o I think that the optional step I stress again this is optional in our case it was not needed because our simulation was good we have a problematic situation where the kinetic energy is increased with this trick you can cool down the electron near the ground state ok for sure this is finished ok I get the new restart as you see the code did not copy new trajectories new pieces of trajectory I did only one step and since I asked the code to print to print the trajectory every time that the number of steps is a multiple of 10 in this case did not print the code did not print anything so now we start the last step that is like the steps pre-used the equilibration with the Noseuva thermostat and this is the input file we are number 5 the last step ok you see always increase this right to point to the right directory job the long-running job so now I want a lot more step because now I want to calculate some thermodynamic quantities from the trajectories we are going to compute the pair correlation function and the mean square displacement so to compute these quantities we need a lot more steps than 1000 a lot more steps than 10,000 probably but just to see something now we put 10,000 we switch again on the cp equation of motions ok this is the input file the time step is always the same pref is always the same everything is the same the ion temperature not controlled ion velocity is default that means to read them from the the stats file here nothing and here I have always the same position that are not used by the code so let's submit it the more time I run portrait by nve that means for constant number of atoms constant volume constant total energy that is the micro canonical ensemble as a professor of scandals said before if you want to compute dynamical properties like the diffusion coefficients you have to use the micro canonical ensemble is the one with the right equation of motion for the ions if you use the thermostat the thermostat has some forces and the ions that are not physical so they are not getting physical trajectories you can get physical averages but for dynamical quantities no this will take a little bit longer like 10 minutes and maybe oh ccp is about 5 minutes but if somebody took 7 minutes anyway you can see the what happens at the end if there are any questions let's see I think we took most of the question maybe we can look at the trajectory that we have now okay so we leave space to the lab no leave space to no I mean is this definition over? I think so we are waiting for the result of the last session and then we are going to compute something interesting but we have to wait a little bit ah there are some classes where if you are seeing now it crashes or something like that don't remember so maybe it's not good idea to do it now by the way you can run the script that will create again the trajectory you can view with obito for example this you can do while you are waiting for the results you see now it is longer and the atom moves a little bit by the way this code is super slow in my virtual machine I don't know how it runs in yours by the way you can see the atom that moves I can make some comments maybe on that you see the coordinates are not wrapped inside the cell the code always write unwrapped coordinates this is because with those unwrapped coordinates it is easier to compute the means for displacement for example there is a question is there any tricks to restart the molecular dynamic simulation without the restart feature working basically yes exactly that you can copy the last position from the input file copy the last velocities from the output file to the input file be aware that the units of the velocities are somewhat tricky yes okay so the velocities has the units of for the velocities you have position the same unit of length of a unit of time this is the same as the atomic position input part and this is always atomic units that means 2.4 times 10 to the minus 17 seconds I have written this number on my desk because I always forgot it and this is the same as position those are the units of the velocities that you have to use if you use the input file so basically you copy the position and velocities as is because in the output it is bor over atomic units of time so it is okay you specify bor for the position and that's it then you have to do the computation of the ground state with the conjugate gradient method if you want you can compute also the velocities of the wave function that means if you use non-conservable potential you can start from this restart file so you will produce a restart file with this conjugate gradient and then you can run again the valet or whatever you want using this restart file as an input and then I can mention in the meantime I can mention where you can find some documentation okay you have this then you can have a look also to the repository so if you google quantum express or gtlab you end up in the repository with this repository quantum class is there and you can find inside this folder cpv some documentation for the caponello method and there is a user guide that is in the process of a lot of updates where you can find some hints some very useful information to use this code there are a lot of stuff inside this file that I didn't say anything about and there are also everything the documentation for the autopilot that is very useful when you want to do some experiment there is a different file and you see how can you change on the fly some parameters like you can put a file in the folder of the simulation with this written inside and the code will start when it reads the file will change the parameter that you have written inside the file this is a mailbox file so there are these interesting features that you can use if you want all this stuff is not necessary when you do a production run so when you want to do your simulation for calculating the quantities of your system obviously you are not going to change everything on the fly but this is useful for experimenting at the beginning this faster so if you want for example to see what happens if you use a larger time step you can say let's try what happens you put this file inside the folder and the time step will instantly change you can see if the simulation explodes or not the most common error that the code outputs is orto went bananas that orto is the part of the algorithm that that it is an iterative algorithm that computes the orto-amity constraints that computes this and it is iterative and if something went wrong usually the wave function become messed up and this algorithm is not able anymore to orto normalize the wave functions and it brings out orto went bananas so if you see this message it's very fun if you see this usually you can try to lower the time step or maybe you have lost you add maybe you don't have a gap anymore or maybe new was too big so it means that electrons are no more for sure in the ground state and you have something very very wrong so you can you have to stop and look carefully at your simulation that turns on some unstable systems like for example I had this issue on the old Marconi K and L cluster some are probably hardware instabilities maybe the simulation is stable so this error was appearing randomly during the simulation but everything was okay so it can be that due to hardware issue this error or two but usually if you have this error and you look at the trajectory and you see there that the electronic tissues energies going to the stars you have to do something let's see if it is finished connection I lost the VPN sorry what happens to the VPN my VPN stopped working I don't know why it's always like that so I stopped to share because I don't see the error message that my computer is giving to me sorry let's try to see if the other script works it is in the post installed directory okay now I don't know why in my post computer does not work okay it works now we are seeing everything before the VPN stopped working again okay now the potatoes should be a lot longer so now I can run again this script that now computes also the peri-correlation function and the means for displacement okay now we can look also at the thermodynamic quantities let's look at the temperature first okay you see that okay it looks okay at the end of the day at something higher that 600 Kelvin you see that the moment in which you switch off the thermostat is important here for example I switched off the thermostat when the temperature was slightly higher and so I got a slightly higher temperature than 600 Kelvin let's see all the other data okay you see the system was oscillating around this total energy I switched off the thermostat the total energy was higher than the average so the temperature at the end is higher than 600 this is the potential energy you see this on the high side of the oscillations then we can have a look at the constant of motion and everything you see there is a jump there is a jump because I switched off the thermostat so there are no more thermostat degrees of freedom and the constant of motion of the Lagrangian changed because the system is in a different state now and it goes here let's see if it is constant enough okay super constant you see it is really constant so the constant of motion is okay I think kinetic energy is okay it is more or less a constant and this is the physical constant the physical constant the physical total energy kinetic energy of the ions plus potential energy that is with the density functional theory it's more or less a constant so I think that simulation is okay so we are happy we are happy with it if you want you can have a look at the trajectory let's have a look at the trajectory so after executing the analysis thing you can have a bigger laundry trajectory okay you see that some atoms went pretty far from their original positions and they are going a lot away from the cell so the system looks like a fluid or a gas where we have really really few particles water molecules so it's hard to say what it is but anyway we have it there the analysis script what is inside you can have a look at it if you are interested but it's not related to quantum expression so it's something more that I put here only to show you what it is possible to calculate with molecular dynamic trajectory there are some commands that compute the mean square displacement and their correlation function now let's have a look at them they prepared some scripts to show them plot let's say for the start from the percolation function okay this is the percolation function on the x axis there is the radial distance in angstrom and on the y axis there are arbitrary units these plots are not normalized but let's look at the peak you see there is a very big peak here this is related to the oxygen hydrogen bond and you see it is right it is about one angstrom so we are happy because our water molecules looks like water molecules so this is oxygen hydrogen percolation function I remember you that this is an histogram practically so the code tries to calculate all the distance in this case between hydrogens with a central atom that is oxygen if I write somewhere so suppose that you have an oxygen and then you have many hydrogens here put random positions so I look at all the distance between the central oxygen atoms and any other hydrogen atoms and I put those distance one, two, three I will have a list of them and I build an histogram of this and I have this blue plot if I do the same but I keep for example an atom an hydrogen then I compute hydrogen the distance of other hydrogen atom with respect to this central hydrogen atoms and I will have another distance prime one, prime two and a lot more and I will have this plot here the hydrogen hydrogen percolation function you see here you have a peak that is related to your oxygen hydrogen hydrogen this is related to this distance the first peak you see it is around 1.5 it is 2 this angle is almost 100 degrees so it is ok and then you have oxygen oxygen percolation function and you see that two oxygens start to see each other at 2.5 something so they are far better than the other molecules at the other atoms in the molecule so this is it and at the end there is a lot of noise the simulation is very small and you cannot have large statistics for this simulation so this is noise then we can have a look at the mean square displacement then I will finish this almost the end this is the script that for you it is nothing it is only some this is a mean square displacement plot you see there is the oxygen and the hydrogen mean square displacement what is mean square displacement so I did I put a formula ok here it is so you are computing an average this is an average over the trajectory ok here are some over all the atoms and you divide also by the number of the atoms of this type so you pick let's say an oxygen atom on an hydrogen atom let's say hydrogen you have a starting position at p equals 0 then this atom goes away during the trajectory you have p equal 42 whatever and you are here now and the mean square displacement is simply the difference between this position between the position at every given time and the initial position squared and you get this plot here what can happens in this case it can happens that if it is a solid for example the atom will will always stay near near its initial position and so you expect that the mean square displacement you have time that's something like that at the beginning it will move a little bit and it will stay still but this is not what is happening here so after an initial transition transient moment you can have some equilibrium behavior let's say that if the system is deep or a gas it is something like a line with a constant slope so we have something here then a line and you can compute the diffusion coefficients by looking at the slope of the line this is the diffusion diffusion coefficient okay so here it looks like we have a diffusion system and another thing that you can notice from this plot is that the two lines here are more or less parallel that is something that we are expecting since we have a molecular system so the molecules are always bonded within themselves so they are not dissociating the hydrogen of the water molecules they are always near the oxygen of their water molecules so they go together okay so if we had a lot more time on the x axis we will see that the plus basically will go one on top of the other okay so that's the end of the tutorial and if there are any other questions I am here if not we can meet later on the talk I would say we leave the zoom open anyway in case somebody but we can stop the streaming and we we wish to see the participants tomorrow as well but but definitely we leave the zoom open in case sometimes needs help we stay around and we can jump in if needed okay perfect by the way what was the time of the end of I think 12.30 okay so 2 minutes okay


WHO urged for an extension of screening and testing due to the widespread presence of the coronavirus SARS-CoV-2. As such, a rapid and reliable diagnostic method is required. We developed a reverse transcription loop-mediated isothermal amplification, a T-lamp assay to detect SARS-CoV-2 in 30 minutes. For sets of primers were designed, targeting the viral INA of SARS-CoV-2 in the regions of ORF1AB, S-gene, and N-gene. A colorometric change indicated the presence of viral INA, allowing for easy visualization of results. The assay was tested on 16 clinical samples, with 8 positive and 8 negative results. The test results were consistent with those obtained using real-time quantitative polymerase chain reaction, RTQPCR. Additionally, we demonstrated that the RT-lamp assay could be performed without INA extraction, making it suitable for use in remote locations. This rapid, reliable, and cost-effective RT-lamp assay provides a promising solution for. This article was authored by Wei Yi Huang, Boon Lim, Kierchen Hsu, and others. We are article.tv, links in the description below.


He runs like two miles if he could get this in one story. All right, I should watch New York. Okay, so one more talk before we do the complicated stuff. It's my pleasure to introduce Andrea Schaefer, who I tried to look through everything that all the various transitions he's done, and I can't do it. I'll tell you kind of the categorization, matter of the discriminations you will. So he did his undergraduate diploma in physics in... Is it already a handbrake? Yeah. And then also stayed there to do his PhD in Dr. Schachmann's super route. And then after that went to London to try Margris at that time with UCL to do a post-op. And then stayed on there as some fancy fellow which came in an independent position. The point is it was an independent position there. Before he moved off to the marks point, he moved in Heidelberg and then became a professor at the University of Heidelberg. I think he probably left the camp back to London. I have trouble keeping him here. Someone will see something first, which then became latest Francis Crick Institute, which is where he will be for the next year or so. Thanks, thank you for the somewhat worryingly detailed introduction. It's just that I've moved back between Germany and between Heidelberg and London a few times. And now I'm happily, happily in Brexit Britain. Well, thanks a lot for this amazing conference and giving me the opportunity to talk here. In particular because of a couple of people in the audience that was very excited to have here, particularly Antonia Massimo, as you will see later on. So for the last day we've been talking a lot about chemicals, chemicals like these that evoke activity in the brain, how they are received, perceived, encoded and so on. Maybe not surprising in an olfaction meeting. But I want to now focus on a slightly different aspect of olfaction that maybe sounded through in Tim's talk yesterday. Namely, looking at this sort of turbulent, let's call it an older plume, or that's actually a smoke plume, there's just a lot of structure and a lot of dynamic information way beyond just the chemical composition. I find that particularly exciting avenue to go down to try to understand how the olfactory system deals with. And a lot of people around the world seem to agree with how exciting that kind of project might become. So what does this sort of spatial, turbulent cloud of odor, how does that reflect into the point source that maybe a nose would be in here? Well, if you stick a detector, a fast detector in here, you see these sort of rapid temporal fluctuations that happen, I guess it's safe to say across all kinds of times, scale up to several tens or hundreds of hertz. So there's a very rich temporal structure in an older plume, and the question that I'm trying to get a little bit into in the next hour or so is what they could be used for and how they might be processed. So I'm certainly not the first to look at that. So studying the dynamics of plumes, this has been done for probably for centuries, this is one of these sort of maybe earlier meteorological papers where this group looked at a large smoke plume, I think from a sort of to study forest fire smoke as well, and looked at different distances. And you already see that at 80 meters, so very different length scales than we usually deal with, it's a very different temporal structure that something approaching half a kilometer, but you still see even half a kilometer away from the source, you see dynamics in this case again, smoke plume. More towards neuroscience, a lot of groups, in particular working in marine organisms, have looked at plumes for a long time. I think some aspect may be because marine organisms allow you to study plumes in water and as Tim has already said, it's much easier to visualize something in a liquid water environment than in air where a lot of the normally fluorescent molecules just become suppressed, I think, largely with oxygen nitrogen. So this is one of the again earlier studies from these groups I've never met personally actually so far, but there's pioneers in studying turbulence in liquids and using saline traces to identify different features of such an order of plumes or measuring what typical neurophysiologists would measure, peaks and these d's and lengths and gaps and so forth. Maybe the most well-known from a neuroscience, neurocircuits perspective along the lines of turbulence and the role of turbulence certainly comes from the insect world. This is part of a famous paper by Hildebrand's group also quite a while ago, this point showing different positions along the plume you do see very different, just qualitatively very different kind of temporal structures and this is a very much more recent, I think probably the best attempt to actually have a quantitative understanding of prediction about turbulence and concentration variants at different positions from, well, Tonyo and Massimo. So still I don't want to exactly talk about this, talk about turbulence and distance and direction. I think that's a very, very fascinating, very interesting topic but I want to now kind of look at a different aspect that turbulence and order plumes might be good for and that goes back for me to a paper that has been quite influential for just my small personal experience. This is the paper that got me into affection, I was in summer school in 1998 as a student and randomly got assigned to read some paper, a different one, not this one, but someone else was presenting this paper and I was very excited by this work in P&S from 1991 from John Hopfield, where he says that animals that are dependent on affection must obtain a description of the spatial location and individual order quality, so again in the direction what Tim was saying, but also order quality, they must get this description through order of affection alone, which I think is a strong argument for nocturnal or crepuscular animals like the lab mammals we work with like mice or rats, they must get a description of their spatial environment through affection and he argues in this paper that the variable nature of the turbulent airflow actually makes such a problem more tractable and makes it computationally feasible and even argues that the olfactory bulk would be a very good implementation of the computational algorithms he proposes in this paper. So what does John Hopfield mean with this problem? Well, let's take this sort of slightly clouded picture where you see, if you imagine somewhere a mouse or something sitting in here or here on the other screen, then what are you going to be challenged with? Are you going to be challenged with a lot of different odors from all over the environment? Certainly there will be some chemicals that on their own will give you a lot of important information about a specific mate or so, but there will be a lot of information, a lot of chemicals that indicate, let's say, that this flower is closed and other chemicals that would indicate that this sort of animal is deer will be present in the scenery. And what you have to do to kind of figure out which of those chemicals belong to the flower, which of those chemicals that might be partially overlapping belong to other flowers, belong to this specific deer. If you want to be able to allocate objects in the scenery just using your sense of smell. Maybe a more natural environment for a mouse would be this Victoria tube stop where a mouse tends to live in here and wants to maybe understand whether the cheese sandwich here is actually a cheese sandwich although you might get a lot of cheesy smells from all over those people as well. So that's the kind of challenge, I think is one of the key ones that so far has not been addressed very much in effect. And how do you separate your environment? How do you segment your scene, figure out which chemicals belong to a specific odorsource, the cheese sandwich, or the shoes, or the armpits, or whatever you find in Victoria tube stop? So the idea that Hopfield put forward as well, there is rich temporal structure in those natural plumes in normal turbulent environments and one of the key features would be, so he argued that chemicals that come from the same source, let's say the cheese sandwich here, they would all fluctuate a lot, but they would fluctuate in a very highly correlated manner. Because again, as we sort of discussed a little bit earlier today, diffusion over these scales generally plays a much less prominent role than sort of turbulent airflow in terms of carrying chemicals. So whether these different chemicals have different diffusional constants doesn't matter so much as the fact that they might be carried by the same kind of little air turbulences. Whereas odors that belong to a different source, like these again are highly dynamic, but they will be correlated within but not correlated so much maybe with the other group of odors. So that's the idea that would allow an animal to segment a scene to figure out which chemicals belong to one, which chemicals that again might be overlapping belong to a different source, just sort of figuring out whether the green and the square and the red and the triangle belong together, so whether it's a green square and the red triangle or a green triangle and the red square and so on. So this is sort of the general idea of scene segmentation or an auditory system as all of you know very well, it's called the auditory cocktail party effect, the idea being that if you communicate with one person you need to understand there all the components that make up the sounds they make as being separate sources and all the background activity. So this scene segmentation or cocktail party quality effect or binding or whatever you want to call it I think it's very prominent in all faction and some people it was mentioned that specific even a specific combination of smells a very different epilogical meaning even for insects than the components in itself it would be a very good example if I could remember who exactly said that and what it was. So I couldn't resist putting up this beautiful picture that's the cover of Nature Neuroscience from paper from Dan, Dan and Venki where they tackle a very, very similar problem sort of figure ground separation and show that individual odors can be identified in the context of varying of very highly different background odors. So they look essentially at the static way of separate identifying individual odors in the context of a large array of different background odors and I think Dan might be talking about that to some extent. So in tomorrow I think. So to visualize a little bit to give you a bit more intuition again this is still kind of a very lengthy introduction I try to not do much introduction to visualize what the problem I'm trying to address here these are just two little blobs of dry ice and image from top and simply using a color scale and you see it's a very dynamic airflow that's here tracked by the sort of dry ice plume that you can imagine that if you're here you see these bouts of odor or dry ice coming from this source you see them coming from this source and they seem to be sufficiently complex that you might be able to attribute different chemicals from one source and distinguish them from the chemicals coming from a different source. So how can we address this problem properly? Well what we want to do is we want to compare a mixture of odorants and compare two odor sources that contain exactly the same chemicals whether there is a difference in correlation if you measure it let's say half a meter or so away to stay in the length scale that's relevant for mice the way we do that is using photoionization detectors 95% of you probably use them themselves or know them for those 5% that don't the idea is a very simple one you suck in and these are commercial devices you suck in odorized air into a structure where you apply so if you relight with a specific wavelength that's going to ionize everything it's more ionizable than this specific specific energy then you apply a high voltage to separate those ions and then simply measure the current sort of sensitive amplifier measure the current that is proportional for large concentration ranges to the specific concentration these devices can be very fast and detect everything below a specific ionization energy and can be very fast with a bandwidth of several hundreds of hertz so what we have to do now if you want to measure these mixtures or individual components we have to actually have PIDs for two different kind of odors to simultaneously measure these temporal correlations problem there is that commercial PIDs don't tend to not have that but if we could get to several different lamp energies we could have one that only ionizes one specific component of one specific odorant so it would be sensitive only to this bluish one and others that would be sensitive to a large group of different odorants and then taking both measurements together we could piece a piece apart which odor is present so what we actually took is this device that many of you are using Aurora Mini PID with a bit of help from Aurora we managed to find other UV lamps that actually fit in there unfortunately most of them seem to be not produced anymore then you need to modify the PID a little bit so that it's resonant circuitry to allow it to operate with this different lamp and then you need to find odors that have sufficiently different ionization energy that are not too toxic for your postdocs and PhD students so the two odorants we picked is Ethobutray there are many many others that have a relatively high ionization energy of close to 10 electron volts but there are not so many volatile chemicals that are not toxic that have a relatively low one of a taping to opinion is one we are using so these are now two model odors we can use this one being being sensed by both PIDs with two different lamps and this one only being sensed by the higher energy one so very simple take those two odorants if they are mixed in some sort of dynamic way we have one high energy one that detects all odorants the low energy one that detects only one of the odorants and then essentially we can take the difference of the two to get to get to one one last sentence they have slightly different filter properties there's some scaling factors but in essence so the ones we looked at the temple bandwidth would not be high enough to I mean we think you know hundreds hundreds of hertz probably the olfactory system is not faster than that so we want to see hundreds of hertz but the ones I saw were kind of in the more hertz or few hertz which would been too slow obviously if you go to water you could use fluorescence and look at fluorescent dye but for air it seems if anyone has a better idea I would be enthusiastic to try something else so what's the outcome of these experiments again as I said we have two sources approximately 50 centimeters apart in a turbulent environment we measure odor one which are at the butrate and then after processing a little bit odor the both are a little bit processing that's the concentration of odor one that's the concentration of odor two two different sources both look kind of dynamic but they don't seem to be very highly correlated we go to the mixture however again same distance we see highly correlated temporal fluctuations this sort of example you clearly if things are correlated you know it was the mixture if things are less well correlated you know two independent sources and that is very robust it's truly if you do that tens of times you see always highly correlated mixture always barely correlated or uncorrelated to individual components so in principle the information seems to be there it's actually relatively gradual if you go tens of centimeters apart it's somewhere weakly correlated this is all done indoors we don't have contaminant odorants and we create turbulence by fans with little cylinders in front we're not yet at a stage where we could actually calculate the turbulence to see whether we understand everything but if we go outdoors on to my my slightly oversized and windy and rainy balcony with all kinds of background odorants we do see the same strong significant high correlation despite all the background going on for a mixture and weak to no correlation for 450 centimeters apart so this is without doing anything except placing vials of odorants onto our balcony and measure with the two PIDs 50 centimeters apart so there's flowers, there's hopefully not rats but all kinds of other smells around that do reduce this correlation as well as increase this correlation so it's a quite a robust phenomenon it's so robust that if you go to different distances so much closer where you see stronger temple variants or further away where you see weaker ones you still see this massive difference in correlation between mixture and two components and obviously we tried another odor pair we could find and again it's the same kind of behavior so the PID is between 20 and 60 centimeters and the two odors are between mixed and 50 centimeters so we tried to be in a length scale that we then could do for example navigation or experiments in the lab and it seemed not too small not massively too small in a length scale for our mice so there's a lot of temple structure and this temple structure there's a lot of information in there about things like distance and direction and so on but in principle those two should be the same because it's a physical mixture the individual odorant is still present exactly the same distance we have started looking at quantifying these things but we are way not as qualified as some other people in the room to do it properly it's certainly not a trivial problem what kind of the measures are that you would have at a specific distance but I think very interesting one we see so these sort of bulk correlations are done with many repeats even independent days so the correlations say the same the structure itself varies it's different again it's essentially a similar answer to Matt we might not understand the temple structure but what we do understand is that they are weakly correlated and highly correlated in those two cases so we use for simple technical reasons of finding odorants with a low enough ionization energy we did these two odor pairs where we find the same correlated versus uncorrelated I think they are a sort of different temple structure you would start getting a situation where diffusion becomes a relevant transport mechanism so I think we discussed that paper even already kind of a few months ago so what we're doing we've been trying those four odorants very simply have a little robot opening lids because we don't want to push air out very similar to what Tim was saying we don't want to push air somewhere we just open up and then wait for 10 seconds or initially we just did it manually we haven't systematically gone through many odorants and just the temple structure and not several odorants then it would be very feasible to do but that's essentially I would think what that paper did I don't think there's a good quantitative theory behind it but just because it's very difficult to do but maybe we can discuss that this is afterwards it's well possible because what we're doing is we're actually lifting two lids we try to not lift them too fast to not create but we will have correlation through the onset so the measurements we actually do for this correlation coefficient are only for the period of odor presentations obviously if we correlate the entire trace there would be a strong correlation simply because of the onset effect I think that's more a technical flaw in the way we can present and can get lots of odorants and conditions because the more natural situation as flowers and animals sit around and maybe there's an additional additional effect from an animal moving so that everything gets emitted at the same time so generally I think from these experiments that are somewhat intuitive from what one knows about the turbulent transport what we would conclude is that the dynamics of odors indeed following hop fields that allow for sort of seen segmentation or object identification or if you want to use it maybe not any more overused term for binding of different components so the question we now want to of course ask is can mammals use this kind of information so in particular if you sort of look at some of the spectrum, I should have put a spectrum here I guess, there's information up into the tens of hertz or even hundreds of hertz where you find very tight correlation so it might be a stretch to figure out whether a mouse that usually I don't know sniffs at 5 to 12 hertz or so maybe that mice would be and with slow receptor neurons that they would be using this kind or be able to use this kind of information. There's several reasons but I don't think it's too far a stretch to try one obviously comes from insects where a lot of work in particular by Paul somewhere in the room up here by Paul showing that bees are very good in detecting instantaneous or correlated onset or sort of simultaneous or slightly shifted onset down to time scales of several milliseconds so there is definitely a factory system out there that would be able to at least detect onset maybe not correlations but onsets in activity and again this old work from maybe we can try to discuss that in the end so a simple answer to the question that Dima will ask is we haven't yet measured sniffing during the tasks that we'll show but we are about to do that so we don't know exactly and we don't know mechanistically very well. What are the patient on the previous slide? I think it's volatility of the two odorants. Is that how you deal with the BID? Yeah, that's a problem. That is all stuff that is actually in the error bars of our measurements here. The reason that it's not one correlation or in particular is the fact that we do have noise in particular the probably maybe a couple of people are interested in this. Technically these beautiful mini-PIDs if you tune them for a lamp that is outside the normal range becomes somewhat unstable and actually you do get noise and then finding chemicals that have a substance that are below that lower ionization threshold they tend to be relatively close to the ionization threshold because it's very inefficient to actually so the calibration I should have said and actually the debundant has done that warned me again today this is a very well calibrated measurement this is much less easily calibrateable because of exactly those noise and PID issues. But for the sake of the correlations because we're comparing two conditions that are the same problem I don't think it matters too much. So in the insect world definitely there's indication that also sort of projection neurons follow fluctuations of auto-concentrations and work by many labs including I don't know Rachel Wilson's lab and Marcus Meissinger-Rohan I think about collaboration in this paper. In crustaceans there's maybe indirect evidence that crabs navigating seem to make use of turbulence or it is difficult to explain without that. So there's maybe indirect evidence that they can perceive those kind of turbulences. In mammals I think evidence is maybe a different issue and this I think the only slide that's published data from my lab, from mine and Dimas and Zack and many other labs work. We know that at least mammalian affection is not incredibly slow so we can do simple detection and discrimination tasks can happen much slower than people thought maybe 20 years ago and most importantly in this case from Dimas work we know that if you give very precise inputs optogenetically mice are very good in discriminating on the order of tens of milliseconds or even 10-20 milliseconds so there is the potential of the system to deal with high-temporal temporary structured stimuli and the system itself can actually respond in a quite precise manner. So what do we have to do if you want to figure out whether mice are really able to use those turbulent information? Well the first thing we have to do is to be able to reproduce temporal dynamics in a reproducible manner. So we have to get away from what we're trying to do to create sort of square order pulses to have it defined onto an offset we need to go somewhere that we can reproduce those kind of fluctuating order stimuli and that is a little bit of finding and engineering effort we ended up using these micro-dispens valves that can operate it up to 1200 hertz with very small volumes and if you use them and some manifolds do some sort of electronic control of them to create the right kind of pulses you actually have quite a small dead volume and can create pulses that should be at least in the sort of tens of hertz and if we are using again a PID to characterize that, these are pulses with increasing frequency we're giving and ultimately the one showing here is sort of 50 hertz stimuli and we still see a very strong modulation on a 50 hertz on a 50 hertz time scale. So, importantly this means that we can now take a recorded order so again in principle replicate those kind of signal structures from day to day and no we don't have to rely on a good generative model of what's happening what can actually give precise and sort of simplified, highly simplified simplified order pulse strains. Importantly with no change in overall flow because we have several valves so we can compensate flow quite well. So if the first question we need to ask then can mice deal with this kind of temporally structured information so for that we need to train them and it's expected that this training might be a little bit of an effort because as I think Leslie put very well you can't ask and talk to flies but unfortunately it's despite expressing Fox P2 you might not be able to talk to mice either so it's just you can't tell them pay attention to the order source you need to train them in a lengthy conditioning process so what we've been working with for a while as we built this sort of cage where we have a group house dozens or 20 mice or so each chip tag they get free food but have to walk and work for getting water so which allows us to have sort of train them on simple go-no-go tasks for quite lengthy period of time this is sort of the system as evolved over the years thanks to our workshop so there's a bunch of mice sitting in here in quite a happy environment that the Home Office, the regulatory authority in Britain likes a lot because they're actually they're not really water deprived they can go to water anytime they want they have free access to food, social environment and importantly very little interaction with any human so if they want water they just have to walk up these little stairs go into a little separate tunnel where they do a where they essentially it's a little operant conditioning box attached to it and that allows us to measure many many trials over periods of weeks or months importantly they perform a lot during the night and not so much during the day as you would as you would expect and with each animal the way we've set it up does approximately 300-400 trials per 24-hour period up to periods of periods of tens of days so this general system allows for quite efficient and automatic conditioning or sort of cohorts of mice with some advantages that it's minimal human minimal human interference that it happens during their naturally active night and we can do some automatic health control and finally maybe an underestimated point is we don't have to water restrict the animals they can obtain water no matter when they want so they're never dehydrated unlike if you sort of don't you take them off water for 24 hours and then have a brief training episode so this set of advantages now allows us to maybe try to train them on correlated and uncorrelated stimuli so to determine this we train them on a go-no-go conditioning task but not instead of discriminating sort of simple odorants we actually ask them to discriminate the same odors but with different temporal profiles so these are going to be the two extreme stimuli we're starting off with a rewarded stimulus where two odors are highly correlated and an unrewarded where they're actually anti-correlated so the most extreme we can try to do this is an experiment that as many I think of factory behavioral experiment comes with a lot of controls necessary and caveats I will walk you through some of them the first is obviously to calibrate the system such that there's no indication in total flow and no indication in total odor concentration averaged over one of these cycles that is different between the S plus and the S minus trial we actually achieve that partially through carefully calibrating those different valves and I think Paul can probably sing a long song about comparing individual valves in their performance we have to go through similar routes here but also then at some point we add a little bit of noise to make sure that there is additional variability that makes it impossible to distinguish between those two stimuli based on an unintentional parameter importantly also we use several valves to make up the blue odor several valves to make up the red odor and several valves to make up the compensatory air flow this allows us to from with each trial to actually use a different combination of valves so it's very difficult for the animal to pay attention to specific kind of click noise and we can train them for extended periods of time and importantly if we start off with training animals on six out of those eight valves and then we at some point introduce these two new valves that they've never seen before and from everything of the performance of all these other valves there's no way to predict whether there's an S plus or a S minus stimulus coming up so we can use those trials as being a completely novel set of valves, directions or whatever the intricacies of our little manifold manifold might be. I'm going into the length of these control details because we had so many nice control discussions with Tim this morning I have to show them slightly unprimed and then after a few days we can just manually move around and refill fresh bottles and look how that's happening and then switch to these switch controls switch controls again so again we first we first train them for about a week with I don't know a signal versus eugenol or something something unrelated and then we use two new orders for the temple structure so I'm more controlled across frequencies maybe drop that so we can start off also with a relatively simple task we do two hertz correlated versus two hertz anti-correlated then the animals tend to learn that these red group of animals is one where we actually well where valves are clicking in the same way but the odors don't have any prediction any predictability and then we do introduce the switch and here's an example of the first switch we're doing so each row is one animal's performance and you see in the different green colors things they got right in the different red colors things they got wrong and so it said these hits or correct rejections for the lamp misses as people call them and then we have this time that we switch where the first stimulus there's no way for animals to be able to know whether that should have been an S plus or an S minus and you see there's some animals that are perfect before that stay perfect afterwards like these these cases here others make some mistakes but overall there's no difference in the performance before or after so for me this is sort of the tightest kind of control we can do in this behavior because there's no difference in the performance and make this distinction except using using what we intend to put in because it's a completely new system so these are two hertz stimuli so these are 250 milliseconds on 200 milliseconds off so these sorry so this length here would be 500 milliseconds and then we're ramping up the frequency to see where up to what frequency actually detect stimuli two hertz is maybe not so exciting but this is sort of our star animal one example to show we started training on 2, 3 et cetera going up a frequency up to 12 hertz and we do a sort of switch control at 12 hertz go up to 16, 20, 25, 30 and even at 30 to 50 hertz the animals perform at 90, 95% correct so this is 30 hertz fluctuating stimuli every 30 milliseconds there's no difference between those two stimuli and so this animal must have been able to somehow pick up the correlation structure of the stimuli on a 30 millisecond time scale and the population of animals these are 14 mice and a few hundred thousand trials so we see that performance goes down with frequency plotted here logarithmically from 1 hertz, 10 hertz to 100 hertz up to on the order of tens of hertz we see it seemingly different from chance line trained from doing sort of statistics and comparisons here because we can discuss with people who want to do that in a minute I can in a minute so because we were suspicious this is I think a relatively well relatively extraordinary claim that mice are able to distinguish correlation patterns on the 20 hertz time scale so we repeated the entire set of experiments in the new cohort slightly different training starts with extensive training on low frequencies but the second cohort of 19 mice again a few hundred thousand trials performed same way we have less variance here because we simply have more trials in these frequency bins in the tens of hertz range and then we at that point we also had my very suspicious PhD student wanted to have a control of a group of mice that are not receiving odorants but the same both clicking patterns and those animals didn't perform anywhere near above chance for the entire frequency perspective so there is a kind of realm where animals might be able to discriminate so they are able to discriminate correlations up to tens of hertz so it's I think similar to what we've done for a long time we have bins and they need to licking I think two out of four bins but I'm not 100% sure I should know we simply haven't done that but we thought we ramp up frequency and that would be the easiest way to make this relatively unintuitive task for them maybe work but we haven't done explicit jumps so now then we randomly mix frequency between one and 80 hertz together to get this sort of large data set that maybe we should do I mean I think we try to do that with all the kind of controls we do in terms of making sure you switch to something new you switch to different valves and using this cohort of animals clicking pattern and same directional pattern I was thinking that's with the pharmacological manipulation that Tim was mentioning but that might be I think you would like them to kind of have learned something and start and then kind of train the probe but maybe I'll take the point start with Dan so the difference is whether the two orders are correlated or whether they are anti-correlated and the anti-correlated case half the trials one order starts the other half the other order starts maybe the next slide answers your implicit question that's what we're doing exactly at the moment so it's maybe could lie feet into it so so this is a little bit this experiment what we've done so I don't want to go too much into a mechanism because that would open up an entire new avenue and kind of convince you of the phenomenon first what one of the mechanistic ideas we had maybe and that goes into Dan's direction maybe they detect onset like what Paul has shown very well in bees so what we're doing here is we are training animals so this is a cohort of animals that does very well at sort of frequencies of 20, 30 hertz or above so we took the frequency where they just were able to perform this range and then we keep the stimuli intact except that we alter the onset so the onset might be instant although the pulse is anti-correlated the onset will be correlated all the pulse is correlated but the onset will be anti-correlated so the prediction would be that if they detect onset rather than the sort of correlation structure performance should actually flip so they should mistake the S plus for an S minus and the other way around if the onset is just part of the overall perception it should maybe drop slightly and what we saw is exactly that, that it never flipped but it just dropped slightly so we think they're not detecting the very onset of it but they actually take a little bit more time to integrate and actually use correlation across the entire structure Dima is not convinced maybe so we are we're in a physics institute so I can use the blackboard so what we're doing is we are so this is let's say the correlated stimulus so this is the S plus and the S minus looks like looks like like this and then we are we are introducing probe trials where we are sort of changing this but still the rest of the trial trace stays the same so the onset is now not correlated but anti-correlated whereas we're introducing in these trials we are making the onset the onset simultaneous relative onset between the two odors I thought I kind of managed to manage Dima's SNF question that's why we're measuring SNFing or we're trying to measure SNF at the moment but maybe in the interest of time so we started looking at reaction times as well what we see is that what we're plotting here is performance so perfect performance, chance performance as a function of their reaction time defined by the first time of licking for the S plus trial and you see that those animals that perform well are the ones that respond later and this curve becomes shallower but still for high frequencies those animals that perform around 70-75% at 60 hertz are those that actually refrain from licking for a long period of time so this is contaminated a little bit by the task structure that licking also indicates when their action but it is some indication that there needs to be some more lengthy integration over at least on the 100th millisecond time scale no I think this suggests, I think what Zak and Dima and we all saw was that discrimination of two simple odorants even if you mix them together can happen very or does happen very very quickly within one sniff within on the order of 200-300 milliseconds here now we're asking the animal to make a much more possibly much more difficult but maybe also a logically more relevant distinction namely whether two odors are correlated or not and that requires more time no this requires a long time, this is a second so the scale here is one second so the animals that perform at a way above chance need, have a reaction time of approximately approximately 900 milliseconds to a second so significantly longer than what Zak, Dima and we had frustrated so this is so that's maybe then come to my last slide as I said I don't want to go into a mechanistic interpretation but hopefully and if I haven't convinced you that the animals are able to detect temporal structure on the tens of hertz time scale then I failed, I want to give you some notion that we think they are able to do that comes from physiology because as Linda and others have pointed out one should maybe do even more controls to the behavior so one way to confirm that the animals might be able to discriminate those structured stimuli to actually look in the brain whether we can see cells that differentially represent those stimuli so we've started doing a little bit of imaging of the output of the olfactory bulb so as Charlie said I should have a picture of Carl so I think this is the olfactory bulb and these are the cells we are recording from so mitre cells and we find some examples approximately 5% of cells that show significant differences between those two stimuli the correlated and the anti-correlated one but this is very early stages so this is a very preliminary based on a few hundred cells imaged we seem to see most the highest percentage of cells at around 20 hertz I don't know whether that's real we haven't understood obviously what's happening there we haven't tried to directly record from those cells we're now doing a little bit of a little bit of electrophysiology extra cell unit recordings for throughput reasons and there we also do find some cells that respond significantly different between the two types of stimuli so the only thing I want to take away from the physiology is that not only can we do behavior with a lot of controls that animals are capable of discriminating temple structure on the sort of 20-30 hertz level but we also do find some representation in the olfactory valve sort of consistent with that so let me try to try to wrap up so like many others we find that naturally spreading odors have a very rich dynamics we find that chemicals that come inspired by hot fields were chemicals that come from the same source co-flux rate and fluctuate in a highly correlated manner and they're weakly or uncorrelated even for closely sort of 10 centimeter closely spaced sources if we build sort of a fast auto delivery device using these microdispens solenoids that allow us to deliver odors with a bandwidth of 50 hertz or higher and we can then use that to the behavior and show that mice can detect the correlation structure up to frequencies of well beyond tens of hertz and you know confirming that yes the correlation structure is already somewhat represented in the output of the olfactory valve so stepping back my conclusion would be that mammalian olfaction is not only fast but actually also high bandwidth sense that is able to detect and discriminate temporal structure in the environment so by the way I'm not trying to say that the animal knows these odors are correlated or anti-correlated I think it simply learns that they are different we've done some extremely under underable human experiments my PhD student looking at trying to learn to discriminate those it would be fascinating if someone who knows a little bit more about that would actually figure out what the perception of humans is from for those highly correlated and anti-correlated similar whether people report anything that has anything to do with the chemicals or whether it's simply two different smells and they can't even tell whether they are correlated or not so I'm simply saying that the temple structure is something that the animal is implicitly able to able to process and I think that might be sort of the orthogonal dimension to the entire chemical space and allow us to understand how the local circuitry of the factory system extracts this kind of information. Finally I want to as Venky mentioned we've just moved into this beautiful new building Francis Crickin Studio in central London it's an amazing place great great colleagues an amazing core funded institute and we are now hiring every autumn hiring group leaders early careers so directly from postdoc this is core funded for up to 12 years for a group of six people don't have to write grants can use core facilities no mouse costs and the great no teaching is an incredible environment so let me if anyone wants to know more let me know and finally the people that have done all that really was spearheaded by an amazing PhD student Andrew Erskine is just about to finish PhD in the next six months or so and was joined by two experienced postdocs Tobias and Tobanjan and yeah they are the true driving force behind them obviously thanks to the funding sources for that and thanks to all of you for all the questions


Thank you for having me here speaking. My name is Ali-Ce Woogie, and I'm PhD student. My supervisor is Misha Alessa Alexander. My project is inserted in a german multidisciplinary project. And the aim of my research is to better describe Social, economic and demographic changes happened through changes in regimes v Cicili v 13. in 16. century A.D. Včetno včetno imam zelo prezent na preliminari desa karboni in nitrogeni stabilizovati analizi vzelo na ljudi, življeni in planti. Ale imam zelo na ljudi, življeni in življeni. Zelo, da imamo počet, Zvom od 1. century, when Sicily was ruled by the Byzantines. In then, during the 17th century, the Arab population started to raid the island from the western part, so from Mazara. And then by the 9th century, they occupy mainly all the islands, and they are replaced by the Normans, that comes down around the 11th, 12th century, and they are a Christian, French-speaking population. Then the last transition is Norman to Zvebian, where the Zvebian are a German-speaking Christian population. So I try to make sense of the days I have so far, dividing them in these three different categories, so Byzantine rule, Islamic rule, and Christian rule. As some of the speakers have said today, one of the important things to take into account to say something about agriculture is that Sicily, during Roman and Byzantine times, had extensive areas of lasifundia, and the Arab conquest introduced new crops and the new irrigation system. And that brought the agriculture to be more productive, the population to grow, and the society changed accordingly. So Watson explained this theory about Arab agriculture revolution, claiming that the Arabs introduced new crops to the places they colonized, and many of these crops are seaford plants, the consumption of which can be dissected by stabilizatopsanalysis. So stabilizatopsanalysis can help clarifying at least the diffusion of these crops in Sicily, analyzing human and animal remains, and this we are linking with the archaeobotanic evidences. The broad research questions of my PhD are if in general the stabilizatops days can indicate a change in regimes from Byzantine to Swabian, the form of these shifts, and how the different food sources played a role in the diet of the different populations. If we can clarify this agriculture revolution, so in terms of agriculture and husbandry practices, and also if these can fit in the description of Sicilian society with particular features in terms of society agriculture and culture. So a brief reminder of what is stabilizatopsanalysis. So they are basically an ecological tool that allows us to have a chemical signature of the food sources. So here we have different food sources, like meat, different cereals, and fish, and these have particular delta 15 and delta 13c signature. That then when during metabolic and other biological processes they are incorporated into the human body, they go through what we call fractionation, which is an enrichment in the delta 15n values and delta 13c values. And this allows us to use the collagen as an indication of the prosaic parts of the diet of this individual. While the hybonate, so the mineral part, gives us more overall indication of diet. So stabilizatops have become in general very used in the field of archeology, because they allow us to draw consideration on the society structure, and as well clarifying relationship between people and say something about agriculture and how the animals were kept. So during the first phase of my PhD I obtained collagen and value for the delta 13c and delta 15n of humans and animals in order to assess the diet of individuals from different sites and presenting different religious background at different periods of the occupation of Sicily by the Arabs. So in this slide I'm showing the results from a previous study from Alexander in 2014 and I think it's important because it shows a similar context. In fact in this study they study Christian and Muslim population in late Medieval Spain between the 13th and 16th centuries, and this study was able to show statistical differences in the values of the delta 13c and delta 15n. And so they were able to sort of characterize and divide Christian and Muslim population, and overall the Muslim individuals show enriched values both for carbon and for nitrogen. And this was attributed to the consumption or C4 crops or animals fed by C4 crops. So these are the sites that I have samples from at the moment. In this first year I extracted samples from the northwest and southwest part of the island. The one in blue are the sites where I have animal samples from and I still have to extract and run the samples from the southeast of the island. That can be very interesting if they show some differences because the area that was colonized more by the Arabs is the northwest part. So in total I have 152 human samples and I have extracted and analyzed 87 of them. The overall state of preservation was good with the situ and ratio of 3.1, 3.2 and rate of success for collagen extraction between 96 to 100% for every site of time. For the animals I have a total of 126 and I've analyzed so far around 60. So these are how the data looks like. The crocs are the animals and the circles are the humans. Before going into the saline to the groups I just wanted to outline that I need potentially to have more food sources to analyze in particular fish and of course to work more on the archaebotanic part as well. Because every of these circles, so C3, C4, fish and freshwater fish may have an impact in the isotopic signature of the humans. These are the animals data. So I'm presenting here three different sites. We have Palermo, Mazzaria del Vallo that you just saw with Gironomo, and Agligento. So here you can see that there are differences both in Delta 15N and in Delta 13C. So we may imply that there were differences in husband in the animals management at different locations. In particular, the values for the pigs have a wide range in Delta 15N. So we go from very low Delta 15N taking Palermo like around 4 to around 9 of these animals. So this may indicate a difference in animal management. So these pigs may be wide or free range pigs and this one may be more farmed sort of omnivorous pigs. The animals from Agligento overall have compared to the other two are a little bit more enriched in Delta 15N. So it's possible, so it's a theory that maybe they were costal grazing but any suggestion is welcome. And then looking in particular at the values for the chickens in Mazzaria we can see potentially a difference in husbandry practice between phase one which is a 10th, 11th AD under Islamic rule to phase two, 13th AD under Christian rule. I received these results when I was back after a break so I didn't have time to really think about them. This is one of the most interesting things that I can see and is the Byzantine rule diet in different locations. So in blue you see individuals from Agrigento which is in the southwest of the island and in yellow Palermo and Trappany. So the population in Agrigento of the individuals have shown enriched Delta 13C values and this may be due to different things, to different reasons. One can be the consumption of C4 crops as we saw for the other population. The problem is this is under Byzantine rule and these are Christian individuals or it can be done more likely, possibly, to see for the consumption. So this is a comparison between individuals that were found in different burial rites and you can see that there is no big differences between them so they are all grouped together. This is Palermo through time so at different time it is difficult to resolve different groups and this is a comparison between Contrada Santargata which is a Byzantine Christian site in the countryside and in general the Delta 15 values for the females individuals are higher than the one for males and compared to Palermo under Islamic rule and for Islamic burial rites the trend is completely the opposite so we need to increase the number of samples that we have in order to make more safe discussions. So in summary, so far I couldn't see direct evidences of C4 crops during or after Arab conquest but I want to carry out more analysis on that. I have already done carbonates on the agrigento population and I am planning to do compound specific of the amino acid for the animals and the humans at agrigento. We can see an enrichment in Delta 13c in the individuals from agrigento under Byzantine rule and we want to understand if this is due to a C4 component or a C4 component. We can see different strategies in animal management at different locations and possibly a shift from the 10th to the 13th century in the management of the chicken. We can see that there are differences in management of pigs so some are wild, free range and others are omnivorous so very likely farmed and animal values for agrigento are different from the other sites so they are enriched in Delta 15n and so we may emphasize cost of grazing for these animals. Thank you.


Yo, what is Sasuke comin' out of him? W-w-w-what's goin' on?! No! Shit!  EVERYBODY WRONG! How about we all gather in front of it and activate it? They're already... oh my God, it's like the King just died. I vote him. He wanted this to happen! Y'all say this arc is slow, I don't mind this. I haven't had one complaint yet. Even the pacing's not bad. This guy's in on the tricks! He planned all this. I- Bro, that was disturbing. Showin' like kids running around, and then a nuke dropping! We found Kankuro's remains. Oh, he- Bro, we've seen him in worse conditions. Come on. Remember when y'all thought- y'all tried to make me believe- Um, Choji died. He said... Yeah, Sasuke said he had the best day ever, man. He was able to kill one of his underlings. Oh my God!  That puppet mouth! Shit! That was awesome, man. Look at them on this green screen right now. She's just walking. She's going. Oh, please join them, please. Oh my God. See, he's fine. He is fucked. They have lights and everything! This is crazy! They got him. Yo, he looks like a grown-ass man right now. He's even saying, Gara unconscious! Swice! She knew it. Yup, her bad feeling was right. Two days! Two days! Get your timers out, guys! 48 hours! He's poisoned. He won't wake up. Someone get a couple of snotty on the phone. It's a new poison. God. They erochi Marudin. I don't like when he's quiet. Naruto isn't a quiet... ...anime.  Naruto's still a child, though. He looks like a side character without tattoos. I love it. Yup. Takashi's quiet when he said that. This is personal now. Yeah! Let's go! Shit, man! That came out of nowhere! I knew all along. Yeah!  Oh my god.   I couldn't find the answer when he was alive. While he was alive, I needed that reason. They wanted the same.  Soba gotta! They're after me, too. Yup.  It's now two! Oh, her whole perspective has changed completely, man. Wow. Water. She's getting all the superstitions, man. Utsumaki. I got used to it. Oh, wait a minute. That was... Oh my god. That's even crazier.  No, man! Oh god! That was a perfect scene! Shit! Oh, that was great. Motherfuckin' said gringe in the chat. Look in the mirror! Oh. Oh, I thought his heart stopped. He looks fine. I forgot his name was Baggy.  Sassety. I could read those lips. Sassety's red sand, the puppet master. Uh-huh. I read those lips. I could read Japanese. He didn't say sassety. Yeah, he doesn't know his name.  He said my man. My man. He's gonna sell with them. Them. Them! This guy's going through this shit, man. The honorable siblings. This is an emergency. What do you mean by that?  He did sexually harass her? I like Sirius Sakura. She's rude. She read about the Lord. She read the Manga's on Hitachi. He's like a little baby here, man. Look at his baby. I don't hate Sasuke.  I just love that I've switched completely on Sakura. Even though she just said it. Yes. Nope. Lie to her. Look at Naruto's reaction. We all know everything now. No more secrets back in the 80s when this happens. Sasuke really think he was about to do something there. But that pisses me off thinking about it. They're good old days. Then they're really going back. We reacted to this like last year. Sasuke's body is the purpose. Yeah. He's after his cock. Six months. She knows everything in those books. Okay. I got to look at shadows, bro. You know what? I don't mind her saying Sasuke right now. What makes sense? She's more angry. She's not a little girl anymore. After that, Itachi. She's more angry now. I love it. She's doing a Sasuke goon and Naruto goon. Yes.  You know what? I'm a Sakura fanboy now.  I like grown up one. That was a weird sentence. You know what I mean. Look at this. Fuck. What is he meeting up with him? My dude was just walking. He says he's going for a walk. What a walk that is. Is this the infinity castle? This guy died? Oh, he's going to sleep. Look, it's a twin. Oh, he's going to talk to the siblings. The old siblings. That's a girl.  Not another big-ass door. Oh my God. So you're big on Ichan and big on Ishii. Wait, are you trying to wake her up? I was wondering. Oh, yeah. He's dead. Maybe this is Naruto in the future. Time jumps. Hear me out. No, don't hear me out.  All right.  Uh-oh. Baki's here to deal. I need your help. Well, we need your help. You really have to go through hell to get here. How did he eat? Who takes care of him? So they're supposed to be on a high shelf. They're referring themselves. He's leaving at the Gen Z. He's like, I don't have any thought in this. Gara's grandma. Oh. Oh, the red sun.  Granny Chiyo.  You know what?  I trust them. I trust the elders, bro. I trust them. They're going to be badass. I want to see Chiyo in action. What's the guy's name? Chiyo. What happened to him? This is our Japanese lesson of the day. We're done. An MPC gathering. Walk the other way. You never see that walk in the halls. Who are they? It's a Bezo and Chiyo, bro. Come on. Who is that?  That tells me all I need to know about his character. So they're going to revive him.  It's insane. I always thought he was fat. He is, he is abs. Imaginating check his blood. What's that?  Speak it through experience. Usually he wouldn't do this. I like that.  Here they go. Satsuri. She said his name out loud. He hates waiting too. Who do you think you've been eating for so long? Yours! This is each other's voice. That's right. Oh, Satsuri's voice. How do you say his name again? Daidara? Daidara? It's not Daidara. Daidara. She's like a witch. Yeah, Daidara. That was satisfying. What is this old woman doing? Wait, spit in his face. I think we need an exorcist, guys. A nen exorcist. Making fun of the younger generation. I love it. I want to see this guy fight. He's the top of the whole town. I love her! She's talking about Gen Z right now. Reflective of our society. God, he's dying inside. This guy can't stop moving, bro. His eyes are shut. He's in like paralysis. Yes. Naruto is hiding in the trees. I knew it. I know he's in the tree.  He has to be different.  I did not even make it to dawn tomorrow.  What is the Great War War World War 2? Please please bring it Nice They were already three all right, so we're before how about that come on Maybe a bird could pick her up that slug a girl She's seen so not his slug And old woman's thinking about me right now. Oh my god No, then a 106 bro. That's a thousand and six.  Oh, thank God. I thought she was gonna separate. I don't know why they could have bring your eye What was he doing?  I think it explosions better happen. I know those fingers Three two one.  Oh, he's an earth vendor. This is their hideout.  Is that like a living thing or is it they're showing up they built a monument wait Is that I feel like we've seen this before in a flashback. What's it called? Wait? Didn't we see it in the first episode of Naruto? I'm thinking of something.  Oh my god. Thank god.  From now it'll take three days at three nights six From now we'll have to wait for people to come. There's basically what they just said Wait, no three days and three nights. That's three days What is he a Venus flytrap? Is that the shark? Who is he? I know that man. I know yes shark man and and atachi Spirit he could do it with a smart Why I bet y'all remember The same order. I already forgot the order. Who is that man? It looks so cool.    You know what man? He's like naruto's age when he started isn't he you remember when naruto was able to do Maybe he has a beast within him.  I just realized that Oh, thank god, this is the wrong room Why are they standing there waiting anyways? We're gonna see them growing up. Wait a minute He looks the same.    She already has more screen time than the original A girl is COVID in it around here. I mean in one day Let's make it half a day. I thought it was three days. Half a day. How about half a day? Hey So now did she go with them look they're already there it's like over New York to Pennsylvania, bro You're close It's good seeing leon shape now with a crutch or a wheelchair I thought he was doomed for life, bro. I'm so happy about that now.    There's something more with these two She's labor or she'd die.  He's gonna say it Nettaka oh I thought it was like their quirk.   He's He has no shame equal rights equals equal fights. Yo Brinkly old man, holy I thought she called him a white something else my son's death by the Oh, she thinks he's someone else Yeah, she thinks he's someone else that's funny. It's not the white fang. That's another keelawa.   She's great. She's killing it. I've turned around completely Hey, what was that about? She looks like a mother right now.   Oh my god. I do it. I knew it. You better be 14 if you said that Good, he's alive Maybe we shouldn't hate the leap village All right, we got this Oh, she's in the drama scene now.    Hell in heaven transition in time ready No, it to the waiting room.  It looked like sausages And it's up Oh god, it's time off fault.  Maybe it's her daughter Why she smiled like that Dude, what's going on in her head? Can I go in her head?  How could I takamaru the go?  I never thought I'd see his eyes open again He's fine he's back to normal We should have a hospital bed count from now on He's gonna sniff it out. Oh, yes the dog with him I'll go with you. What? I was just having an internal warfare Your puppets are fine puppets are on hospital beds too That was a disturbing transition I should buy a puppet guys or I could be a puppet channel smells hands Great move Yeah, the sand ninjas are terrible.  I knew it.     Yeah, this is the spooky music, bro I forgot this is naruto. I'm like, why are they painting sakura's character development? I hope it keeps developing and she doesn't go downhill again. What's sasuke's here? Oh my god with sasuke's here.  I'm gonna. I'm gonna appreciate her as I can for now Okay, while I still can He's gonna ruin it Keep him out of the show, bro.   That was great.  That was great That that that y'all see right now. I don't care about sasuke in the future.  He has to deal with this One day one eye opened right in transition every time This is going to become the new orochi maru and lord okage thing, bro All those eyes aren't going to open though.  Nei chan, so itsu wo motte hiku no ka? If i'm gonna fight against him. Oh, she's dying. She's dying dying Yeah, why'd I read that? Oh my god. I wasn't prepared for it, man. It looks like the walls an attack Always knees are up. Oh my god.  Oh my god. All right That was a weird shot, man, bro.    Tamari you can stay back. She's coming with us. I thought she was going separately.  Oh, yes Watch another eyes about to open and then we're gonna transition ready Say that the bio one more time Look at grandma running, man I want to run with her. Do you smash grandma? Ask me in 60 years when I'm reacting to the next ball, so Don't worry. You're gonna join the fight in like 10 15 episodes. All right Yeah, keep it up. She hasn't done anything in the series. She wants to slow down Facts What is it pacoon or is an mpc villains?  I don't want a commercial break They want to do this to Naruto too All right, that's the shukaku is shukaku This is it the name of it or is shukaku the name of the spirits.  Oh my god I wonder if she knows Naruto has one like she's just speaking as if she doesn't know but she knows She's just saying it purposely so he hears all this and they all hear it Oh, yeah, tsunami could have the other one. That was sick. Nice lore. It's easier. I'm understanding more and more I got the two beasts. Yeah I can't wait to see gara back in action. Not gara.  It's logic.  Yep All right. Oh, I was wrong all of them are opening.  Thank god. We skipped trick to the end I can't wait to hear their new voices, man.  It's osts, man Yeah, shippuden definitely like increased the legendary osts regular naruto had a good one like really good ones But shippuden's raising the bar I wonder who the weakest member is if it's not kisame. Yes. I mean oh, I miss this so much Let's go.  I don't think lee does It's shark time It's shark week.    Oh, yeah, this is battle music. Let's go man. I'm the venus fly trap Wait, that is gonna go fight them Look at them fighting it in the dark lord's chamber Yeah, pay attention Oh, this is great. We got so many different things happening right now for the one place I don't want to be is the sand village. Fuck. Yeah, let's go How is sakura gonna look at this because that's sasuke's bro Who was that?  I want to see both. I just don't want to see the sand village That's the most boring place to be right now What's guy gonna say How would you not remember a shark? It looks like the freak beasts intelligence Is at the level of a beast too. Oh, I thought he was like implying that guy has something in him too Wait, some soccer finds out. That's brother sasuke. Oh god sasuke koon's coming back. Do not ruin her Let's go Let's go Oh, now she knows. Yeah, she knows now Yeah, sasuke koon's unichan Yeah, that's now don't just say that wait, what's this? I'll learn japanese another time I'll fish dude. I love his voice act kiss on me I love it. I love it Yeah, we got good episodes today bro. Shit.   Look at his feet. Close your eyes, bro. Okay I love you. It is hard It's been a long time since I've been fighting Yeah, bro, she's bought every part He's blinded What if this is recorded is one thing Yeah, do you run away? Be a pussy. Don't do this. Don't do this Okay, what if he traps all of them They've got the limits in this moment of naruto Oh, oh soccer's gonna love hitting naruto with a bat.   Thank god.  Oh, this is awesome. Oh no, Tomasaka What say it's don't blueball me. I want them to say it could it be what? Shit He got his own mukanji. Oh guys try to still figure out who it is I've seen you in an aquarium somewhere guys I'll go you want bro.  They're still there. They're two places. They can't he can't be at full potential right now He's elsewhere Yeah Those are 10 times legs I knew it.  I'll look at you Yeah, I'll take my time not like we're doing anything. Let's complete the sex now. I've been waiting Don't smile this ain't a place to smile One on one, baby I never thought I'd see this guy again. We're gonna see a tachi come on the thoughts next I'm worried man Yeah, I'm waiting for a tachi to laugh. I need a villain laugh from him, but he's not that type of guy Oh god, we got nowhere with that.  I want to see the dynamic action.  What are we doing? He's Yeah, there we go I never thought I'd see him land it hit on a tachi, but that's not even a tachi. That's that's a tachi clone. Yeah That was oh god.  It's time. They're real fights better begin. Meanwhile. What are you doing? That ain't him. That ain't him.  I mean they're getting praise from him 10 times gonna die first Now we can fight without dead weight now that pakun gets ahold of them. You don't want that to happen Under resonating himself He's like our cheerleader right now I'm a hadoa.   It's butachi That's what tachi No, now he's gonna use his clones That me one let's go Did Naruto really believe that that was it like why even be stuck Naruto's biggest fight yet.   It's just gonna sink bubble now. He's just gonna drown Easy it's that easy.  I love it. I want to see his nun chucks Isn't a funny guy still doesn't even know he's fighting Guy's just able to stop in the middle of second Look at that pause man.  No character is given 100% ever.   It's on gear four already now it is blood. Oh my god. Punch it in the nose This should better be resolved by the end of this episode That they're not real animals guys. It's okay if they're abused No, they're not That then's already dying bro. Come on Oh, you don't want to see what he's gonna do Daichi Is the episode gonna end? Please don't end the gate oppressed.   You know what that is Yeah Oh, he's gonna use that Yes, it's gonna end. Please don't end. No, I gotta see it. I gotta see it Yeah, maybe he'll know who he'll know who he is because all the gates are open, right?   I keep calling her temtem. It's temtem I love this song so much, man. I'm gonna be singing us all day now.  This is your potential wy now. We're in the air. Now.  You know that stands, bro just like mr.


Disasters definitely do not know borders, and California has always been there for those in need. Recovery efforts have just started for those affected by the hurricane, but many Californians affected by this summer's wildfires have been at it for several weeks, and we want to remind you of some important deadlines. For Lake and Shassett County residents or businesses affected by the wildfires, the deadline to register for federal disaster assistance is Friday, October 3rd. You can register online at disasterassistance.gov or by visiting one of the Disaster Loan Outreach Centers or by calling 1-800-621-3362. The Lake County Disaster Loan Outreach Center is located at the Tribal Community Center, located at 9460 Main Street in Upper Lake. The Shassett County Disaster Loan Outreach Center is located at the former Kmart at 2685 Hilltop Drive in Reading. Both centers are open Monday through Friday from 9 a.m. to 6 p.m. For Shassett County property owners whose homes were destroyed and wish to participate in the state-coordinated debris removal program, you must turn in your right-of-entry form, or ROE, by September 30th. You can visit ShassettReadingRecovers.org for more information. That's it for this quick look. For all of us here at Cal OES, I'm Rob Mayberry. Thanks for watching.


Hello there, this is Jimmy Powers coming your way with another story from the tumult and the shouting Hi there, this is Jimmy Powers transcribed once again I pick up the tumult and the shouting and open to the chapter headed the game of football an appraisal by Grantland rice and Will continue the narrative in first person I Saw my first game of football on Thanksgiving Day 1892 before I had reached the dignity of long trousers Vanderbilt met her staunch rival Siwani that day and won 12 to nothing I Have been playing Refereeing and covering football ever since in many respects. I grew up with the game I wasn't conscious of football back in 82 when Yale's Walder camp worked out team signals But I was knocking heads as a 10 year old when camp had his big guard Pudge Heffelfinger pulling out and leading interference in 1890 the same year that Eli's McClung Perfected the cutback on wide-breaking plays. I was conscious of watch the ball a camp byword for his crushing defensive lines In 1900 when cross-checking the first mousetrap became fashionable. I was a senior at Vanderbilt I saw the flying wedge as dreamed up by Yale's George Woodruff in 1893 become a murderous mass weapon that had to be outlawed Why I was a pea-green freshman when the six-man line with the center dropped out started the scrambling of defenses Bob Zupke's short spiral snap from center was newsworthy in 1906 as was the legalization of the forward pass Zup was the first to drop back his guards to protect against passes in 1919 the same year John Heisman divided the game into quarters In 1910 I thrilled to the power pop Warner achieved from his single-wing attack and a year later To the deception of pops double-wing prior to world war one Percy Houghton explained to me his conception of floating defensive tackles covering crashing ends and vice versa That was when Houghton first baffled him with his cycle of deceptive plays. I wrote about his will to win Applied psychology with which Houghton primed and rolled his Harvard teams Rockney shock troops were another psychological wrinkle Amazing pass patterns and the unending search for speed on the line where other Rockney moves But now we're into the modern era The point I'm stressing is that after centering much of my life around football much of the game still leaves me bewildered Due to the ingredients courage mental and physical condition Spirit and its terrific body contact which tends to sort the men from the boys football remains one of the great games of all time, but Football has one glaring weakness the game is built largely upon constant rule breaking such as holding Offside backs illegally in motion pass interference and other factors that play a big if illegal part in results The game has four officials who can't see or follow one-third of the rule infractions It is football's big weakness fielding Yoast told me I am certain that there is a penalty that could be called on every play Most of the penalties that take place are not seen or called, but the big point is they shouldn't be made in the first place How many times have you heard? There's a horn on the play that age old bleat that slows the average game Perhaps it slows the game for the spectator, but I've seen at least 50 important games lost or won Because the officials fail to call fouls that were easily detected from the press box high above the field I Found out that I could see what was happening from the press box much better than from any vantage point on the field as an official The official looking from ground level is too often cut off by one of the 22 players The forward pass brought in another official headache on pass interference one of the toughest of decisions to call correctly Football is loaded with fouls which coaches invent such as the fainting act Where time is running out the big excuse that these violations are used by more than 80% of the coaches is probably true It is also completely fallacious Most coaches in their frenzied desire to win at any cost Employ any known or possible act to win the game regardless of its legality for this I blame the majority of coaches not all of them They may all be decent honest people and most of them are but too many are split personalities Jekyll's during the week hides when Saturday's kickoff whistle blows Pressure from alumni and students and criticism from football writers Which doesn't happen too often crowds them into an untenable spot They're all supposed to win when but one team can win they forget that entirely Nothing makes me sore then to have a coach say sure. I did it. I broke the rule, but so does every coach in the country It is like a murderer's defense sure. I killed them, but there are 10,000 killers who do just as bad It has been the idea of too many coaches that the main offense or penalty in breaking a rule was to be caught If you can get away with it fine, but don't get caught. I Don't know of any coach who spends any amount of time in teaching his squad not to hold not to be offside Not to consciously break any rule a golfer who sees his ball move But who doesn't call the penalty is a cheater the player who does the same in football Holds or gets offside and gets away with it is a hero. Can you imagine a big tackle saying that game doesn't count? I held on the play Years ago. I ran across a fine young tackle playing on a glamour professional team. Good work. I said after a particular game Not yet. He said I don't know enough. What do you mean? I said about holding all the older fellows know all the tricks They'll grab you by the pants for just a split second. This throws you off balance, but they never get caught It takes only a split second Do all linemen hold I said Every good one I've played against he said they are trained that way. I'm not too good yet I've been caught three times this season and the coach didn't like that 45 yards. It cost us Coaches forget that a holding penalty an offside or some other penalty may offset an 80 yard run or a touchdown effort They should be the most ethical sports directors. We have they are playing a game full of dynamite on the side of fouls Players should be thoroughly trained in not breaking the rules While many coaches may be ethical a great many still follow the old slogan of winning at any cost No matter what rules are involved when a coach has a bad team. He will stay jokingly. I'm building character this year There is no place for a joke in this situation a coach that isn't building character should be fired No matter if he wins every game He is doing far more harm than good if football isn't character building. It is no game to be played Football is a peculiar game featuring 22 contestants on the same field Unusually keyed up and ready for mayhem. It is a tough game to control We have no special quarrel with the over anxious player who is offside or who holds an opponent But there are entirely too many foul moves that are deliberate. There are too many foul actions that lead to injuries Any number of leading stars have told me there is no excuse for excessive roughness for the deliberate foul tactics So often employed this goes for both college and pro especially pro I can't see any reason for so much illegal and unnecessary roughness Otto Graham one of the game's best tells Tim Cohane one of the game's soundest critics Football one of the greatest games can be made greater only if it's cleaned up and protected It has taken more punishment than boxing has and boxing on the average doesn't deserve to be mentioned with any decent sport comparatively speaking Football is in an entirely different setting It has practically none of the thugs crooks cheaters bums and chisels that boxing knows to a large degree Most of the people connected with football college and pro are decent citizens their mistakes are not connected with boxing's Navery they are merely connected with football's frenzy to win regardless of hiring players Recruiting stars even regardless of the rules they play by football must change its ways in this respect Did you ever hear of any scandal connected with Newt Rockney and the four horsemen with red grains the galloping ghost? I will stand for the fierce and continued spirit of Notre Dame teams They have led the list through the years Spirit is the most vital of all football factors They got this from the fathers at Notre Dame and from Newt Rockney. It can't and won't be destroyed But such teams as Notre Dame, Michigan Yale Princeton Southern, California, Tennessee Georgia Tech, Oklahoma, Duke, Texas and the others must see to it that football is played in the spirit of the rules that it is kept Clean from hypocrisy and dirt and placed on a high level of decency in every way Otherwise football will pass and be forgotten The keenness to win the will to win the desire to win is important in football I'll admit I have hammered on these points for over 40 years without making much of a dent the desire to win Even illegally is too great, but if big changes critical changes are not made soon Football will die through its unwillingness to face up to its greatest mistake Now this is Jimmy Powers transcribe saying that's all for now But I'll be back again real soon with another Grantland rice story from the tumult and the shouting until then so long


that this itself is the most beautiful thing possible. This is the most beautiful thing possible for creation to create where we can feel the illusion of that separation and play and all be that and feel that and experience it through each other through the interconnectedness of all. This may be nothing possibly more beautiful than this. It's maybe the only impossible. It may be the only impossible. Nothing else being impossible except something being more beautiful than creation, than what this is.


It's CursePipe. My friends call me Big C. I'm back in action today. I am back in Suno AI version 3. Gonna show you how to create full songs just like this. You'll see here I've got Bulldog Groove. This says here right beside it, full song. And if you go up a little further, I think I have another one here somewhere. Maybe I don't. There's one, another one. Bulldog Groove. The second one. So there you go. I've got two versions of the same song. Let me show you how to do this. Alright, so of course once you've logged in, your first step is you just want to go over here to the left side, click on create. And then I'm actually going to turn custom mode on. And I'm just going to go ahead and enter in a description. So in this case, I've got an electronic high energy, futuristic song about a French Bulldog that just sends it. He always sends it every time. There you go. I have instrumental turned off. This is going to have lyrics. And then I'm going to click on create. This should use up, I believe, 10 credits, 20 credits because I'm generating two versions of it. When these are done, I'll come back and I'll show you how to connect them and create the full song. Alright, welcome back. So you'll see here that it's gone ahead and created two new audio and videos, actually. And it's called Send It Frenchy. Now if I listen to it, let's listen to the top one here. Okay, you know, not great, not bad, but whatever. Hey, I'm showing you a technique. The next step here is click on these three dots or the ellipses. I'm going to left click on that. And then you're going to see here you're going to get the option to continue from this song. Let's click on that. And then on the left side, you're going to see here that it's loaded up and it's got custom mode open. But if we go down a little bit here, you'll see here that it says continue from a minute 40. This is what we want. So I'm going to go ahead and make sure that this is correct. So the first version was a minute 40. Now I'm going to go ahead and click on continue and then watch this. It's going to go ahead and create two part twos. And you'll know they're part two because it says part two right here.  All right. So it has generated two second parts to the original audio and video. Now what you want to do now and you can click on these three dots or you can click on the three dots up here. But what you do is click on the three dots and then you're going to see the option to get the whole song. When you click on that, what it does is you'll see here it's become full song and it's now combining it together into one song. So I'll come back when this is done. We'll listen to it and then that will call it a day. All right. So it has cooked it up. Let's go ahead and click on full song. When I do that, you'll see here that it's gone ahead and shown me the entire song verse one, verse two, chorus, verse, verse, chorus. And if I want to listen to it, there it is. That's how you create full songs using Suno AI version three. Thanks for watching.