The following is a presentation of TFNN The Tiger Technician Hour with your host Basil Chapman call now toll free at 1-877-927-6648 Basil Chapman here on this Monday the 4th of April my pleasure to be here and we're looking at the Dow down only down 18 and 34,798. I think in the very shorter term The Dow is just digesting the very big gain it had essentially from a very last not the 33272 low of February 24th, but the Low that was around about the March the 7th and 3578 that's where this extension started to come up and We hit 35,372 and now I think it's going to be good But now we've got some new leadership at least at the beginning of the week and that leadership we'll talk about in a moment Well, let's go to the Parameters we're looking at within the Dow if the 30 I Said to subscribe to my opening call 34,950 or maybe 970 to 35,050 or maybe 70 that area is where there should be a lot of Resistance, we've seen it before we saw it when we stopped dead on that big spike up over 35,000 to 335,000 35,372 That really big sell off on Thursday Assessor baited by many fund managers saying hey, this has been good. I've just got I've got to take some pride I've just got to get out of something and they just increased the selling pressure right into the clothes So Friday's action was just kind of okay for the Dow today's action is just okay What we're really seeing is that the SMP is now so the Dow used to be leading now and then the SMP and then the Index 100 and then the IWM the Russell 2000 and now what we're seeing is The SMP the Dow is a little bit weaker S&P is a little stronger up 14 and a half at 45 60 It needs to get to the 45 95 40 603 level Sometime this week without breaking down below 4500 Let's see if we can do that then comes the QQQ. Well, look at the QQQ today The index 100 is up sharp needs up 1.2 percent up 4.37 At 366.21 this is the area that I've said to subscribers. We're gonna focus on this area for now We've got a lot of commodity area type Sectors, let's see what what can happen in this particular phase because it has to be a catch-up and I didn't want to be Beholden to a particular stock. There's some stocks in the index 100 that have just been Absolutely decimated on the way down and we're ready for it Not just a good bounce, but at least The chance of an intermediate term move to the upside. Maybe it's just percentage terms. Maybe it is In time, maybe it's a combination, but I mean, let's just go to square I mean square is up to day eight at 141 up 6% That went from 289 in August of last year To 8272 the low of about the 23rd 24th of March of February So this peak D with the left side right side price time matches really good I just didn't want subscribers to be beholden to any any particular stock that looks like it's doing great and Suddenly another shoe drops. I'd rather have the composite in other words the index 100 to go to the upside and Yes, you give up some of the gains because you're not getting individual stocks can really fly But I'd rather take that chance and be have a little bit. Let's see what DocuSign is doing DocuSign Struggling yes, it's peak A peak B peak C. Oh, I thought I finished that Let me just do this right here for those of you are new to my work identify the lowest low bar County successively higher peak. It's gone from DocuSign DFC you go from 314 chapwave to bar reversal at the top back in August of 2021 And what does it do? It has a little bit of a pullback It comes down to where it comes down to 71 round number low It's trading now at 111 40 points I mean, that's what 60% gain but a 60% gain after our whopper of the loss But even here you don't know what the next year it could there be another I don't I don't think It's going to be the kind of selling spree we've had but certainly you could pull back and then stall So having the composite I think is making up for at least It gives a little bit of a sense of comfort because you're not as I say beholden to one or two stocks So the IWM the Russell 2000 Week down 72 at 206 we've been watching this to see whether Very often as the year ends in the beginning of the new year starts You will get a huge rally in the small caps the Russell 2000 Well, even the 3000 the I shares Russell 2000 IWM ETF and It's done very nicely to get to PD stalled right at what the 200 period exponential moving average right there 211 point 48 and We're down a two or six a lot of work needs to be done. I think it's going to be time Maybe the price is kind of not as much price to the downside from here, but maybe it's time All right, let's get to the nitty gritty gold Gold is up nine at 1932. There's a pattern that I talk about a lot It is this pattern right here if I can find it we have to go No must be it has to be there Let's find it Yep, there it is So I only look at basically three directional moves one is straight up and straight down Here it is number one The other is a cup formation. It could be a V shape formation basically you're going from one point down and then back again How does it deal with the left side high or it's the left side low when it's an art formation Green when it's up going up and it can take out that left side high That's the reverse Y pattern, which is really positive if you break out significantly on the downside The dreaded H lowercase H But that lowercase H if it holds the left side low even if it goes under it forecloses above it It can meander and go sideways in a kind of a rectangle formation and make a second option I call I call the lowercase M. So yeah, you are you've got Eiffel Tower straight up That's the a a pattern right there. I'll just make it a little brighter so that you can see a Pattern looks like the Eiffel Tower Then it finds a base and then it tries to read and it goes to a peak B and it fails a and a B Pulls back breaks to a new low, and then it tries again. He has another a this is a for this particular little Diagram I'm calling this an a again a gray a All right, so yeah gold is acting well fabulously in fact considering what it did going from under 1700 to 2070s, but now it's stalling because most of that Most of the fear factor where gold becomes the icon of fear is Kind of subsiding just a little bit, but it's still elevated and that's exactly I'm talking about human nature, and you can see this is the price point of human nature in gold and it says I'm still watching gold real closely, but right now. It's just it's just in a holding pattern So the same thing not quite as the pattern is not quite as good as the as the gold It looks like it wants to retest 24 27 level of the 200 period moving average at 2448 down a little bit more like an arch The dreaded H pattern and it's being below the left side low a couple of times. We're gonna keep a kudo Kudo is up people nine four one or three twenty three good action, but in in a way Are you looking for a way to consistently add winning trades to your portfolio? Tom O'Brien is here to help Tom O'Brien has been successfully trading markets for over 30 years a frequent contributor to TD Ameritrade Network and CNBC Tom O'Brien founded TFNN over 20 years ago to help educate investors just like you Tom's daily market newsletter market insights is published every morning when the markets open to give you the competitive Informational edge you need to succeed these newsletters are packed full of Tom's advanced technical analysis In our gear to deliver comprehensive strategies for a successful portfolio Get Tom O'Brien's newsletter market insights today and try all of our products and newsletters 30 days risk-free With our money back guarantee at TFNN comm TFNN educating investors What's separating you from the most successful men and women on Wall Street? That's right Information having all the information gives us the perspective we need to place the right trades at the right time The TAS profile scanner is the premier market profile base scanner powered by its acclaimed TAS proprietary Algorithms this feature rich scanner instantly filters over 2500 plus global financial markets such as stocks ETFs commodities futures and forex This powerful suite of tools Leverages instant trade filtering and strategy formulation to show you emerging trades Before they happen for a limited time you can save $100 off your first month by using the promo code Upgrade and you still get a 30-day money back guarantee So you have nothing to risk Level the playing field with the TAS profile scanner which you can find under the services tab at TFNN comm Sign up today Sharpening your skills as an investor is like getting better at playing a musical instrument You have to practice sure, but you also need excellent instruction from experts at TFNN You'll get advice and guidance from the authority and technical market analysis And it's not just dry tedious text either TFNN airs live financial content streamed live on TFNN.com and TFNN's YouTube channel with Tiger TV live every market day from 8 30 a.m. To 4 p.m. Eastern for free each host is an experienced trader and gives their take on the market while taking calls and questions live from around the World from the moment the market opens until the closing bell sounds Tiger TV has eight different shows with expert hosts to help You make the right moves with your money watch online at TFNN.com or on TFNN's YouTube channel and become the Investor you were born to be TFNN educating investors Toll free at 1-877-927-6648 Internationally at<PHONE_NUMBER> Everyone bouts a trap and we're back Couple of things I want to just look at you because a number of people who ask what are you going to be doing in your webinar? Well, the question is Can they be higher indices in 2022? Can they be record highs and? I'll be discussing that in great detail. I'll be discussing The selectivity that we're looking at what it would take what is going on as far as I'm concerned just in the in the way I like to look at markets and Which sectors are working? Well, which sectors could come under pressure They had a statement in the den folks try out the den is really a terrific medium What we're looking at here is I just did the This is a continuous contract of the you wouldn't be trading this business what I'm using right now of the Ndx 100 and you can see that the one minute chart made a peak E. This is that right? I always like to do this. It's really a good way to Assess and I'll be talking about these techniques when I do the webinar Look see this high that was made yet peak D in the chapwave and the chapwave always looking for at least four higher peaks This is the second peak D in a row Usually you don't get Thursday. You've got to be careful on the second one and look the MACD and stochastic I started to pull back look at the difference here when they made a slightly higher high at 15,000 and 68 at about just after about 10 10 12. Let's say and I was pulling back It's not breaking down. It's just pulling back in the one minute chart two minute chart made a peak E and this basically looks like Like a rogue wave in that it made a high and it looks like it was pulling back And then suddenly there were just these couple of bars They went pop to the upside and then failed and you were back to the down mode And that's just the one minute chart, but it's still only a leg B a peak. Sorry peak C in the Five minute chart. So think of it as like a like a daily a weekly and then monthly So we're in C in the five minute chart and only a B in the 10 minute chart So it could have digest gains and maybe start up again. This is the NQ Okay, now, let's get back to our story. What we're looking at is a crude oil has held very well after these Huge spikes to the upside starting about the 21st of Feb got the whoppers and then finally it goes to a high on the 7th of March That price could change because it's a continuous contract gets moved down. Yep. There it is now the highs 129 17 This has changed the price nothing changes except the price because it gets smoothed out one two nine point 15 All right on the 7th comes down to about 91 92 and then ready sharply to the 117 ish area comes back down holds the 50 period moving average Remember, you don't need these moving averages until you need them. We need them right now We needed them the last two days because they touched it twice And it's not moving up a little bit the Mac these weeks the casings very weak on balances is weakening And the nine has just crossed under the 14 so the big question here is wait a minute with everything that's going on with the talk about Using up some of our reserves what a million a day or something like that. We're going to be adding We're looking at least for the month for the shorter term Amelioration of the tension in crude oil. Well, if you look at crude oil weekly chart gave from 60 Some months back to the high of 120 that's called 130 just in March That is a huge move you can see a consolidation But until there is a move back under 87 85 somewhere around there This still remains elevated and you've raised the base of support. That's the way I like to look at it However, based on the candle this long wick in the monthly candle for crude oil spiring up to that high of about 130 in In March and then pulling back and closing with like a like a hammer inverted hammer candle Moving up is is going to be important. I give it the whole of April to say on any two days I would say a week, but a week could be I'm talking about a week But you could get that in happening in the daily charts. I'm not going to go to the week I'm going to say if any two days Out of three it doesn't have to be consecutive could do it once and then stop and then the next day It doesn't again if there is a close above the halfway marker in this candle right here It's called 112 We're at 102 you could do that in a second, but if that you just say that again 112 I'm going to the wick Yeah, let's call it 113 if there are two closes within three days above 113 In crude oil it means oil is still in play. I think it's going to be in play I'm doing about the shorter to more kind of a little bit intermediate term to about weeks in other words That's going to say be careful because stocks like Exxon came out with earnings. I believe today It's down 42 cents and 82 70 All of them have had that big spike to round about the 7th of March and pull back if you look at chevron cvx Same thing. It's more like it looks more like the crude oil actually looks more like the gold chart So cvx is one of the better ones in the multinational oil companies So if you're looking for a play in these You even have to scale in and the came the question over the weekend. What do we do about these multinational oils? As far as i'm concerned i'm going to do it just purely on Chart formation and history. I'm not going to say Geopolitically there should be a huge further gain in oil We just don't know because we don't know who's going to produce a little bit more who's not It's kind of complicated and the patent says it was easy Now it's complicated because it sideways in a rectangle formation in my rule of thumb A rectangle formation can last a lot longer than your patients unless it's a wide Um Rectangle that is not the narrow long one, but a wide one This kind of fits a combination And it's already made the arch formation rather than the stair step move to higher highs to a seed stop That be underneath the previous high all I can say is chevron is stuck in a range But this is one of the better companies if if you're looking if you're if You're in leg d already in the monthly chart. That's the objective in the chaplain wave methodology So, um, it's achieved everything you want and the e e p e with four bars of consolidation so far in the weekly says The upside could be limited because it could just be momentary hysteria because all of a sudden everybody gets nervous because of whatever's happening But if you look at the pattern it says there's been a decisive Weakening in the technicals Yes, it did fill in the gap. This is chevron and the one the leading multinational oil companies and therefore There's a better chance. It's going to retest the area of 155 Which was what was right 26 was alone the 15th And if at 163 if it closes under 160 any time this week there's a chance it'll start to arch over And that's where I would start to want to start A three position entry point if you're interested in chevron and in the you'd have to you'd have to Think that it maybe is a successful test in the beginning So 153 is the level we're looking at I'd say 157 if you haven't got any you could even nibble here But that's just a nibble that's different altogether to planning a move that says chevron later in the year should go higher So if you're thinking that way then I'd wait in the 157 I would it's only five points down. I would start the position, but I'd prefer Um that I got that position and then I'm running strongly because if it starts to break and go to the next level That I'd be looking at which is at 151 If it takes that out the next you could go quite a bit low So I would say I don't start a smaller position A little bit lower down the full points maybe five points and then you have to test how much spread this level I'll be back down to 15 Are you having fun trading the markets but having trouble finding like-minded individuals to discuss your trading and investment ideas with Become an apex predator in the trading markets and join the tiger's den trading room only at tfnn.com The tiger's den is an exclusive trading room where successful traders from around the world come to exchange trades and ideas Join the den and surround yourself with the sharpest minds in the trading world Subscribers to the tiger's den are also the first to have their questions answered live on air And can privately chat with our tfnn hosts live during their shows Interact with other tigers and tigers as they share trading ideas news analysis and discuss the market action all trading day Subscribe to the tiger's den risk-free with our 30-day money back guarantee and become part of the tfnn trading community tfnn educating investors You could be making money off the stock market and if you're already making money off the stock market You could be making a lot more Check out tfnn and tiger tv and get expert investing advice to give you the power to control your financial future Go to tfnn.com and find the newsletter for you Whether you're into trading gold metals futures currencies or options You'll get advice and analysis to help you seriously get ahead tfnn also features trading services with a 30-day money back guarantee for new subscribers As well as tfnn's tiger den trading room trading software and educational webinars for all trading levels And make sure you check out tiger tv for free on tfnn.com or tfnn's youtube channel for live financial content From 8 30 a.m. To 4 p.m. Eastern on market days Stop watching on the sidelines while other people get rich and become the investor. You were born to be tfnn educating investors tfnn is excited about our new software charting program the art of timing the trade charts In collaboration with tom o'brien and using his best-selling book the art of timing the trade your ultimate trading master system David white has programmed an outstanding piece of software that will complement any trader's methodology Using this first-of-its-kind program the art of timing the trade charts allows you to scan thousands of stocks for fibonacci Formation setups including guardleaf abc's butterflies and much more The art of timing the trade charts is designed to help you when scouring the markets for stocks Just beginning to form the trading patterns that many investors spend days weeks or even months searching to find And right now we're offering licenses available at only $79 a month We are so confident that you're going to love this new charting software That will even give you a 30 day unconditional money back guarantee Don't miss out on this incredible new piece of software Get your copy of the art of timing the trade charts today by visiting tfnn.com This segment is brought to you by think or swim for more information Just click the think or swim banner on the front page of tfnn.com So we've got leg c in the e-mini Uh, he has a five-minute chart using the chapeau wave automated every support resistance lines And what we're looking at is right there 45 61 will be the next area of resistance And I had spoken about the nq continuous contract. I had questions about that You see the five-minute chart is 15,059 resistance and in 50,068 that was peak c in the five-minute chart Over a period of another what are we doing at by the end of the end of the show We'll see if we've actually been able to make that leg d But that'll only be a leg c in the in the 10 minutes Remember what I'm going to be teaching in my my webinar coming up on a week from wednesday April the 13th for subscribers to my opening call is how do you use How we how we so successfully use the smaller time frame That gets to say a peak d What is the next time frame if you're in the daily? Where's the weekly? Is the weekly now building strength isn't saying hey, I'm only in b I could still go to a c or I'm a I could go to b and that's really important That's how you can stay in positions much much longer But it also allows you to get out of positions when you start to weaken now. Let's go back to So I'm done with that with the whole chevron thing a couple of questions came in Could I look at ung and that's you could ung ung is trading it just had an alternate count So it's peak a peak b peak f slash c. This is leg d It's gone above the rectangle formation. Remember my rule of thumb in the rectangle formation If it starts to make a lopsided gravy cup pattern, you can get a left So I had this written in but it wasn't probably in the in the contract itself This is the way I would have been looking at this To see a left side right side price time match Let's see if we can get that here. That's red and this goes green And I'm using not the fulcrum from the bottom the plum line because that's way off That's that's the gravy cup lopsided cup formation. So this is where I'm going from this leg d right here And that takes you to it takes you to The first of april to break the the high of umg which is united states natural gas fund the high of the second of february 1950 Well, we did that a day before and now we've gone a little bit higher What's the rule of thumb in this in this huge rectangle formation? You remember I actually I had already drawn this in let me just make this darker So you can say well, let me make it green like I usually do this is called the chaplain wave inside wedge target resistance line and that said It extends a little bit further. It says that yep by Friday you should be taking out that left side high of the second of Feb and that's exactly what it did And you got the magnate strong stochastic spread at 88 percent nine's way over the 14 period moving average But the the wide rectangle formation if it makes a lopsided cup and starts to make higher highs With a stair step move Constantly cheating some areas key support. Look at this 14 period moving average broke it Closed under it twice, but closed above it all that other time That says it should take you to just under Right on or just above the previous high and then be careful because you could pull back into About a third or maybe even a half of the previous rectangle formation So we're going to be watching this But the left side right side price time match of the weekly chart of ung with the high of the 8th of October at 2210 Um, let me draw that now Let me just to oh, I already drew that in I drew the uh This is chaplain wave inside. I'll also teach you how to draw these inside wedge target resistance lines on the on the way down They are target support lines And styles usually dash green on the way up and that says I don't even have to look at the bottom I'm just going to the top and I'm saying from this level on the left To that high and to this place on the right right there What what what have we got? We've got the week of You got the week of the 22nd of april to get to the high of 22.10 and we're at 20.20. That's a whole two points. That's it's a big move But anyway, that's what it's looking like right now And I can now make an adjustment Oh Yeah to that. All right. There we go. All right. So we'll see what happens meantime back in the launch key support in the 1910 to 1875 area a question came up. Where did it go? Oh, thank you for that statement that was uh Yeah question about the comp question. Oh amazon a rectangle formation You know, I did this when gt when you sent this over the weekend. Um, I I don't see the rectangle quite maybe the way you do it, but I'd like to do this amazon straighting up even after the vote To unionize and what was it one of the one of their facilities Oh, I see what you mean. You mean this kind of rectangle here. Yeah, I I agree with you in that regard But there's a rule of thumb that I have another rule think a lot of thumbs And that says Within this context when you get a dreaded h pattern that gives you a buy signal to buy mode Which basically the mac deans stochastic did There's a good chance that the arch formation then becomes it morphs from a negative to a very positive level of Upside action and that takes you to like this So amazon trading at 33 25 up 54 right now It did get very close to the left side high that I would have I would have treated as resistance at 34 58 We went to 34 twin 34 16.63 on the 29th of march in the daily chart we've pulled back It is a peak c the the stochastic went back under 80 percent I don't usually like that. I I don't like it if it's very quick like here We're into a peak d and remember I spoke about this in the chapter We methodology if you've had a very sharp pullback and whatever you're following If there is just a very quick peak a to a b to a c and a d And when you look at the bigger picture, it is just a really it's kind of a pathetic rally Be careful because you could pull back and retest the low You don't have to break it significantly because once it's gone to a d It's used up a lot of negative and positive energy. It's more just the arch formation Well, lo and behold, we went from the low of In amazon you went from the low of the 24th of jen 2707.04 All the way to peak d just under the two orange 200 period moving average right there on the 9th of feb At 3270 669 and what do we do? We went down just below that low of the 24th. I think it was and that went to 20 2671 0.41 So this is this is a brand new by mode We're in in place here. There should be some way it should squeak I don't think it's going to be a breakout yet, but I think it will squeak to the 34 17 or higher area and that'll be leg d Okay, if you look at the monthly chart, I there's a pattern now You can read books and books about this expanding wedge formation. I couldn't even tell you how many expanding wedge formations We're spoken about spoken about spoken about in this huge negative way And then over a period of many many bars It just disappears as something to consider and this is typical. Look what happened It makes this pattern a low lows lower lows higher highs higher highs and then what does it do? It has this magnificent rally from under 2700 to uh To almost 3400 So it's almost negated this pattern So remember this like it's like a head and shoulders by the time you recognize the head and shoulders It's too late use other patterns to confirm And get in earlier for that fact I'll be back in a moment does down 10 sbs up 19 Let's see where the qq curious because that's the one of your favor right now The whoa big move almost up five Are you in the market for buying or selling real estate in the bay area? Including the surrounding st. 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That's tfnn.com and hit watch tiger tv Folks we're back. So let me just get to some of the questions here I'll just go and order that I can see CLF one that we've liked a lot. We don't actually own it right now CLF is Cleveland Cliffs Inc federal steel iron ore pellets Uh, this is a leg d in the monthly chart peak c already in the weekly chart in the rectangle formation broke above it after being in that 26th area To the 20 to the 19s for a long time for since last Oh, you can go back even to to summer of last year And it finally breaks to the upside like a one-to-one to the upside Holding really well because my fear always with these patterns of the rectangle is it can break above And they're very often like the IWM it goes zoop right back in again to the rectangle. So this goes Cleveland Cliffs I like it. The big question is To add to add or not to add yes to be or not to be but to add or not to add If you've already got your position I think because of the rotation that I'm looking at right now It's holding well I suspect even if it goes to from 32 oh four clf is a symbol down 33 cents today Even if it can get to the 34th I think it's coming back to do a whole bunch of testing in the 30 32 and a half to 30 area So if that's the case, I'm just going to say hold off now that another question someone else asks is Do I take some profits in clf? And I'm going to say if you've had really good profits Money management suggests Yes, take a little bit of just to make yourself comfortable. That's all not to say. Oh my god No, it's a leg c a peak c in the weekly chart It should still try to get to a d I look at this as a magnus strong 95 percent in the weekly. You've got a chaplain wave squash formation That's where the magnus Just rockets to the upside with the stochastic with the price and that says very quick peak a to b to c And then you might take a little time before you get to d So i'm just saying for money management If you're just a little uncomfortable Take something off if you're looking to add to it because I think steel Is the big is this a late cyclical so that the steels look that they do really well But it's almost the end of the run they do that very often historically I'm I'm doing my assessment here if you look at slx, which is the steel Van Ack vectors etf would have spoken every web and I ever talk about I've had the steel that we've spoken about it has gone to that leg c in the monthly chart And a peak c in the in the it looks almost the same and it looks like in like cleveland cliffs Holding in the pattern right here To you Do you add or if you're not in at all do you buy I think that you just if you haven't been in for the big move up Why not just hold off? Because everything that's going to go up from here. I think we'll come back and digest gains in the steel area New month mining is a new month and a new core. That is What i'm going to say is Why don't you have patience if you aren't in it you're waiting to buy rather Use and that was cleveland cliffs clf. I would just wait Preferably it's a big deal.  But if if you haven't got anything You don't have to wait for uh 29 to get in As it's pulling back here. Let's look at it together But it needs to test the 14 period moving average of 30.47 and if it closes under it I suspect that steel stocks are going to have a slightly longer time out Uh, but still holding very well almost like the oil like the xle another question came in xle Well, it's almost the same pattern. You've had your big rectangle formation You started to move towards whichever way of stair step move to go just on just under or just above the previous high In the xle which was uh march. I think the seventh Was it march the seventh yet march the eighth at 80 point 22. I may as well put that in because i'm always going to be talking about it eight 80 point 22 on three eight 22 And i'm going to make that read because it's still in a consolidation phase in the daily. It's a weekly pd This can go on for a little bit. So what i'm saying is I would I would treat them all together They're holding extremely well, which means that over the period of months We've got to look at these as potentially going higher the whole energy sector But on a short-term position if you haven't got anything Where do you get in that's what we'll be looking at and subscribers as well. We'll be looking at Getting back into some of the oils that we hadn't gotten to before next question is vst Vst is um Vista core. I vista core electric power business. I didn't have a chance. I did this last week I just finished some of it right now, but I did the notation haven't done the weekly Oh, it's trading at 23 36 down nine cents It's making a higher highs and higher lows with interact angle formation I I think for a dividend stock I like this when I get it Now when it's just about to start bumping into resistance have it. Let me have a look at my chairman. We've automated Uh resistance levels vista vista. I keep saying vista vista 24 06 is next in the weekly and it's a 23 38 Then nothing in the weekly 23 56 23 64 in the 120 minute chart and you can see I have no support levels So previous resistance becomes support I like it and if you treat it as a dividend stock figure out the dividend And then proportion to get into your risk and you could I would start my position here in vst For the for the questioner And on this one I would have just because it has a dividend just for the moment. Let's give it a one point stop 22 38 will be the stop um, I think 22 yes 22 38 and uh, let's follow this one again a little later in the week Um, not the big position, but just like a starter position Okay, a small starter position. Let's go back to another question moz That's mosaic mosaic is the mosaic company potash phosphates fertilizers This is a little different in the sense that The area of potash and fertilizers I think that demand is going to be there for quite a while, but it might only last Part of maybe this this summer. I don't know. I need to figure out when All of these really come to fruition. I suspect if it's fertilizers you have to use up the summer So I like this very much. I also say it's in a digestive phase. It goes into the same category But it's a little the sector itself is different. So in this particular instance I would think of it's the question was Do I take profits? so the question is Oh, I can't find that right now, but I believe it was do I start taking some profits and I'm going to suggest yes Why because you've been this in a long for a long time. It's at a fabulous move It's now digesting gains Just for comfort and money management at 66.43. I take a little bit off. Would I get back in? You watch this closely because if it pulls back and it goes and it closes under 64 30 Then I think you've got yourself the dreaded H formation and just says it could be a test of the 60 or 59 area and You might want to think of adding that back Oh, you know, even if it's five points down if it's part of your portfolio And you've had a really good gain and you're actually taking some off for a really nice gain Putting back five points later means that you've got a good comfort factor So that's the way I will look at a lot of questions. Oh, we've only got one segment to go I will be back to the Tom of Blind show at three o'clock and we can some of the questions sent to me and I'll talk with them I want you to look at I'll be back in a moment Sharpening your skills as an investor is like getting better at playing a musical instrument You have to practice sure, but you also need excellent instruction from experts at tfnn You'll get advice and guidance from the authority and technical market analysis And it's not just dry tedious text either Tfnn airs live financial content streamed live on tfnn.com and tfnn's youtube channel with tiger tv Live every market day from 8 30 a.m. To 4 p.m. Eastern for free Each host is an experienced trader and gives their take on the market while taking calls and questions live from around the world From the moment the market opens until the closing bell sounds tiger tv has eight different shows with expert hosts To help you make the right moves with your money watch online at tfnn.com or on tfnn's youtube channel And become the investor you were born to be tfnn educating investors You might think that if you want to be successful at trading in the stock market You're going to need a crystal ball after all it's impossible to predict the future, right? Like any endeavor in life before you decide it's impossible get some advice from the experts You might find that it's not so impossible after all for daily market overviews that give you direction on the key indices Selective stocks and commodities subscribe to the opening call newsletter at tfnn.com The opening call newsletter is written by basal chapman creator of the trading methodology known as the chapman wave The chapman wave up down sequence gives you an edge in identifying price turns Finding the peaks and valleys in stock prices get the opening call newsletter by basal chapman and your inbox every day First time subscribers also get a 30 day money back guarantee If you're not satisfied let us know and you'll get a full refund within 30 days of signing up tfnn.com educating investors Are you looking for a secured investment which pays you on a monthly basis The tiger first mortgage program may be the program for you The best rate on a five-year cd in the country right now according to bankrate.com is paying 1 per year or $1,000 per $100,000 invested The tiger first mortgage program pays 7 per year paid monthly on secured high value buildable properties in st. Petersburg, florida The investment is for four years paying 7 per year or $7,000 per $100,000 invested Your investment is secured by high value real estate in st. Petersburg, florida Your investment can be anywhere from 100,000 to 500,000 Do you want to make 1,000 per year on 100,000 dollars invested or 7,000 per year on a secured tiger first mortgage The tiger first mortgage program may be just the program for you The tiger first mortgage program pays 7 per year paid monthly for more information You can call<PHONE_NUMBER>. That's<PHONE_NUMBER> This segment is brought to you by thinkorswim For more information just click the thinkorswim banner on the front page of tfnn.com How on earth did you know that the nq would go to a leg d in the five-minute chart? Well, number one The 200 period moving average is pink line Which you would never need when you're up above it or below it until you're getting close Became the most absolute touched it perfectly at about just on nine o'clock And gave a trigger for a peak a And then you saw that the nine crossed over the 14 period And it went to a peak b and c and yet the price was holding using the nine as a walk It just walked in the nine period moving average and the manky was very strong I had it. What about we call a chapwave squash That's the reason why I put the manky above the stochastic Look at this stochastic going from what from the single digits At about nine just before nine to nine thirty after nine thirty usually positive Over 80 percent almost 90 percent 90 something percent now it's at 81 percent And the rule of thumb with the chapwave squash and the mac d and stochastic is that it should take you very quickly to peak a Peak b peak c did not talk about that I think I might have and then it pulls back and then the momentum That's the torque. That's your first second third gear And then the torque of the higher gears is the momentum from the mag d And then it finally takes you to a d and you've got your d Now what we're looking at is is it going to be a d in the 10 minute charge? Remember I said learn how to do the sequences the data goes to the weekly the weekly goes to the monthly 120 minutes is your trigger point to get in and in this case I'm using the one minute two minutes five minutes and 10 minute charge just as an example I'm not actually trading that I usually use the mini s and p Look, so there should be a leg d and above what above the high of 15,074 That's chapwave methodology in a nutshell a very simple technique when everything's functioning Smoothly when you get your bumpy ride like it gets to a peak c then pulls back gotta be careful The big issue you noticed that I didn't even talk about the semiconductors I'll talk about that tomorrow because I think the big surprise 2022 will be if we get a glut of chips And those auto companies come back on track again I think they might just never do better than me But anyway, we're closing out now. I'll do the news and then I'll be back later for the summer brine show


Members of the Fort McCoy prescribed burn team oversee a prescribed burn, November 13, 2023, along a drop zone in South Post at Fort McCoy, Wisconsin. The post-prescribed burn team includes personnel with the Fort McCoy Directorate of Emergency Services Fire Department. Directorate of Public Works, DPW, Environmental Division Natural Resources Branch, Directorate of Plans, Training, Mobilization and Security, and the Colorado State University Center for Environmental Management of Military Lands. Under contract with the post. Prescribed burns also improve wildlife habitat, control invasive plant species, restore and maintain native plant communities, and reduce wildfire potential. Prescribed burns benefit the environment many ways and are one of the tools we can use on a large scale to improve our wild habitat, said Fort McCoy Forester Charles Menzel with the Directorate of Public Works Natural Resources Branch. Menzel said prescribed burns help set back invasive species, and they burn up their seed banks. Burns also give native species an opportunity to compete against some of the non-native species, as many native species depend on fire to help stimulate them and set back non-native species.


I believe government is a necessary good, not a necessary evil. I don't think society can actually exist in any kind of healthy way without a government. And then the question is, what kind of government do we need? And I believe a government is limited, limited to one thing, only one thing. And that is the protection of the liberty, the freedom of the individual. That is only to arbitrate disputes and to protect us from the cooks and criminals and motorists and rapists and so on. So other than that, government has no rule.


You're watching FJTN, the Federal Judicial Television Network. The Federal Judicial Center presents Science in the Court Room, a series of programs for judges on science and scientific evidence. Program 5, Basic Principles of Epidemiology. This lecture is presented by Dr. Leon Gordes, Professor of Epidemiology at the Johns Hopkins University School of Hygiene and Public Health. Dr. Gordes is also a professor of pediatrics at the Johns Hopkins School of Medicine. In recent years, epidemiology has taken on increasing importance in the courts, largely as a result of the Daubert ruling that places increasing responsibility on judges to understand the scientific underpinnings of the evidence which they hear. The purpose of my presentation is to try to give you an overview of epidemiology as a science. It is done in much greater detail in the second edition of the Reference Manual on Scientific Evidence, published by the Federal Judicial Center, and in particular, in the reference guide to epidemiology. In this presentation, after a few introductory comments, I will try to describe to you the kinds of study designs that are used in epidemiology, how the findings from epidemiologic studies are used to infer causality, what are some of the problems with such inferences, and then to close with some specific comments that are of interest to judges and to the courts. If we want to know about disease in human populations, we have to be able to study human populations. We can do excellent studies in rodents, for example, but even the best such study means that we have to extrapolate from one species to another, and therefore studies of human beings are critical. Epidemiology plays this role. What is epidemiology? This slide shows you one such definition. It is the study of how disease distributes in human populations and what determines differences in disease risk among different population subgroups. Why does one group of people have a higher risk of disease than another? What can we learn from that? How can that help us to prevent disease? And if we turn to how epidemiology is used, there are many uses of which three are shown here. First, epidemiology helps us to assess the magnitude of the community burden of disease, how much disease and what type of disease is there in our community. Second, epidemiology helps us to identify the cause of human disease, a critical factor if we're going to be able to prevent disease. And finally, epidemiology is used to study the effectiveness of different types of treatments. In this presentation, I'm going to focus on the second use to identify the causes of human disease because this is the use that is most prominent in toxic toward cases. Underlying all this is the basic assumption that disease is not randomly distributed in human populations. That is, some people have higher risks of disease than others. And what we want to do is to account for why the risk is higher in some people than another in order to identify factors that can be modified in order to prevent disease. You see here a list of some tongue-in-cheek facts about carrots.  Obviously, the effects are cumulative. An estimated 99.9% of people who die from cancer and heart disease have eaten carrots. 99.9% of people involved in car crashes ate carrots within 60 days of their accidents. 93.1% of juvenile delinquents come from homes where carrots are served regularly. And finally, among people born in 1839 who later ate carrots, there has been a 100% mortality rate. Now, we might chuckle in looking at this list, but it pays to ask, what is the real problem here? And the problem is that we have no comparison group. These data are given without knowing what is the percent of people in the general population who have eaten carrots. And so underlying the questions that epidemiology addresses is the need for comparisons. And I will stress this during this presentation. How does epidemiology and epidemiologists go about their work? We basically have a two-step process seen here. First, we try to determine whether there is an association between an exposure and a disease or adverse health outcome. If we demonstrate that there is an exposure, we then try to determine whether the observed association reflects a causal relationship of the exposure and the health outcome. I will first focus on the first question to determine whether or not there is an association between an exposure and a disease or adverse health outcome. This is a quotation from the Roman or Greek physician Galen, who is well-recognized in his day as being an expert physician. He wrote as follows about the treatments he provided. All who drink of this treatment recover in a short time, except those whom it does not help who all die. It's obvious, therefore, that it fails only in incurable cases. His excellent reputation may have very well been built on the logic implicit in this, because we have here a hypothesis that could not be falsified. There was no way of disproving this. The essence of what we do in science and in epidemiology is to develop hypotheses that we can test and either confirm them or refute them. And this is an essential. I'd like to turn to the types of study designs, therefore, that we would use in trying to confirm or refute a hypothesis. The first type of study is the randomized trial, also called the randomized clinical trial, because it's often used in testing new therapies. What is the design shown here? We begin with a study population, and we randomly assign the members of that population in this slide to a current treatment or to a new treatment. We then follow up both groups of patients, determine how many die from the disease in the current treatment, and how many die from the disease in the new treatment. If the new treatment is more effective than the current treatment, we would expect to see fewer people dying from the disease who receive the new treatment than receive the current treatment. So the design of the randomized trial is basically a simple one, and it's a very desirable type of study. Let's turn to the issue of breast implants and connective tissue disease, which has received great attention. If we wanted to carry out a randomized trial of breast implants, we would identify a population of women who would be randomly assigned to receive breast implants or not receive implants, and then both groups would be followed to determine what percent of each group develops connective tissue disease. Clearly, this diagram represents a hypothetical, because we could never carry out such a study. We would never get women to cooperate. We could not do it for ethical reasons, and so it is really a totally theoretical design, because a randomized trial can be carried out only when we are looking at a potentially beneficial intervention. If we have a toxic or potentially toxic substance or a putative carcinogen, clearly we cannot randomize human populations to receive that type of agent. Nevertheless, the randomized trial is often considered the gold standard, the standard of truth that we try to emulate even in other types of study design. If we're not able to randomly assign people, we have the following type of study called a cohort study, a defined population not randomly assigned, but self-selects or is assigned by other people to exposure or non-exposure. People, for example, may work in a certain industrial plant. Others seek jobs in another plant, and then we follow up people who have the exposure and people who don't have the exposure and look at the rate of disease in both groups. If indeed the exposure is related to disease, we would expect to see a greater number of people with disease in the exposed group than in the non-exposed group. Sometimes when we approach this type of study, we may just focus on this part of the diagram. Instead of beginning with a defined population, we begin with exposed and non-exposed people. Indeed, this is what is most often done in occupational studies, where we compare people working in one industrial plant with people who are not employed there. So what we're talking about is the cohort study also called a prospective study. Let's look at this in a little bit more detail. This slide shows that in a cohort study, we begin with exposed people and compare them to non-exposed people. This is the hallmark of a cohort study. We then ascertain what proportion of both groups develop the disease in question. If exposure is associated with disease, we would expect that a greater number of exposed people will develop the disease than do non-exposed. This is the straightforward rationale of the cohort design. And if we apply this to the issue of silicone breast implants, we would identify women who've had implants, compare them to women who've not had implants, and look at the development of connected tissue disease in both groups. And if implants are indeed associated with the development of connected tissue disease, we would expect to see a greater proportion of the implant group developing connected tissue disease than of the non-implant group. So we've now talked about the randomized trial and about cohort studies. And the final study I'll discuss in this presentation is the case control study. In the case control study, we begin with people who have the disease called cases and we identify people who don't have the disease for comparison and they are called controls. Hence the name case control study. We then determine the history of exposure. What proportion of people with the disease were exposed in the past? And what proportion of people without the disease were exposed in the past? If exposure is indeed associated with disease, we would expect a greater proportion of the cases to have had a history of exposure than of the controls. Again, let's look at the implant question. If we were doing a case control study of implants, we would first identify a group of women with connected tissue disease and a comparison group without connected tissue disease. We would then determine what proportion of the women with connected tissue disease have a history of receiving implants compared to women without connected tissue disease. And if exposure is associated with disease, we would expect a greater proportion of the women with the disease, the cases to have had exposure than of the women without the disease, the controls. So what we've seen up to now is basically three major types of study design that are used in epidemiologic studies, randomized trials, generally not used for putatively toxic agents, but case control or cohort studies that are used to explore the relationships of exposure to a specific disease. Well, let's assume that we have done the study properly. Now the question is, what do we do with the findings from the study? And so to recapitulate before turning to how we analyze these data, remember that in a cohort study, we're comparing exposed people to non-exposed. And in a case control study, we're comparing cases, people with the disease, to controls, people without the disease. And we're then looking at the rates of disease in exposed people in a cohort study and we're looking at the proportion exposed of the cases and the controls in a case control study. Both of these approaches are aimed at demonstrating whether or not there's an association of exposure and the development of disease. Let's go back to our original question. We're carrying out these studies in order to determine whether there's an association between an exposure and a disease or adverse health outcome or as it's restated here, is there an excess risk of disease in people who have been exposed? I therefore like to turn to the question of how we measure excess risk. The first measure of excess risk is the relative risk. Relative risk is perhaps the most commonly used measure of increased risk. What does it mean? The relative risk is the ratio of the risk of disease in exposed people divided by the risk of disease in the non-exposed people. How do we interpret that? Well, if the relative risk equals one, it means the numerator of that fraction. The numerator is the same as the denominator. The risk in exposed people is the same as the risk in unexposed people and there is no association between exposure and disease. If the relative risk is greater than one, it means that the numerator is greater than the denominator. The risk of disease in exposed people is greater than the risk in non-exposed people and this is a positive association and it may be causal and we will shortly discuss how we move from association to causation. If the relative risk is less than one, the risk in exposed people is less than the risk in unexposed, the numerator is smaller than the denominator. This is a negative association and could be protective. For example, if we have an effective vaccine, we would expect to see a relative risk less than one because people who had been exposed to the vaccine would subsequently develop less disease than with people who had not been vaccinated. Another measure of excess risk is the odds ratio and this is again discussed in some detail in the reference manual. Suffice to say that for general purposes you can interpret the odds ratio just the way you would interpret a relative risk. The odds ratio is most commonly used in a case control study. The third and final measure of association that I would like to discuss with you is called the attributable risk and the attributable risk is shown schematically in the next few slides. Let us consider an exposed group and a non-exposed group, each of which has a risk of developing disease. This bar represents the total risk of developing the disease in the exposed group and this is the total risk of developing in the non-exposed group. For example, let us say that the exposure is radiation and the risk is developing a certain type of cancer after radiation. What do we see? We see that the risk in the exposed group and the radiated group is greater than the risk in the non-exposed group but we also see that even in the non-exposed group that was not radiated there is some risk of developing the cancer. That is that all the cancer is not due to the exposure because even some of the non-exposed people develop the disease. What we see is that the non-exposed group basically represent a background group. They weren't radiated in this example. They have a background risk and this background risk is a risk that even the exposed people share because they're members of society and members of the community. If we want to ask the question, in the exposed group, how much of their exposure can we attribute to the fact that they were exposed or to say it differently? In the radiated group, how much of their risk of cancer is due to their having been radiated, we can figure out quite clearly how to calculate this. The total risk in the exposed group is due to the exposure and to the background risk, not due to the exposure. The exposed people have an additional risk that the non-exposed people don't have. If we want to calculate how much of this risk is due to the exposure, we would take the total exposure, the total risk in the exposed group and subtract from it the risk in the non-exposed group. This would be the attributable risk. This would tell us how much of the risk can we attribute to the exposure. The attributable risk has taken on meaning in the courts because it has been suggested that an attributable risk greater than 50% could be equated with more likely than not that a specific exposure caused the disease. This is extremely controversial and complex and is discussed in more detail in the chapter in the reference manual. So far, what we have discussed are the various types of study design and how we use those study designs to determine if there is an association of exposure and disease. Now we have to go to the next step and say, is the association causal? And this was the second question I showed you in the earlier part of the presentation. How do we move from association to causation? This is a particularly challenging step. Decades ago, when the possible link of cigarette smoking and lung cancer became apparent, the Surgeon General convened an expert group to set guidelines or criteria for how we would move to causal inferences from evidence of causation. Some of these are seen on this slide. First, is there a temporal relationship between the exposure and the disease? What does this mean? If we believe that a certain exposure causes a disease, then the exposure should have occurred prior to the development of the disease. If the exposure occurred after the disease, clearly it's not consistent with a causal inference. Next is the strength of the association, also called the relative risk, which I just discussed. Third is the dose-response relationship. The dose-response relationship says that if an exposure is related to the development of disease, the greater your exposure, the greater your risk of disease should be. The association should also be consistent in different studies. And if we remove the exposure, we would expect that the risk of disease would go down. The relationship that we're suggesting of causation between exposure and disease should be biologically plausible, and we should rule out alternative explanations. And it has also been suggested that the association be specific for a certain exposure and a disease. Let me show you two examples. And particularly the issue of temporal relationship is what I would like to focus on for a moment. This is a well-known saying, post hoc ergo proctor hoc. After this, therefore be cause of this. This is a human tendency to interpret the cause of any event as being the event that preceded it, that because something follows something else, we generally assume that it must be due to that. Clearly that is not so. As I said a moment ago, we need to have a temporal relationship. We need to know that the putative cause, the exposure occurred before the disease developed, but it does not mean that every time something follows something else, that it is causally related. This slide shows the dose response relationship of lung cancer and cigarette smoking. As I mentioned to you a few moments ago, the greater the exposure, the greater the risk. And this shows that with more cigarettes smoked, the greater the risk of dying as reflected in the mortality rate. So this is an example of a dose response relationship which provides extremely strong support, extremely strong support for a causal inference. Let's stop and ask the question, what are the legal and policy implications of finding a strong association even if causation cannot be determined by using these criteria or guidelines? That is we show a strong association, the relative risk is high, but when we go to that list of guidelines, we're not able to document them. Often we just don't have the data, the appropriate studies haven't been carried out. This represents a major problem for the courts in interpreting epidemiologic evidence. We speak of factors being risk factors rather than causal factors, only because the evidence is not strong enough for us to come to a conclusion regarding causation. But it is an unresolved issue and poses serious problems for people faced with interpreting the legal implications of strong association and yet not having the causal guidelines fulfilled. At this point, I'd like to turn to some of the problems that we encounter in trying to interpret the results of these studies and in trying to infer causation. If we want to infer causation, that is to conclude that a certain exposure is associated with an increased risk of developing disease, the first question we have to ask is could the association be due to chance? To chance. Let us look at an example. Years ago, there was a major issue raised which had tremendous legal ramifications regarding the question of whether bendectin use, bendectin was a sedative hypnotic used by women in pregnancy, the question was whether bendectin use might be associated with congenital malformations. Let us go schematically through the considerations in this issue. This oval, shown diagrammatically, represents a population of pregnant women. Within this oval, there is a subset of women who've used bendectin in pregnancy, shown by the circle.  Well, what are the possible relationships between bendectin use and congenital malformations? Let's look at a few scenarios. In this scenario, we see that all the children with malformations were born to women who use bendectin, shown schematically here. This would certainly be very strongly suggestive of a relationship between bendectin use and the risk of malformations. Another possibility is that none of the children with malformations were born to mothers who took bendectin. They are mutually exclusive circles. And this would be strongly indicative that there's no relationship between bendectin use and the development of malformations. What usually happens, what usually happens, however, is that we have a partial overlap of the two circles. There are women who have a child without malformations who didn't take bendectin. Many bendectin users never had an abnormality in their child. And yet there's an overlap area of women who took bendectin and whose children had malformations. This overlap has taken place by chance, not because bendectin caused the malformation, but just because you would expect with these two-size circles that there would be some overlap between the two. Where does the dilemma arise in interpreting that? When a child with a malformation whose mother has taken bendectin is presented to the jury, what the jury is seeing is a child from this area of overlap. But it doesn't take into account what is the probability that this overlap could occur by chance. And so we have statistical methods that are not part of this presentation for addressing this issue of the importance of chance and could the findings we have of an association be artifacts of chance? The next issue is that of bias. When we come to interpret the findings of a study, we have to ask whether there are mistakes made in the study. And there are many types of bias. One is selection bias. Who has been selected for the cases or for the controls? Was there a bias in the way we selected them that would cause us to come out with certain findings? Or in a cohort study, is there a selection bias in who was selected as exposed people and who was selected for the comparison group of non-exposed? We may have a bias in the type of information we obtain. How good is the information? Does it differ from one group to another? And what we try to do is to minimize the types of bias that might occur in a study and also to characterize the bias so we know the extent of the impact that the bias could have on our findings. I'd like to turn next to one of the most important issues in trying to interpret associations and to derive inferences of causation. And this is the issue of confounding. It is discussed in the reference manual in detail, beginning on page 369. This diagram shows us a causal association. We observe an association between a certain characteristic or an exposure and a disease, and the characteristic or the exposure causes that disease. This is a causal relationship and causation here is indicated by the arrow connecting the two boxes. It is also possible, however, that we can observe an association as shown here not because the characteristic or exposure causes the disease but because both of them are linked to a third factor. Both are linked to a third factor and that results in an observed association that is not causal. For example, this slide shows two possible interpretations of the well-known association of increased cholesterol and increased risk of coronary heart disease. On the left is a causal relationship, on the right is a confounded relationship. Here we see that increased cholesterol causes an increased risk of coronary heart disease. Here we see that increased cholesterol is observed to be associated with an increased risk of coronary heart disease, not because they're causally related but because a third factor called factor X is linked to increased cholesterol and is a cause of coronary heart disease. What could that be? It could, for example, be the genetic profile of the individual. There could be a group of individuals who have a genetic profile that puts them at increased risk of coronary heart disease and that same genetic profile is associated with an increased cholesterol. Well, you might ask, why do I care? What's the importance of this? The importance is that if the true model is what we see on the left, then if I can intervene and get people to lower their cholesterol, I can anticipate that I'm going to be able to lower their risk of coronary heart disease. But if the model is a confounded one that we see on the right, no matter what I do to reduce the cholesterol, I'm unlikely to have any impact on the risk of coronary heart disease which is being caused by that genetic profile. So understanding whether a relationship is causal or confounded is extremely important. Here is another example. Many years ago, Dr. Brian McMahon, Professor and Chairman of the Department of Epidemiology at Harvard, reported an association between increased coffee consumption and cancer of the pancreas. The question arose, was the association that he reported a causal one or was it the result of confounding? On the left again, a causal relationship. Increased coffee consumption causes an increased risk of cancer of the pancreas, and therefore we have an observed association of the two. On the right, we have the same observed association because both are associated with factor X. What could factor X be? One suggestion was that factor X could be cigarette smoking. Cigarette smoking is known to be a cause of increased risk of cancer of the pancreas. It is also known that you almost never find a cigarette smoker who doesn't drink coffee. There's a close link between cigarette smoking and coffee consumption. So that if we observe an increased risk of cancer of the pancreas in people who drink more coffee, it could be not because there's a causal relationship but because both of them are associated with cigarette smoking. Clearly the interpretation has major clinical and public health implications depending which one appears to be correct. Finally, I want to show you a more recent example of a study that appeared within the past few months that raised the question whether high blood levels of Agent Orange are associated with a high prevalence of diabetes in adults. The authors reported an observed association of increased blood levels of Agent Orange and prevalence of diabetes. Well, what does that association mean? It is possible, if the association is true, that we are really seeing the result of a causal relationship. That high blood levels of Agent Orange cause a high prevalence of diabetes. That is certainly one explanation. But the possibility was raised that this association that we observe might be due to confounding. How could that happen? We know that obesity is a risk factor for diabetes. We also know that the dioxins, which Agent Orange is a mixture, dioxins are stored in the fat tissue, in the adipose tissue. And therefore we would expect higher blood levels of dioxin in people who have more cells storing the dioxins. Therefore it is possible that we observe the association between high blood levels of Agent Orange and high prevalence of diabetes because both are associated with obesity. Obesity we know is a risk factor for diabetes and obesity is linked to high levels of Agent Orange in the blood. This has not yet been clarified what the nature of this relationship is. But it is evidence that the problem of confounding is a terribly important one that we have to take into account. And it is a problem that you're going to hear about in the courts as you hear expert witnesses testify about whether confounding has been taken into account in a given case. We will come back to that in a few moments. What is the problem in the courts? We can have a recognized confounder, such as cigarette smoking in the example I just gave you, or we can have unrecognized confounders. We can have it as a legitimate problem. That is, there can be a potential confounder, a factor that we know may be a confounder but it was not studied in the research that's being reported and presented as evidence. And that would be a deficiency in the study. But we often hear the statement made in trying to dispute a study quote, all confounders have not been taken into account but no specific confounders that have been omitted are listed by the person who is trying to disparage the study. The world is full of potential confounders. All we can expect is that confounders will be taken into account if they appear to be likely to be relevant in the given situation. And so the second statement is much too general to be worth very much. The person who wants to make that criticism has to say what are the specific confounders that could have affected the relationship that were not taken into consideration by the investigator? At this point then, let's just summarize. If we observe an association, it can be non-causal or causal. If it's non-causal, it can be due to chance, to bias, or to confounding. Or it may indeed be causal. I'd like to turn now to some questions regarding science and scientific evidence. These are questions that have been raised with me over the years by judges who are dealing with epidemiologic evidence in their courtrooms. First, why don't human and animal studies always agree? This can be very disturbing. One scientist gets up and testifies about findings from animal studies, and epidemiologists may get up and testify about findings from human studies, and the findings don't agree. We're obviously dealing with different types of subjects. You cannot automatically extrapolate in dose or in effect from animals to human beings. And so there are very legitimate reasons why the studies may disagree. Secondly, we are asked, why do epidemiologic studies or epidemiologists often disagree? It's a more difficult problem, and the reason we often disagree, maybe not that often, but the reason we may disagree is because there may be questions about certain methodologic issues in the study. There may be questions about differences in how we interpret the data. And this can be extremely complex. Judges will ask, why do many scientists often refuse to commit themselves and seem to hedge in their opinions? Is because there is not an end point in science. The scientist is seeking the truth. Today's truth may be modified tomorrow by further studies, where the dilemma arises that in a trial, a judgment has to be made yes or no. But science doesn't work in that way. It works in small increments of knowledge, and we are always subject to having our opinions refuted to make decisions. And finally, how can I tell who is an expert whom I can reasonably believe? Judges tell me that they are besieged by experts, and they don't know whom they can trust and whom they cannot trust. I'd like therefore to comment and to offer some personal opinions about how I believe you can try to assess an expert witness. I'd like therefore to comment on an expert witness. I would ask the following questions. What are the educational background and the training of this witness? Did the person train at a good institution and a good training program with reputable people? Second, is this person a professional witness? Does he or she make most of his living from being a witness? If the person is an itinerant witness, I would tend to have a greater level of skepticism about the testimony to be offered. Third, has the witness worked, done peer review, published research and teaching in the field or discipline in which he's testifying? Or has the person come from a totally different field and become an instant expert in epidemiology or in any other field? Does the witness always give an extreme and unequivocal position? I mentioned a few moments ago the importance of uncertainty and of changing opinions in science. Does the expert acknowledge the limitations and uncertainties and admit to the possibility of being wrong? Can the witness name other people working in the field including some people who disagree with his position? And finally, if the witness can name those people, can the witness state the reasons why those people disagree with him? I think that these questions can provide very useful guidelines regarding the potential testimony that the witness is going to provide. Perhaps one of the major questions that epidemiologists are confronted with in the courtroom is the following. Can we derive causal inferences regarding disease in an individual? The judge will say did this person's disease occur because of this exposure? The problem is that epidemiology is not well equipped to answer that question. Epidemiology can answer the question best whether a certain exposure has been shown to be capable of causing this disease in human populations. But in a specific individual in whom there are often multiple exposures for example such as at an industrial site it may be very problematic to come to a conclusion regarding the question of whether a specific exposure has caused the disease in this individual. I mentioned earlier that the attributable risk has been used particularly by lawyers with an attributable risk of over 50% being considered by some to be an equivalent of more likely than not. But I should say that this is a use that has been made by lawyers discussed on page 381 of the reference manual because it is an important issue. The issue of whether we can draw a conclusion regarding the cause of disease the cause of disease in a specific individual is one where epidemiologists would generally say they cannot draw that conclusion but in which the courts are desperate to be able to draw such a conclusion and therefore gone to this issue of attributable risk. It is a legal decision and not a scientific or epidemiologic decision to use attributable risk in this manner. I'd like to briefly mention a problem and that is the problem of how the data and conclusions are presented. Words have great power and you don't have to be right or wrong to convey an opinion with subtleties of how opinions are expressed. I'll give you two examples. First we have the question of the relative risk that I spoke to you about before as against the absolute risk. What is my level of risk? Not a comparison just what is my level of risk as an individual. Sometimes we'll look at relative risk and say the relative risk really shows a 20% increase. You say gee that's quite high but then you say well what is the absolute risk what is the baseline risk here and you say well in 100 million people. Well a 20% increase of that risk is minimal. So it's not just a question of saying there's a 20% increase the question is what is our starting point what is the baseline and depending on one's opinion one may choose to express it as a 20% increase or one may choose to express it as a baseline risk. So we're often using the means we choose to express the risk it often reflects the feeling we have about whether or not there is a true risk and what we're trying to convey. Let me show you another example. Let us say we carry out a study, a clinical trial a new therapy and an old therapy and we look at the mortality in both groups. In one group it's 94% and now with the new therapy it's 93%. Well you might say that's really not much to write home about. 94% versus 93%. Doesn't look like it's having much effect but someone else who may be advocating for the new treatment comes and says oh no you're not looking at it correctly let's look at survival with the two therapies. Survival with the old therapy was 6% it's gone up to 7% here we have a 16% increase in survival with these two therapies which is true the answer is they're both true. Again it's the question of how you choose to express the findings and therefore if you're hearing scientific testimony in the court you have to be asking always has this person specifically chosen a certain way to present the findings that may tend to color the conclusions. Another issue that I alluded to before is the question of whether an exposure is a risk factor or a causal factor. There is yet no unanimity among epidemiologists in defining risk factor as against causal factor but most of my colleagues would probably say that when the evidence is not strong enough to make it a causal factor but there is evidence of an association we would tend to call it a risk factor but the exact point of demarcation is not clear and often these two terms are used interchangeably even though they may not mean exactly the same thing. Finally in closing I would like to stress what I consider one of the most important issues that I've mentioned earlier. There is a tremendous need to accept uncertainty and to deal with it and I think this reflects the difference in culture between the scientific community and the legal community. Many of my colleagues say they do not want to participate in legal proceedings they don't want to be impeached by lawyers because of their opinion about whether a certain agent caused the disease because they believe there is a level of uncertainty that would qualify their comments and yet when they get into the legal arena they often feel that they are being forced to make an unequivocal statement yes or no regarding whether or not a substance caused the disease in this person. I believe there is a tremendous need for us to bridge the legal and scientific communities to see how can we make both groups more comfortable with each other so that scientific evidence can be best used in the cause of justice and of truth. Thank you.


So our journey through spectroscopy begins about 150 million kilometers in that direction, the Sun, which is showering us with, well, at the moment far too many photons, as you can see, and they will travel across space, they will hit the upper atmosphere, they will dodge various molecules from ozone to carbon dioxide and carbon monoxide and so on, and land somewhere here. Now what happens next depends on a number of different factors, but we're mostly going to be talking about frequency and energy, and that brings us to our first equation, Planck's relation. We'll unpack this a little more as the course goes on, but I first want to draw your attention to how this is, like many physics equations, simply two values linked by a proportionality constant. The same is true of famous equations like E equals MC squared, and other thermodynamic equations like the ideal gas law. This makes the Planck relation less of an equation for something and more of a definition, and a key relationship between two physical properties. This equation relates energy E to frequency nu, and the proportionality constant between them is H, Planck's constant, named after Max Planck, who first proposed that energy is quantized and related to frequency this way. This equation tells us the energy of a photon of light. In many respects, saying that a photon carries with it a specific frequency is the same as saying that it carries with it a specific energy. They're the same thing. So properties related to frequency, like wavelength, are also a measure of the energy of the photon. The nature of this photon is a question for the quantum mechanics course. So for now we're just going to blindly accept that a photon has a frequency and wavelength, which means the electric and magnetic fields are oscillating back and forth a certain number of times per second, while also accepting that the photon is a single discrete particle that can't be broken down with a set position and momentum. So when it comes to visible light and ultraviolet light, the energy of a photon is enough to start moving electrons around, and if you can move electrons around, that's a chemical change. From quantum mechanics, we know that electrons are bound to discrete states that we call orbitals, a bonding and anti-bonding orbital for instance. It takes a set amount of energy to move an electron from one orbital to another. Only this much energy delivered in a single burst will do it. If this photon has the right frequency and therefore the right energy, it penetrates deep into the cells of the leaf, and into the chloroplast where it's absorbed by a magnesium-containing porphyrin called chlorophyll, and kick-starts the light-dependent photosynthesis reaction. But if it's the wrong frequency, it's too much energy or too little energy, it bounces off and into our eye. And if it's not the right frequency or energy for photosynthesis, it might just be the right frequency to stimulate the green cone cells in our eyes. And that means that colour, this thing that we take for granted around us every day, is one of the first bits of evidence for quantum mechanics, and is itself a very crude but effective form of electronic spectroscopy.


So, here I'm talking about Python for cloud services and infrastructure. Let me tell you something about myself. I'm Bomic. I came from India. I have around five years of development experience. I'm an open source savvy guy. I love Python. I do some DevOps and site reliability things. But my core will be the cloud. So let me tell you my current product and a little bit about it. So we have developed a smartphone case which can read your body vital when you place finger on the case like this. It will read your BP, ECG, heart rate, skin temperature, SPO2, and it will show those things on your mobile and sync it with the cloud. So I worked on the cloud part. So this talk is all about cloud and internal components. So yeah, to build any web application or any cloud services, we have these questions for us like from where to start, which tools we can use, how to integrate stuff, and things needs to be taken care of. So from this presentation, you will get all these answers maybe. So yeah. So I'll let you know the Python-friendly stack that I have been using since three-plus years, and which is very reliable. So of course, any application, any web application, or any cloud service will have this kind of set of components you need to prepare where there will be some web framework, WSGS server, task queue, database, login, caching, and many other things. We also need to take care about other components like this. So we'll discuss all these things later on. So start with where to start. The first thing will be the web framework. Let's finalize the first web framework. What kind of web framework we are going to use. When it comes to the Python, we have two famous framework available, which is Django and Flask. Django is fully armed and fully included things inside Django. But Flask, well, it's kind of a small framework, which is very extensible. So you can attach other things with this Flask. So these two are most famous. I always prefer Django because it has a few things included, like authentication is there, so you don't need to worry about all other things. Yeah, so how to run our web application. So we need WSGS server, WSGS server. So what kind of WSGS server we need? It basically gets the data from the upper layer and process the data inside the process and generate one output, which can be a response and send it back to the request. If it is a request-response thing. So we have two good WSGS server available in Python. These two are most famous. So one is G-Unicorn and one is Micro-Wisky or U-Wisky. I generally prefer U-Wisky because it has much more configuration power. There is no specific reason to, you can choose any of them. So yeah, we should have some WSGS server. Next question will be database. So what kind of database we need? I mean, either it's a SQL database or no SQL database. It's based on our use case. So if we have some data elements, which we need to be relational, so we need some SQL database. So these are a few databases that we can go for. PostgreSQL is there, MySQL is there, and won't go to be for no SQL. So currently in that product, in that cloud, we use MongoDB for the 90% of the transactions. So no SQL you can use for if you have some unstructured data. So yeah, that's the thing. Next is web server. So any client, any request will not directly communicate to the WSGS server. It will pass through the web server. So web server will take care of all the requests. It handle it and pass it to the WSGS server. WSGS server will process it and return back the response. So this is the general architecture we need to figure out. These two are most in use web server. Actually, these two takes 50% of internet traffic right now, combinedly. So yeah, either you can go for Apache or you can go for Nginx. Nginx, mostly known for speed. And Apache mostly has some configuration power. So based on your use cases, you need to define your web server. Yeah, this is very interesting. Next is the task queue. So when you want to perform some ad hoc tasks, like on some request, like if you are creating one account, one create account request comes. And you want to generate some newsletter or some email thing that can be done in a distributed way. So you should have a task queue which can perform all these things. So if you write your task queue, it's good. But we should not write our own task queue because it's already there, which can solve few problems like queuing, like a retry mechanism. For example, there is one task came to send one email to a customer, which just registered himself on our website. So if there is something failure happened, we should have some mechanism to retry that. So that is one. Some timeout, some scheduling, or some status of the task, maybe. So that can be solved by some existing task queues. Celery is most famous there. Redis queue is there. I always prefer Celery because it has a good dashboard as well, has good monitoring of tasks. So yeah, you can go for Celery. So next is logging. So logging can be event-based, or the full logging feature could be you can log everything or some specific. So I always prefer Sentry over there because Sentry has a good logging power as well, plus it provides one good dashboard where you can search your data, event-based data, and all the events you can monitor it from it. It also provides notification. When you configure your event, like if any error occurs, you should get an email. So that can be done by the Sentry. CloudWatch is under the option. So you can go for it. Yeah, you also need to take care about other components. As I said, like source control, it's a must thing. I think everybody does this. So yeah, a specific version, if I want to check out some specific version, so source control will do it, all things. It also provides good history and accountability, remote accessibility. These two are most famous source control system. One is Git and SVN. We use Git there. So deployment and configurations. So these two are most important thing after the development when you want to check out a repository in the cloud and remotely access this server and execute some SSH, execute some commands through SSH, or maybe that can be done. So few things are there. Like fabric we use. It has a good SSH-based remotely accessibility. And Ansible Chef Puppet can be used for configurations management. And deployment could be automated, not manually. We should not do that. So Jenkins is there. Jenkins will do all the automatic deployment initiation. After getting deployed, all the things, we should have keep our eyes on process and system and activities. So we need to monitor system. Like how many nodes are there in our server system and cloud? Each server has their health, and we need to monitor all those things. For that purpose, we use NegiOS. NegiOS provide a very good monitoring platform where we can monitor all the system as well as processes. When I say processes, it means there can be UWSDA processes. I mean UVSGI processes. Or Nginx is there. So we can monitor Nginx from the NegiOS or MongoDB service running well or not. So that can be monitored through NegiOS. Sanctuary is a kind of monitoring service where we always monitor our logs if any error occurred. If any unusual thing happened, then we can directly be notified by an email. So Sanctuary is a good kind of monitoring service there. It's basically a logging system, but it provides some kind of monitoring. Supervisor is there. So a supervisor will do and control your processes. You can start. You can stop from that dashboard. So you can configure by your use case. So supervisor is also there. So yeah, cache is also one part of our cloud where we need to have some cache mechanism based on our use case. If we are serving static content on a website, then we should have some front end cache. And if we are serving some content, not the static content, but some content which can be reusable or frequently asked. So some caching mechanism we can implement by Radis or Memcache D. We use Radis there. So yeah, messaging. So in messaging, I would like to share one use case where messaging can help. Maybe you have a multiple app servers or multiple DB servers, or let's take an example of app servers. For example, three app servers are there. If one app server is doing some task and wants to notify others that I have done this task, now you can start. So at that time, messaging can be useful. We use RMQ, RevitMQ, many people say, which provides some pubs of mechanism, public and publisher and subscriber, where a subscriber can join and subscribe to the server. And it will be notified if we publish something on the channel. So yeah, it is a messaging, that's it. Yeah, virtually. So I love this feature because it provides one isolated Python environment in your system because you can have a n number of Python environment in the system. And if you are working on a different, different project, you always have different dependencies. So virtually, we will help there. You can create one environment. You can install the dependencies like I need some dependency of version 1.0. And another project, you need some dependency of 1.1. So it will be isolated for each of them. So yeah, it's a really great feature.  So analytics can be done by either you can use Google Analytics for the static page where JavaScript can send data to the cloud and it will show you on the dashboard. Or you can use internal analytics where you can build your own dashboard. So there are a few tools available, like Graph Fight is there, StessD is there, which can send all the metrics to the cloud and Graph Fight will arrange it into the graph. Yeah, a few other things we need to take care of is scaling. It depends on your use case, what kind of usage you have. You may have a database overload, so you can scale your database vertically or horizontally. You can have a performance-based scaling where your application number of applications are not sufficient. So you may scale those applications and servers. You should have a periodic backup of your data, which can be done through Jenkins and Fabric jobs. You need to figure out how you can do it. And your application and periodic backups may provide data reliability. So your data will always be there if you have set up all those things then. And load balancing is there where through Nginx or through Apache, you can kind of load, balance your load. Yeah, that's it. Any questions? Thank you. Thank you, Belmi.