If I speak, I am in big trouble, in big trouble, and I don't want to be in big trouble. If you need Madden 21 coins for anything, make sure to go to buymuntcoins.com. Check it out with the link in the description and my code MMG is 15% off. I need to start this video out with a massive apology.  I had so many opportunities to make that, a fire video, and I did not play well.  Trace McStorley, you're not getting just one, but you're literally kidding. I can't believe I'm doing this. You're getting two Trace McStorley gameplay videos, okay? And if that's not enough, then I don't know what to tell you. He's got 79 speed, I did not utilize that nearly well enough. Just for comparison, the 79 overall patch of my home has 68 speed. I don't know if that's realistic or not, but all I know is Trace McStorley can move and I need to utilize him on the read option more. So, we're hopping back in it and I'm getting my redemption. Yo, can we all agree right now though that if any of us watching this video pulls a golden ticket six months from now that we make a golden ticket Trace McStorley, can we please like shake on that? How fire would that be, bro? Make him like a scrambling art style, it's like a 95 speed Trace McStorley throwing, throwing it out of time.   So, if you guys think anything good, got any good bars, shoot them my way. This is going to be the game where Trace McStorley goes absolutely ballistic, and I'm sorry I didn't do it last time. I will redeem myself. All right, it's Trace McStorley redemption time. Let's start out with some good defense, get the man the ball. First in 10, I'm sending a blitz, why not? Oh, he runs the ball, good timing. Third in two, let's get big stop right here. Oh, can he get there? Can he get there? Oh, good pass, big hit. Jamal, let's go. Calm down, Jamal, don't pull out the nine.  Correct, the piss out of him, right on the ball too. That is a hit that should be a bumble, that is an accurate bumble. First in 10, McStorley's first throw. Let's see where this heads are, B, down the stripe, hit B, got him, 31 yards. All right, already, already having a significantly better game than last time. I say we come out in the same set, and we scramble his puppy in. Is this no blitz though? All right, no blitz. McStorley up the middle, get the jill. Go, go in. Look at that spike for McStorley too. All right, we're going for two. I should be able to feed Olsen maybe?  Olsen had no business catching that. 8-0, this is the McStorley I was looking for last time. I'm just embarrassed all around for that last one. I gotta imagine he's passing here. I'm on high tower, wait, high tower? Dude, what lineup do I have in? Uh-oh, that's kind of open, no, no, Lamar. Not 2019 Lamar, not MVPs using Lamar right now, two fumbles. All right, we're going to send some heaters and just try and clamp the middle here, let's see what he goes with. All right, you got a couple of slant routes. I'm trying to cover all of them and I cannot cover all of them.  Third and four, let's get a stop here. I want McStorley to have this ball. I'm sending the heater. I'm sending the heater, boys. More slants. Oh, good play.  Oh thank God, it's Nick Boyle. Who is he having at tight end, bro? Wow, that's a touch. If you got George Kittle, that's a tutty.  Chase Holcomb, this man is a goat. I'm telling you, bro. Washington football team stud. Ah, get there, yes. Boyle does not have the sauce. Third and four, I'm sending the blitz. I think this is a run. I'm coming in hot with Jamal. Ah, it is a rock and a goal. That's my assignment. You know what? It doesn't matter. It really doesn't, because Chase McStorley is just going to walk us back down. Plus, did with the Eagles did versus the Niners, we went with a bold, aggressive two-point conversion at the start. What are you going to do? Where are you going to throw? Now it's open. Where are you going to throw?   Passing game is lethal right now, so we're going to stick to it. But I have the read option ready to be deployed. Oh no, we just scrambled that one. We just scrambled that one. Give me a block, Bo. Give me a block. Let's go. Stop and go. Ah! Oh, I tried to stop and go and he didn't switch out quick enough. I could have taken that even further. Let's go. McStorley is moving. All right, same shit, different day. Does he QB spy me here? No QB spy. That's bold. Ah! Ah!  Shoot, but I'm hurting his passing stats. I can't be doing that. He is surely only completed one pass. I'm going to look for Olson right down the seam here. I really like that pass. Yup, yup, no, ah! Whoa, whoa, it tip off his. That's not on McStorley, dude. That is not on McStorley.  Oh my God, look at this pass. That is a great pass.   Wait, what did he actually do? Let's get this ball back. All right, I'm going to send a screamer and go in hot with Jamal. Just got to look underneath so I don't get sauced up by anything. Yup, right here, right here, right here, no!   I don't know how that just happened. All right, this could be the marking room. That's the only way I'm getting dusted here. This could be a handoff. All right, it's not, it's not. I got it, I got it. Are you homeless?  Ooh, a punt, is it a fake? Yeah, it was a fake. I came out and covered three and he called the timeout, that's a fake. I'm going to run press coverage here. I'm excited to see what he goes with. I have no idea if this is going to work or not. Oh, he does run the ball. You're marking your powers, well played. Looks like pretty basic slants. Ooh, he's throwing sketchy. Nothing deep, boys, nothing deep. Let's play over the top. Oh, oh, he quick snapped it, but I rocked him. Dude, thank God I was there. Oh my God, he had a lot of room. I'm interested to see what he's going to try and throw here. Presumably slants. Let's just keep it clamped. Yup, I'm on it. I'm on everything here.  Good defense, boys, we needed that. All right, I haven't pulled out read option yet and we need some fire under this offense.  That shit's going to happen, all right? Make the correct read, very good.  Ooh, wrong button, damn it. I should have hit dead leg and I hit juke. But I guess I'm glad because I want to trace McSorley with the touchdown, not Bo Jackson. Let's see if he'll bite on Bo Jackson now that he just dusted him for so many yards. Oh, he doesn't bite on Bo Jackson. One more time, come on.  Dude, go get Bo Jackson, seriously. He's murdering your team right now.  That's the most likely scenario. Oh, he's got the QB spy on me, but it's not fast enough.  We're in a good spot here. Alicia hit him with something weird, dude. There is no way in hell he is aware of a slip screen right now.  He is kind of aware of a slip screen. Oh, it doesn't matter. No, that is not clutch. All right, third and seventh, Olson Redemption. No auto, 10 seconds on the clock. Greg Olson, redemption, perfect pass for McSorley. Ooh, this is a really bad play call. Oh, and it's Mahomes. It's not even McSorley. Well, if I can still hit it, that'd be cool. Hey, you know what? We completed the pass. Can you please bite? Please just bite on Bo Jackson right here. I want that whole defense to shift to this man. Yup, ah, he did not. He did not. He did not shift. Trace McSorley, the juke was effective and I broke the tackle. I just was not in a spot to make a play. Shit. All right, well, you know what? Do I continue to trust in Greg Olson? Yes, I do. Look at that. First in 10, does he take the drag underneath? Kind of. Olson's there though. Greg Olson really wants to make it up to Trace McSorley.  Second in six, I'm gonna send Bo Jackson underneath just in case. Is there a QB spy? Yes, but it's slow. It's a slow QB spy and McSorley doesn't fumble. Let's make sure that's no. He really is QB spying Trace McSorley though. That's definitely happening right now. I gotta say, I'm pretty sad about it. Third and fourth, will they finally bite on Redoption? He does. He does bite. No, we need to stop and go. Oh, they're all over me. Gotta make something big happen. I'm thinking Julio on a slant. This is gonna be my money play here, but we'll have to see. Oh, does he bite on Olson? Does he bite on Redoption? He did. He bit. That's good. We're gonna try the two-point conversion with QB draw here. See how that goes. Oh, damn. Damn. Oh my God. Whoa. Those blocks are incredible. All right, Fulblitz. I'm coming in with Minka. Oh, maybe not. Maybe not, maybe not. Don't you dare, Mark Cooper. Oh. All right, Fulblitz again. Ah, he keeps doing that. He keeps accidentally throwing it early and it's working because I'm blitzing everybody. Is he gonna run it now? If he runs it now, they'll be depressed. Okay. That's okay. My two-point conversion puts me in a really good spot here.  That's a classic bag fumble right there. Ooh, this looks more open. I'm a little scared of that free safety, but let's see how this looks. Yup, yup. Finally, no. Give me a block, yes. Thank God. Stop and go magic. Oh, he knew. He switched off. Damn it. He switched off his lineman, but finally, Trace McSorley gets the read option to work.  Let's try it one more time. He's got a corner over there. You want a bite? Nope, he's not gonna bite, but that's okay because Bo gets five yards every time I hand him the ball. All right, let's send Bo on there. Dude, this tight end street crowd has been absolutely electric all game. Oh, X. Oh my God. No! Oh, it's bad. This is honestly his first truly fumbled pass. He's really QB spying. Trace McSorley. I got lots and lots and lots of time in the pocket. Can I make a move? That was basically exactly what happens when you get really cocky. As 22 to 14, if I go for this, don't get it. I'm really glad about the 2.5 conversion right now, though. That's for sure because he's gotta get to even tie this puppy up. Fourth and 22. Let's see who's gonna get open here. Yo, proper woods! Damn, I needed that ball to come a little more inside. Six for 10, two touchdowns. He's playing well, though. All right, second and two. Does he keep running it? No, he might wanna throw this underneath. Oh! You know I respect this decision. We got a bunch of slants here. Kinda clamping everything. Dude, I just boofed twice on slant routes. That's so uncool. Oh, it's a pass, my ball!  Now, yes, I think I could just hammer the run and we'd be in business. I'm gonna call a couple pass audibles and then I'm gonna switch back to slip screen and I'm gonna hit Bo Jackson on this. Oh, yup. Set those blocks up, boys. Set him up! All right, all right, all right. Tracy McSorley can really scramble this right over top of the QB spy. Oh, he's QB spying by himself! What are you doing? Let's go! McSorley! He just iced the game with that. That's it. Do I got woods for the touchdown? Do I get bulls? I'm sketchy too.  Yup, take off. Oh, okay. Dude, Tracy McSorley actually just led the team to a dub in a highly competitive high-scoring game for two more yards. But McSorley, with 111.6 rating, eight for 14, compare this to his last game. It's so much better. 198 yards, 57% completion, three passing touchdowns, one interception that was not his fault. Look at the rushing stats. He's the leading rusher from the game, nine for 69, average seven and a half in a touchdown. He has one broken tackle. All right, boys, I had to redeem myself on Tracy McSorley. I do hope that you enjoyed this video. I don't, this will be the last one though, unless there's a golden pick at McSorley, that's it. All right, well, I hope you guys enjoy it. I'll see you in the next video. Peace out.


It's brutal battle beer break and today we're going to be doing actually a style I've not done on brutal battle beer break and I've had maybe one on the podcast itself but not a whole lot. It is a Scotch ale and it is a Scotch ale called Big Sound and it's by Cigar City Brewing out of Tampa, Florida. You can see Big Sound and I actually looked and there's no information on ABV for this beer so I'm wondering if it'll taste the stringent or not. We'll have to see what happens here because while I was setting up to record I actually knocked the bottle over so I'm hoping that when I open this up it's not gonna have an issue but we'll see. Oh thank goodness. Safe. All right let's pour a little bit of this bad boy.  I mean that's what I expect from like a Scotch ale is like a red aspect to it but this is a nice reddish brown. There's an okay amount ahead for what you would assume is more of a viscous style beer. I can't really see through just because I have dark it is. It's filtered though but you know you can't see much. It just looks dark. It's got this nice sweet, sweet aspect to it. Some nice kind of cherry notes on the nose what I'm getting first. A slight bit of a raisininess but actually a lot more cherry. A little bit of a roasty maltiness. A little bit of a grassiness in there as well. Like there's some solid hopping added to this. It smells very clean though. You know there there are no aromas that they make a smell like funky or weird or it just smells like such a clean straightforward Scotch ale. I'm smelling a lot a lot a lot a lot of that cherry and it's like fresh cherries. It's not like canned cherries or maraschino or anything like that. It's like legitimate from the garden fresh cherries not tart maybe like bing cherries something like that but there's a nice sweetness really rounding it out. It smells really good. I'll try this. Yeah wow okay it's um it's not as viscous as I thought it would be but it's also not like extremely light so it's kind of like a medium body to it. I was expecting maybe of like a medium heavy body to it something like that but I get a lot of that kind of a raisiny aspect. I get that those cherry notes as well. Really gotta dissect this. Lots of cherry actually. I'm getting a little bit of that grassiness coming through as well. What's sticking around is that kind of cherry aspect mainly. A little bit of alcohol to it not anything too crazy but as far as Scotch ales ago I feel like a lot of Scotch ales have a tendency to get kind of sweet kind of alcohol-y. This is neither of those. This is dialing back the sweet, dialing back the alcohol. It's got a nice like legitimate kind of cherry flavor to it. The malts are very nice in it and like I said a little bit of like a grassy aspect to it. Not a ton but a little bit. Nice beer. Easy drinking as far as Scotch ales go. A lot of Scotch ales I've had before don't seem as easy drinking as this but actually as I'm sitting here I'm noticing I'm feeling a little bit of like an alcohol burn in my throat at the moment and it's funny because it wasn't there at all and then all of a sudden as I've been talking it's just slowly started kind of building and building and building. Not a bad thing at all but it lets me know there's some serious alcohol in it. I'll taste it but I can feel it after. So nicely crafted beer. Cigar City a lot of people love Cigar City and expect nicely crafted beers so this Scotch al big sound is no different than what people expect from Cigar City. Thanks so much Cigar City for making this beer. If anyone out there can get their hands on it I would recommend it so go ahead and find it if you can. I actually got this from the brew pub when my wife and I were down there recently so I know it's there so if you live in that area if not sorry you might not be able to find it but anyway thanks so much for checking this out everybody feel inspired.  Thanks for checking it out.


What's good y'all it's your boy Ross back here again with another video so we're gonna check out PC Hooli Warzone Mega Rage Complication number five R.P. Steve. I guess that's what he named his dummy in his room now I did see some of his clips in like a previous Warzone rage compilation one of you guys has sent it to me in the DM saying yo You need to check this out because he'd be going in on the dummy And I think it's actually pretty smart to have a dummy in your room or something you can punch on When you rage and you know you tend to rage it it saves you a lot of money So you don't end up breaking stuff. So I'm gonna definitely check this out Pretty sure it's gonna be hilarious. So I appreciate all the love and support Roll to 30k and let's get into it I wonder if that's really his dummies Oh, no, yep My god, this is great. Oh We're the oh wow.  Yep the combo for the storm. All right take beat them so hard. It started lagging No, come on. Come on, man. He doesn't deserve that. He doesn't deserve that God damn Steve could talk. No, come on, man. He completely miss No, no, this is great Bro, bro, I've never seen someone just rage this hard and attack. They dummy. Oh my god This wraps. Oh, you're done. Oh Boy Steve. No, it's actually low key kind of a workout, bro. Look at him.  That should be all wet This low key a workout man, this is low key a workout, bro I like you got a shirt for Steve man.  Oh my Rage is real This is all my god. This is amazing Yo, this is so amazing, bro, and I thought I raged This is great. Oh my god. This is great. This is great, bro So you can click with confidence.  Oh, I don't know. I hope you don't know. Don't do it, bro That's what Steve is there for. He's saving you money. Oh Steve Those gut shots I Couldn't be in a party with him. He'd be kicking me out because I would die and I definitely couldn't watch this stream while I'm playing a game with him because I'm definitely going to I'm definitely going to lose it. Uh-oh. Well, oh Here we go.  I love it Still doesn't deserve to stop a punch me man, but I love it Then you're dead This is good, bro, this is great, man. Oh my gosh, this is good Dog what What was that? Streams sniping you Steve in the danger zone. Oh my god. This is so great. This this is Great, bro. Oh my goodness. It makes my rage look minuscule Hard to discover. Oh my god, bro. It's time to try taboo. Look This this is great. This is true entertaining bro This is great. No, no, no, no, no Steve. We'll have mercy man. Oh, no, he's gonna lose it He's gonna lose it. He's in the final circle. Yep. He's gonna lose it. Oh, he's gonna lose it. He's gonna lose it He's losing it. Oh No No No, Steve get out of there Get out of there Steve. Please get out of there Wow. He's still got the dog Good good plays by a teammate Steve deserves better man Oh, no, come on. Come on, bro. Come on, man.  I definitely will check it out. This was funny, man Rp Steve man Steve didn't deserve that type of punishment.  Come on, bro. You get you deserve better, man Don't take that treatment. Don't take that punishment man But yo, this was funny as hell I love seeing people just lose their shit and call the duty because I know I do not as bad as that But I definitely be having my moments while I be ready to just flip shit, bro But comment down below Let me know if you guys would be interested in seeing more of these are these are rage reactions from PC Hooli I definitely will if you guys are interested in it I appreciate all the love and support brought to 30k appreciate y'all kicking it with me I'll see y'all in the next one. Peace


So this is my setup right here, I've been streaming those three days here in the embedded world. We're filming right now with the AstroSlide so you can check out the camera quality. So it's the YOLOBOX Pro with three HDMI inputs, USB host so I can get a fourth HDMI input. I'm not using those two inputs right now. I'm just doing a selfie with the Filmic Pro running on a Samsung, I could do it with my Huawei too. It runs out of power, I just swapped the camera. Now this one is down to 23% after three hours and a half.  So I'm presenting, sorry people in the live chat, I'm showing with my setup. So there you have it, with live chat, people were posting comments on your video right there. I just put the comments on top of the video. I can do it full screen like this if I want to monitor and full screen. I try to balance my weight so I can even do it hands-free a little bit, walk around like, is it called a frog walk or the way I'm walking? I'll take it out. This is the frog balance a little bit. Here I've got a 5G router. You can see this is ZTE5001 and it's using a bunch of gigabytes over the 5G and at the same time this is going ethernet in to the YoloBox Pro and there's a 4G O2 SIM card. So I've got 3G telecom plus O2. They are bonded using speedify VPN that's running on the YoloBox using the hack, some kind of hack I'm able to run right here. What about the camera? I can do a dual view right here. This is my Panasonic G9 which is still the best camera in the world even though it's a little bit out of focus sometimes. I'm thinking to eventually change to something that will have perfect autofocus. It's not yet. Sorry about the autofocus once in a while. This is the most expensive power bank I ever bought. It's 100 watts so it's got enough power to give power to the YoloBox right here so I can power it up and it shows how much power is being used. It's got enough power to run the YoloBox for three hours more. So in theory I could do six and a half hours of live streaming. If I keep swapping this battery I've only got one home baby, I'm not sure. I forgot to charge one battery last night. So I'll be swapping over to the dummy battery which is hanging right here. I'll have a dummy battery and I'll go over to the power bank to extend the live streaming of the main camera too. So I can try to do my targeted five hours per day. And this is an exercise for me. It will last the three years of what's called the COVID. I need to do some exercise. So I'm taking everybody to the gym with me. You can see how I try to work out. I'm using my light hat and everything powered around the YoloBox Pro which is running on the Qualcomm 660. I don't know how they capture all these. It's so cool. They've got a bunch of functions here. They even have an HDMI out. If you can see up here they have a Type-C that also does display out. It has a microphone input, a line input. But right now I take the shotgun mic. I use the shotgun mic because I've had a little bit of interference. When I was filming at ST Boost today I didn't want to have a clipping and stuff because there's so much Bluetooth everywhere on the show. So I got one comment yesterday on the first day. Never use wireless microphone. So I shouldn't do that. I did that the first two days. 95% of the time it was okay. But then sometimes it's 5% when a busy booth has Bluetooth and Wi-Fi and everything and it starts to clip. So now I'm just doing the shotgun mic. But I'd like to have a combination of the wireless mics and go over to shotgun back and forward. I'll think about that. Maybe I'll connect the wireless directly here and have a shotgun there and just switch. Because there's a sound mixer. I can choose the audio inputs and I can put people on hold. And then they watch this video right now while I'm on hold and I put them back. So that's what I've been doing here at the Embedded World. I've been wanting to livestream for a long time. But thinking of the funny way to do it, this is a cool way to do it. Otherwise I might get the play computer smart glass as soon as you release them. I'm joking. That would be great. Maybe I'll get the smart glass to see the live chat in my face. It's one of the plans I have also. And looking forward to EFA. EFA 2022 is not going to be cancelled. I've decided already. Olaf Scholz told me everything is going to stay open. The rest of the year, even CES is going to be normal CES and you won't need to get special medical treatment to attend. That's what I've heard. I mean, I'm joking. I have no idea. I wish I could have gone to SID Display Week. You went there and I'm very jealous.  I should maybe try to see if I can edit something. You can have them. Big less. All right. Cool. All the best. Thanks a lot. Thanks for showing my equipment. No worries. I needed to do that. That's so cool.


What's going on everyone Sam here with late in sports guard German 22 23 tops you apha club competitions Merlin chrome soccer hobby six box break number 13 random team style Here's a look again at your random results as always you can find those on the websites under the results tab as well as the link in chat Good luck everybody again. We are down to just 14 spots on Bowman chrome sapphire Jeff. Thank you again 14 to go. Let's get it filled up And that's 22 Bowman chrome sapphire. Raj Garyas Has his first in there. You've got Christian Mckarrow with his first in there a couple other big names as well Matt McClain who's in the MLB right now Rainden Cohn, Daniel Quavo, Anthony Gutierrez, Juan Benchow Ricardo Cabrera Samuel Zavala, Samuel Munoz. A lot of other big names That is a Rooney Bargey refractor rookie Coban Hagan under 21 Nuno Mendes PSG At a Saints remain Antonio Silva nice one there to 75 on the under 21 blue rookie for Benfica Benfica this Yeah, sure Refractor Chavi Simons for PSV Einhoven Merlin Masters Frank Ricard. Just a base pack there a under 21 Antonio Nusa for Club Rouge Chavi Simons Einhoven under 21 PSV Get a Merlin Vintage Osemane D'Ambele for Barcelona nice one. I like the vintage Merlin You top-loaded for Kyle up for this on Thursday, right? Yeah, Mohammed Kudus for IX Yeah, that's true forgot about that That's very true Pedro Gonzales for sporting to 150 nice one there Holland base Pink Mojo Gabriel Martinelli to 275 going to Arsenal. Nice one there Arsenal Lucas Gorna duet for Salzburg refractor Refractor Merlin master Makayla Moudric Jonathan said what's up by the way? Oh, what up John her non Crispo for ages alchemy. I think I think I see you see it Seem you say it or we're a commercial Tour a auto Harry Kane to 150 for Tottenham. Congrats. Tottenham. There you go. Hot spurs Eric W with two spots in I'm at collegiate very nice. Thank you Timberburn Refractor Antoine Griezmann for Atlético the Madrid Bruyne and Lorenzo Pellegrini for as Roma refractor pretty solid box right there nice Harry Kane Just transferred to Barnacle head Barnacle man Pedri refractor at least I'm not a barnacle head Invisible mobile Exactly William Saliba refractor for Arsenal The dirty bubble man Ray That's Benjamin Sesco for Salzburg dropped your wallet Yep Matias Suley for Juventus vintage Merlin rookie Mateo Cancelieri for Lazio refractor rookie Nice green shimmer Erling Holland 350 grats there man city Chavi Simons for PSV white speckle Desiree do it for Renee to 150 refractor Mario Gila Lazio Gavi got ages alchemy at Dennis Bergkamp as a Merlin masters a Robert Lavandoski messy a Vinnie junior Merlin masters That is a Rooney Bargy 11 and 99 for Copenhagen on the auto grant. Why great auto so far Nice Rooney Bargy stupidly young a Matias Suley who meant this rookie Refractor Pedro Gonzales sporting nice. That's gonna be Takumi Minamino for Monaco 48 to 50 true gold Grats Monaco on that one Refractor Jack relish going to man city Refractor Benjamin Sesco for Salzburg under 21 Fabio Moretti who got this blue shimmer to 75 Bettina going to Olympic Olympic hung in Sun for Tottenham Hotspur Fracture Schmerlin masters Pauli de Bala face pack right there that floated Usman Dembele for Barcelona refractor Lavandoski Brille and Bolo for Monaco refractor Roger van Dijk nice What is this? Fireworks Keeping that Paul Vaughn we can make that into something what Cole Palmer under 21. Hello Shelby, right Shelby Timmy Yeah, it's random to all there's a a Franzi Perio for Mockaby Haifa. Hi Shelby Aurelian Chau Mani for rheometry What yeah gaming's gaming's live There's a green Sadio Mani to 99 Firemanic Anthony refractor so he went to the gaming shop. Yes, I had to bring a top loader to Caleb Mateo You and dozee for Olympic to 299. Oh Gotcha. Gotcha. Gotcha. It probably was supposed to be a card Doug That probably was supposed to be some sort of card Caca in Central Merlin masters Harry Kane Refractor Otto Jota going to Celtic Nice one there. Whoa Luckily, I didn't replace the auto. That's what I was a little worried of Jeff C. Pick it up the a's sold out all the way up until Bowman chrome sapphire, so thank you there Jeff pick it up the a's we've got again 14 to go Let's get that sold out guys 14 to go Then we got to work on some of our later breaks and T You know breaks like that as well on the next you sleeve in top It's actually stupidly enough, but we'll keep it over here Yeah, that's a sonar True sonar Gaby Fireworks There you go Yeah, I can just blow it up Gaby Luka Romero for Lazio under 21 Anthony on the atomic the 250 for man United Sadio money refractor and zoa Fernandez Rookie Merlin masters got a green mojo Mohammed Dharami for Copa Hagan to 99 nice one there Refractor Jared Bowen West Ham Alex Lowry Rangers FC I know. Oh my god so close vintage Merlin Nicola Gonzalez for Fiorentina. I'm so excited for that dude We have I think preseason is on all today Zero in immobile Should be we got a red to ten zero immobili One of ten for Lazio nice one there red lime green shimmer Nicola Gonzalez Fiorentina to the 350 Oh Riley, I got a primary I think it's this is NFL Network, right? Yeah, it should be showing NFL football. That's a little annoying. Oh It's not a ESPN. Maybe Pavel Nedved That's probably just a Replay game Kevin de Bruyne. Oh, yeah, we're spring game. Yeah Romelo Lukaku refractor Forthole Mojo Otto nice art a goulash to 99 Go in a fennel Congrats on that Sean M a big hit right there the biggest rookie in this entire class 39 of 99 are a goulash Show for show Pablo Torre refractor Rookie for Bartholona, how'd you say that Bartholona? Yeah. Oh, there we go. No, it's on. We don't like such it Oh, cool. Oh, maybe it's not on NFL Network because we get it Since we get it's the dolphins and then probably after this it will they will show it if it's not a Florida team Hopefully they're got bears in some of them. Yeah, so that should be that should be on a bank. Here's thing getting rocked Uh, Takafusa Kubo for Sociedad 350 Refractor is Sound Goto Magasa for Monaco Surround's not looking great. No, Anthony. So me and my buddy We finally got our Jags Texans tickets. Oh nice. Nice. We count for like 30 bucks. Wow. That's awesome. Andrea Schlitter up under 21 And they're like actually pretty good. Are they really? Refractor of Jude Bellingham Dorpon like I'm low key happy. We didn't buy him as soon as the schedule was released Benjamin Sesco Salisbury. That's probably I was smart. I'm sure Vintage Merlin is Jude Bellingham for Dorpon. Kyle try to do the Tesco, but it didn't work It doesn't work. Amine Gouda refractor rookie Got a green, Bukalaya Saka for Arsenal to 99. It is a Teal Lorenzo Pellegrini to 199. Did you bring food or no? Dehan Kuleshevsky for Tottenham. I wouldn't be opposed as always. Mosala Dennis Bergkamp HS Alchemy That was a huge error card to find out what it was supposed to be. Honestly though, Doug Alex Lowry for Rangers. Nice refractor rookie otter there. Actually, they had a checklist for Eric. Yeah, right Be boddish Mark Casado refractor rookie at Barcelona Just do some block of itch for who bent this that's back here is under 21 Mateus Suley for this as well I'm just gonna Taco Bell or something if you wanted to get throw something in there saying dude again guys 14 to go on Bowman Chrome Saphir and I'm a team stele Andrea Schlutter up than Fika. He's probably done. What is it? But yeah, he'll be done for sure. I'll probably pay like one or two drives Alessandro Bastoni to 299 rose gold shimmer. I think I don't know what the chiefs played yet, but the Holmes and the starters are supposed to play at least one Yeah, simulating junior rookie refractor. That's what I saw that too I think you told me that or we saw that together or something. Maybe Anthony on Merlin Masters Hey, well, your box course Renaissance Ronaldo for international Milano R9 congrats on that one there Milano. That is gonna be Where's Milano at? No, no, that is inter Milan Josh H. Desiree.  Yeah, that's what I noticed as well Pablo barrios It does the Renaissance are cool. I like the Renaissance Pimo Verner Matias Sule Francisco Conuchow for IX We'll get an orange Orange shimmer Matteo Canceleri for Lazio nice one there to 25. That's Lazio very nice very nice very nice Refractor Makaylo Moudric for Chelsea. Mr. Messi and Matteo Guendosi for Olympic Moussala. That is a Nikola Zoleski for Roma to 275 pink mojo Auto Tiago Alcantra Liverpool nice one there the refractor auto very nice Marcel De Salle H. Salkmé and last pack These mom and Evan goisant for knots Quick recap here everybody We had Some color to 99 greens Makaylo Saka Mojave daughter me Saudi Oman a blue to 75 patina and Antonio Silva under 21 rookie Goal to kumi at Minamino for Monaco Matteo Canceleri to 25 for Lazio. We had it zero Immobilia for Lazio as well to 10 on the red autos. We had Tiago Alcantra Alex Lowry Jota Harry Kane 150 a Rudy Bargi to 99 We had a Ronaldo R9 Renaissance case it and Arta Goulash to 99 for Fener I'll do it for the break guys. Thanks again for the film up next is the next


Bio-based polymers have been gaining popularity due to their potential applications in place of traditional polymers. In particular, they can be used in electrochemical devices, where the electrolyte is a key component in determining the device's performance. Collagen has been identified as a promising material for use as a polymeric matrix for the development of gel electrolytes. This study evaluated two types of collagen membranes, uncross-linked and physically cross-linked to determine their suitability for use as an electrolyte in electrochromic devices. The membranes were tested for their stability in water and aqueous electrolyte solutions as well as their mechanical properties. The results indicated that the cross-linked membrane had better water absorption capabilities and greater resistance than the uncross-linked membrane. Additionally, the cross-linked membrane exhibited improved optical characteristics and higher ionic conductivity when immersed in sulfuric acid solution. These findings suggest that the cross-linked collagen membrane may be suitable for use as a bio-based electrolyte in electrochromic devices. This article was authored by Carmella Tanya-Prontra, Nunzia Gallo, Roberto Tinuzzi, and others. We are article.tv. Links in the description below.


Hi everyone Joe for jazby's casewrakes.com coming at you with a multi-team random number block randomizer That'll unlock pick your team attribute pick your team for here's how It works Remember the non numbered base cards will be randomized as one big lot to one person in this number block We're also giving away a couple extra spots right there So there'll be two different dice rolls here first one will be for the two extra spots were given away So Andrew you officially get last spot mojo star next to your name And then the second dice will be randomizing the full set of names and the numbers Let's give away a couple spots here So the first dice roll is three times top two after three extra spots little buy one get one action one two and three good luck There you go. Johann Jeremy After three times Couple extra spots for you now. Let's gather all of your names put them into this list here and Let's roll it randomize names and numbers five into two seven times one two three four five six and Seventh and final time we've got ariano down to jerry five into two seven times for the numbers one two three four five Six and seven and final time good luck one down to seven now Remember zero gets any and all redemptions for that big group of teams and that tab down here including one of one redemptions One of course still gets live one of ones All right, so ariano with number one Ryan with six yohana with eight Andrew with four yohan with two Anthony with five Jeremy with nine ariano is zero Simon with three Jeremy with seven It's order these numerically and coming up in a separate video in the next video will be that tribute break We'll see you for that jazby's case breaks calm


And President Baalachinibu has written the National Assembly for the approval of $800 million loan to support poor and vulnerable Nigerians in coping with their basic needs. Reading Tinibu's letter during plenary, President of the Senate Gotswilakwabiu said the loan is for National Social Safety Net, Winder of the federal government. According to the request, the World Bank facility will aid federal government to make unconditional cash transfer of 8,000 Naira per month to 10 million poor and low-income households for a period of six months with a multiplier effect on about 60 million individuals. Request for approval of additional financing of the National Social Safety Net program have proved an additional loan facility to the tune of USD, not 800 million, to be secured from the World Bank for the National Social Safety Net program. You may also wish to note that the purpose of the facility is to expand coverage of shock-responsive safety net support for the poor and vulnerable Nigerians and to help them cope with the cost of meeting basic needs.


Thank you. So what I'm going to talk about today is the work I've been doing for the last two and a half years and actually a little bit beforehand I was doing this at NHGRI2 which is related to the data commons. So I'm going to walk through the pieces that sort of led to why we wanted to do this, the structure that we're actually using and what you will see further this afternoon from Valentino de Francesco and Ken Wiley about how that's being built based on some of the conversations we've had. And I'll describe a little bit about how we're working across these other genomic data, well, there's genomic data commons, but further than that they're beyond genomics data that exist outside of NIH but are often run by NIH researchers. Also a little bit about the work that's going on inside NIH which is relevant to the conversation you'll have this afternoon about the sandbox because there are multiple commons going on and clearly there will be questions around how we actually interoperate. So I'll try and cover all of those pieces. So let's look first at what's driving the need for the data commons. So I think it comes down to a number of factors and I think you heard that from Eric Green this morning in some of his director's report. There's a collection of things. The first one's obvious which is the mountains of data. All of you are probably dealing with that already at the moment, but it's changing the way we're thinking about data in a number of different ways. First of all it's changing the fact that we now have to really pay attention to the way that we're actually going to handle some of the computational aspects of it. It's also driving the way we're trying to do discovery and I'll give a little bit of an example of that in a minute. There's also an increasing need and also support for data sharing. Again Eric pointed to some of the genomic data sharing policies but I'll speak a little bit more about that as well. And also the emerging concept of fair which is findable, accessible, interoperable and reproducible. These principles allow you to make sense of some of the data so at least when you've got two different data sets you can start asking questions between them in some common ways. And I think a critical factor which has also come up in some discussions is the availability of digital technologies and infrastructures that support the data at scale. And the most obvious one at the moment is the cloud which has come up in multiple conversations. This has come up in the form of clouds that exist within institutions themselves but also in terms of commercial clouds and the most obvious ones that most people are aware of is AWS, Amazon, Google and Azure which is Microsoft's. They're playing an increasing role in this particular field and it's these three four factors that we're actually going to look at. So the first one is I was looking at the mountains of data. So we all know we're generating a lot of data and we also have computational needs but it's also driving the way we're doing science. It's this multiplicity of data and it's the volume of it that we want to be able to search through and across that's allowing us to ask important questions. So we need the infrastructures to support this so that we can ask these questions. And what we're seeing a lot in the work here is this is an example in cancer where you're starting to get these kinds of headlines which are coming out are incredibly important. So it's really data driven discovery that we're looking at. In addition, I mentioned the issues around the need and the want for data sharing. So a couple of things have happened. This is the memorandum that came out from the White House, from the Office of Science and Technology and Policy looking at really the issue of we need to share more of our data, especially because we know it's digital data. And this has changed the way that funding agencies have looked at data and are considering how it should be shared and why. And that's impacting all agencies across the United States. Obviously NIH is one of them but I've had multiple conversations with other US government agencies and I'll speak about that in a little while. This is a note as a Holdren Memo came out in 2013 and essentially it's really saying ensuring that we have open and shareable digital data. We're also looking at the genomic data sharing policy as an example of what we're looking at and improving sharing of data. So here are just some examples to go to that. Again, Eric Green was talking about that this morning but it's really looking at requiring public sharing of genomic data sets. And I think at NIH, certainly for grants over 500K, there's an open, there's a data sharing policy but we're looking at how do we extend that, what's the right way to think about data sharing that we should include in what we're doing on an everyday basis. So that's one of the other factors that come in. The fair content, what I was just talking about before, which is the findable, accessible, interoperable and reproducible. This is starting to gain steam in the communities and I think we're starting to see papers like this which are the foundational ones looking at how we actually need to think about this concept. So in the future when we have data at scale, how do we actually analyse it? How do we use it? How do we interoperate with it? These are the founding principles that I think are really essential to the commons. It's not just a compute infrastructure. It's what do you do with the data and how do you handle that? I guess one of the good examples here is many of the projects that include metadata don't necessarily include standards or issues around that to make it more useful and I think what we're finding in the future is common standards for metadata are really important and we need to adopt those and we need to push these through the communities. This is part of the fair process, just an example of what we have. So now touching towards the kind of things that we see in terms of technologies that support this, we see headlines like this and we've seen examples where Google, Amazon and Microsoft are impacting the way that we do biomedical science and they're involved in a number of different areas. I've just got a couple here, but you can see how these are involved. In particular, they're heavily involved with a lot of the NCI work because of the genomic data commons there and simply the volume of data cannot be stored locally nor can it be used. So this is one of the key reasons why they were wanting to use those commercial systems. So all of these factors come together to think about what do we really need to do moving forward? They're all important, but we need to have some sort of cohesive strategy around that and I think this has been a common discussion that I've seen at NEH. What do we do to bring these pieces all together? So the data commons in my mind is really enabling the data driven science. It's really the idea is that you want to enable investigators to leverage all possible data and tools to really accelerate biomedical discoveries, therapies, etc. And importantly, you want to have the data infrastructure and the data science capabilities that workers are collective to do this. So how do we think about doing that? And that's what I'm going to cover next. So I think up until now, these are all the shaping principles that have helped think about this. And now we're actually taking the direction of how do we actually do something about it? So we think about the data commons as something that treats the products of research, whatever that is, that's data methods, papers, anything is a digital object, it doesn't matter what it is, it's digital. And we want to be able to do something with those digital objects in a shared virtual space. Here are just some examples I've got up here of the things that you can do these seem obvious. But I think it's important to state that we want to do these things. And as you can see, they're starting to move towards the idea of using fair principles, which is the other thing we want. You want the commons to be able to work on these objects using fair principles, which is findable, accessible, and usable. If you can access it, it doesn't mean it's necessarily usable. You want it to be able to interoperate, and you want to be able to reuse it. So an example here would be you have some data that's large, you want to be able to find that you want to be able to share with somebody else that can actually use that they need to interoperate with it for their experiment. And they need to be able to reuse that in such a way they don't have to recreate the wheel or generate the data again. It's relatively cheap to generate certain data sets again. But the compute right now is still fairly expensive in these kind of infrastructures. So what we want to do is promote that kind of process. So I think of the commons as a platform that allows transactions to occur on fair data at scale. And I'm going to focus at the at scale part today. The reason for that is because many of the in the context of NIH, there are many very large data sets that we deal with. And it's very difficult for us to be able to operate on those at scale. They either sit at repositories, or they sit at local institutions, which is terrific. But it's often extremely difficult to operate on those data sets within those environments, which is why people are moving towards the cloud. It's you can move the data set there operate on top of it. And often you can compute against it quite cheaply. Storage is different, but people are doing that. It's a common use case that I see amongst NIH researchers. So what we're trying to look at is if you think about a commons for data at scale, how do we incorporate that in our project? So what I've been working on for the last 18 months is a platform, essentially, structure of it. It's in three parts. You have a platform which is compute, and you obviously need that because you're going to need data at scale to operate on. You have data. And you have what I call reference data sets. These are mature data sets that have been out there that have been cleaned and polished and ready for use by the community. And you also have user defined data sets, which are often smaller, potentially not as clean, but definitely useful, and definitely usable. And you also have an ability, you want to actually able to operate over the top of that using services and tools. So essentially have a compute layer. You have a data layer. And you also have a services layer. And the most common one that certainly NIH has seen is a scientific analysis tools area. We fund a lot of those kind of things. But a key area is also the services component, which is these APIs that allow interoperability between the data and allow you to also act as transactions between computes on various systems. Indexing is also really important. If you think about this and we have a whole lot of data in various places, not just the cloud, you need to be able to find it. So we need to think about those things. They're essential parts of the system, but they're often not the kind of things that we fund, simply because they're not directly involved in solving a scientific issue. But they're essential in the transactional analysis that need to occur at scale when using fair data at scale. The other thing we need to consider thinking about on the top layer here is what I call an app store user interface or a portal haven't really quite thought of what the right term is. App stores are easiest for most folks that don't deal in computational biology because you know when you've got an app just works and it connects magically. And that literally works on a platform. And if you think about platforms like Airbnb and Uber, which most of you have used, they work on the same very same principles as here. So what we need to do is create interfaces for our biologists that don't have the computational experience to be able to access this information quickly and readily efficiently and correctly. So if you want more information about this, there's a link here at the bottom, feel free to go do that. Just a quick comment about the left-hand side of the slide. For those folks doing more computational work, the cloud is seen as the infrastructure as a service, which is the IAAS. And the platforms as a service which allow you to interact with these systems are platforms as a service, P-A-A-S, and software as a service which on the top line is here is allowing you to have software over the entire stack to be able to operate. And we've seen examples in the commercial world of SAS applications. In the genomics world, I think you see seven bridges, genomics and DNA nexus are two examples of what you see in this particular environment. Those SAS components are where biologists interact most readily with the system that have low computational knowledge. But it does not mean that we shouldn't be looking at the other pieces in place. There are also examples both in the commercial and in the academic space at the PASS level. For example, Broad's Fire Cloud fits into that category as well for PASS. So I think when you're looking at the IT stack, this is the kind of things that we see in the industry, that's the way they talk about it. And we see examples within the biomedical industry that are populating this space. I think it's really critical for NIH to understand how this operates and to be aware of this terminology as it impacts biomedical sciences. On the right hand side of this diagram, I talk about digital object compliance. Essentially, I'm talking about being fair. How do we actually make this whole thing fair? And these are the conversations we're having at the moment. This next side is complex, but I'll try and walk through it as best as I can. This is digging down into the architecture and I just want to shout out that this is the work I've been doing with Alistair Thompson and Kishel Jekish and Wayne Ogan over at NHLBI. They are also building a commons and it's built on this structure as well. Simply drilled down of the previous diagram I gave you and Valentina Dufresco and Ken Wiley are actually going to be looking at this diagram as well. I want to point out just a couple of things here. The green layer is at the bottom is the compute and all I've done here is broken out a couple of pieces. The type of storage you need will be whether it's close nearline storage or offline storage depending on where you want your data to be. I'm not going to go into a lot of detail here. Just trying to show you that we're looking at the architectures that need to support this. We can go through that in question time where I can take this offline. The key point here too is that we want to look at cost tracking and management. Many times when you use commercial clouds the costs are quite prohibitive for research scientists, especially at the storage layer. And so what we need to know is what are we spending our money on and for what and what's the right way to do it. Researchers cannot support terabytes or petabytes of data on commercial clouds using their grants. They have to do this through another way and what we need to do in NIH is to figure out what are the right places to look at what's the cost and what's the right way to do this. The data layer I spoke about before, you obviously have data in this system. We need to look at the security data access rules. We're going to deal with a lot of human data. So we have to be careful about what the security access points are. And there's a lot of discussion around the right way to handle interactions with dbGaP. And what are the right ways to do this in the future now and also in the future. I just want to point that out because human data is really obviously important to the nature of what we do. Fair data access is the same as the previous one, which is literally the service layer, which is critically important. I just want to highlight it again because it's the boring part, but it's the necessary part to make this work. Now let's get to the point about the staging, the sandboxes and the workspaces. People have slightly different views about what this means. But in my mind, there are two parts. When you generate a project, especially in a project like encode, which is something an HGIS funded, there's a period of time where that data is not in its clean state, final mature state. It needs a lot of work. You need the researchers to be able to work with each other to clean that data up. I had experiences dealing with the human microbiome data for the same reason. You have multiple sequencing centres, you have multiple scientists. What you want is a sandbox, a scratch space for those collaborators to work together to make sure that they can pull that data together so that it's mature and ready for the community to use at large. So you want that. You also want researcher workspaces so that they can actually collaborate inside these environments. That is one of the benefits of the cloud. You can create these collaborations and it's not limited by geography. So these are the pieces I just want to point out here. My colleagues, Valentina DiFrancisco and Ken Wiley will speak about this later today with the sandbox for NHGRI. Over the top of that, there are the user interfaces in the portals. I mentioned about those briefly before, but this is just simply a drill down stack of what I was saying before. And this is consistent about what I'm seeing and what the sandbox has been developing. And also there are other data commons. And this is a question that I get asked as well. So I've been working closely with the genomic data commons at NCI. Also the Fred Hutch Center, which is looking at the Hutch Commonwealth. NAID developed what's called NFALY and this was essentially, again, a commons, an early commons over human microbiome data. This is work that I did with them and actually I was part of NHGRI. So this is an early form of a platform commons. But we're also seeing the New York Genome Center is also developing its own commons and the UC Santa Cruz group of developing methods for actually deploying commons. These are key players in the field and I've talked to them extensively. The structure I've described here, if I can go back, is the structure these guys are using. So the reasons why that architecture I think is reasonable is because it's based on the conversations I've had both with industry and also research is about what's the right way to think about that. I will talk a little bit later about where I think NHGRI is to play in that infrastructure. I just want to touch on a few other data commons. So I mentioned the ones that are external to NIH, which are shown here on the left. But on the right we've got where we're going here internally at NIH. Clearly the commons is taking hold and we have the National Heart Lung and Blood Institute which is putting together a commons related around top med data. I've been working with them extensively on the structure of their commons and exactly what it would do and how it supports the use cases that it needs. Common Fund also has data sets I mentioned the Human Microbiome HMP project but I'm also working with the GTACS project which was mentioned earlier today and they also have some other very large data sets which are resources that the community wants to access. And lastly the National Human Genome Research Institute which is this group is essentially looking at the same thing and you'll hear far more detail about the kind of data sets and the systems they want to operate on this afternoon. Another thing to point out is that this kind of engagement doesn't happen just at the biomedical research level. All of these groups which are US government agencies shown here on the left under the slide are starting to actually contact me directly or indirectly mostly directly about the commons work what does it mean and how does it actually impact their agency because that's really it's agnostic of data the type of data the platform is still the same and so we're starting to engage in conversations around what does it mean to have a commons what does it mean for different organizations how that should be done and I think importantly they can bring perspectives that we don't necessarily see it's always good to get a different perspective additional work that I've been doing is with the European Commission there is an European Open Science Cloud which is using the CERN Cloud and I've been involved in some conversations around what's the right way to create relationships there and also Elixir which is a European based organization looking again at the fairness of data and looking at being shared across the EU they're very interested in a lot of the components that we've talked about in the commons and want to know what's the right way to create the right relationships can we interoperate so one of the conversations we had is could we actually run a service that runs on CERN but the data actually exists over here in the United States we've been having all of these conversations simply because we know this is going to come and researchers need to use these kinds of technologies so we want to find the right way to integrate and interrelate with the appropriate folks I'm going to finish up on this which is a busy slide which is the interoperability with other commons is I think the first thing is discussion we're really at the early days different people are doing commons is because they know they need to operate on fair data at scale they're all going to plan to use some form of cloud they have some level of security layer and there are services we all have the same problems so we need to get together and talk but we all have common goals which is to democratize and to enable collaboration and sharing of data that is consistent across all of them what we also realize is we don't want to reinvent the wheel so we want to look at reuse of currently available open source tools which support this interoperability and there are examples of this the global alliance which was raised again today the GA4GH UC Santa Cruz the genomic data commons the New York Genome Center all have tools which they're either using or want to use and realize that it makes no sense to reinvent the wheel so when you create these open standards amongst the groups you avoid some of the silos but we need to have those conversations so we're looking at planning right now a meeting of commons developers that are working key people in this field and also to bring NIH staff together because the commons as you saw from one of my previous slides NHGRI Common Fund NHLBI are talking about this but I'm hearing other work also being done inside NIH PMI follows very similar issues structures to the commons here so we also need to talk with NIH and their pieces planned we are looking at a session at BioIT which is a very large conference in the East Coast in Boston looking at actually having a commons session and we were approached about actually having a commons session there it's starting to reach that level where people are really asking us to participate the rest of the slide is looking at some of the more details around it but really I'm trying to get at we've got a lot of stuff that we've already built we should reuse it and not reinvent it and when we share that information and we reuse it we hopefully avoid some of these silos because we're starting to have the same conversations so if I'm using the same API to exchange my data and you're using the same API the chances are we're going to have some level of interoperability and that interoperability happens at a number of different levels this is what the rest of this is which is these open standard APIs to allow that transaction at the data and the computing level when you deploy across clouds one of the concerns has been each of the cloud providers works separately understandable but some of these groups I just mentioned have also been working on tools that allow you to actually interoperate amongst the three different cloud providers there are concerns understandably that simply using one cloud provider locks you into that understandably so so what we're looking at is how do you deploy across each one of those using open standards Docker which is the containerization actually preparing your tools for use in the cloud that's Docker creating a registry of these with IDs and a store so that people can actually find them and redeploy them that's an important aspect there's work that's going on within the commons and BD2K which we'd like to reuse there's workflow management when you do something in these environments it's not usually one tool it's a collection of tools that operate in synergy together to create what you want to do for your analysis and it's critical that we actually do the same for those kind of things to make sure that we have the right workflows that can be reused another one is discoverability this is about indexing if we do this with all these different data sets and we do reside in commercial clouds it would be really important that we can find all of our objects wherever they are so we have to find ways to do that there are efforts within BD2K to look at indexing but there are newer methods out there as well the Europeans have been looking at some methods for indexing well and we're discussing that as well so it's a collection of ways to do it the important point is we know we need it we don't yet know how to solve it globally unique identifiers really important that we all have a set of identifiers that we can agree to otherwise it'll be apples and oranges in comparisons so there's a lot of work being done in the GA4GH in this but also other areas but it's critical for the way we go forward so if you call something an apple I know that it's an apple because we've agreed on the same identifiers additional to this actually the last point is a common user identification system that is when you're using human data do you have authorization to use it? is it you? and are you allowed to use this data? this is what it means and we need to look at what's the right way to do that with one data set or across them I can see reasons for keeping them separate but at the same time you don't want to do 25 of these if you're going across a bunch of human data that's funded by NAH and lastly the NAH Commons working groups there are several of these and Valentina raised those some of them this morning they are made up of BT2K members Alexia members and also the broader research community outside of BT2K and they cover some of these areas which is Commons fairness metrics what exactly does it mean to be fair and what guidelines do you need to develop so that can be deployed by other people interoperable APIs what standards are we using how are we actually coding to that and what can actually affect Docker registries can you containerize your tool for use in the cloud can I know what it is and I know I can reuse it data object registries that are beyond tools can we actually identify those because that impacts the way we actually can index so these are the kinds of conversations that are going on right now at the sort of technical detail level to say how do we as commons interact with each other but we also know that we just simply need to get together and talk we know we have a lot of the pieces now it's time to actually sit down and work on a plan to ensure we can actually do that so lastly I have an acknowledgment slide because I really would like to thank all these people I won't go through them individually however my point here is that there's a lot of work being done here across a whole lot of different institutes this truly is trans-NIH and it's broader than that I've had a lot of discussions with industry and research scientists outside of NIH outside of the United States about how this could be done and should be done so a lot of these folks cover from different ICs and we're also working with Andrew Norris from the Center for Information Technology she is also the CIO of NIH so I think what we're trying to do this slide shows just how broadly we're actually reaching across NIH and that's important because this kind of thing impacts everybody and their ability to do science okay I'm done thank you very much and I'll take any questions Carol yeah so thanks Vivian for that overview so I think we all realize how transformational this kind of work is going to be for for biomedical science right so to be able to share data seamlessly so so these are all great things in the architecture you spell out it's good to know that some of the commons that are being developed are following sort of at least a common architecture framework but the seamlessness of this whole thing lies in the details and so I know there's a lot of discussions going on but are there so I have two questions one are there specific agreements that have been made in those discussions to sort of enable the seamlessness across different cloud based commons resources and in the architecture and I think this is really important you talked about mature data so even mature data are changing and the example I think of very often because it affects me directly is genome assembly updates version changes which then lead to different annotations in that genome assembly will then propagate through this architecture and affect every single layer of it and I'm wondering if those discussions have been had as well about how to accommodate that kind of fundamental change and the ripple effects through the stack of this architecture that's been defined so let me see your first question was about agreements between the groups and the second one was about version control and change is that right okay so first one about agreements no agreement has been made what has happened is that everyone who's developing this knows we need to speak uh... so this is why we want to bring everyone together to get to a point of agreements but a lot of the work has been done already the g a four g h has done a lot of the work here one of the key things that we all agree on so far is let's not reinvent the wheel so we want to see what's already out there what do we need to reuse and then to come to an agreement what that is and communicate that so that if others come along we say here is what we used in why so that's where we've got so far with agreement in terms of version I didn't get into here because that's just not enough time absolutely versioning comes at exactly what you've described and also versioning comes in how do you do that across clouds so it happens at a number of different layers we definitely expect to see that let me just distinguish the datasets that i would call that in the early stages which they're often uh... very early parts of a project undergo tremendous types of change which is sometimes different to the more mature ones still change on both sides but i think what we want with the early stage datasets is to have a shared space where people can simply work on their own it's not for the broader community yet it won't make sense to them there are also issues around the use of that data for the versioning for the more what i call mature datasets absolutely i do not see them as static but the discussions have been around how do you ensure that the versioning is correctly done how do you ensure the versioning happens seamlessly across those clouds and is there a point where you don't necessarily need to store them when do you no longer version them that kind of conversation is happening not finalized yet but the good questions one of the issues that comes up all the time or seems to come up all the time in developing these very very large data resources is the business of privacy uh... of security and of sanctions against individuals who misuse the data uh... can you comment a little bit on on what you know how you would see uh... a structure that would would uh... would allow would guarantee to participants other research participants or researchers uh... maximizing security and at the same time figuring out a way to slap hands or worse of people who abuse the system so here christians being security and policing so sank sanctions which is a word uh... two s words so as far as security goes yes something we're really looking at which is one of the reasons i showed the architecture slide which is we're paying a lot of attention to how do you actually access this data in the appropriate way so how do i know what you're you and how do i know that you are permitted to use that data and for how long so one of the things the how long part is important right if you've been allowed to use it for a period of time it'd be nice to know that at a certain end of time you're not allowed to use it anymore all the uses ended or whatever ways to do that we're looking at ways that we can do that with machine-readable files how can i know that and let the system work through that way that's a technology piece but i think there's a bigger issue here also around consent which is sort of part of what you're describing particularly when you're going across data sets how do i know that the right consent was set up to use two data sets when they were never designed to be used like that in the first place which is why the conversations are not happening just at the technology layer for the security level api they're also occurring at this is why i have denapal 2 and the crew over at the office of science policy what are the right policies we need in place when we're starting to look at the and dealing with the issues of consent and how does that impact the way we develop the technology those conversations are underway in terms of the sanctions i'd say we know less about that but it's important to do what i will say though is once we can actually track the use of this data if somebody's actually booked it and using it we can electronically tag it there are some ways there we can actually look at this in ways we couldn't do that before what's the right way to balance that so i know that you've got the data for a period of time you're allowed to use it for so long i can actually look at in the track logs how can i use that to help figure out what the right sanctioning is not necessarily against you but should you need that i mean there will be people who will go into these data sets and say oh you know this is eric greens genome and look he has x and and that that will happen i it's a real snoozer i'm telling you right now go ahead try and then gal yes so first of all thanks for the presentation i think we all support the notion of the commons and it's clear that what you've presented is very well-designed and and thought out i wanted to ask a question that maybe is is related to dance but the flip side about openness and data access so uh... and and what's become very i think uh... clear to many of us who have benefited from the the general access one now has to genomic another molecular data in part pioneered by this institute over the past ten years and in terms of requiring people to deposit data uh... in the public domain in the timely fashion no subject to publication uh... requirements like that that the same culture does not exist at the clinical data level so so one thing is certainly one needs to worry about privacy uh... however i think that there was a separate issue which is simply culture and and uh... it's it's become painfully clear to some of us that when one tries to relate as one tries to relate these different genomic and and and molecular features the different clinical outcomes that it's it's simply been harder to get a hold of of those those outcomes that kind of data and it isn't just an issue of privacy and making sure that the patients are protected i think it runs beyond that to just a culture and i'm wondering if clearly for the commons overall to be successful you want people to be able to access freely once you're in inside of that firewall however it is you you define it you want people to be able to leverage different data sets from all sorts of of tronches genomic molecular uh... and and and you know metadata and and clinical if that's indeed a separate object so what you hear is issues of clinical data and also the culture changes needed exactly okay so let's take the first one clinical data one of the reasons i included here uh... the clinical center is because i do two things the clinical center has been very active in discussions around how do they participate in a commons so there's a couple of i spent about almost a year working with them on which data sets we could actually use because they are bound by very strong legal issues for the office reasons and what we did was identified some data sets that could potentially move into this commons environment there are some leaders within the uh... clinical center really trying to look at this we've identified some data sets that we'd like to try as being part of a commons set uh... for a couple reasons they're the right data sets to look at uh... they're very important and it also breaks some of that culture issue so we know it's going to do both of those so the clinical center is very important on that i've also been given the honor to be on the clinical center steering committee they've asked me to act on that because they want more of this in their environment so that's actually going to that this weekend kicking off in terms of the culture that's harder but i think what you need is folks that are going to be leaders in this field taking it and running with it example of clinical center and what we see with the pios out there and also some of the commercial companies that see it as a value add to their business but are also willing to have a conversation beyond that there's another culture change that needs to happen and that is at the data and tool level i'm sure you've been involved in this the publication is still the currency of what we do and yet what we don't make is data the currency of what we do and that's where we need to go doesn't exclude the paper it makes it as important but if i can actually go if a researcher can actually uh... presenter an application to any age that has collection of data and tools with potentially do i is associated to this as part of the application process and review process it also changes the culture what we do and the comments i think we'll start moving towards those kind of issues we can cite data for those very reasons those are the kinds of things that have to change within the context of any age and that can only come from us also testing these systems to try and change the way that we handle culture i hope that helps a little bit yeah uh... i too uh... was fascinated and a little bit overwhelmed by your task but a couple things really struck me and and these it's really sort of the nosology of what you're doing with regard to uh... that the words that are being used basically with regard to this new vision uh... or maybe not so new but it is a uh... a vision for the future and what one is common which has a long history in law and ethics uh... and which can be thought of as being as you said very democratizing like what is our comments really as as people in the u.s. as humans etc and the other is fair or fair and they've got this wonderful acronym which i kept thinking meant fair and i think that it it could but it but when i looked at what f a i are beans it's it's not equitable as much as it is making uh... i think maybe making access and and finding things and so on more broad uh... but not necessarily fair in in a kind of uh... ethical sense so it just made me wonder about and in this i'm awfully glad that two questions that came before me actually did come before me because it's set up you know you've already responded questions about privacy and security and also the culture or a culture change and uh... and i'm wondering uh... especially when i'm thinking about uh... who has access for how long and some of the things that have been written previously which may now seem almost pedestrian about by the rise of biobanks and the need to really create new standards for people put stuff into a bank who may need access later etc etc that you've got this uh... you know so who are the community that you're talking about is it researchers or if we think about the vision and uh... kind of uh... p r maybe about uh... the precision medicine initiative it's highly democratized it's access to data on the part of a number of different groups not just people who would be putting data into the this cloud right it's it's much much broader than that so i i feel like there's a number of really important sort of ethical and legal issues that this vision generates that uh... you know i i know i'm sure you have lots of thoughts about uh... and i'm sure people have asked you about that already so i wonder if you have a couple of comments to this broad-ranging set of questions the first one was you're so good at that i'm just trying to get my own head around it one was i probably summarize it by saying whether you said nomenclature or nomenclature whether it's potato or potato okay there's a lot of issues around terminology and we haven't settled on a lot of stuff so whether you call it nomenclature or nomenclature i think we need to come to a versioning of what is useful that people agree to there's the commonwealth the commons right then there's the tragedy of the commons there's all sorts of other things here so words have meaning and which is really important so the etymology this is really careful for us i have no issue with moving it to something else i want the community to have a conversation so that they're comfortable with a set of terms that we can live with whatever that is so and when you have this conversation with the community uh... this touches your second question it's not just about what important api do i need and what's the right work for language and if i used a jason object which is all the technology side that's great but if we don't address the social political reasons behind this and also the lc issues raised i think it's really not a good thing so i have done a lot to work with uh... the office of science policy because i know it's critical to what we do and i'll give you an example of that so a couple years ago the policy for dbgap did not permit us to use the data in the cloud and a lot of researchers were having many concerns about this i could see that researchers were doing it but the policy folks didn't know much about the cloud so you had a schism essentially between the technology people and the researchers who are wanting to do this and yet our policies in a h precluded us this is where technology was a head policies and so myself and a group of people work closely together to change that so you know how to move dbgap data to the club for a period of time but now you're permitted to do this so there's an example we have to work because the technology is changing so rapidly you must work with the folks in policy and lc i do this together to ensure that that moves at the same pace and there are times where they need to be educated in the technology but there are plenty of times where we need to be educated in the lc aspects policy particularly because we're dealing with human subjects and when you're starting to traverse different datasets there are going to be issues there that could preclude us not technology-wise but simply because of the way that we're dealing with very sensitive data so i think it's really critical that from the beginning we include these conversations at that level immediately and ensure that we have a discussion around those things from the start not at the end well just relevant to that i think it would be helpful if your group also thought about developing educational or templated materials for consent many of us still use i think outdated language about the data being on a specific network and things like that and i think part of the reason you're getting a lot of these questions your answers are very reassuring the slides actually talked a lot about public sharing and things that i think give less of the impression of the security of the data uh... and so i do think that that aspect of it is very important because most of the people in these studies have not contented the public sharing of their data that's a really good point you can show what you can see where i come from when i look at that structure at the api for the security labor is critical as is the policy pieces but you're making a good point which is to call it out in language inside the slides will be confusing to people you also may know the critical point which is training this is not included here but it's essential we need to include those folks that don't come from these kind of backgrounds to help us with some of the use cases uh... to be part of it and also to provide training outwards so people know how to use the system i just didn't include it here but it's critical i want to point out that training actually has two components there's training of what we usually think of as users of a workspace such as say data analysts but there is also a complete it there will be a a substantial training required for method developers for software engineers in the context of bioinformatics computational biology because a lot of them have been trained historically in very different software paradigms and have not really picked up some of these newer things not that they're incapable of picking them up but you need to find kind of the space for that to happen and so for example thinking in the slightly longer term of about say administrative supplements to encourage which i think the NCI cloud pilots did that if you had an NCI grant to develop some software you could apply for a relatively modest administrative supplement to really push your thing to become dockerized or to interact with data that was in workspaces for that were handled by the NCI cloud pilot and i do know that in ITCR which is an NCI program that supports a lot of software that handles cancer data people really took benefit of that opportunity and it served to train the software engineers which is a very different community than the users I 100% agree and I would say that previous slide here I'll leave it at that what we were talking about before is exactly that is the training of the users, the traditional users that we think of but ensuring that we use open standards around that and documenting that so that people know how to reuse it it's very common as I'm sure you know that we'll all write our own API if you just can't understand the documentation you'll redo it and then no one else can reuse that that's actually a problem so we need to ensure we have that writing the documentation and so on is one component of the training but there has to be some additional incentivation to really push people in there's a little bit of pull and a little bit of push and so a lot of the interaction around this at least from my limited experience does require you to have more than the documentation especially at the early phases of a lot of these data platforms which are not neither none of which is fully mature and they're really a work in progress in different phases of progress presumably across these many different entities and so you need real effort and by that I mean like person's effort like portions of FTEs on both the commons developers side and the incomeers with whatever things they're docker rising making compatible and so on and that needs that needs real incentive and real resources it's not just going to all happen on its own so to comment the Carol was saying which is about agreements although we haven't reached agreements there's a discussion around if we are going to reuse this what's the right way to teach each other what the right way to do it is so we document that and then teach each other and then teach the community that is definitely something on discussion I was wondering if you could say something about whether this will lock the community into using one of the cloud computing providers and course in general you know establishing monopolies is bad because it makes things more expensive and less good and you can comment on that. Yeah it's a double-edged sword so there are some groups thinking of just using one cloud provider because it's problematic enough then you get yourself into vendor lock-in and the work that we're actually doing is to with certainly with an HALBI and I don't know yet with an HGRI but I think it's actually up for discussion certainly the work I'm doing with common fund is to work across three clouds and there's a couple reasons for that so let's look at the downside first you've got three clouds that you have to replicate their environments are different it makes more work but on the other side what you're doing is creating essentially innovation and competition also there are tools certainly I know in talking with the genomic data commons they're looking at very much the tools about how do I actually operate across agnostic of cloud rather than focusing on it as you're the cloud provider I'm saying I'm going to use multiple clouds what's the right way to deploy across that so some of the tools I was actually talking about from UCSC are really about that it's agnostic of the cloud because they know we're going to need to use it and it will drive innovation and competition importantly from the cloud providers many of them have wanted us to essentially work only on their platform and we're resisting that for these reasons and I think that's important for us otherwise they potentially could hold our data hostage which we don't want I agree completely I think that's fantastic hopefully this becomes a huge resource that the community in general want to use and just to add to that point we're not planning to use the archives of that we don't want to use the cloud as an archive we want to use it as working copies of the data for the reasons I just spoke about there are archival copies at different centers repositories like EBI and NCBI and that's great and in this phase what we need to do is use those working copies so we also avoid our lock-in we don't want to be in a situation that our only archival copy goes so I'm going to ask a question that may sound very simplistic but can you give me at least a vague definition of what the data is we all talk about the data and I think we all probably have different ideas of what data we're talking about when we're talking about putting it there I mean is it any data that just happens to be large is it any data at all does it include derived data that you're generating off of these things can you give me some sense of that in the case of HMP data what we looked at was the final derived data sets but we also felt that the whole genome assemblies were really useful as well I think we all know that the derived data is what people tend to use a lot simply but I think that's big for a couple reasons it's what they tend to know how to use more but the other thing is they didn't actually have the possibility to do more with it because they're often their systems can't enable them to look at the larger whole genome sequence so what we're finding is people are interested in looking at the additional larger data sets like WGS and the tools are starting to come around that it's easier for you to do that so I would say it's a changing conversation where data was originally derived but now we're starting to see people wanting to look at more of the I guess the earlier data sets or the the larger data sets before the derived in part because they want to mine it and it's easier to do and I think the other one is because you want to mine across data sets and it's not the derived data set you necessarily want to use so by data I mean everything from the early derived ones for I'm talking about genomic data to its derived form phenotype genotype associations which is where a lot of people want to go or what SNP caused a particular you know there's a certain variant associated with disease but they're looking at all of the other information as well you've got a SNP call you've got a certain quality score on it that's great maybe for your project but maybe you want to look at how deep that coverage was or the quality score because you've looked at some other data and you're looking at a different disease and you care about that so there are reasons to go back to look at the data at the earlier stages for scientific reasons that I think are really valid so when we talk about data we talk about the entire gamut do we know how much that's going to be in the future? No what we do know is it will be dynamic and I think it would be a mistake to assume that it's static right now and we know what it is so our system has to be flexible sufficiently to be able to handle that to think about what are the use cases around that as we move forward I think that's otherwise we're in a really deep hole first thank you for the informative presentation so from my own experience there's kind of two parts to the commons they get conflated one is a place to bring together and integrate that data and then to serve it to the community usually for local analysis the second part of it is a place for people to do analyses to discover based on data that was already data and tools that were already present how much are you putting those two together in the so-called NIH commons and how much are you separating them? See if I understand your question so one of them is kind of like a sandbox approach when you've got early you want people to collaborate together and some of it is when people want to actually use the products of that data research is that right? and then your question is how much of that discussion is occurring at NIH the discussion is happening a lot but people are conflating those two things a lot particularly inside NIH and I do see it outside of people that are just starting up commons conversations and the reason for that is because I think as Carol was getting at the data changes both whether it's mature or where it's in its early stages and people don't delineate between those things we have to do a better job of explaining that I think you'll hear something from the sandbox crew this afternoon about that I think it's important to disambiguate the two some of the early tests that we're doing at the moment are with what I would call more of the mature data sets which are ready for consumption to the community that have gone through the iteration from the original communities simply because we want to see we know that people are wanting to use that and it's ready for broader consumption to the community and we want to test out what that will look like and how people would use it what we're noticing though that was where we started from but what we're noticing over the last six months to nine months is people are starting to look more at the sandboxing idea because they're starting to understand more of it but the conflation comes from lack of understanding of the whole piece the fact that there's not a lot of people with technology backgrounds that can understand this and you really have to think very carefully about what it is you're trying to do otherwise you're just going to boil the ocean these are the issues that I'm seeing right now and then my last statement I guess is a comment the tragedy of the commons and Garrett Hardin's work some people chalk up in these conversations to silly words actually think there's a lot that can be learned from her his work I think they can be his that could be brought into this we can learn a lot how to avoid that tragedy by learning from that literature yes and additional work that I've done that I didn't explain here is I've actually been working with some economists and people that work on e-infrastructures not necessarily for biosciences because the way that we handle governance here and looking at the way the models work here very different anything we've ever done and so I think it's really good to get that external perspective to look at what we do and almost think of it as a business model that we need to drive and that business model yes I think institutions are a business model but that business model also goes across to how do we operate with the commercial providers in this space that are trying to crowd in quite strongly and we as a research community need to figure out what's the right language to interact with them and what are the right social economic economic political areas that we need to include in the way when we build this comments okay we're ready for lunch can you be back here at one thirty please


Conductive polymers, CPs, are organic substances that possess electrical and optical properties similar to those of inorganic semiconductors and metals, but with additional advantages such as ease of synthesis and fabrication, high mechanical and optical properties, and greater environmental stability than traditional inorganic materials. CPs have been extensively studied due to their potential use in a wide variety of applications, from drug delivery to tissue engineering. By coupling CPs with other materials, many of their limitations can be overcome, making them highly attractive for a range of medical and biological applications. This article was authored by Shiranya Paramshetty, Mohit Engalkar, Adele Al-Fatiz, and others.


I love you. Oh, am I alive? Yeah. Let's go. She asked me am I hunting tomorrow white like I'm dead. Who made these works of art? I don't know. I think that might be Nathaniel. Nathaniel's work? Candy work? Morgan and Adam already have a few. They're over there. The birds are jumping back and forth so we're just going to stand over here. Ah, Nathaniel! Oh, nice book. Nice, good. Oh, yeah. Right there in the mortar. Nice! That was a face shot right there. Get him. Oh, you smoked. Nice shot. Oh, wow. I didn't lead him at all. In the trough thing over there. I want to shoot that way. Oh! That's 18 birds with one box. Oh, nice! Pure. Dude, that's crazy. Why? I tried to wrap behind it. I was like, maybe it's vandit. And I ran over there and I was like... Why does snow? How many boxes have you shot, Morgan? Hi, Dad. Got a ring. Shoot, someone shoot that one. That was a smoke. If you guys like these pigeon hunt videos, let me know down in the comments. Give it a thumbs up. Let's get some more. How are we doing? You got Suzanna, Lizzie, Sarah, Suzanna. I wasn't recording. What? No, I'm getting it. He did the same thing to mine. Look at that. Whoa! Please tell me you got that. How does it go, bro? I hope it was videoing. Dude. Alright, let's not tell him. Tell me Suzanna's video. I'll clean it up. Don't tell him what happened. I'll never know. I got it. And you won't find this out till you watch the video. You think he'll notice? I don't think so. Dude. Oh, dude.  You guys better film it. Hey. Hey. That one might be bandied. I landed one foot from our module. What do you guys say about it, John? I'm having a blast. I messed them easy shots, but it seems like they're easier to hit than ducks. Wait! Nice. I wasn't even videoing. Are you kidding? I didn't know you were going to shoot. Are you kidding? I hit the left, John. Nice. Double. Are you kidding me right now? How many times is that, John? I've only landed one on the 10, thank you. Ah, two. I dropped two on the 10. Still less than you. You dropped like five.  I hit the bucket. Edit this out, Titus. Double. Show it to the camera. Double band. Look at that. That's like a homemade. That's a homemade one. That green one. Sweet. Look at that green one. I thought I saw it. I hope I recorded that. 2022. Dude! And I had one show and I gave it a few minutes. Morgan, do you hear me? I said, if this thing's banned, I'm going to cry. Do you hear me? Come on. I hope I got that on video. Double band, baby. Nice. How sick. That is sweet. I'm missing both times, too. Yeah, you missed both times. I had one show. Is that an albino? His eyes are red. Does it have any numbers on it? 2022. Say hi. Hey! That's Jake Yarbrough. Nice shot. Jeff, you're going to get a slap. Make him relax. Nathaniel. Nathaniel, sir. They're spitting all back in the jug. Good day.  Had a blast. Nathaniel. Thank you, Nathaniel. Stay and fight. We filled the truck bed up. Morgan, John, Adam. Hope you guys enjoyed it. Let me know in the comments if you guys like the pigeon hunts. We'll see you on the next one.