general synchrotron radiation facility looks like. So first of all we had to have some electron sources and electron source may be a cathode. By heating we can get the electrons or by field emission or by the photo electron effect. So there should be some source of electrons. And after some source of electrons there will be a small accelerator which raises the energy up to certain level and which can be injected into the synchrotron. So this is the first synchrotron which is known as injector machine and it is a booster synchrotron and it raises the energy up to certain level which is desired by the storage ring. This may be this energy may be equal to the storage ring energy or this may be slightly lesser than the storage ring energy. So when energy of electrons reaches up to the desired ring in the booster then this beam is extracted from this point you can say this is the extraction and using a transport line this is the electron beam transport line. We studied many kind of optics means photo and other kind of optics. Using these kind of optics we can make a transport line and this transport lines through via this transport line electrons are injected into the storage ring. Now on each bending here are the bending magnets. So on each bending synchrotron radiation is emitted and these radiations are guided up to the experimental station. So on a storage ring when electron keeps evolving and it keeps radiating here and whatever the energy is lost in the form of radiation RF cavity replenish that energy. So electron revolves at constant energy and many different experimental station can work to simultaneously. Now we see what is the effect of this synchrotron radiation on betatron and synchrotron motion. Does it affect the motion of the electrons? Yes it affects. So how it affects? Suppose it is the oscillating electron means these are the betatron oscillations and I am plotting these oscillations in the vertical beam means this is the vertical betatron oscillations. Why vertical beam? It will be clear. Now at this instant it is passing through the dipole magnet. So it emits a photo. Electromagnetic wave is emitted from this electron. Means we can see that this was the momentum of the electrons prior to photon emission and photon carries such momentum from the electrons. So now the momentum of electron has been reduced. Now when electrons momentum has been reduced and it passes through the cavity again cavity gives the energy and makes the momentum as equal to this. So this momentum and after passing through the cavity equals the same means we replenish the momentum lost in the form of photon by the RF cavity. However again you can see that here in this case again I am trying here for clarity. Here it is the PY component and it is the PS component. Cavity replenishes momentum via PS only. So PS component has been increased while PS component remains its reduced level. So this angle of particle trajectory with respect to design trajectory has been reduced means Y prime has been reduced and if Y prime has been reduced means amplitude of betatron motion has been reduced. Means emission of radiation damps out the betatron oscillations. So there is a kind of damping due to radiation in the betatron oscillations. In horizontal plane as momentum changes by photon emission and emission is taking place inside the dipole magnet where the dispersion is non-zero. So picture becomes a bit complicated than the vertical plane. So for clarity I draw here the vertical plane rather than the horizontal plane. In case of horizontal plane we have to take care of the dispersion also. So this is the damping coefficient when we calculate for the vertical plane how the vertical betatron motions are damped. So this is the damping coefficient when we write down the equation write d2y by ds square plus twice alpha dy by ds plus ky is 0. So this 2 alpha is this. You can see that this S subscript in these formulation shows synchronous particle means e s means synchronous energy ds is revolution time of the synchronous particle and e radiated means how much energy is radiated during the one time. So if we increase the energy e radiation also increases and damping coefficient increases because e radiation increases as e raise to power 4. So as we increase the energy alpha y increases rapidly and betatron motion damping become fast and this is the damping coefficient for the horizontal plane. Here the factor is same as for the vertical plane however one more factor is there due to dispersion and this function depends on the dispersion this is dispersion d and this is the banding in radius and this is k in the dipole magnet means if dipole magnet has some gradient we can modify the damping coefficients of the machine. What is the benefit of modifying the damping coefficient of the machine we will see later in this. So emission of the radiation takes away some energy from the betatron oscillator and oscillators damped out. Now about the synchrotron oscillation synchrotron oscillation also damps due to emission of the radiation. This damping is known as radiation damping radiation damping means emission of radiation helps us because it makes beam sizes smaller. So if we inject a larger beam size in synchrotron radiation source or electron machine it damps out after a certain period and becomes smaller. Now this is the I am taking three particles at three different energy levels. You can say central particle is the synchronous particle which has a synchronous energy and this particle is at higher energy and this particle is at lower energy than the synchronous one. Now suppose these all three particles passing through the dipole magnet and emit synchrotron radiation. Now higher energetic particle because of the gamma raise to power 4 dependency will emit more and it will emit least. So this emitted and after emission this becomes the energy level of this particle. Synchronous particle also emits some radiation and this is the final energy level of that particle and this is the energy level of the particle having least momentum. So now you can see that this gap between higher momentum particle and synchronous particle in energy has been reduced after emission of the photo. And similarly is the case that here the gap between the energy of the lower momentum particle and synchronous particle has been reduced after emission of the synchrotron radiation means energy deviation between the particle has been reduced due to emission of synchrotron radiation. And if energy deviation is reduced means amplitude of the synchrotron radiation has been reduced. So synchrotron oscillations also dance out due to synchrotron radiation. And this is the damping coefficient of the synchrotron oscillation. Here you can see that derivative of DE radiation by delta E because there is a delta E term. So emission or damping coefficient will depend on the delta E energy deviation and when we differentiate it we come off with this number. So this is the damping coefficient in longitudinal plane. Now you can see that the factor is same here also. So alpha x was k I am calling this factor as k 1 minus this dispersion related term. Alpha y was only k and alpha s is equal to k 2 plus this factor. So if you will add these three derivative coefficients this is a constant for a given number. This constant number means alpha x plus alpha y plus alpha s is a constant. Now if damping is there slowly slowly beam will damp out, emittance will be reduced and emittance will become zero after say 100 or 1000 multiples of damping time. No it is not the case. Actually there is a counter phenomena of damping that is known as quantum excitation. So far we considered the emitted radiation classically. Means a nicely fan is built and continuous emission of the radiation is taking place when acceleration is there. However quantum mechanical picture is defined. In that case photon emission is probabilistic. There is a probability of the emission of the photo means an electron can emit different number of photons in different terms. Or you can say different electrons in the same term will emit different numbers of photons. And there will be a definite energy distribution also. So it means photon emission has some kind of randomness. And some kind of randomness means on electron beam there will be random kicks due to photon emission. And when beam will have some random kicks due to photon emission each particle has some random kicks. So overall amplitude of betatron and synchrotron oscillation will increase. So quantum excitation will increase the emittance and radiation damping will decrease the emittance. And at a particular number of emittance these will be balanced. So that is the equilibrium emittance of the machine. So this is the equilibrium emittance. This formulation shows you the equilibrium emittance. So in electron machine after few damping time the equilibrium emittance will be attained by the electron beam. So here you can see that this is a Jx. Jx is basically these numbers. These number is Jx. So for Jx we say 1 minus Jy is 1 and Js is equal to 2 plus this function of dispersion. So you can see that summation of Jx plus Jy plus Js is 4. As alpha x plus alpha as alpha y was constant and this is a 4. So Jx is this number. And in this number this is a function of dispersion. We have seen it. So this is a function of dispersion, bending radius as well as gradient in the dipole magnet. And now you can see that this edge depends on the dispersion. This quantum excitation strongly depends on the dispersion. So this number is basically the coherent Snyder invariant like we have gamma x square plus twice alpha xx prime and beta prime square. So instead of x and x prime use d and d prime and you will get the edge. Now you can see without going into a detail of this formula seemingly some dependence. You can see that emittance depends on gamma square. And gamma square emittance means as you increase the energy of the machine emittance increases. As you increase the gamma, this gamma and this gamma is different. This gamma is relativistic gamma factor and this gamma is the twist parameter. So keep it in mind. I am talking about this gamma means relativistic factor. So if you increase the energy gamma increases and emittance increases. And now you can see that if r is constant r bending is constant in a synchrotome means all the magnets all the dipole magnets are same are having the same bending radius. There are no different kinds of dipole magnet used in making the lattice. Then we can write down h by r cube r will be outside of this average bracket. And they will be 1 by r formula finally. Emittance x in that case will be varying with 1 by r means if you are making r larger means smaller bending per magnet then you will get a smaller beam emittance. I am talking so much about beam emittance. We will see it that radiation damping and quantum excitation these two phenomena governs the basic equilibrium emittance. And equilibrium emittance actually shows you the brightness. Brightness of the SR. So if you want to increase the brightness of the emitted radiation you have to reduce the emittances. Brightness is directly proportional to 1 upon emittance. So that is why you need very very low emittances in this synchrotome radiation sources for increasing the brightness. So emittance can be low if you are having a low energy machine but however if you are having a low energy machine then harder x-rays cannot be obtained.  A bigger synchrotome will give you the lower emittance even at higher energies. And how to control this Jx? It is a complicated function of the dispersion and twist parameters here you can see. So bending radius gradient dispersion and twist parameters all comes into picture of this formulation but this formula strongly depends on the dispersion. So by proper shaping the dispersion in the optics means properly choosing and optimizing the magnets so that your dispersion is in the desired beam then you can control the beam emittance or you can reduce the beam emittance. So this is the major goal of a synchrotome radiation source designer that how to reduce the beam sizes how to reduce the beam emittances and this reduced beam emittance enhances the brightness of the emitted radiation. So we see now something. Suppose we put a dipole here because we are talking about the dispersion then the most important magnet is the dipole. So suppose this is the dipole and this is the S and suppose we put a quadrupole here means suppose dispersion is dispersion and then quadrupole sends this dispersion and this dispersion becomes lower in the dipole magnet and again becomes higher because this dipole magnet will again enhance the dispersion. So dispersion will come again at higher values again put a quadrupole magnet and again this dispersion. So this value of dispersion and this value of dispersion will be the same means we have a periodic solution. This kind of lattice can be used for making the SRS because in this case we have reduced dispersion inside the dipole magnet significantly. However you can see that this optics has no space for dispersion free region means everywhere dispersion is non-zero and for some kind of elements such as RF cavity or injection system we need dispersion free region otherwise a bit complicated occurs. So for obtaining the dispersion free region we need some other kind of lattices. So this kind of lattice although can be obtained for low imitances is not useful for making the SRS. So again the first choice comes by the double band acromit which we have studied during our acromit part and this is SRS. Here you can see we can take a periodic solution like this dispersion is increasing here due to dipole magnet then going the dispersion here like this and you make a series of quadruples to make the acromit and here you can see that another quadruples are there to take care of the focusing of complete beam of beta functions and alpha functions. So this combination takes care of acromitic condition as well as vertical beta function and these quadrupole magnets takes care of vertical and horizontal twist parameters. So this kind of lattice is the basic choice for making the SRS this is a double band acromit. However you can see that if you want to make an acromit you cannot reshape the dispersion in this magnet because there is a unique value of dispersion which is needed here say d1 d1 prime to make the acromit means dispersion here is 0 and it's derivative 0. So when there is a unique value of d1 and d1 prime you cannot tune dispersion to other values to reduce the emitances. So why not put the third dipole magnet in between and that can be used for controlling the dispersion and controlling the d1. That is a triple band acromit and even though you can reduce further the emitance by introducing more dipole magnets inside the acromit that is known as multi-band acromit. So multi-band acromitic lattices are the preferable choice for making a very low emittance storage links for the synchrotron radiation sources where we can get harder X-rays with higher brightness. Now in our country in RR cat Raja Ramanna center for advanced technology indoor we have synchrotron radiation sources. These are the only two synchrotron radiation sources in our country and these are housed in the RR cat. So it is the simple layout of that facility here first of all there is a microtron which raises the energy of electrons up to 20 Mb source of the electrons is situated inside the microtron and then there is a transport line which sends the beam in this booster synchrotron and this booster synchrotron then after attaining the energy desired energy level of the electron beam it sends in two storaging. This is the Indus-1 storaging and this is the Indus-2 storaging this bigger one. So this Indus-1 storaging is a small synchrotron radiation sources and its operating energy of the beam is 450 Mb so emitted radiation is in the soft X-rays and this is a bigger machine Indus-2 and it is a 2.5 G beam energy inside this ring and it is producing harder X-rays for experimentalists or for users. So you can see here 16 dipole magnets are used to make this Indus-2 and on each magnet there is the radiation coming out and in one cell you can see this is a schematic of the Indus-1. Indus-1 is a very small storage ring so four dipole magnets are there making the four super period and in each super period two quadruples before the dipole magnet and two quadruples after the dipole magnet is there. This is the RF cavity based in the ring and now you can see the twist parameter of this Indus-2. You can see that this is the dispersion which is minimized inside the dipole magnet to reduce the impedance and you can see that here nowhere is the dispersion free zone in Indus-1 however this is a small machine we can run with non-zero dispersion also. This is a bigger machine this is the circumference of Indus-1 is only 18 meter while circumference of the Indus-2 is roughly 172 meter. So you can say Indus-2 is 10 times bigger than the Indus-1 and this is a unit cell or super period of the Indus-2 here two dipole magnets are there means we are making double band achromate. This is a dipole magnet this is a dipole magnet this is the variation of the dispersion so dispersion is like this again it is after the dipole magnet is G. So this is double band achromatic lattice there are three quadruples in between to take care of the achromatic condition and three quadruples here and three quadruples are here for optimizing the twist parameters. The equivalent beam emittance of Indus-2 is 58 nanometer rad. So now you can see that here 58 nanometer rad is the beam emittance and roughly in the range of 3 to 20 meter 3 to 20 meter is the values of beta function. So you can calculate at different location what is the beam sizes beam sizes will be square root of this emittance multiplied by the beta of that location that will give you the beam sizes this will come out in hundreds of microns. This is a picture of booster synchrotron you can see that these are the dipole magnets these there are six dipole magnets in six super periods are there in this booster synchrotron this is the RF cavity and these magnets are quadrupole magnets and this is the transport line coming from the microtron beam is injected here and beam is extracted from here and it is going towards the Indus-1 or Indus-2. This is the picture of the Indus-1 installation it is a very small drain 18 meter circumference and you can see that there are four dipole magnets 1 2 3 4 these are you can see this one this one these one are the radiation beam line by which synchrotron radiation is coming out and beyond that hatch there is experimental station here RF cavities placed to replenish the lost energy of electrons and this is a part of the Indus-2 where we are going to inject the beam in Indus-2 in the beam from the booster comes via this line known as transport line 3 and it is injected here you can see that at the injection optics is very complicated we did not cover the injection in this course because it is a different and typical scheme to inject the beam in any synchrotron and you can see that they are green tiny magnets these are small dipole magnets for correcting the orbit these blue magnets are the quadrupole magnets you can see this is first coil second coil third coil and fourth coil is beyond this this is quadrupole of the transport and these are the quadrupole these bigger quadrupole are the quadrupole of the industry you can see two coils are seen here for this quadrupole this is the RF cavity of Indus-2 so RF power source is kept beyond this wall and these four cables these are co-excel cables feeding that RF power to this RF cavity this is the RF cavity so you can see that four RF cavities are there shown in this picture actually Indus-2 has six RF cavities and these are the quadrupole and this is a bird's eye view of the lattice of the industry so again references are seen and each book covers to some extent about the synchrotron radiation and how we can choose the correct chromate for meeting the lattice in next lecture we will talk about the protons and chromium which will be used for expedition source


Well as the sun goes down behind us here in Tetro, qualifying is done and dusted. Lake Cumbermati Zegar pulled out a flyer and finished in the top spot, but Leon Madsen, our current championship leader, six points clear of Bartos, came in third. So let's hear from him and the rest of the guys. Yeah good, the practice went well, the qualifying went well and I could pick gate number one, so that was working well for me in Molyland, hopefully I can do that again tomorrow. It was good, the first two laps for me was okay, I was fair, but when we race the qualification lap was not perfect, but we will see what happens tomorrow, I hope it will be good, I'm feeling good track today, so let's start. As usual practice is not the best for me, but I seem to wind up more in the race time, so overall I feel pretty good, felt comfortable on the bike, so tomorrow is a new day and we're ready for some action.


Let's go down everyone. Chris from jaspierscasebricks.com, 2022 Panini Absolute Baseball, 10 box Casebrick number 4. Nothing too crazy going on at the end, so we'll just get right into it. Thanks to everyone who got in on this break. Our players down from Kevin, down to Kim. And here are our teams from Atlanta, down to Washington. So one roll for both the players and our teams. Good luck everyone. Thanks again for getting this filled out. A five out of five is ten. So ten times. One, two, three, four, five, six, seven, eight, nine, and last one ten. Five out of five is ten. Ten times right here. So Daniel, down to Nestor. And then our teams, once again, five and five is ten. Good luck. One, two, three, four, five, six, seven, eight, nine, and last one number ten. Baltimore Orioles down to Maya, Los Angeles Dodgers. Freeway series, that should be a fun one. All right, so let's get this a little bigger so we can see. Here's our first half. So Daniel with the O's, Kim with the Cardinals, Eddie with the Royals, Robert with the Mariners, Larry with the Brewers, Josh with the Padres, Nick with the D-backs, Chris with the Tigers, Lonnie with the Marlins, Chris M with the Twins, Lonnie with the A's, Nestor with the Blue Jays, Kevin with the Reds, Daniel with the Guardians, Lonnie with the Phillies. Good to the second half here. Ryan with the Cubs, Lonnie with the Giants, Mark with the White Sox, Daniel with the Yankees, Lonnie with the Rockies, Nick with the Rangers, Daniel with the Red Sox, Stacey with the Nats, Austin with the Braves, Chris P with the Rays. Nice, congrats. Jonathan with the Astros, Nick with the A's, Robert with the Pirates, Jason with the Mets, and Nestor with the Dodgers. All right, want to pause the video real quick, see if there's any trades going on, and after that we'll get this break going, we'll be right back y'all. So no discussion going on, so we're going to get right to it. Happy Tuesday everyone, thanks for stopping by today.  Don't really appreciate it, but I guess that's the skin of the game. Jaws is a good one. It's also his body control, he's a good one too. He really does remind me of Derek Grosz when it comes to what he can do driving or mid-air. So here is our case of Absolute Baseball, and here are our players across the South States. Number four on our Absolute Break. Thank you very much once again y'all. No R&Bs, nothing too crazy so I'm going to get right to it. Good luck everyone. That's the one thing, I guess you can be a good shooter, you can have good handles or whatever, but when it really comes down to it, to have that kind of body control is really what makes good players great. It's still the most efficient shot, is Alaya driving with shots within two feet of the basket. It's actually my first time breaking this product in particular. Yeah Joe's been playing recently, it's been a nice little well of mine as I try to fall asleep unsuccessfully. But it's nice Joe. You know what, I want the skills of Bo Jackson. Yeah, just being an all-around incredible athlete. Throw it, hit it, run it, catch it. I mean, taking the athletic ability of a multi-sport athlete. Tennis, golf, cycle, run, swim, everything. All-around, all-around loss. They pay him the big bucks for a reason, Joe knows. Our booklet right there. First hit, Carter Crawford, rookie ink out of $199, going to the Boston Red Sox, going to Daniel. Grade baseball name, 80 grade baseball name. 36, 96. 96 out of $199. Nice. One of one. Iconic ink, Ronald Acuna Jr. Wow. First boxing of this case. And we got a really nice one for Austin and the Atlanta Braves. Austin congrats. Ronald Acuna Jr., one of one. Wow. Good start to the day, folks. Tools of the trade, Ole Ho Lopez for the Cincinnati Reds. What I'm saying is, I don't want to give those to Joe now, but I want his tables so they use those. Bo Jackson with the fingers, too. Does he play the guitar? 87 out of $149. Stan Musial, Stan the Man out of $99. 17 out of $99 for the Cardinals. Buy Storm Shohio Time. Rookie Class Con Waller. Aaron Ashby, Rookie Materials. Let's go into the Milwaukee Brewers. Let's go into Larry. What's up, Joe P. 136 out of $299. Our booklet. Luis Fries, $95 out of $99. Go into the Arizona Diamondbacks. There we go. Jose Fernandez, Lakebird Jose Fernandez. Luis Fries, Arizona. Rookie Baseball signatures out of $99. Let's go into the Diamondbacks. Go into Nick G. Serenade the folks back at home. $25 out of $25. Mad Max shows our New York Mets edition. Go into Jason T. Be pretty nice. Get some music in the back. Royalty Free, Joe displays the classics. That Spanish guitar. What do you think of that? I think of the last of us. Whoa. And there it is. Hill, H-I-E-E-R. I should have learned to play the guitar. Should have learned to play them drums. Got a redemption. For the Angels, iconic ink. Joe Madden. Angels edition of Joe Madden. That is a... This probably came out about a week or so ago. Maybe a little more viable. 62 out of 75 on the Joe Madden iconic ink. Christian Walker. Two color patch. Established threads. Another one going to the Arizona Diamondbacks. And Nick G. This guy turns into Babe Ruth against the Dodgers. Very annoying. Two out of $99. And a printing plate of Just Dangers. JD Martinez. Another one of one. JD Martinez, Boston Red Sox going to Daniel. One of one printing plate. Nice. Let's get to our redemption. That works, Joe. Good luck, everyone, our redemption. He's incredible. I mean, not incredible. He kills the Dodgers. That in itself is incredible. Spectrum Gold. Nice. 157. Joe Ryan. Joe Ryan Rookie Baseball Materials Booklet. Spectrum Gold. I know that is going to go to the Minnesota Twins. One of the non-traditional little favorites for Rookie of the Year so far for the American League. That's one of the Minnesota Twins that's going to Chris and... Nice one, though. Oh, awesome thinking. Joe Ryan. So we're getting a second booklet in this box. 25 camp boxes. I think it's kind of crazy, like the progression that we've had with the face guards for the helmets. Because no one was wearing them until Stan got hurt. 2013, 2014. And now it's commonplace. Everyone has the guards. The chin guards, the face guards, whatever you want to call it. Statistically speaking, Frank Chance out of 99 is going to the Chicago Cubbies. 79 out of 99. Frank Chance out of the Cubs is going to Ryan. Ryan Peep. Established threads, Jeff McNeil. Going to the New York Metropolitan. Going to Jason T. 63 out of 299. Our second booklet of this box. Chase McCormick, 29 out of 50. That's going to the Houston Astros. Blue. Orange Patch. 29 out of 50. Going to the Houston Astros. Bang, bang. Going to Jonathan B. Matt Shabman. 95 out of 99. Yeah, man. Happy Tuesday. You want to turn us into like Chuck E. Cheese? I'm convinced that Jesus Jasper, one of the other many J's here. One of the sorter and shippers along with me. Can program anything? Fix our stacker. Build this PC here. I guarantee you can figure out the animatronics. That kid is a wizard. Another manager. Marks of Fame for AJ Hinch. Remember how that one engineer at Google thinks that their AI could be sentient? Yes. Terrifying. Terrifying. Just don't say that, man. Don't say that. I don't mean to know that. 101 out of 199 AJ Hinch for the Detroit Tigers. Mario is a definite possibility. Great. Curtis Terry on PA. 150 out of 1 at 99 on the Curtis Terry. Two Swatch Auto. Another one for the Minnesota Twins. Going to Chris M. Did you pull a Joe Ryan earlier? I did. Joe Ryan of Redemption. He's making the start tonight. He's been quite good. He's been quite good for his Logan Gilbert tonight. Two pretty solid rookies. Logan Gilbert at one point was looking pretty nasty. He cooled down a little bit as a rookie is supposed to. But they've both been really good today. This season. Ryan Vellani for the Rockies. You say Rockies don't hit. 210 out of 299 going to the Rockies and Lonnie. Shoeless Joe. 181 to 199. Are you a foot-flops guy, Joe? Do you like foot-flops, sandals? Are you a shoeless guy? Are you relaxing or after I work out or something like that? Slided to some slides? I was never a slides guy. I told you I got the easy slides. They're super comfortable. Red Sox, what are they? The third wild card at the moment, yeah? We can only hope. Mike, we can only hope that that is the case. Mariahs. O'Neal Cruz, a rookie class. 107 out of 149. Very Pirates. Going to Robert Teem. Another one, going to the Buccos. Renasi Contreras, rookie materials. 43 out of 299. And a Buccos box here. Your booklet. 34 out of 99. O'Neal Cruz. Very nice. When he comes back up, I think he's going to start getting some people up an arm. He's good. Out of 149, Blue Jean-Carls stand for the Yanks. If there's nowhere else we'd rather be. In your ears and in your pockets, Logan. We always appreciate y'all sticking in. Tune in wherever you may be. Work home on the road. Like Joe likes to say, from coast to coast and around the world. From coast to coast and around the world. Thanks for making this part of your day. We're at Rosa Beach, California. It's not as muggy as it has been today. I like to wear all black and jeans. I like cold. That's a good question Rex. I mean, I sorted enough and broke enough of the prison football to know that prison football was pretty dang good this year. I'm hoping the same thing for prison basketball. And then we will obviously see what the flawless tomorrow with the football. But if the flawless football and flawless basketball and of course in a lower sense, the baseball. Super high end, I mean, sheesh. Penini goes out with a bang. Potentially. I want to see him stick around though. We've got some great products. Rookie class of Matt Manning. That's 25 out of 99. Team Tandem. Randio Rosarena and Brandon Lau. 107 out of 199. Two swatch. Two color for the Tampa Bay Rays. Going to Chris P. And our next book with T.J. Friedel. Going to the Cincinnati Reds. 39 out of 50. Going to Kevin M. I like leaf though. I am a leaf guy. Rhino, Ryan Sandberg for the Cubbies. 28 out of 149. Got a B-Fresh to Refresh. You got a Subway, E-Fresh, Refresh. You got a B-Fresh to E-Fresh. You got a Refresh to E-Fresh. Matt Manning. Just won a 999. These look super clean, I think. I think absolutely it's been pretty nice looking this year. Going back to football as well, the football. That's a nice one. 292 out of 999. Another one for the 20s. Absolute Inc. of Ryan Jeffers. Second year catcher for the twins. 135 out of 199. And a Tools of the Trade. Wow. Four patch auto. 10 out of 25. Four patch three color. This patch right here on the top right. Some of it's sticking out so I'll be a little careful with that. But another one going to Nick Galvin in the D-backs. D-back's doing pretty well. In this break, the IRL will wait a few years. But Drew Ellis out of 25. Another tool of the trade. Extra hit here. Three Swatch. Aristigas Aquino. Cincinnati Reds. Going to Kevin M. 54 out of 199. All worthy, Miggy. Box 5 here. I agree, Rex. I think it's tough because of the amount of like, they're high end, quote unquote high end stuff. Like these eight player, 10 player, like 15, 20 player autos with patches. It's just hard to get those kind of things around, circulated. I would love, you know. But even just like the sole players. It's a one of one. I got a five and a three. Whoa, single digit numbers. Just send it to them. It's a lot of retired players, you know. I don't want to say these guys don't have a lot going on, but they can sign some cards, you know. Not sure twice a month. As they enjoy their legacy. Being immortalized on a card. I do love Weave. Jake Myers to 999. Houston Astros Edition. Marks of Fame of Louise Petino. Tampa Bay Rays Edition, Louise Petino. 81 out of 199. Another one going to the Tampa Bay Rays. Tools of the trade. Luke Williams. Phillies Edition. You can know he's currently on the San Francisco Giants. This will go to the Philadelphia Phillies and Elani. Dual patch rookie auto. At a 75, 15 of 75 Luke Williams. And for quote unquote my fish. Brian Anderson. Tools of the trade. Dual color, dual patch. 150 out of 199. A-Rod, Mariners Edition out of 199. 144 out of 199. It definitely, I think it can. But they have some pretty impressive looking cards. Some good products. Back to potential. Could have had class. Could have been a contender. Historic duals. Ken Griffey Jr. and Alex Rodriguez. Both for the Seattle Mariners. 42 out of 199. Jorge Lopez. Another cool looking patch. Three color patch on the left. Two dollar patch on the left. Two on the right. Triple swatch. For the Baltimore Orioles. 29 out of 49. Going to the O's. Going to Daniel. Our next booklet. Brian Dale Cruz. 84 out of 99. Going for the Miami Marlins once again. Going to Elani. 44 out of 99. Another Stan the Man. Just about a 25. 5 for 25 on the Stan Museum. What's the city that him and Griffey were both born in? Hopefully done. Rex getting upset. I didn't even know that was possible. I thought Rex was an unfeeling monster. Box 6. Yes. DeNora. Thank you Diego. So yeah. The Griffey with the A-Rodder 149 to the Stan Usual. Once again. Griffey getting second place in that little mini box. The second... They have the same... They have the same birthday too, yeah? Griffey and Usual. That Griffey is the second best outfielder born in DeNora, Pennsylvania on so and so day in history. Just because he shares a birthday with Stan Usual. Tough break. Desire Gray. Nationals edition. 658 out of 999. Going to Stacey. Rent Honeywell. Absolutely. 24 out of 199. For the Oakland A's. Lonnie C. Tower of McGill. Nice one there. Dual patch. Auto. Rookie Auto. Tools of the trade. 43 out of 50. I think it's a 23rd. That sounds right. I get you Rex. Don't worry. 43 out of 50. And an Amir Garrett. Other tools of the trade. Dual color patch. I'm a dual swatch. 21st. 53 out of 99. Waddy. 76 out of 1. 49 on the blue ray wave. I get it Rex. Trust me. I know exactly who you are boy. Because you're me. Man I love yonder. Other Frank Chance. Statistically speaking. This time blue out of 1. 49. Out of 1. 49. Territable. Territable. And Casey Meyers. 82 out of 1. 99 going to the tires. Going to Chris P. Our next booklet. Jose Ciri. Another booklet going to the Houston Astros. Two color. Patch. Jonathan B. Pre-Priching the choir brother. Look at me. 39. Bang bang. Pete Rose is a shop in Vegas. That he he'll sign anything at. You can go to Pete Rose. Baseball, Jersey. Anything in between. And he'll sign it. You can make a napkin. He'll sign your t-shirt. I think it's pretty crazy. The mix of active players they get too. These are pretty decent active names too. They're a little weird. That's why you're not sorry. I like this one. It's different. Luis Heal. For the New York Yankees. Out of 9.61. Daniel. With the Yankees. Taylor Chamele. 133 out of 1.99. For the Seattle Mariners. Robert T. Sometimes you can't do what you gotta do for a buck. Nice. Piece of the lumber auto. 20 out of 50. Jake McCarthy. Another one going to the Snakes. Those Serpientes. Nick Jean. And a Stephen Max. Two. For the St. Louis Cardinals. 11 out of 99. I won't judge too harshly. I will have to. Nice. Out of 1.49. Chris P. Randomized the Tampa Bay Rays. Out of 1.49. Very nice. Shane Bass. Teammate of Wander Fongos in Tampa Bay. Rookie Materials. 264 out of 2.99. Our booklet. Tony Santillon. Out of 1.99. Go into the Cincinnati Reds. Kevin M. A lot of breaks still. Pretty close. Those R&Bs in particular. After that, just that one box of triple threads. Fills out the rest of that NT baseball. Jacob DeGrom. Out of 49. Going to the New York Metropolitan. Going to Jason T. A 99. Shane Bass. Out of that. And then the R&B and the triple threads. The optic football number 39 on the left side. The hanger. Fills out the mystery crate. Dan B. Leaves the yard. He's been hidden really well. He's been hot. Atlanta Ribs of 1.14 straight. 13 straight. Pretty sure. Dan's Bay Swanson. Frank Hiller is Frank Hiller Joe. What's in the name? The name says it all. Mitch White Absolute Ink for my Dodgers. Nester. 88 out of 1.99. Mitch White. Otto. Rookie Otto. AJ Alexi. Tools of the trade. Rookie Otto RPA. 183 out of 1.99. This patch on the right. I don't think it's camouflage. But Elias Diaz. Game used? Game used by Panini. But Elias Diaz. It looks like tobacco juice. It looks like tobacco juice. Pretty interesting. I've seen the dirt stains. I've seen the grass stains. But I don't think I've quite seen the dip. The dip on the jersey before. Some slander. I don't know about that. Tools of the trade. Elias Diaz for the Rockies. Another one for... It's always Rocktober. For Lonnie. After this break, we were doing the giveaway. Allworthy Gary Carter. 74 out of 9.99. Going to the New York Mets. Absolute Heroes. The GOAT. 159 out of 199. Clayton Kershaw. Patch going to the Dodgers. Bookwood. 49 out of 9.99 on the Spencer Strider. Atlanta Braves. Austin. Juan Soto out of 199 for the Nats. And the Man. Two more boxes. So looking for a kaboom as well. You know. That just makes the game use stuff so much more valuable. You know? What if he touched it? He didn't put it on, but he put his hand on it. He got his fingers and dust particles. You know, maybe some germs. Maybe, maybe not. That's how they get you, man. Icons of Jimmy Fox. 65 out of 99. That's going to be the Philadelphia Athletics. So the A's. We'll be going to Lonnie. Team Tandem. Vladimir Guerrero and Beau Bache. Dual color. 62 out of 99. Going to the Blue Jays and Nesca. Brooklyn. 53 out of 99. Shane Bats. The Black Baseball. Another one for the Reyes. Another one for Chris P. Wilson Contreras. Out of 149. Looking like potentially the NL All-Star Starter behind the plate. For the Chicago Cubs. Joe, incredibly fast. Joe, do you ever play any PC games? Do you ever play any? No. There was a summer of Starcraft. Nice. Donnie Hernandez for the Rangers. Rookie, Inc. 23 out of 199. Going to Nick A. I never got into Starcraft. Never had a PC until a couple of years ago. Starcraft is okay.  I like those things, you know. Kind of game. You can kind of get, kind of get addicted to it. Another one for the Reyes and Chris P. Rookie signatures. Barrel. Four out of 50. Josh Lowe. And a Bryce Wilson tools in the trade. For the Pittsburgh Pirates. Don't know if you lose. I don't know if you're going to win that fight. 110 out of 199 on the Bryce Wilson. Going to the Pirates. Going to Robert. Robert T. Your 2021 A.L. Rookie of the Year. Randy Orozarena. 129 out of 149. Big Mac. Alright, last box. Thank you once again for getting this break off, Philadelphia. Our first break of the day after this. We'll be doing our giveaway. Joe doesn't, you know, fight for the fun of it, the exhibition. Yeah. You got to put something up. Joe Pizzle had, like, chip on his shoulder. He's like, I could beat you in a type of war. Joe, Joe here, Joe Jasker would, Joe Jasker only fights for the money. He's a prize fighter. I need some, uh, something to prove for Joe Pizzle. I'm good at stuff too. I could beat you. Look how high I can jump. Yeah, look how high I can jump. Uh-oh. Joe P. wants to get some on me on it. This one for last. Alright, last box. Thanks again everyone. Good box. I'll look for a Kaboom as well. Kidding Sour? That's crazy. I am as sweet as an apple pie. 12 out of 75 on the working ink for the pie. Joe Pizzle is the one with the chip on his shoulder. Another one for Robert T. 1, 3, 5, 7, 9, 8. Are there your odd numbers right there? Tony Santillon. Triple Swatch RPA. Another one for the Cincinnati Reds. Kevin. 38 out of 50. Dual collar on the pinstripe. The thick pinstripe. It felt like the piping at the pants problem. Another one. Well, maybe there's the Kamel actually. Are the Rockins? Are the Rockies rocking with a Kamel jersey? I just didn't know about it. You know what, where was Elias Diaz before? I didn't know I had a Padre. Tools of the trade, Elias Diaz. This is an advancing pointer of Jesus Sanchez. There we go. Look there. Anaheim Angels Edition. LA Angels of Anaheim Bartolo. Elias Diaz. Elias Diaz. Yeah. Elias Diaz. Was it Pittsburgh for half a second? That would do it, yeah. I know they wore those Kamel jerseys. Yeah, then he's been in Colorado the last few seasons. But still. Kamel jersey. I don't know where the Rock is. For the AO? Actually, Pittsburgh for a number of seasons. I don't know. Maybe three full seasons? Three full seasons? Maybe Machado, statistically speaking, blue. It seems like a Plutuny sort of situation. I know he was probably split in time. If he was in Pittsburgh, probably split in time with Jacob Stallings. Most likely. Pretty solid catcher. A 2 out of 1.49. Aaron Judge, established threads. We're talking awards. I know who's going to be in my ALMBP if the season ended right now. All rise. 88 out of 99. Our last booklet. According to Vegasinsider.com Mackenzie Gore is your favorite to win NL Rookie of the Year, plus 175. He's been pretty dang good for those Padres. And Julio Rodriguez leading AL plus 125. Really? I know he's picked it up certainly, but... I would say Payne. He's been tough. And then behind, in the NL Mackenzie Gore Nolan Gorman, 4 to 1. He's been good. Atletom is 16 to 1. 27 out of 99 on the Ozzy Albeas. Historical duels. So, that is going to be it. Nice. Thanks very much everyone. Congrats on those who hit. We have absolute baseball number 5 on the website right now. Jasper'scasebrakes.com. Thanks for getting our day started. We'll be right back. A couple more breaks.


My name's Roberto, and for those who don't know me, and for those who do know me, I'm Steve Roberto, so I'm gonna be, this is the last talk, I know you're tired, I know you wanna go bar hopping, I'm gonna be doing my best to keep you awake. So I work for Critical, because it's a cryptographic, a customer cryptographic creation company, we also do software development, and we love Django, myself and the company. We've been backers of many high-profile Django projects, like the Schema Migration Project, like High Performance Django by Peter Baumgartner, and we are goal sponsors of the Django Vest framework Kickstarter. I've been doing software development for 29 years. My first claim of fame came by helping reverse-engineered Nintendo, so if you ever got fired by playing a sloppy made pixelated games in your cell phone, that's on you, not on me. In the Django world, I'm known for a few projects, and one of the most recent ones who have had a lot of visibility is my young EDMS, it's a document management system done entirely on Django. So how I got into this mess. In 2013, I was appointed Director of Software Development for the Government of Puerto Rico, and I had to oversee the creation and use of software in the government. And one of the projects I was handed was that the Governor of Puerto Rico had just signed an executive order ordering all government agencies to start sharing data electronically, but we had no infrastructure to do that. And this is the problem, this is the scenario I was given. We had at the time 142 government agencies, each of them creating and accumulating data in completely incompatible formats, and with no way to share the data. Some of the most forward looking agency did try to fix the problem on themselves, but because there was no policy, no oversight, the end solution was the same. Everybody just kept wasting money doing completely non-interoperable interfaces and export of the data. So pretty much this was my reaction to what is going on here with. So I realized we did not understood the problem. So the first thing we did was just make a checklist. What do we need to make this happen? Okay, we need an export, an universally compatible export tool where we can take any data, government data, and export it into new formats like JSON and XML, and regardless of what the original file format was. And then we realized that does not exist in the universe. So basically we just had to create it ourselves. We just were a new experimental software development department for the government, so let's honor our name. Let's start development, developing. And this is what we came on. We came up with Libre. It's actually a background to create an engine to free up government data. Libre in English means free. So it was also kind of a political statement. This is the ego I view basically what the platform actually managed to do. We can take completely heterogeneous data source regardless of format in the place where the data is being originated. And just by doing a simple description of how the data is in corporate structure, we can import government data. We can do versioning on the government data, and we can start hosting also open government data from the same product because infrastructure is also another big problem in the government. You can have, you have very few government agencies that have good infrastructure. Most of them will collapse as soon as they get 100 concurrent users. We also had to create a unified query language because our users are now more technical. The public is more technical. So some people do want to see just an infographic but most of our users now just want access to the data themselves to do statistic analysis, mathematical analysis. So we had to come up with that in an unified way so that our new clientele, the developer clientele could filter, could select what they wanted. And we had to support as many output formats as we could not just the original file format. We had to support JSON for JavaScript development. We had to support XML. So Django's rest framework was very crucial in this part. So now we can have completely outdated government data and it can be used in a lot of different scenarios. So this is now how Libre fits in the whole ecosystem. We can have now all government agencies producing data, how they know how to produce it. And we can now drop in this tool and they don't have to change anything internally. How to do things, how they keep producing this data. And yet the data can now be shared, can be used by all the government agencies or the general public. And we can start turning stuff very ugly stuff like this.  They have no kind of validation. They didn't tell you anything. And we can start turning them into beautiful stuff like this that a software developer can use without having to worry about importing the file. We can turn completely ugly stuff like this. This is a cheat file. It is a very bad name for a file format because it's not a single file, it's a distribution of files. You can blame ESRI for that. And we can turn them into this. The tool also had to support geospatial capabilities which is another big topic in the government. The government has a lot of geospatial data that is being produced. But it's being produced sometime in outdated formats. In Puerto Rico we had most of our maps, our state plane projection in that 27 format. It's a format that was standardized in 1927. And we started to move to that, not 1883. It still was not interoperable because it was a state-centric format. And with this tool, we can convert all those data completely transparently into WGS 484 which is a geocentric, it's a world-centric projection. That's how now Puerto Rican data can be plotted in stuff that is designed to work around the world. So basically we are modernizing government data. For developers, for example, now they can take a legacy cheat file from the government and using the Libre platform. They can, we can render a map and a developer can just capture the map in an iframe and you can actually now incorporate geospatial capabilities in your software without having to write code just by capturing a render map from a query you just issued to the platform. And you can just start doing stuff like this from data that was originally came from outdated cheat files that were just accumulating big rot in a government server and from Excel spreadsheets. So this is the kind of reaction we started getting from the developers but the administrators started hating it because they already have this amount of work and DevOps are very stressful people. They have the weight of the infrastructure on their shoulders and having them create descriptor files for the files that they were going to import into the platform was very much becoming another obstacle into the platform. So that's where the Django administration tool came into the rescue and on top of that Django suit allowed us to create this new web interface where a person without no knowledge of how to create a Django file can describe the file format that they are going to export. So now DevOps, which are sometimes the only technical person in a government agency staff now he can without having to know be a data scientist as a software developer now he can use this tool to start exporting its government agency data. And we started getting this reaction and this is so software development is so easy I want to become a developer myself. So that's how successful the conversion to Django admin was. So the came from, we started, the platform got very popular in Puerto Rico so we had a company whose name started with M means very small and soft at the end. And they said, no we already fixed this problem that you are reinventing the wheel. We have tools that create web services from all our databases. Now, which ones of you work with web services? Which one of you like working with web services? Nobody, see? So the problem with web services is if you don't have sufficient documentation have any one of you have tried to reverse engineer a complex type from a web service without documentation? It's not possible. So you're very dependent on documentation and web services have become a way to promote vendor locked in. Another problem is the standardization. That's why we jumped from WSDL 1.1 to 2.0. And there's a 1.2 and 1.1.3 draft that never made it into the public because they were completely interoperable. And the tools that are created in WSDL files, the website description language files sometimes create description files which are not even interoperable between one vendor or the other. So it's like trying to assemble an IKEA table with instructions and bad things tends to happen. And so web services were just outside the door. So the tool had to be a rest-centric tool. Even if people didn't like it we had to do because there's a beautiful thing about rest. Rest and JSON are self-documenting. Even if you don't have documentation, you see these and you know it's a dictionary. It's a key value pair. And even as cryptic as the key value is you still have a rough idea what this is and how to operate it. And because we are using Django rest framework from the same solution now we can re-explore using Django rest framework vendors to a different formats. And I love this. This is why our company is a gold sponsor of Django rest framework. The browser ball API allows developers to start playing with the data to start exploring the data and get used to the data even if there's no documentation for it. So what about a unified query language to be able to access all these completely different data sets? This is the same reaction we got from the company whose name starts with M. They said, no, we already solved that. There's something called SQL that's used for accessing data where you want to create the re-create the wheel. Because stuff like this, this is the name, this is the source code from an actual website, a government website, I'm not gonna say the name. Shout out to our government. And they're actually concatenating and creating an SQL statement in JavaScript, trusting user input and not doing any kind of sanitation or checks. So I talked to the developer that did this from that company and I was gonna ask him if he knew about SQL injections and sanitation, but I said, no, I'm gonna ask him even a more interesting question. Did you know who Bobby Table is? And he said, no, so that was my answer. So SQL was out of the question too. Because SQL is not a standard, it's a structured query language.  It is not. This is an actual question in Stack Overflow I did while creating the platform because I wanted to know how to limit the amount of results in a result set for that query. And it turns out it's not even that simple thing, it's not even standardized across databases. So we ended up creating our own language. It's called the Leakworld, the Leakworld query language. Now another problem with data exporting tools is that you need a software, a server, and a client. So still you get that element of bend or lock in. So what we did is we created a RESTful query language. Basically the URL is the query that will give you filtering a selection and slicing for the data. Here we have an example. This is a shape file, a polygon from the municipalities of Puerto Rico. And if you, the URL is kind of small. But if you see it, I'm asking, I'm having to prove two predicates. I'm selling it, give me only the shape, the polygons whose properties in the name municipal, which is municipality, contains the fragment GUA ignoring case. So I get GUA, GUAS, BUENAS, GA, GUAS. And instead of getting just a data, I'm telling it, give me that, render it into a leaflet now. This is a very nice feature of Django REST framework. The renders can also give you maps or charts or tables. They don't necessarily have to be numbers or serialized data. This is another example of a simple query. This is the crime points of the department of police. And we are filtering just for the crimes of PSY4, aggravated aggression. This is the kind of thing now we can filter, we can start analyzing just by rewriting a simple URL. Because we were using Django and leaflet, we're starting incorporating Django's templating system into leaflet, popup and markup language. And now from Django, we can start customizing, creating customized map and we created a map builder. And we can start doing stuff like this. I can take a shape file from one government agency and start doing stuff like this. This is the whole universe of crimes in Puerto Rico being filtered by the result querying from a polygon of a municipality from the Puerto Rico planning board. Basically this is a join between two data sets completely different, two completely different government agencies. And this is a municipality centric querying. And this is a URL that produces that. There's no code, it's just one URL. Looks complicated, what you will see in a moment is actually just four elements. And even with the first two, you can produce them up. The last two are just cosmetic markup. The first thing is I'm telling the engine what is the data I want to work with. This is the crime data. And I'm telling it filter all those crimes where the geometry of the crime, in this case a point, falls within the geometry and the minus bracket is a subquery marker. Where the encompassing geometry is the result set from a simple query to the planning board asking just for the polygon of the municipality called Arecibo. And the JSON path is actually slicing the properties of the geospatial feature and just giving me the data points, the map points. And then passing that then to the geometry and doing a filtering. So this is basically a typecasting during runtime from the URL. This is then, this is telling the engine to render a map, not giving me the data points and to be able to see the outline because the map wouldn't produce anything. I'm passing also context to the renderer. Please pay me the outline so I know what I'm filtering about. Because knowledge of the language there was a little bit of barrier so we created also a query builder for the tools and this is where you can start experimenting filtering data, you have a preview on the bottom and you can do stuff like producing the result set as a dictionary list. So it is already processed to be able to be plotted into a chart. You don't have to do any post-processing for example in JavaScript and you can take that as it is outputted into stuff like D3JS and already start plotting charts. Excuse me.  And we can start using doing stuff like this. This is an egocentric, a self-centric result set of the same crime map or the same crime data. I'm asking the engine show me all the crimes in our radius from where I'm standing from and the query is even simpler. I have the same police crime data but I'm filtering instead of filtering for the result set of a polygon, I'm filtering just for a point and because points don't have area, I'm doing a buffer which in this case, in this projection and zoom level is just 0.1 arcs which correlates to roughly 10 miles. So I'm basically telling the engine give me all the crime that have happened where 10 mile radius from where I'm standing to see if I'm in a danger of being mugged or assaulted or killed and it's a good place for example to do a party because the only thing that has happened is you saw aggravated aggression, just a fist fight. So if I'm gonna park my car, I know that it's a good place because car theft has not happened there in the timeframe that this data set was created. And we can do also this, this is called feature analysis. I can see how the crime behaves in regards to a geographical feature. In this case, this is the PR 22 Puerto Rico's biggest highway and it has been criticized that there's enough police, I don't know how to say this in English, but the routing, the preventive patrolling. So we did this simple analysis and we can automatically know that at the south to the south of the highway, there's basically no crime happening in the time set which is two years that was collected. So there is something happening at the north of the highway that's causing a bigger crime rate. I cannot tell you what it is, but now I can give you the observation to do the right questions. And this is the start of the scientific methods. I give you the observation, now you explain why this is happening. Before this, we had no idea this was even happening. The query to do this is basically the same, but instead of a circle or a polygon, we are creating a polygon runtime just for that point as square. So this is more in that now how the tool works. This is now more nitty-gritty details because I cannot filter or give users the data every time they requested it. It is a very heavy operation. We took a page from DNS. This is a write once, a worm, write once, read many times. So all the processing was moving to the import phase and this is the import phase. The first thing we did is do a scheduler because I cannot trust the government agencies to give me the data. They basically have to go and get it forcefully. That's how great they are. And the next step is to do an audience layer. So I tell the engine how to get to the data. Once the engine has the data, there's a data driver's layer, which is to tell us how to understand, how to process the data. It's an Excel file, a REST API. It came from a shape file. Then we serialize the data to store it to be able to store it in a database because it's binary data and for this specific implementation, we chose base64 encoded pickle files so that they can be stored in the database. Base64 pickle file. This is your cue to squirm to get nauseated. So it's not glamorous, but for this particular implementation, we wanted just to get the data out. So no MongoDB, no fancy infrastructure, just code one order of magnitude of your worst case scenario. See, you never thought you were gonna get a business less informed with Django to come to the center. And this is now the read part. This is where we process the request for the data. Just cookie cutter stuff, Django REST framework does most of it. We make sure that the user that is accessing the data has access to the data. Is it maybe we want to control these specific data set just for government employees or maybe it's a public, completely public data. Then we pass it to our own custom engine where the query is split into its parts. Filtering, grouping, aggregation and segmentation. The data is then deserialized from the database and rendered in whatever format the user is asking it. And then we just pipe that to the response, to the response object that Django REST framework supports. Now that, and this is a bookmark of the presentation, that's where the project died. After 12 years, I became tired of the hate if you're a software development in a place where nobody's technical, you get a lot of hate. If you work in the government, you get even more hate. You get hate explicitly, implicitly and secretly.   And the public in general, you are just a government employee.  So after 12 years of being a lightning rod of hate, I decided to move forwards. And now the company where I work for are very open for community projects and we are actually hosting our own copy of Libre and hosting public government agency in our infrastructure. So basically we are doing the government's job. And with this data hosted, now we can start doing really cool stuff like this, like for example, creating dashboards using completely disparate data. For example, this is the section of the data sets of the Department of Energy Agency has really not much interesting data like how much clients they have, how much energy they've sold. You can see it in the table. But when you plot it into stuff like this, you start seeing patterns. You start seeing correlation. You start seeing behaviors that should not be happening. That's for example, in this chart, you see that the amount of industrial clients, the power company has to excuse me because this is from right to left. At this time we had, we hadn't even implemented ordering in the engine. That's fixed now. So the power company has lost two thirds, two thirds of their industrial clients. And yet their revenue for the concept of industrial income never decreased. That's not supposed to happen. So we started selling stuff like this. This is for example, the dashboard of the health department. Puerto Rico is a tropical island. We have a lot of mosquito-borne based disease. Sadly, some people do die, but diseases are preventable. It's just about making sure that people get the help they need at the right time. So there's a lot of money allocated into awareness. If you see now, if you, when we plotted this and we added the data of asthma, the problem of asthma in the island completely overshadows the problem of mosquito-borne diseases. And when you look at the amount of budget that's being allocated for asthma research and asthma awareness, it's just a fraction of us, mosquito-borne diseases awareness programs are getting. And when you plot stuff like diabetes, it completely crushes the problem of asthma, even though both are chronic diseases, asthma diabetes is a really big problem in the island. And when you put hypertension to something very interesting happen, the behavior of hypertension in the island almost directly correlate the behavior of diabetes in the island. So a statistical will bark at this and say correlation doesn't imply concession, but you cannot deny that there's something happening there. The government of Puerto Rico also wanted that we have a very big problem in the town halls. The people are leaving the town centers because of technology, now they have Netflix and stuff like that. And the central government wanted to start giving free wifi in public spaces. And they were starting already to allocate a few million dollars till we got this map up. This is the map of all the municipalities which were by their own initiative giving free wifi in the town centers. So they were fixing the problem in the first place and fixing the problems and getting people already into the public spaces. So just this map save a few million dollars in budget. And this is the same crime map, like I said, created just using just an iFrame with just refilters, municipality, time, and type of crime. And when you start running this, you start seeing time-based crime maps and you see how crime is more organic than you think. Crime behaves very differently from the time of year and even, excuse me, from the time of day. We started seeing how most crimes have a peak at 2 a.m. And yet how Steph, it speaks was 9 a.m. 9 a.m. and 12 p.m., 12 p.m. Usually the times the working class were outside the homes. So even doing stuff as simple as sending employees at different time brackets to have lunch at their houses would have reduced the problem of house theft. This is, this was one, a very interesting data. This is the department of solid waste data. And they give it to me, they were very nice. This was one of the few government agencies that really cooperated with the effort. And he said, but this really was worthless. They had that, I'm gonna give it to you and say, just put it out there. People are gonna find a way to use this. And they did. This is a project from a hackathon. They actually won this mobile app, a web app. It was created by three university students in less than 24 hours. And it's called GeoTires. And it's this scenario for the application is you're just doing internal tourism in the island and suddenly your car, you got a flat tire in a place you have no idea. You don't know anything about that place. So the application will give you a map using our technology and give you all the places where you can go fix your car before you become stranded with the metadata so you can call negotiate places. And if you click, we'll give you the route to get there as soon as possible. All this from a data from a government agency that's actually disappeared because that's how unimportant the government think that is from a data that even the government agency was producing it thought was worthless. Now we can have a commercial, a product that can resolve a real social problem. And this is a snippet of the code and you can see we are serving. You can see the name of the company in the middle and you can see that actually they are feeding the application from the instance, the public instance, we are hosting. They get the latitude and the logi to be a JavaScript from the user and they just filter it. Thank you. So these efforts got noticed by one great, awesome government agency, the Institutes of Statistics and they contractor us to start, they have a massive amount of information, a massive amount of data and very few tools to get to them. So we got in contact with them and the stuff that have been happening with that data is amazing. I'm gonna try not to get you all killed. I did sacrifice my last copy of Microsoft Office of the Gods. These are the maps I just showed you. This is using all open source software, the open source Libre Engine and the Cards BI and opens on a dashboard applications, application I created from Django 0.6 beta. You can see the behavior of the electric company. You can see the behavior of the Puerto Rico grid for the last 10 years and you can see the peaks and the valleys of how usage behaves in Puerto Rico and you can start predicting which month of the year the grid is most likely to collapse and the power company didn't knew this and when they were sending their brigades in June and July and when they saw the data we realized September or October are usually the most. So they were paying overtime in two months that nothing was happening and they didn't have enough brigades at the times at the months of the year that the electricity was collapsing and we also saw a very interesting curve. The electric company likes to make everybody uncomfortable and blame the problems of the electric grid and the people that you are wasting too much electricity. Please turn out what your likes. But this chart demonstrate that now 1.3 million kilowatts in 10 years ago Puerto Rico has actually consumed less electricity now than 10 years ago. So why is the grid continue to collapse? It's not because of use, it's because of a lack of maintenance. So now it can start shifting play and it can actually point fingers now. So this is just the open source version and now this is the commercial version that we recreated from scratch. It doesn't use base 64 anymore. Now it uses some more sane solution and the kind of projects we are doing with it are much more interesting like for example this one. Exodus in Puerto Rico is a very serious problem. People are leaving the island and now coming back at one rate at an alarming rate. This is all bureau transportation data combined with census data and this is the comparison chart of how many people are leaving the island, the destinations, the airports they're using to leave the island and the final aggregation. 5.2 million, 5.9 if you round it up, 5.2 million people left the island in 2013 and only 5.2 came back. So I have a difference of minus 1000 residents in an island of only 4 million people. You can see the problem now. And there's stuff like this, I can start predicting the peaks, the touristic peaks. So at what times of years the government need to prepare to receive and to make enough accommodations for tourists to see if it can fix this problem. And we can start doing things like this. We're gonna have to, there. There's a big problem in Puerto Rico and it is a political issue that says the argument is that there's more toxic emissions in places where there's a lower economic income in the area and this is a great project to start experimenting with that. It is a map that will, I'm getting some latency there. It is a map that correlates the amount of toxic emissions which companies are emitting them if they're emitting the correct toxics they are registered for and the income level of the area compared to the mean gross product, gross GPD of the island. And you can start doing experiments like this to see how this theory is correct in the island. You can see that some companies are starting to throw into the atmosphere these nasty chemicals just a few miles behind your backyard. Nobody knew this until we did this. So that pretty much is my wrap up. If you have questions, comments, please be kind.


Hello everybody welcome back to another Adobe Premiere Pro tutorial. In this one I'm going to show you how to find anything inside your timeline. What am I talking about? Basically for those of you that work on long projects or projects with lots of cuts and effects and different lighting etc etc sometimes you just can't remember where you put something. Let me show you how to fix that. The trick is if you're on a Mac hold down the command if you're on a PC hold down the control and then hit the F key. This is basically find in timeline. Now in this case I'm going to show you that I've got a bunch of different things going on. I've got some effects, some transitions, some stuff like that. So what I'm going to do here is I'm going to go to the search section. I'm going to go to all contains and then I'm just going to type in something like Lumetri and then we're going to see what happens. You'll see here that it has now indicated that this here has Lumetri the Lumetri color attached to it. So I'm going to left click on it and now I'm going to go to my effects workspace. So it'll show you a little bit better here. Left clicking on this you're going to see here that I have exactly Lumetri color attached to it. Now I have some text in this. You'll see here in V2 I've got some text. I'm going to hit down command or control F again and then there we go. Let's just load it up nice and slow here. Command F. There we go. And I am going to find, let's just look for the name Curtis. That's my name. I'm going to left click on find. You're going to see here that it has found the text that I put in here at this section and of course it says Curtis. That's my name. I've got some other things in here too. So I'm going to command F or control F again. I've got a noise effect on here someplace. Let's see where it is. Left click on find. Bang! Noise has been applied to this final one here into my final piece here and as you'll see here if you're on the left, that's where the noise is. So if you're looking for something inside your timeline and you can't remember what it is, this is all you need to do to find it. Thanks for watching this tutorial. A ton more stuff coming up. Stay tuned. Be back soon!


OK, so let's do another one of these problems. Calculate the number of protons, neutrons, and electrons in iron 55. So iron 55, you're going to have to remember if it's not written for you, like I wrote it up here for you, how to write it. So iron's atomic symbol doesn't look isn't I or IR or anything, it's FE. Ferris is what it comes from. But anyways, remember 55, the number 55 refers to the mass number. And so you put that as a superscript in the top left. And then the atomic number, 26, is iron is number 26. Atomic number is 26. And so you put it as a subscript right below that. But anyway, so let's calculate the number of protons, neutrons, and electrons in this element. So anyways, the number of protons is the same as the atomic number, so that's going to be 26. This is a neutral atom, no charge. So number of electrons is the same as the number of, and the number of neutrons, you remember, is the mass number minus the atomic number. So 55 minus 26, 29, an isotope of iron, not the only one. And remember, so the mass number here is 55. So it's saying there's exactly 55 protons and neutrons. It's not a weighted average, like you find on the periodic table.