Well, that's up to Joe Shaw, but I think we can just keep going it. Okay. That's great. You just led right into it with those questions. So it's a good time. Unless you feel like a break Joe. No, I think we should just go on. I'm fine. Yeah. Okay. I had to hurry at the end there quite a bit. Sorry about that. But well, I'm happy to keep going to finish things up at the end, even if we have questions. I need to go back to sharing. Okay, so now we're going to talk about light art for the atmosphere, which really came first light light ours for the atmosphere came first because like I said, one of the first things people did with the laser was pointed out and start measuring distance to airplanes and distance to clouds and that kind of thing. I spent the first 12 years of my career working at NOAA, which is the in the United States, the National Oceanic and Atmospheric Administration. That's this logo right here. And at that lab, I learned all about atmospheric light ours because we were developing light ours for both atmospheric and oceanic research. So we're going to go, we're going to see the differences between autonomous vehicle light are an atmospheric light are in this talk. In, I guess the short answer is autonomous vehicle light ours are designed to be much smaller, much lower cost. And to get a very rapidly updated signal compared to atmospheric light ours, which need to see much farther away. So they generally use much larger lasers. And they need, they do not need to operate so rapidly, and they generally do not need to be so low cost. So now we change our design principles accordingly. So let's talk about the basic principle here of. Of atmospheric light are the idea is that we send laser light into the atmosphere where it scatters. It scatters off of particles in the air and off of clouds. And some of that scattered light, of course the scattered light goes in all directions, but a tiny bit gets into the receiver where we detect it versus time and we use the speed of light to turn that into range. The range equations are all the same. And this. The uncertainty equations are pretty much all the same. Okay, so if we have a laser transmitter that puts out n sub T laser photons per laser pulse. And the pulse has some width that corresponds to a range bin delta R. We have a tech transmittance of the atmospheric path. Scattering in the hard target case that we looked at for the self driving cars. We just multiplied by a reflectance and divided by a solid angle. In this case, we're just going to multiply by a scattering coefficient, which describes the amount of scattering per distance and per solid angle. We have the same atmospheric transmittance again. And then we have this, this quantity, which is the receiver area divided by distance squared. This is actually just the solid angle of the telescope as seen from the scattering point. And then we have this overlap factor that we talked about briefly in the previous discussion. And then we have our transmittance of our optical system, which I was asked about just a few minutes ago. And that produces some count as a function of time, which we express as a function of range. So if we multiply all those pieces together, we find that the number of photons received from range R is equal to the laser pulse energy divided by the photon energy. So this is number, this turns the pulses. This thing in parentheses represents the number of photons that are transmitted. And then we have all the usual things. The only extra piece that I'm adding is that we always have a background signal. So here's the background signal, which is coming from scattering of, scattering from the same particles in the atmosphere, but the source is the sun usually. So this is scattered sunlight and all of this is scattered laser light. And that, that's the photon counting version of what we call the LiDAR equation. We can do the same thing with flux. This is optical power. Oh, I just realized I, I have a inconsistency here. I used power here and flux here. I'm sorry. Radiometrically, we often talk about flux, but I often also talk about power. So I apologize, I'll fix this, but these are the same quantities. These are just the optical power that's received. This is the transmitted power. This is the Delta R. That's the range bin atmospheric transmittance squared. Angular scattering coefficient. Receiver area divided by distance squared. That's the small angle approximation of the projected solid angle of the telescope. Overlap factor and optical transmittance. Let me get my, yeah, this is easier to see. This right hand term is the background light that's collected. This is the radiance of the background radiance multiplied by the throughput of our receiver, which is the area of the receiver and its field of view solid angle. Multiplied by the optical transmittance. Okay, so you remember this slide where we talked about the equations for a hard target. We had all these equations that we talked about before. And I just wanted to remind you that we had this equation that was expressed as one over R squared and we had an F number. This is the same basic equation. It's just that here we have a reflectance of the hard target. And here we have beta, which represents the distributed scattering. And so that's the scattering coefficient, which is in units of inverse length and inverse solid angle. So that's really the only difference in the equations is that now we are dealing with distributed scattering. In other words, volume scattering. Oh yeah, so now I can skip this. You also might remember that we talked about the range resolution being inversely proportional to the bandwidth, the electrical bandwidth, and that for a pulse laser, that's that bandwidth is expressed as delta T. Basically that that's determined by delta one over delta T. And that gave us a 15 centimeter range resolution. And I told you that for hard targets, we can improve that by pulse edge detection. That's no longer the case in the atmosphere. We do not have hard targets generally. We are generally looking at distributed scattering. You also probably remember that we looked at this. Sorry, I'm having a hard time with my slides here. We looked at this slide that had a time to digital converter. This is the biggest difference between an atmospheric LiDAR and an autonomous vehicle LiDAR. Instead of just recording the time that it takes to get a bright. Scattering return. We usually record the entire wave form. So. Here's a little diagram that shows you kind of how that is done. We send laser light out. And some of that comes back. Down from the atmosphere gets collected in a telescope. We have a filter to limit the optical bandwidth. It may not be here, but we have a filter somewhere in the system, usually. And then we have a detector, often a photo multiplier to more an avalanche photo diode. And that electrical signal is amplified and it goes to an analog to digital converter. This is the most important difference between what we talked about just previously and now. Because this analog to digital converter can be very expensive. We. With today's technology, we can get 16 bits of digitization. And we can add about a giga sample per second. And that gives you about 15 centimeter samples. And that's. That's pretty good in the atmosphere. We don't, we often don't need better than that. But if you need faster sampling. To get shorter. Range resolution bins. Then we have to start giving up something on the bit depth. We have 16 bits. This is 12 bits. But we get one giga sample versus six giga samples. The problem with. The problem with. Lidar is that the signals have very large dynamic range. And so we have many orders of magnitude. Between large signals and small signals. And so therefore we desire. 16 bit digitization. Whenever possible. This, this is actually very good. But these things cost a lot of money. These are, you know, 10 or even $20,000. Again, talking from the US dollar perspective. But that allows us to record the entire wave form with high. And then we have to figure out how to do that. 10 years ago, this was a much bigger problem because to get one giga sample per second. You could only have maybe 10 bits here, something like that. But in the last 10 years, we've made huge improvements in. The analog to digital converters that are available commercially. Okay. So let's talk now about how we lay out the optics for a Lidar for a Lidar. This is a system on the left. This is a photograph of a system we built when I was at Noah. And it was built into a box so that the whole box could be scanned. You can see here's a computer on the bottom. Laser power supply on the side. This is the receiver and transmit optics. And this on the top right is a telescope. You might remember that I talked about by static and mono static optics. In the atmospheric Lidar world, sometimes we do mono static, sometimes we do by static. It doesn't really matter that much. It's a little bit easier. To achieve overlap with mono static optics. And so that's what I'm showing you here. So in this system, let's start at the laser. We have a mid-yield laser. This is basically just like mid-yag. It's a 1064 nanometer. Or 10, very nearly 1064 nanometer. It goes through a half wave plate. A diverging lens, a converging lens. And so the combination of these two lenses acts as a beam collimator. We steer it over here to a polarization beam splitter. The beam splitter is oriented so that the transmit light goes this way through a pocket cell. And reflects off of the secondary mirror, primary mirror, and out to the atmosphere. The back-scattered light gets collected by the telescope. It goes through the pocket cell. And the pocket cell is now. Transmitting the polarization and the polarization beam splitter is transmitting the polarization. We have a, we have a time variable polarization state here because of the pocket cell. And so basically we're, we're transmitting the beam. And then we change the polarization for the back-scattered beam. So then we come through this polarization beam splitter. And we have a very narrow band optical filter to reject scattered sunlight. We have a beam splitter here that puts part of the beam here and part of the beam here. What we have is there's a narrow field stop, a little tiny 100 micro-radian field of view. And this one is 640 micro-radian wider field of view. And it's the, these little pinholes act as the field stop in the optical system, which means they determine the field of view, which is of course the angular field of view out here. That is done with a narrow channel and a wide channel because in the narrow channel, the overlap range is several hundred meters away from the telescope. With the wide field of view, the overlap begins at just a few meters in front of the telescope. But it's so much wider that the signal gets buried in background light at longer ranges. So the wide field of view channel is only for the signal close to the telescope. The narrow field of view channel is to get the signal farther from the telescope. Oh yeah, and here's a photograph of it. I showed you a photograph on the opening slide of that same system. Here's a smaller LiDAR that is not, oh, and by the way, let me back up and tell you that this whole box then was scanning. This is a big scan motor. And in this case, we were doing polarizations. And so because we're doing polarization sensitive detection, we did not want to use a scan mirror, but we wanted to be able to cover much of the atmosphere. So we scanned the whole LiDAR. The whole LiDAR was scanning. This system also is dual polarization, but it is not scanning. And so it just has a transmit laser on one side and a telescope on the other side. This is just a commercial astronomical telescope, just a small little 20 centimeter kind of telescope. And it has a photomultiplier tube receiver on the back end here. But before that, there's a box of custom optics, and that custom optics box is shown here. And it basically has a filter to reject any light that is not laser light. And then there's a liquid crystal variable retarder and a fixed polarizer. This is kind of a clever technique that I developed about two years ago for doing polarization switching. And what it does is the liquid crystal allows us to electronically switch our polarization state, very similar to what we were doing with the Pockel cell in the previous system, but I think the liquid crystal is easier to use than the Pockel cell. This is the port through the roof that we point it. So this is at my university. The first thing I told them is that I had to cut a hole in the roof. And luckily they let me do that. So this LiDAR sits in a room that is temperature controlled. And then we point the laser beam out into the sky for measuring clouds and aerosols. Aerosols are just particles in the air. The question that I had earlier about the question that I had earlier about measuring PM 2.5 particles, those are aerosols. So when I talked about aerosol detection, we're talking about those kinds of particles. Here's a schematic diagram of the LiDAR that I just showed you. And so let's see where's the laser. Let's start at the laser. Here's the laser. It fires 30 pulses per second. So this is not ISA. I told you that the autonomous vehicle LiDARs all had to be ISA. This one is not ISA. It sends 30 times per second, about 100 millijoules, which would burn your eye seriously if you got that light into your eye. Which means that we have to coordinate with the government. In the United States, the organization is called the Federal Aviation Administration. This is the organization that controls the airplanes. And they announced to the airplane pilots that we are firing this laser so that they can steer away from our university. Okay, so the laser fires through some diverging lenses, goes out into the atmosphere. Some of the light comes back, gets collected in that telescope that you saw in the photograph. It goes through a field stop aperture that is variable. It gets collimated, gets passed through band pass and neutral density filters, and the liquid crystal and the fixed polarizer, and then the photomultiplier tube. Notice that there's a collimating lens here. Many of you probably already know this, but it's very important that in an earlier graph, I showed you a interference filter at the focal point of a telescope. We don't usually do that. And the reason we do not like to do that is because the filter transmittance is changes with angle. So the wavelength of transmission changes with angle for an interference filter. And because of that, you don't want to have steep rays coming in. You want to have collimated light coming in if possible. So that's something to remember if you're designing a LiDAR is to try to put the filters in a collimated space. Okay, so that's the layout. This is what it looks like when it's operating. It's shooting light at 532 nanometers. So this nice green beam, he has laser eye safety glasses on. And you can see the computer is showing you the signal falling off of distance. And then there's a peak and that peak is a cloud that we are studying. This is what it looks like outside. And in this case, this is a photograph of my LiDAR beam going up to study this cloud. And this cloud is creating this colored ring. This is called a Corona. And the Corona is a set of diffraction rings around the light source. In this case, the light source is the moon. And I had been using this LiDAR earlier in the day. And I noticed that this cloud was these clouds were very, very high, high altitude clouds. Historically, many textbooks have taught that a Corona only is formed by diffraction by liquid water drops. And I take many pictures of things like this. And I, I did some meteorological analysis in the 1990s and realized that more than half of my photographs of very beautiful cronies were actually in conditions where the clouds probably were ice. And that was confusing because ice crystals are much larger than liquid water droplets. So it should not be possible to get visible diffraction rings from ice crystals. So we were, we had a mystery. And we went to a person who is an expert on mountain wave cloud micro physics. And he explained that they have measured the particles in these wave clouds. And very often these kind of wave clouds have tiny little ice crystals that are not normal crystals.  And they're about the same size as liquid water droplets. They're about 10 microns in diameter. So that was the, that was the solution to the mystery. And this photograph actually shows the first ever measurement that proved that that was true. Because this dual polarization LiDAR proved that this cloud was ice. And the photograph proves that we are getting a diffraction pattern. And so let me show you what those signals look like. Here we have a linear display of altitude on the vertical and signal on the horizontal. And I have co polarized signal on the left and cross polarized signal on the right. What that means is over here on the left, we are detecting the same polarization state that we transmit. So let's say we transmit something that we will call horizontal polarization. That means over here we are also receiving horizontal polarization. And here we are detecting vertical polarization or orthogonal polarization. The co polarized signal is scattered by the molecules in the atmosphere. So this is all molecular scattering. As we go up, then there's a thin cloud layer followed by another cloud layer. And so notice that the signal is getting smaller as we go higher. Over here the signal is zero until you hit the cloud. And that's because the cross polarized signal is only generated by ice crystals, something that is not spherical. And so these ice crystals create the cross polarized signal. And the molecular scattering is not generating cross polarized signal. So we have zero all the way up to the cloud. And then we have only the cross polarized signal. This is how we prove that that cloud contains ice is because liquid water will not create this signal. Only ice will. And so in LIDAR, in atmospheric LIDAR, we often use what we call the cross polarization ratio. A lot of meteorologists in LIDAR people actually call it the cross polarization ratio. I don't think that's a good name because it's not really depolarizing. It's changing the polarization state. So I like to call it the cross polarization ratio. But it's the ratio of the cross polarized signal to the co-polarized signal. And you can see it gets very noisy because we're dividing by zero nearly, especially up high. But you can see that it's near zero until we are hitting the cloud. And then in the cloud layer, we have about 0.4, 40%. That's a very large cross polarization ratio. And that tells you that that is absolutely without any doubt ice. So these are ice clouds as they really must be because at this altitude, the temperature was about minus 50 degrees C. And at minus 50, we have to have ice. Down to about minus 35 degrees C, you can have liquid. That's called supercooled liquid. And that's why this kind of measurement is so important. OK, so now I'm going to show you the same kind of plots, but in a different form. This is now altitude on the vertical again, but instead of signal amplitude on the horizontal, this is time. So this is what we call a time height plot. And the color shows you the signal intensity. And so what this is, is a case where we have a cloud near eight kilometers and another little layer near, what is that maybe six between six and seven kilometers. This is the co polarized signal. And this is the depolarization or cross polarization ratio showing you that we have, you know, 40 percent here and maybe 20 percent here. Both are high enough that we know that these are ice cloud layers and they're thin clouds, which is why we can see two layers with a thick cloud. You only see the bottom layer. Here's a case where we have two layers. There's a thin layer up here and a thin, a thicker layer down here. And the cross polarization ratio shows you only the top one. The bottom one is gone, which means that we now know that this bottom layer was something that was either liquid clouds or smoke. And this was ice. It turns out there is one other thing that it can be. And in addition to ice, the other quantity that can scatter and create significant cross polarization is desert sand. So some of you live in the part of the world where we get big storms of desert sand from the Saharan desert. And it comes across the Atlantic Ocean. Well, it can come up into Europe. It can come across the Mediterranean. And it can come even all the way across the Atlantic and be measured here in the United States. Some of that high altitude desert sand has little crystals of sand that are not spherical. And so it also generates a cross polarized signal. And I've seen that. I've seen Asian dust. I've seen desert sand from Asia come over where I live. Okay, so let's move ahead. This is a, this is a LiDAR that was, this is one of the first LiDARs that was ever launched into space. This is called Calliope, which stands for a cloud aerosol LiDAR with orthogonal polarization. So it's very similar to the LiDAR that I just showed you, except for it's in space looking down. And so it has a new jag laser. It operates at 532 and 1064. 110 millijoules each pulse. Remember, I told you 100 millijoules was very dangerous. But that's, if you're close to it, this LiDAR is so far away that by the time the beam reaches earth, it has diverged enough that the energy density is eye safe. So you can stand outside if you're in the right place at the right time and look up and see a flash of green light when this LiDAR goes overhead. The laser fires 20 times per second, 20 nanosecond pulse width, one meter telescope, 130 micro-radian. Remember, I talked about how field of view on a telescope for a LiDAR is often in the micro-radian dimension because we're trying to minimize background light. Photomultiplier tube and avalanche photodiode for detectors. On the 532 channel, we have a 37 picometer etalon filter, very, very narrow band to reject the scattered sunlight. You don't need to work so hard to reject the scattered sunlight in the infrared, and so that's no problem.  This LiDAR was launched in 2006. It was built in the 1990s. Well, it was built in the early 2000s, but it was designed in the 1990s. And so this is 20 to 30-year-old technology. The sample rate was only 10 megahertz, 10 million samples per second, which means that they were faced with the same trade-off. They need a lot of dynamic range. They claim to have 4 million dynamic range, which means they have a lot of bits. And to get that high-bit depth, they had to accept a smaller sample rate. But that's OK because if you're sampling the entire atmosphere with 50-meter samples, that's still a lot of data. And so this is perfectly acceptable. The layout is that the lasers... I need to move the pictures here. The laser fires downward. The scattered light comes back. Remember, it's over a very long distance because this is in orbit at, I forget the number, but something like 500 kilometers. And all the scattering is happening mostly in the bottom 10 kilometers. So the 1 over R squared losses are very large, but the signal comes back, gets collected by the telescope, gets split by a dichroic beam splitter to a green channel and an infrared channel. The infrared channel is simple. It just goes through a filter to the detectors. The green channel goes through a depolarizer for calibration some of the time. Then it goes through an etalon and an interference filter for rejecting scattered sunlight. Polarization beam splitter splits it into two components, the parallel and orthogonal. This is the copolarized and cross-polarized term. They're doing the same dual polarization method that I described to you before. And then after the detector, there's an amplifier, probably a transimpedance amplifier with an op amp. And 14 bit digitizers, they would like 16 bit, but you just could not, you could not buy them back then. And so we have 14 bit digitizers operating at, what was the speed? 10 mega samples per second. And here's what the signal looks like. So this is altitude and signal level on the horizontal. The signal level is logarithmic. Because again, I'm showing you how many, how large the dynamic range is. We have very weak signal from the upper atmosphere. And down in the lower atmosphere in the troposphere where we live, this is where all the aerosols and clouds are. The dashed line shows the molecular backscatter signal with an offset. And that's calculated. That's just calculated from the pressure and temperature of the air. And so up here, we can use that Rayleigh scattered molecular signal to calibrate the LiDAR signal, because we know that it's pure Rayleigh scattering. But down here, of course, the scattering is generated by things like aerosols and clouds that are much different than molecules. Now to remind you, a jet airplane flies somewhere in this range, 10 to 12, let's call it kilometers. That's the top of the troposphere. And so all of our weather occurs down here. And then this is the stratosphere. And up here is just the outer reaches of the atmosphere. So the signal goes very long distance. And because of that, the signal is very weak. And you can see what they do to overcome that sometimes as they'll average. This is a 20 minute average for the signal. Now here we see some plots as the LiDAR was flying across Africa and sort of Mediterranean region. And what you see is altitude versus distance. And this is the 532 nanometer signal showing serious clouds up to 15 kilometers smoke down here in the bottom three kilometers and desert dust. So how do you think the LiDAR people were able to determine that this is dust, this is serious and this is smoke? How do you tell the difference? Well, the difference is because you look at the cross polarized signal that's shown in the second panel, the perpendicular backscatter. You see that you're getting lots of cross polarized light from this stuff, but not from this over here. Therefore, this is something, it could be ice or it could be desert sand, but given that we are over the Saharan desert, it's not likely that this is ice. So this is desert sand. And over here, this is smoke because it is not desert sand that we would see it in the perpendicular scattering. Here's the 1064 beam. It also shows the same kind of thing. You can see there's less scattering in the 1064 channel than the 532. And so we can use the ratio of those two scattering measurements to tell us something about the size of the particles. And that's what I was explaining to the gentleman who asked me about measuring PM 2.5 particles. It's not a perfect measurement, but it gives you an idea of the size of the particles. Okay, so this is a complicated argument, but I'll try to be clear and I'll, but I also need to be quick. When we do this kind of LiDAR measurement, we have lots of unknowns and we have too many unknowns. The first thing is that the backscatter signal arises from both molecules and aerosols. So the backscatter coefficient has a term from molecular scattering and aerosol scattering, but the extinction, which means the absorption in the scattering losses comes about from a molecular term and an aerosol term. So this is absorption by molecules. This is scattering by molecules. This is absorption by aerosols and scattering by aerosols. So so far we have one, two, three, four, five, six unknowns. We have way too many unknowns to make sense out of the measurement. So what we do is we use Rayleigh scattering theory to give us the molecular coefficient up here and the scattering molecular coefficient here. So that's just Rayleigh scattering theory. If we know the pressure and temperature of the air, we can calculate that. If we operate our LiDAR on a wavelength where the molecules are not absorbing, then this term goes to zero. So now we have three unknowns. We went from six to three. So what we usually do is we take the aerosol absorption and the scattering, I'm sorry, the aerosol absorption and the aerosol scattering losses into a single extinction term that we just called the extinction coefficient. And then that leaves the final unknown as the backscatter coefficient for aerosols. That's what we're trying to measure with the LiDAR. So now we have two unknowns. We have the extinction coefficient and we have the scattering coefficient. But we only have one measure. So we still have too many unknowns. And so what we do is we combine these two into one parameter called the extinction to backscatter ratio, which is also called the LiDAR ratio. So it's the extinction coefficient over the backscatter coefficient. And we either assume it or lots of people published papers where they say for these kinds of conditions, it's generally in this range of numbers. But this is a problem. So when we, when we are trying to determine particle sizes or particle scattering coefficients, we have to either assume something or have to, we have to get another independent measurement. One of the more clever solutions to this problem is called high spectral resolution LiDAR. And in this case, we solve the problem by separately measuring the molecular and the aerosol scattering. And so if you look at the spectrum in the frequency space of a backscattered LiDAR signal, you see that it's got a broad component and a narrow component. This is aerosol scattering. And this is molecular scattering. And why is this the case? It's because the molecules are being, the molecules are moving and they are randomly moving back and forth much more rapidly than the larger aerosols. So the larger aerosols have less motion. So they have a narrower Doppler shifted frequency spectrum compared to the molecules. So if we can tune our laser to measure over here, we can measure the molecular scattering. And if we tune it here, we can measure the aerosol scattering. And that's the idea behind high spectral resolution LiDAR. And one way that it's implemented is by measuring the center channel and then using something like an iodine vapor filter to block out the center channel and measure only the wings, where you get the molecular scattering. And that's shown here. This is a paper from 1999. So it's not new. It's a very simple high spectral resolution LiDAR. And so the laser light goes out, the backscattering comes in the telescope, goes through a field of view, fixing iris. And then we beam split to two different channels. Part of the light goes through an absorption cell to knock out the center. And part of it goes through just straight to the detector to get the total signal. And by combining the two carefully, we can separately determine the molecular and aerosol scattering. Modern systems are a little bit more complex than that. And I'll show you an example in just a few slides. Okay, so we can also measure gases in the atmosphere. So far, we've really just talked about measuring particles, cloud particles and aerosols. And this is a technique called differential absorption LiDAR, or dial. And in this case, we also rely on a tunable laser. If we have a tunable laser that can be on an absorption line and off the absorption line. And if these are very close to each other, then what we can do is assume that all of the Rayleigh scattering is the same. And the only significant difference between these two signals is the absorption by this gas. And so if we write the LiDAR equation for the on channel and the off channel, many parameters cancel out. And what we're left with in this ratio. Oh, I guess I didn't write the final equation, but we're left with pieces of the equation that just relate to the scattering coefficients and the extinction coefficients. And so we are able to. Oh, I see what I'm going to just skip this one because it's too complicated for the time that we have the ratio of the on to off signal gives us essentially this tau ratio, which is the tau is just using a beer's law kind of factor. And it's just e to the minus path integral of the number density and the scattering cross section or the, sorry, the absorption cross section of the absorbing gas. This is the extinction, which we can separately calibrate out. And so what we get is we get an equation from the ratio of the two signals, we get an equation that is essentially e to the minus two times the absorption coefficient of the target gas. Well, that tells us, if we know the cross section, which we learn from spectroscopy, then the only unknown in this equation is the number density, which means we can both detect the presence of some gas and we can measure its concentration. We can measure the range dependent concentration of some target gas. One of the gases in the atmosphere that is most important for radiative balance is water vapor. And this is the layout for a dial light are that was developed at my university recently for measuring water vapor. And it uses diode lasers, which is very, very exciting because now we're going to do atmospheric light are with very small low cost lasers, limited range of course, but we can, we can do most of the troposphere, most of the boundary layer, you know, maybe five or six kilometers and that's where most of the water vapor is. So the way it works is we have diode lasers on the absorption line and off the absorption line. In the early prototypes, we tuned the laser back and forth between two wavelengths. And then we decided, let's just operate this laser at that wavelength and this laser at that wavelength. And they're controlled by a diode laser tuning controller. They get transmitted one at a time through it through an optical amplifier. And out the telescope, the back scattered light comes down here through a beam splitter. And we do the same kind of trick where we have a detector for the near field channel and a detector for the far field channel. And these are photon counting detectors. And by detecting at these two wavelengths that the lot diode lasers are operating on, we can generate a ratio. And that ratio tells us the water vapor profile. So here's examples of data over three days, three days and nights. This is height on the vertical and time on the horizontal. And you see on the top panel, this is the backscatter signal. So this is a conventional backscatter LiDAR signal showing you clouds and aerosols down below. And on the bottom panel, though, this is the actual water vapor density. This is grams per meter cubed of water vapor in the atmosphere derived from the on and off signals up here. And so you see that there's a lot of structure that we don't see in the scattering signal. We don't see any information about the water vapor. But in the water vapor signal, of course, we see a lot of data. So here's a low level bunch of water vapor that changes over time. Over here, the air is much drier. So this is dry. This is moist. And this kind of information is really important for both short term weather forecasting and for climate under climate modeling.  The two that we just talked about, it's a high spectral resolution and dial LiDAR system. So the blue part is a water vapor dial, the one that I just basically just the same one that I showed you. And the green part is a high spectral resolution LiDAR that is actually measuring temperature in the atmosphere. And so this is a really exciting development that lets us do thermodynamic profiling with a single LiDAR that has two, really four channels, right? There's two, there's four wavelengths. These wavelengths doing high spectral resolution LiDAR near the oxygen band. And these two wavelengths being out in about 830 nanometers for water vapor absorption. And this shows you that we have very similar data when we integrate this system next to a Raman LiDAR, which is the classic accepted way of measuring water vapor. And what do I have here? I forgot. Oh, this is the aerosol backscatter. Because we're doing high spectral resolution LiDAR, we can obtain the backscatter coefficient without having to assume, remember the problem with the too many unknowns. This removes that extra unknown. And this automatically calibrated backscatter coefficient. So now we can measure the PM 2.5 and all the other particles, much more accurately. Okay, we're just about out of time that I'm going to wrap up with just a couple of things. Another very popular way of measuring gases in the atmosphere is with Raman. And all the LiDAR I've talked about so far has been elastic scattering. And this uses in elastic scattering, which means that the frequency of the transmitted light is different from the frequency of the scattered light. And so for a given gas, there is a fixed Raman shift. So you can design your receiver to measure that Raman shifted light. But of course the Raman scattering is very weak. So these have to be very high powered lasers and very high frequency. So just to give you an idea of how this is done, I show you here that from the telescope, we split the signal into a 355 nanometer and 408 nanometer channel. 355 for aerosols, 408 for water vapor. 387 for nitrogen. The 387 and the 408 are both these are both Raman channels that are used. This one is used to calibrate, and this one is determining the water vapor. The 408 is the inelastic channel. 355 is the, that's the transmit wavelength. And we, we double this because there's long range and short range channels again. And this is just showing you an example that, that you can, you can then derive the water vapor profile versus time from this method. Notice that it gets noisy during the daytime because the scattered sunlight competes with the Raman scattered signal. Okay. So once again, we come to this idea of coherent light R, we already saw this plot where we talked about that we can generate a local oscillator and mix it with the back scattered light and get a difference or some frequency on the detector.  We had a question earlier about wind LiDAR. So I will take the time to show you this even though we're pretty much out of time, but I think we're probably okay to take another minute or two. This is a wind LiDAR that I helped to build at, at NOAA many years ago, but it illustrates the point. In this case, we were operating out near 10 microns, but this can be done at many other wavelengths. We have two lasers. They go through acoustic optic modulators. The purpose of the acoustic optic modulator is to put a frequency shift relative to the local oscillator.  Then we raise the frequency of the transmitted light by 80 megahertz with these AOMs. We go through an electro optic modulator just for polarization control. And in this case, these are, these are lasers that are operating with RF discharge optical amplifiers. So just think about this as a gain stage. And the more times I pass through the gain stage, the more gain I get. So I go through the gain stage, go through another bunch of gain stages, and the, oh, and when we come back off of this one, we go through a quarter wave plate. And so going through a quarter wave plate twice makes it a half wave. And the half wave shift rotates the plane of polarization, which means that we are now rotated so that we can use polarization splitting to separate between the transmitted light and the received light. And so basically what happens is we send out, usually we implement this with circular polarization. That's what this quarter wave plate is for here. So you send out one polarization and you get back the other polarization.  So it gets passed by this beam splitter and comes onto the detector, mixed with the original local oscillator. That local oscillator is shifted by 80 megahertz by these AOMs so that the mixture, the difference frequency no longer sits at zero frequency and instead it sits at 80 megahertz and it can be processed with RF electronics. And then these are plots of measurements of winds in these canyons. So here's mountains on one side in a valley and we were sitting in a valley scanning the winds around the valley. So you can see these, again, using Doppler shift to determine the direction of the wind. These are winds blowing toward the lidar from the south. These are winds blowing toward the lidar from the north. And you can see the different patterns shift over time and with angle. This idea has been used to create much smaller, lower cost systems. This is a commercial Doppler lidar that was built. The guy who helped me build that previous one actually started this company and now he runs this company Halo Photonics and they put these out at airports, for example, and they just are doing constant monitoring of winds, looking for dangerous winds that could cause an airplane to crash. And this is 1550 nanometers and so it's eye safe. So it's an eye safe wavelength and we just don't have to worry about it. It just runs all the time. That's all I have to say for now. And so I see some hands up. Let's go to answering your questions. Okay. Thank you so much, Professor Joshua. So far we have two questions from two participants. The first one is from Susanne. Susanne, I think you are already on mute it so you can ask first. Thank you very much. Thank you for the very nice presentation. Thank you. We have seen a few times the transmittance of the atmosphere in the equations. And I was wondering how do you calculate it? Because I suppose it is very difficult and it is complex to calculate and maybe it includes absorption and scattering of the molecules. Right. One way, I'm going to go back to a slide that I showed you near the beginning. One way to do it is by looking at the satellite light signal. And you can see that the background transmittance is the only thing that's affecting this signal up here. Down here. We need to know this underlying transmittance, but it's too complicated to sort it out. So if you have a signal that if you have a LiDAR that is powerful enough to see far away where you have just clean air, I can back out the atmospheric transmittance just from this signal right here. And so that's one way, is to use the signal in a region where there are no clouds or aerosols. But if it's only a short-range LiDAR, then that just becomes a problem. We can't really do it. So if you want to, and really that's the problem that I was talking about when I talked about this, let me find it, that's what this problem is all about. The atmospheric transmittance, the atmospheric transmittance is this extinction term, right? This is the absorption and this is the scattering. So that's exactly the problem I was talking about, is that in the end, with a single wavelength scattering measurement, we have two unknowns. We have the extinction, which is essentially the transmittance that you're asking me about. And we have the scattering coefficient that we want to measure. In that case, you have to get some other information. One way of doing it is to use a solar light at the sun and determine the extinction along the path. That will not give you a range-dependent number, but it will give you a path-average extinction, and that can be used to bound the retrieval. But the other solution, of course, is this high-spectral resolution LiDAR, where you essentially remove the transmittance by separately measuring aerosols and molecules. So yeah, really good question. Does that make sense? Thank you very much. Okay. The second participant, Hugo, he's from Japan. He wants to ask some questions. So Hugo, you can unmute and ask, please. Thank you once again for this very informative talk. Thank you. I think for atmospheric LiDAR, it's one of the main research teams I'm trying to investigate. And as you previously mentioned, that the extinction event, we have too many unknowns, but the extinction event, for example, on a Raman scattering LiDAR, it can be determined directly by the back-scattering signal from the molecules, correct? But that requires a very high-power laser. Is there any reason that there is no trip pulse amplification done for Raman LiDAR? Oh, that's a good, that's an interesting question. I don't know the answer to that, but that's a very interesting idea. Maybe nobody's done it because I don't know. With that kind of power density, it might be really difficult to do. I can't think of how to do it without burning up my components. That's the trade-off, right? The chirp is done with sort of low-powered elements, but yet we need high power for the Raman signal. So, yeah, that's the trade-off. I'm curious, Hugo, where are you in Japan? Right now, I am in Sapporo in Hokkaido. Oh, wonderful. Are you at the university there? Yes, I'm actually under the research team of Dr. Tomohito Yamada, and he is very concerned about understanding the hydrological cycle and global climate modeling, and for that it's better to have smaller errors on things that are known and trying to determine things that are unknown yet very complex. Yeah, I spent part of my sabbatical at Hokkaido University about six years ago, and I didn't meet him, but I wish I would have now, because that would have been fun. So, yeah, you should maybe email me, and I would like to communicate with you guys some more. Japan is a favorite place of mine, so I'd love to come up and visit you guys sometime. Thank you very much, Dr. Shah. Yoroshiku onegaishimasu. Okay, any other questions? Okay, I think this is the end. No more questions from participants. So any final remarks from Joseph Nivela, please. Yeah, sure. Well, thanks very much, Joe. Really very, very well presented for a lot of people who even aren't experts.  Yeah, that's all right. I didn't want to send them to me on email. I had to move on fast, so I apologize. Yeah. I was just interested about whether you actually put these things on airplanes or not. Because I can imagine the short term. People for light ours on airplanes. I have tomorrow in my talk tomorrow, we will see some airborne light our work. Okay. All right. Yeah. Well, anyway, so. I think tomorrow, anyway, thanks very much again. And tomorrow you're going to give your last lecture on insect and fish lighter. I think Montana has no shortage of insects. Or fish. Very beautiful fish. And then also, John how will be speaking right after you. Photon counting compressive lighter and John. I will try a little harder tomorrow to stay on time. So I don't show up John's time. Yeah. We're kind of a little bit loose here.  But for those that don't, don't remember John how is the ICL president. So anyway. Good friend of mine and wonderful guy. I'm looking forward to hearing from him. Right. And a collaborator, I guess, right? So you guys published together. Yeah. So it's really great. Okay. Good. So anyway, thanks very much again. And I look forward to seeing everybody back again here at. Five PM.


Hi everyone, Joe for JaspeysCaseRakes.com. Happy Sunday. Coming at you with a pack of Panini Prism football. Hobby pack break number 11. It's the last filler we got to do to unlock that hip parade football dual case break that's coming up in the next video. Big thanks to this group for making it happen. Appreciate you. Basically, Brian, Chris, Chad, Greg. Congrats to you guys. Thanks to you guys for filling this up. All the teams are in and let's do the pack break. Let's roll it, randomize it. Six and a one. Seven times for names and teams. One, two, three, four, five, six and a one. Seventh and final time. Six and a one. Seven times for the teams. One, two, three, four, five, six and a one. Seventh and final time. All right. There's the first half of the list right there. Here's the second half right over here. And let's print and rip. We've got a silver tray McBride. It defores Buckner to 249 for the blue horseshoes and a Chris Alave rookie car. Chris Alave will go to Greg. The defores Buckner will go to Chris. Now let's see who's going to win those hip parade spots. So let's gather everybody's names again. One through 32. New dice, new list and let's roll that dice and randomize that list four and a four eighth the hard way. It's going to be the top nine after eight. Good luck. One, two, three, four, five, six, seven and eighth and final time. Now from 11 through 32. We know it's the top nine, right? From 10 through 32. It's going to be sad times, but we know Chris has got a lot of spots. Chris is probably going to be up top somewhere in there, but who else is joining him? Or did he sweep all the spots? There's Chris. Eight, seven, six, five, four, three, two. It's a clean sweep. Top nine after eight. There you go, Chris. We'll see you in that next video. Congrats. I'm Joe. I'll see you for the next one. JaspysCaseRace.com.


What is your favorite Johnny Depp movie? Whoa, I know you haven't seen it as much as I have seen, but. Um, my favorite or the one I think that is the best? No, your favorite. Okay, so little honorable mention. The most artistically excellent one I've ever seen is Platoon. You haven't seen enough, then. But my favorite Johnny Depp movie, man, if I had to choose between the two, I'm probably just gonna stick with the original Pirates of the Caribbean. Edward Scissorhands, I love so much, but that one makes me sad at the end. It's too heartbreaking the way he's treated. Here's the Finding Neverland. Yes. That's a great one. It's a really good movie, and that would be in my top five for sure, but the original Pirates of the Caribbean. I think he was nominated for an Oscar for that one. For him, whereas I like two even more because of Davey Jones coming into the picture, but the introduction of Captain Jack Sparrow is one of the most important and wonderful moments in cinematic history. Hey, welcome back to our Stupid Wrecks, The Corp. What about you? Because you've seen way more Johnny Depp films than I have. I've seen almost every single one of them. Yeah. There's two obscure ones that I haven't seen, Brave and... I think I know what would be one of your favorites. Vinnie and June's my favorite. Yeah, that doesn't surprise me, which is a great film. I love, obviously, Pirates. If you haven't seen Vinnie and June, it's a great, great film. I love Donnie Brasco. I love Blow. I love Sweeney Todd. Yeah, there's a lot. What about the Black... Black Mask? That was great, too. I enjoyed it. I own it and I've probably seen it maybe two times, probably. Would you like Charlie and the Chocolate Factory? No. Yeah, you didn't like that? No. That's probably one of my least favorite. I'm actually much more of a fan of Johnny than I am of Tim. I'm a fan of Tim Burton. But I've always been more of a fan of Johnny's acting than Tim's directing. Gotcha. I like them both. Right. But if I had to pick one... So your larger problem with that would be the direction of the film per se, not necessarily Johnny's. But also Johnny's always had a problem with picking films just in general, because I think he just looks at a character. He looks at the character. He looks at the character and he's like, I like this character. Right. I'm not really looking at the director. The experience involved the writing. It shows. Because that's why he has some really, really bad films. Yep. And then he wants to play characters that interest him. That's it. That's the criteria for him, it seems. He's coming back. He's doing a French... I saw the trailer. Have you seen the trailer? Yeah. He plays King Henry the Eighth or something. Is there a trailer? Brand new. Just dropped. Yeah, I haven't seen it. Brand new. Yeah, Lexus just sent it. Well, I've been following it. And so I've seen pictures and stuff from set, but I haven't seen it yet. Have you seen the Indiana Jones trailer? I want to see that trailer. I haven't seen it yet. It just dropped today. Anyway, that's all what this is about at all. Sorry, let us know. Your favorite Johnny Depp film is down below. Yeah, this is WTF Moments in Cricket. Great. Yeah, so... We were talking Cricket last night. My wife loves Cricket. Who's your team? And Cole Cullinat, right? The night, yeah. She is... Because you're with Cole. Well, we were actually... We were watching, we were with our friend Joanna and the Dodger game was on. Joanna's a huge Dodger fan, so we were watching the game and we had a baseball that their son Clint plays with and I was talking to her and she had never seen a baseball before and she said, oh, it looks so close to a cricket ball. And then she just started saying, the minute they have a cricket team that's going here and I said, yeah, that's SRK. He's already got the rights for it. It's just a matter of time for the to be the Los Angeles Nightwriters. So I'm probably close to becoming a watcher of it soon. I feel like I've learned enough and I can jump back into it. Well, last time I jumped into it, I didn't know enough and I wasn't ready for the fans. Just don't post anything about it. I'm ready now. I'm ready now. Here we go. It's unbelievable. Yeah. It's on fire. Oh, no, he got bit by my mother. What? Bees. Was a bomb. Gotta be bees. Excellent delivery. Oh, no, he's missing. He missed it. Dairy, dairy, may, one of us. Dairy, dairy, may. I promise everybody going down to the ground is because there was a swarm of bees. Bees can't go to the ground. They are less likely to go down to the ground. I'm going down to the ground. Excellent delivery. Ah! Dairy, dairy, may. He was dead to rights, man. He was long gone. He's telling them, run back, run, run, run, run. That's hilarious. Wow. The game. And the love of hitting. Died to the man, Chris Lee, the danger man. What? I don't know. I don't know why that was. That's not mysterious smoke. It's cold out. And his, that's not that. He's on fire. That's called steam. When you're sweating, your body's hot and it's cold out. He went over the line. What? Look. Ha, ha, ha, ha. I was confused. Just to be sure. Let's just be darn sure. Let's make sure that thing is out. Final match, your performance is happening. Final match, your performance, what happening? Final match, your performance, what happening? Yeah, he doesn't understand that question. Final match, your performance, what happening? Final match, your performance, satisfied. Are you satisfied with your final performance? Right. Bless his heart. It's not his fault he didn't know the language. What? Hold on. What's going on? I don't know. I saw that he threw and then lost the ball in the air. Gotcha. Mm, uh, uh. Is he okay? That looked awful. Woo, that looked, oh. He's lucky he didn't get hurt. Seriously. Geez. Yeah, that's remarkable he wasn't injured. What happens there? Is that a ball or? Yeah. Oh. What? What? Ball's in play, bro. What's everybody doing? What? That was bizarre. What? I don't want that buggy. That was weird. Whoa. Oh. What? Was that in play? Did that count? Whoa. I would have liked to have seen that again. Oh, oh. That's hurt. Arm out of the socket? Yeah. Must be arm out of the socket. He just popped his arm out of the socket when he slid. I didn't see it, okay. Oh, it's our baby, yeah. What? Did he just hit it into the wickets? I think he did. I think he slipped and he hit it into the wicket. Oh no, he just missed it. Why is that a WTF moment then? Because of how he slipped? Yeah, or how he, yeah. Okay. I thought he hit it into the wickets. It's in his helmet? Oh yeah. It went up and through. It's a good thing he was wearing a helmet. No joke. I've seen that happen to umpires and catchers. Oh, it's our baby, yeah. What was that all about? Was he about to hit him? It looked like he was about to hit him. He was, he was just pissed off because he was in his area or something. Yep. Bees. Oh yeah, okay. Yeah, that's happened in other sports because why, why? Ouch, that would hurt if you got hit with the ball. Is that the same guy? Not all white people are the same.  Did you hear that? Yeah, it happens. It happens. It could happen. If you're not wearing a proper supporter or a cup, that thing just exploded up at his face from the ground. That's what she said. Wow. Boink. Woo! Why isn't he wearing a helmet? Yeah, why is he not wearing a helmet? What is it, no pads, no helmets? Uh-oh. Oh yeah, he juggled the ball and missed the opportunity to get him before he got back across the line. Not too much of a WTF. No. What? Why wouldn't it be a... That's not a legal delivery, I thought. Did he step over? No, it's not that he was too sure. Oh, far back? Is there a rule you have to be on the, whatever it's called, the strip? Interesting. I'd like to know. Interesting, let us know. Oh no. No, okay. What? Right there. Yeah, they ran into each other. Bummer. This just a mix-up. Boink. It happens. Yep. They ran into each other, yay. Mixing up the balls, yay. Did they penalize them five runs? Well, we can't see it because your, the end cards are covering it. So, yeah, I couldn't see what that was. The first one. Most of those qualified as WTFs, some of them were genuinely wild. You ever popped anything out? No, thankfully. It sounds off. I've sprained an ankle. I've gone down on my ankle and heard my ankle go pop, pop, and it turned purple and I could walk on it. You're not like a joint pop out. Yeah, I've never dislocated the shoulder. Sounds terrible. Were you in class when, good grief, what's his name? I don't know. He dislocated his shoulder and I popped it back in against the wall. I don't know what class we were in, but he was goofing off with somebody and popped his shoulder out and so I put him up against the wall and put it back in. Bryce, it was Bryce on somebody else, but I don't think it was Bryce's shoulder that was getting popped back in. Nick? I've come close to breaking and having fingers when I played baseball. I can do this. Get popped out. Yeah. No, that's weird. So it's like I'm, no, I'm very, very, even talking about baseball last night because Mookie Betts got hit in the back of the helmet. He was okay, but I've been- I don't want you hearing about Mookie Betts. I've been hit by pitches, but they've all been in the arm, the back, the hip. I've never been, I've never thankfully been hit in the face or the head by a ball. I have had a ball, I have had ground balls pop up and hit me in the cheek or in the neck. I had one hit me in the lip and it kind of cut my lip a little bit. I've played basketball. I've torn open my lip and had to go get stitches, but that's the extent of it, thankfully. I've torn open your mom's panties. You popped anything out? No. No, I have not. Yeah, thankfully. No, I've never- For all of the sports- Sounds awful. For all of the sports I did, I was really active in sports, but granted, I didn't play football, for example. I played soccer, never broke anything, never popped anything out. Yeah, I mean, for all the baseball I played, I played football, I played basketball, never. Nope. I'm just, I drank a lot of milk. That's it. He's a kid. That's the reason. I've seen bad injuries. I saw a guy, he just forgot where he was running down the ball in the outfield. I was playing left field, he's playing center and the ball was hit really far. And it was hit far enough, it was a line drive, but I could tell it was probably gonna leave the park. And unfortunately, the field we were playing on didn't have a warning track. He forgot where he was, man. He was just full out stretching to get the ball, running full speed and slammed into the fence. And it was a small fence, so his arm went over the fence and the fence impaled? No, no, he didn't get impaled, but he bruised, thankfully he didn't break anything, he bruised ribs. When he hit the fence, everybody went, oh, we all ran out to the mountain center field. Gross. Anyways, yeah, fun video. Let us know what are the cricket videos and any information here that we did not understand. Please let us know, obviously, as you always do, know what actually happened. Yeah! And what are the cricket videos we're gonna do down below? Juice!


So, let's start with the brief introduction. Maybe, okay. I decided to use a sort of a comical approach to heritage, so I was quoting Monty Python by rephrasing what the Romans have ever done for us, what heritage has ever done for us. So, basically, I hope we will all agree that heritage is offering us raw and flexible resources. Some people may say they are renewable, some others may say they are sustainable, but we still have a resource that can be used in an appropriate manner. And that creates what we're going to look at today, the heritage industry, and how we can manage it. And from the heritage industry, we will be able to create opportunities and perspectives. Opportunities are basically conservation in the long run and job opportunities for the people working in our sector, but also benefits for the population living around the sites or museums as well as local businesses. Now, this is just to give two examples where we should look at when we think about management. So, we have a famous site in England, an iconic site, Stone Age. It didn't used to be like this. It used to be visited by only a few thousand people in the 70s, but then Her English Heritage stepped in and the number of visitors skyrocketed to 1.6 million a couple of years ago. And now you've been charged between 15 to 20 pounds to enter the site. And if you want a private visit, you need to go there at 5 o'clock in the morning and pay 50 to 75 pounds. And you can only have access for like 45 minutes and then there is another good example of how visitors are really consuming a site but also endangering the site at the same time because if you imagine that at some point there were only 10,000 people visiting and now every year we've got 2.5 million visitors. Site erosion is the first problem to be addressed on that site. Then we have many organizations and that's the title of the session, controlling sites, museums, historical buildings and all of them could be controlled either by the state, by a union between states and private companies, charities and so on and so forth. They all have issues and they all have good aspects. One of the main issues of a state-controlled site is the network which is effective but it's not always used appropriately and then human resources are always stretched to the limit. Financial resources, I'm just touching points that anyone can make even a 5 years old child can assume the same things. For independent ones they have similar problems but one of the most important is that they tend to be reasonably newly developed except for a few cases like National Trust in England that was created in 1895. For instance we have a similar National Trust in Italy that was created only in 1975 almost 80 years later. There are also quite a few advantages which are basically unlimited financial resources in theory from the state because the state should not go bankrupt but we have theaters of that as well. We have unlimited human resources because if you think how many people work for the Ministry of Culture in every country you can definitely pull a lot of human resources from every person that is working in that ministry. You just need to make sure that they are connected and easy to reach out and the same works for the independent ones and one of the good points is that they have a really large pool of human resources available and they change quite often so new ideas keep coming in independent institutions because there is a large turnover of stuff. And then before we start with the first one I just wanted to propose this analogy with heritage as a car. Now heritage is the main resource so I lost the car now there it is but we can have a beautiful car Ferrari Lamborghini but if we don't have the petrol the fuel which is the visitor doesn't go anywhere. If we don't know where to go the motorway which is the museum and the site again we completely miss the point if we don't have conservation program the person that is going to take care of that car the mechanic, again there will be a problem and if we miss the management organization again we will not have a vision where we head into with heritage and what we want to do with heritage. So the question for today is to find out who could be the ideal infrastructure, organization charity whatever that can be combining all these different aspects together to make a management of heritage viable and feasible. So that was the introduction.


YouTube team keeping clean. Now that was old school AFC North football style. I saw a lot of people saying how born the game was and I was like, what game were y'all watching? I loved it. I loved it. That was a straight up defensive game, like 15 to 10. That wasn't nothing but defense and I appreciate it because these defensive games, I mean, you could kind of say the same thing for an offensive game where they's scoring like 35, 40 points but defensive games, every play counts that much more. Every mistake, it gets emphasized that much more because if you're struggling to move the ball, then everything just is emphasized so much but in this game, Baker Mayfield, this was his first game back I believe and he came back first drive. Oh, they were moving. They were moving that ball downfield. Baker Mayfield, he was hitting his receiving and he was showing like, hey, I'm straight y'all. I wanted to play the other day but they ain't like, I'm straight now, I'm here, let's get it. Let's go and they were moving and moving and moving. Then the Steelers were like, hold up, wait a minute. No, let's go ahead and put it into this and they stopped them, they held them and then the Steelers, they ended up getting a field goal and the teams, they just, they had a little stand steal for the longest. I think that the first half ended 3-3 but I did love how to commentate us because it was Tony Romo and I can't remember the other commentators name but usually it's always fun to say like this quarterback versus this quarterback. Like in this case, been Rothesburg versus Baker Mayfield but Tony Romo was like, oh, this is actually Miles Garrett versus TJ Y and both of them were showing out for their teams, both of them, they got their money and both of them continue to show you why their teams paid them the big bucks because they deserve it, they earned it. So it, let's just fast forward because again, it was just defense and defense and defense and defense and defense which I loved, loved it. And at the end of the first half, the Steelers. Ooh, I was scared for the Steelers. I mean, either way that this game went, I was really hoping for a tie but I was worried for the Steelers because I was thinking toward the end of the game I was wondering, oh, is this gonna be one of those Thanos moments where Gamora is asking Thanos, what did it cost you? What did it cost you? Everything. That's what it was looking like when they went for it on that fourth down they did the fake field goal and they turned Boswell into a quarterback and he was looking, looking, looking, looking and then he just, the tight end was just, the tight end was one versus three and I mean, he had no choices fourth down. You don't wanna take a sack. You gotta at least put it up and he did that. So he made the right decision and I wasn't even too mad at the Steelers for going for it right there. But at the same time, it's a tricky one but I wasn't too mad at them for going for it.  You lost your kicker for the rest of the game to a concussion to what should have actually been a penalty, should have been a blow to the head or a late hit, one of those two, but it should have been a penalty and that really changes the way that you run your team. That changes the way that you operate. Reason being because now and Steelers have been in this situation before, I forgot what kicker it was of theirs that got injured. Oh no, no, no, he might not have even been injured. He just may have been missing during the season. It was a couple of years ago and the Steelers, they will go for so much on fourth down. They will keep going for two point conversions all the time. It was a couple of years ago. I forgot who the kicker was at that time. But anyway, you lose your kicker, that changes the whole game plan because now you're forced to make some tough decisions on some fourth downs where you will be in field goal territory. It's like, oh, we can't, we don't want our punter kicking. So what do we do? But I was thinking, uh-oh, if this comes back to bite them then that could be big. But they ended up squeaking out of there with the win. Now I just, I really appreciated their aggression at the end of the game. To that 50-yard pass to Deontay Johnson, I really appreciated that aggression because, you know, enough teams like, and these days the game has changed a bit to where teams aren't just, a lot of them won't just run the ball out to end the game. Be like, oh, we'll just run the clock out and hope our defense will know. Teams are trying to win. They not trying to just run it out. They trying to win so they trying to get that first down so they can really control the game. And when they threw that pass to Deontay Johnson, it was perfect. I mean, the only thing that could have been even more perfect for it was if it resulted in a touchdown. But it was such a smart decision. It was a good decision. And again, plays like, you didn't see plays like that too often this game because it was a defensive game. Such a defensive game. Najee Harris grinding it out, grinding it out. All game long. Grinding and running yards. When he would break up the semi big one, it took a lot, took a whole lot. They're tight end with that touchdown catch. I know I'm gonna mess up his name. Friar Muth, Friar Mouth Friar Muth Friar. I'm gonna call him Sir Friar. On that touchdown catch, he initially dropped it. He initially dropped it. And it was a good pass by Ben Rosasberger. But he initially dropped it. Then he was like, hold up, man. I ain't trying to be shaky hands, Eric Ebron. Let me get this thing in the bucket. And then he went on that second effort and grabbed it. That was nice, man. And he was balling all day. And that other tight end was doing good too. I think his number is 81. I can't think of his number off the top of my head. But the other tight end was doing good as well. And I saw Eric Ebron on the sideline. I'm not sure if he's injured or not. I'm not sure what the status of Eric Ebron is, but you know, he had to be looking like, come on, man. Why do you do balling while I'm on the sideline? I'm sure he's probably injured or something like that though. But anyway, Baker Mayfield, man, it was tough. I know Browns fans like, ooh, I'm sure there are a lot of tears that were dropping in this game because the Browns receivers, they were dropping in this game. Baker Mayfield, he was doing this thing. I felt like he did it. I mean, I feel like he did, I can't even talk. I feel like he did everything that he needed to do in order for this team to be successful. Now, there was one play early on where he, I think you threw it to either, either Odell was wide open and he threw to like a triple-covered Landry or Landry was wide open and he threw to a triple-covered or Odell, one of the two, but that was early on in the game. But I had tweeted out during the fourth quarter, I was like, is Odell Beckham Jr. even playing? Now, I knew he was active for the game but I just really hadn't seen him. So I looked up the stats on ESPN.com. No, this is not an advertisement for them anything, but I looked up the stats on ESPN.com and said, Odell Beckham Jr. had like one catch for six yards, something like that.  I understand that. Not every receiving if they're an elite receiver, they're not gonna have 100 yards every single game. I get it, but one catch, six yards. Okay, and again, Kudos to Steelers Defense because they were doing that thing. You do have four sacks at halftime. They were doing that thing. So they were obviously holding Odell Beckham Jr. down but then it was like right after I tweeted that, Baker Mayfield, he's looking, throws a shot, Odell Beckham Jr. He goes for a one hand and in the past might've been a little bit high. Might've been a little bit high, but Odell Beckham went for a one hand and them Steelers, they were coming to whack him and they did whack him, but he ended up dropping it. Ended up dropping it. And then Jarvis Landry, he had some crucial drops. One of those drops being that fumble because if you rewind like right before that, Baker Mayfield, and you know what, let's rewind because I was about to talk about the play with Baker Mayfield ran for that first down and he got what I thought they were gonna call a late hit on Minkoffice Patrick, but even if you rewind before that, the touchdown to Deionis Johnson, because that was a really nice touchdown. I said, hold up, are these Browns? They Browns, they been watching those, they been watching my Ravens play, huh? Because that was a play straight out of Raven's playbook. But, with Baker Mayfield, he put it in Deionis Johnson's chest and he held it. He held it, held it, held it, held it, held it. Felt like he held the ball in his chest for like 20 seconds and it looked like that and that, when you put the ball in your running back chest and you hold it, that freezes the defense for that split second. And I saw one of Stila's cornerbacks, he was right there, but he just kind of missed it and he was like, ah, he was out of position. He was out of position and he missed and Deionis Johnson, boom, touchdown, touchdown. But even though it is Baker Mayfield, and you know it's Baker Mayfield, he ain't taking off on nobody, but he can scramble good enough, but that threat, just him putting it in his chest and just holding it, that makes defenses hesitate. And when you hesitate on defense, that could end up being all she wrote. So, that was a really nice run, really nice play design, really nice execution too. Chubb, Chubb was running nice in this game too. Chubb was running tough, he was running hard. And especially toward the end of the game. I know in Madden, for Nick Chubb, his ex-factor, he could break like 50 million tackles. 50 million tackles. And sometimes when I'm playing against the Browns in Madden, I'm like, man, that's so glitchy. It's so glitchy. But then when I watched the games like today, I said, oh, okay, maybe it's not so glitchy. But Chubb, he looked good. Of course, still missing Karim, but again, you got the Ernest Johnson. And he can't have games like he had every Thursday night, like he had the other day on Thursday night against the Broncos, but he definitely is still a key contributor. Now, back to the Baker Mayfield run. When Baker Mayfield got that run for the first down and he got hit a little bit late, and he got up and he was hyped, he was like, oh, okay, let's go. I was like, oh yeah, he got that place rocking. He got that crowd rocking, they all into it, they hyped, he's hyped. But I was like, uh-oh. I just, I don't know, man, I was just like, uh-oh. That's what I was thinking in the back of my head, like, uh-oh. I just felt like something was gonna go down in a bad way for the Browns. And Baker Mayfield drops back. Those are the Jarvis Landry, Jarvis Landry fighting for more yards. Pow, fumble. Fumble. And it was like, ooh, man. So I just felt like in this game, and they said that was Jarvis Landry's first lost fumble in three years, I believe. But I just, I felt like Baker Mayfield's receivers kind of let them down in this game. Early on, it was looking like they were gonna be on point because he threw a really nice pass in the first drive of the game to Hooper.  But they just, they kept shooting themselves in the foot. Shooting themselves. Now Pittsburgh defense was nice too, now. Gotta give them that credit. But Browns, their offense was not helping out. Then you had the Hollywood Higgins, the false start.  Uh-uh, it don't work like that, man. You gotta wait. So now Browns are last place in the AFC North. Because they are four and four. The Steelers are four and four. No, no, no, Steelers are four and three, excuse me, so they came in this game three and three. But now they have the division win over the Browns. And they're over 500, so they're above the Browns. The Ravens are five and two on a bye week right now. And boy, when we needed it after that beat down, we took to the Bengals. I actually gotta check on that game, see how that's going. The Bengals and the Jets, hopefully the Jets held it down, but we'll see. And then the Bengals, they sitting up top at six, no, excuse me, at five and two. And again, we'll see the results of that game. But anyway, AFC North, it's gonna be tough. It's gonna come down to it. This is like, it's like a good version of the NFC East. Because NFC East, the seasons always come down to the very end, but all the teams are usually pretty bad. Now Dallas been doing it thing this year now. Okay, I see Dallas. But usually they're pretty, all the teams are pretty bad. But in this case of the AFC North, all these teams usually do their thing. And it's a tight race. So we'll see how it turns out, we'll see how this thing goes. Congrats to the Pittsburgh fans, Browns fans, I know it's rough. Especially a game like this where it was close throughout. The games like this, they hurt the most. Not a beat down like my Ravens took last week. Those games, they hurt a little bit, but they don't hurt nearly as much as these games because these games, in the Ravens game where they got beat down by the Bengals last week, we knew we were losing well into like the third, fourth quarter.  So we knew what was going on. We knew the situation. But games like this, where it could literally go either way, and it comes down literally to the very end. These are the ones that sting the most. But it's early in the season. So we'll see how everything plays out. Team Keep It Clean, I love y'all. I appreciate y'all and we out.


Chinese medicine to me is one of the most incredible sciences that I've ever seen on the face of the planet. These ancient physicians were ones that, just like Einstein, tried to find a unified field theory, but not in relation to physics and just the laws of nature, but also how the laws of nature affected human beings in terms of illness, from the most macro forces in the sky to a plant, a color on a person's face, where a rash shows up, and all of that becomes key diagnostic information. So in this video, I want to talk a little bit about why I think Chinese medicine will be the saving grace of modern medicine, and why it has this unbelievable simplicity and complexity to address disease on every level that you won't find from your conventional doctor. I'm Alex Hain, current doctoral student in traditional or classical Chinese medicine, also author of the wellness book, Master the Day. Now look, I've also included a free little PDF download in the description there on how to add 10 years to your life with traditional Chinese medicine. So a couple of key practices you can do on a daily basis. So check that out in the description box there below. It's the very first link. Now to me, the big problem with conventional medicine is, let's say you have insomnia, you go to your doctor, and he or she gives you something to help you sleep. But there's no consideration whether you are recently divorced and you're heartbroken. There's no consideration over whether you have pain.  There's no conception of whether or not you have anxiety or you're depressed. Most physicians will still give you something to just help you sleep like a log to just knock you out in the most generic way possible. And yet, through that drug that's given, to me it doesn't even matter if it's a plant, the point is that it doesn't deal with anything related to the root cause. The person taking the Ambien still is divorced and heartbroken. The person with digestive problems still has acid reflux. The person who has anxiety or depression still has anxiety or depression. And so we go through this whole rigmarole where we're given these things over and over and we never once touch anything close to the root of the issue. And to me, the reason why this is such a deep flaw with conventional medicine is that conventional medicine has no health philosophy. There is no concept of what it means to be healthy and the practice is to be healthy. You ask your doctor what does healthy mean and she'll probably say, no illness, no disease, how do you get healthy? Work out, eat right, follow the USDA food pyramid, maybe you meditate or something. It's very generic, not at all customized advice which shows nothing at all about what's going on with the person, specifically what's going on, what's the pattern out of balance and what is the unique pattern to them that needs to be rebalanced. And when you compare that to the ancient Chinese physicians, they took every little thing from how the season this year, let's say we have a long summer, literally the long summer is going to affect what's called the chi or the, you can call it the energy if you want, of nature, which is then going to affect the expression of certain diseases and illnesses in a different way than any other year before. That long summer will affect the next season, it'll affect the expression of colds and flus and other illnesses in the human body, which will then even have to get treated differently. With different herbal formulas, different, there's a different progression of pathology, more serious, less serious, more lung, more large intestine affected and it's amazing the level of sophistication where from everything from the patient's thoughts, the gender, the age, the location in which they live, the environment, like the actual weather patterns, how that relates to their illness, to their daily life, colors in their eyes, brinilness in their nails, dryness in their skin, the way they lean in a little bit too much when they're explaining what's going on or the way they are back and a little bit covered up in sedate when they're explaining what's going on with their health. All of this is key diagnostic information in Chinese medicine and this is why it's so incredible because like Einstein with his obsession to figure out the force that unifies the entire universe, Einstein said that the more he learns about physics, the more he's interested in metaphysics because in his understanding there was no chance that this was just chance. These universal forces are not only functioning at such a large level in terms of like the force of gravity in the universe and the cosmos but also coming back to human nature and how consistent these patterns are, these laws of nature, they're not just these accidental forces like he was saying. And so these Chinese physicians noted what do these macro forces all the way to the most micro, how do they relate to the patient's health and the patient's wellness and what does everything reflect about that person's the energy dynamic in the body, whether they lean too forward, they lean far back, the voice is loud and shouting or the voice is kind of quiet and sedate and they can't really like muster that strong voice. All of these show exactly where a patient is on a spectrum in the most genius way that brings together every piece of data, every speck on a patient's body where there's moles, where the rashes show up, where psoriasis shows up, if the asthma is worse on the inhale or the exhale, all of these help trace back that paper trail to figure out what is going on. So in my mind there is no medicine that has ever been as customized and its understanding is such a high level as Chinese medicine where all of this information is so key and critical where a normal physician would not really care in relation to your gender for some issues, in relation to your age for some issues, your diet, where you live, are you in a moist or a dry environment or even your emotional states. Many physicians now they don't ask those questions because apparently it's not important to them but Chinese medicine every little thing is a little bread crumb that traces back to the root of what's this bigger imbalance going on in a person. So that is my impassioned rant for today. I hope it helps you understand a bit more about why Chinese medicine is so incredible in the hands of someone that knows what they're doing and how it can help you understand the patient and understand maybe your own self and self-healing. How everything is not coincidental, that it's all related to the health and the pathology and the balance, the imbalance in the person. So before you go I want you to leave a comment there below. What do you know for you? What has been your most common frustration with seeing a physician? Doesn't matter, East first West. What has been your worst experience and what's been your biggest frustration? Comment there below. And don't forget you can check out my last two related videos right there and right there.


Let, allow, make, and have. Which is correct? Number one.  Let him play. Let him to play. Allow him play. Let him play. Two. The teacher read the paragraph. Had the students. Had the students to. Had the students. Had the students. Three. My parents would not eat candy. Allow me. Allow me to. Allow me to. Allow me to. Number four. We finish his vegetables before he could go outside and play. Made our son. Made our son to. Made to our son. Made our son. Five. Your phone number so I can call you back. Let me get. To learn more about this topic, see video at link. Or check out our websites for more free English learning resources. ESL gold.com and freeenglishstudy.com.


The reason behind it was just to give our community a place to congregate, come together and enjoy fellowship together and really to show God's love. We just felt like it might be a need in our community. We don't have a lot of resources like soup kitchens or if there's a family who needed it, then we wanted to provide that. I'm glad to see something positive going on in our community. I think it's been too long that we're only noticed for the negative things that happen and I think this is a great way to start.