weeks due to a knee injury which is an immense Decrease to their offensive production and it's like this is the time for the Kings to like okay East Coast road trip doesn't end well with two losses back at home time to show everybody who we are Divisional matchup or non-divisional matchup Western Conference matchup come away with the win It's as easy as that and that's again a three-way money line for the Jets and Kings Tom likes the Kings minus 125 in that market Specifically you mentioned the money line the overall money line for them is minus 188 there as well I prefer to go that route instead on the Kings. Let's talk player props Tom What's you eyeing in that department for tonight? So the player prop market at least at first glance is is kind of tough tonight Because they're like the the aisles have been playing a lot better as of late and the their shop props are accurate They're just there's no value in the shop prop market. Yeah, the penguins are in a good spot tonight going up against Montreal I think Sydney Crosby is due for a goal. It's Sydney Crosby. He's amazing. We can see all these things But more importantly the matchup is fantastic He has great shot volume as of late and he only has one goal over his last four or five games So we have a player with immense skill easy matchup incredible shot volume. He's just not scoring. I just don't like the odds So it's kind of the same situation in some of these games where bad odds great player But it doesn't make the right combination. So the easiest spot for me tonight would be in Colorado with Nathan McKinnon over four and a half shots Minus 113 going up against Buffalo six-and-a-half over under I'm expecting the over McKinnon is averaging four and a half shots on goal per game He has I think he's third or fourth in the league depending after last night's I would have to check in terms of overall shots in the League he is constantly up there over the past few seasons top center top forward Top forward line center and the top power play unit. I'm expecting the overtip which means I'm expecting a lot of back-and-forth Their defense has certainly slipped which means they're gonna have to constantly push the pace because the Sabres aren't Terrible on offense this year. I was expecting to be a little better, but we had the right combination of odds role and Production and McKinnon kind of fits that not only tonight, but on most nights very annoying when the sportsbooks are on to the guys We want to target so I definitely understand the pain there McKinnon over four now shots minus 113 Right now at Vanduul sportsbook you mentioned the total in this game six-and-a-half right now for Sabres versus avalanche Over is minus one 14 So it's something you just like the game environment overall You think that McKinnon is a guy who with the way you plays benefits from that pretty greatly, right? And I mean his speed and and the lackluster defense really from the Sabres should allow that Okay, and if you can find a shot prop for the aisle someone like Noah Dobson I think he's at minus 188 or minus 180 for over two and a half which is It's a little heavy on the juice as you're asking me if you could find it at minus 150 minus one minus 140 I Think he's listed there. It's not in the alt market. Unfortunately. Actually. Yeah. He's plus 140 to get four plus shots Too much. Yeah. Yeah, it might be a little bit too much like over two and a half or three plus That's probably the best spot for him. He is taking a big step forward on offense this year Yeah, minus 182 to get three plus shots for Dobson. So again Was dang sports books doing their jobs. Well, very unfortunate When that happens. Alrighty, that is Tom and Vecchio Tom want to thank you as always for the time Looking forward to hearing you again later on today with prime time Tom talking that Raiders and Sharger scheme and good luck And enjoy all the basketball and hockey for tonight. Thanks for having me. Alrighty fine Tom on Twitter at Tom underscore Vecchio one I am on Twitter at Jim Saunders. You can find me on threads at Jim dots on us You can find fan dual research on Twitter at fan dual research subscribe to covering the spread to get the prime time Tom show later On today, you can also find that on a fan dual TV plus want to thank you all for tuning in Good luck to you all with your best for tonight as well. We'll talk to you once again tomorrow for NFL week 15 preview This has been covering the spread right here on the fan dual podcast network


Hi, I'm Kevin Trennicosta, a policy analyst with the Electronic Frontier Foundation. And I'm Ernesto Falcone. I'm the legislative counsel for EFF. And we're here to talk because the Senate just passed a resolution to save the 2015 open internet order, which was the FCC order that enshrined protections for net neutrality, abandoned blocking, throttling, and paid prioritization. So Ernesto, with this vote passed, what does that mean? So it's huge. I mean, it's huge because the United States Senate has officially put its stamp on where they think policy should be. And what that means next, now it's up to the House representatives to take it on from here. And we're currently in the House. 160 representatives have stated affirmatively that they'll vote for this, right? So it's really important that if you live somewhere where your representative hasn't come out in favor of voting for this, that you go and tell them. EFF can tell you where your representative stands at checkyourreps.org. So now that this vote has happened and it's moved to the House, what's the time frame? What's the timeline going forward? Most importantly, by June 11, the SEC's repeal of net neutrality takes effect. So once that day hits, then we will no longer be able to use protections. And the ISPs will then be free to engage in things like blocking, throttling, and I think probably most critical to them, picking winners and losers through paper monetization. What are the possible outcomes? So if it goes to the House and they say yes or no, and if they say yes, what happens? If they say no, what happens? So if the House, if 200, so going back a step, the means of forcing a vote in the House of Representatives right now is your House member has to sign what's called a discharge petition. The reason they have to do that is because Speaker Ryan has officially said that he personally will not allow this come up for a vote. That doesn't mean the House of Representatives will just not vote on it, it just means a majority of the House can override the Speaker. And as Kathy mentioned, 160 members of the House have already pre-committed to signing that discharge petition to move the bill forward. So we're looking at 58 more yes votes, positive affirmative commitments to vote on this bill. And at that point, we're gonna get to the president next. And with 86% of Americans in favor of net neutrality and a majority across party lines, it should be, you would think, a no-brainer.  So if it gets to the president, what happens? Do we know? So no one knows exactly how President Trump will decide on this. And that's to our benefit, right? He hasn't come out and said he will veto this once it gets to his desk. And I think that's because the fact that it's not just popular with one side of the aisle or the other, it's popular with Trump voters too. I mean, this is something when you're talking about 86% of the people are on one side of an issue, there's very few things in Congress that have that kind of lopsided public opinion. And that really comes down to, but a caution, don't take that for granted. What needs to happen from this point forward is you have to talk to your member of the House and demand that they vote yet, they have a vote on the Congressional Review Act. If enough members of the House feel pressure from people back home, which means going to their town hall, picking up the phone and calling their office, writing them an email and going to their district office. I mean, taking those steps to personally weigh in as they're constituent, that you expect them to be voting on this, those are the things we all have to do across the country to make this happen. A lot of people are gonna say, there's no way it's ever gonna come up to the House, but they underestimate, one, the internet freedom movement, I think, we're talking about millions and millions of people across the country. And it's still a political process at the end of the day. And so, with that, that neutrality is incredibly important. We're really excited that it passed the Senate and we wanna use that momentum to put pressure on the House. You can learn more at eff.org and you can check on the position of your representative at checkyourreps.org.


Hi, I'm Dr Praveen Ghanagi working as a consultant neurosurgeon and head of the department in Department of Neurosurgery Manipal Hospital, Bangalore Recently now we started doing the craniosynostasis through endoscopes craniosynostasis nothing but the children who are born with the closed skull bones that is in a new born The skull bones is not completely fused it will allow the brain to grow So that when the child grows to one year two years when the brain expands the skull also will expand But in few of the children the skull gets fused in that condition you need to do cut those sutures earlier we used to do a larger skin incision on the scalp and With a lot of blood loss it was risky But now with the infants as young as 40 days We have done and better preferably done under the five months of age where we can use endoscope and cut the sutures and then postoperatively need to put a helmet to remodel the skull so that the children can accommodate the normal shape of the skull


This is banned by the NFL. And for good reason. Feeling good. In 1981, the NFL banned Stickham. We wanted to see just how effective it was. I found this $8 bottle of glove glue on Amazon. We're gonna test it out. Didn't even ever get to my palm, look at that.


Hi, my name is Achim and I'm co-founder of JetLight, Comfort to Light and JetLight and I know what it means because yesterday I flew to Boston and today I came from Boston here to Helsinki. Now I'm here and as me today more than 60% of all passengers suffer from JetLight. And this is not only a problem for the passenger but also for the economy because it occupies high costs. Beside, airlines aim for differentiation. Not only in services but also in the cabin lighting and that is what we were thinking about with my colleagues and as you can see here, Rambo at least he's not my colleague but he has one part of the solution in his hands, a blue light. Normally you see a video here and perhaps you know the video with a blue light and blue light is one part of the solution because with blue light you can decrease your sleeping hormone melatonin. And based on this knowledge, we proved it if it also would work in an aircraft to shift your inner clock to a new time zone. Based on this outcome, we developed an algorithm and the JetLight algorithm now steers, for example, the cabin lighting in the A350 of Lufthansa as you can see here. And with this you can reduce JetLight because you influence your inner clock to the new time zone and it's dependent on the overflow and time zones and the direction of the flight and in the morning, for example, you get blue light when you should become activated. Besides also cookies, not cookies but nutrition is one part of the solution because with nutrition you also can influence your melatonin level. And that is why we also adapted the catering concept in the aircraft to reduce JetLight also by catering and also by cabin lighting. Over the whole passenger journey, you can reduce JetLight, so, for example, already in the lounges and in the aircraft but also at home, for example, with lighting beside your bed, wake up light. And this you can use for many airlines and so Finnair could be one of our next customers perhaps, would be great and as we are here now, we try to fix it. And beside aircraft retrofit is going on, so we are scalable. So it's a very huge market. Three and a half thousand aircrafts will be retrofitted in the next five years. And also in offices and trains you can use the knowledge regarding the light and can activate people and make the life better but also in cars and health industry and in military. So it's a huge market you can use. We also tried it in a Porsche. So we had a project together and we developed lighting for Panamera 4S. And this is our team and if there are some strategic investors who would like to join us, feel free and contact me. Our team exists out of me who wrote the PhD thesis about this topic. And Alexandra, who is a nutrition manager who studied nutrition management and Felix, who makes administration stuff and some other people. So the companies beside are our main partners at present. Thanks a lot. Cool, do we have any questions? You're being so fast. Maybe I don't get it. What exactly are you offering? Is this because it seems like you recommend the company to do it better. Okay, I understand with the blue lights and all that things. But what exactly was the project behind? So besides consulting, it's one part of the topic. But the algorithm is the key of all. So the algorithm steers the lighting, for example, dependent on the flight direction, the duration of the flight, the overflown time zones. And it calculates the cabin lighting in each phase of the flight dependent on the destination where you go. So it's every time recalculated and adapted to the new time zone. I mean, before the industry or many industries start paying a lot of money for this, you would assume that you need massive research data on the effects that it actually works, right? Yeah, we have the research data. So it's not only that we collected research data on this topic, also other companies and not companies, but universities collected data. So we matched all these data together and out of based on this outcome, we developed the algorithm and it's so it's a self learning algorithm. So many data come in and then it's extended, it's extends. So you're saying it's proven? It's proven, yeah. And the reason why I came from Boston today is that we also asked now the passengers if they really like it, not it's proven, but also if they like it, if they like the atmosphere on board and so on. So we asked more than 100 passengers over the last six weeks. So I travel a lot. Excellent. Thank you so much and we will move on.