so yesterday what did you do about recycle reactor smaller and larger i think still you understood that know smaller and larger why it comes ya but the other areas anyone prove you got it excellent very good one person you have done a good i think two people atleast good okay so we will now go to auto catalytic reactions ya i tell you there are lot of equations that you have to derive for recycle reactor for first order, second order, second order with epsilon and all that and reversible also reversible also a going to r reversible reaction all these things it is only just mathematical exercise so that is why those mathematical exercises you have to do on your own if you are not still believing then you know i cannot conduct 100 tests you know only maximum 3 or 4 only we thought okay first only 3 we will say first afterwards we will see depending on if you are writing very well why 4th all of you for one person i cannot okay there will be always one person who has not done well for that one person alone i cannot conduct test one, test two, test three, test four and all that so on the average if all of you have not done well then we will conduct another test okay that is not a problem so that is why these mathematics are very important those derivations so now let us take auto catalytic reaction recycle reactor ya okay recycle reactor auto catalytic reaction that means you know why recycle reactor is better for auto catalytic reaction but till now we have not discussed about auto catalytic reaction let us discuss also about auto catalytic reaction by name we know that auto catalytic reaction means the product would have catalyzed the reaction okay so the general scheme that is normally written for catalytic reaction ya r is the product that is for the balance okay so if that is not there then it is not auto catalytic reaction because r is again participating and you know the reaction takes place because of that and if it is irreversible i can write this one as C A C R okay and there are also many equation many reactions that are available in particularly organic chemistry where some names also some of them i will give you later right so this reaction is possible so now we would like to find out whether which react is the best for this so before that we should also have an idea what kind of rate versus conversion graph we get so from this rate what we can first discuss is that initially this is C A not to start with and there may be very small amount of product that would have formed very small amount okay so then that small amount is represented by C R to give a value this C R may be point not not 1 and C A not may be 10 for example so when you multiply that then K is constant for a given value then R is smaller then as the reaction is proceeding R is falling i mean R is increasing more and more and C A is decreasing also along with the reaction right so that is why this product we will first go start with lower value then go on increasing reaches a maximum where C A and C R values are sufficiently large and the product is larger then afterwards C R will be increasing but C A will be decreasing and finally it may go to almost point not not not 1 so that it will again rate will be decreasing so that is why if i plot minus R A versus C A other thing i will also tell you ask you this is rate versus time these two okay so first tell me this one how does this look like yeah initially it may be because we are this side or this side i have to start this side why because this is C A not okay that side C A not then it may increase like this and then finally it may go to 0 also because when C A equal to 0 C A equal to 0 so that product will be 0 so the direction we can show like this with the time how does that look like same parabola yeah so at time t equal to 0 i may have some reaction because i have some C R left otherwise it will never react okay some C R is there so it may start and then go to like this it may go to okay so this is the one okay yeah so it seems in nature it is also found that you may start with A there is no product right you are not adding any product there and on its own there is a route where a little bit of R is formed and then that R once it is formed then it starts again auto catalytic okay so anyway different schemes are there but i think what we think is that anyway whether we have R in the beginning or later our reaction starts only when you have sufficient amount of R which is now started catalyzing the reaction good okay and if i want to plot this as 1 by minus r A versus X A 1 by minus r A versus X A now tell me how do i S shape yeah puja says like this thereby and says like this S shape yeah any other shape there are infinite shapes yeah which is right why did you say yes you saw in the book which book is that leon spiela do not blame leon spiela i said poor fellow huh yeah puja why did you say this way you have to explain no otherwise simply you cannot say but this is C A this is X A no that is why this is X A that is C A huh starting will be left butter what is the shape yeah okay so it also goes like this okay but it need not be symmetrical that depends on stoichiometry and all that it need not be symmetrical okay but under some conditions you will also get very symmetrical good so this is the one now when i have this kind of 1 by minus r A versus X A which react is the best which react is the best because you know this i tell you i also told you earlier that you do not have to learn anything new great concept now onwards it is only delta X here and there right so i think whatever you are supposed to learn in C R U already learnt basic concepts but those things only either you are combining or subtracting and you know the concepts and then finally you have to solve the problem that is all what you have anupriya which react is the best anupriya i was asking which react is the best huh X A X A okay agree with you there where depends on X A C C i said which reactor is the best first one one reactor afterwards we will see P F R okay so P F R what is the area i have to take where so if i have let us say this is X A F yeah that is X A F so total area under the curve i have to take right yeah that is not bad okay that is not bad someone was telling that depends on conversion or something to anupriya yeah so what do you mean by that say if we be the minimum of that curve then if we are taking M F R then that area will be lesser than yeah definitely what you said is right it depends clearly on the conversion at which you are trying to do the thing okay so if i take that the conversion is corresponding to the maximum rate somewhere here this is the maximum rate so that is why 1 by R is minimum okay 1 by R is minimum so here if i have somewhere here then C S T R is the best so we think that always C S T R is very bad no normally it is giving large volume and all that this is one case where C S T R is the really best okay so that is why normally what we can say here is the reactor selection depends on whether you have small conversion or large conversion so when i have small conversion so that means i have similar versus X A so then you have something like this and till here if i take anywhere between you know this point this is the conversion which is corresponding to maximum rate X A 1 i say X A 1 corresponding to where X A 1 corresponding to maximum rate so till that point always mixed flow is the best this is mixed flow M F R and if i take P F R here this is the total area this entire area okay P F R okay good so when i have intermediate conversions intermediate conversion means you know somewhere here till here so when i plot that so X A versus 1 by minus R A like this so my conversion corresponding to maximum rate is somewhere here X A 1 but i am interested somewhere here okay so that means anyway again for P F R i will have all this and for M F R from here to this is M F R so sometimes both may be both areas may be same then which reactor you choose if conversion is intermediate where this this area okay i have here again M F R and P F R both areas are same equal to okay sometimes you may get that you know in between yeah which reactor you choose Swami yeah you tell me whichever is more economical which is more economical how do you say that it is giving same volume M F R is why what do you mean even even for P F R also one cylindrical portion only required that is what he is telling Abhishek telling you know go for whatever is the cheapest yeah but other than cheapest do you have any other criteria for what temperature control okay temperature does not matter i think you know i can control then what is the thing i am removing that restriction also okay temperature control is not very that much crucial for me somehow i will manage is there any other point yeah which is easy to operate M F R why P F R is difficult to operate because i have to i have to explain all the yeah there is no ideal P F R anywhere it is only in our mind correct no it is only in our mind ideal P F R where is ideal P F R right because as long as you have walls you have some liquid which is sticking to that the velocity profile is different there near the wall so that is why theoretically there is no particularly for you know liquid and gas flowing through pipes right as long as but whereas if you have coal and then you are burning on a what is that conveyor belt and all that so then you will have definitely no problem i think excellent plug flow you can have that is why whenever you have this kind of pipe flow for homogeneous reactions theoretically there is no i mean plug flow the reason is that the velocity flat velocity profile you get only when you have velocity equal to infinity theoretically infinity okay so that is why reason why whenever we have a choice between P F R and M F R people jump to M F R okay so that is why so the next one is next alternative is high conversions so that one we have 1 by minus R A versus X A similarly i have again somewhere here we have X A F now which reactor is best P F R because only this area that is next that is next yeah so this is P F R M F R will be this one very good okay now we will go to combination of reactors these are the individual reactors what we have either P F R and M F R so now individual now i think you have become master so i think i do not have to take much time to explain this is 1 by minus R A versus X A so the best thing is till maximum rate yeah maximum rate M F R and then till this X A F P F R yeah first C S T R then we have M F R okay so here i have X A 1 X A 1 that is the best setup 2 right there is another best setup also if you bring mass transfer and reaction together what is that best setup yeah up to maximum rate we put 1 by minus R A versus X A this is the one so i will put a C S T R okay so then i have here that is X A F right this can go back again that is okay right so yeah able to follow sorry yeah what is happening here i want my 90 percent conversion that is true my conversion may be 90 percent but what i do is i conduct the reaction only till X A 1 and use either absorption or distillation procedure to that is what you are doing in distillation no you are only just increasing the product or one of the components purity right so that way you can now go to X A F and this is X A 1 so if you are able to combine these 2 then we have the best thing because reactor volume is decreasing it does not mean that this is economical as you said finally finally economics only either this or this or individual reactor or the next one is recycle reactor okay good so physically discussing why at this point for example okay this one why it is giving that is the best reactor what you have if i operate this one as at X A 1 okay X A 1 why what is really happening there why now suddenly this inefficient fellow has become very efficient or in this insert now we are saying that mixing is better for this reaction correct no earlier we say mixing is not good at all now we say mixing is good you know that much physics we should we should be able to imagine a little bit why earlier we were telling that you know mixing is very bad for reaction and all that but now we suddenly say that mixing is very good you go for only mixed flow but you can tell any idea not able to imagine can you tell what is the reason what is the reason why mixed flow is very good now for autocatalytic reaction what do you mean by probability and we are deliberately mixing both because there you know when you are continuously feeding what is happening the fresh reactant is mixing with the product where we have that product conversion is yeah X A 1 not very high X A 1 very high means again it is becoming very inefficient okay at only one point it is excellent okay yeah because you are mixing product with very simple thing is this equation combination of this C A C R is the best in in uh mixture flow reactor and how many how many rates you have in that how many rates are there in this system only one rate which is equal to the maximum rate right so if you take any other rate it will dilute correct no you will have different conversions so that is also the reason why plug flow is bad here you know all this area plug flow is bad because there are so many rates those rates are not good here right so that is why uh this extra area will come because along the length of the p f r you have so many rates whereas here i have only one rate which is the maximum rate and i am able to operate the system only at that maximum rate so it is not you know no contamination no dilution anything nothing so that is the reason why this uh you know every dog will have its own days people say you know so this dog has its own day mixture flow reactor best so at least it will be proud i mean every one of us in the nature you know should be proud so that is why this is the one of the best reactors okay if you understand this then going to recycle reactor is easy another possibility for autohydrolytic reaction is one reactor okay but you see here here i have two if i want to go for slightly higher conversions right and here also i have two maybe mass transfer and reactor both this is mass transfer equipment maybe distillation column and this is the one but if i go to actual recycle reactor then we will have only one reactor but only thing is recycle you have to you have to put a pump and then recycle it to the inlet that is all what we have there so why it is better than as one reactor sometimes it is better sometimes only it is better you have to again calculate the overall economics why it is better is that for autohydrolytic reaction you need some product for reaction now if you are able to choose that recycle ratio where you will get the optimum recycle ratio so that inside the reactor you are going to have it is a plug flow reactor the average of all those reactor all those rates are very high the average rate you know i do not know still you are able to get me or not when you are doing integral d x a by minus r a that means you are nothing but you are averaging all the rates you are trying to average and then you will get that so in normally n greater than zero that average is more for plug flow reactor that is why you get more conversion for a given volume or vice versa and in mixed flow because you have only one rate and that rate corresponds to your outlet rate which is x a f that means rate is smaller no x a f is 90 percent rate is small so you are able to operate the mixed flow at only one rate which is the lowest rate possible for that reactor because you have fixed x a f equal to 90 percent so now what is the volume 1 by r a correct no x a by minus r a equal to v by f a not so that is the reason why you should have automatically very large volume for the reactor okay i mean again i am repeating the same concepts only okay that is the reason why and because you should not forget you know these concepts very simply beautifully can be explained all these right so that is the reason why we are not able to get very high conversion for a given volume or for a given conversion you will get more volume this is for n greater than 0 n equal to 0 which reactor is the best both are both are best now you have to give me why physical reasoning why both are best that is what is always required i say that physics that physical reasoning i have been telling you know very typical i ask her everyone answers right it or wrong except her e by f a not will be same why i am asking you are talking mathematics i am talking about physics we should have chemistry together no better chemistry they say you know if two people work in team means you should have better chemistry that is what everyone uses i do not know whether they understand or not but anyway so everyone says that yeah that team has excellent chemistry that is why it won okay what about physics we do not know what about mathematics we do not know so i think see me you are telling about v by f a not equal to something mathematics i am asking physics unless our chemistry is good you cannot answer that is also there yeah okay i think puja puja try to say something that is very simple see why what is happening is you know you would have got that point because at this point of time you should have not got that to your mind but we know that we feel that why because for zero order reaction the reaction is independent of concentration and how p f r affecting concentration how m f r affecting concentration m f r affecting concentration because it gives the lowest concentration okay corresponding to that outlet concentration whereas in plug flow you have a concentration history from starting to c a not to c a f there is again concentration history the overall rate is again definitely better than this m f r that is why we are getting better for zero order it does not matter concentration is not coming into picture so whether you mix or do not mix it is same that is why you have zero order for both same because these things physically you have to explain not mathematically mathematics also required but i think first physics then mathematics right so that is the reason so that is why if you take the recycle reactor now okay recycle reactor now what is the objective now you see we have two things now we understood what is recycle reactor we have an equation v by f a not equal to that entire thing right and now we have also understood what is autocatalytic reaction and we now say that autocatalytic reaction definitely needs some product to be formed now the question we have to ask is the conditions that are going on inside plug flow element of a recycle reactor depends on how much you are recycling yeah how much you are recycling that r now you have to choose that r such that your volume is minimum for a given conversion what is that r what is that r which gives me minimum volume for a given conversion we can do the other way also for a given volume what will be the maximum conversion okay i think either this problem but i think let us see only the volume thing puja you are able to define the mathematics now i am talking about mathematics okay yeah so now what is the mathematical condition for this first of all you understood the condition yeah why why why why recycle ratio i have to choose i am asking sometimes stupid questions yeah autocatalytic reaction needs some amount of product now this product is coming through recycle what is that recycle ratio which will minimize my total volume that means you know maximizes their r throughout the reactor throughout the because it is average okay throughout the reactor that is the mathematical problem now so what is the mathematical condition double derivative okay double derivative will come first what is the first derivative yes so that means the condition here is i have d v by f a not by d r equal to with respect to what i have to differentiate with respect to r because that is what what is the optimal recycle ratio optimal recycle ratio which will reduce my volume to i mean lowest minimum volume so this is equal to zero okay and one can write this also as tau by c a not that is okay right so that is the mathematical problem now so how do you solve this problem so whenever you of course i have where v by f a not equal to zero anyone remembers to smitha r plus one into excellent r plus one into well r by r plus one x a f to x a f d x a by minus yeah so now you have to differentiate okay which is not a simple task that is why i think really like levenspiel he gives again some mathematical clue for us there is a formula called leibniz formula for this kind of integration so the reason is here this d r also present in the limit in the limit okay so the condition levenspiel gives for this kind of if i have a function f r this is function f r right yeah so then with limits where the variable with which we are differentiating okay is present here right because the boundaries also are changing this is boundary this is boundary limits okay when you have that kind of thing so yeah this one will be x r d x so now the differentiation of this function is d f r by d r equal to integral you have to sincerely follow this and then substitute and tell me the answer a r b r dou of i mean differential partial differentiation of x r by dou r into d x that is one term plus this function this function this function b r that is upper limit into d b by d r b is the upper limit d by d r minus i also have a r into d a by d r so what you have to do is now you have to get this term for this function okay and i have the lower limit lower limit upper limit even lower limit is very i mean upper limit is very happy because it is not a function of r so that will become zero we like zeros except in the question paper answer paper okay answer paper we want zeros but you know one zero zero okay so now you have to have this term is not present for us now you differentiate have this term and then this term tell me quickly because i am asking you to do because you have to participate in the class you take this function as it is you know that function is now one by minus r a that is what is function that function is one by minus r a you do not have to substitute r a as first order second order third order that i will give you in the examination but this is different this is only this is only straightforward now you identify that function first what is that function one by minus r a okay this you have to take inside r plus one by one by minus r a i mean that r plus one outside so i forgot sorry that has to go inside that is the function okay so now this f of r f of r is now r plus one by minus r a right that is the one now it is must be easy okay tell me what is the first term that is the first term right because i think only r plus one you have to because it partial differentiation with respect to yeah with respect to r so that means dough actually you have to only r plus one dough r d of r plus one by dough r dough of r plus one by dough r that is one so then the remaining function is only minus r a okay this one one by minus r a that is one yeah next one zero that is very happy next one r plus one by minus r a this is at x a one that is at the entry which is equal to of course r plus one and all that also let me write this one is x a one lower limit because i am leaving sometimes with lower limit yeah this multiplied by there is r by r plus one this term this term is only r plus one r plus one divided by minus r a because your function you know what is this function this function is this as it is that is all copy we are experts in copying right i think maybe not from the board from others answer paper maybe okay so this comes as it is no i mean there is nothing wrong anything great thing that is involved but only thing is at x a equal to x one that is all yeah so that is the one this is the equation what we have but now you have to differentiate this fellow what is this d x a one by d r equal to this is d by what is the equation for this r by you differentiate this very good so this is equal to x a f divided by r plus one whole square this one differentiation very simple differentiation no i think they are not difficult at all okay so now but anyway i have to substitute this is equal to zero finally right to be optimum then second derivative we can check whether you are really getting minimum or maximum okay depending on the sign you will get but this is the one so now there is a nice exercise of saying and arranging this equation so i will substitute here first of all x a f by r plus one square so one this one this will get cancelled so then what do i have here this a is this one minus a no minus minus that is right it is minus only is right yeah so this is minus so then i have equal to zero if i put i am just simplifying this one x a one to x a f d x a by minus minus r a equal to this one is r plus one yeah this is at x a one this is important yeah okay okay i am just writing again yeah so how do i eliminate this fellow r plus one i do not like that fellow intensities to calculate r but i you know for me to get one condition i do not want that r how do i eliminate that then that will give you a very beautiful condition you have to eliminate that condition i mean eliminate that r from the derivation v by f not is coming there okay i will give you the equation can i say r plus one equal to x a f by x a f minus x a one how how do you say yes because i have written there yeah yeah yeah please do that you know i am a very dangerous fellow this alone will be separated the small portion five minutes okay so that you have to arrange that and then only you have to find that okay good so now i want to know happily remove this that means what is that i have to remove x a by r plus one now x a f by r plus one equal to yeah it will not get cancelled okay cancelled means i am just taking this x a f by r plus one equal to x a f minus x a one so now the condition is if i do that wonderful condition one by minus r a at x a one okay x a one equal to x a one to x a f d x a by minus r a i am just writing this equation minus r a divided by x a f minus x a one what is the meaning of this condition this you got no no problem i think after substituting here and rearranging who can tell the physics of that this mathematical equation yeah this is again you know simple calculus only how do you find out the average of like for example temperature varying with length if the temperature is varying with length how do you calculate the average average temperature temperature is varying along the length what weight average how do you find out temperature into temperature into temperature into length that is sigma of yeah okay that sigma if you are able to extend to integral integral t d l again another integral that is zero to l okay that is just you know we are only talking in air but i have not written there but are you are you really familiar with that because this is where is missing you know from you not only from you from all these students that relationship between mathematics and physics okay and this is the one average you should have done many times like exactly what you said you know yeah like if i have some temperature changing with length okay so the average temperature for example t bar how do i calculate integral yeah so some function this this t is a is a function of x because t is changing along the length okay so then i have dx where this is zero to l divided by l here or simply one by l divided by l or the same thing no yeah so that is all i mean that is what is exactly told here so that means what Ramakrishna told is correct okay so this condition is a wonderful condition i think please take down the condition okay in words the above equation i think you are writing below this you know that is the above equation okay yeah in words the above equation indicates that the optimum recycle ratio introduces to the reactor a feed whose one by minus r a value equals the average one by minus r a value in the reactor as a whole i know normally you would have written without thinking what i am trying to say okay now someone has to explain this in words the above equation indicates that the optimum recycle ratio introduces to the reactor a feed whose one by minus r a value where is that whose one by minus r a value which minus r value are talking right hand yeah what is left or right left hand side exactly this is the rate okay yeah yeah at x a one at x a one right that is what whose introduces the value whose average rate value average rate equals equals the average one by minus r a of the entire reactor this is what this is x a n x a n x a one entering the reactor x a two or x a of leaving the reactor this is the average that is for the entire reactor so the optimal recycle ratio introduces a rate because when you mix the recycle ratio as well as the f a not coming from the fresh stream those two rates must be combination of that must be this rate okay so because i am mixing two streams know so i have a rate also there average rate so that rate must be equal to the average rate throughout the reactor when when when that happens you will get the minimum volume for a given conversion it cannot go wrong because it is only mathematics mathematical equation because this is the first one and if you want to prove that whether this is really true take this same thing second derivative you will get negative slope second derivative must be positive or negative positive for minimum yeah right right negative for maximum okay here minimum volume okay so that is the one


In this study, researchers examined ticks collected from free-ranging domestic sheep in the southern region of Hubei Province, China. They identified 16 different tick-borne pathogens, including rickettsia, anaplasma, ehrlichia, beryllia, thyliria, and hepatizone SPP. The most common pathogen was rickettsia japonica, which was detected in 13 of the ticks. Additionally, researchers discovered a new ehrlichia species, which had not been previously reported in the province. This study provides valuable information on the presence of tick-borne pathogens in the Hubei Province region of China, and can be used to inform future control measures. This article was authored by Zhong Xiaotang, Yan Shui, Na Zhao, and others.


All right, Sabra Traders, welcome on back here this Thursday. I can finally officially say it's Thursday at least. March 31st, shortly after 2.30 p.m. Eastern time. Great to see all of our students live inside the Cybergroup room. Great to see all of us as well on social media. And I can say finally because I've been thinking like this whole week ahead, like Tuesday as if it's Wednesday, Wednesday yesterday as if it's Thursday. It's been a long week. Great to see Gary, Felix, all of us otherwise live inside the Cybergroup room. I know Norman picked up 15 cents. Not on the LGVN here, another stock, NNOX, which we'll get to in a bit. Felix ended up picking up just over a dollar on the LGVN here just now. He was in from 11.15. And Gary just got out with about 16 or so. He was in from 12.15, he was in from. So, you know, hey folks, what we'll do is pretty much just cover this stock to begin. And we'll just go right from top to bottom otherwise. We don't have class this afternoon, but I do have a coaching call at 3 o'clock. So I want to make sure I'm ready to go for that. But with that said, LGVN, man, ended up making a big push pretty much as soon as the market had opened up. But from there, came back down. It started to get really choppy. And, you know, normally with that in mind, you would hope to see this type of run. But it's not guaranteed, you know, oftentimes for a stock that's already up, you know, what was it, like 35, 40% pre-market? Well, you know, you tend to see it dump back down a bit. Not everything just continues to run like this would after the open. So with that, it was a little, you know, indecisive. But we ended up seeing it begin to really squeeze once it broke that top, roughly off of 10 and 970 from pre-market that was. And then ended up really going from that point, accelerating up towards just about 12 and changing. From there, though, that's where things got a little dicey again.  I did well in the first run up, and I ended up leaving a lot of money on the table there too. I picked up just about a dollar, but I ended up, you know, just leaving a little on the table. It's all right. Well, came back down. Well, I stayed away from this trade up until, I think it was like two o'clock even, maybe 205 Eastern time. I ended up jumping in. I was off to a good start, roughly off the 11 level, 1090 in fact it was at.  Essentially, I would call it a break even. But I stayed away from it again. I thought it was going to tank. I thought it was going to drop all the way down to 10 at least. So completely took me by surprise with this new run up, new run up you're heading into the afternoon. So for right now, obviously we're going to put this on the watch list just to begin. It'll probably be at the top by the end. I'll just simply say this. This is just free advice for pretty much everybody. We expand upon this a lot further throughout the phase one, two, and three curriculum. But it's to say for a stock moving like this throughout the day, and you've seen it happen on two separate occasions already here with the LGVM, for a stock that continues to go and go and go, you begin to wonder, when's it going to begin to top? And the question, as I teach in class a lot further, is not so much when will it top, but more where will it top? So with that, I would just keep the whole number levels in mind. You're looking at 10, 11, 12 just earlier, now 13. So you could see it basically move up towards 13, 1277 there at the peak. I don't know if there's another iceberg order perhaps under 13, but I would still assume 13 to be a major resistance heading into the afternoon here for this trade. It's been a lot of talking. My God. All right, let's go from top to bottom here otherwise. For any of the other stocks that ended up running, like the SABS trade, CLBS, a bunch of others here. We'll just kind of see what's doing. All right, the first of many water breaks. With that, the SABS trade, I know Will was looking at this trade, at least going into this meeting. I was asking all of our students inside the chat board, just, hey, what are you watching right now? So Will said the SABS, and at the time, I wasn't watching it, my first looking. It was looking pretty good. Well, it was beginning to make lower high since pretty much like this wedge or pendant pattern that you can kind of call it. But yeah, with that, it needs to make another big pop soon.  And I'll say here, as I typically say on a lot of these stocks, and I could have said it on LGVN from earlier. But when the volume dies off on a stock, typically, so does the stock, so does the trade. So be on the lookout here for a bit of a shake down here off support. Hopefully it ends up running like the LGVN and it makes another pop sooner than later. But yeah, we'll get this a look, SABS. All right, we got the warrants for ISPO here. We're gonna skip over any warrants or whatnot. But ISPO itself, you're down a little bit lower on the gainer side. We'll jump to that in a bit. The COVS trade, hey, this one for right now, it's dropping off a little bit right now. But yeah, I mean, it's not as good of a pick for the afternoon. I am in this off of 235 exactly right from here. So I'm just gonna keep an eye on this on the other screen. But I wanted to see if it was gonna begin to make a move off support. It started to, but it's just been flat since I ended up getting it on this trade shortly after 215. But otherwise, just because I'm in it, doesn't mean I'm gonna put it on the main watch list. This is more of like kind of like a hopeful type of move. If it ends up popping during this meeting, then I will put back on our list. But let's see what we have here in the meantime though. The CPSH trade, hey, this one looks good. The chart looks all right. It's a double top at the highs, but it's only trading about 3,000 shares per minute. Not really a whole lot going on with that, right? So, again, I'll even come back to this at the end though. I would wanna see more volume traded across this year. Going into the afternoon, ICVX, not a whole lot there. Jagex, not a whole lot happening there, I can tell. We'll keep it going. I see Norman's trade, the NNOX stock here. So we'll take a look at that next. IMTE ended up making a nice move from earlier this morning. Drop down at first, but then made that kind of famed slingshot type of move, broke under and over from 18 and then completely took off up towards 30, 30 plus. All right, so Norman picked up 15 cents. He was in on the NNOX trade. Just going up here on the chat. So Gene just picked up 10 cents on the ISPO. Norman ended up getting 15 cents from 11.55 as his entry. So this was from prior to us beginning the meeting. Great exit at least from Norman there. Ended up dropping down. Looks like it kind of broke under and over that resistance you could just see from the chart. What is that? 11.45, 11.50, just kind of the highs here. This could be a nice little trade right now. Now, if it pulls right back down under that same very level, then false breakout, I would expect a lower low should that happen here. So I'll come back to it at the end. It looks interesting, not fully convinced just yet. If it's a false breakout and it dumps off, then it would be worth it. CELZ kind of just call this a tradable stock. Ended up making a bit of a choppy move throughout the morning. Nice little bounce just going into the early afternoon here. So it's a sideless stock for right now that pops more like I always say during this meeting, then we'll come back to it. That's why I wanna save the list for stocks that look like the WWR for right now. All right, so this one's a no-brainer at least to put it on our watch list. Nice breakout here from 205 up to 227. At a 44,000, 45,000 share iceberg order on the ask at 229. So just keep that 229 level in mind here on my level three. Now, when WWR moves at times, we tend to see other like energy type stocks look to move, Pola in the past ended up making a big move with this WWR. There's one other setting SunW either doing Jack right now. All right, maybe it's new specific to the company. Who knows? Yeah, WWR looks great, the stock at least itself kind of skimmed down the remaining parts of this list here. The ISPO, I know that Jean just picked up some money on that just before. Ah, it's like a flat move right now. It's kind of looking like my CLVS from before, right? So, I have my stop set now on the CLVS trade just so you folks know I didn't have it set as I kind of went through that. But the ISPO is like, probably a hundred times more volatile in the sense of the lack of liquidity on the order book. So with that, I mean, just this stock had begun to make a bit of a shake down within a moment's notice. I hope that's not the case. You know, it's just flat otherwise. So for right now, I'm not really fully convinced, but you know, who knows maybe later on. All right, we keep it going. GOED good chart trading about 70,000 shares a minute. And I'll tell you, looking at the order book, that's not really too little. I'd say that's all right. This thing looks interesting for right now, but it's a little slow, you know? So if it ends up dying off after this meeting, then it's scratched off the list. But for right now, it's in good standing here, good faith. So I like this little push so far in the GOED, perhaps on the way up to test two. Let's see what else we got here to finish up. ITM, CLVU, a couple of familiar names at least. Ah, this thing's not looking good. All right, so with that, I think it's best to just hop on over to the loser side. Market's been trotting on down at least, you know, steadily heading into this meeting.   PATH was a nice short from earlier this morning. Now it looks like it's trying to make a little bit of a dead cap bounce, you know, trying to grind back on up from like 2050-ish, broke back over 21, and moving back on up here towards the VWOP and pretty much 22. So, as far as the tradable stock, doesn't hurt us to put this on our list. The PATH trade, still shortable.  So this could be a nice continued move up towards 22.  Let's see what else we got here. SC or SHCR, we have Vnet. Just easy to borrow trades, just looking at here pretty briefly. I can just tell nothing really else that looks too much like a familiar name at least. You know, I mean, there's definitely a lot more that's down here. I'll just kind of take a quick scan, quick look. YI's ETF, if I'm not mistaken. Maybe, maybe not. Either way, the chart doesn't look good. All right, I think that's pretty much it. As far as I can see, I'll go through some side list stocks now. At this point, so the NEO trade, this stock was a great short for earlier this morning, broke down below 22. It actually broke under a stack of iceberg orders that popped up early in pre-market. So that ended up happening just minutes right before the market opened up. And from there, when the market did open up, just completely tanked, gave me no chance to try and short it from those price levels. And then from there, I had to try and readjust. But for 21.50, I ended up getting it on this trade. It was for about 35 cents at the time, 30 to 35 cents that it was around. But I ended up leaving money on the table, continued down towards just about 2080, 2075. Right now, if it was at the lows, I'd be a lot more interested in it. Spy looks like it just wants to continue to break down. It kind of just pushed up a bit and slammed right back down to the lows here. It's been holding above American Airlines. Actually having a pretty decent day comparative to the Spy. CCL too. CCL, I did call out earlier today, at least heading into the late morning, making a really nice push up then. And right now it's kind of hanging in there. I don't know if news came out, earnings or any sort of upgrade, downgrade, but yeah, I'm gonna have to stop down, by the way, at CLVS minus one, but that wasn't really looking to go anywhere. I was hopeful for it to make the bounce. The LGV entry looks really good still, folks. That's already on our watch list. One of us just on YouTube chatted that to us here. Mark calling out the LAC trade. Yeah, LAC looks really good. Wow, I mean, I guess it wasn't up enough as I went from top to bottom on the gainers list, or was it? And maybe I just kind of skipped over it. Yeah, it was, towards the bottom of your LAC. Yeah, this was a really nice run from the last, or from really yesterday, really approaching all-time highs, I think, right? Just broke over 40 for the first time back since it hit that high. So let me just get that all-time high for us here really quick. That was back from the end of last year. 41.56 is technically the all-time high. Still has a little bit of a ways to go, but it's getting there. Relatively speaking, it's pretty close. Keep this in mind, not only for this afternoon, but really going into tomorrow, going into next week, if it can hold kind of strong towards there. All right, that was a lot of buying off at 40, by the way, so off the first test of it, you'd expect for it to fail. Well, let's see what happens going into the next hour and 15 minutes, because I feel like this trade's not over with yet. All right, Donald, nice catch. Donald on the LGVN, at least picking up 10 cents. It ended up pushing up a little bit higher, but don't look to jump right back in. Look to kind of reassess. The LGVN trade's actually on the way up towards that 13 right now as we speak. So say what, we got a little time. Bitcoin ended up dropping off a tiny amount. I wasn't planning on doing a whole analysis type of video as I would here in this meeting, but it dropped off down towards the 200 EMA on my hourly chart, holding above there pretty nicely for right now. So as I kind of teach in stocks, if it's not going to break higher at the time, there's only one other way it's going to go. So Bitcoin failed to continue to make that big pop and pull back a little bit, but I'm still very bullish, at least on the short term move here. So I'll come out with another video over the next couple of days on Bitcoin. Still looking good. In fact, actually, I'll probably do another stream later on tonight. So we'll actually do that. We'll jump back on YouTube live stream later on this evening. More of a chat, no audio base just yet. A lot of talking throughout the day as you can now tell throughout my stutters during this meeting, but otherwise it's more of a chat type of session on YouTube later on this evening at six o'clock. If you're interested in joining that, just subscribe right to our YouTube channel, youtube.com slash cyber trading you. Just have the Bitcoin chart up with alongside a couple of others. Ivan, how about that? One of our members joining us here inside the trading room. Ivan picked up just about 20 or so cents on the TISI. Let's take a look on that. Wow, the LGVM blasted over 13. Off the retest, it broke above it, pulled back, and then when it re-broke above it, this is just being just the next bar, but there's your higher high for right now. TISI, as far as a day trade, I don't know, I mean a great trade from Ivan. Phenomenal catch from Ivan. This seems like from bottom to top.  It's not really looking like two, you know, momentum packed here, heading into the final hour or so of the day. So very nice trade from Ivan. But for right now, I'll pass on this. From Linda, the PLPX or BLPX, I think maybe. PLPX, maybe I'll type something. BLPX. If it's the BLPX trade, Linda, let's see, it's up 11 percent, but there's no volume to it right there, so pass on it for right now. Oops, she corrects herself, PLXP, there we go. Nah, not really doing much either. You gotta have a lot more volume than this traded across the day for us to be interested in it. You know, and volume's not the only criteria. So you know, that's something that we do teach throughout the phase one stock course. You know, we talk about that throughout our scanning classes. We have another class called tradable, not tradable. You know, just breaks down the basics of, you know, what we look for in a trade altogether. Yehuda, on the LGVN trade, you got about 30 cents on that trade. Got it in right from over 13. Cool. Johanna says, Torey could move voting on marijuana possibly tomorrow. You know, Torey's more just a sideless stock for this afternoon, but should that be the case? Then we'll definitely keep it in mind for tomorrow morning. If it was making a much better move right now, like as I'm talking, I would be more convinced, you know, but for right now it just looks like it kind of normally trades just kind of a sideless stock. Hey, if you wanna follow it for us or if anyone else does really well until Ray, you know, day to day, more week to week, then hey, put it on your personal watch list. It's definitely, you know, a tradable stock. This is a rather more follow compared to some of the others at least, right? But you know, I like the list so far though as is. I feel like we're pretty good. Even that GOED, like, let me go back to that. That's not looking like too great, not too fast moving, but you know, it's up over 8%. It's at the highs at least, it hasn't dumped off yet. So we'll keep this on our list for right now. The CPSH, I kind of had on the side, it's at the highs, but this one's trading less volume per minute. So, you know, I'm gonna pass on this if I'm gonna put the other on. But then the NNOX for right now, this one's trying to make a squeeze back up. This one I will put on our list. The NNOX Trit, at least for right now, kind of going back to those stocks I'd said I'd get to at the end. All right folks, for all of a sudden, Facebook Live, YouTube, as always, I appreciate you sticking with me each and every day, each and every afternoon.  A little under the weather also. So hey folks, I appreciate you even more. So if you have any other questions, feel more than free to send on over an email to josh at ctutrading.com. That's my email address. I always like to post here at the empty streams. Click post, give me a quick second here. It's taking a sweet time. But for Johannes, for Norman, for Grant, for Yehuda, Linda, Ivan, and all of a sudden, otherwise I look forward to talking to you folks coming up right at 330 Eastern. Talk to you soon.


Hi, everyone. Welcome to today's talk on the art of product management. The reason why I chose this title is because in today's world, as many of you either know from experience or are studying at school, product management often becomes a lot about measurement, about doing quick experiments, about data, about just making sure that every KPI, every metric can be quantified in some way or the other. But I think there's a huge portion of product management that is more than just science, it's art as well. And I think it's the combination of those two things that can actually chart paths to success and have a fruitful career in the field of product management. So today, we're going to be talking about the art of product management and more specifically soft skills. But before that, a little bit about me. So who am I, right? My name is Rohan. I have been in product management for about 12, 13 years now. Currently, I'm a product leader at Amazon. I have worked from the start of my career in the semiconductor industry all the way to most recently in cloud gaming and pretty much everything in between. That has given me exposure to various technologies, various levels of people, various company sizes from startups to giant companies like Amazon. And what it has taught me so far is not just what needs to be valued in product management. As I mentioned earlier, that it needs to be, in my opinion, a blend of technical skills and soft skills. But also it's given me this desire to help others as I was helped on my path to try and enjoy the fruits of this career choice, right? So anyone who's looking to break into product management, I'm happy to speak with them, to coach them and to teach them whatever I've learned along the way. And hopefully I achieve some of that in today's presentation as well. So what is going to be today's agenda? Today's agenda, as I mentioned earlier, is going to be focused on soft skills more specifically within the art of product management. So we're going to be covering questions like, what are soft skills? How do they pertain to the product management life cycle? And for those of you who are not familiar with what the product management life cycle is, I'm going to go ahead and define that as well. And once you understand what those soft skills are and how do they pertain to product management, we'll also dive into why they're important. So not just listing them out, but trying to talk through how they can actually benefit you in your career and your day-to-day jobs. And then how do you go about actually developing these skills, right? Just listing them out is one thing, reading about them or building awareness around them is another thing. But how do you go about actually trying to develop these skills? Are these skills something that you're sort of born with? And if you don't have them, then that's it, you're done. Or is it something that you can actually build through practice, through education and learning in general? And then I'm going to try and frame some of these skills. There's actually a lot of them out there and we have limited time today. But in today's session, I would love to narrow it down to a few case studies that talk about how through the product management life cycle, some of these skills that we're going to highlight today and focus on how do they actually help in the day-to-day, you know, whether it pertains to actually shipping a product all the way from ideation or whether it pertains to managing your own career. Hopefully today's examples will be helpful and then we'll end in conclusion. All right, so let's dig in. I'm going to start with this tweet from Adam Grand, who I'm personally a big fan of. If you haven't heard of Adam Grand, he's an organizational psychologist. He's also a best-selling author. I think he's authored five New York Times best-selling books. One of them, I think, is Originals. It's really a fun read. It's an educational read into how you can actually become a better communicator, a better listener, and how you can actually apply that to your day-to-day work. But outside of that, he is also a podcast host. I think his Ted hosted podcast is one of the top podcasts out there. I think it's called Work Life. And in general, when he says, when he talks about soft skills, I certainly want to stand up and take note and listen. So in his mind and the way he defines it is not only, you know, what it pertains to in terms of leadership and communication and so on, but two other things stand out, right? Like, one, that these are what actually make human beings indispensable. And I think in today's climate, when everyone's talking about the resurgence or the reemergence of AI and chat GPT and even in product management, a lot of people are a little bit concerned that, you know, am I going to be sort of AI'd out of a job? Is the AI going to come in and replace me? I think this line around the behavioral, social, and emotional skills are what make human beings in general indispensable. And even in our field of product management, I truly believe that these are the skills that are going to help product people stand out.  But not all that might be the topic of discussion for another day. And I don't want to get into that here. But I think needless to say, in terms of the importance of these skills, I definitely believe that this can give BMs an edge over others who may not have worked on these skills as much or who may not recognize the importance of these skills. The other thing that he mentions here that is very interesting is that these are often the hardest to master. And we're going to dig through this plenty in the rest of the talk today. But this is something that while it's hard to master and while it can take time, it can also be incredibly rewarding for the course of your career. So what are some of these skills? Now, this map is great. I wish I could claim credit for making it. The credit for this map goes to Shreyas Doshi. For those of you who haven't heard his name in the field of product management, a hundred and fifty percent recommend that you write it down, search for it and read pretty much everything that he has on the topic because I think a lot of what he says resonates very clearly. He's articulate. He's got the right skill set and experience to actually educate other folks on this topic. But borrowing from Shreyas's framework, what PM's skills overall are there? And my goal with this particular image and slide is not to dive into each and every one of them. There's a lot to cover here. It's one to generate awareness around this general topic. If you haven't heard of these skills before or if you haven't seen product management skills being referred to in this particular way, this is a great place to get started and say, hey, if I'm going to become a successful PM, what skills should I even be looking to master? And then more specifically, when I talk about soft skills for product management, I am focusing on some of the skills that are in the orange and yellow arrows towards the bottom right, which is when you start getting into the influential communication aspect of listening and writing in public speaking. But also persuasion and presence, right? High agency is another one. How do you, without being able to directly manage people, like let's say you're an ICPM and you're not in no one's really reporting to you, but you still need to have that influence, that authority. You can't quite just force and order people around. You still need to be able to work with them, convince them, inspire them and so on and so forth. All these words sound sort of intuitive in the moment and it feels like you're nodding along to it and saying, yeah, yeah, I need to be persuasive. I need to be a good leader. I need to lead by example. I need to be able to influence folks. But what does it actually mean? How do you, you know, what are some of those typical skills, the individual skills that you need to cultivate and how in order to get to those places? So we'll get there today. Hopefully, I think we'll probably just scratch the surface, but it should give you enough of a lead to go and chase and follow and learn more. But the point of this map, again, is if you're not aware, there is a vast sort of array of skills that you can go and acquire, you can learn. And if you're already focusing on the ones that are really popular in interviews, especially like product sense and execution sense and analytics and product vision and strategy, all the stuff that's on the left hand side in the map, that's great and that's absolutely going to be needed. But the communication critical thinking, some of it may even help during product interviews. For example, Amazon's leadership, the sort of leadership principle based interviews or their interviews around behavioral questions. Those, these skills will help with those as well. But in addition to that, just in your day to day job, this is something that's going to be very valuable. So with that, how can they be very valuable, right? As I mentioned, these can have a direct impact on how you're performing, but what kind of a direct impact are we talking about impact with people in terms of, you know, people within your teams, people that are your peers or people you're reporting to or people outside your organization, most importantly, your customers or partners. Or are we talking about actually being able to ship successful products to market and the answer is both, right? So everything starts in my opinion with building relationships, right? Product management is absolutely a team sport and it's interesting because a lot of the work that you do will feel like it's solo work, right? Even though you're in likely a team of PMs, you are pretty much the owner for your own space. And so from a product management perspective, often it'll feel like you're kind of on your own and you're operating solo. But if you dig a little bit deeper and think about it, you can't really get anything done without building relationship, relationships, excuse me, with your teammates, with your leadership or management or with partners and stakeholders. And so soft skills can definitely help you do that. They can definitely help you do it effectively and potentially even stand out to the point where that starts to get recognized as some of your strengths. Understanding customer needs comes from empathy and empathy is not necessarily a technical skill that you would pick up in your college degrees, right? So it's something that definitely is one of those almost intangible human skills. And if you get better at some of the soft skills we discussed today, then you'll be able to understand your customer better, which means you will be able to build hopefully the right products for them. And then leading various cross-functional teams, people often think that leading cross-functional teams comes down to being the smartest person in the room, having the most domain knowledge about a particular topic or being able to solve technically challenging problems, especially if you have a technical product. But the truth is that leading cross-functional teams actually comes down to understanding people, their motivations of what's driving them and ensuring that you have that in mind, you have that interest in mind and you're also able to communicate your interest to them when you are able to successfully collaborate on some sort of a product or a project. And then of course, actually growing your career. This is, I think, something that I have learned the hard way over time. I always wanted to make sure that I have as many product launches under my belt and I had the right metrics to show for it, the right kind of growth in the right areas to make sure that I show an impact on the business directly. And yes, those things are definitely important. I'm not saying that those are not going to help you in your career, but as you start thinking about making that leap into a senior PM role or from a senior PM role into a group PM or a director and above, the further up you go in my experience, these skills are going to matter more and more and more. It's almost like the weightage around these skills starts to go up and that's why it's important to build these as well and building, in my opinion, starts with awareness. So today, hopefully at least the awareness piece is taken care of in this talk. A lot of, when I've talked about this in the past or I've shared this with my mentees or friends and colleagues, one of the first questions that comes to mind is, is this something that I can even work on or either I have it or not? Like, is this something that I'm just born with? And I have seen this in myself. I have seen this in colleagues and friends. Definitely not something that is innate. It's not something that you either have it or not. It's certainly something that you can work on. And I think the philosophy around this in my opinion, the one that resonated with me was, you're going to have a lot of strengths and skills and superpowers, I think is the right word to use over the course of your career.  In amongst those superpowers, like there's a notion that there's a school of thought that says, hey, you already have superpowers. They're already great. You don't need to work on them. Go work on all your weaknesses. That's one. The other school of thought is, hey, you know, instead of trying to spend all your time developing weaknesses that perhaps were weak for a reason and you may not enjoy doing that. Instead, you should focus on just continuing to build your superpowers because that's differentiating you from others. But in that second school of thought, the advice is not to completely ignore your weaknesses. The advice is to at least bring them to a point where they don't sort of hold you back or drag you down with them. So get them to that good enough point. And I think that's what I have found effective as well. Develop your skills to the point where they're not holding you back that they're at least good enough if you feel like that's something that is not naturally your superpower, right? And I would encourage you to keep that in mind as you think about how to develop your soft skills. And so for example, if you're talking about communication and if you feel like that's something that's never been your strong suit, then think about things like active listening, right? Go look that up. See how active listening can actually be, what it even is to begin with, how can it be developed? And you'll see that it helps you throughout pretty much most aspects of your life. But in particular in product management, that could be something that could really unlock your relationships and your performance as a whole, right? Now, let's talk about the product management lifecycle really quickly. And this is a framework that I will try to bring all examples back to. And hopefully it'll be helpful to track. We know hopefully most of you know this lifecycle, but I'll cover it really quickly. This is not catch all for all PM work out there. There's going to be obviously variations of this, but just for the sake of time and brevity, I have picked an example where you're starting with a brand new idea. Imagine you're going into a new team. You have a brand new idea. You're sort of building the team out and you have to take something from zero to one, which is another very high in demand popular term these days, right? So let's say you started with the idea generation. You have to test out its feasibility. You have to kind of do a market analysis. And a lot of the action at this stage is basically talking and writing and researching, right? You aren't actually building anything yet. From that point, once you feel like you've done enough ideation, you get to the definition phase where you're starting to actually zoom in on what's important and what needs to be done and why and you start to like share that with a lot of your teammates. From there, you go into building and testing the concept as early as possible, hopefully putting as minimum effort as needed so that if you need to make big changes, then you don't have a lot of wasted investment. Then you go on to validate that idea with the market and if you get good feedback or even if whatever feedback you get, you make the changes to the product and then if all your criteria for launch is met, you go ahead, launch it to the right customers via the right channels with the proper strategy in place and eventually after launch, you go ahead and you figure out ways to track the product post launch but also think about growing it in a way that is sustainable for the business. This is something that most of you should already be familiar with. So how does this pertain to the soft skills that I've been talking about so far? Let's take a case study of leadership as an example, right? I'm at Amazon right now. Amazon has 16 leadership principles. So that's a lot of them. There's a lot of ways in which leaders can be defined and leaders by definition don't have to be people with exact titles, right? Director VP and above. Leaders are folks who can essentially lead in any situation. You could be thrown into a room of people that you've never met before and you can recognize what the room needs, what the problems are, why they're dead together or perhaps even facilitate that conversation and you could naturally take on a leadership role. And so one of the favorites of mine in that list of 16 is Earn Trust. You know, I won't go too deep into sort of explaining and defining it. It's a little bit self-explanatory, but in the interest of Earn Trust, how does one build the skills, what soft skills are even needed? First, let's say earning trust and how does that pertain to the product development lifecycle that I had just talked about? So first of all, think about things like putting others' interests before yours, right? How do you earn trust with someone? You don't go in into a conversation or into a group setting with a very prefixed agenda, right? You try to put in the work to get to know who the people are that you're with. You get to learn their interests. You lead by example, right?  You don't just try to take all the credits and the plots and paint yourself as the most positive successful person ever. You actually go ahead and own both your successes and failures, right? And then be consistent. You repeatedly do what you actually say, put in the work, right? Don't just show up saying, hey, I'm the product manager.   Go ahead and do the things that you're supposed to do and just tell me what the result is. Take a little bit of interest. Do some research in their areas as well and understand where your partners are coming from and just keep doing it over time. It's a little bit of a grind, but it's the work that will earn you the trust that you need to be both a good teammate but also a leader that your teammates are looking to follow. And how does this fit in into the actual product development lifecycle? Especially in the early phases, when you're coming up with ideas, when you're ideating and you're brainstorming and you're looking to define where the product is going and you expect others to follow you, it's not just the strength of the idea, how innovative that is and how impactful that might be to the business that would get the kind of attention you need from your teammates. It's also your track record as a leader, which is why often if you're brought in brand new into a team, into a space, this can take time, right? No matter how successful you are, no matter what your track record is in the past, if you're put it into a brand new situation, give yourself time to establish yourself as a leader on that trust so that then the team can truly gel and deliver innovation at the rate that you're looking to deliver. Another one, another pillar. And as I said earlier, we're just going to cover four case studies today. There are many, many soft skill areas that I think are important in the art of product management, but for the sake of time, I've sort of nattered down to these four. So after leadership, the next case study I'd like to focus on is teamwork as a soft skill. How do you become better at teamwork? You know, there's a communication piece to it. You should ideally over communicate, right? When there's a need to actually share what is it that you're up to, whether it's in terms of product vision or strategy or whether it's in the form of status updates for where the project or product development life cycle is, make sure that you are going overboard in communicating because silence is worse than getting too many pings on the status of something. Make sure you have empathy for where your teammates are coming from. Don't just go in and have a my way or highway attitude. Resolve conflicts quickly. This is a huge one. I can't stress enough how many times in my career so far, I have been in situations where inevitably either me directly or others on my team have gotten into conflicts because of some reason or the other. It could be a time pressure. It could be a difference in opinion on going in a certain direction. It could be people stepping on each other's toes. How do you get around that, right? Do you have what it takes to actually recognize that first of all, right? You could be passive about it. You could just be kind of having an attitude of this is not really my problem and those two people are fighting about some topic and they'll figure it out. Instead of that, try to actively get on it, offer your help, see if you can actually help resolve the conflict by either finding common ground and figuring out that there must be something that the two people are agreeing on, if nothing else at the very least, that they're trying to go towards the same goals that you would help define earlier and then from there, understand each of the side's motivations and grievances and make sure that everyone feels heard, right? So get in there, resolve those conflicts quickly, recognize them and act on them, actively participate. You are the heartbeat of the team and you have to make sure that everyone feels involved. Again, it feels obvious to say and it feels like these are just things that should happen organically but they often don't. So make sure that you actively do that and of course, respect your teammates. No matter how smart you are, no matter what you have achieved in your career, everyone's on a journey of their own and everyone has earned the right to be in the room same as you. So make sure you are aware of that as well. Everyone should feel psychologically safe to be their most productive in the area, right? In the area that they're in and what they're building along with you and this in my experience has been most apparent during prototyping and validation because this is often where teams are under most pressure. People think that the most pressure comes from launches or post launch and of course it has its own pressure but when you're building something new and there is anticipation around it, especially when you're in that prototyping and validation phase there is a lot of uncertainty around whether we're going in the right direction or not. We don't really have a lot of signal. A lot of resources are being poured into XYZ project. That is the time when your teamwork especially needs to be really stellar. Communication is a golden one. You can imagine at all phases this is important but especially when you're coming close to launching and growing at the product you can imagine that others within your group or across your group teams within the company or your leadership would want clear and crisp communication around what's going on. We spoke about active listening a little bit earlier. Make sure that as a PM your spoken and written communication is top notch and this could be each email. It doesn't have to be a six-pager or a memo that is two pages that you're working on. Every email that you send, work on it, work on techniques that help you become better at writing these. There's a lot of frameworks out there.  Internal and external communication is important. Recognize when you're sending an email to a vendor or a customer versus your colleague or your leadership. Know the difference between what it means to send an internal versus external communication. Learn that same for technical versus non-technical verbiage just because you know something in and out very well does not mean that everyone needs to understand every aspect of the technical architecture of your product as an example. And the same for individual contributors and executives. Your software development manager partner or your engineering manager partner may need to have a great level of detail around, let's say, bugs that are impacting your product. But in your executive product reviews, your VP of product may not really care for that level of detail unless asked. So there's a lot of detail here. This could be a whole different topic in itself, but another timeless piece to pay attention to. And then time management, speaking of time, I think I want to stress that for those of you who are thinking of developing your soft skills, time management is perhaps on the edge, right, of soft and hard skills. It's something you can actually kind of measure the impact of very easily, relatively easily. But if you're in that mindset of like, hey, I'll just get every single thing done on your plate. That is not a sustainable approach.  You may sprint for a week or two or a month or a year, but inevitably no matter who you are, you are going to burn out and that is not good for a long and healthy career. So I would highly encourage you to manage your time and to think actively about it. And how do you do that? Well, you learn to delegate. If you want to scale, if you want to climb the managerial ladder or just grow in your career, you have to be able to delegate. You have to be able to trust others. But don't just offload busy work, right? Think through how you're doing this in a manner that's actually also helpful for the people who are helping you prioritize ruthlessly. Anytime, no matter how small the task comes to you, if someone comes in with a request, it almost feels too easy to be like, yeah, I'll take care of it and just say, yeah, I'll get it done. But the truth is you have to be able to prioritize. You have to be able to make sure that you are very intentional about every day or every week and the way you spend it. So build in some time to actually think about prioritization. Use a framework like the LNO one from Shreyas Toshi I mentioned earlier. I won't dig into it or dive into it here, but please do look it up. It's an effective framework and also learn to say no, right? Say no often. You should be saying no more times than yes, especially once you get established because you're going to get requests for doing way more things than you have the bandwidth for. But of course, when you do say no, try to be polite, try to give a reasoning, and then once you respect your boundaries, I think others will start respecting them as well. And over time, you'll hopefully feel like your work-life balance is also being maintained. So that was a lot. I felt like it went by way faster than I expected. But to recap, in my opinion, don't ignore soft skills. Hopefully, this gives you a little bit of a glimpse into what soft skills are. Technical skills are definitely important if you're going into technical product management or just direct product management technical skills for any PM role. But soft skills, in my opinion, are vital and you'll especially reach that tipping point in your career pretty soon when you realize that these soft skills are the ones that are actually getting you further forward in your career. Practice them. That's definitely the only way whether you think you're good at them or not. Practice them. Make sure you pick the areas that you want to develop. And then there's a lot of material out there to actually help you get ahead. And then finally, balance them both, right? Of course, soft skills are important and I've reached that for the last half an hour. But make sure you find that right balance of technical and soft skills and that'll help you in your career and it'll also help your customers who you're building the products for. Thank you so much for your time. Hope you had a productive session and hope you can take away something from this that helps you in your PM journey. Thanks.


And finally, we are on to the last tin, the title dragon ruler of waterfalls, if a magician, cool. Different dimension, deep sea trench, stoic prophecy, deep sweeper, metalizing parasite, soletite, the heraldic beast, bernice falcon, rage of the deep sea, mermel abyss spike, and... Air, number C32, sharp drake, vise! Ah!


it over to Greg to fill us in on CSDMS activities. Okay, thanks very much, Brad. Let's see if somebody would release the screen share. I'll share my screen. Okay, so thanks again, Brad, and welcome everybody to this online and virtual incarnation of the CSDMS annual meeting. I'm disappointed as Brad is not to be able to see you all in person. On the other hand, it's thrilling to see so many of you joining us from literally all around the world. So that's great to see. I wanna say a few words about CSDMS, both as an introduction to those of you who are new to it and an update for those of you who have been involved for a while. So CSDMS, the acronym, is the Community Surface Dynamics Modeling System. Sometimes people say it with a soft C so it sounds like systems. And it is both a community and an MSF-supported facility that is all about supporting computational modeling of earth surface systems in all their variety and complexity. The community has been steadily growing. We're close now to 1,900 members, 70 odd countries, several hundred institutions. And it's important to point out that this is an open community. So whatever your career stage, your personal background, if you're interested in the study of earth surface by computational means, know that you are welcome in this community. So the current NSF Award supports a small integration facility that's located in Boulder, Colorado, which is where I'm talking to you from. This is the, sorry, the ancestral home of the youth Cheyenne and Arapahoe people. And in a moment I'll say a few words about resources and services that the integration facility provides. First though, I wanna say a little bit about CSU Mass Science. The earth surface is a complex and exciting place and the science of the earth surface is equally broad. This slide shows just a few examples of some of many projects that are sort of recently published or ongoing that explore different facets of earth surface dynamics using systems tools and technology. And they range very widely from permafrost to natural hazards to landform evolution. A particular interest here, of course, are things that have to do with life and landscape and seascape. So for example, how do we cycles in climate and vegetation influence landscape evolution? Or can changes in grazing and wildfire regime trigger woody plants encroachment? We're gonna see some exciting developments in these I think over the next two days. I wanna point out that the systems community is organized into a set working in focus groups about a dozen of them. And I wanted to welcome and thank the new chairs and co-chairs who joined us this year. They include Leah Mayo from the University of Central Florida, Susan Emery, Julia Moriarty from CU Boulder, Kevin Shue from LSU, Olaf David from CSU, Pristina Benderagoda from University of Washington and Derek Robinson from the University of Waterloo. So thanks to all of you. Thanks to the outgoing chairs for your service and contributions. I also wanna welcome three new members of our hearing committee. They are Pat Weiber, the University of Virginia, Khadidia Thiero from NCAR, Paulo Pasalakwa from UT Austin and Michael Barton from ASU. Thank you for joining us and contributing. And let me say a word of thanks to to the integration facility. Actually, I'll do that in a second. First, I wanna point out this year's award winners. So here at the annual meeting, we offer awards both at the senior level and at the early career level. At the senior level, this year's winner of the Lifetime Achievement Award is Professor Gary Wildwoods of the University of Newcastle in Australia. And Gary has recognized there is outstanding intellectual leadership in modeling, landform evolution, soils, data dynamics, weathering, vegetation and a variety of integrated related processes. Gary, as many of you will know is essentially one of the founders of modern landscape evolution modeling as well as probably the founder of the field of applied landscape evolution model. So congratulations to Gary. We also have at the early career level the Sivitsky Student Model Award. This is given as a jury award, students apply with a portfolio that includes both the science and the software code behind their models. And the applications are reviewed on both of those counts. This year's winner is Ian Reeves from the University of North Carolina, Chapel Hill who was selected for his submission on the impacts of seagrass dynamics of long-term evolution of barrier marsh bay systems. We'll be hearing from Ian later this morning or whatever time it is in your time zone. So congratulations to both awardees. Normally tonight would be a banquet at which we celebrate them in person. And unfortunately that's not gonna happen this year but we look forward to celebrating with these folks and you all sometime in the not too distant future perhaps next year. Okay, the integration facility as Brad mentioned is a small group of people based here in Colorado who work hard to provide resources and tools for you and are responsible for putting on this meeting every year. And I wanna thank them especially for the late game pivot from what was to have been an in-person meeting to this online format. Thank you very much. I also wanna say a few words about some of the resources and so on that this group provides to you all the research community to help you do your research more effectively, more efficiently, more sustainably. And it's useful I think to do so in the context of scientific computing broadly speaking across the sciences. So one thing that's clear is that scientific computing is here to stay. Presidential advisory committee several years ago called scientific computing a new pillar of science taking its place alongside the traditional modes of theory experimentation. And those of us in geology and ecology would add direct observation as a cornerstone or a key method of doing science. And that's a big deal. And we've seen the growth in computing in any number of prominent discoveries just in the last several years. So for example, the black hole imaging that was widely celebrated last year was in part a telescopic discovery but also in part a computing product. You may or may not know that the Nobel Prize in Chemistry in 2013 was awarded for numerical modeling. And closer to the earth and environmental sciences of course we see the gradually increasing capabilities of hurricane forecasting. And we have now the first at least two national scale operational hydrological models. And those are just a few of many, many success stories around scientific computing. But this being a really new area of science it's natural to expect that there are some changes that it brings and some growing pains too. One of those changes is that today software is infrastructure. Software that we use for our numerical modeling for our data processing and to operate instruments is every bit as complex, intricate, worthy of and indeed demanding of careful engineering and maintenance as the more familiar ships and planes and accelerators and flux towers and whatnot. Indeed none of those pieces of equipment would operate without software. And yet one of the challenges with software is that it is invisible infrastructure. And it is maybe partly for that reason that there have been some growing pains. Some of those growing pains have arisen around the idea of reproducibility. So if reproducibility is a cornerstone of science there's been any number of calls of alarm around the potential for the lack of reproducibility in much of the computational work that we do. So a number of years ago, Randy Lavec at the University of Washington commented that science and math journals are filled with pretty pictures of computational experiments that the reader has no hope of repeating. And that was over 10 years ago had things gotten better since. In fact, if you look at studies of reproducibility there are still some worrying signs. One study for example that I'm showing here on this slide from just two years ago attempted to reproduce the results from some 300 articles in Journal of Computational Physics. They were only able to get the digital artifacts without authorist systems for like 2% of them and unable to easily regenerate all the findings for any one of those articles. So we have a ways to go in reproducibility and reusability. There have been concerns raised too about quality and related issues of productivity and sustainability. In other fields, fortunately, not in earth or environmental sciences so far as I'm aware, but in other fields there have been some prominent retractions of results that were found to be flawed because of software bugs. And that's not a good situation to be in. And in trying to diagnose some of the reasons behind these issues and exploring how it is that research scientists use software, various studies have unearthed some interesting findings. It turns out if you survey scientists who work with software, for example, the gluten modeling, they will often report that they spend as much of a third of their time working with debugging, writing, et cetera, software. And yet if you ask, how are we taught and trained to do this, the answer is usually that we're self-taught. And very often we're unaware of tools and practices that would make our lives easier and make our products more reliable. One study that I thought was interesting, like in scientific software creators as being a bit like castaways on a desert island left behind by the modern world. And when rediscovered, the rediscoverers, software engineers are appalled at the primitive conditions in which they operate, even if they're quite innovative at making it all work. So we have some challenges along the road. On the other hand, the good news is that gluten solutions to address some of these problems not only are on the horizon, but I think are already starting to exist. One of the classic obstacles has to do with incentives and credit. We write software to do research, but it's the research that we're judged on. But one potential solution to that is a growing number of journals that are devoted to research software, either a domain or a general. And some of these, in fact, have the software itself as the published product. In other words, you're presenting the software's documentation, its tests, and that is what gets reviewed. The Journal of Open Source Software is one example. So that's a good development because it provides those of you who write software as part of your research with a vehicle for getting the credit you deserve. At the same time, we have an increasing number of journals and funding agencies who are insisting on higher standards. American Geophysical Union, for example, now considers software as part of your data. And they will no longer accept data available or software available on request as a solution you need to put it in a trusted repository. At the same time, we know that despite concerns about quality, it's been demonstrated that research software can be extremely high quality. One study of climate models, for example, showed that they have very low defect densities compared with other kinds of open source project. Really reliable software is possible. We have the tools to do it. And there is a growing literature that provides all sorts of advice, recommendations, tools, and techniques for scientific programs. On the other hand, it's not that easy necessarily as an individual to sift through all this and to put it into practice in your own work. It helps a lot if you have availability of training, enabling tools, and expert support. And this is where CSDMS has tried to make some contribution to the Earth's surface science community. So I'll say a couple of words about resources and services available for CSDMS. The integration facility really works in three areas to support your work. It's community, computing, and education. I'll give a couple of examples in each of those categories, starting with community. As many of you know, CSDMS runs a public repository. So this is an online, open, and accessible database of model programs and tools written by and shared with the community. And the repository includes a rich set of metadata for each tool and model. There is a pathway to add a digital object identifier if you wanna make your product citable. You can add references as part of the information. We currently have over 2,000 references in the database and systems will even track a citation index, an H index, for the program, not for an individual, but for a particular model to give a sense of how widely embedded is that model in a particular community. Currently, we have around 350 models and tools and it's steadily growing. We also provide help with projects and proposals. So, for example, if you're writing an NSF proposal and you'd like to have well-tested, sustainable software as a broader impact of your research, we can help you come up with a plan to do that. We also help with various projects, sometimes through collaboration on proposals, sometimes through site visits, though that's unfortunately not happening for the immediate future. And we can provide research software engineer as a service consultant. We have a certain capacity to do that pro bono through our current NSF award. And if you need more support than that, we have a mechanism to provide you with a budget for a certain amount of service assistance. In addition to all that, we run a user help desk to answer various kinds of technical questions that come up. So that's community. Let me say a couple of words about computing. You know, one of the original visions behind CSF was established back in 2007, was the idea of a modeling environment with a community built suite of integrated software modules that are targeted toward predicting erosion, transport and accumulation of sediment and solutes, landscapes and sedimentary basins over a broad range of space and time zones. Now that's an ambitious project. And it's not something that a very small facility could ever hope to do on its own. It's a community effort. The idea is that we need something that is built both by and for the community with the integration facility, providing a little bit of pinch of support to make it all work together. And really there are sort of four technical ingredients that are part of this system. And I'll say a few words about each one of those. The first is an interface standard. So it turns out that standardization is key to being able to operate things together. Just as you need the right screwdriver head to fit in the right screw, you need standards to operate in miracle models. And it becomes much easier to couple them or simply even to work with them when they provide a consistent interface. So to that end systems provides the basic model interface or BMI. And really what this is, it's just a list of functions. And if a model provides these functions that can be said to be standardized. And their functions like initialize to start up the model and read its inputs, update to advance it in time. If it's a time advancing model, get value to interrogate what are its state variables at the moment, set value to tweak or adjust those if you want to do coupling or data assimilation or simply to play around and experiment and finalize the cleanup. So those are five of what ends up being about 30 odd functions. The second technical ingredient is language interoperability. The communities judging by the codes in the model repository have a certain set of languages that they like to work in. And it's important to be interoperable to have a lingua franca that could connect all these. So systems has developed some in-house tools that will provide a Python front end. So Python is the lingua franca to be able to execute programs written in Fortran or C or C++ through a Python interface. And maybe someday we'll add R to that collection. I know that's popular one in the ecosystem community. Third element concerns, what if you want to write a new model? That could be a daunting task. There's a lot of potential headaches in doing that. And so we've created a software library that helped make that easier at least for two-dimensional grid-based models. It's called LandLab. And it's a Python language programming library. And it handles things like gridding and layers of data and input, output and things like that. And it has the ability to encapsulate numerical solutions to particular processes as reusable components. So this slide shows images of some of the applications that have been published or are underway using LandLab model. It ranges from watershed hydrology to tectonic gene morphology to vegetation dynamics, landform evolution. And then finally, the fourth ingredient is a framework in which to explore, couple, run, plot, analyze models. The current iteration of systems modeling framework is called the Python modeling tool. So here again, Python is the lingua franca. Python modeling tool is simply a little Python package through which you can instantiate, run and explore any one of currently a collection of 16 legacy models written in different languages under the hood. And these cover a range of different kinds of disciplines. We are now also working on data components. So these are components that operate the same way but they fetch chunks of data from a particular data source and LandLab components of which there are a few dozen can also be operated this way. Let's put Python modeling tool. Lastly, let me say a couple of words about educational resource. Those of you like me who have had to pivot from teaching in person to teaching online know the value of online teaching resources. And so we have worked recently to try and clean up and curate a collection of online lab exercises. Many of them use Jupyter notebooks that involve modeling that students can do directly through a notebook through a server that we've set up to explore all kinds of different systems. In addition to the labs, we have a webinar series that some of you have contributed to that covers a range of different topics from the technical computer oriented to the scientific. If there is a webinar topic that you'd like to see let us know and especially if there's a topic that you would like to offer, let us know and we'll get you on the schedule. So that's a really quick tour of some CSTMS tools and resources and with that, I'll pass the torch to Albert. Happy to answer questions via chat if there's time for that one over to you.