Welcome to MIT Supply Chain Frontiers, brought to you by the MIT Center for Transportation and Logistics. Recently, food security and food systems have become top of mind as we face seasonal disruptions and unusual disturbances caused by the pandemic. MIT CTL's Tim Russell speaks with his fellow humanitarian supply chain lab researchers about systems mapping and how they're using rapid ecosystem assessments to inform government and the private sector in diverse scenarios. Take it away, Tim. Welcome, everyone. Today we're speaking with the humanitarian supply chain lab contributors about their innovative systems work, responding to emergencies, specifically around COVID this last few months here. Today I want to welcome Dr. Jared Gensel, the founder and director of the Panitarian Supply Chain Lab. Thanks, Tim. It's going to be here. Chelsea Graham, a graduate of the MIT Supply Chain Program and a research engineer in the Humanitarian Supply Chain Lab. Thanks, Tim. Great to be here. And Tristan Downey, a graduate student in the technology and policy program here at MIT. Thanks, Tim. Before we go into depth on the methodology that we used to respond to this emergency, I wanted to ask for a brief description on the projects that Tristan and Chelsea were working on. Tristan, can we start with you? And can you tell us a little bit about the rapid systems assessment that you recently led in Uganda? Yeah, we did a rapid system assessment for the agriculture market system in Uganda. Doing this, we basically surveyed about 300 separate sources of information for what was going on on the ground. From that, extracted hundreds of distinct facts and layered them onto a system map, from which we determined key impacts on the system and what that really means for specific actors on the ground. Great, thanks, Tristan. Chelsea, could you describe a little bit of the work you did with SCAN? Yeah, thanks, Tim. So we were contracted by FEMA to provide ecosystem assessments as part of the supply chain analysis network. And what that entailed was similar to what Tristan did. We tried to provide rapid assessments based on what we saw happening in the market in terms of food supply chain within the US. And we also relied on a Sentinel network of industry partners to ground truth that information. And our goal was to let FEMA know if there were any bottlenecks occurring within the food supply chain. And if so, what type of action would they need to take to remedy that? Thanks, Chelsea. Next, I want to turn to Dr. Gensel and ask a little bit about the methodologies that both of these two projects use. Thanks, Tim. It's two methodologies that came out of different places when we started seeing linkages between the two. So we had already been before COVID starting to think about private sector supply chains from a systems perspective. So we started doing this work with FEMA and it's based on engagements we've had with them over the years and actually was formalized a little bit through work with the National Academies of Science, Engineering, and Medicine in understanding the systems behind private sector supply chains and how they adapt and respond in a crisis. Rather than just try to anticipate dynamic events as they happen, let's see if we can understand how the system works so that we can anticipate the adaptations and the shocks that happened during a crisis. And so then that just naturally played out during the engagement with FEMA. Completely in parallel, we were working with a different part of the US government with USAID in Uganda over the last several years looking at market interventions. So USAID trying to support the private sector in providing goods and services to smallholder farmers. It was really around agriculture in Uganda. So we had already been thinking more deliberately around systems and markets as systems in Uganda. So as we were talking with USAID about what we were doing in the US looking at grocery supply chains and making sure that grocery shelves can be filled, they were also saying, well, we wonder that the crisis wasn't as bad in Uganda but they were wanting to anticipate, well, how would markets change, private sector markets change in Uganda as well. And we hadn't really thought about trying to put those methodologies together but we've started exploring the work we did in Uganda with agricultural markets and contrasting that with the emergency supply chains of private sector supply chains for grocery stores in the US and started seeing some connections with the system's lens. Could you say a little bit more, Jared, about reaching out to trusted partners and people to ground truth this information? I know Chelsea mentioned ground truth, I mean, and Tristan mentioned talking to like over 300 different sources. Can you maybe tell us a little bit more about how that fits into this? The work in Uganda is inherently working with activities who are working with actors directly trying to support their work. And so it's obviously they're trying to facilitate so there's a direct connection on an ongoing basis. The work with FEMA, you need to get quicker reaction time. You don't have time to learn like we have been in Uganda over a longer period of time. You need to be able to in a crisis, you need to adapt quickly day to day. And so with the FEMA work, we try to think about something that's a bit more nimble than the effort it might take to learn about a system over time. And in 2017, we started with this concept of if we understand the structure of the supply chains of private sector supply chains, maybe we could identify key nodes in these demand and supply networks that could be ones to pay more attention to. So in the US, for example, this could be a grocery distribution warehouse which may not normally be thought of as a critical infrastructure component. I think of critical infrastructure being power plants and refineries and things that you would assume that are normally covered by what people tend to think of in the emergency space as critical infrastructure. We started looking at the whole supply chain and saying there may be other points where you need to pay attention. We actually learned in our work with FEMA that the refineries are monitored very closely but the fuel terminals where they actually load the trucks with fuel to go to the retailers is not monitored as closely. So this whole concept, looking at these complex networks, how can we anticipate where we would wanna have conversations on a more rapid basis? Because you have to work quickly. Who would we wanna talk to to assess what's going on and then be able to adapt quickly? And so that's where the concept of sentinels came in. Points where you try to monitor the health of the community, of society by taking regular samples and checking in on a fairly rapid basis. Normally that's in the sense of public health where you're trying to anticipate the flu season. So you'll pick a few key hospitals and be gathering really rich data on the nature of patients coming in and what symptoms they have and you try to track early if the flu season is starting to spike or not. So we thought, well, we can apply this maybe to supply chains and identify key points in these supply chains and therefore the key people who understand what's going on at those key points in the supply chain and interact with them. And that's where that concept of a sentinel network came in. We're literally talking to the people who are watching the supply chain as it's operating and saying what's happening. So that's what that sentinel network came about in FEMA. Thanks, Jared. Tristan, as Jared was just mentioning the sentinel network, maybe you could talk a little bit about how already having an understanding of the you got an agricultural market system was able to help you as you did a rapid assessment for COVID. Yeah, for sure. So we're taking a look at the whole system, right? So by mapping it out first, we can sort of start to place where all these bits of information are coming in from and by information sources, I mean everything from news articles to discussions we've had with USAID partners with people within USAID but also reports from other actors. So one thing that we found was that within the supply chain for, well in this case it was mainly maize, we found we had a lot of information about say importing and manufacturing. So upstream in the supply chain for agriculture inputs. And then we also had a lot of information sort of downstream. So we had a lot about consumers but also about say exports and traders and retailers. But one thing that we didn't have as much information about was about farmers themselves. So it's sort of the center of the supply chain there. So we sort of noted that that was what we'd call an information gap in the system. So we actually then went out to interview basically several farmer cooperatives to get more information there. But in addition to some key government statistics and surveys about other bits of the supply chain, we also set up interviews with key informants in those other parts of the supply chain as well. So importers and commodity distributors basically.  Well, no, it actually means something quite specific. And if we tease out how that price has gone up, we can see, oh, it might be that specifically just the retailer is making a higher margin now and maybe they're trying to recoup losses from before. But that price increase might not be going all the way through to the farmer. Thanks, Tristan. Chelsea, maybe I could have you comment on maybe some examples where this systems knowledge that Tristan's talking about, you're able to use that to get a better understanding of what was going on in the US. We took a slightly different approach in that we really honed in on what was happening with the freight market in the US in order to try to get a pulse on where bottlenecks might be occurring, is freight flowing or being stalled in certain areas. And this is really due to just not being able to analyze at the industry level across retail and food. So trying to get a holistic picture, we decided to focus on freight and freight included rail, included trucking, also shipping as well. We fortunately have industry partners that are in those various categories and they might be either a retailer that moves product with all of those modes of transportation or it might specifically be someone that's within the trucking industry that we could reach out to to get different perspectives of what's happening. So some perspectives are very product oriented while other perspectives are more related to freight movement itself. And that allowed us to create a really a well-rounded picture of what was happening in terms of how freight was moving across the country and how it was, we can't just look at food supply chain in a vacuum because the food that's being moved is those trucks are also moving other products across the country. So you really need to be able to see how they're all interacting with each other. Chelsea, do you have any examples of these interactions that were surprising? Yeah, one thing that I think everyone will remember in the media and some big headlines was related to the meat industry and meat packing. So there were a lot of COVID outbreaks within meat packing plants. And there was fear that there was going to be meat supply shortage due to this issue. So the COVID outbreaks caused the plants to shut down. And then that started to impact the upstream farmers that needed to get their animals to these plants. What we noticed was that while the plants were being affected because they were having to shut down, there was still a large amount of frozen meat being stored. And this did not actually impact the supply of meat that was going out into the country. Because we were looking at cold supply chain, we were talking to people in the industry that move the meat and had a good understanding of where this frozen meat is being stored. We were able to connect the dots to see that while the supply might have been impacted at the meat processing plant level, it was not actually going to impact the consumer. Tristan, let me give you a chance to say, did you have any unexpected findings as you were doing your analysis? Yeah, I guess so one interesting thing. Well, I guess some interesting themes were just differential impacts, so how it might impact different actors. And one was about exports actually. So the Ugandan government imposed some pretty strict COVID movement restrictions and border closures, but still allowed shipment across the border. But to do that, you need some certifications basically. So what we found was that although there were some increases in delays for formal exports, so those would be bigger companies that would have the capacity to get the certification needed to ship product across the border that completely halted informal trading. So that's something that is typically much smaller traders, often women in these border districts. And it's quite striking actually the export stats. Basically the formal export stats are not that far off of seasonal trends, but informal exports. As soon as that border closure came into place, they dropped to zero immediately and they've stayed at zero. And in terms of value for Maze alone, that's since COVID, that's millions of dollars of value lost. What did that mean for the farmers that normally do this informal trade? So that's a significant loss of income for these small informal traders who would be trading just across the border, just into South Sudan or into Kenya or into the DRC. So that was a big impact that wouldn't be immediately obvious just from looking at sort of normal aggregated export statistics. And as far as that informal export volume has stayed at zero for all commodities. So that'll have a disproportionate impact for people who are already vulnerable. These are already small traders who would already have less of an access to finance or other sort of cushions basically. Well, just to add to that, it disproportionately affects women because we also were able to pull together data from working in the system to see that these traders are often women, these informal cross-border traders are women. So yeah, just trying to piece together information from various sources. And I'll have to admit, Tristan developed a pretty interesting approach of taking facts from news feeds and different experts and synthesizing and pulling it together using our system map. And so there's a nice formal way to track everything in real time so we can connect those dots. No, that's interesting. And we saw the same thing in the US when we're talking about differential impacts to small businesses versus large businesses. Jared, you mentioned reaching out to different sources. Maybe you could do a compare and contrast with like the kind of people we're talking to in these two different projects, how often the frequency just give a little sense of how to reach out to these Sentinel networks is different between these two different approaches. We know that supply chain management is a human endeavor, it's human management. But when I was first thinking of these Sentinel networks, I was thinking of data feeds, like let's get Sentinel points, let's identify the key nodes and let's get data and in real time we'll get data and we'll do all this analysis and we'll see what's going on. And especially this year, we've kind of been learning over the years, but especially this year we realized that it's not just the Sentinel points and data about what's happening there, it's the Sentinels themselves. The people that are managing those critical nodes have information. And in a crisis, they actually want to talk, they're trying to make sense of what's going on at the same time. And especially something that's as unique as a pandemic. I think sometimes in the U.S., these grocery supply chain providers, then the transportation providers and so forth that we typically work with, hurricanes are somewhat normal and they're looking for new information, but in this pandemic, they're all looking for new information, they wanted to talk. So we had a much richer discussion. In fact, what ended up happening, I've called this, we had an industry peer review process for all of our assessments. We would do an assessment two or three times a week. We would send them out with that frequency and these industry people would read them and give us feedback. It's real time review with all of these different experts, these Sentinels across these important supply chains, getting information from them in real time to really get a sense of what's going on that probably would be, if we tried to wait for data to come in, it'd be too slow. So that rapid interaction and the desire of groups of people to want to learn together and make sense of what's going on together really helped connect. But one thing that's different in Uganda than US, I mean, US has very concentrated supply chains. When you're talking about food distribution, there's a few key food distributors that cover most of the grocery sector. And so if you talk to a few of them, you get a really good sense of what's going on. Chelsea mentioned before the meat packing industry, we could talk to a few people and get a pretty broad sense of what was happening. And Uganda, the supply chains are much more fragmented to try to understand what's going on in Tristan's case with cross border trade, there's hundreds of traders you'd have to talk to and there's not a really good consolidated place to do that. So that interaction is more challenging in that kind of situation. At the same time, that fragmented decentralized structure in some ways, they're all adapting themselves rapidly. They're talking to each other, they're figuring out how to adapt. And I think one of the gaps we have going forward is to figure out how do we learn from that kind of informal Sentinel network, the discussions among them, the way that they talk to each other and make sense of what's going on to adapt. And then they often face much more challenging crises than we do in the US in much more vulnerable conditions with much fewer resources. They're somehow able to adapt and show some resilience. And I think there's a lot to learn in how they actually communicate with each other in these kinds of situations. Well, Jared, that's an interesting point. The work that was done in Uganda and the work that was done in the US, it seemed to have, like they had a little bit of a different audience. They were written for or directed at different people. And maybe in the US, there were maybe two audiences at once. Maybe you could talk a little bit about how the audience of these products shapes what's being done. I mean, in both cases, we were trying to inform the US government, FEMA and domestically and USA and internationally about how private sector supply chains were working. But in the US, the audience also, we developed a really rich back and forth with all of the sentinels, these actors who were engaging with us on a regular basis. And so they were as much of the audience as the government. And again, back to the challenge of the fragmented structure in Uganda, we've got to find a way to help the products to develop, get out to the people. They're adapting on their own, but we also need to cultivate those richer networks and be able to share information with them effectively, not just inform where the government can fill gaps and play a role, which is important, but also help them leverage the information that's being gathered so they can, have even more data points to help them adapt and go forward. And in some ways that's in Uganda, they may not be able to see networks across the country. It's very local, the adaptation is very local, but they may not see opportunities with actors in different parts of the country or in different countries as formerly. And that's where again, the work can be more effective if we find a way to serve that audience of informal market actors in those fragmented supply chains in Uganda. I think next I wanna talk a little bit about what it took to do these projects and how maybe the people listening to this podcast, that they were going to try to undertake something similar, what they would need to do to do it. I'll start with you, Tristan, and say, like, what do you think if there was another student who was gonna try to do a project like this, what would they need to kind of make this work? Yeah, I think starting with an understanding of the system is a big advantage and all the work that we had done previously in Uganda was a big help. So I think developing, trying to develop an understanding of the system and basically validating that with system actors is really important. But then in the crisis where things are rapidly changing, I guess having a way to quickly process sort of diverse bits of information has been really important. So developing a methodology for that is really key because, and this is for a crisis specifically because things are changing really fast, right? A lot of incoming information, you want to make the best use of it as you can because there won't be time to do sort of full, rigorous studies a lot of the time. You know, this can come later and can be integrated later, but when things are changing day by day, accepting some uncertainty is really important. And as long as you have a way to sort of deal with that and still make use of the information as best you can. Nice. And maybe I'll turn to you next, Chelsea, to say what Tristan was mentioning, being overwhelmed by events, we often talk about being overtaken by events and trying to have time to synthesize things and make sense of it, but still be able to turn it back to people. Do you have any sort of hints or things you could suggest for people that are trying to do the same sort of work that you did? Yeah, I think that, I mean, we do a lot of preparedness work as well outside of responding to emergencies. And there's a lot of groundwork that needs to be laid prior to an event like this happening or responding to such an event in order to really build out that Sentinel network that you would need. And to Tristan's point, the methodology laying out the methodology prior is really important in being able to adapt as you go as well. So we quickly came up with a cadence that worked for us in order to provide FEMA with the information that they needed. And it allowed us as we went to to figure out how to prioritize the information that was out there. And you've developed a sense for that as you go. So some of it is an adaptation during the process, but I think a lot of it is really happens before the event occurs. Thanks. And then, Jared, maybe I'll leave it to you at the end here to kind of wrap us up and to give us an overall picture here. Well, I think just building on what Chelsea was saying here, there's, you have to do this ahead of time. The preparedness work is important. And this idea, we've talked a lot about systems and supply chains are systems. And maybe it took a health pandemic looking at food supply chains, looking at all the different interconnections of these supply chains to help a broader group of people take an interest in supply chain management and how that's gonna be critical in a crisis like this. And my hope is that then, we can address the crisis quickly and then we can remember to do that preparedness work to formalize what we've learned to build a common vernacular around systems thinking around supply chains and how health supply chains and grocery supply chains and fuel supply chains all connect together. And that, if we have a more common understanding of the structure and especially, a lot of people in the private sector in our supply chain profession have this more innately because they live it. The government may not have it in the same way. And so getting the public and private actors to have a common understanding of those supply chain systems so that then they can anticipate and have a common language to quickly sense make and see what's going on dynamically in a crisis and adapt quicker. That's what we really need to move forward. So I'm hoping that this, it's been remarkable how well the food supply chains have responded to very changing conditions, but we should be ready and do the preparedness work so that we can't adapt better in the future. And we especially having, I don't wanna rest on our laurels that the food supply chain will always be able to be resilient. We may have been fortunate, we should continue studying that and understanding it, but and building that common understanding across public and private sector actors so that they can when faced with a new pathogen or a new global crisis, be able to continue to adapt more quickly to conditions you can't really prepare for, but you can prepare your mindset to be able to react quickly. Well, I thank you for ending on that optimistic note as we head into maybe another COVID spike here in the fall that the grocery supply chain systems are resilient is a nice note to it. And we hope the cold chains that they use will be adapting to get a vaccine out as well. I mean, there's a lot of cross-pollination between these supply chain capabilities. And so some of the actors we worked with on food supply chains are very much central to getting a vaccine out. Well, and these Sentinel networks that you've developed, both in Uganda and in the US, I think will be critical to be able to reach out to them for any needs here in the future. So thanks to everybody for joining and doing this podcast. Really appreciate it. Yeah, thanks, Tim, for coordinating things. Okay, thanks. Thank you, Tim, for the opportunity. All right, everyone. Thank you for listening. I hope you enjoyed this edition of MIT Supply Chain Frontiers. My name is Arthur Grau, Communications Officer for the Center. I invite you to visit anytime at ctl.mit.edu or search for MIT Supply Chain Frontiers on your favorite listening platform. Until next time.


In the United States, every day is a Christmas. Pause every day we eat meat. Rise every day. Every day is a Christmas. There's no hope in the refugee camp. I don't know how to express that, but life in the refugee camp is something which is beyond imagination. I'm going to change. I'm going to change. And I expect it to have new friends. That was awesome. That was awesome. Cheers. This was a miracle. Everything's a dollar in the Dollar Tree. Okay, so that's helpful. Yep, you just push it. Hello. Hi. Salt Lake City? Yeah. You've been in the United States for how long? For just two months. Good luck to you. Because some people hug, some people shake. Okay. My hug is real. I like hugs too. Hug means love. That's a dream. That's a dream. Now things are changing. I feel like America.


Sleep paralysis is when your body paralyzes your muscles so that you don't act out your dreams during the night But if you wake up during that process, it can be terrifying. Now in this video I'm going to tell you 10 things that you should never do during sleep paralysis These are sleep paralysis dangers, if you will. Things you should avoid doing and You really need to pay attention to these things and make sure that you don't do them because otherwise It's going to be a lot more scary than it needs to be. It's going to be terrifying Okay Now sleep paralysis is actually nothing to worry about if you follow these steps And if you make sure that you just don't panic But before we get into this video make sure you do subscribe to the channel because I do share regular lucid dreaming tips and tutorials As well as sleep hacks and methods as well So number one the first thing you should never do during sleep paralysis is panic It's so easy to just panic and think oh my god. I'm stuck in this state I can't escape it feels terrifying and you just want to be able to move But if you panic you actually make it worse. So just remember to stay calm stay focused on just avoiding the panic stage and just remaining calm try not to move This leaves me nicely onto number two, which is just don't move try not to move During sleep paralysis if you wake up and the first thing you think is oh my god I can't move and then you try and like twitch of your hand or move your leg or something like that And it doesn't move that's just going to make you panic even more and that's going to keep you in the sleep paralysis state It's going to keep you in that scared Experience which nobody wants to really have so remember don't try and move during sleep paralysis. It's a big mistake Number three and this is kind of don't get too scared by this But try not to scream if you end sleep paralysis and your first thought is I can't move I want to escape this and you then try and say something you try and shout out You know asking for help or if you're sleeping with a partner or even just screaming out for somebody that's in the house To try and help you that's just going to reinforce the scared experience that you're having It's going to make it even more terrifying than it needs to be So don't try try not to say anything or try not to shout or scream out or anything like that Now in a couple of minutes I'm going to explain how you can actually use sleep paralysis to reduce a dream But let's just stick with this for now So number four the fourth thing that you should never do during sleep paralysis Is to try and escape if you try and escape the sleep paralysis state You're going to be fighting against your own body and your own mind which is a losing battle You're not going to be able to do it now. There is actually a purpose to sleep paralysis It's designed to help make sure that you don't act out your dreams during the day and during the night By trying to escape that state too soon You're going to be interfering with your natural process and your natural sleep cycles So don't try and escape there's no need to because it's not it shouldn't be scary It won't hurt you and it can't do you any harm So there's no point trying to escape especially when as I'm going to explain in a minute You can actually turn it into a lucid dream very easily So number five try not to stay in the sleep paralysis state for too long Okay, I know this sounds a bit controversial But if you stay in the sleep paralysis for too long, then you might find it Increasingly scary and uncomfortable as time goes on If you just stay in the state for a few minutes and you know You tell yourself that you will soon turn it into a lucid dream That's fine, but if you stay in it for 10 minutes or even 15 minutes It's going to start feeling more and more uncomfortable and you're going to experience things like the sleep paralysis demon And various other scary things, you know vibrations. It can feel like there's a crushing feeling on your chest You don't want any of that So try not to stay in the state for too long and I'm going to explain in a minute how you can escape The sleep paralysis experience and just turn it into a normal lucid dream Which is going to be much more fun. All right, so number six try not to get frustrated Okay, I know it can be annoying. It can be very frustrating But if you just try and stay calm and just remind yourself that the sleep paralysis is a fairly normal thing everybody experiences it And just try and remain calm. You're going to have a much better time It's really going to be So much easier to deal with if you just try not to get frustrated at it and just tell yourself that it's normal That you can't move All right, so number eight try not to lucid dream too soon at the end of this video I'm going to explain how you can actually lucid dream as a result of sleep paralysis But if you try and lucid dream too soon before you're ready Then what's going to happen is you're going to be unable to lucid dream You're going to be more aware of the fact that you're in sleep paralysis And that's just going to what that's going to mean is that the whole thing is going to be more uncomfortable for you So try not to lucid dream immediately. You can you can lucid dream but not straight away What you need to do is just let the sleep paralysis run its course and naturally shift into a lucid dream This will take anywhere from one to 10 minutes. It really depends on, you know, how deep you're in the sleep paralysis How much your mind is awake But as I said try not to lucid dream before it's before it naturally feels like you can enter the lucid dream If you've watched my other videos about techniques like the wild this is very similar to that you want to try and Wait until the perfect moment before you jump into the lucid dream and actually enter that state And number eight, this is quite an important line. Try not to forget that it's actually not real So the sleep paralysis state can feel scary Especially if you have an experience with something like the sleep paralysis demon, which is really just all in your mind But if you forget that it's not real and you actually take it for real and Believe that it's actually happening to you it can feel scary It can feel like, you know, it hurts in some cases if there's something pressing down on your chest So try not to take it too seriously try and constantly remind yourself that the sleep paralysis experience Is not actually real.  You know, there's no secret hidden danger of sleep paralysis that I'm not telling you That's literally it. All right So number nine, which you'll recognize this tip if you watch my other video about the wild technique Try not to tense up your throat too much If you're in an experience where Mainly in sleep paralysis, but you know, you can have this also when you're trying to do the wild It can be very easy to tense up your throat and to try and say something or to try and you know Go as if you're going to move or breathe in a different way But all that does is it makes the state even harder to escape And it's just going to make the whole thing really frustrating and uncomfortable So try not to tense your throat up too much We hold a lot of tension in our throats in our neck and in our jaw as well So I'm just about to explain how to actually turn it into a lucid dream But first on I tell you the last thing you should never do in sleep paralysis, which is number 10 Don't get discouraged If you experience regular sleep paralysis, it can be very discouraging and it can stop you from wanting to learn more about lucid dreaming It can stop you from Even being excited about dreams in general You know, you might even be scared to go to sleep Which is really not what you want to be having as an experience So try not to get discouraged Remind yourself constantly that sleep paralysis state is natural. It's safe It's not going to hurt you in any way and it's actually a good thing You know, if you didn't have sleep paralysis, then you would be acting out your dreams You'd be doing things like kicking the bed or rolling out of bed Sleepwalking and causing harm to yourself in the real world So sleep paralysis is actually a good thing And so lastly I want to explain how you can turn sleep paralysis into a beautiful lucid dream This is a really easy thing you can do and it basically you're just going to follow the steps of the wild technique So the waking lucid dreaming technique involves keeping your mind awake while your body goes to sleep And actually one of the stages in that technique is to go through sleep paralysis It's a very simple thing you can do So all you need to do is just focus on not moving like we said Not panicking but also not trying to wake yourself up You know, you want to keep yourself in that state So your body is still asleep, but your mind is going to be kept awake This is really important and this is essentially how you do the wild technique in the first place You know, you keep your mind awake throughout that So as you experience the sleep paralysis, you will slowly start seeing what's called hypnagogic imagery This can be patterns, it can be lines or shapes, it can be colours It can even be flashes of light that you see behind your eyelids But what happens is if you keep yourself aware and awake during that stage Slowly you'll start to see pieces of a dream scene forming You know, you might see like the quick a quick flash of a skyline or a tree line or even you might see As if you're walking down the street You'll just see a flash of a dream scene and then you'll go back to seeing the shapes and colours Now to actually enter a lucid dream during that what you need to do is constantly remind yourself As we said in the other tips that the sleep paralysis stage is not real It's not going to harm you and it will be over soon. So remind yourself of those things But then also keep telling yourself I will lucid dream any moment now. I can control my dreams these positive affirmations Which if you look around on my channel, you can find some other videos that I've made about this this sort of thing But just keep reminding yourself that you're going to enter a lucid dream. You're going to be able to control it So if you enjoyed this video guys, please remember to subscribe to the channel and turn on notifications Because I make almost weekly lucid dreaming tutorials. I make videos about all sorts of sleep related topics And if you are one of my existing subscribers, I'm sorry about the noise I'm actually staying in Marbella right now as you can see from this view And uh, unfortunately, this is the best lit place sunlight the natural daylight is coming in from this area so this is the best place to film videos and uh I will be home in uh in a couple of weeks where I'll be able to use my proper recording stuff, but Yeah, this is it for now and remember to go and subscribe to my uh to youtube channel Follow the instagram which is how to lucid Links to all this is in the description and if you do want to see my travel vlogs I'm making almost daily travel videos on transcend travel Which the link for that is in the description as well Now lastly just leave a comment letting me know what you think about this Have you ever experienced sleep paralysis? What did it feel like? And uh, let me know if there's anything I missed if there's any warnings that you would give Leave a comment below and remember to subscribe. I'll see you next time You


What's up basketball fans, check it out, the brand new Mohegan Son Fandall Sportsbook just opened in Connecticut, in person betting dozens of massive screens, 11,000 square feet of absolute awesome, including two levels of food, drink, kicking it with friends and family while catching all the hoops action and so much more. And here we are, welcome to the newest addition to the family. We are inside the brand new Mohegan Son Fandall Sportsbook here in Connecticut and you're watching Fandall Sportsbook's more ways to win March Madness style. We're so excited to be here, we're hitting the hardwood, we're breaking down the biggest tournament matchups ahead of us, we're giving you picks from round one all the way to the national championship and who's cutting down the nets in New Orleans. I'm your host Lisa Kearney, our gambling experts in house as well. Of course Dave Weaver, Ed Egros and Andrew Filiponi. These guys have been crunching all the numbers there ready to reveal their best bets for the big dance and you can take their information and play bets right from your phone. Just download the Fandall Sportsbook app, check out all the wagers we're talking about on this show and so much more and get this because it does get better. Fandall is giving new users an assist to get started, just sign up for an account bet $5 on the tourney, you're going to get $150 in sportsbook credit bonus, that's right sign up deposit money, bet $5 or more and you'll get that $150 in bonus sportsbook credit, you can do it right now. Alright let's get to it and bet these games. This first round is about to tip off and we are tipping things off with the top teams in each region here and we are starting in the west guys, here's a look at the entire bracket in the west is absolutely loaded, it features the number one seat of the entire tournament, the Gonzaga Bulldogs, looking for their first championship in school history. Bulldogs take on Georgia State who won the Sunbelt Conference Tournament to get that automatic bid to get in where they are. Dave and Ed, all these top seeds are going to have huge lines of course in the first round, we see it every year so the question is can they cover? Gonzaga is giving 23 and a half points in this first round, Dave which side are you taking in this one? I think they cover, you go back to last year, they want to make a statement here early, they beat Norfolk State with 16 seed by 43 points, they hung up 98, this is the number one ranked offense in the country, Georgia State offensive efficiency 126, this is just a huge match up for Georgia State to try to get inside against these bigs, it's not going to happen, their three leading scores are all guards, so what is that for? Make perimeter shots, it's going to get ugly Ed, I'm thinking 89-60, Gonzaga. 89-6, all right fine, I will mark this down on my tablet here and pay attention to that. Just because Gonzaga is a heavy favorite to win this national championship and that's the statement that I think they want to make, it's not so much what they're going to do in this first round, but I actually think that Georgia State can cover this number, I think this is going to be closer to a 20 maybe even a 19 point game in large part because I think Georgia State can do the things that will frustrate Gonzaga, especially when it comes to guard play, you think about Gonzaga, it's all about the front court, but it's the guard play that I think is a question mark here, you look at for Georgia State, Cain Williams, Nelson Phillips, they're going to frustrate it, offensive rebounding, Georgia State is not bad there, I think they will do the pesky things to keep this game a little bit closer than you would normally see in a first round game. Are you guys good stuff there? Let's get to the Midwest region now and my roots, a lot of championship contenders lurking in this bracket. Take a look here, the number one seed in this region, Kansas, who won the Big 12 conference tourney and they all face Texas Southern, who won their first four matchup on Tuesday. Dave and Pony, the J-Hawks Pony 21 point favorites here, they got a lot of pedigree coming into this tournament. Pony, how are you playing this one here in the first round? Well, it's a late start for Kansas fans, so they can go to bed at half time, because this game is going to be a blowout. I'm going to take the J-Hawks, you look at Texas Southern, they don't have a player that averages more than nine points a game, they got blown out by Louisiana Tech, 27 points, NIP team, BYU in Oregon, beat them by 17 points respectively. Dave, the Big 12 does well in tournaments, they've gone to the final four, four out of the last five years, and I think they get up to a good start with Kansas here, they cover. I'm going to take the dog in this one, and I'm on Gonzaga, but I'm going to say Kansas will not cover. Yeah, here's the thing, Texas Southern does play well as a dog, nine and two, their last 11 games in this situation, and Kansas, their last five games in the Big Dance have only covered once. Why? Because they're usually big favorites like this. Georgia Southern can rebound 28th in the country, so if they can clean up the glass a little bit, get some offensive put-backs, I think they can keep this one close enough. Cover, fine, just don't take them on the money line, boys and girls. All right, let's move on now and focus on the east. And here's a look at that bracket, a tough field, but none of the top four seeds won their conference tournament. Baylor, the number one seed, will start their title defense against Norfolk State, who won the MIAC Conference Championship, guys. Ed, Baylor's giving 21 and a half. Which side do you like in this matchup? If you take nothing else from my analysis here, just remember this. Injuries are overrated when it comes to college basketball.  Offensive rebounding, I get it, took a little bit of a hit, but Flothaba is still there. Crier, I know he's one of the great three point shooters on this team, but they've got a lot of other great ones. To me, the depth of Baylor is why they're going to cover this number. Well, they don't lose in the non-conference. They went undefeated this year in November and December. I think the familiarity in the Big 12 wore them down. Teams knew how to play them. Now they're going back into very familiar territory the defending champions. Well, Norfolk State played one of the weakest schedules in college basketball. They played one tournament caliber team. That was Xavier, who's in the NIT, and they got pounded by 40 points. Baylor is going to blow them out. This is a rocking chair play. Take the Bears. All right, guys. As we wrap up our whip around the regions here, we're going to land in the south. Take a look here at this region. Arizona, the number one seed. They're taking on a first four winner. That game had not been played at the time of this show taping. So, hey, we're looking ahead. We're betting the number two seed, Villanova, the biggest tournament champion taken on at Delaware, a school just 45 miles away from Nova Dave. Villanova's giving 15 and a half a more respectable number coming out of those 20s. Can they cover that? They can. You know, this is where they're supposed to be in March. They thrive covering in the tournament. 14 and three against the spread as a favorite going back, obviously, you know, decades. But this is where they're supposed to be. Delaware, on the other hand, this is only their day tournament in 21 years. Villanova, the best free throw shooting team in the country at over 82%. So, if they get to the line, they're going to be making those shots and they will get to the line and they will outrebound this team by a big number. I don't think they keep it close. Villanova covers easy. Program history matters not. What matters is what's happening right here and right now. And right now, I feel like that Delaware can actually keep this game two within about 10 points apart because they have the 40th best effective field goal percentage shooting, top 70 in free throw rate. They get to the line, they make their freebies and Dylan Painter, six foot 10 senior post guy. Delaware's got a lot of good experience that could keep this game relatively close. Doesn't matter what the program has done over the course of the years. It matters what's happening right here, right now. And look, Villanova can get into some foul trouble. It's been one of the bigger problems that they have had all season long. Delaware knows this. They could put Villanova in some tricky spots. I think Delaware can keep this a little bit closer than the line at least. What have you done for me lately? I get it, Ed. All right, now that's a look at some of the top teams in the big dance and our experts picks of course. And a reminder for our new users, welcome. Excited to have you with us. Sign up for an account now. Bet $5 on the tournament. You'll get $150 in bonus sports book credit. That's right. You can deposit money, bet $5 or more, and you'll get that $150 bonus sports book credit. You can do it right now on the Fandall Sports Book app. And of course the tournament is all about upsets, as we know, and picking the right upsets could lead to a big payout. Now, as you know, underdogs are plus money. So let's get some guys. You know this is what I show up for. So let's bet the first round dogs here and see who our betting experts like to pull the upset here.  Give me an underdog that's going to win outright. Who are your money line money makers here in this tournament? I'm going with the hottest team in the country and that is Colgate. Yes, Colgate has won 15 games in a row. I don't care who you're playing. When you win 15 in a row, you are legit. Wisconsin, the Big 10, I think it's down this year. I'm going to fade a lot of the Big 10 teams in this tournament. Colgate, the number two three-point shooting team in the country at 358 teams. They're second 40%. They're going to be bombing threes and pull off this upset. It's about time Dave used some Colgate for numbers for starters. But I like Vermont in this one. I think Vermont can pull off the upset against Arkansas. In the history of the tournament, teams that overwhelm, get those underdog upset wins, they shoot 5% better from three than they normally do. So you want to look for teams that are willing to shoot a lot of threes. And Vermont has one of the higher three-point shooting rates of any team in this tournament. Arkansas does not. And so if Vermont gets hot, watch out. I'm going to dedicate my upset special to the most famous Chattanooga Mock. And that is P.O. If you're watching this, my man, your mocks are taking down Illinois. I'm going to be at this game Friday night. Chattanooga, very good defensively. They hold opponents to 30% from three. And here's the thing. We know about Kofi Coburn for Illinois. Chattanooga has a Kansas transfer. Filvio DeSosa, he's 6'9", 250. They have the size to match up with Illinois' big.  An excellent player, Pony. I like to shout out. There are dozens of games and thousands of bets that you can make right now. So time now. I want you to focus on some other games on the board here, guys. We're going to have a little friendly competition, if you will. You each get 100 virtual dollars. Now with that money, you have to make one spread, one money line, and one total bet. And you get to decide how much to put on each. You only get 100 bucks. The person who makes the most profit wins. We will crown that champion on next week's show. We do this throughout the NFL season, so you guys know how to roll here. Let's get things started, Dave. Give me your winning picks. All right. I'm going to stay with my upset special on the spread. So I'm going to take Colgate with the points in here. Getting the seven and a half. Yes, I do think they'll win the game, but this is a pretty safe play to take them on the spread. That's $25. My money line play, I love Virginia Tech. Virginia Tech is a team that will out-shoot Texas from the threes, 39% to 32%. Texas is kind of spiraling right now. Lost three in a row. Virginia Tech's won four in a row. The strength of schedule has been better for VTech. So that's my money line play. That's almost a pick-and-game. I'm not going to make a ton, but that's my play for 50 bucks. And then the total, Houston UAB. Houston, you know, notoriously kind of a juggernaut defense. They had to set this line kind of low. But UAB, you look for their last five games that they've scored. 81, 87, 80, 102, and 82. And Houston average is about 75. That game's going over. That's my final 25 bucks. I'm going straight after Pony right between the eyes for my spread pick. I like Illinois to cover the seven and a half against Chattanooga. In large part because they've got some really good size to guard the post. Not to mention a top 50 effective field goal percentage offensively for my upset money line money maker pick. I'm going to go on $50 taking Davidson to upset Michigan State. I think Davidson has the third best offense among all mid majors behind obviously Gonzaga and Houston. Davidson going to be really good. And then lastly, I'm also taking the over in the Houston UAB game.  The data sample is more than supple enough for Houston to showcase an incredible offense. I feel like they can blow out UAB, score a ton of points, and get over that 136. All right, I'm going to start with a $50 wager on the Richmond spiders to keep it close against Iowa. They're a very experienced team, one of the most in the country, the oldest, and they take care of the ball. Great assists, very few turnovers, get a lot of steals. That's number one. My money line money maker, 25 on Marquette. Sorry, Vish. I'm going against your North Carolina Tar Heels. To have a defense, North Carolina's guards are very erratic. Jaco Smart's going to get a win at Marquette. And then my last one, $25 here on the under in Duke Fullerton. Duke, they couldn't shoot the ball against Virginia Tech for a 20 from three. Fullerton's got only two guys who can score. I'm going under for 25. Yeah, Pony, our producer, Vishal, just got in my ear and told me next time you pick against his team, he's just going to go ahead and cut your mic.  Great stuff by you guys. Those bets are all available right now, of course, on the Fandall Sportsbook app. You can hit them up. And hey, you can tailor guys or make your own picks. I always say this on the show, you do you. And remember, new users, download the app, place a $5 wager to get $150 in sportsbook bonus credit. So make sure you take advantage of the special offer going on right now. Let's keep this thing going by taking a look at the tightest spread in each region. And having our guys pick that game. So let's get right to it. And let's start off in the West region for that, the 7 to 10 matchup. Guys, featuring Michigan State taking on Davidson, a 7-10 matchup, this one expected to be close. You see right here, Dave and Pony. Spartans are just a one point favorite. Dave, who do you like? Who do you like in this matchup? I'm not sure this game is really going to be close. I like Davidson. This is a team that does not turn the ball over. They can block shots. They can shoot the three. They have a great offense. They're averaging three and a half points more than Michigan State throughout the year. And as I said, I'm fading the big 10 pretty much in every spot that I can, Pony. I like Davidson. Well, Davidson to me is a poor man's Iowa. They're a great 3-point shooting team, 6th in America. They don't have great interior play. Well, Michigan State's not built like they have in the last few years. They don't have scores. They don't have a premier point guard like Cassius Winston. And so I think Davidson can shoot it from the outside. And I think Michigan State won't keep up. The closest team, like I said, was Iowa. And they drilled Michigan State by 26 this year. I think Davidson does get the win on with Dave. All right. This fighting Steph Currys, if you will. Hey, same drill for the South region now, guys. The closest spread in this bracket, the 7-10 matchup right there, Ohio State versus Chicago, Loyola. Guys, Ohio State, half-point favorite over these two. Pretty evenly matched teams, really. Ed, who do you like in this matchup with Chicago, Loyola?  But I like Loyola Chicago a lot. And in large part, because look, Porter Moser's gone. I get that. And they have perhaps the youngest head coach in division one college basketball. But coaching, yes, it matters. But you leave a program and then you come back and everything's going to be just fine. The program is in terrific shape. They were known for defense. The defense is still great. Defense of rebounding metrics are absolutely outstanding. A ton of great seniors, a ton of great leadership. How can you go against Loyola Chicago and Sister Jean? I agree. I think Ohio State's actually the worst power five program in the field. There are seven seed. They lost four or five down the stretch. They've got key injuries to big men. Kyle Young and Zed D. We don't know their status for this game. They got beat by Penn State convincingly in the big 10 tournament one and done. Ed just touched on it. Loyola great pedigree. They're going to win this game. I've got a little dyslexia, guys. Not Chicago, Loyola. Loyola Chicago, guys, I see you. All right. Let's get to the East region of this bracket. And it is the 6 11 matchup between Texas and Virginia Tech. That's the tightest spread in this region. Six seeded Texas giving just one point. I love these games, Dave. Two schools from major conferences going at it here. Which side are you backing? I'm Virginia Tech. I'm just not in love with teams that come in kind of limping to the tournament on losing streaks. And Texas has not looked good over their last three. So to me, the hotter team in here is Virginia Tech. They shoot the three a little bit better. You know, I just give them, give them the edge. Slight edge. I don't think this is going to be a blowout, but I think they get the job done. Conference tournament runs really don't matter to me very much. The ACC was absolutely weak. If there is a conference that you should be fading as far as a major conference is concerned, it's the ACC. Almost nobody looked good there. But here's the thing about this particular matchup. I get it's the national pastime to make fun of the University of Texas. But look, sometimes the AP preseason poll is absolutely correct. It just takes time for a team to sort of fulfill what the expectations are meant to be. Texas was ranked fifth at the start of this season. At some point, they are going to showcase the talent, the transfers in that front court, and Chris Beard showcasing what he can do defensively in terms of getting his fingerprints on this, on this team. To me, I think Texas Tech takes care, or Texas rather gets it done. All right, let's move on. Last but not least here, the Midwest region guys, odds makers think this 7-10 matchup between USC and Miami is going to be a tight one. Another close one here, the Trojans giving one and a half points to the Hurricanes. Dave, who do you have in this matchup? Well, neither of these teams are going anywhere. So whoever wins, I'll be betting against next time when they lose to Auburn. But I've watched a lot of USC here in Southern California and really haven't been that impressed with their entire body of work. So I'm going to go with Miami, but I really don't like either of these teams pony.  I disagree with that. I don't get why USC is so discounted when compared to team the Pac-12 that everybody loved, Arizona and UCLA. USC shoots a better field goal percentage than UCLA. USC shoots a better from three than Arizona. They're a very good offensive team. I'm in an ACC market. Miami, two up and down. I think USC wins this game by double digits. Great stuff, guys. And plenty more coming up from our guys, including their final four picks and also their best value national champion at pick. You're going to want to stick around for that, of course. But I just want to take about 30 seconds to tell you about the spot that I am standing in right now. The Mohegan Sun Fandall Sportsbook. We're taking you inside here. This brand new space just debuted less than two weeks ago and it is absolutely gorgeous. The Fandall Sportsbook is in the middle of the Mohegan Sun Action. 11,000 square feet of space to enjoy two levels of self-bedding access, food, drink. There's a VIP lounge upstairs. Dozens of massive screens playing every single game that you need. So you can hang here with your friends, your family to enjoy the action while betting on your favorite teams and players. And if you're in Connecticut or, hey, traveling anywhere in the New England area, this is a must-see spot. You won't want to miss it. In less than two weeks, I have now been here twice already. You got to join us here at the Mohegan Sun Fandall Sportsbook Open seven days a week. This is your formal invitation to join us here. So let's get you set to place your bets here while you're here and back to basketball now to do that. We're handing out championship picks in just a second. But first, we've got to reveal which teams are going to make the final four. So guys, you're back in here. We're going to put the final four futures right there on your screen. Gonzaga, the odds-on favorite here to win their region. Baylor, the only number one seed not favored to win their part of the bracket. Guys, it's go time here. Give me your final four picks. Dave, you going off the board? You like something here? What do you think? I got one sort of semi-non-favorite team. But I'll start with Gonzaga. They're the heaviest favorite to make the final four at minus 135. They really don't have that tough of a schedule to do that. They're going through their bracket pretty easily. Yan on Gonzaga. Kentucky, you know, their talent rivals anybody's. When you look at Shibway, Taitai Washington, Wheeler, they've got some guys that can shoot the three. I think they're going to make a big run. This is their best offensive output that they've had in five years. When you go back to Malik Monk, the Aaron Fox, and Bam Atabayo, what team that was, by the way. And they didn't go all the way. But I think Kentucky gets through their bracket. Arizona plus 145. I know Ponies didn't sound like he likes that much. But boy, do they have some offensive scores. And then Iowa would kind of be my sleeper of a non-top team that's ranked, you know, outside the top four. They, to me, have the easiest path. That's my biggest price at plus 400. But I'm pretty chalky overall. Brace yourself, guys. I'm going to take Gonzaga to win the West in large part because, look, Chad Holmgren drew Timmy. That is the best front court in the country. I get that guard play matters in the tournament. But when you have a front court like that, it almost doesn't even matter. In the East, I'm also going to go with Kentucky. Second-best offensive rebounding rate because of Oscar Sheebley. Off-night shooting is not going to matter. They're going to get enough possessions to overwhelm just about anybody. In the South, I like the value play with Houston at plus 550. That second-best opponent effective field goals shooting percentage should mean they are at least favored to get to the sweet 16. Then they'll place in San Antonio, which is close to Helm. So not much distance traveled for Houston. So I like them there. And then the Midwest, I'm going to go with Chalk and Kansas at 2-1. Bill Self's high-low offense. It finally features some experience led by Occi Abachi. They finally have the personnel that I think can handle that high-low offense about as well as anybody. So Kansas makes the final four. Well, I'm going to try to give you guys value plays. These are things that I think can happen. Like Alabama here at 25-1. Nobody takes more threes than the Crimson Tide. So that's going to be my first pick here. They beat Gonzaga this year. I'm going with them 25-1 to go to the final four. Let's get the next one up here. Who do I got as my next team to get there? UCLA, the Pac-12. They brought four guys back from last year's final four team. I all played big minutes. I think UCLA can get there at six to one as a four seed. My third team in the final four. Dave, surprise. It's Arizona plus 145. They're a little Gonzaga. I like their path to get there. And my last pick to make it to the final four is Auburn. Jabari Smith, I think he comes alive in this tournament. He's probably the best player in college basketball. Here we go from the regional champion to the national champion. It's what everybody wants to know. Time to see which team our experts think will be cutting down those nets. So everybody back in here, guys. We're going to put the NCAA championship odds on your screen right there. Great stuff. You guys know what to do. Dave, let's hear your pick. I'm going with Kentucky. You know, I've liked them all year long. I think they have a really easy road to the final four. They're going to have to beat Gonzaga on their side. But if Kelly and Grady can get hot behind the arc, they have all the other pieces. I'll go with the cats. If you listen to more ways to win radio on Sunday, you heard me say that Gonzaga's value was there when it was close to four to one. But now at three to one, I don't like the value play. But I love it for Kansas at 11 to one. Look, there's so many things to like about Kansas here. You know, David McCormick, Remy Martin. There's enough depth there for Kansas to overwhelm just about any other opponent offensively. Somebody is going to step up for Kansas. I feel like they can get it done. I think the best value by far is Purdue. Kate and Ivy. I lived through it with a guy like Carmelo Anthony watching him win a national championship. He is good enough to carry the Boilermakers with three point shooting in Williams and the big seven for Edie inside 20 to one on the big 10 runner up to win it all. Great stuff, guys. Fandall is teaming up with Visible to help you win money just by watching March Madness and answering some questions about the games. Check it out. It's the Call Your Shot Pickham Contest presented by Visible, and it's free to enter. Just go to fandall.com slash free slash hub to lock in your answers for round one before the tournament games begin. If you get a certain number of questions right, you'll be eligible for a share of the $10,000 prize pool. Hey, and if you don't win during the first round, keep checking back before each round of games for a new set of questions and a new chance to win part of that prize pool. So go to fandall.com slash free slash hub this week and every week before the games start to enter the Call Your Shot Pickham Contest presented by Visible. Good luck and as always, have fun and thanks for playing with us. And before we let you go, we've got some breaking news here. Fandall Casino has a new offer for players 21 and older in New Jersey, Pennsylvania, Michigan, Connecticut, and West Virginia. The Casino 5 on 5 is here and you can score up to $25 in casino site credit. Here's how it works. Place a bet of $5 or more on the tournament. You're gonna get a $5 credit in your casino account. It is that easy. You can do that a total of five times during the NCAA tournament. Only one eligible bet is allowed per day. So make sure to come back each round and each matchup to continue to claim more. It is all there on the Fandall Casino app. All right, that is a wrap for that. Let's get to the women's. Let's get to the women's bracket as well, guys. Dave and Pony, come on in here. Let's get the women's odds on the screen as well because we are going to pick a women's championship that tournament underway as well. Dave, I'm gonna start with you. Who is winning for the women's side? Well, with the best player in the country, Caitlin Clark in Iowa, plus 4,000. I can see Baylor in South Carolina, but give me Maryland to get some value there. One seed usually wins. I'm gonna take the Louisville Cardinals. There you go. Give those ladies a little love. That's a wrap on the show. Let's March Madness begin, guys, for Dave, Ed and Pony. I'm Lisa Kearney. Thanks for hanging with us here. The Fandall sportsbook here at Mohican Sun. We're so excited to be in Connecticut. Tournament edition is underway, guys. We'll be back next week to get you ready for the Sweet 16. Catch our shows today and next week, leading you up to TIPA.


Počkaj, pl called the definition of the general-indegral. It is said to be integrable. If the positive part, both the positive part and the negative part integrable. And moreover we define also that in this case as the integral of f ki me nickel imamo pozitiv košnju, očer, pozitiv košnju, bojez, očer, jez obradi pozitiv. Zelo se sezamo pozirte proprate delinjarnost, danes monotonist, meni? Zelo se so drželi, da je obradi pozitiv, Do veče, da se počite vzpe, da je kot se blizno vzpe, da je to či izvajno, da je zelo, da je je vzpe, da je je vzpe, da je vzpe, da je in zelo, da je vzpe, da je in zelo, da je to vzpe, da je reverz. tako našel je niskem tako, bo smo videli, da, nešel njih, je F in G in viči, tako, vsej ne vsožite o vse zač marque, vse pokazujemo zero.  Izgledaj Mark. Tako da je f je in tegrobijšk. F in nekaj, kaj je vzaj, da je vzaj vzaj, f je in tegrobijšk. To je, nekaj, to je od vzgleda, da, if f je integrabil, we know that... F is integrable. We know that both the positive part and the negative part are integrable. So of course you have that f plus, you can express like this. And so you have that this is finite. Ok, the reverse. Ok, if you have that f is integrable, then you have that f plus is less than this. And the same as for f minus. And so of course you have that being the difference between the two. You have that this, this still. Ok, now we see another important theorem of convergence under the sign of integral, which for sure you already know is the dominated convergence theorem or it is also known under the name of the back theorem. Ok, so here you have, for this theorem you have no requirement on the sign of f, ok. So you consider a sequence fn of measurable function, ok. And you have g is a function, which is measurable and integrable, ok. So what we require here is that we assume that the absolute values of fn is bounded by g. Ok, g is clearly non-negative. It is bounded by g for any n, ok. In e, this is also for any n, ok. And moreover we also assume that we have the point-wise convergence of this fn to point-wise convergence almost everywhere to some function f in e. Ok, then what we can say is that indeed under this hypothesis the limit of fn of x, the integral of the limit is equal to the limit, ok. This is f of x is equal to the limit of fn of x in gx. Ok, let me, maybe I should write it more, just write it f of x. Ok, for the proof, may I erase this, the blackboard in the middle? Ok, the proof. So we want to prove two sides of this equality. Ok, we have, of course, that minus gn is less or equal than fn minus g. Ok, so, first we observe that g plus fn is larger or equal to zero. So, and of course we have that, and so fn plus g converges to f plus g almost everywhere in e, ok. Ok, so, what can we use here to deduce at least one first convergence result? Here we use the Fatoulemma, no, because these are positive and so we are under the hypothesis of Fatoulemma. We have that the integral over e of f plus g is less or equal than the limit fn plus g. Ok, so, this is what, this is the limit, the integral of fn over e plus, here it doesn't depend on n, so, plus g e. And, ok, here we have, this is of course, by linearity, is this. Moreover, here we use the fact that g is integrable, ok, so the integral is bounded, so we can cancel out and we can first say that we have this side, ok. And then we consider the other inequality, so g minus fn is larger or equal to zero. Ok, again we use, so we have that the limit of g minus fn is g minus f and again we use the Fatoulemma. Ok, my Fatoulemmas we have that g minus f is less or equal than the limit of g minus fn. Ok, and here you have, ok, the integral of g, of course, does not depend on n, so you can, and here you put minus the limit soup of fn. Ok, for the same argument that I thought before, you have this is g minus the integral of f over e, so these terms can cancel out, and so what we get, we get that the limit soup is smaller or equal, yes, thank you. So we combine these two, ok. So, and we use the fact that of course the limit is always less or equal than limit soup, and so if you ask, we get that indeed the integral of f coincide with the limit of fn. Ok, so we are done. Ok, and now, because you have that the fn is, because of this, so you have that fn is less than g and minus fn, yes, I mean, you have this two inequality, you know, this come from this fact. I didn't get your questions. Ah, you mean to rephrase this hypothesis in the case of g, I mean, here the thing is that you have that fn must be bounded with an integrable function and also the negative from above and from below somehow. And so this is a way to express this.  But they are equivalent, I mean, the fact that you value this or you consider the two inequalities is equivalent. Ok, maybe we can, yes, here. Ok, this is due to the definition of limit soup. You can exchange, ok. Probably we use this, I mean, this trick also when we prove that the limit soup of measurable function is still a measurable function. Ok. Ok, now we see another version of the dominated convergence theorem, which is somehow the hypothesis are a bit relaxed and this goes under the name of generalized dominated convergence theorem, ok. Ok, so we have gn. So we start by somehow, we consider, we replace g by a sequence of function, ok. So gn is a sequence of measurable and integrable function such that we have that gn converts to a function g almost everywhere in e and we require that g itself is the limit is an integrable function. And then we consider let fn, a sequence of function, which are measurable and such that fn converts to a function f almost everywhere in e and we have that fn is bounded by this function gn. So we don't need to have the same function here for any in e for any n and we have that if we know that the integral over e of gn is equal to g here we can assume that they are positive. Ok, then. Yeah, yeah, yeah, sure. Ok, then we can say that also the limit then goes to plus infinity of fn converts to the integral of f over e, ok. Ok, so somehow the proof is a bit analogous of the previous. So we divide it in so you have that gn plus fn is larger or equal to zero. Ok, is it clear this, no? Ok, maybe later we can. Ok, and gn plus fn we have that it converges of course to g plus f almost everywhere in e. Ok, so we have again by the fatulema you have that g plus f the integral of g plus f is less or equal than the limit. Ok, so in this case for g we know that the limit exists so this can be written as as the limit plus here we have to to maintain the limit of e fn and then here we use our hypothesis and here you keep, ok, again since we know that g is ok, g is finite so we can cancel out the g the integral of g and so we get one side. Ok, ok, the other side it's analogous less or equal ah, no, less now this is this step is equal because you know that the limit of gn is equal to g, no? And here, ah, before this ah yes, this is this is equal, no? because in principle you can split the limit of gn plus I mean, I think I mean, this is you can split between the sum of the the two limit, ok? And then this is equal to the limit you know that the limit exists and here you just have to get the limit ok, so the other ok, so you have that gn minus fn converts to g minus f almost everywhere in e and again by the fatule you have that g minus f is less or equal to the the mean of fn and again ok for me it's equal, but this is equal to the ok, the integral of g minus ok, here you can use the trick that we used before ok, so finally what you get is that f is the integral of f is larger or equal than the limit sup and so again if you combine the two you get you get the thesis may rise here ok, now we will see an exercise so we have fn, a sequence of of integrable function some sequence ok, and we assume such that fn converts to f almost everywhere in e and what we want to prove is that with f measurable then we want to prove the following equivalence so this goes to zero if we have that this goes to zero so one side so this implication the fact that the modulus of this difference goes to zero implies this fact is the easy part so the other part is somehow the difficult one and we have to use also this hypothesis so proof ok, so so this part so this side comes from the fact that in general you have that this is equal to fn minus f and so when you get so in general so when you pass to the integral pass to the integral we obtain the convergence of the integral and then for the other for the other implication so if you start by knowing that this convergence holds this one we have to use some theorem of convergence under the sign of the integral ok, so we pass to the integral ok so if you take the integral ok ok, so what would you use in this to prove the other the other way around maybe we can use the generalized theorem that we just proved ok and so we have to find for instance somehow this difference the modulus of this difference plays the role of the fn ok, and so we have to find a sequence that bound this this modulus here ok how would you one way is that ok, so we want to apply generalized the back convergence theorem ok ok, so first of all we notice that so we have to infer something about the point wise convergence of this first of all ok, but this is easy so we have that fn minus f goes to zero almost everywhere in e ok by hypothesis ok and then how can we bound this in terms of a sequence that satisfies the hypothesis of the generalized the back convergence theorem so one way is for instance if you observe that this is less or equal than this ok so this is somehow plays the role of the gn ok of the gn, they are integrable and we have that gn converges point wise almost everywhere in e to some g where this g is where g ok, gn are this ok g is two times the modulus of f what we have is that what we need also to check is that the limit of gn for the limit of the gn is the limit plus f but we know by hypothesis that this first part of the limit converts to the integral of f so this is indeed two times f ok ok, so we are done because now we are under the hypothesis of the generalized the back convergence theorem and so we are done ok ok, now I want to show you another way to prove this second implication the most interesting without using the generalized the back convergence theorem but only the the back convergence theorem the first one that we state it's a bit more it's a bit more lengthy but it's interesting to see ok, just to simplify the things we let me reformulate so you have fn and f some function so assume that they are non-negative because otherwise we state the result with the absolute value so just assume that they have non-negative integrable ok, and we assume that fn converts to f point twice most everywhere and assume that that we have the convergence of the integral ok, so we want to prove that we have also the convergence of the integral so the integral of the absolute values of this difference goes to zero and we want to prove this without using the generalized convergence theorem but just the classical the back convergence theorem ok ok, we observe this fact that if you consider this sum you can express this sum has the maximum between f and f minus plus the minimum between the same ok, so let me call this denote this with with a dot ok ok, this is because this is if x is such that fn of x larger or equal than f of x then you have that the maximum between fn of x and f of x is equal to fn of x and the minimum is f of x ok so if you sum up that things are consistent if otherwise x is such that you have that fn of x is less or equal than f of x so you have the reverse of course fn of f is f and the minimum is fn ok, so is it true? and moreover we use another representation of this form ok, moreover we have that fn minus f values of difference is equal to the maximum of fn of f minus f plus ok, plus f minus minimum of fn of f ok, just because if you have two cases if x is such that fn of x is larger or equal than f of x ok, then this is equal to this and you have that the maximum between f of n and f is equal to f of n and the minimum of n and f is equal to f ok, so so if you replace here the maximum is fn so you cancel these two f and the minimum is f and the other case is completely analogous ok, so ok, just to wrote it in a more simple way so you have that this is equal to of fnf minus the minimum of this ok, so we want to study the convergence of the modulus of this difference and we want to to use this representation of course ok, so we have that this is the integral of the maximum of fn minus the integral of the minimum so this is a, the term a and this is the term b so we start by this one which is the easier somehow ok, so we have by hypothesis b ok, we have that fn converts to f almost everywhere in e and so we have that by this you can also prove that the minimum between the two fn and f converts to f almost everywhere in e I think we already prove something of this type ok, ok, so we can apply the the back convergence theorem so by the back convergence theorem so why we can apply the back convergence theorem because ok, let me also sorry, let's state like this, because this is less we are interested in saying that this minimum can be bound by by f and this is integral ok, so now we can apply the back convergence theorem and we have that the integral of this minimum converts to the integral of f ok ok, now we have to treat the other part, the part a ok, so here we still have the point wise convergence of this so we have still that the maximum the maximum between these two converts to f almost everywhere in e but what we don't have in general it's hard to find a function that bounds this sequence, ok so we have to argue in another way so we recall that by this formula that I denoted with this dot that the maximum of fn f can be represented as fn plus f minus the minimum between the two ok so if we pass to the integral what we have we have that maximum minus the minimum ok ok, so what can we say about the convergence of this part by hypothesis by hypothesis we know that this converts to two times f so here we just prove by part b that this converts to the integral over e of f so at the end what you obtain is that this converts to the integral over of f so at the end what we get here is that this converts to to zero, yes, because you have f minus f ok, so this is ok, so this is somehow another way to prove the same result but by using by using the theorem of the classical lebel convergent theorem ok, and now we see somehow some consequence of the lebel convergent theorem so a classical consequence is that you can differentiate under the sign of the integral but ok, we will proceed by step so we prove this theorem we consider f a function defined in this product space so e is a measurable set and y is a metric space ok, we assume the following we have three three hypothesis basically that for any y in this big y the metric space the function which with y fix associate to f x, y is integrable over e then the second hypothesis is this time we fix x and we consider f as a function of y this times we require that it is continuous in y ok and finally we require somehow the existence of dominating function so resist some g defined from e to non negative function integrable such that this is less or equal than gx this is for any x in e and for any y in y ok, then where in the question why associate f as y is continuous in e yeah, it mean in y, I mean in the variable y, yes of course in y below I mean has a function ok, it is clear because yeah, I know that it is ok in y this was just to stress the fact that thinking at it as a function of y ok, y in y ok, then so what we want to prove is the following f, big f defined from this big y to r is continuous and now I tell you also how it is defined f y is defined as the integral over e of this function f x y e x so here you think that y has a parameter somehow ok so we have that this is for any fix at y this is integrable, so somehow this is a good definition it makes sense to consider the integral ok, in just 2 so we want to prove that this f is continuous this big f is defined on a metric space ok, and on a metric space the continuity is equivalent to the sequentially continuity so it is enough to select a sequence which converts to some sequence yk to some y and to prove that f yk converts to f of y ok so f so since y is a metric space continuity if you want f is continuous if so we take point y small y in this big y and in the sequence yk which converts to y ok, what we want to prove of course is that if f y k converts to f y ok so we use the definition of f so we just maybe it is convenient to define this auxiliary function hk x defined as f x y k and in analogy hx defined as fx in y ok, these are measurable functions and so on so we have since f is continuous in y hk x converts to hk ok so infinity and then we can bound this hkx by this function g ok, so we can apply the dominated convergence theorem we have that this is ok by definition so then we use our notation in this converts by the dominated convergence theorem ok, so we are done so many of you guys ok, now we see another application of the the back convergence theorem ok, so ok, we have that f e times i r e is a measurable set and i is an interval ok and then we assume the following ok, this time that for any y in the interval i the function which to x associate fxy is integrable in e for any x in e this time we require more than the continuity is we want that this function is differentiable so in y belong in 2 y ok, this is clear and 3 as usual we want that there exist an integrable function that control from above this time the partial derivative of f with respect to y ok, such that this is less equal than this g and this must hold for any x in the measurable set and for any y in the interval ok, now we can imagine what is the proof the thesis then we have that f is differentiable ok, of course and ok, f f is defined as before and we have that so f is f of y is defined as exactly as before v x and what about the derivative we can somehow bring the derivative inside the integral ok, this is the interesting part of the theorem so we can exchange somehow the integral and the derivative ok, so one false question that one may ask is that it makes sense to consider this this integral so is this function measurable ok, so the answer is yes, because you can you can think just that the definition of derivative has incremental quotient so you have that df dy xy take a long sequence so this is the limit as k plus infinity of x yk yk minus f of x divided by yk so somehow this is still a measurable function this quotient, this is the difference and the quotient if we take the difference and then the quotient in the framework of measurable function and the limit is still a measurable function this is we already prove so somehow this this integral makes sense this is a first remark ok we have that say what else I want to say that and ok, it is measurable of course it is integrable because of this ok, we want now to investigate the differentiability property of this big f so we just as before take a sequence yk that converts to y and you have f yk minus f y divided by 1 of yk minus y ok, and now we use the definition so this is the limit as yk tends to y of ok, of this so we have this is f x yk minus f x y ok, then just use the linearity of the integral you can exchange ok, so now we are interesting in study this quotient ok, so we want to apply the dominated convergence theorem so we have basically to check two things the point-wise convergence and if it exist a bounding first a function an integral function that can bound this quotient ok, the first thing is that the limit so point-wise limit x yk minus f x y yk minus y converts point-wise, as k tends to infinity to the y of f is y so we have point-wise convergence and b ok, let me define this as before introduce this auxiliary function hk xy this time is all the quotient and this let me call this hx y so b this is a function of course of x I treat the yk as a parameter here so here you have that at any fixed x you can apply the mean value theorem ok, so this is ok, by at any fixed x we can apply the mean value theorem and so we can continue this inequality by saying that this is df dy in x c and this is less or equal than g of x ok, we can get rid of this g of x, this is by hypothesis so this is true for any x and for any y ok, now we really can apply the Lebesgue convergence theorem ok so here we can continue here, ok we can exchange we can bring the limit inside the integral this is k plus infinity fx k minus fx y divided yk minus y and that's it, now and then we are finished this is indeed so we have that f is differentiable and the quality that we state and we can represent its derivative in this way ok, maybe has an exercise you can prove the following this is somehow a slight variation of what we saw so you have that g is an integrable function and ok, e is measurable and bounded f y be defined in analogous way for instance g of x times the sinus of x times y in dx yes, sin sin in dx, of course ok and y, ok, y, this time y I took as matrix space r and then we can prove that f is sin infinity in r, ok so the proof somehow we have to combine the previous theorem so combine so the previous theorem and the and then you have to prove by induction ok and so and induction ok, the induction on the degree of the derivative ok, in the last 10 minutes let me show you this lemma so we have we start by e by a function f which is integrable ok, e, of course is measurable and we suppose that this integral is non-negative for any a measurable contained in e ok ok, then as we already did we want to extract some point-wise information this time on the sine of f from the information sine of the integral so what can we prove is that f is non-negative almost everywhere in e ok so somehow the proof is basically always the same so a way to rephrase this is to prove so the thesis can be viewers saying that f where f is negative as measure zero ha? sorry? f is thesis ok, so it is ok, we want to prove this is to say that f is non-negative almost everywhere so we want to prove that this set as measure zero so as usual how can we express this set here as the union ok, the countable union of f is less than minus one over n and then ok, by assumption we know that the integral of f of x over this set here is non-negative so this is less or equal by definition of the set minus one n time the measures of f ok so we have that is equal to zero because here I have a minus sign for any n and then and then we are done ok because you have that measure of this union is less or equal than sum of the measure of and so this is zero and so we are done ok, we can stop here


Amanda's a cow skis next on the hot seat. Amanda, I'm gonna give you the exact same question. Everything you've been through, for it to be coming through this way, for you to have this opportunity coming up on Wednesday night to be able to celebrate senior day this way, like can you put into words what it means to you? I think we've worked really, really hard to get here, especially in our four years. We had some rebuilding years in between there. And I think that this year coming out the way we are, but especially with the freshman class, they've really done everything that we've asked them to do to really make this a good last ride for us. It's working out pretty well, right? Yeah, it's working out for ya. It's really working out for ya. Are there some nerves in terms of playing Messiah Wednesday night for the conference standings? I think we're gonna bring it to them. I don't think there's any nerves, honestly. I think we want this so bad. Four years in the making, we're coming to you. We've been waiting for this one. Well, they're actually coming to you. Yeah, right. All right, we get some shout outs on senior day. Who you shouting at? It's just my mom and my boyfriend. All right, all right. They're probably both good guys. They're probably both. Congratulations. Thank you.


Hello everyone, my name is Ankur Kotival and I currently work as a software engineer at Akinox. Today, we are going to talk about how to automatically derive security policies using observability data. Let's first take a look at observability. Observability is a way of understanding complex systems based on the output they generate. This data consisting of logs, metrics and traces can help us to better understand application behavior, application performance and in identifying security postures. These security policies when applied can greatly reduce the attack vector but they are not very easy to implement. In this talk, we are going to focus on using observability data to identify security postures. Let's first look at the issues we face today. It is common to analyze network and system logs for generating security policies but the manual process is inefficient and has a high chance of missing important logs. Manually analyzing observability data to come up with the least permissive security posture is in itself a very difficult task. Even if we assume to handle the certain time security for a single point in time but to maintain that security posture over a period of time is extremely difficult. For example, suppose we are able to create an apartment profile to harden our application but that application is going to change very soon which means the security profile will need to be updated again. Furthermore, these questions about how to identify important logs, generate least permissive policies and regularly update the security posture are difficult to achieve manually. Thus, it is imperative that this process has to be automated. The challenges in identifying security policies from the observability data are there is a lot of noise in the raw observability data. For example, there could be random URL connections or random file accesses. It is required to produce a minimum policy set covering maximum flows. There is no point in deriving policies rules on per flow basis as the policy becomes intractable very quickly. The discovered policies should make use of right abstraction. For example, in case of Cade's environment, the deployment labels should be used in place of other transitory constructs like IP address. And handling data aggregation is the key. The answer to all our questions is to have an automated policy recommendation engine which can analyze the observability data and can derive appropriate security posture. So when the workloads are deployed in the CI CD pipeline, the idea is to get the observability at that point in time so as to identify what the application is actually doing. When the application is updated, we get a differential view. This gives an understanding of what is changed in the application. From this, we can derive a set of system or network policies which can then be pushed into the production environment. So here, we can see two sample differential views with application behavior differing slightly in v0.1.1. This information can be used to derive a set of security policies. The idea is to achieve zero trust security setting in a DevSecOps model. It can be done by deriving least permissive security policies which can only allow essential resources required for running the application and deny everything by default. And do all this in real time, which means to generate security posture which is in sync with the application changes. Let's look at some of the questions we asked earlier. To identify important roles, we need an automated policy discovery engine which can convert the raw observability data to useful runtime security policies. To generate most restrictive policy, denying everything by default is the key. We need to use least permissive policies that can only allow essential resources required for running the application and deny everything else. The security posture should always be in sync with the application updates. This can be done by shifting left and testing the discovered policies in the early stage of software development cycle. I'm glad to tell you that we at Cubarmer are already working on such a policy discovery engine and we call it discovery engine. It is an open source recommendation engine which works as a case plugin. It consumes the visibility information from container network interfaces across multiple clusters and has the ability to auto derive a least permissive security posture from it. The engine averages aggregation techniques to reduce the number of policies discovered, uses pod labels for rule specifications and handles discovery across multi-dimension for both networks and systems. Discovery engine easily integrates with CNS like Cubarmer or Cilium and can ensure their easier adoption. So to summarize, it is not only inefficient to manually derive security posture but also has a high chance of missing important logs. Observability coupled with a policy discovery engine can provide a seamless DevSecOps setting. Such permissive policies can help achieve zero trust. Observing application behavior during testing can help in identifying runtime attack in the early phase of development and shifting left is the way ahead.