Svaj zelo, da jaz sem počutila, kaj smo odložili jasnjev. Vse smo pripravili, kako zaprejamo, kaj evovačne prizavno. We have a hypersurface flowing by in curvature flow, which is closed with positive in curvature. Zdaj je pravda na vse eta. Zdaj se vse eta. Tako, da vse vse skorbeče zelo je odličen. In za vse, zelo sem izgleda prvom, da je nrv nrva n.2. Vse je vse, da je odpojevačno izgleda uniformne obrine na ampullivne funkcije, kaj je to počet. OK, da sem... ...zelo v dete, da je... ...zato vse, da smo je zelo vse... ...zato, da je vse... ...zato vse. ...zato vse. ...zato vse. have you noticed, that if f is positive if f is positive at some point and if a certain pointin time is positive this means that in 2-dimension, A squared minus H squared is minus 2 the product a of the 2 curvatures minus two, the product of the two curvatures, and then we also have minus eta h square is greater than zero. So this is negative, this means that this is positive. So the product of lambda one and lambda two must be negative, since the sum is the mean curvature, which is positive, this implies that lambda one is negative, lambda two is positive, it is also greater than minus lambda one, but we also have that lambda one cannot be too close to zero, must be negative away from zero by an amount, which is comparable to eta. There is an important point, which I forgot to mention yesterday until the question that came at the end, that is, if we have positive h at the beginning, then as I told you at the end by answering one question, there is a uniform control between a square and h square. So there exists c zero such that a square is less than or equal to c zero h square for all times. Actually, this bound is invariant under the flow, so the c zero, which holds on the initial value, gives an estimate, which also holds at later times. So using this, we can say that the lambda one must be large enough, more precisely, what can we say? We can say that minus two lambda one, lambda two, is greater than or equal to eta h square, but h square is greater than a square. And a square is the lambda one square plus lambda two square, so we also have this. And then this means that minus lambda one is greater than over two c zero, lambda two. Well, if lambda, we are at a point where lambda one is negative, so lambda two is greater than h at this point. So this means that we have a kind of an estimate which reminds the pinching that we had in the convex case. That is, when we study convex hyper surfaces, as in we can first result, all curvatures satisfy an estimate of this form with a plus, so lambda one is greater than a constant times h. Here we are, the point is that we are considering surfaces which are not necessarily convex, so lambda one can vanish, can become negative, but we choose this function in such a way that at the point where we work, we gain a little pinching which depends on eta, so it will not be uniform in eta, all the constants that appear in the proof, but this is okay, because the statement also gives a constant which depends on eta. This shows that this constant will become larger and larger as eta is small, but this is perfectly okay. So in particular, recall that there was this tensor which appears in the evolution equations, and it can be proved, so this is not trivial, but it is a relatively short calculation that is in whiskey and first paper, so in general in n dimension would be greater than this. Here we only have one of these components, so this is just this, and then at points where f is positive, so lambda one is greater than this, so this is greater than eta squared plus c0 squared h squared greater than h squared, so this is an estimate we used yesterday to derive LP bounds on this function f. Recall, what was the last estimate of yesterday, which was the derivative of this, let me look back. So this is greater than or equal to something quadratic in p. When we have these terms, c is a suitable constant depending only on the initial value, so that c0, which appears there, sorry, which exponent? f is 2, and this is what I wrote yesterday, but if you follow the proof, you realize that it's not true written in this form, because, I read it back in a moment, because this estimate holds where f is positive, so this would not be true for also the general power of a negative function, which will be defined in general, but this is actually, so my argument works for the positive part of f, so I have to put a plus here, f plus means the positive part of f. If p is, let's say, greater than 2, then f plus to the p is c2. The positive power smooths the corner, which is at 0 for a function like this, so we do not need to interpret this in a weak form. If p is going to be very large, so this is a function which has all the derivatives, which appear here, so we have this estimate on the positive part of p, of f, and now the point is to show that this term is less than this other two for suitable choices of p and sigma. So, philosophically, it's like an estimate for the general inequality. We want to show that something without derivatives on a closed manifold can be bounded by something with derivatives, but the point is actually not, it's not a matter of general inequalities on Poincare type, but comes from a geometric fact, so comes from specific properties in the objects we are looking. And the way Quiscan manages fact that this was one of the key ideas in his first paper was to somehow combine terms without derivatives with terms with derivatives starting from the Simon's identity. So, recall Simon's identity, which says that so one of the form of the identity is this one. The laplation of a full second fundamental form is equal to this expression. Basically, this expression is commutation, so you compare the plus, which is the trace of the hash of something without trace, so you put the trace on the tensor or on the derivatives, and you somehow commute derivatives so some curvature terms appear in the Gauss relations for the curvature tensor. So this is something which contains derivatives and zero-order term, so the hope is that if we integrate on the surface, we obtain an equality relating zero-order terms with derivatives. So the idea is so it's a long computation but it's rather straightforward, so I just sketch the main steps. So write the Laplace of our function f. Our function f contains also a square in the numerator. So we replace Laplace square in the expression of Laplace f by this expression here using Simons. So we obtain Laplace f equals something. Then we multiply the two members of this equality by this expression f plus over p times divided by h to the sigma and then we integrate over empty. So it's a long computation but so basically what do we have here? Two terms with two derivatives. So except for the ones that come from here. So let us call this expression z, so it's the only expression without derivatives. So the point is that so I single out the term with z here. Recall so f contains Laplace f contains Laplace a square over h to minus sigma.  So what we obtain is a term like this is equal to stuff with derivatives. So in all these terms so something like that with square of a gradient or you have second derivatives like here or like here. So where you have second derivatives you integrate by parts in order to find again product of two first derivatives and where you have this product use Schwarz inequality to say that the product of two derivatives is less than the square of the first one plus the square of the second one. So by using integration by parts and standard computations you find that this is less than something with gradient f square plus something with gradient h square plus something with gradient a square but yeah gradient a square can also be somehow turned in some gradient f so this can be you can get rid of these terms and therefore you are left with something which we can estimate in principle of course I'm skipping the details so things are technically more complicated than I'm saying now but so what's the use of this I have that this expression can be estimated by terms here while I would like this expression to be estimated so my question is what's the relation of this and this so I want this to be larger than the one there so you see that we have a factor f plus over p in both cases so what we need to show that z is z over h square greater than equal to some constant times a square this was true so a similar step was in Wisconsin paper on convex surface so let's see how things are in our case so one can compute for when we have only two curvatures z is equal to lambda one lambda two times the product times the square of the difference so you see that so the inequality that was in the convex case that does not hold because this means that this is negative if z is equal to if f is greater than zero so when we first saw this we said well it's no problem that z is negative because this argument here we can work the same argument with a negative sign so let's estimate minus z instead of z the same computation goes through because so at the end we have maybe some scalar product where we estimate by the modules so maybe some good term become bad term become good but what we find at the end is again something like this so it's the same if you can prove this inequality but this inequality holds true because this you recall if f is greater than zero then two lambda one lambda two is minus two lambda one lambda two is a square minus h square and this is greater than eta h square so this is in modules in absolute values greater than eta h square lambda two lambda two minus lambda one lambda one is negative at points where f is zero so this is equal to h minus two lambda one lambda one is negative so this is greater than h so this means that minus z is greater than this is greater than eta h square and this is greater than h square so minus zeta over h square is greater than eta h eta h square and h square you know it's greater than eta over c zero h square so this is exactly what we needed and the constant of course will depend on eta is that it's true that this term so has hope to be absorbed by this one so with some computation we can show that this is less than or equal to zero if p is large enough and sigma is smaller than suitable constant times the inverse of square root of p ok so this shows that we have monotonicity of the LP norms and now we need to pass from an LP estimate for large enough p to an infinity estimate also there is some one has to be careful because sigma depends on p so we do not have a fixed function whose LP norm is monotone for every large p but we have to adjust sigma in order to have something monotone so the thing is delicate but so now there comes the most technical part of the proof but the final part is really was already done in the first paper by Whisk one uses to pass from LP bound, L infinity bound one uses iteration technique there are various iteration techniques and integral estimates due to the Georgi, Moser but the one Whisk was using in his first paper is basically to Stampakia crucial point in this procedure is the use of a sobolefin equality on manifolds due to Michael and Simon and there are interpolation for LP spaces and to just to give you a small flavor of the technique one studies the trankated function which is a typical technique by Stampakia, one defines given positive number k, one defines vk as the maximum of our function f minus k and zero so you only turn down your function by a so you only look at your function where it is greater than some value k and this becomes your zero level so what happens below you don't care, you only see what happens above the idea is showing that f is bounded is equivalent to saying that this vk is identically zero, if k is large enough and you call a k t the set default where vk is greater than zero, so where our function is greater than k and the final step of this iteration technique that I'm not going to say more than this shows that for suitable values of p and sigma one finds this relation that the suitable large pair of positive numbers h greater than k, you can compare the measure throughout all the life of our hypersurface of this sets and we have this that so capital T is the singular time so you integrate over the time interval where the solution exists the area of the sets this is the set with h, so with a larger value and you can see that one can prove that this is less than some constant times the same times the same object for the lower value but this time there is an exponent gamma for a suitable gamma minus one and the inequalities are common in this iteration techniques there is an elementary lem by Stampakia which shows that if we consider this as a function of a real value function evaluated in k and h Stampakia show that this inequality implies that this function becomes zero in finite time has to decay so fast that it has to reach zero for a finite value there exists some k bar k such that is equal to zero but so this means that f is empty for every t which means that f is greater than or equal to k empty for every t and as I was telling you yesterday this is the conclusion because if f is bounded from above then this implies the convexity estimate in this case ok, so that part is if you read the papers quite technical so some people working in this area usually like to find alternative proof if possible which avoid this part but while it is technical on the other hand it's like a black box where you can use you know that when you have some ingredients some estimates to start with you can apply basically the same proof every time so once you understand this you can apply this with little changes and in fact although the original results have found alternative proofs you see again and again these papers which use this integral iteration technique to find estimates from above on suitable quantities because there are new problems where you see that this is a useful technique so this is somehow the simpler case where n is equal to 2 and let me give you just a brief sketch what do you do for higher dimension what if n is greater than 2 the function we have just used with a square and h square is not enough one can make the same trick but you would not find convexity you would just find that the scalar curvature becomes asymptotically non-negative but this does not imply convexity then what you use is what we did in the original proof we considered the elementary symmetry polynomials which are the product of different curvatures in particular n is equal to h as n is equal to Gauss curvature and these polynomials have many important properties for instance all curvatures are positive if and only if all symmetric polynomials are positive k from 1 to n so to prove the convexity estimate for general n we want to prove that sk, so for every eta there exists c eta such that sk is greater than this quantity c k k equal 1 sk so the mean curvature which is positive we want to show that the other ones are not necessarily positive but satisfy an estimate like this from below and we do this by induction prove that sk is greater than minus eta h, so k equal 1 this is true with 0 k equal 2 this becomes h square and it's basically the proof that we have already done and to pass to continue the induction up to k equal to n we use the function like this and this is something skin invariant up to this h to the sigma and with a minus because we want to prove that this is less than some constant so it's analogous to what we did before so prove that that f is bounded from above and the good the reason for using this polynomial is that this expression is a concave function of lambda i this property was well known some people had studied before elliptic equation involving these terms these terms evaluated in the of some unknown function so there were works by trudinger or by kaferelli using those functions so those properties were well known and this concavity is crucial to yield properties similar to the one we have exploited in the proof of the n equal to case but there is a problem that in the induction step we don't show that the case polynomial is positive so we just bound its negative part so this denominator can vanish so if I write it in this way this is not well defined so the real definition is some perturbed quantities so sk are evaluated in some perturbed eigenvalues lambda i tilde which are the real ones plus some perturbation I'm cheating here a bit this is not the same eta of the estimate we have to prove some other small value but related to this eta so we somehow the induction step the fact that sk minus one satisfies the corresponding estimate shows that sk minus one is to be in positive so if we increase a bit so with a small h eta prime and with a big c eta prime then sk minus one becomes positive because of the previous step so this function is well defined since we have done the perturbation there will be some additional term in the equation that we will have to handle but this can be estimated by the fact that what we are adding is something plus times a small constant plus something of lower order in the curvature and we are only going to prove estimates which become significant when the curvature is large so we can use a similar technique there have been more recently simple proof of this property so there is a so the proof by Hasselhofer and Kleiner which uses some shorter but less direct argument based on the non-collapsing property and by using similar ideas but so it's basically possible to prove convexity without induction so in a single blow there is for instance a paper by Matt Langford appeared recently on calculus of variation called general pinching principle so we looked for this function somehow by making guess what function could be which has good properties but it's possible to work in a more abstract way in order to prove these properties I want a certain function of the eigenvalues which has some properties which is concave which is positive and a certain set negative in some other set so I can construct such a function using the distance function in the space of matrices and this way rather than using the specific properties of this function one can work more abstractly and find the result in a shorter way ok, so this was my sketch of the proof of the convexity estimates so what's the conclusion for the analysis of singularities this is something that Gerard has already mentioned in his lectures but I can see it in more detail now so classifications classification of blow up limits is the procedure that Gerard has described what he called the second procedure that we consider a family of rescaled flow you consider a suitable function of points in space and time approaching a singular time you take suitably these points such that they maximize the curvature for previous time and possibly also compare with some later times so you make parabolic rescaling of the flow so you obtain a family of rescaled flow which has uniformly bounded curvature and which converges to an ancient solution so by rescaling family points such that a square of tk tk goes to infinity tk of course goes to t so this classification I stress that it's confined to the case of mean convection then there is a limit m tilde t which for type 1 is an ancient solution so t in minus infinity so t0 for type 2 is an eternal solution so type 1 you know already by monotonicity formula implies that the mt is m tilde t is a homothetic and using positive mean curvature you see that m tilde t can only be cylinder so I should say a family of sand with radius going to 0 cylinder sk times rn minus k or this abreschlanger type abreschlanger are curves in the plane with the self intersection which shrink homothetically so if you take the product but they only exist in one dimension so it's something like this so this was already said by but the case of type 2 the monotonicity formula does not give information because the blowup rate of the curvature is too large for type 2 so what can we say we can say that convexity estimates imply that m tilde t is convex this does not have to do with type 2 this is true in both cases but in the other case you already know we already knew that it was convex without a convexity estimate but now we explain this property I underline convex in this case does not mean a necessary strictly convex you see for instance you can get cylinders then there is a sort of strong maximum principle by Hamilton you know that convexity is an invariant property because the second fundamental form satisfies maximum principle for tensors so if it starts positive it remains positive so for scalar functions you know that scalar function with this property either is strictly positive all the time or it is identically zero all the times for tensors you have something like so the alternative of being strictly positive all the times is having the same rank all the times and the kernel is a parallel section of the tangent bundle and this implies that there is a splitting so Hamilton strong maximum principle implies that m tilde t can be written as the product of some nk t times rn minus k with this strictly convex the typical example would be this strictly convex times flat factor so we have something strictly convex and eternal and there is this other result by Hamilton if if t is eternal strictly convex and h assumes its maximum at some point of course eternal cannot be compact so it's not compact so the fact that curvature assumes its maximum is not trivial so when nt is translating soliton so hypersurface which up to reparameterization moves by translating like these examples that Gerard told you so does our n tilde satisfy this assumption because this follows from the rescaling procedure so this rescaling is done around points where we have a maximum of the curvature so the rescale function hypersurface will have a maximum at the center of our rescaling so the limit will have a maximum of the curvature so this is okay for us so this means which is a translating soliton translating solution so when we did this result it was not yet clear what are the translating solutions so it is easy to see that there is a rotationally symmetric one so in one dimension the only translating soliton is the Grim Reaper curve in higher dimension the question is not easy for a long time it was not known whether all solitons are rotationally symmetric but then there was a paper by Suja Wang who somehow showed that in higher dimension there are many translating solutions but only one is relevant in this case so for a greater than or equal to 2 convex translating solutions are not unique but the only one with which is non-collapsed is rotationally symmetric one called the bowl which looks much like a paraboloid so it is not exactly a paraboloid but it is asymptotic to a paraboloid and so contrasts with the Grim Reaper the Grim Reaper is confined in a strip this opens up more and more so at each point you can find a ball inside with radius compared to the inverse of the curvature for instance the Grim Reaper is collapsed because the curvature here becomes smaller and smaller but the radius of the ball cannot exceed a given value functions you can see that they are non-collapsed so that also here the curvature decreases but since they are opening up you compute that you find enough space to have a sphere inside with radius so the other translating solutions become more narrow in some direction so they become a bit like a product of something like this time something flat and this gives again collapsing so this was proved by basically it was already contained in a paper by Suža Wang and more recently there is some result by Simon Brandle in a more explicit and precise way so this was the classification of the possible profiles in the last lecture I will speak about the surgery procedure we did with Gerard for higher dimension in the class in the remaining minutes I would like to say something more about this result by Hamilton which is a consequence of a very important estimate for the mean curvature flow which is a parallel to another estimate for the Ricci flow which Hamilton called differential inequality differential Harnak in fact his statement that eternal convex has to be translating is a consequence of this because somehow shows that an eternal convex attaining the maximum and at some point must satisfy the equality case in some maximum principle argument so by strong maximum principle has a certain rigidity which implies that it is a translating solution the proof is not easy to say in a few words but I would like to say something about this if you have a PD background you certainly have heard about Harnak inequalities but this name differential may be new to you so Harnak inequality is a standard type of results for elliptic and parabolic equations so for elliptic equations it says that under certain hypothesis positive solutions of elliptic equation in a given domain satisfy some in every compact subset there is some bound between the maximum and the minimum so the maximum cannot be arbitrarily larger than the minimum parabolic equations that are similar Harnak inequalities in a certain complex subdomain where let's say the heat equation or some more general parabolic equation hold you have a bound between the maximum and the minimum but it goes only in one direction in time somehow it says that the minimum at a later time cannot be too smaller than the maximum at previous times and there was a famous paper by Li and Yao which established the connection between some differential inequalities satisfied by solutions of parabolic PDs and classical Harnak inequality basically you have this differential inequality then you use this inequality to estimate the difference of the solution at two different points by integrating along a curve in space time during these two points when you compute the derivative of the solution along this curve you apply this inequality and you find a bound on the possible change of the solution between the two points so Hamilton in his papers call this inequality just differential Harnak inequalities but to explain this background some authors have called them Li, Yao, Hamilton Harnak inequalities with acronym LYHH and maybe I don't have time to say more about this now but maybe I will say some words at the beginning of the lecture of this afternoon let me remind you again that we have switched the order of this afternoon with respect to the original program I will give the lecture at 2 p.m. while Toti Daskalopoulos will give the last lecture at quarter to four so thank you for your attention and I will meet again this afternoon


Hi, Professor Friedman. Again, Department of Economics, University of Massachusetts. We're here today to talk about Prisoners' Dilemmas. These are a lot of fun. And note that in the course syllabus, there's a link to a game conducted on some British TV show. That's a Prisoner's Dilemma. Check it out. It's really cool. Okay. Why do economists talk about games? You know, we're not the athletic department. When we talk about games, we mean social interactions, strategic interactions, with what happens to you depends on what others do. And you know this, and they know this. So you choose a strategy based on what you think others are going to do. And they choose a strategy based on what you are going to do. So we're moving a little away from the neoclassical or the orthodox world where Robinson Crusoe stuck on his desert island. Now there's Robinson Crusoe and Roberta Crusoe or something. Two people. And they're both thinking about how to do the best for themselves given what the other person's going to do. You've already been in this game. Some of you may be first year students. Others in college. Others, you know, remember being in high school. Senior year in high school in Massachusetts, people are supposed to drive to school and not take the bus. I found this out when my older daughter was a junior. And at the end of the year, she asked me, are you getting me a car? I said, no way! Why would we do that? Haven't you ever heard of global warming? And she said, well, how am I going to get to school? I said, the way you always have. On the bus. She announced to me, seniors don't take the bus. I took this information to my class and they were very upset that I wouldn't get her a car. They told me I was going to ruin her social life if I made her take the bus to school. I figured it out, but think about it. You drive to school. Your friends are thinking, what are they going to do? Are they going to drive to school or not drive to school? You want to drive and you want nobody else to drive because your favorite situation is where you're driving, you're cool, you can park easily, you don't have much traffic and nobody else is driving which makes you extra cool.  There's another possibility which is nobody drives and you all take the bus and it's like, well, okay, at least there's no congestion. And the worst possibility of all is you all drive. Nobody's cool because everybody's driving, everybody has to get a job after school to pay for the car. There's lots of congestion and you actually leave the house earlier than if you took the bus because of all, because you can't park anywhere near the building. Okay, you could put this into a table.  You take the bus, your friend drives, you're in a box over here, where? She's cool, you're miserable. Or everybody takes the bus, you're in a box down here and you just live with it. This is the same situation that Greek philosopher Sakretis faced in one of his dialogues he talks about, how he was in this battle. And he sat there thinking, hmm, if we win, nobody will care what I do because we'll have won. But if I fight, I risk and kill. If I run away and we win, fine. If I run away and everybody else runs away, we get slaughtered. If I fight and my friends run away, then I get killed. Prisoner's dilemma. Same situation that happens with bad guys. Two thieves captured by the police. The police didn't see them do it. Police have some evidence. Put them in separate cells. You've seen this on Law and Order and other police shows. You go into one bad guy in a cell, you offer them a deal. Rat on your friend and you'll walk. Your friend gets nailed. What do you do? Do you rat? Or do you keep quiet? If you all keep quiet, you'll be okay. If you rat and your friend keeps quiet, your friend goes to jail for a long time and you walk away. The problem is your friend's thinking the same thing. So what do you both do?  Worst situation possible, just like you all driving to school, or everybody fleeing from the battle. You all act on your best interests thinking about what the other person's going to do and you all end up worse off. Prisoner's dilemma is also about good guys.  You get this escalating war where everybody's trying to outdo the other, get a higher status activity. Prisoner's dilemmas undermine the idea that individual action can lead to a social optimum. The social optimum may be you and your friends all get together and set standards for the prom dresses, for the prom vans, for how much money you're going to spend on corsages for your friends, and things like that. All get together, collectively govern these things. Left to their own devices, the prisoner's dilemma and game theory indicates a situation where people's individual choices can lead to the worst situation possible. If you have any doubts about that, think about the little island nation of Tuvalu, which is sinking under the rising seas because so many Americans drive their cars to school. Thank you.


Dear students, in this module, we are going to discuss the psychological theories of crime and deviant behavior. Is it something that has to do with our brain that triggers, that instigates, or that motivates us for deviant behavior? Psychological theories suggest that criminal behavior is the result of mental, emotional or personality disorders. So in other words, it has nothing to do with our external socialization, but rather it's more important that we should look into or look inside the brain and try to find out the reasons of committing crime or reasons of committing the deviancy. So very famous psychologist Sigmund Freud, psychoanalytic theory proposed that criminal behavior is the result of unresolved conflicts in the unconscious mind. It is not something that we are deliberately committing, rather it's our unconscious mind that is motivating us towards the criminal or antisocial behavior. Similarly, social learning theory suggests that individuals learn criminal behavior through observation and imitation of others. So these mental processes are instigated by these external factors, however, this mind becomes the ultimate source of committing this deviant behavior. In Pakistan, some research has linked the high levels of poverty and social inequality to the increased risk of psychological disorders and thereby the criminal behavior. So perhaps you would have heard the news about people who are committing suicide or killing, even killing their children due to the poverty or due to the lack of resources or due to the loss of unemployment. So these kinds of psychological disorders, these kinds of stresses are becoming more and more prevalent in Pakistani society because the more triggering factors, although they are external factors, however, they have a lot more significant impact on our psychological behavior.


Oh man just another day well hello welcome back to the vlog glad you're here today I'm taking you on a little behind-the-scenes action we're at 6 8 we're at 6 0 8 a.m. that's my brain is not fired yet because I have not had coffee you know how we like to start off a Monday right there boom with the chick it's not a day I typically film got a lot going on doing some work with the Guggen squad and I'm going to pick up one of our camera guys right now and we're gonna head up to the lake to go meet John here a little bit but we just cannot start today without strict play so I'm gonna get to play for for all the boys before we get started started off right no hmm get to go now if you guys have never downloaded the Chick-fil-a app let me just introduce you to awesomeness right there it just pops up every once a while says hey guess what we like you today here's a free sandwich now that I have kids I'm gonna be up at that place all the time you know to go to the playground probably just gonna load up on some nuggets though okay we have fuel now it's time to add the fire good morning yeah I'm doing a little behind-the-scenes today these fine gentlemen I hope you have some warm clothes that's warm as it gets in Florida let's check on let's check out old gear real quick look at that Christmas tree hey Gary all the gills are looking shiesty Gary's looking fine Arowana doing his deal and there's his buddy catfish is growing right there he's in deeps in the darkness y'all ready to roll I got Chick-fil-a I got coffee already life is excellent yes take care of life on Monday West raid bring a fire the fuzz out the fire oh you're gonna definitely need that fuzz today fuzz what I think does good in high winds though just rolled up to the ramp had to add some layers oh this is a cold one this is a really cold one John just got here with lucky already gonna make some movie magic I got a good white bass hole I do no John's backing in the weeds over there what's up oh yeah I forgot I'm with I'm with the man you guys don't know Wes he's basically the senior director of photography executive producer and hashtag is good buddy squad here you do make man doesn't matter you can take it an iPhone I wasn't active for that I hear I'm just tell them the truth is all John's weapon oh man just another day we got to try to find some fish we're doing we're making like three videos today and it's hard to do it when the fish aren't like hopefully we got we trigger the strikes no idea what John's even doing yeah but that is some back meat just let the mondo go oh yeah you eat skin off where it was gonna try some eddy rays first time sauce I eat the whole skin on it oh yeah you just put in your mouth give it a go is it frozen still no perfect okay everybody loved him Eddie made some people think I'm sponsored by I'm not I just love this is so glad dude yeah I think next spring we're gonna have just tons of these in the boat with us y'all we just made we made fire juice fire juice big ones sniffing ooh actually we had we had a little bit of scripting thanks to Wes he keeps me on on track but telling you guys he makes all these awesome videos you see on the Guggen channel and there's a lot of them too that that aren't on the Guggen channel and Wes makes that are just fire it's his eyeballs yeah it's one thing to shoot it really is like you can you can be a good shooter but you got to have an eye for like how it's gonna come together and imagination and I like doing that Wes is the man he is the man at that so it's always good always learn stuff from Wes all right we got to go find John we got to try to go catch the white bass now that's our second goal today we nailed the first goal which was to make a fire little promo video got her done now we're gonna eat some deer sticks and go find some white bass just chill white bass and chill put it on a shirt I don't know yeah we're dangling deep y'all we're winning today these are dub days these are dub days right here probably got like eight eight white bass in the box right now this is what I'm doing see right there see that bam right off the bottom there's actually fish on it oh huh oh yeah yeah dang oh I had Wes all bottom bottom sometimes I like it when he's just sitting throwing a little blade bait literally just kind of hovering it over these small schools white bass there's nothing big about them the white bass are big but the schools aren't big feeding on little pods of shad I love doing this 23 feet water John kind of was he was comparing it to the ice fishing look at these fish right here I'm about to get smoked smoked biggest group so far biggest group so far John biggest group it's candy it's like taking candy from a baby please get in here I'm telling you oh they're moving through quick come on now we're doing big things I'm talking there was probably a dozen in that one they were moving they were like 10 foot all the way down to 23 foot on the bottom half my bites have been just what I'm like looking at the graph and it's sitting there like a little kicker yet some of them have just tickled it any day soon as the camera turns on it's like oh please excuse me I'm so sorry what is going on it's like that big group came in and the group of spotted bass maybe oh oh oh all the way up oh ah Western champion I'm just wanting to get one for you you're gonna catch one big ball bait coming in I'd like to do this for pike oh areas sitting still oh here we go oh here we go yeah I'm serious this could be a big spot or something dang it that was a good one back up how big it was a three-pounder no yes go just hammered it oh you never know this this is why I like doing this this time of year everything kind of huddles around these creek channels out deep around points and everything so you could literally catch crappie white bass largemouth catfish it's alright it's fun yes put them in he didn't know I had five-foot run on my boat I sleep done well that's a wrap for fishing day on the water fantastic day caught a few larges I actually end up catching one on one of the MTV Bates it's like a deep dive it's a blade bait look it's a blade on a blade I hooked into a decent size three pound large mouth on that and of course you know caught up caught a toad caught him on now it is time to go throw some white bass into the grease y'all one of my favorite things to do I love catching white bass and crappie and put them in some grease stay greasy what yeah oh sick yeah I have your keys to put all the trouble tell us to keep coming keep coming west very successful eating sesh here y'all something to head back to the crib though right I gotta let you go let me go yeah gonna let you go like a sweet release peace out guys had fun today I did to it was a good dangle your good chef thank you I'll give you that thank you very much see it's not just Stephanie all right see you later man John good dangle today said good dangle all right take care peace peace peace on the streets totally dark you guys can't see it's time to go back to the cave I got a check on my wood see how it's doing is looking good y'all next day right here got one more coat to put on put on my table and that video is going up soon for you guys by the way I woke up this morning to find a samurai sword in my boat I guess John forgot to take it out last night I don't know I don't know it was literally like sitting right here on the front deck as I came out to my boat this morning we're about to totally switch gears from fishing and go to the archery range me and John we're thinking about doing a little archery range competition with different kinds of bows and I didn't even know John shot bows maybe doesn't I don't know it's gonna be fun so I think today's video was definitely different not really showing the exactitude of the fishing talk about the fishing just behind the scenes filming and if you guys like it let me know in the comments I normally do not film on the days that I'm filming with the other camera guys just cuz it's another camera more gear more stuff to carry around I do appreciate all the work that Wes and Bryant and all of our guys do and they're very good and I hope you guys enjoy the videos over the Guggen channel that these guys produce so if you like today's format just a simple vlog behind the scenes let me know in the comments down below and I'll be glad to take you along next time if you're unfamiliar with the channel I mostly do outdoor content it's fishing it's hunting it's just enjoying the great outdoors have a great appreciation for it I'm up in business the outdoor industry business I also have a brain tumor inside of my face and I vlog about that sometimes and I'm sure a lot of you have come to this channel for that and anyways everything's good at the moment so I love you guys thanks for subscribing thanks for being here and thank you for all the support if you're doing some holiday shopping for a fish and frig don't forget to stop by at the merch store links down in the description we can pick out some of the new gear help support the channel and the family here at the true house appreciate you and I'm off to make more videos y'all as always make sure you're having a great day blessed day in the outdoors enjoy the freedoms and sights and sounds of nature I certainly do I'll catch you out there on the next one


Hello people of the internet, my name is Johnny and welcome to FNAF Killer Night, a brand new FNAF fan game developed by, well that was a good beat drop there, developed by good old Bonzi, also the creator of Night Stores and the upcoming Deerwood. This is a fan game made in celebration for the 8 year, I think it's the 8 year anniversary of FNAF 3. All I know about this game is that it's apparently very similar to an escape room, which I absolutely love. However, if I do bad, it definitely is going to be very, very embarrassing, because usually I like to think of myself as a pretty smart guy when it comes to escape rooms, but I guess this game is gonna test my limit. Also quickly before we hop into it, thank you so much to Bonzi himself for sending me an early copy of the game before release so I can make a video. So without further ado, let's just hop right into a brand new game. Fazbear's Fright, the horror attraction. Look at that terrifying Freddy mascot costume. Oh, I really hate how the eyes are all hollowed out. Tip, remember to interact with your environments and use your notepad if necessary. Oh boy. Okay, so we got a timer in the top left. Alright, that's how I'm gonna be embarrassed here. Okay, so I got a magnifying glass. I found a crowbar. Maybe this can pry something open. Use spacebar to continue. Oh boy, there's a trash can. You found an old drawing. Maybe this can be hung up somewhere. I didn't quite read what it said. It looks like it had a number and then a triangle. But I've already forgotten what the number was. The door is locked. I'll need to find another way out of this room. Okay, so we can't go through the employee's only door.  What are these? Hello? Um... Ooh. Hehehe. I can draw. And yeah, there we go. Think that just about does it? Anyways, let's get rid of that. Is this my inventory? It is. Okay, so I can hold four items. What is this? I can drag and drop. Can I pry open this vent here? Let's try clicking on it. I'll need a ladder to get up there. Come on. Just reach up there a bit. It's not that high up. There's a closet. And I can't open. Can I use the crowbar? Ooh, here we go. And there's the ladder. Perfect. Can I pick it up? Oh, I gotta exit out. Okay. I found a ladder. Talk about reaching new heights. LaMau XD. Let's put that ladder there. Perfect. And now, we can get right up to this vent. I need something to open this vent if I want to see what's inside. Okay. Hmm, so probably like a screwdriver or something. What's this? I need to find the code to open this lock. Oh, I can change it. Okay, so there's a triangle. So what did the note say? God, if only I could look at this note. Okay. There's more notes out this way. Ooh. This seems important. Okay. Can I put the note on here? Yes. I put the drawing on the pin board. They seem to form a code of some kind. But for what? Well, I know. So one R, rectangle, B, no, that makes no sense. What if the colors match? So number one is a square. I'm assuming these letters mean nothing. So let's go square, pentagon, then triangle, circle. Square, pentagon, triangle, circle. Oh, it was on square. Square, pentagon, triangle. Hey, look at me go. Oh, within the toolbox, I find a screwdriver. Maybe this can open something up. You don't say. Let's hop right up to this vent. Unscrew. Do nothing after. Oh, there we go. I keep getting. I have to click out of the inventory icon. Did I make it out? No. Oh boy. Okay. Draw. What's this? I found a red key card. Looks brand new. Okay. I'm hearing a loud buzzing noise. Door. I need to find a way to open the security door with a key card.  Can I just use this? Oh, that was pretty easy. Hey, sub three and a half minutes. That's not that bad. Oh boy. Here we go. Bonnie's arcade and my timer continues. This is perfect. What's this? I wonder if this key towards us anything. Red, red, red, red. One. No. Okay. So it's not like a Simon says thing. Four reds. Door. I need to find some key to open the door. Okay. Chicken hunt. There seems to be four arcades. Okay. I wonder if they still work. I can try. Oh, chicken hunt. Darn chickens always stealing my pizzas. Time to teach them a lesson. Completely original title owned by Fazbear Entertainment.  Get a hundred points and enjoy your food and peace. Press enter to continue. I don't have to shoot a hundred chickens. Do I? Boom. I have to shoot pretty close to a hundred though. Five. Actually, it's not that bad. Oh my God. Do I have unlimited? Unlimited ammo? I'm going to hope so because I'm just going to... What's stopping me from just doing that? Almost there though. Only like three more, two more. Nice. What did that do? Nothing. Win a prize. A key card. Okay. Does this work? Wackabare. Tired of screaming at spooky brown bears? Wackabare is just the thing you need. I have no clue what these voices are supposed to be. Use your top hat hammer to hit the bears when they come up. And get your sweet revenge. Get a hundred points. All right. Here we go. Oh, that's not at all where my cursor is. Oh, this ought to be real fun, ain't it? Okay. I think I'm starting to get the hang of it. No. Okay. Maybe... Okay. Mouse is a little finicky. Kind of wish the hammer would plop down where my mouse is. The depth perception is just the best, ain't it? Doesn't seem like there's any penalty for missing them. Or just swinging randomly. Here we go. One more. Oh, shoot. I missed them. I keep looking at the score. No. Got him. Sweet. What did that do? It said four arcade machines. I only played two. Erm. Security camera? Nothing. Ooh, a key. I found a small key. I wonder what this could open. Maybe a door. Hold on. Hold on.  What's this? The wires from the arcade room seem to connect to that box. Playing the games must activate the lights on the box. Okay, so I need to find other arcade machines here. Oh, basket bunny. Bonnie's not feeling too good.  Rest the space bar when the arrow is on the green square. Okay, so it's just the basketball game from pizza sim, right? Maybe? Oh. Kind of, but it's like really delayed for some reason. Oh, boy. Why is it so delayed? Hold on. Go. Go. Go. That doesn't seem like that was quite- Oh, is that it? I guess I'm just a master at shooting hoops. And we've got fishing fox. You already get it. Foxy's been skipping lunch for a while now. Why don't you get him something to eat? Follow the sequences of keys that pop up on the screen using WAZ. Don't like this. Let's have a look. Oh, no.  God, I'm always so bad at games like this. This is why I never liked Friday Night Funkin'. A-W-S-D-W. Okay. W-A-A-S-S. All right. That was pretty simple. So does this now give me a pattern? Maybe something in the arcade room could help. Well, it did, but it was just four red sequences, right? Blue? Blue. Yellow? Oh. So yellow, blue, green, red. Yellow, blue, green, red. Because they blinked in accordance to whatever their thing was. So yellow? How do I change it? Uh, whoa. Yellow? What? Whoa. This is being weird. What is going on? What? Huh? Did I just overcomplicate things? I found a red key core. Looks brand new. Okay. Wait, no. Okay. No, I guess that's what I was supposed to do, I guess. Oh, no. I guess I just overcomplicated that puzzle. Chica's Kitchen. Hey, Chica.  There's an oven right here. Nothing on top of the oven. Okay. That's the oven again. I can't look in it. Rules for safety.  LaMau? Good joke. Black! I'm starving.  Can you prepare me a pizza- Why is pizza capitalized? And why is chi- Huh? It's not proper nouns, Chica. I'm sorry, what did you say? Hold on. Need- Repeat myself? Yes, I actually do. Pizza with cheese, meat, olives. Okay, cheese, meat, and olives. I need to find cheese, meat, and some olives. Uh, a key. I found another small key. Maybe it opens up another door. I would assume so. Usually they do. There's a door there. Perfect. Uh, freezer and storage. Let's go in the storage. I need... Onions. I feel like I'm about to cry. I didn't need onions though. Got some not meat. It's meat. Not meat. Okay, but she wanted real meat though. And the freezer, we got some meat and some- I can't see what that quite says. Wait, so I got cheese. I need meat. Okay, that's the only thing I'm missing. So let me go to the freezer. Let's get this meat. I got some meat. It's pretty meaty if you ask me. Okay, I think I have everything. Does she just not want... sauce on it? Cook. Okay, forgetting I need to click out the goddamn inventory. I'm still hungry? With cheese, tomato sauce, onions. Oh wait, this is so much. I can't carry all that. So tomato sauce, onions, pepperoni, which is right here. At least they aren't pepper lonely anymore. I'm assuming the ingredients will stay on the pizza then? I'm gonna hope so. Okay, it does seem like they do. So let's get the mushrooms. God, I've been on this level for a while. Mushrooms, they're very mushy. Chica, if you ask for a third pizza, I swear to God. Yummy, I think there's some room for dessert though. No, I don't think so actually. Meat, olives, not meat, pepperoni, eyeballs, cheese, and onions. Why the hell am I supposed to find eyeballs? Oh, real eyes. I got some eyeballs. What are these doing in here? That's a good question. So I needed eyeballs. Do I need meat? I do need meat. Let me get the meat. And I also need not meat. I got some not meat. It's meat, only not. Perfect, and I think that's everything I can carry. So let's dump these. Oh, that's so disgusting. Onions, pepperoni, and cheese. Perfect, Chica. This is going to be the best pizza you've ever had. And probably your last pizza you'll ever have too. Ta-da! Thank you for the meals. They're the best pizzas I had in a while. That rabbit man doesn't make them right anymore. As thanks, take this key card I had lying around. Appreciate that. Let's find... You didn't give me the... Oh, it's right here. Okay. And now we can get out here. Chica, thank you. See you later. Jesus, 16 minutes. Oh my God. That pizza section was killing me. Oh, and this one looks wonderful. Boxes. Can't interact with those. Hey, Foxy. Yarg, you be looking for the key to Faz Island. That to be washed away within the cabin near the balcony. No worries, matey. I've given you a... I'll give your hint to help you. The year I gave me last bite was the year nobody forgot. I expected it to rhyme and I'm heavily disappointed. Whoa, what the hell's going on here? I need a special kind of key. Okay. Who's hanging up their underwears in Pirate's Cove? What's in this way? Um, one, nine, eight, seven. That was pretty easy. And I found the key. I got the key to Faz Island. Time to set sail. I can't steal any of his doubloons.  Oh, wait, hold on. The whole area. You've got to be trolling. I wonder what lies inside. Before entering the treasure room, you must complete the cave puzzle. I see the cupcake. Find all the hidden objects. Oh, it's like, I spy. Ooh, two shadow cupcakes. Well, I see one. And of course, I can't click on them with the thing open. Here's a shadow cupcake. Um, oh, that was a golden cupcake. I need to find another shadow cupcake. Two mango limbs. That looks like a limb. One puppet mask. Oh, there's the shadow cupcake. Like an actual puppet mask or a Freddy Fazbear. Oh, it resets. That's not bad if they stay in the same place. Yeah, who cares? One top hat. Okay. Um, one spinning desk fan. I see it. One birthday cake. I see that. Hmm, this puppet mask is really stomping me. Oh, it's right here. I found all the items. I wonder what the treasure is. Hopefully something good. Where am I supposed to go? Oh, here. Okay. Ta-da! Within the box was another key card. How many of these are there? That's a good question. I saw it would appear to be a... I'm sorry, did I see something? Or am I being made a fool of? I can't... It seemed like something was there and then it disappeared, but I couldn't make out what the hell it was. Ah, Freddy's Theater. Wonderful. I see a whack-a-bear again. What's this? I found some kind of button. What could this be used for? That's a good question. You can go down here. Oh, hello there. I won't hold you here for long. I used to bring joy to every kid. But that was a long time ago. Do this old bear favor and help me perform one last show. Yes, sir, yes, sir. Ah, spotlights. You can't have a showtime if you can't see it, right? Connect each color-coded wire together to end the task. Oh, it's like among us. Um... Or is it not like... Oh, here we go. No, it is like among us. It's like a mogus. But for some reason, it's really finicky a mogus. Yay. That was easy. What's this? Music. Make sure every note is harmonized. Find the notes that are out of tune. Okay, so the task ends when you've repeated three. So this be just Bonnie's... Jesus Christ. I found it. So this is just Bonnie's help wanted repair minigame. Recycling content, Bonzi. Yeah, no, that doesn't sound too good. Gotta fix that one up. Yay. There we go. That should be the final key. That should be music all set. Perfect. And what's this? Performers. Freddy and the gang are a bit rusty. Let's help them move a bit. Copy the colors. Okay, so once again, just some slime and says... Green. Green. Red. Red. Red. Green. Red. Red. Green. Red. Red. Please be red four times. Not quite. Green. Red. Red. Red. Green. Oh, perfect. What are these? Curtains. Regulate the curtains' movements by pressing the button connected to the last green light. The task ends once you've pressed all the buttons. Okay. So once again, this appears to just be recycled. Wait, what? Was that not right? This? That? Oh, that goes here. That's... Okay, that was easy. Yeah, once again, that was just a Ender's Game from Help Wanton. Nice callbacks, though. Is that everything? Hey, Freddy! I fixed... No, I definitely saw you that time. No, no, no, no, no. You can't fool me. Hey, keycard. Aren't these usually hidden away? What's it doing out here? Good question. What can I do now? Oh, a button. Hey! I found the button! Keycard? Anywhere new? No, you've... They've seen better days, but, um, it's their moment to shine. I'll let them have it. You guys look good up there. Security, who let him up there? Okay, maybe you don't look too hot. Thank you for helping put on one last show, friend. But now you need to get out of here. It is an exit through the backstage you can use, but be quick. It won't be long before he finds you. I love the pronoun game. Time to use my keycard. Hooray! Also, it's not really hidden behind the stage all too good. It was kind of just in the middle of it. Quite an eyesore, actually, with the whole aesthetic of the, uh, rest of the stage. Also, this doesn't look... too inviting. Um, birthday cake? What? What? Oh. I'll need a keycard to get out. Yeah, no, that is usually what that means. Anything in here? Ah, the bathrooms. Employees only. I'm not an employee, but I can get in here. Only four FAS coins. I need to find coins, then, for a key. I found a FAS coin, alright. Big enough to fit a whole person inside. I need a key to get in. Maybe we can get one from the vending machine. None around the table, it seems like. Men's room. This is quite... Hey! I'm sorry, I'll leave! If you're using the bathroom, I should have knocked. I'm sorry. Can you even do with this? No, don't... Oh, don't tell me there's going to be one in the... Oh, no!  Come on! Can I go in the ladies' room? No, respectable. Respectable. Go away! I found a FAS coin in the trash bin. Is it worth the same value? Not quite sure. Is there one in here? Sounds like there should be. I guess not, though. Hey, can you... I'm sorry. I'm sorry if I'm intruding. But please just get out of my way. Okay. How many do I have? Three. I need four. Let's just deposit these for now. But maybe if I shake it enough, one key will just fall out. I don't know. It's just an idea. Sorry. Just trying to find a key. Sorry, just trying to find a key. Don't mind me. Just trying to find... Oh, I found a FAS coin under the top hat.  Okay. Well, I got all of them, though. That's pretty nice. Let's use it. Hey, I got a key from the vending machine. How perfect. Now, let's go in here. Nope. Don't mean to do that. Let me use my goddamn key. Boom. Here we go. Hey, there's a key card. Two evil eyes and a puppet mask. Hmm. Seems like someone is trying to have a pretty happy day out here. Well, too bad it's so sad for them. Why can't I... Aha. Hey! I need to hide. Okay, let me go hide in the... Hide in the men's room. Maybe? No? Go hide in the... In here. No! Okay, hi. That's great. Thank you, thank you, thank you. Oh, shoot. Am I going? Am I going? Am I going? Am I going? Am I going? Am I going? Am I going? Am I going? Am I going? Am I going? Oh, I know I'm going, I'm going. Locker! Good. Maybe if I would breathe a bit quieter, he wouldn't see me. I need to get out of here before that thing comes back. Well, let me... Let me leg it then and just make a run for it. Why can't... Why can't I inspect this? Oh, okay. I never used it. Attention, patrons. Fazbear's fright is entering lockdown mode. We've discovered that our performer suit has been stolen. This is not part of the attraction. Wait. What? Whoa, press it. I'm going to keep pressing the space bar. You won't best me. I am a fast masher of the space bar. I've played so many mashing games with the space bar. I don't know how that helped me. What... But I made it out. Did I just like push him aside and I just ran out as fast as I could? All right. But yeah, I made it. That's great. What was my time? Oh. Fazbear's fright, killer knight. That's the name of the game. Once thought to be just a clean, cheap cash, definitely not clean. A cheap cash grab strategy, get its own horrible history, one dreadful knight. A new local attraction based on the ancient pizza chain closed down overnight. The Scare Dome attraction staff reportedly spotted a figure stealing the, quote, salvage performer suit from the employee's only room. The suit in question was used to scare customers during their time at the attraction. At the time, the terror took a whole new shape. One of the customers confirmed they were being followed and eventually attacked by a figure wearing said suit. While authorities, when authorities searched the building in the footage for clues, everything was gone. This includes the suit and the figure's appearance on the security footage. Was this a ghost doing or was someone trying to hide the evidence? We may and never know. Published March 2nd, 2023 by what appears to be Jamie Madison. I actually have no clue if this is Jamie. Spectro hunt, ghost sightings, SH Origins, equipment books coming soon. Recommended. That's a, that's a dear word. Even in his own game, Bonsie can't help itself promote a bit. I spent a total of 26 minutes at Fazbear's Fright. That seems pretty slow. That seems pretty slow. I'm sure if I redid it, I'd get, ooh. Oh, sweet. I'm sure if I redid it a bit, I could definitely get below 20, maybe even 15 minutes. I feel like I could be pretty quick with it. This was fun. This was a short and sweet game. And I got a star on the menu. And I've unlocked the museum. Salvage. Hello, Salvage. How are you doing, my friendo? Stans. Nice. Concept art. Concept art. Making of. Oh, here's the dastardly fella. Quite the mischievous fella he is. Oh, and he gained his suspenders. Classic. Damn, for free, Bonsie? You're giving those out for free? All right, Ben. Teasers. Oh, this is classic. Look at this. Oh, wow. I didn't even see this one. Sweet. Oh, that was great. This was a pretty sweet, short, simple game. I'll leave it linked down below if you want to go check it out. Maybe I'll do a speed run version of this and see how fast I can beat it. Actually, I might do that now just for the hell of it. Never seen someone match like me. Actually really proud of all. 11 minutes. Oh, I could have gotten some 11. I'm fine though. I am fine. I'm proud of that. I'm proud of that, bro. But that was FNAF Killer Knight. Hopefully you all enjoyed this special fangame video. If you want to go show Bonsie and the team some support, I'll leave the page linked down below. And stay tuned because they've got another FNAF fangame called Deeword coming out in the future. That's going to do it for this video though. Thank you so much for watching and I'll see you all on the flip side. Goodbye.


Here are three holiday party outfit ideas. Option one, go with some black watch tartan trousers, a cozy cashmere turtleneck and some suede loafers for a simple classic holiday look.  Or option three, go formal with some bold tartan trousers, don't forget the cummerbund and a black velvet dinner jacket for a fun, festive and statement making look.


Teaching English in Spain, the Salary and Budget Guide This guide will help you answer the question, How much can I earn and save teaching English in Spain? You'll also find information on the local cost of living in order to figure out how much to budget for when making the move to Spain. The typical salary for English teachers in Spain. Spain is one of the most visited countries in the world and has a large tourism industry. Because of this, the demand for TEFL qualified English language teachers is very high all across the nation. Most teachers find jobs in private language schools, but positions can also be found in public schools through government sponsored programs. You will find most available positions in large cities such as Madrid, Barcelona and Valencia, but opportunities can be found all over the country. The typical salary for English teachers in Spain starts at around €700 per month, rising to €1,800 for higher end positions. How to earn extra cash while teaching English in Spain? Since teacher salaries in Spain aren't among the highest in the world, many teachers supplement their income by taking on private students in their free time. Rates for private tutoring range between €18 and €22 per hour. Getting a work visa in Spain. While it can often be a challenge for teachers from outside the EU to obtain a long-term work visa to teach legally in the country, there is a relatively easy way to teach legally in Spain. The cost of living in Spain. Spain is an incredibly popular destination for teaching English abroad and there is a strong demand for TEFL certified teachers. However, salaries aren't high, which often teachers teachers from moving there. On the plus side, living expenses are usually lower than in some other European destinations, such as Italy or France. Therefore, you can still live comfortably when teaching English in Spain. Cost of living in Spain, food. If you avoid eating in areas catered to foreigners and tourists, you will be able to save a lot of money on food while living in Spain. Shopping at local markets will also help your budget. Milk, 1 litre. €080. Eggs, 12. €160. Apples, 1 kg. €160. Chicken breast, 1 kg. €570. Rice, 1 kg. €1. Bottle of water, 1.5 litres. €060. Bottle of domestic beer, 0.5 litres. €220. Cost of living in Spain. Leisure activities. Spain is a country rich in natural scenery. You can go skiing, hiking, swimming in the ocean, surfing or sampling your way through the country's rich wine culture. There is so much to see and doing people love to enjoy life to the fullest. 3-course mid-range restaurant dinner. €35. Quick restaurant meal. €10. One-month fitness club membership. €35. Movie ticket, international release. €8. Cost of living in Spain. Transportation. Most large cities in Spain are equipped with a well-connected subway system. Trains and buses also connect the country's large and smaller towns with one another. Metro ride. €140. Monthly pass, regular price. €45. Taxi rate per kilometres. €105. Start fare €3. City bus. €140. Cost of living in Spain travel around Spain and beyond. Every region in Spain is unique and offers its own cultural heritage. From food, architecture and art, you will never run out of things to see and do while teaching English in Spain. One night in a mid-range hotel. €50. Train from Madrid to Barcelona. €3. €65. Flight from Madrid to Paris, round trip, 2 hours. €55. Sample monthly teacher budget. To give you an example of how an English teacher in Spain spends their salary, here is a sample monthly budget. Gross income, salary. €1,300. Average. Rent, shared or one bedroom. €500. Utilities, electricity, gas, water. €115. Phone and internet. €40. Food. €150. Insurance. €20. Remaining disposable income, €475, currently $540 USD. How much you can save when teaching English in Spain? As you can see from the sample budget above, you will be left with approximately $540 USD after the average expenses when teaching English in Spain. Of course, this amount varies depending on your salary, location and personal lifestyle. While it's true that you won't be able to save as much compared to places in Asia for example, where the salaries are generally higher and the cost of living considerably lower, you will still have the time of your life when teaching English in Spain. Take your TEFL Tezal in class course in Spain. ITTT has in class TEFL courses in Spain where you can spend four weeks learning everything you need to know about teaching your own English classes abroad while exploring Barcelona, Granada, Malaga or Seville.  Apply now for your TEFL Tezal certification course and start teaching in a matter of months. Speak with an ITTT advisor today to put together your personal plan for teaching English abroad. Send us an email or call us toll-free at 1-800-490-0531 to speak with an ITTT advisor today.


Just every step and every act is hilarious. He decided instead of sharing this agony with people, he decided at least he'll make them laugh. Somewhere he understands this agony could exist in a whole lot of people. So, sir, you know there's always… there's like… there's light, darkness, black, white, yes, no, life, death, there's always… I always find the universe to be in some kind of dichotomy, you know. And in what sense are you calling it as a dichotomy? Like whatever… like when I have these thoughts I'm like there's always two things at play, you know. In… in every… every aspect of life, big, small, there's always an opposite. Is… like can you elaborate on that? The very way you're characterizing yourself and the question that you're asking itself is a dichotomy. People always thought Charlie Chaplin was very funny, but if you listen to his private talks and things like that, there was a deep sense of agony in him. He was… he was especially sensitive to the agonies of life. Yes. What an artist. When you see him on the screen, he just made it… that's so ridiculously funny, hilarious all the time. Everything, every step, every act, not just some act, just every step and every act is hilarious.  So because there was such a deep agony, he decided instead of sharing this agony with people, he decided at least he'll make them laugh and… because somewhere he understands this agony could exist in a whole lot of people, in different measure of course. So when we say dichotomy, we're talking about contradictions. You said light and darkness, let's take that, because that's a very basic day and night light and darkness. There are many ways to look at this. One fundamental way is like this. There is light right now. You know there is light right now only because you have seen darkness. Suppose let us say, twenty-four hours of the day, everything from your childhood, everything was lit, you would not know what is light. So you know light only because in some way you have tasted darkness.   You know what's a day only because you've seen a night. So what seems to be contradictory on the logical level of your mind in terms of making of life, they're complementary to each other. They're working with each other but pretending to be opposite to each other. This is why in this culture, everywhere in the world, not just here, in one way or the other, they figured this and they made it in so many ways. They called it yin and yang, here we called it shiva shakti. And if you see the images of Shiva, one half of him is man, another half of him is woman physically. Because what is being depicted here is, this is the nature of physical existence. As long as your experience of life is limited to physical, when I say physical, right now everything that you can see has to be physical, isn't it so? Can you see something that's not physical? Can you hear something that's not physical? Can you smell, taste or touch that which is not physical? Or in other words, your entire experience of life is physical, even your thought and emotion is physical. We can measure it today. We can measure your thought and emotion, that means it's physical. So your whole experience of life is limited to the physical dimension of the existence. And the very nature of physicality can only happen with this. Even if you take the basic electric charges, there is a positive and a negative, without that it will not work. If you take an atom, there are positives and negatives. So the very construction of physical nature is between two opposites or two complementary dimensions of life. So when you live here, if you live here with the necessary perception, in a very brief amount of time, one can realize this contradiction or this complementary nature of these two things can go on playing endlessly upon you without taking you anywhere. When you realize that, that the physical will not get you anywhere, that is when you turn spiritual. It does not mean you've rejected this physical, you're still living in the body, you're still living in this world, it is physical. But this is the longing of every human being, it's not just some spiritual person, every human being is trying to touch something beyond what they are right now. If you know money, you're just thinking more money. If you know power, you're thinking more power. If you know pleasure, you're thinking more pleasure. If you know love, more love. If you know knowledge, more knowledge. Whatever it is, you're always trying to touch something more. If it finds this longing to become something more, if it finds a very basic physical expression, we call this sexuality. All you're trying to do is be something more than what you are. Something that's not you, you're trying to make it a part of yourself. If it finds an emotional expression, we call this love. Once again, emotionally you're trying to make something that is not you as a part of yourself. If it finds a mental expression, it gets labeled as greed, ambition, conquest or simply shopping. Something that's not you, you're trying to make it yourself. But if it finds a conscious expression, then we call it yoga. Yoga means union. Yoga doesn't mean twisting and turning. Yoga means union. Why do you have to know union? Because that's the nature of the existence. On the surface, it seems contradictory. If you go deep enough, suddenly it is not contradictory.


noon wherever you are, and it is my great pleasure to introduce Mark. Mark, you are not only my boss, you are also the senior director of technical marketing in our application developer and services business unit, and you are basically responsible for everything I do during the days and also you and your team curate a ton of patterns around cloud native application architectures, and this is exactly the talk you're giving today, so take it away. Thank you so much for being here. Thank you so much, and I'm really excited to be here because this is one of my favorite topics. It's really about trying to make developers more effective wherever they are and whatever type of role they have. So maybe before I talk about red hat patterns, maybe I'd like to start off just providing some context when it comes to patterns. What do you think about when it comes to patterns? What does the word conjure up in your mind? And I think for a lot of people, if you say patterns, you'll think, oh, yeah, a pattern. That's like a piece of fabric or a large roll of sheet with a repeated motif, and yeah, that's a pattern. I recognize that. What I'd like to do is to share a different type of pattern, which is closer to what we'll be talking about. This type of pattern is more of one, it's a pattern set, and if you combine this pattern set, it allows you to assemble a piece of clothing, for example, a shirt. So that's great. And you may ask, well, why bother with this? Because you could always have had a seamstress, and a seamstress is so expert, and a seamstress could come up with a wonderful shirt. But for a seamstress, that requires a lot of time, a lot of effort, and a lot of background training for the seamstress. In short, it's a very artisanal approach. What I'd like to do is to take us on the path on how we can move beyond that artisanal approach. And once you start establishing patterns, that gives you the ability to take this pattern and repeat it. You can scale out, you can make the same shirt again, and again, and again. You can set up an assembly line to churn these out in mass production. You can swap out the actual graphics that are imprinted on each piece of fabric. So you have a shirt in different colors, different pattern styles. All of this is enabled by taking an artisanal approach to creating pieces of clothing, and taking a pattern-based approach. It helps us get more maturity, and it gives customers more choice and better quality. We see this evolution happening not only in the clothing industry, but we see this in industry after industry. It's a very common path of evolution. Let's take a look at one more example. Let's look at automobiles. So I guess none of you were around when the first automobile came out, so that was a real work of craftsmanship. Each of the original automobiles were created piece by piece, assembled from unique parts. In many cases, they even had to create the very machinery to make these pieces. So that really was an artisanal approach at an extreme. Then came along the assembly line, and Henry Ford was the pioneer of this movement. The assembly line gave us mass production, and through mass production, price points came down dramatically, and automobiles became accessible to more and more people in the population. One of the drawbacks, of course, was Henry Ford's famous quote that you can have any color as long as it's black. So that wasn't the pinnacle of the evolution of the auto industry. Things moved forward, and the industry began to mature. The next step, it began to form into different groups of modular components that would be combined together to create the full car. And that modularity allowed the different subsystem teams to work at different paces, depending on how the technology behind those subsystems was evolving. And what that ultimately gave you was a much broader reach for the automobile industry. It gave a lot more choice in different price points, different market segments that could be reached, and there's pretty much an auto for every type of consumer today. This all has been achieved through industrialization. Now, coming back to our industry, we've seen evolution along three dimensions. We've seen evolution along architecture, deployment and process. And when you think about this relative to cloud native, the further you move along to the right, the closer you are to cloud native. Many of you are on this path, or hopefully many of you are quite a long way on the right. Now, I'm sure many of you appreciate that getting there is not being an easy path. There's a lot of rocks in the path, and the complexity is really challenging at times. So the potential is great, but there's still a lot of work to be done to realize that potential and to make sure that we keep the complexity under control. Now, that complexity is driven by the nature of the software industry. Developers started off being, when we look back, it was relatively straightforward for a developer in the 70s, even going into the 90s. But as we started moving more and more towards cloud native, the demands and expectations of developers has become ever greater. It's not just the technologies, it's also the processes and the practices that they have to learn. This has meant cognitive overload for developers. And we're frankly reaching breaking point right now with what we're asking developers to be aware of, to learn and to be expert at. So I urge you to think about how to deal with this kind of crazy complexity. Here, you cannot even read all of the blocks. Now, for those of you that don't know, this is an overview of all of the technology building blocks in cloud native. It's a popular framework that's been shared by the cloud native computing foundation. And you can't even see what the building blocks are on this slide, let alone expect any individual to learn about what's here. So we need to simplify. First of all, really think about the use cases that you're trying to solve and take the right mix of technology to be able to solve those use cases. Don't take a technology-driven approach where you start with a fancy architecture and try to ram that into all of your use cases. Secondly, look at how you can automate the development process. You want to be able to reduce that cognitive overload on your developers. Give them the opportunity to focus on application logic and not on code around all of the non-functional aspects such as how to deploy their applications. And then, thirdly, take advantage of the latest organizational methods to prepare for better agility and to be able to scale up your organization. I won't cover it here, but a great path I recommend in this area, the concepts outlined in the well-known book Team Topologies and popularized in the industry as platform engineering. As I say, we won't go into that here, but moving forward right now, we're going to take these three steps to simplify and we'll map them to the popular process improvement triad of technology process and people. So we've got this triad here, and if you focus on improvement, you can't overweight your focus only on technology or only in process. You need a balance of improvement in each of these three areas. As you do that, you start to mature your capability and move forward. This way we saw in those earlier examples of the industry, the auto industry and the clothing industry, you begin to get closer and closer to that nirvana where you want to be of highly productive, delivering great applications to enable the competitiveness of the companies that you're working in. What I'll do now is to take us on a journey to explore some of the red hat patterns and how we tie that together to these three process improvement dimensions and help you on this journey. So before I get into showing some examples along those three dimensions, I'd like to start with an overview of what are red hat patterns? What is this about? Well, they're really looking at the types of scenarios and problems that you occur as you're on your journey to cloud native, and they provide repeated solutions to be able to move forward and unlock the roadblocks. They'll help you as you modernize your applications and as you adopt the cloud. Let's look at the three different pattern types we offer. On the left hand side, you have portfolio architecture. That's a high level looking at conceptual designs and architectures. It's very visual in the form of block diagrams. It's something that an architect or a CIO would be interested in. It gives them the opportunity to see proven implementations by other red hat customers. The two sets of pattern types on the right hand side are implementation patterns patterns. If you want the richest set of implementation patterns, go with a validated pattern if it covers your use case, and here you'll find patterns which are ready to be deployed into production. It's fully automated deployment, and red hat provides an SLA and tests these patterns over time as the underlying components go through version changes. The middle one solution patterns, think of that as a compromise where you've got some real code to help you with implementing the pattern. It comes with a sample app, so you see exactly how the architectural pattern is solved, but it's not something that you'd actually want to deploy directly into your environment in production. You take that as a building block and tie it together with other building blocks to create a specific architecture that suits the challenges that you're facing in your environment. Together, these three pattern types give you a full set of coverage for your journey to the cloud. Let's go back now to the process improvement building blocks and see how these relate and how they help you, and we'll just give some examples in each of the three dimensions. For the first dimension, well, we'll start off by actually giving some more insight to what a solution pattern looks like. What can you expect if you look for a red hat solution pattern? We'll take an example in the process dimension, and if you think about process, one very common challenge is that in a multi-cloud environment, it's really difficult to automate deployments of application code to different clouds at the same time. What we'll do is to take advantage of a solution pattern, which helps with multi-cloud deployments using Qtops. Let's jump into the demo, overview of the solution pattern. You'll see this with all solution patterns. It starts with an overview of the solution pattern itself. Then you can drill into the architecture. Probably, first of all, you wonder what are the actual components within this solution pattern, and you get an overview of which technologies, quite often these are red hat technologies, but they can also include technologies from red hat partners or from the open source community. Then there's an overview of the architecture itself, a graphical overview. Here we see thinking about our challenge on multi-cloud deployments. We've got a central management hub here, and this is showing that from the central management hub, we can unify and automate deployment to different managed clusters. Already we know we're very much on the right track. This is a pattern that will help solve the challenge we're faced with. It goes into more detail on exactly how some of the architecture works in practice, some information flows between the different architectural components, but then that's great. It's some documentation and paper, but let me see how this really works. We jump into seeing the solution in action, and you'll see with all solution patterns that there's a visual demo or video demo showing the solution pattern in action. In this case, we've actually got two demos that show this. That's really good to see in more detail, to ramp up your learning, but you'll probably want to even go further and say, well, that's good. I can see it, but I want to recreate this in my own environment. In that case, we provide full instructions on how to take this solution pattern and all the detailed instructions to actually run this, deploy it in your own environment. You now have an idea of what solution patterns are about. Let's return to have a look at a different scenario. For the second scenario, let's look at the technology dimension. This is all about what are the architectures that I want to deploy to help move towards Cloud Native. Let's have a scenario that I'm a technology executive and I'm looking for something. I'm working for a manufacturing company. I've got a central data center. I've got a variety of manufacturing plants dotted around the world, and I'm looking for some technologies to be able to better manage these edge devices on the factory floor. Let's see what Red Hat has to offer in this area, but I don't just want to hear from Red Hat what Red Hat has to offer. I want to explore and discover what other Red Hat customers have actually implemented. For that, I'll go into the portfolio architecture. Here we have a full catalog describing all of the different customer implementations using multiple combinations of the Red Hat portfolio. There's a lot here, so you can always browse it, but being a busy technology executive, I'll actually want to filter this. So I'll filter it going into Edge and have a look in Edge. What I see here is industrial Edge. That sounds pretty much what I could be looking for. Let's go in and see what industrial Edge is about. We see here it's got a factory floor element interacting with applications in the central data center. So I'm on the right track, more information of different components addressing different users, my DevOps team, the data analytics team, business analysts. So yes, this seems to be on the right track. I've seen an overview. I know customers have run this, but what are they actually running? Let's get into the implementation details. And for that, we go to a validated pattern. So for a validated pattern here, we'll jump straight into a demo, and I won't go through the full demo. This could be a bit of an eye test to see what's going on here. Very simply, it's a bit of MQTT-based instrumentation points, or feeding data around the environment using data streaming based on Apache Kafka. And then if you drill down to see an actual scenario that's covered in the demo, here we have a vibration instrumentation on one of the manufacturing devices, and the AIML behind this implementation detects vibrations and then recognizes anomaly spikes and vibrations, which then trigger a work order for an operator to visit the line and repair the device. So that's an example of just a simple instrumentation. But really, the heart of what this validated pattern is about is to show how you can automate the deployment of configuration from the central data center to those remote shop floor devices. Here we've got an example where we want to add a temperature sensor, and so that's simply done by making a change in the configuration file and then triggering the GitOps process to automatically deploy that. And the end result is that without any intervention on actually changing code on those factory data center systems, it's also been deployed automatically and you see the vibration sensors working as before. And now the temperature sensors have been added. As always, you can actually deploy this, and being a validated pattern, you can deploy this and run this directly in a production environment. So a really great set of capabilities. Let's go back now. So we're still on this discovery journey. And let's say now we'd like to see if we could leverage some of these concepts and apply them over in our retail arm of our business. And so our retail arm offers an e-commerce store, and they're trying to figure out how to put a recommendation engine together, and maybe there's something around Kafka and data streaming that could help. So to do that, we'll jump over to the solution pattern catalog. Here's a list of all the solution patterns that are available. Right at the top, we see a pattern that's available for, well, it's a recommendation engine using event streaming and Kafka's in there. Sounds very much like what I'm looking forward to. It's got the standard details you see here. So I wouldn't go through the full details. You've seen it's the same format as the first solution pattern example. What I would like to do now, though, is to show you an example of when you actually follow the steps to deploy this in your environment, what the end result is. So here we're going to actually go and see the result of going through this implementation, following the guided instructions, and you'll end up with an OpenShift cluster with an application deployed in your OpenShift cluster. What we have here, we've got a couple of ancillary services, and then there's the main application for the recommendation engine and the e-commerce website. The e-commerce website is a Node.js application, and that's feeding information, storing information in a Postgres backend database. There's some streaming going on that's taking care of handling the tracking of user activity on the website and then generating a list of recommended items to see in the site. Let's have a look at that site. So this is the starting point. Remember, all of this comes from the solution pattern and following the guided steps. So we've got a full web store here. This main page would normally show in this area here some featured products. This is the very first time that we're launching this, and so there isn't actually any user tracking yet. Let's go in and see the store itself. So these are browsing through the store, see lots of Red Hat memorabilia, also some IBM memorabilia in here. And okay, so this is the store. I'll now take you behind the scenes, and we want to track whether our Kafka streaming is working correctly. And to do that, we'll go into KafkaTrop, a utility for Kafka. And with KafkaTrop, we can see what's going on. It's tracking all of our Kafka topics. We'll go into the topic on global tracking. So that's actually just looking at the messages that are flowing through. At the moment, you'll see that there's no messages, a size of zero in the topic queue. So we're actually going to the website. We'll generate some user activity here, liking a few things. And with that, I'll go back into KafkaTrop. We'll refresh. And if everything worked out, the demo didn't blow up. No, it's worked. And we have four messages have been received in the Kafka topic for activity tracking. Now, how do we use it? What's the outcome of this? Well, if we go back to the shop store, and if we go to the home page, we'll now see based on the likes, and if you just imagine this scaled up for multiple users, we've got simulation engine that's also built in, based on user activity, and likes of different products, it comes up with a featured product list. And if you want to follow this offline later, you can play around with it yourself, invite your friends to also put their likes in and see how this all works in reality. So that took us through some discovery and exploration of patterns related to technology implementation. Now, I'd like to get us closer to the end and take us on a quick look at the third dimension of the triads around people. How do you improve organization? What can Red Hat do to help in this area? I did touch on something earlier around platform engineering. There is a lot that Red Hat does in this area. In this short presentation, I don't have time to go into that. You can expect at Red Hat Summit to see a lot of presentations talking about platform engineering. So I do encourage you to consider coming to Red Hat Summit. But what I'll share now are some very practical things that are accessible, right today. It's the open practice library. Now, this is based on the many years of experience of our consulting teams, our product teams working together with customers. And we've documented all of these different practices for improving teamwork between developer teams, between say developer teams and platform engineers or the implementing DevSecOps processes. All of this catalog of tools and processes is all available. And in typical Red Hat fashion, this is completely open source. So I do encourage you to explore that. Now, in closing, I'd like to leave three takeaways. First of all, begin to make the improvements on improving your developer processes and get ready by bringing your development practices into the up to the latest standard for cloud native and ready to scale. And you can do that by driving along maturity and taking a balanced approach across the triad of people, technology, process and people. And by all means, take advantage of the patterns that Red Hat shares with you so you can get a head start faster and you can simplify that complexity and find ways to reuse best practices of others that have gone on before you. With that, thank you so much. In the recording that you'll find on YouTube, you'll be able to take a picture of the QR code and have a look at explore those patterns for yourselves. Thank you so much. I don't know if we have any time for questions. I think we need to make a wrap. But if there is anything, Mr. Yeah, let's let's just wrap it up. There are what is the link to the open practice library, Mark? Maybe you can share that so I can. It's also a QR code. I'll put a link to that in the chat right now. Wonderful. Thank you so much. Thank you, Mark. And we'll be back in like two minutes. So hang tight while we set up everything else for the next two presenters.