it's it's it's not the models it's the modelers and the scientists and i think that's why that would be my pushback to this community that that particular community is you know we don't believe the models anymore than you do you know but we use them as one set of tools right okay so uh paul um i i fully agree with this um stakeholder statement honestly uh and i think that um christoph was very correct in saying that when it comes down to actually using the data having a multiplicative factor is going to be the most easily communicated means allowing folks to adjust to the future and i think that the use of models is to allow us to actually have confidence in whatever multiplicative factor we actually come up with like when we say that 1.4 and we say it's derived from clausius claperon do we have a response when somebody comes along and says well how are you so confident that the change in precipitation will be constrained by clausius claperon and so we can use the models to explore the space of possibilities and see if there are instances where that 1.4 factor may not hold and that deeper understanding of the the underlying processes will then give us greater confidence in its employee in uh impacts thank you uh andrea i also fully agree with the statements i think we really need multiple lines of evidence like whatever tool and this could be machine learning statistic statistical methods observations and often those tools have um different strength and weaknesses so really using all of the information that we have um is is essential and i also want to defend the models a little bit a little bit here because i think it depends which type of model you're talking about if if stakeholders only work with c-mip type models i fully agree like but this this high resolution models are different type of models if they believe in weather forecasts like if they get a warning take care like in a week your dam might spill over because the high resolution model puts a lot of rainfall there they should also believe in this kind of of modeling that we are using because it's the same type model um so it really depends here as well and and one more thing i think your task not only for changing the future but also looking at current climate estimates isn't it so i think modeling has a has a role to play here as well so taking into account in the current climate what the pmp is in addition like paul made this comment as well like observations have large uncertainties and there are really big regions in the us that are very badly observed um and modeling can definitely help to fill this gaps thank you uh christian and then uh christoph yeah i'll keep my short i was about to say almost the exact same thing andreas just mentioned but i will say that it matters what stakeholders were talking about if you're trying to build one dam in one particular area maybe it's complex terrain right the way that you would look at a gcm versus a convection permitting model estimation of the future is quite different than if you're trying to engineer like the you know the levy system in the mississippi river basin right these these things are 30 years out of date we need to think about these broader scale things so i think the what the stakeholders are looking for and what the strengths and weaknesses across these tools across skills i think all of this should be considered and i also think we need to do a better job of communicating our uncertainties in these different modeling frameworks as well uh to better bridge with those stakeholders very well said thank you uh christoph can i just comment on that okay hi not just not just convey our uncertainties but also convey our confidence yes thank you thank you yeah uh chris yes i i i think i wanted to say something about combining models and scaling and i think that's something we have to look into there is some evidence in europe for instance where we have the mediterranean amplification and dramatic reduction in precipitation frequency forecasted by the gcms and rcm at any resolution in the medical of the mediterranean during summer in particular and so it might be there might be ways maybe to combine changes in frequency taking these the kind of information from the models which will depend also on changes in circulation which will not be included in the scaling and and changing scaling which can which can really be based on a physical argument based on the thermodynamic processes so there might be ways that should be explored whether one can combine these kind of different pieces of information great thank you very much so now let's go to jim sorry jim you have been holding for a while yeah well um my question kind of ties back to the long history of probable maximum precipitation and its heritage uh was a quantity that meteorologists would develop first principle assessments of maximum precipitation and my overly broad question is whether there are ways of of thinking about that problem thinking about bounds physical bounds and i think it would would serve a variety of roles but one would be providing a physical process context for studies so any thoughts on on studies that directly address upper limits to precipitation 1800 millimeters per hour in one minute how do you do that and can you do more yep any any response very tough question yeah um i've always been enamored with this study by martinus villalobos and neland from a couple years back which is entitled wide precipitation intensities fall tend to follow gamma distributions where they use a very simple physically driven model physically justified model in order to derive probability distributions associated with precipitation intensities and i think that line of thinking could be taken further in order to um in order to get better statistical distributions of precipitation intensities and basically what they find in that analysis at least for somewhat longer term precipitation events on the order of a day or so is that you have a regime where you have a gamma distributed precipitation distribution and then you have a fall off region um and so i think one of the difficulties in the statistical analysis of the precipitation distributions is getting the point at which that fall off region really begins all right thank you um michael i'm going to defer to christin okay christin yeah so just a couple comments it's a really good question um and in thinking about kind of the dozeball ingredient space framework for flash flood forecasting which is intensity and duration pieces of that equation include things like precipitation efficiency and vertical moisture flux and so things you know thinking about how those particular parameters uh you know may shift in a future climate thinking about you know what is the actual maximum amount of rain that we can get out of the atmosphere some theoretical kind of studies on that may help some of that i know there has been some work looking at precipitation efficiency i think we need to do more on that uh but i i think it's a really hard question i think we should all think about how to answer that question with the tools that we have available to us yeah and i'm also curious whether the answer to this could also depend on the storm types that that we have been discussing all along yeah if you're in the tropics or the sub tropics or the mid latitudes you know these things would would you know these things would change so yeah great thank you any other comments i think this is indeed a very important question right so so so the maximum the absolute maximum in the present day as well as in the future michael yeah i wanted to wait until i heard what chris had to say but it is an important question and and i think jimmy you raise it you you pose it in a different way than we've been talking about you know about instead of looking at precipitation look at the drivers you know like you know that we're that that originally went into these calculations a long time ago and and you know perhaps these kilometer scale models have the fidelity to tell us something about that and that might be a more tractable question you know by framing it based in the old way and looking at the inputs to that calculation and say how do we think those are changing you know we certainly know the moisture is going up by clausius clavron but how are these other factors changing and and that would be an interesting thing to do and we probably have enough model output from christoph's calculations and andrea's calculation to to make some headway great back to christa i'll just make one quick comment too that you know i show a table in my meteorology class on you know the historic rainfalls right the the rainfall records of the of the global um you know distribution and a lot of the rainfall records come from cheripunji india in like the 1800s so the question is going back to how well do we trust those observations right we saw some really great today about challenges and observational networks even today so you know some so this brings back to the question you know how how trustworthy are some of those 1800 you know metrics of rainfall records that's something also to consider in this in this question yes thank you uh obi uh yes let me let me explain my my issue i think uh i think michael mentioned you know number of models that are needed to do the estimation statistically and you know the upper bound and you know the shape parameter is very poorly estimated in some methods and you showed you had to have a very large number of models now given that i think from christry heard that you know observation based estimates just don't go to very rare extremes because we don't have enough data so my question is are these you know two questions is there any other alternative but to use a combination of data and models and the other question is do these models the high resolution models have the right up right type of physics to sort of so they can be driven to generate pmp like you know estimate i think it's ruby's question like do we have the right physics in there and that may be my lack of knowledge on the model so great so obi i think you're asking two question number one is how can we combine data with model to better take advantage of both oh is there any other is that the only way because given the non-stationarity and climate change right uh huh uh huh yeah and and that goes back to also tie a little bit to to one of the questions that i gave uh the panelists is how can we take advantage of both models and statistics to help us maybe get that that upper bound or constraint right and then your second question is related to the physics yeah so i would like to see if anyone okay so i think paul's hand was up first yeah i just want to address that question about the physics if i was to rephrase that i would ask are there any vertical distributions of relevant meteorological fields like aerosols and water vapor content and cloud water that give rise to anomalous precipitation regimes and so an anomalous precipitation regime here is one which is like far outside the norm of what we would expect from precipitation uh and so in order to make an argument that the physical parameterizations don't capture pmp type events we would have to make the argument that pmp naturally emerges from an anomalous precipitation regime and so i'm not sure what the literature necessarily says on that subject but i would suspect that you could we could make an argument that the parameterizations probably capture the the relevant physics correctly oh there's gonna thank you andrew yeah i wanted to comment on exactly on this as well like if we look at our simulations also the weather forecasting simulations that we run at ncar like this very like we had a range of very intense rainfall events over the last couple of years like in the order of 500 to 1000 year return values and those are very fairly well simulated off like it depends on the large situation how predictable those are but harvey for example the west virginia flood that i showed you the kentucky flood um tennessee that we had last year two years ago like this were all pretty well captured and like especially if you look at the ensemble the mean of the ensemble intensity was pretty close to the observations which gives me quite some confidence so but i think also what pristoff showed like we really have to look at how if we really are interested in the in the physics we have to look at fairly short rainfall records like 15 minutes or really maybe even higher resolution this gets challenging with observations as well because if you look at daily accumulations you can get various ways to get to higher accumulations by raining over a long time a little bit or having a really big system that drops like so i think if you're really curious about physics we have to really look really closely at the process level and i think there are some compensating errors that we have in the models which work in our favor but i think overall they do really good all right thank you any other comments related to um both obis question as well as if we want to go back to some of the previous questions like from jim and some of the earlier ones or particularly i don't think we have heard too much about combining data or statistics with model yet now michael yeah i wasn't going to comment on that specifically but rather on something that pristoff said about um inter comparison of different models i think it's something that we really should do and you know we have we know we know how to do inter comparison um we should should think about what are some interesting experiments you know either short term forecasting which means we could do it relatively easily or or else or otherwise i think that's an excellent idea and and use the e3sm the screen the the the icon morph whatever have you and and and not just one but maybe multiple uh uh uh inter multiple situations to inter compare so it so this can be in the context of model in the comparison as well as in the context of generating ensemble right yeah and you know the more things we do the more we learn i mean the office great so i think the next yeah the next hand up is andreas and then paul yeah fully fully agree with this point and i think that even idealized simulations like if we can break down everything to get to the core could be very interesting to run with this different modeling system as long as we can do this i think one really important point and pristoff brought this up as well like we really have to make sure to use the same statistics to look at the the quantities you're interested in right if you look at the literature you can almost get anything you like by using like dry days wet days use some local viewpoint or higher level temperature like we really have to work together to make these studies comparable because otherwise like it's confusing it's confusing even for us that work in this field but we mentioned how confusing it must be for like stakeholders that want to use the data yeah and sometimes these details are even lost when people read the paper or maybe not even reported yeah good point paul yeah i was just going to say as part of the hyperfastest project we have a big component of the project being the development of testbeds which are effectively individual events where we simulated with this with several models and try to combine try to compile a consistent set of observations that folks can then use to evaluate their own modeling systems and so we have a recent paper out on the 2012 North American Duresho that you kind of saw as one of the slides in my presentation but the idea is to expand that to six or seven different historical events of different types and have that that data set of consistent observations available to the broader community in case they want to run essentially the same simulation and same uh evaluation right thank you any other comments or we could even ask new questions yeah if anyone has new questions to ask between the panelists or yeah ruby i guess one of the questions you posed that we haven't talked about is that black swan right what about the events that you know we don't currently see in the current climate but may happen in the future climate just bringing it up in my list yep uh huh right yes uh huh i think it's a particularly hard problem you know the suitable for example right we take existing events and apply thermodynamic shifts right to see how those change but when you think about a climate model right you know while the thermodynamic environments are well represented and we have storm shifts and storm tracks how do i identify those those black swan events that then we would downscale i think that's a really tough problem but it's a really interesting one in representing potential extreme precipitation that we don't the spectrum of modes that we see in the current climate so right yeah so this is also partly related to an earlier question that i asked andre is it's like if we select a set of storms to do the storyline type of simulations i mean how do we know that those are the storms that will produce the maximum amount of precipitation in the future potentially that even the storm types could change right the the types that produce the the maximum amount now may not be the same storm type in that location that would produce the maximum amount uh michael i found it amusing you raised that because i talked about that today in the other lecture i gave oh we had a project that at berkeley lab led by provot for using machine learning um pattern recognition uh technologies i call it the facebook app where we could identify storms um by training um so a supervised machine learning technique what we never got to though was the unsupervised machine learning pattern detection and and that might be the way to find these things and let's say you have you know multiple decades of um of high of kilometer scale or two kilometer scale simulations that's a a lot of data you're not going to be able to watch movies to find these things that i've tried that um you know so having some you know exploiting these pattern recognition algorithms in some unsupervised way could find the things that we don't you know the unknown unknowns as it were yeah i like that a lot michael and you know some of the flash flood history that i showed in my talk comes from the you know the big challenge of predicting heavy rainfall it's really hard and there's so many different storm modes and synoptic modes that produce flash flood rainfall i see russ on russ schumacher on the call here his group has done some really exciting work with kind of short-term heavy rainfall predictability using machine learning um and i think that you know applying some of these techniques to these longer time scales may help us identify some of these situations that fall outside of what we currently observe and so i think there's a lot of merit to what you just mentioned michael and it comes into the context of you know how forecasters actually have built these pattern recognition types of frameworks because of the challenges of heavy rainfall across the spectrum wonderful any any other comments related to a similar topic on black swan or going back i or going back to the one about statistics combining statistics and and modeling i think these are the two questions that perhaps we um could hear a little bit if there are more suggestions of how we move forward that's a really hard poll okay yeah city poll has an answer well i mean we just need a meta analysis right basically you have statistics and models are two different ways of trying to tackle the same problem and so we just do the sure what at all thing and collect all the evidence and see if it allows us to constrain the uncertainty bounds the the the issue is that you know if you were just to calculate return value on 50 years of data with all the covariates you have when you go to say the thousand-year return value the uncertainty bounds are pretty large the i actually i didn't mention this in the pictures i showed there were two sets of error bars and the the wide set was just an empirical estimate of of the return values and the the the narrow or blue bars were that from the extreme value analysis and so extreme value theory if nothing else it didn't really change the the the mean estimate of your return value but it tightened the error bounds on it and so you know that part's good but you know you know in the u.s. we do have some we have quite a bit of data that is over a hundred years that is that that that would pass most quality control as christin says in the 19th century you know it's a little wonky but not everywhere i mean you know maybe some places great thank you uh andres uh like what came to me was really to to try to trade space for time like we do this with the stochastic storm transposition like the the pmp field depending on where you are if you're in the mountains it's way more complex but if you're more in flat terrain it should be fairly smooth i would say so you could try to to get better estimates by really doing the statistical transpositions in a smart way and i know that there are people out there to do that and i saw some fairly encouraging group on that in indeed andres um my my esteemed colleague mark riser has some new papers on that over the united states um where we we we use multiple covariates um uh seven different ones including modes of natural variability as well as greenhouse gases and aerosols um and spatial statistics um uh there's a concept called um uh tail dependence that um we've also been exploiting that our other colleague li huong jang um i can send you some of those papers if you're interested it is powerful and and and and um we haven't looked at it they're really extreme really getting more in a detection and attribution sense but that that actually is something i'll bring up with mark next week when i see him all right any other comments or or new questions okay i'll just wait one minute to see if yeah if there are new questions that we have an answer i would have expected some questions from dan uh cooly or statistical um specs andres this is more a question for you what are the next steps that you're taking now like how do you incorporate this information into what you're doing yeah yeah yeah indeed in my closing i will okay very briefly talk about that okay yeah huh all right any other questions okay so with that i really want to thank everyone the speakers the panelists for really lively discussion i i learned a lot and there's so much so many new points and so many new insights that we have heard i think this is really wonderful and for for all the time preparing uh the presentations definitely those are really high quality and very um useful presentations so so with that i want to thank everyone again i also want to thank the committee member for joining and participating in questions and and and a lot of great discussion um so first of all i'd like to say that there is a recording of this session which um anyone can go back to uh to to view and and in fact even the previous two information gathering session you can you can go to our committee website and and review those um and then also the event website has a link to a form where you can contribute perspectives as well as insights on the session's guiding questions we really welcome uh those who um perhaps haven't participated but would be able to provide some comments and perspective and if you visit the project website you can also find the links to the event pages for past event including recordings of those events etc so what we would be doing next for the committee would be to review all of these information that we have gathered from the information gathering sessions three of them and then we would have more meetings convening um among the committee member to review what we have learned and ultimately um we would be producing a report uh based on that uh based on all of these information as well as uh deliberation by the committee um i want to maybe also call on Jim to see if Jim has any um perhaps a comment or two related to the next steps since Andreas asked about that um ruby just one comment um the committee is tasked with addressing these four specific tasks um not to address other issues um but to fully address each of the issues and provide recommendations uh to know and that's what we plan on doing mm-hmm great yep and you all have been helping us a lot i think we have heard a lot of important points that that and and also new insights that are that are very useful so with that i think we would be ending um thank you very much all for joining in especially also for Kristoff and Michael who are joining from Europe um and it's very late over there um thank you all again and have a good day bye


All right, Sabre Trader is welcome on back. It is Monday afternoon. Feels good to be back in my normal setup here at least. Well, trading wise. Great to be back, at least for right now, but it was great to be back in New York, seeing family and friends. And it's great to see all this back here inside our live trading room. That is Margaret, just before she just dipped out a moment ago, I wish her well, but great to see Louise Irving, Charlene, all of our students and members just joining us right now. A special shout out to my friend Grant rejoining us here today. Brighton, early as he typically is, and it's great to see him back in his normal spot here in our room. So just give me a quick sound check to begin for all of us here. Let me know if you can hear me loud and clear. Should be good to go though. I got all of a sudden YouTube, Facebook Live, LinkedIn, et cetera, that being at Cyber Trading U. Just on the lower left, you'll see that pop up. I'm late to typing that out there to you there, but if you're not the follower, subscribe yet to any of our News Feed social media platforms, that being at Cyber Trading U, just to know when we're streaming live, when we are not each and every weekday. And then, of course, I know that Fausto actually just finished up with the fine folks over at Bookmap. Just did a whole nice presentation, introductory to day trading webinar, using level four, as we nickname it, formerly known as Bookmap. And that should be on their YouTube channel as well. Just go over right to Bookmap YouTube channel right there, and you can actually check Fausto out. Now, with that in mind, hey, we have had a really good day today, normally for a Monday. You don't really expect it, right? You just kind of nickels and dimes. And if there's a stock that has a good order book that is moving up, can make a pop within the first 10, 15 minutes of the morning, then there's pretty good opportunity to at least see it ride out up until 10 o'clock, maybe 10, 15, 10, 30, right? So, the stock now isn't looking too hot. I actually have a bunch of lines here. For the meantime, let me actually just delete all this stuff here. But the GOF, G-O-E-V stock, ended up making a really good push for us. Thankfully, it did, because, you know, we were hoping for it to, of course, but it was on our pre-market watch list out there prior to eight o'clock. Fausto had, this is like number two or three on the main morning watch list that was there. We're familiar with this trade too. So, between everything, right? We were hopeful to see this pop. It took maybe like a minute or so, and then right away, ended up popping and running right from that point. We'll go over this trade more in our workshop tomorrow inside our live trading room. That is Traders Talk. So, for all of us on YouTube right now, just scan that QR code on the top left to get the full rendition of said workshop tomorrow. But, you know, I already had a couple of emails coming on that trade, just about the G-O-E-V. So, that's kind of why I'm saying that more so than anything, but it was one that a lot of us, pardon me, end up capitalizing on early on today. Like, actually, if I could scroll up in the chat just for a quick sec here. Got Barbara joining us, Bill, Patrick, Grant, Alex, all of our students at least. Let's see here. I gotta try and fish through for it a bit. All right, here we go. Got everybody. So, yeah, Luis, yeah, Grant, yeah, Tony, Charles, Steve, Yehuda, John, Chuck, Lee, Roseanne, Pehl, Bill. You could go through that exact same lineup scrolling up in the chat. I'm not just going through random names. You could see everyone chatting at 9.51 in the morning. And then from that point, well, it ended up topping off. You don't need to be perfect on the trade. You don't need to get out at the top in order to feel happy about making money on it, right? On a thousand shares, making even 20 cents on this trade. You're getting very close to your day's pay within just a matter of minutes. So we did a lot better than 20 cents, but we still weren't perfect, and that's fine, right? Now, if you're still in on the Go-Ev trade right now, this is where we say this is not a swing trade. This is simply in and out, right? Normally, right around 10, 15, 10, 30, you do tend to see reversals. This one ended up dropping back down a little bit sooner. It's because it moved up so much so fast. But now at this point, just be careful here. You have lower highs, so you hope to see more on this trade. I hope to see more on this trade, but for right now, we're gonna put this to the side. We're gonna see if there's stocks that are trending up better, making a stronger move up at this point. So this Go-Ev stock, just also be careful of because we're familiar with it. So we've been getting beaten up over time, and even on days where it gapped up and may have ran in pre-market, maybe pre-reverse stock split, maybe it wasn't 100 bucks back then, but no, it just ended up pulling back down. It wasn't really a good swing, was it? So that's where you gotta be careful here. All right, so what we'll do though is go from top to bottom. The Go-Ev trade was really one of our main runners. I guess one of the only other ones I'll just shout here really quick would have found it on the gainer side anyway. But the IMRX, this was one from the morning session too. Fausto was head on pretty much right from 240, maybe 250, then from there took off pretty well towards like three, three and change. This one topped off even a little sooner compared to that 10, 15, 10, 30 time zone. So that's where you say for as much as the stock goes up and up and up. Well, of course it's gonna hit resistance, pull back. Can it make a higher low though? You know, is it possible for it to consolidate back down here and go back up again? At times, yes, but once it begins to continue to stumble, you don't wanna continue to give up unrealized profits, right? Especially this early in the morning when, you know, if you didn't hit go of, you know when we did at least, you know, this was the next one up. But you don't wanna start the morning off on a loss. You don't wanna start the morning off at least giving back a bunch of unrealized profits there. It's unfortunate that this one ended up reversing a little sooner than we normally expect the stock to. But the same to be said here as we just said before in go of, right? It just goes up, comes back down. That's pretty much it. All right, now we'll run from top to bottom here. I wanna talk about a swing trade that I'm in on right now too. On DraftKings, we had called that out just directly inside our trading room for James Irving, Barbara, you know, all of our students there. We talked about that one in the morning audio broadcast and we'll come back to that one at the end. But really top percent gainer here, STI. Let me actually run this one more time to see if there's anything new. All right, so STI, I also used a volume scan here just so it filtered out all the low volume stuff at least, but I mean, same to be said here. It just looks washed up right now. Perhaps it can continue to fill the gap, I guess, on the daily chart, but that's a pretty sharp pullback off the high that we had. I'm not really too interested in it now. Now, Pixie on the other hand, tail of two stocks. Pixie, Scott calling out in our trading room just before, so I was gonna get to this, of course, eventually number three on the gainers list, but the only issue on this trade, Scott, and Scott knows this, all of our students here should. Big spread, thin order book out there, very small tier size, even just on level two, looking at it simply from there. It's running, and we like that. We're gonna put this on our list, but hopefully the order book fills in a little bit more, right? For as much as I couldn't even finish. I couldn't even finish my sentence right there. Just snapped right back down at 489. I was going to say, well, just take one look at Goev and all the others. Same could easily be said here. Actually Pixie, we've traded before in very similar fate that the stock suffered. All right, L-I-C-Y, Lysie, Pixie, Lysie, get other Y stocks there. A little push up for right now. I do like the order book on this. Contrary to the other one, definitely a better liquidity, so it's low risk for us to kind of slip this on our list right now. Got the Pixie, you got the Lysie. CDXC, ooh, not bad. I mean, this thing really exploded back from Friday last week. Forgot about this trade, and it's been sneaking up really pretty much right under our nose. How could we not, right? At this point, just again, be careful of the spread. Starting to open up a little bit here and there. SMR, also this one too, this thing's been on a tear. I don't know what this company does, and pardon my ignorance for that. We don't really need to know in terms of at least day trading. It's been a great swing trade in hindsight though, of course. Yeah, I mean, I guess I'll slip this on our list for now, I just wanna see better trades that are closer to the highs for as much as this pumped up the last two weeks straight. Eventually this is gonna come crashing back down, make a lower high, lower low. Keep going through. This was a little bit of a disappointment. Gave back some unrealized profits on this trade earlier today. The ACB trade, I was up like 15, 20 cents, maybe at the time on it just didn't really get that push up to four, and it pulled back. I'm like, all right, well, I'm not gonna hang on any longer. If it's not gonna make that continued move up, there's no purpose in just like forcing it, right? You know, maybe if it pops during the afternoon, I'll call it out, but we'll put that stock to the side. QSI, not a bad trade here. I mean, on the way up to two, up 14% sneaky little stock here. So I'll add that, and there might be a lot more left that kind of looks like that trade there. There's actually a lot of stocks still sticking near the highs. This TSLT trade, oh no, it's an ETF Tesla. Okay, all right, well, that takes us to Tesla. There we go.  We had it on the morning list. We're familiar with the stock, obviously, so Tesla obviously we're gonna add to our list in general. Cipher, this is a mining stock, crypto miner. Little run up here across the early to mid afternoon on FGEN, looks like big volume getting filled off the top here nearly at 235, starting to round off there for right now. So maybe I'll come back to that at the end if we need to. Man, it got a lot that's up percentage-wise here. I mean, we don't really need to go through every single one. Already have a decent list here already. Here's a stock back from Thursday last week, Bloom that ended up dropping off, a decent little short then, trying to recover now, tradable, I guess, but see if there's anything looking stronger, not just on the intraday, but perhaps also just on the long-term. Maybe a 52-bicai, maybe a stock breaking at double top, things like that. Like TNDM here looking at this pattern here. This looks like a big Fausto flag on the daily chart. This is actually a great-looking chart pattern looking on the daily, just looking on the one-minute chart, though, a little sluggish. Kind of walked right into that, at least they're a good example, if anything, but... All right, so I think that's pretty much it on the gainer side here. If there's anything else looking good from the gainer side going up on the way up, just type it in GMM, getting crushed and we can't short the stock. So we're going to pass on that. I'm going to pass on YMI, this stock, remember this back from Friday last week. This is why we say we don't want to turn this into a swing trade, right, recklessly. What goes up comes back down and you're lucky that this thing even opened up kind of higher from Friday's close. Oftentimes, it'll gap down and that's pretty much it. LSF, ABEO, you know, really unless it's like brand name now at this point, I'm not going to really be too jumpy towards it. Can't really short any of these stocks otherwise. BlackBerry, who's about to trip myself up there and say the other one. S-O-U-N, not really looking too good there either. All right, so you know what? I think that's pretty much it, folks.  Let me just jump to DraftKings. I will slip that one on our list. You know, more is a swing trade at this point, but you know, it's still at the highs. So you could day trade it, of course, hoping that there's a stronger pushup into the afternoon, but you know, I called this out earlier as a swing trade. So for anyone unfamiliar, and there's probably plenty of us that are, no sweat. You got the big college basketball tournament coming up this weekend, next weekend, the weekend after, right? Really quick, little participation if I may. If you are a college basketball fan, or if you have a school alma mater that you are proud of, type it in on the chat board right now, college-wise. For Scott, Charlene, Luis, you know, we got a bunch of people looking to follow the big college basketball tournament over the next, like three weekends it is, a lot of money going into this stuff. So you know, if you're not a sports fan, I get it, you know, Super Bowl brings in a lot of big business, not just across gambling, but across a lot of different sectors. So, you know, Draft Kings is one that we've had an eye on for quite a bit. And with now heading into March Madness season, I think that this could be a really good swing trade. And I said that earlier today, you can see on the bottom right here on my screen, 4205, or 4205 there, as far as my swing price right now. I started it off as a day trade, and I gotta say, I was like freakishly lucky as far as like, you know, the pop-up. I called it out as a swing right here, and it instantly went up. Doesn't always work out that way, right? So I left a ton of money on the table as far as my day trade position went, but I scaled it out, turned it into a swing. That was my intent from the start, and here we are now. So we'll see if this trade continues to push up over the next two, three weeks. Obviously we're off to a really good start on this one. You know, as far as Pfizer, you're talking about the 28 level, and that was a key level of work off of going into like the end of last week, into this week, and there's like struggling for a little bit. It tried on Friday and then closed lower, and look what happened. So this trade I did not take, I had mentioned that. It was more just kind of showing you as far as an opportunity, looking at the chart, seeing resistance become support, but clearly we didn't get that bounce. So we're off to a good start on DraftKings. Actually a hell of a lot better start on that one, and this one I'm in on at least, but you know, we'll see if this makes higher lows over time. If we get lower highs, we'll have to make a decision. Can we get out? Can we wait for the lower low? We'll wait on that, but no otherwise DraftKings I'll put on our list either way, and we'll see if there's anything else that we could work with here at this point, right? Let me know if there's any other stocks up or down that you'd want me to check out here, folks, before we finish up. Luis, Charles, Michael, any of our students here. I'm getting stocks like this from Benzinga. I think that's kind of my cue to finish up. Let's see, Pixie, I think we already talked about that one there, PIXY there, already on our list. ACB trying to eke up over my 375 line. So you know what? I'll kind of slip the ACB on our list one more time. It's been a tease of a stock. I mean, historically it has been, so no surprise here today, but what can I say, I'm a sucker for a tease. So ACB will add to our list, it's already too slow. This one we're not going to deal with at all. MSOS, one of the pot ETFs, isn't really doing anything either. So if anything, ACB all kind of put towards the back end of our list, more speculative, but it's tradable. So we'll kind of put it on there for that reason. What was the other one? CGC, pretty much the same price, right? I mean, now from my experience, at least I will say, recently especially, that CGC was the more volatile of the two, made the bigger of the move the last cycle in which these had popped. So you know what? I'll add CGC kind of for that reason, like I know that it's more bang for the buck for that matter. They're kind of moving the exact same right now, and they're at the exact same price. So it doesn't seem like there's much of a difference, but that's kind of just all my experience there. All right, folks, I think that that's pretty much it. Last one I said I'd come back to maybe it was SMR. I feel like it's moved up so much already. Eventually it's going to make that lower high, lower low situation, and you're seeing it here at least on the intraday side of things of late. So for right now, it'll pass. All right, so hey, for all of a sudden, social media just again, hit the follow or subscribe button on YouTube at CybertradingU on all of our social media streams otherwise. And then if you're interested in joining us for our live trading room, a week long trial, especially for our workshop tomorrow, scan that QR code on the top right or on the top left, might I say, of the stream.  I will slow down as I finish up at least. But folks, give me a little bit. I'll be back on the mic in just about 12, 13 minutes just for the afternoon audio session. Talk to you soon.


Tired of the everyday routine? Ever a dream of a life of romantic adventure? Want to get away from it all? We offer you Escape! Escape! Designed to free you from the four walls of today for a half hour of high adventure. Escape! Brought to you by your Richfield Gasoline dealer and the Richfield Oil Corporation of New York. Marketers of Richfield Gasoline's motor oils and other petroleum products. Look for the Richfield Eagle on the cream and blue pumps. Tonight we escape to the headhunter back country on the island of New Guinea. And the story of two men trapped there with a beautiful but treacherous woman. As Jules Archer tells it in, two came back.  There's a million dollar jackpot and I'm cutting you in. And suppose this blonde number all curves and green eyes leans up soft and murmurs. Johnny, you're bad. Like me? I like you bad. Like me. And suppose this blonde number all curves and green eyes waits until his big back is turned and then leans up again. It can get to be a problem, you know what I mean? A problem. By the time we'd passed over the Golden Gate and were headed out over the Pacific to the west, I could see this business of Gabe and Lily and me were strictly for the squirrels and I wanted no part of it. There was no backing out now. I tried that for a week before takeoff and it hadn't worked. Johnny, don't talk crazy. You're my friend, aren't you? Aren't you? I'm sure I'm your friend, but I don't want to go, that's all. Oh, you gotta go, Johnny. It's a million dollar strike, I tell you. Oh, and after what you've done for me, I gotta let you in. I gotta. You really ought to come, Johnny. Well, I don't know. But I did know. I knew that million dollar strike or no million dollar strike, this was the time for me, John Walker, to stay home. You see, it was all because this pal, this Gabe, had been my sergeant on New Guinea. We were doing guerrilla mop-up work, rugged duty, what were the jabs scattered all over thousands of miles of interior and all. When Gabe disappeared, just plain vanished. We all figured the guy had caught one and was dead. Lieutenant reported him missing in action, we forgot about it. Then one morning, about three weeks later, he shows. Not a scratch, not a word about where he's been or why or what. I'll leave her off for shipping him back to Guam for a desertion trial, but Gabe being a real rough soldier and all. Being the kind of guy we needed bad right then, they decided to chuck the book for the time being and keep him on. It was, like I say, guerrilla mop-up work. And a couple of nights later, we were heading down this trail when a machine gun nest went off right in our faces. We all hit the ground, except in Gabe. He dropped a one knee and sprayed the trees with his browning. A big guy, he stood out like a pinwheel on the 4th of July. Yup, Gabe caught one. I saw the BAR fall out of his hands and down he went. I wriggled through the kunai grass, none of the jungle trail and got him by his collar. Well, I go into it. I was a hero, I guess. I saved his life. And what did it get me? Baby. Trouble. It was in the spring of 47 that Gabe's letters finally caught up with me. I was in New York then. He was in Frisco. At first I thought it was, well, just the old hurah, but I was his buddy for keeps because I'd saved his life. But one of the letters had a plane ticket and a C-note along with a line about, I'm gonna let you in on something big if you'll just come out to the coast. So I thought, ah, maybe the guy's got something. I caught the plane and the next day I found myself walking down this empty street in Frisco with an address in my hand.  Hello. Looking for somebody? Yeah. Who? Oh, it doesn't matter. I can see I got the wrong address. Uh-huh. Hey, that's a, that's a real slick house coat you got on it. This? Oh no, it's just an old thing, you know.  Yeah? Yeah. Um, what address was it you were looking for? Oh, a 403. This is 403. Yeah? Yeah. You, does Gabor Krilovich live here? My husband. Uh-huh. Uh-huh. Gabe! Huh? For you, a man. Yeah? I can't imagine. Well, why... Oh, Johnny! Hey, Gabe! Oh, Johnny, boys, so you got here, huh? Yeah. Oh, gee, I'm glad to see you. Gabe, you're looking good. Hey, so are you, so are you, look at that guy. Uh, is this the Johnny you've been talking so much about? Yeah, Lily, this is Johnny. Johnny, meet Lily. Lily, Johnny. Hey, hey, didn't know I got married, did you guy? Uh, no, no, Gabe. No, I didn't know you got married.  Congratulations. Shall we come in out of this doorway? Yeah, let's do that. Oh, Johnny, Johnny, Johnny, are you a guy?  A million times. And that's how I met Lily. A lot of night we set up talking until the sun came up. I was wondering just what she was trying to pull.  Hey, what do you think of this, Johnny? Gabe. Gabe, that gold? That's just samples. Well, that came from there's enough more to make us all millionaires, Johnny. You're kidding. No, no. Remember in New Guinea when I went AWOL? Yeah, yeah. That was just before Johnny saved my life, honey. Did I ever tell you about Johnny saving my life? Yeah, you told me. Gabe, Gabe, about the gold, huh? Oh, oh, yeah, yeah. Well, when I went AWOL, I thought I'd just do a little fishing or something. You know, I was kind of tired of the war.  Yeah, I understand, Gabe. So I took off into the hills. Oh, Johnny, that is some country. Believe me, wild but pretty. Real pretty. And what sunsets? You never saw sunset sunsets, huh? Gabe, Gabe, the gold. Oh, yeah. Well, I seen this quartz stuff up there in the hills and some of it was glittering. And thought this is it. I made me a map when I came back down. I can find it again without any trouble. That is, I mean, we can find it. You want me? And Lily, the three of us. Lily wouldn't want to miss all that adventure, would you, baby? I should say not. See? Ain't she cute? Ain't she?  Because you're so manly, sweet meats. Sweet meats? And you hear that, Johnny? Ain't she the limit? Sweet meats. Me. Well, it didn't take any great genius to figure that she'd smell money when she married him. It also didn't take any great genius to figure that Lily was going to disrupt some harmony. Now, I've never seen myself as a wife stealer, you know? So by the time that Gabe had bought all this stuff for the trip, I was ready to duck out, money or no. But Gabe, Gabe wouldn't hear of it.  All of a sudden, I wake up to realize that we're flying over the Golden Gate and on out west over the Pacific. And I thought, oh, this is no good. You know something? I was right. San Francisco to Honolulu. From Honolulu to Guam. And Guam to Morrisbee. And all the time, she's leaning up against me with perfume and all on those big green eyes. Morrisbee to Salamow. Salamow to Wewack. And Gabe has given me the happy stuff about how glad he is, his best friend and his wife like each other so much. Then down, down over the palm groves, the native Lakatois, sego-thatched huts down, and there we were. No guinea. Gold. Trouble. Yeah, going up the Pacific River, eh, mates? Yeah. Oh, you better give us a couple of pounds of that powdered milk there. Pacific River. That's a rum country that another patrol officer got done in up there last week. Done in? Oh, hey, how about some 45 ammunition? Yes, done in. Eight hunters. Gabe, you didn't tell me there were head-hutters. Huh? Oh, don't you worry, honey. You got me and Johnny to look out for you.  This Yamo you want? Yeah, yeah, that's it. No bloody business of mine, but I wouldn't take a woman up into that country. Might make it worse.  Gabe, I want to go home. You worry, honey? Of course, a woman would be a prize up there, lady.  I'd say they'd make a queen out of her. Wouldn't touch her, just worship her life. That's good. Well, that's up to you. Well, I don't like it. An hour later, Pax bulging the supplies, we were off on the trail that wanded up over the Purple Mountains. The Prince Alexander range. And on toward Miami, Gabe carried the heavy float boat bag on top with a thick duffel of provisions. I followed, carrying two packs, one on top of the other. Lily brought up the rear, carrying a light pack of clothing, mostly her own. It was rough going that first day. Gabe didn't seem to mind, but me, my feet started to cave in after the first 10 miles. It was all right with me when Lily squawked. Gabe! What? Let's stop. It's only 3.30, honey. Let's stop, Gabe. Another couple of hours, we can be over the first mountain. Manana, Gabe. My back is breaking. Okay, honey. He lowered his big pack and then took off into the jungle. Hey, where are you going? We'll need some firewood. Oh. Johnny, I'm tired. Yeah, me too. Oh. Oh, it feels good to get those up. Oh, whoever heard of carrying two packs at once. Good old Gabe. Yeah. Yeah. Come here, Johnny. What do you want? I know what you think about me, Johnny. You think I'm bad. It's only because I'm bored and happy and bored. I could be a one-man woman, Johnny. Oh. I'm glad to hear about that. For the right man, Johnny. Sure. For you, Johnny. Nothing Gabe would think it's such a hot idea. Maybe he wouldn't have to, Johnny. Meaning? Maybe after we get the gold, he'll fall off a cliff. Or he gets eaten up by a tiger or stepped on by an elephant. There's no elephants and no guinea. Don't be dull, Johnny. I gotta be, Lily. I gotta be your real poison. Oh, Johnny. Your real bad poison. Mm-hmm. I'm bad. So are you, Johnny. Yeah. Mm-hmm. You know, that looks real funny. Lipstick in a jungle. You think so? Looks even funnier on you. You're nothing to do there, baby. Here comes Gabe. I forgot my gun. Always like to carry a gun in the jungle. Never know when you're gonna run into a snake. Huh, Johnny? Yeah. Yeah, that's right, Gabe. Yeah. 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ESCAPE! Well, there it was.  Very dramatic situation, except for a minor point. She had figured that I shouldn't kill him until after he'd found the gold mine. And another minor point being that I was his best friend. But you know how it is, life... best friends always kill best friends. Oh, sure. But while this sort of drama unreal, we had to hike through that lousy jungle. Hike and hike and hike and my feet were killing me. The sixth day was the worst one of the trip. We were wading through mangrove swamps, thirsty leeches. There were giant mosquitoes that swarmed around us in clouds and every time I slapped one, I killed ten. Oh, sure, we had mosquito lotion. They loved it. Gabe? What? What are we going to get to the river? After a while, honey. After a while. After a while turned out to be nine days more. Then we reached the sephic. A sluggish muddy river winding like a serpent through huge Greenford mountain ranges. And now we ride. We blew up the collapsible boat, loaded all of our stuff aboard and shoved off. I took the bow, gave the stern, Lily set a midships and a piled sacks. Easy, Gabe, will you? This baby was designed for two people, not three. We're drawing a lot of water. Don't worry, Johnny. It's flood season. And with flood season, the water's high. We can carry three, but later it won't work. Then it'll be only two. Yeah, but we'll be back before then. Sure, Johnny. From time to time when we camped, Lily would give me the business. She didn't seem to care whether Gabe caught on or not. I cared. I cared a whole lot. And Gabe? I didn't know yet what it was that he was feeling.  I owe you a lot. Maybe that's what it was. But one afternoon we camped early and went for a swim. I was paddling around. Water felt good. Gabe and Lily got out and were drying off when all of a sudden... I looked up. It was Gabe. He was standing on the bank, and his 45 pointed right at me. I dove. I dove as deep as I could. I could still hear him shooting. I stayed down until I thought my lungs were gonna pop. I surfaced. Gabe was waving at me and yelling. You're crazy, Gabe!  I'm not shooting at you! Come on! So I came out and I looked around. And there, a few feet beyond where I'd been there was a tremendous crocodile with blood streaming out of him. When you dove, I thought Shuri had you. Yeah.  I don't know. I must have lost my head. Gabe saved your life, Johnny. Yeah. I guess that evens us up, huh? Yeah, I guess so, Gabe. No, I don't know your thing. That's right.  Well, you figure that one. We kept on going until we came to a place where a narrow, rocky tributary came boiling down a big mountain and into the Pacific. This is where we started walking again. The goal was up that fast little creek and we could never paddle against that current. So we folded the boat, shouldered it and the pikes and started climbing. For a day and a half, we scrambled up that mountain by the fast little string. Then we came to a wall of gray and white rock. Gabe said, this is where the goal is. And he was right. Holy schmuck goalie, that goal. Sure, we had to work to get it out of the rock. Well, in six days, we took out nearly half a million bucks worth. We could have taken more, but the stuff was heavy, you know. No, you don't know. You've never seen that much pure goal. I'll just take my word for it. Six days later, we started down the mountain. Then when we made camp by the river that night, Lily waited until Gabe was sound asleep. Yeah? Now, Johnny. Now what? Now you can kill him. Go away. Do it now, Johnny.  I'm a rich man. Will you get smart? Smart? You get smart, Johnny. Three ways isn't good enough on the split. I wanted two ways.  After all, Johnny, you're the serpent in our happy marriage.  I don't hear anything except the water. Yeah. A minute ago, you couldn't hear that for Gabe snoring. They came in the morning while we were loading up. They came out of nowhere. Get down. What's that? Elves. We could tell from the arrows where they were. We laid low and tried to make every shot count. It wasn't long before we saw they really mean business. They weren't going to go away. Johnny. We haven't got enough ammunition. It's the last more than 10 minutes. That's just great. Can you keep them off that long? I'm going to... I'm going to get down to the stream and load up the boat. You're crazy, Gabe. You can't make it down that stream. Sure we can. It's sad to end up with your head on the pole. Okay, Gabe. All right. Now cover me. Here, I shot you and Lily come fast. All right. The longest 10 minutes of my life, Lily lay there beside me. She was plenty scared and she had every right to be. Those arrows were ugly, big and jagged and sharp. Johnny. Johnny, those arrows are getting closer. Will you stop jiggling my arm? I can't help it. Look, how am I going to shoot if you jiggle my arm? Suppose they get Gabe. That'll be tough. Yeah. I'll come you worry about Gabe at a time like this. Gabe, Shmayb, I'm worried about the gold.  Will you stop jiggling my arm? So sorry. Yes, I kept fire. Have you any idea what you're shooting at?  I mean it.  I should have stood in Frisco. Oh, don't talk. Just keep shooting. How can I keep shooting when you keep jiggling my arm? A nasty little thought crawled into my mind. Here I was up to my ankle scenarios and there was Gabe with a boat half a million bucks and a downhill ride to freedom. Just suppose, just suppose Lily must have gotten the same idea. I'm going to go help Gabe, Johnny. He may need help. Stay here. No. Goodbye, Johnny. What did I stay? I don't know.  But I stayed. Came ten minutes, I heard it. Gabe signaled. The boat was already in the water, all loaded to go. Gabe faced the jungle, he's automatic ready. Lily was crouching on the sand. Good boy, Johnny. Thanks.  Yeah. Just one thing I didn't counter. What's that? With all this gold and the boat, it'll only carry two people now. Okay, Gabe. Okay, I get it. Only one thing.   Wait a minute, Johnny, wait a minute. Maybe we ought to ask Lily who she thinks ought to stay. Maybe she'd rather I stay. No, Gabe. How about it, Lily? Who do you want to stay? That's a tough question. I know. You both got guns. Why don't you fight a duel for it? It'll only take a second, and the winner gets me and the gold. The one who stays behind will be dead, so he would have to be tortured by headhunters. Oh, she's pretty cute, huh, Johnny? Oh, yes, indeed. Get in the boat, Johnny. No, Gabe, look. Go. You go. Look, now's your chance for a clean start.  You sure this is how you wanted, Gabe? This is how I wanted. Yeah. Yeah, that's it, Johnny. Now, you all set? Yeah, Gabe. I'm all set. I hope he can get us down, Johnny. It's an awful fast stream. Don't you worry about it, Lily. Why not? Because it works this way.  If you stay here, you can be a queen. You can live.  You'll rule a whole tribe, all by yourself. Gabe! What are you talking about? Stay away from the boat, Lily. No, Gabe, let her get in, will you? I'll get her. I'll stay. Come on! Sit down, I said. Gabe! Johnny saved my life once. You. All you did was try to get him to kill me. Anyhow, I'm the only man who can get this boat down the rapids. And for that, I need Johnny. All right. Go.   You'd say it, Lily. I knew you'd understand. Here's an amazing fact for every motorist. The film of oil in your motor is often no thicker than a spider's web. But that thin film is all that saves your motor from destruction. That's why it's important for you to use the best motor oil you can get. We suggest Rich Lube, all-weather motor oil. Rich Lube is refined 100% from the finest Pennsylvania crewed obtainable. Rich Lube protects your motor with a tough, elastic oil film that holds its body even under the terrific heat of summer driving. At the same time, it draws excess heat away from moving engine parts. Moreover, Rich Lube, the Pennsylvania premium motor oil contains special chemicals that clean your motor of harmful deposits as you drive. Yes, it cleans as it lubricates. So keep your motor clean. Keep your motor young. See your Richfield Gasoline dealer tomorrow. Ask him to change your oil to Rich Lube all-weather motor oil. Escape is produced and directed by William M. Robson. And tonight has presented Two Came Back by Jules Archer. Adapted for radio by Savage Dollar. Featured in tonight's cast were Joan Banks as Lily, Stacy Harris as Johnny, Paul Freese as Gabe, and Ben Wright as the Trader. Special music arranged and played by Next week You are lost in the wildest mountains of Idaho.  A death from which there is no escape. Next week at this time the Richfield Oil Corporation of New York invites you to escape with an exciting story of love and murder in the wilds of Idaho. As Anthony Ellis tells it in The Red Forest, be listening. Goodbye then until the same time next week when once again we offer you Escape. Tom Hanlon speaking. This is CBS, the Columbia Broadcasting System.


Hello everyone. In the previous lecture, I discussed the applications of radioisotopes in healthcare both in diagnosis and therapy. And I also explained the three main concepts behind these applications. I would like to repeat those three concepts for the sake of continuity. And in the presented lecture, I will discuss the applications of radioisotopes in industry, environment, agriculture and food technology. Though the topic is very fast, I will just take one or two examples in each area to bring home the point. So, as I mentioned previously, the radioisotopes can be used in the form of radio tracers. The radio tracer, you can use to trace the path of an element. So, that finds a lot of applications which will be clear when we will discuss these applications. Radioisotopes are emitting radiations which are highly penetrating. And this can be used like you use x-rays for detecting the practice in human body in the bones. You can use radiations in many applications which will make things very clear subsequently. And the other aspect is that the radiations can kill pathogens, they can generate heat, they can introduce defects in the materials. So, and you can even use polymerization of the materials. So, there are, you know, you open up a new chat, new areas for applications. And this is a kind of one has to do a research, what way you can use radiations in different applications. So, this atoms in the service of mankind, that is the concept we use that not only these radioisotopes when we use, we have to have in mind, what is the benefit? So, the benefit can be in terms of money, you save the money. There can be alternative methods, you can save money, you can save manpower and you can save time. So, unless you have the gain in terms of these three parameters, money, manpower and time, if there is an alternative methodology, then it is no, there is no point using this. So, it should score over other techniques both in terms of all the three aspects that I just mentioned. So, I will just give some examples of each these three previously, one I have mentioned. Radio tracer concept in industry and the list is endless. I will give you some examples also. So, leak detection in buried pipelines and high pressure heat exchangers. So, their pipelines are going thousands of kilometers like from refinery from, you know, Gujarat to Mathura. There is a big line in refinery going, the refineries in Mathura and crude is going from somewhere in Jamnagar. So, there is a leak in this, how you detect the leak. So, and if you have to dig out the whole thousand kilometer, it is a very, very Herculean task. So, that is where the advantage of radioactive isotopes. C-page location in dams and water bodies, you can trace the path of the water by using radio tracers, flow rate measurements, what rate the flow is man, flow it is flowing, time of mixing and blending in the different types of industry, residence time distribution measurement, there are mixers and many chemical reactors, wear rate measurements by, you know, this you can you can produce radio isotope in the machine part and it is wearing out worn out so that radioactive decay as a first of time. You can see how the wear and tear takes place, sediment transport in ports and harbours, effluent dispersion in coastal waters. These are all very big experiments which the enormity of the experiments will be clear when we I will show you some results. Effective management of oil fields. So, oil field, you know, there you are is taking out the oil and then the water will gush. So, how much time we can continue to tap this oil field, there are techniques based on radio tracers, you can do the time management and radioactive particle tracking technique for flow visualization in the reactor which is copied from outside, how the particles or the reagents are moving in the reactor, you can track and you can simulate the the processes that are occurring inside that. These are some of the examples which I wanted to highlight, but I will take some of the from this and give actually illustrate more by these examples. One of them is leak detection in buried pipeline and I will give you the real examples from one of the them is Gas Authority of India Unlimited, there is a pipeline, very short explanation I will give. Suppose you have got a pipeline here and the fluid is flowing from here to here, it can be hundreds of kilometers and suppose there is a leak somewhere here. Now, how do you know, you find out where is the leak, this is the project, you cannot dig the whole line. So, what they do, they first put place the marker sources from the surface like 4W-60 sources from the surface, on the from the surface you just dig them and put above the pipeline, they are outside the pipeline and now you inject the fluid containing the radio acetyl, like methyl bromide. If it is a liquid, you can use bromine VT2 labeled liquid and then wherever there is a leak, the activity will come in the soil and now you take a detector through this pipe at a particular rate. Detector will detect not only the leak, but also the gamma ray from the markers. So, in the output of the detector, you will see these markers that they will tell you the position of these markers. So, you can know, suppose there is a leak here, you will see a broad peak here, this broad peak is due to the leak and you know this is between these two positions. So, in a very short span of time, you can identify at what place the leakage has taken place and you need to dig up only in that area to plug that leakage.  Another important application of these radio tracers is residence time distribution. So, there will be many different types of chemical reactors where you mix the reagents A plus B going to some system and there is some process taking place in the system and then there is the output. So, you have an input and the output. Now, inside the reactor from outside it is blind, you do not know what is the dynamics, you know hydrodynamics of the material that is going churning in the system. So, you want to know that how, what is the time during which the reactants stay or the product stay in the reactor. So, you put a detector here, you put a detector here and then you inject the radio tracer. The radio tracer when it goes at inlet, it will show a sharp peak because it is quickly flowing in the system and the outlet you will see you will get a broad peak because inside the reactor the radio isotope leveled the material will take some time. So, for example, you are mixing sand and cement.  So, inside how much time it is residing and what is the informity you can know from this one. So, residence time distributions are utilized in many chemical reactors. The performance of the chemical reactors are equally determined. You can have some even industrial circuits, there can be many other plants, then mixing units, I was telling the mixing units cement and sand or there can be many other industries where you are the chemicals are being mixed. So, how well the reagents are getting mixed you can find out from the residence time distribution. So, residence time distribution is given by like ET is the fraction of species that has spent time between t and t plus dt in the reactor. So, this is the concentration of the particular species that has come in the time t plus dt, t to t plus dt and this is the integration. In the denominator you have the entire concentration total area. So, this is the total area under this graph is the concentration total concentration and at a particular time what is the fraction of activity that is come. So, this is the residence time distribution for how much time the reagent is residing in the reactor this study can be obtained. Then you have flow rate measurements they are all big projects very big projects involving hundreds of crores of rupees and you can see by what experiment one can save so much of money. In fact, sometimes you will find there is no alternative to these techniques. So, for example, if you are having a this is a actually a hydroelectric plant. So, there is a some 3.6 meter pipeline which is taking the water to the turbine.  So, that is the capacity of the pump. So, you want to calibrate this because how much is the power consumption of this pump, what is the flow of the pump. So, to calibrate these pumps you require to do investigation and how to investigate the pump capacity the flow rate and all that. So, for this the bromine 82 can be used as a pressure. So, what you do you measure the flow rates of water. So, in water you can mix sodium bromide and so bromine will go with the flow of water. So, you can use this technique and you can put suitable detectors at initial and final stage and you can see the activity that is flowing. So, you can check the calibration of flow meters or you can check if you will flow of any fluid you know stream liquid or gas you can use. So, in fact, these are the pumps made by the industry and when they are selling to this particular thermal power company they want them to calibrate these pumps to to ascertain you have to give a certificate this is the capacity of the pump and this is the wattage of the pump. So, if you want to validate the capacity of the pump, water budgeting and optimize the power consumption then the the industry can come to the the people who are doing this kind of investigation. So, this is actually an example which the department of nuclear energy in fact, solve this problem for the industry partner. Another kind of investigation is silt movement in ports and harbors. So, what is this silt? See in the big ports you know the big ships are coming to the dock and gradually you will find that this dog height will come that the dog that the shore know the level will go up because wherever this there is a movement of the silt in the sea and so what do they do? They do a dredging. Dredging means they remove that silt and park it somewhere in the sea so that the big ships can come to the shore. But over a period of time that silt will again come and you have to do the dredging again and again so it is very time consuming. So, in fact, this is an experiment at Calcutta port. So, what was done actually that the sand particles were labeled with Scandium-46 as a tracer. So, the movement of the sand can be traced using this radioactivity of Scandium-46. So, what they do? They dredge this silt and park it somewhere quite far off and so this is the place where they have placed the dredging sand which is not tagged with the radioactivity. And over a period of time now you map you measure the activity of Scandium-46 in x-y direction and you can see here these are the contours of activity asymmetric points and so essentially this tells that these tracers this tilt can move in these directions. In this direction there is no movement. And so you can identify in which place you should put the dredged sand silt so that does not come to the port or harbor as a function of time. So, these are the kind of mega experiments which you can do. So, they are used to investigate suitability of dumping site for the dredging material and optimization of the dumping operations. So, in what place they should keep placed the dredged sand so that it does not come back to the place from where it was taken out. These are the kind of experiments you would are doing.  The other application is penetrative power of where the gamma rays are penetrating through solid material and they follow this exponential decay i equal to i0 raised to minus mu x where mu is the attenuation coefficient. So, these techniques are called non-destructive testing methods NGT. NGT you know very useful in the industry for measurement of thickness, density, defects in the materials. For example, in the high technology materials there is some welding to be done. So, how good is the quality of the welding because they are going to remain in the plant for long long times. If the welding is not proper it will affect the integrity of the system and for that gamma radiography is used extensively in industry. In fact, we train the people who do gamma radiography in the industry. So, there is a training program in the Department of Atomic Energy one can enroll for that and do the certificate course and then you can become a radiographer. So, the non-destructive examination of welds and castings this is not the only example you can have many other examples you require you have a high energy gamma source and low energy gamma source for radiography. If it is a heavy material big bug equipment you require high energy gamma typically a cobalt 60 of 20 kilo 20 curie and if it is a smaller product you know some smaller machine then you need to have low energy gamma emitter and 100 curie of EDM 192. So, like welders pressure vessel ships aeroplane components all can be investigated for their integrity their structure there is no crack inside micro cracks you know there could be micro cracks the NDT the radiography can tell you even micro cracks and so this is a typical example of a a component you know a component which has got thick parts and thin parts. So, when you when this is a this is the area where is thin wall that means it is a doesn't have much thickness. So, when you do gamma radiography with low energy EDM 192 you can see some opaque part but when the same thing you see in gamma in cobalt 60 we don't see that part because gamma energy which cobalt 60 gamma will just pass through. So, by playing with the gamma energy you can investigate the different types of samples small or big and this is a typical gamma camera called roly developed by Brit the board of reducing astro technology BAE. So, this this can be taken and you the the source is kept inside the shield and when you want to do the radiography you take out the source from the shield expose the sample and again after the exposure you take it back to the shield. So, it can be transported in different places for NDT experiments. So, these are the kind of you know big machines radiography of aircraft engine of concrete structures or even the plug valves you know the small as well as a big you know aircraft and the big machines can be done you need to do radiography because you have as a part of the quality control you have to assure the end user that this will meet those requirements. So, when you say an aircraft you know the like the the probability of accident one in billion times how that number comes because they have undergone through tough test flight this kind of testings. Now, I come to the another NDT technique called computer thermography CT CT. So, computer thermography is an advanced version of radiography where you not only do that take the image you get 3D image of the equipment. So, NDT of engineering and industrial specimens you can do even cross sectional images of the internal structure of the object. So, in radiography you just expose the equipment to the gamma rays and you take the film it take a film on which you can take the image of the like you take an x-ray. So, radiography is like x-ray but tomography you know is much more advanced. So, you have an object you put the object here there is a there is a source inside this shielding. So, there you could come as a beam through this collimator and you can do x, y, z movement of the object by a gonometer and then the gamma ray will go and by a collimator will fall in the detector. So, what you do you rotate the object in x, y, z direction in the form of thing. So, you get image cross sectional image of each slice of the object. So, you can you can go take it up you get the circular plates circular images you take in x, y direction you get different cross sectional area and those images are constructed by the computer and develop the 3D image of the machine part. So, this is the more advanced version of radiography in where you you get the 3D image and these 3D images are then you can see you such a crystal clear image you get after computer tomography. So, this is a typically a cold bed test reactor you can see the kind of image that you get by computer tomography the full digital radiograph 3D surface rendering from CT data and representative. So, you can see the kind of dilution that you get because you have a collimated beam of gamma ray and then you get the image. So, as in one scan you will get a particular plane of the system and you have thousands of scan in x, y, z direction. So, that is the kind of dilution that you get, micron levels of fractures you can detect using computer tomography. This is the image of a typical metal or ceramic handicap of electronic equipment. So, again the point I want to emphasize that by computer tomography you get much more well resolved images than the normal pedography. Another application is in gamma scanning. Gamma scanning is another area for troubleshooting investigation. Do you have suppose you have got this what you call as the fractional distillation in the refined region you have big towers and the big towers different heights will have different collections of different types of products of the petroleum products. So, now you this these are you know they are working for long, long time and there is some defect inside is it you are not getting product of desired quality. So, how do you rectify? You see you open it up for maintenance you know it may require shutdown for a week or two and that is huge loss to the industry. So, what you do non-invasively you can do you put one detector you put a source over 60 source here and you put a detector sodium iodide thalium detector and they are they are they are moved synchronously. So, if this source moves detector also moves by the same. So, they can they are joined together. And now what you are getting is the this this attenuation of the gamma ray of over 60 when it is passing through the internal parts of the column. So, this column so this is the cartoon of the column there are different plates inside you know different fittings are there. So, the gamma ray intensity you will see. So, when the gamma ray is passing through a thick object the intensity will be low. So, that tells you the profile of the different objects inside the column. Now, if you have taken this profile in the beginning when the column plant was started and you can periodically monitor. So, as a function of any time suppose there is a problem in the plant you can immediately run the scan and find out there is a flaw. So, this scanning of this column and it is very low cost a cover 60 source and like detector sodium iodide thalium is not at all very costly. So, manpower will be one or two personnel and even a day you can do the whole investigation. So, you save the time money and the manpower and by very very low cost very low short time you can do troubleshooting of the problems that are occurring in the plant. So, the diagnostics of problems in operating columns like fractional distillation, separation, stripping etc. in petroleum plants. So, very quickly many of these defined reason in Lusanne petroleum all many in the petroleum companies employed these techniques to do troubleshooting whenever they have problem in the plant. Now, I come to the another aspect again the penetrative power of the radiation is called the thickness gauge, look newly gauges. So, you can you can determine the density, thickness, level of a compound and so on. So, measuring the and monitoring the thickness of films, sheets and metals and plastics during manufacturing. So, you have a like giving a paper industry. So, the paper industry paper is prepared and it is moving through a conveyor belt and you know the paper quality you say this much you know gram per square meter gsm 100 gsm, 50 gsm and so on. So, how do you maintain that quality control you want to know. So, for that you know you can have a very simple system you have a radiative source outside the this is the paper which is moving above the paper you have a source below the paper you have the geiger ruler counter very cheap equipments and you suppose it is a it is a for example, if we have a metal plate you can put beta, if we have a thicker plate you can put gamma, if it is a thin paper you can put it in all forms and then measure the activity as a function of time. So, suppose it is the thickness is constant you will get constant activity in the counter, but whenever there is a change in the thickness that intensity will change. So, beta and gamma can be used to find out the change in the thickness whereas, alpha in the case of alpha the energy of the for a very thin foils you know micron thick foils you can use the change in alpha energy because alpha intensity will not change as a much thickness, but alpha energy will change. So, for very thin foils micron thick or less than that you can use alpha and for millimeter thick to millimeter you know you can use beta or gamma sources. So, they have the advantage of non-contact movement you can place it even the plant is running you can do continuous measurement accurate save and reliable there is hardly any ventilants the plant need to shut down gauges can be often installed and commissioned without processor down and at the sources and detectors are mounted externally from the vessel or process they are completely unaffected by the chemical and physical property of the plant. So, it is you know non-invasive the plant is running you can do all in the modification in the in this system to determine the thicknesses without affecting the plant that is the kind of advantage with this. Like you know the examples are level gauges oil level in refinery you know refinery the vessels are few thousand very big ones lakhs of liters plants. So, this level level of the fluid you can do you have a source and a detector you will put a source and detector and you can play them. So, when the gamma source is below the level you will see the high attenuation and when it is above the level there is less attenuation. So, you can see there will be a discontinuity at the level. Similarly, you know this when you have the mixers and so there is a uneven level inside like clickers you know they are used in cement industry. We put a source and a detector here and from the attenuation the intensity of the gamma in the detector you can see the level of the material inside the this this plant. The glass furnace the glass the molten glass what is the level of molten glass you do not know from outside but if you put a source and a detector source and detector that attenuation in the primary when it is going to the molten glass there will be more and if it is above the molten glass level it will be less. So, you can again see very precisely you can find out a level of the glass furnace. So, level gauges and similarly you have density gauges and so on. There are many many areas where you can use this radioisotopes. Okay lastly I will discuss the applications based on radiation effects the heating the killing of pathogens and so on and there are I will talk about three areas. One is the agriculture. In agriculture you can do crop improvement by radiation induced mutations. Radiations when they are bombarding the seeds then they can generate normally the seeds are undergoing mutations even our body is undergoing mutations but that is happening at a very very small times 10 power minus 5 minus 6 scale. But by mutations you can accelerate the mutation by radiation acceleration mutation by orders of magnitude 1000 to 10,000 times faster mutations can take place. Food technology the radiations will kill the pathogens you can do disinfestation and you can delay the ripening of the fruits and you can do sterilization of medical products again the pathogens can be killed and also the radiation processing you know radiations can induce polarization in materials. So, like rubber the bulk management of the rubber can be done in your radiations you can hydrogenize the sewage sludge and use it for the manure in cities now it is a big problem of sewage sludge. So, you can make it hygienic by using radiation and then you can use it this manner during of surfaces coatings heat shrinkable forms you know in radiation technology is a past area there are more applications you can modify materials you can graft a compound on a solid support there are a lot of modification processes using radiations because radiations can induce crosslinking in material polymers it can even cause chain season like teflon can be powdered by radiation but the normal polythene become hard by crosslinking. So, I will not touch upon this aspect because I do not have much time I will just quickly give you the example of the first three. So, in agriculture you can do crop improvement by mutation as I mentioned the mutation radiation induced mutations you can enhance the mutation by radiation. So, they irradiate the seeds by gamma rays the gamma ray will cause genetic changes in the seeds and then you will show these seeds. So, apparently we cannot say what will happen to the seeds we cannot selectively generate positive mutation. So, mutation can be negative. So, you you will come to know after you reap the harvest the seeds the mutation can be positive that means the fruits that you generate for out of this mutated plants they can have good traits positive traits or there may not be any mutation no effect. So, once you show them once you harvest them then you pick up the ones which have the positive traits. So, the genetic variation you see and select them and multiply them 5-6 cycles. So, once the genetic changes have become stabilized then the varieties released the government as to their government agencies which will approve that you this is now certified to use by the farmers. So, what are the traits what are the attributes that you can have I yield variety. So, per hectare omniquitans that is a parameter disease assistance this the after genetic modification they have you know the mutations they have become more this is the one adopted they can adopt you know the desired conditions or topic and conditions or better nutritional nutrient value. So, these are the parameters which you can see if they are improved then you know that we have produced a good material. Second is the applications in food technology you can prevent the sprouting of vegetables because the radiation will kill the the the the enzymes and bacteria they will deactivate the enzymes they will kill the bacteria you can extend the self-life of perishable food products because you can delay the growth of the microorganisms you can disinfest the food products spices many products meat products, canned food products you can preserve for longer time and you can delay the ripening of fruits like mangoes. So, this is a typical you know the plant for radiations and so many products have been certified approved for radiation by gamma rays, potato, onion, many several types of food products are now certified for radiation by the gamma rays. So, there is a long list of products I have listed here meat, meat products, chicken, spices, onion, potato, ginger, garlic, shallots, mango, rice, all these products are now certified for radiation to improve their self-life or to do disinfestation. Lastly as I was mentioning you can stabilize medical products using a radiation plant and this you know so you pack the implement the medical devices like you can usually throw types of medical syringes, surgical gloves, tools used in surgery, tweezers, scissors and so on and you pack them in cardboard boxes this these are the cardboard boxes and you put them so there is a source in the plant and this in the conveyor belt this whole the packets will go stay there for some time and after proper dose has been delivered they will be taken out and then sent to the places hospital, sword industry. So, there are several plants in the country now running and one of first plant was Isomet at Trombay for the last month now not three more than four decades it has been working and this industry is very much growing now. Now, people have radiation plants not only for medical sterilization but also for food technology, food preservation. So, combination of medical sterilization and food technology are making the throughput high and many people private people are now developing these radiators for the benefit of mankind. So, that is all I had to say I wanted to bring home the point that not only the research should be done for the understanding the system for underpinning phenomena but the research that is going on the laboratory must reach the land and for that you need to have innovation development of technologies. So, you do the research then develop demonstrate and deploy so any research should be ultimately going to useful for the mankind. Thank you very much.


But something I'm always interested in is kind of thinking who's the opposite to that, right? I mean, he's a very marginal figure in Irish politics, but you have Sinn Fein who are less marginal and, you know, potentially are going to get a lot more votes in the next election. So, you know, when we're looking in the doll and in the shanad for people who are really kind of standing up to the anti-Israel sentiment and taking on the likes of Mary Lou McDonald, Richard Boyd Barrett, Paul Murphy, and all those kind of, let's say, agitators on the left, do you think there is any kind of a pushback at the moment in the ararctis? Not enough, a lot. There's one senator of our senator, Nego Sona, who is pro-Israel. And he's a very brave voice. Apart from that, I think there is an ararctis friend of Israel group, but I'm not really sure that they're doing off a lot. It seems to be, it seems to spend a lot of time in the closet. I mean, you would find the main government leaders pushing back on some of the more extreme rhetoric, you know, Leo Veradkar and Mihail Martin would tend to distance themselves from the more extreme rhetoric. And a few months ago, when there was a report from Amnesty International about accusing Israel of being an apartheid state, Mihail Martin actually said that he wouldn't use that term and he didn't find the term helpful. So, you know, but still at the same time, he has issued some very harsh criticisms of Israel's actions in Gaza. So, I mean, apart from senator Nego Sona, there isn't really anybody you can point to and say that they are supportive or understanding of Israel's position. It's kind of, it's degrees of opposition. Leo Veradkar and Mihail Martin did very strongly condemn Hamas in the first few days after the October 7th attacks, but then very quickly moved into the usual attacking Israel kind of speeches and your comments. And everyone again, they would say, oh, of course, we condemn Hamas, but, but, but. So, yeah, there's not much there really, apart from senator Nego Sona, there isn't really much in terms of pushback, unfortunately.