Yes, perfect. So welcome around to the afternoon session where we'll be focusing on like exploring spatial transcriptomics But before we get into that, I just wanted to give you a brief introduction on myself here So, you know, who's on the other side of the screen. My name is Alma Anderson. I'm from Oosterbeek, Sweden Which is a fairly small village with a population of like 69 people At least as of the day before yesterday and the influx and outlooks isn't super huge So I'm pretty sure that this is like a correct number Though now I'm living in Stockholm, Sweden, which is a slightly larger city, you can say and I'm working and situated at Syloflab in Stockholm and I'm also associated with KDH I've been here at Syloflab since 2017 where I did a short spree in the Deltemot lab where we focused on molecular dynamics and even more specifically like membrane proteins and you can get even more specific about that where I focus on ion channels and viral potassium ion channels Since 2018, I've been a part of the Lundberg lab and we work sort of like exclusively with spatial transcriptomics or ST, the technique And in this lab I've been doing like computational method development So let's use some brief information about me and I should also make a small disclaimer here This is sort of like my first online teaching experience So if the technology isn't sort of like on par every time, I hope you have some understanding Before that So here's some information here about the outline of this session I'm just gonna super quickly go through some Realtation here and then we just take a couple of seconds and then we look into some background of spatial techniques And I know Michael and Charlotte said that we sort of expected you to have a bit of a background knowledge But my idea here is that spatial is a pretty new field So maybe it's good to just add some context to what sort of data that we will be working with And then we'd brief the touch up on the data processing Touch and move forward to the data analysis And we'll do some basic analysis and compare how this compare look at this have compared this compares to what we do It's a single cell data Then we'll have a short break and answer some questions if those have arisen And then continue on with the data analysis where we will be looking at mapping of certain cell types And I would be elaborating a bit more on this later on and then we'll do another example Look at some more spatially focused analysis, which you can't really do with single cell data And my idea is also to give some information regarding the exercises and also some more questions So for the notation here You will see later on in the exercise session consists of three parts and a lot of that material We also be covered here in the more theoretical part And I've tried to indicate whenever that is the case using this symbols here and I will place them in the top right corner Just for you to have something to relate to Right so moving on to the background then and my idea here is to just give you a very like overview of the different techniques special techniques that are out there and You can more or less put these into five different categories Where the first one is the micro the section based techniques and here you isolate a region of interest In your tissue or sample the place is isolated in a separate well and you sequence it either using like bulk or a single cell methods And this is very much like a brute force approach to reaching spatial resolution And some example here is our LSEM, Tomosek, Tiva, Proximity and Nilsek Then we have the in-serial sequencing methods Where we sequence the transcript in place that is within our tissue and these methods tend to offer like a sub-cellular Resolution some of them relies on our priority priority defined targets, but not all of them For example, Fissek is a bit more unbiased We also have the in-sate to hybridization methods and here we use labeled probes for specific targets And we let this hybridize to these targets and this tends to require of course a priority defined target since we're aiming for them And before there was quite an issue with the multiplexing capabilities here But due to some clever expansion strategies and some good decoding schemes we sort of have like overcome this issue We also have the in-silicobase methods and these are a bit of a curiosity Maybe there are more of them out there, but this is the one that I'm sort of aware of And here we try to like infer and reconstruct spatial structure from non-spatial data, for example single cell data And I think that this is a pretty cool theoretical Approach to something. Yeah, so I would recommend you to like check this one out if you haven't seen it already And then as a fifth category, we have the in-sito capture-based techniques And here we captured the transcripts in-situ, but we sequenced them ex-situ And usually these are a bit less dependent on prior selection of targets And I've actually grabbed this sort of classification of the different methods from a review That was recently published, so if you want to know more about the different techniques and just get some insight into the field I would recommend you to have a look at this one, for example But for today we will be focusing on the in-sito capture methods and even more specifically the ST method here And that stands for spatial transcriptomics Which I will just give you a brief background or history to here So this idea here of spatially barcoded arrays, it was introduced to the scientific world As you can see in mid-2016, I think this paper here was published in July And it was a science publication by Storlital And they made this, sort of like, then they thought it was a really good new to name this spatial transcriptomics technique Today it causes quite a lot of confusion when you say that you work with spatial transcriptomics Because that's more or less the whole field However, in late 2018, TENIX acquired the IPerite Studies Technology And that resulted in the launch of the Visium Spatial Lean Expression Platform And that is sort of like the type of data that we would be working with today So just to give you some brief specs about the Visium platform here It is an array-based technique And we have this 6.5 x 6.5 mm area that we put our sample on And within this array we have about 5,000 different spots arranged in a hexagonal grid And the spots are 55 micrometers in diameter and the center to center distance is about 100 micrometers And each spot has millions of capture probes And I tried to get a bit of a more specific number on this But TENIX is pretty like secretive with that information So they state that, yeah, the spots have millions of capture probes However, each of these probes have a spatial barcode And that's sort of like what allows us to link gene expression to an actual physical position on our array They also have a polarity sequence which allows us to capture the polarity-related mRNA And it gives us sort of full transcriptome-ish data And I add the ish here because we can't really distinguish between different isoforms and so forth But it's untargeted and tries to capture the full transcriptome at least What I want to point out here is, and you might have seen this from the resolution Or the sizes of the spots that I just mentioned before Is that we don't really operate here on a single cell resolution yet TENIX says that approximately 1 to 10 cells contribute to the observed gene expression in each of the spots And that's something that's pretty good to keep in mind and I will come back to this later on as well So for the experimental workflow, just to briefly summarize this And I'm not like in the lab doing this so it would be very much of an overview here What you do is that you take your sample, your tissue of interest You put it on this viscimery, you take a bright field image And this is something that you use later on as a reference to back map the gene expression to Sort of like where in the tissue you capture these transcripts You do the mRNA capture, a CDNA synthesis, you cleave off the probes And you put them into the sequencer, there's some preprocessing going on there And now it's bits in the account matrix And this of course is very similar to what you would observe in a single cell experiment Where you have genes along one dimension but rather than cells you have spots Along the other dimension And these spots have barcodes and the barcodes are associated with certain specific spatial coordinates So I should say are there any questions so far? No, doesn't seem like it, great So like I said before, we'll briefly touch upon the preprocessing here But the majority of the rest of this session will focus on what happens once you obtain this count matrix But still it's good to know how to like how we end up there to get this count matrix So yeah, let's head on to the data processing So just you have the cell render for the single cell data, we have the space ranger for the spatial data And we can use the make fastu to convert our VCL files to fastu files And then we have the space ranger count command that do tissue detection or alignment and the UMI counting And when I say tissue detection or alignment it's sort of like to find which spots that are under the tissue and where they are located physically Once you run these commands you will end up with an output like something like this depending on which parameters you specify You have some automated analysis there which I don't tend to pay too much attention to And then you have your count matrices represented as max files or agf files And you will see that some of them are named raw and some of them are named filtered The raw data contains all of the spots whilst those that are named filtered only contain spots that are under your tissue And you can read more about how these commands work and the different options that you can specify at Tendix website So I won't really go into too much details about this So let's say now that you processed your data and usually what I want to do is to convert this to a more convenient format to work with And there isn't really any standardized format for that but my personal preference here is to convert this to an H580 file And this is what we will be using in the exercises as well And up until recently scanned by Ndata didn't really have a good module to use Visium data but they've just recently released one Which is slightly different to the format that we will be using because I didn't really have the time to update that it was super recent but it's very simple So, just as Charles was speaking of before, this Ndata file have different slots sort of where we have different types of information And to just shortly give you some information on how the spatial data will be stored here is that in the variable slot we hold the genie identifiers and some with IDs and genie names The observation slot holds the spotted identifiers and the respective coordinates and this unstructured slot here it holds the image, the h&e image or like the bright fit image And some scaling factors that allows us to go from the count array coordinates to the actual physical pixel coordinates And I will elaborate a bit more on this in the exercise session and you can also check out more information on this GitHub page here that I've linked Right, so now we have our count data, the matrix and we're ready to start like doing some initial assessment here And I will try to like give you some examples using human breast cancer data that I've taken from 10x website so it's public data and anyone can use it And that is also what we will be using in the exercise sessions So the very first thing you can do is plot how the spots are spatially arranged and you sort of like see what your tissue outlines are and everything but it's way more informative if you also overlay this on the h&e image And we can actually add an additional layer information here, let's say for example that we're interested in how our certain gene is expressed across the tissue So what we can do then is to let the face color intensity be proportional to the gene expression values here And then we can see how this gene, ERBB2, sort of like it's more highly expressed in the cell dense darker regions Which makes sense because ERBB2 it's associated with healthy positive cancers, we would expect that where there are more cancer cells perhaps So one question that I tend to get quite often is how you sort of like visualize this high-dimensional data So in the previous slides we looked at the expression of one gene, but we actually do have like 20,000 features And somehow maybe we would like to condense all of this information to like a single representation And here we have 12 different gene expression profiles for certain genes And one suggestion might be that we just like join this all in one image And that works if we have used 12 genes, but if we start to plot like about 5,000 or like 20,000 features it's just going to be a mess So another alternative or idea here is that we take this gene expression data, the full gene expression data set And we embed it in three-dimensional space using for example UMAP, we do a fine transformation where we move this data set into the unit cubes So all the values will be between 0 and 1 And we can consider these values as RGB values or values in any other color space And then each spot is associated with a different color and that allows us to plot this in a bit more informative way Where regions with similar color also have a similar gene expression profile So that gives us some information about what we can expect from our data So moving on to the data analysis, pardon And before you go start doing some more deep data analysis, of course you always need like filter, normalize and perhaps use some batch correction And as we noticed in like the previous exercise, there's actually no like magic recipe to give And how you process your data is very much like dependent on the samples you have and the objective of your analysis But what I can say is that much can be learned from analysis of single cell data You can transfer most of these concepts to the special data So I would just also give you some general advice here regarding some things that I've learned from analyzing quite a lot of special data here So regarding the filtering, it's good to fill the genes based on their expression level Or we make a cutoff and say, okay, we only include genes that have a total expression across all the spots higher than some specified level And this depends a bit on how many spots you have, just as previously dependent on how many cells we have We can also fill the genes based on spot presence here And what I mean with that is that maybe you have one gene that is extremely highly expressed but only one spot That's like like a technical artifact or some kind of stuff going on with the mapping so it could be a good idea to exclude those genes as well We could also filter spots based on the expression levels or we say that, okay, to include spots in our analysis We need to have a total gene expression level higher than some threshold This is not always necessary, it was more necessary before in the old STRIs which weren't like as standardized as the current epistemaries But it might be a good idea to do this if you expect that the automatic detection of which spots that are under your tissue is not completely correct We could also filter away ribosomal and mitochondrial genes, they tend to exhibit quite sparse expression patterns and sometimes like quench more relevant signals As for the normalization or like batch correction, I would recommend you to account for the spot sort of like library size Since we have varying cell density across our tissue, yes, because we have higher expression levels of certain genes in some regions It doesn't really mean that it's upregulated, maybe we also have more cells that are there to express these genes Also, if you try to like regress out certain covariates, it could be a good idea to include a slide or array as a covariate to regress out and not only like sample ID and such We've seen that in big data sets, for example, this actually did come into play And some tools that have performed pretty well so far is SC Transform and Harmony And they are of course developed for single cell analysis, but they are applicable to ST data as well, especially data Right, so just to give you an example here of some basic analysis We could start with clustered spots based on their gene expression after we've done some normalization and then we visualize this in the UMAP space Just as we would do for single cell data, the neat thing here is that we can back map this to the actual tissue that we are working with and using the image as a reference And the image here is actually a really valuable source of information, it could act as a sanity check where we ask ourselves like does this make sense Do the clusters seem to somehow correlate with the morphology and if they don't, why don't they? So that's something that people tend to forget when we speak of spatial data that just having the image to like compare with could add quite a lot of support for your conclusions Next, the natural question is usually to ask like what do these clusters represent And of course you can proceed to use the like a standard analysis, maybe we're interested in what these orange clusters up in the right corner represents We find some genes that are upregulated in this cluster and we subject them to some gene set enrichments or functional enrichment analysis And all of this information can guide us in the annotation of this cluster, maybe it's like a cancer related cluster or it's more immune related But there's this but here, we need to remember that each of these spots is a mixture of multiple cells, meaning also that we can have a mixture of different cell types present at these spots Hence if we sort of cluster our data based on the spatial gene expression, the clusters doesn't necessarily represent a specific cell type I rather tend to like think of these clusters as an assembly of spots with similar gene expression profiles, or maybe they have like similar population of cell types Some of them like the BH cluster here, it might be like purely consisting of one single cell type, but that is not always the case So a natural question that tends to arise and in which a lot of people are interested in, where are my cell types then, how do I find out where certain cell types are located in my tissue So let's take off where we left, and some of you maybe have started to think about this question here that I just posed And one suggestion might be that we just look at marker genes And this is like an easy and straightforward approach, but there are some issues To start with it requires like knowledge of our marker genes, that we know the marker genes for each respective cell type, and that is not always true There's also this risk of an overlap among our marker genes, if you're working with a really complex tissue with a lot of different and similar cell types, maybe we can't really find a mutually exclusive set of marker genes for each of the cell types And then if you observe a certain marker gene, we're not sure if it belongs to cell type A or cell type B, and which cell type indicates the presence of There's also this question of how we interpret certain expression values, so if we have a high expression value of a certain marker gene, does that mean that we have like a lot of the cell type there, or is it just a few cells that really highly expresses this specific marker gene And as for the lowly expressed marker genes, they may not even always be observed or maybe don't capture them, so we sort of like overlook these cell types So now another alternative solution here is to use single cell data, we integrate with this with our spatial data And the idea is that we extract information regarding the cell types from the single cell data, and then try to use this to infer the spatial location of these cell types within our spatial data And of course the big challenge here is that we need to deconvolve our data in order to get an idea of how much of each cell type we have at each of the spatial locations or response So our objective is to like present this in perhaps a more visually like easily interpretable way is we want to go from information regarding the gene expression in our spots to be able to make some form of informed statement regarding the cell type population at each of the spots And the suggested approach here that I will be presenting on it's a method I've been working on for about a year and there's a preprint on bio oxide And that's where we're using a model based probabilistic inference approach. So basically we can summarize this in three steps, we start by inferring the cell type expression parameters from the single cell data And then we're more or less translating to characterizing a statistical distribution for each of the cell types and actually each of the genes within each of our cell types Then we use these inferred parameters to try to find the optimal combination of cell types in each of our spots that best would explain the observed expression values And then we can simply just like back map these proportions back onto the tissue, just like we did the cluster labels before Just to give you some insights into the like underlying machinery here, we work on this assumption that single cell and spatial transcriptomics data can be modeled as negative by normal distributed Just for some notation here we say that x is n be distributed with the first parameter r being the rate and the second parameter p being the success probability And here below we have the PMF for this distribution as well So, used to start with a single cell data here to say that the expression y of G and G in cell C when C is of the cell type said it falls in the distribution The first parameter is a product of a cell specific skating factor in a cell type and gene specific rate and the second parameter we only condition on the gene Now looking at the spatial data to say that the expression of a certain gene G at a given spot S from a specific cell C when C is of cell type said it can also be modelled using a negative by normal distribution And here we use the same parameters as we have in the single cell data when we condition it on the cell type And the idea here is sort of that no matter which technique we use to start your data with or our cells with They should sort of behave in a similar way. It's not as if a B cell behaves like a B cell in the single cell data, but all of a sudden turns into a T cell is because we use spatial techniques to study it But we also introduce a scaling factor that is spot specific and the gene bias coefficient And the reason behind the inclusion of this gene bias coefficient is that maybe certain transcripts are more effectively captured in one technique compared to the other And that's a very good trade account for that as well Now we don't really observe the contribution from the single cells we observe their sum. So the variables I used to refer to before they are sort of like hidden variables and we like you said observe their sum And those are the elements of our count matrix So the idea here is that when we have a sum of nb distributed variables with a shared a second parameter the pg here this sum is also nb distributed and even more beautifully the first parameter here is just the The sum of the components respective first parameter So having established this We can make a neat trick here where rather than summing over each of the cells we change the index of summation and start to sum over the cell types and we introduce this new variable here n which represents the number of cells from a certain cell type at a given spot We also make another change here where we joined the scaling factor alpha and these newly introduced cell counts And then we introduce a new variable which we call the unadjusted proportions and I will soon explain why and we end up with this bottom expression here And the idea then is that we use the maximum likelihood estimate to get estimates of these cell type parameters Then we use these as known information when we try to model the spatial data And again we use Emily to get the gene scaling factors beta and these unadjusted proportions And the reason for this is that once we obtain estimates of the unadjusted proportions if we just like normalize them within each of the spots We'll actually get an expression that looks like this here Where the scaling factor sort of cancels out the alphas and when we end up with a fraction of the number of cells from a given cell type set at a spot divided by the total number of cells at that spot and that is just like a part divided by the whole and of course that represents the proportion of each cell type at this spot And that was sort of like what we wanted to know in the beginning, right? So to summarize the theory here we use a probabilistic model where we model the data as n be distributed and this has all been implemented in a tool called seroscope In the output from seroscope it's a spot times cell type matrix where each of the elements represents the proportion of the cell type that belongs to a given spot And you can find it on github if you're interested and like I said there's also a preprint So if we apply this to our breast cancer data, the same sample that I showed before, you can see some of the proportion estimates here And I should say that the single cell data was provided by the Swarbrick lab in Australia And you will also be working with this in part two of the exercise session So here's just a bit of a shared picking of some different cell types for them so we can look at the CD4 T cells, the memory B cells, the epithelial cancer cells and the plasma blasts And what we can notice is that the B cells and the T cells they seem to spatially correlate when the epithelial cancer cells and the plasma blasts have sort of like a spatial anti-correlation And we can quantify this in a better way using this cell type colloquialization plot which is used like the Pearson correlation between the different cell types And if we look for example at the memory B cells we see that they have a high correlation here with the CD4 T cells And the same goes if we were to look at the epithelial cancer cells and the plasma blasts that would give us like a high anti-correlation So just to summarize the integration of the single cell and spatial data part here, it leverages the strings of respective technique and it gives a spatial resolution of well-defined cell types It could also be used as a basis in subsequent analysis, for example looking at patterns of cell type colloquialization And of course ideally we would like to have an experimental technique here that gives us single cell resolution but up until then I think this is a good approach to the problem And also it should say that there are other alternative approaches and this is not the only method that tries to solve this issue And that says my internet connection is a bit unstable so yeah, hopefully that's resolved now And the final point here is I just want to say that this trend of publishing a lot of atlases as a resources both with single cell and spatial data that's super exciting Because now we don't have to like scavenge the whole web for a good single cell data set to use to integrate with our spatial data There's way more available for us so probably we can get some really cool analysis results from that as well Right, so now I've been speaking quite a lot about the integration between single cell and the spatial data And also compared like how we can do clustering which is again very similar to what we do with the single cell data So my idea here was to give you an example of an analysis that is a bit more spatially focused And say that we have some spatial data here some vision data and we find an interesting domain of the clustering our data For example cluster two here and just to give you some context this is data from the mouse brain I think it's the subjectile section but I'm not 100% sure So we then may ask for example how the gene expression changes with distance to this cluster And when I say distance to this cluster I sort of like mean how far away we are from the edges of this cluster And this image here to the left I should say is represents the distance the higher the larger the distance the higher the intensity of the face color of our spots So if we just plot the gene expression of three different genes here Where we have on the y-axis their expression level and on the x-axis their distance to this cluster, you can really see some trends here For example the gene DDN and the green one it has an elevated expression it seems like the further we get away from this cluster While for the blue gene and the RG1 the expression seems to be a bit higher when we near the cluster but then decreases as we get further away And if we were to just like visually represent the gene expression here overlaying that on the tissue and our colored cluster two here in black is to have a reference to compare with We can see that our inferences that we made from the previous plot really do check out and the most clear example perhaps here is the green gene DDN Where we see that there's almost no expression near the cluster while the expressions of like increases quite significantly when we get further away And now just having become familiar with this idea or notion of expression as a function of the distance to something within our tissue We can also continue to ask which within which distance D from cluster two or like boundary that we're interested in, can we find absolute percent of all transcripts from some given gene So if this plot here again represents the expression on the y-axis and the distance to our cluster on the x-axis when they graph the model states relationship This question is sort of like equivalent to solving the equation that you see here to the right with respect to DD And to further emphasize what I mean by this for example say that we want to find the distance within which 50% of all of the transcripts of this gene is contained We can sort of like try to see and solve this equation and without but seeing okay about 0.17 distance units away from these clusters we might find 50% of our transcripts If we were to say that we want 85% of all of our transcripts, of course we would need to move further away from the water and if we increase this number even further we need to move further away from the water Now we can also flip this question and say which genes have epsilon percent within the shortest distance DD from cluster two And that allows us to sort of like find genes that are spatially upregulated or like how you express nearby the cluster of waters And this might not be the most interesting example if you're not like a mouse brain phantast But if we for example put it into the context of tumor tissue or cancer tissue Maybe we're interested in the tumor micro environment, the regions just nearby the tumor edge And this could be one sort of unbiased way of identifying genes to have certain expression patterns and how they relate to our tumor edges


I'm Dr. Valerie Lindsay. I'm the Director of Graduate Programs in the School of Business Administration at American University of Sharjah. At American University of Sharjah we offer an MBA, Master of Business in Administration and also a Master of Science in Accounting within the commerce area. Our MBA is a world-class MBA. We are number one in the Arab region according to the USA Times ranking system. We encourage students who have participated in working in the industry or government to join our program.


Hey what's up folks, in this project we're making a midi foot pedal with Stricke Python. You can DIY this midi controller in 3D print parts to build your own foot pedal. A foot pedal can add an extra layer of expression to your musical performance. This has about 22 degrees of rotation, which gives you a wide range of expression. It features a single potentiometer that can be assigned to just about any midi CC. Powered by the Adafruit QT Pi RP2040, this tiny dev board is perfect for both simple and advanced midi controllers. Stricke Python has a midi library that makes it easy to develop your own midi controllers. In the code, values from the potentiometer are mapped to a range of midi CC values. With a serial monitor and plotter, you can see the values from the potentiometer and set the minimum and maximum values to fit the range of control change. In your music software, you can assign the foot pedal to control any number of midi CCs. In this demo, I have it mapped to a Wawa pedal for a guitar synth. Get the parts to build your own and check out the tutorial on the Adafruit learning system. Links are in the description. If you're looking for more, the midi for makers learn guide is an awesome resource filled with project ideas, demo code, and wiring diagrams. So what type of midi projects would you like to make? You can let us know on Adafruit's Discord and the weekly show and tell. Thanks for watching, and be sure to subscribe for more projects from Adafruit. Thanks for watching, and I'll see you in the next video.


Shannon Sander, U.S. Air Force, 92 to 96. My motivation for serving in the military was actually to pay for college. Ran out of money for college, identical twins. Parents couldn't help both of us, so the military was good to my family, so I decided to go into the Air Force. Being the only female, you had to figure out how to fit in. And my flight sergeant used to bring everyone over to his room after shift.  And that was the one time he'd invite everyone else from the squadron over. And I didn't drink a lot. I wasn't 21 yet. So I had a couple, and he's like, well, just lay down here. Well, I lay down, fell asleep, and then I'm waking up to him, raping me. And when you're medically boarded out of the military and told at 24 years old, you're disabled for life. You can't serve. You're disqualified for further military service. It just multiplied into, I've done something wrong. I'm not good enough. So it became where you isolated. You didn't talk about it. DEV has given me a purpose when I felt my purpose was gone. Has shown me I can be a leader again and inspire people to do something.


Yeah, you know, but if you don't see the dot gov, right, right, you know, you knew, okay, I'll tell you what you do. Start a campaign. If you don't see dot gov, leave. Here's what I tell people. If you, if you reach out to someone, if they ask for your credit card number or your checking account or as a check as any type of payment, stop, pause and go back and look and see, are you at dot gov? I like that. Start a campaign. I like that a lot. Yeah. Yeah. It really hurts me because when people are starting a business, you already have enough to deal with as it is. Yes.  You know, someone calling me, uh, let me help you. No, I could just, no, I don't let them get it out. No, no, we call that nipping in the bud. Or as a mama, you said, I like to say, uh, excuse me, with your mind shutting your pie hole. Thank you.  That's the way I like that. But so you said you started out doing that at first and then what happened next? Oh, when I came here. So you know, you said you start out with your friends. She helped you were helping set up. You weren't making money intentionally. And then he moved and then what changed? Okay. I decided I didn't want to be homeless. Oh, okay. Okay. So the price of living in North Carolina and living in Northern Virginia. Okay. So yeah, you have to do something. So yeah. So what I did, what actually I came here and, um, I knew I needed to have employment because my federal retirement, I retired to North Carolina. So when I came to this area, you know, I had to do something, you know, could not do what I had done in North Carolina. So I took a position working for a company, an 8A company. Okay. Uh, for sale. Absolutely. Oh my gosh. Uh, I've never had a person to have this type of relationship with. He's like a mentor, uh, a son and a friend. I mean, all combined, he was, he was the president, uh, president and co-founder of the sale. I worked for them as a contractor, supporting a government agency, and life was great. Okay. And then they lost the contract. Yeah. Right. That's what I'm saying. So I'm, I'm, I'm assessing my possibilities, right? Yeah. And I believe in being very realistic. So I'm like, old and chubby. Okay. Who's going to marry me? Okay. Scrap that idea. So I had to do something else going back to the government. You make it hard for me to laugh on this call. You know that, right? I'm sorry. No, I'm not stopping. Yeah. I'm just being realistic. I mean, those were, you know, that wasn't an option. So, um, then I, I thought I was asked to go back into the federal government, but I said, been there, done that. I didn't even get a t-shirt, so that, that's not an option. And so, uh, one day I was, um, working on the contract and someone from the government came by and said, Hey, um, we really like your work, but you know, it's, it's going to be over soon. And by the way, are you, are you in GSA schedule, or are you 8A? And I said, no, I'm not. And he said, well, if you were on one of those, we would certainly come back to you. So hey, that was, that was the avenue. Right. I needed to do one. So I prayed about it and went into the 8A program, the business development program. Okay. Okay. And were you, did you win that contract, or was that already passed, did that pass by during the timeframe? Oh, no, um, I, I know because I was the, um, what is it called, the clean and refresh. You know what that means? No. You send me something and you know, I like the one they do on Friday.  That they're a hot potato over the fence. They like Jewish, Jewish on a Friday. Yep. Oh, look, I will drive, call, walk, whatever to do. Look, that, that potato is going back in your over on your side before the end of the business day. So that's what I did. And they would ask for something, um, that I would, you know, give it to them immediately. Even if I had to get somebody to walk it through, you know, in another town, another state, I would do that. Um, I remember once I sent something and they said, Oh, we haven't received it. I said, Oh, really? I said, do you happen to know? I was like, make it my name Karen Jones. They said, yeah, I said, uh, well show me that she received this at 1013.  So based on that, I was really able to get into the program fairly quickly. So when I was, uh, in the program, I received my letter, um, on the 9th of March, 2010. The next day I had a federal contract. That's incredible. That's incredible. Yeah. That you're the first person I've talked to that's that happened to. Well, you know, they need to follow the three P's, you know, what they are prayer, planning and patience. Most people don't have a problem with number one or number two. It's number three. That's the problem. Yeah. But she lands your contract the next day. Where was patience involved? Uh, well, patience is, is what you need when you're going through the process. And let me tell you, if I didn't do some planning, you think this just happened? No, of course not. Absolutely. Okay. So you have to begin with the end of mine.  You won't want to leave once you eat here. But if I should have invited you over for dinner, I don't wait till you get to the door and then say, Hey, I'll be right back. I'm going to the grocery store. Great analogy. Yeah. I think a lot of people need to hear that.


Hello and welcome to the third part of this series. If you want to check the previous ones There are some links in the description. This time we're gonna be making some updates to the auto clickers We're gonna make the price a dynamic value and we're gonna be also Duplicating this element several times. So we have different tiers of auto clickers and stuff like that I'm going to move all the gold relevant to this element to itself instead of having it on the main one As we had it before. So let's go ahead and create a script Which is gonna be auto clickers that vs just the default that we have here is okay and Now let's go and open main visual script, which is the one that we had before and here we have the own auto clicker pressed so This one Let's sum out a little bit Let's select everything Control C. Oh, oh, no Okay, we cannot copy this Function, but the rest once we can copy. That's something. Yeah Since this is the function definition It seems like we're gonna copy, but the rest of them we can so let's go ahead and copy and now on the auto clicker Let's select the function that we had here on this button Here instead of press I'm gonna disconnect it And I'm gonna connect it again To this node instead of the main one that way whenever we Press the button instead of going to the main script. It will go to the auto clicker Script if you notice a difference with previous videos in the new version of Godot They updated how this dialogue looks and I think it's much clearer. There's nothing new about it But I think it's more simplified. So it's just better to understand You can see here in blue is the node that has the signal and then you select the node You want to have the method created this method on bottom pressed. We want to have it on auto clickers Now that we have it connected and we had everything copied we can Control V which will paste it and And We have everything now We can connect the function with the condition and everything and this should be the same as it was before On the main script, let's go ahead and remove the on auto clicker press Which was the signal that we are not using anymore from before so we don't get confused and Now we have the main one the bottom press which is the make something button and Here we have the on button press which is This button inside the auto clickers a little bit confusing, but yeah, let's go ahead save it and try it out Let's see if we have any issues with our program Okay, it's disabled Okay now Okay The gets and the sets they don't seem to be working as Intended why is that since these valuables were defined on the main script? You see here. We have these variables We need to have the auto clickers get the reference from the Main node instead of the auto clickers now and This is starting to get confusing really really quick That's why I think the best way to work with visual scripting is When you have a very simple task to achieve whenever you start making things complicated Code will always be a better way of doing that. So how can we get the variables from the other node? Well, remember we had exported those so we can try and drop so if we click here on the main node and Here on the inspector we will get the count here and we can try and drop and This is the set count on that node And we can replace it with this one and if you try and drop pressing the control You get the getter so we can get the Count here Okay, let's replace the values here so a is gonna be this and Also, we want to have it here. We can remove this node We are now getting the correct one The auto clicker value Now the set we can set it here Here instead of having it there we have it and we replace this one We can remove this one. Okay Now the auto clicker If you remember This was also here on the variables which was Handling all the how many auto clickers you had We're gonna have to move this one onto the new code here. We can create the amount variable Which will mean how many of these? Auto clicker we have enabled So instead of counting in all the auto clickers from the main one, we're gonna be adding the Amount from here now that we have the variable here. We can replace it Like so instead of getting the auto clicker. We're getting this one the amount and instead of setting with control set the amount and We set the value here and This should be working Okay, we had replaced it all those values. Let's go ahead now and do the weird parking fix. Okay. Now it's zero and We have this on press but we also want to have the timer affect The auto clicker node instead of the main node since we're gonna have many different auto clicker nodes We want to keep track of each auto clicker and its speed so We save we go back to here and on timer timeout This is another function that we have created for the main one from as node like this We're going to do basically the same. Let's go to the timer node Let's disconnect the signal and connect it again But to the auto clicker node Now let's copy all the code except the function declaration here on timer timeout, which was the signal used before and to the new one So we have all these variables. We already know from before and we have to replace them Let's select the main the count We can have it here Prepare the nodes first and they get by pressing control Okay, can remove this one and Let's replace this one like this and the values are gonna be this one Now auto clicker. It was a variable. We are not using anymore. We're using this one. So We get the amount sorry here and This should be happening now all the time and we can go to the main one and remove the timeout So goodbye timeout Let's check if we had something here on As well. Yes, they disabled. We also need to handle this like If it's bigger than 10 like the count It's actually this part. We need to handle it as well on the auto clickers So it was in the process function. Let's go to the auto clickers and Create the process function Sorry instead of creating one you can click here on the drawer and find the process Here process Now they have the process function Let's copy this part Okay, we copy. Let's go to the auto clickers We paste it Okay Now we connect these two nodes again The count we need to get it from the main one We select the node and from here we Press control and drop it. We get the correct node. Okay So we're gonna replace these two as well because I wanted to reference self instead of this node specifically So let's go ahead and select the auto clickers button and They disable here one which was false and again Disabled It's going to be true and we connected here Okay, I think we have everything now. Sorry if this part was confusing But yeah, this is also the life of somebody that is using visual scripting Let's try it out. Let's see if it works. Let's get to 10 and buy one. Okay But does not leave no What is happening here is that on the set text We have to update the reference on where this text is So Let's select the label node and Move the text as well again. This happens because when you're selecting a node God is Generating the path to that node relative to where the node that you're calling it from is What does this mean? It means that if you're on main It's going to search for auto clickers and after you search for auto clickers is gonna go to the label But if you're calling the same node from auto clickers It's gonna look for another child Which is called auto clickers which it doesn't exist and that invisible thing is gonna call for a label Which it doesn't exist either That's why you have to update the references if you are moving code from one visual scripting to another one and The paths are not the same So let's go ahead and replace this value Okay Let's rerun it again click hard and Click it. Okay. We have one auto clicker, which is updating one value by a second and Yeah It seems to be working now. Let's update it. We have to know It's getting two by the second three now by the second. Okay. Everything seems to be working as we had it before So that's it for all the changes we have to do and now we can start to Separate this officially from the main scene Okay, let's save this auto clickers as Save branch as a scene this will create a new scene with only that content. Let's call it auto clicker scene that's gonna be the name of it and As you can see here, I cannot see the children anymore and there's like a movie clip like link Which if you click it, it will open this auto clicker in a separate scene Now that this is alone together alone in the world without any context whatsoever Let's reset the position from the wrecked Which is the distance from the start of the scene if you can see here is 30 pixels and 92 Why so if you press here and the reset is gonna go to the corner that way whenever you create at the node This scene into another place. You're done. You're not going to have that Offset Okay, let's save the scene and it's gonna be move it move heroes also all this will be of course Fixed is instead of just drag and dropping like I'm doing right now You are actually using container nodes, but we're not gonna be using them right now Okay, now that we have the auto clicker as a separate scene. I can duplicate it Okay, duplicate it and I have another one and I had another one and yeah as many as you want That way when you play the game You can have a lot of auto clickers and this is starting to look more similar to what a clicker game is, right? like you have different options With different prices, and yeah, you can start buying all of them And I don't have to really like have to reference the new ones a lot or anything like that Because there are all clones of this one So as long as we continue upgrading this New scene all of this will update as well The first thing I want to do is to add the price as a variable instead of just a number so let's go ahead and Open the script and create a new variable here. Let's close the output Let's create a new variable which is gonna be the price Let's edit it's gonna be an integer We do the fix. Okay, so this is going to be the price of these Auto clicker. Let's set it to five. So it's a different value and we can check it And now every time we have here the 10, which is what we were checking before We have to add updated to this value to five. So let's get it We're getting the price And we'll place it here. So now this is going to be five We do the same here or Remember we can drag and drop the value to this one as well think this would be easier if the lines were Not crossing that much, but okay, the position is clear like We don't need anything fancy here. Okay. I don't have any 10 here. Nope. This is okay This part is ready. This was the unbutton press function. Let's go to the timer timeout We don't see anything here with any 10. Let's go to the process here We have a 10 which is like checking if we can buy or not and Let's try it here Okay so Now that we have the price We also will need to update the label here. We have the label here as a 10 on the button Looks kind of ugly. Let's remove it from there and Let's create a new label which is going to be called price and This label will be price equal five Okay, some custom color Fund color is gonna be like, I don't know green. Yeah, okay. This is the price now Let's update now this Value like I hard coded the price here by typing it, but we want to set it dynamically. So on the auto clicker Let's go to the functions and here on the process function. Let's update the label. So We get the label price we drag and drop the text and Now here we have like the string value. We want to get the price like what is the price value in this case five and If you remember here we do something similar Which is getting it and transforming it to a string so Let's go back and We transform this one to a string string Where is it string? Int here Okay, so now we're gonna have it as text and We also need To add the string value which we're gonna create a new variable for Which is gonna be price string Let's edit the number string value price equals and a space Okay so if we get the value and We add math add we get the price equals and The five and we set it to the The same text Okay If we want to continue the process process gonna come to the condition The condition is gonna be checking if it's true or false for the disable and then it's gonna continue with the done So we want to do this after we check that so we continue the program and Now we are setting all the time the label depending on that value Why is this important because if we want to modify now The price for each of the auto clickers We want to update that all the time and we know that the price on every clicker game is only going to go up so The last thing we have to do now is on the price variable edit and export it Okay So remember when we sport a variable We can see it from the inspector as a script variable here. We have it price five okay Let's try it out like this. Let's see if it's working or if I missed something. Okay now it only should cost five and Okay, I it seems like I forgot something. I think it's checking for the 10 in some other place when I click on the button. Let's see Let's see how much set the amount Here a minus B What am I getting? The price This is tricky why is it not happening? Oh Oh Here we have a 10 Why do we have it here? Get the count set disabled? Think we should remove this part, right? This is happening on the other one. So we don't really need it Okay, this wasn't mine. Okay button press. Okay, this should be fine auto clickers Let's see. We're getting the count We're getting the price Where is the conditional here is the conditional Interesting, let's see if we go to 10 if it's still happening. Yeah, I can buy if it costs 10 What was that? Okay, it seems like that other part was confusing Then the main script was Confusing the the other button. Okay, we have it working now like we wanted So what can we do with all these confusing stuff? I hope you're following this If not, I'm gonna be answering all your questions on the comments So they are coming and I'll do my best to help you with any questions you might have But yeah, now that we have all this set up We can set the price for each of them from the inspector here and since Now we know that it's going to be updating we can set the first one to five the second one to ten Third one to I don't know 15 This one is gonna be 20 and this one is gonna be 100 Okay Let's try it out and we see different prices for all the auto clickers Let's see if we only have five only this one is available if we have ten this one is starting to be available 15 20 and I'm not gonna click 100 times right now But let's do it auto clickers to base which is by stuff Start buying stuff Okay Yeah Okay. Yeah. Yeah, let's get it. Let's get it Okay, as you can see here now that we have 100 it's available and You might already be able to Think on what we can do next which is another principle of clicker games how much The auto clicker is going to be augmenting this value right now. All of them are only adding one and That every time that we buy one upgrade the price is gonna go up Those values we're gonna set them on here as a script bearable so we can continue to edit them from the inspector like this ones and Once we have all that we might already have a fully fledged clicker game ready for us to now select a theme and Start adding some graphics and things like that if you want to get the code for this tutorial I'm gonna be leaving it for my Patreons if you want to help me continue with this series Please consider being a patreon because if thanks to my patreons that I'm able to do these videos And if not, I'm gonna be releasing the code when I finish the series anyways, so Just remember to subscribe to know when that happens. Thank you very much everyone See you next time on the part 4 of the visual scripting and clicker game tutorials Bye


A wise man once said, all great change in America begins at the dinner table. Think about it. When the American farmer sets the table, he puts out plates to feed himself and about one hundred of his closest friends and neighbors three times a day. It didn't come easy, it took strong men and women willing to change, to become the most bountiful nation in the world. It started with a draft horse and a plow that covered four to five acres in a day has turned to tractors covering 18 acres an hour. We sure have come a long way, but we can't stop growing and changing. That dinner table is getting larger. The world's population is expected to grow from 7 to 9 billion people by 2050. Over the next 40 years, farmers will have to produce as much food and fiber as they did in the last 500 years. More mouths to keep up, more mouths to feed, rising cost, challenging weather, and a shrinking land base. How do we meet the needs of tomorrow, maintain our precious soil and water resources, and grow our bottom line all at the same time? Sustainability and profitability. It's a complex balancing act, but by achieving one, we also expect the other, how, doing more the same hasn't worked. Get up earlier, work the ground more, leave less residue, rebuild the terraces, and watch water or wind you rode the soil you depend on. Financial stability and sustainability can only come with change. We can't look for better yields, healthier soils, fewer man-hours, less erosion, and more profit without change. Change is what we have to do. Take an uncomfortable step, take a step down a new road, change. Each grower may start at a different point and travel at a different speed, but there are 10 common signposts to sustainable soil health and prosperity along the way. If we are willing to honestly look at what we are doing now, consider alternatives, ask questions, adopt and implement solutions, and stick to it through the rough ride, we'll make it. It starts with number one, recognizing the problem. Land, it is the most precious resource a farmer has. How many times have you heard someone say they're not making any more of it? But healthy soils are under attack from erosion. Sometimes it's wind, and sometimes it's water. The 50s were kind of tough down in our area, and there was a lot of dry weather and a lot of dust storms and that sort of thing. At that time, virtually everyone in the community used moldboard plows, primarily wheat country. The scenario was the plow would be the first thing that you would till the ground with and then a spring tooth or light cultivation of some time, and maybe three, four or five times of that during the summer. So by the time, seeding time came around, everything was pretty powdery and vulnerable to both wind and water erosion at that point. We farm in an area that's a real high clay soil, it's a red clay soil. Not particularly vulnerable to wind erosion, but very vulnerable to water erosion. And also, if you worked that ground a little too wet, it pulls up tremendously big clods and chunks that we spent the rest of the summer working back down to something we could make for a seed bed. Over the years, wind and water erosion have taken their toll on soil health, and traditional farming practices deepen the negative effects. I remember Dad telling me that, well, you know, I've always thought that you usually get paid for your tillage one layer or the other. What was true in his generation may not be true in my generation at all. What was good for our grandfathers may not be good for us. Now we know that tillage disturbs the soil structure and makes it more vulnerable to erosion. It also reduces crop residues that protect the soil from wind and water erosion and holds moisture. Each time the ground is worked, valuable moisture is released into the air. Tillage requires more fuel, more labor, and more equipment hours. As I watched my dad and talked to him, I felt like it would sure be nice if you didn't have to come out here and turn that soil upside down, working that soil back down to make a seed bed. We were very conventional. My grandparents terraced and I farmed the way that the manual indicated it would be the proper way. I really couldn't make up the decision to go completely no-till, but at one of the meetings where they had the rainfall simulator, and when he flipped over the tray with the plowed ground and it was completely dry, I just instantly made up my mind that that was the proper way to, we should be farming some of this ground. I remember having to plow the ditches in before we could plow across them. In my understanding of what needed to be done in those built terraces and contour farm, I was looking for ways to better that situation. The big realization when you go into the banker and you can't pay your notes, then you know from an economic standpoint that's not working. There must be a better way. As we begin to realize the need for change, it's time to start asking questions of other farmers, crop specialists, suppliers, and exploring our own willingness to try new tools to get answers growers can attend meetings on tillage, cover crops and residues, develop a pool of knowledge for new tools and technologies that reduce tillage, and seek out support for open-minded solutions, which leads us to number two, asking questions. Now that I've had children from some of the questions they asked me on questions I asked some of my neighbors, different equipment they bought, different things they did, directions they worked the ground. So I wasn't asking questions of others in my area. There weren't people to ask questions of, because it was and still remains predominantly tillage applications, but it did get some exposure through going to no-till-on-the-plains and the summer tour to South Dakota. That's where I started to ask questions. It wasn't so much why are you doing what you were doing, but why can't you do it this way, and it was more looking for the next step, the next better way. The mindset was that there should always be a better way, and that it's our job to kind of look for that. Even when we start to get answers, change is hard. With information, the need to change becomes clear. Number three, formulating the answer. Having once said, a pessimist complains about the wind. An optimist expects it to change. A realist adjusts his sales. As we come to the answers, we make adjustments based on an understanding of the problem. Probably the most important thing that I have been made aware of is the idea that I don't know everything. So the idea that we can always improve is something that was necessary for me to be able to learn is it's pretty hard to teach someone that already knows the answers. Because each grower will start in a different place and go at a different speed, he will also stop at different solutions along the way. We need to formulate our own answers based on location, soil type, and needs. We adjust farming practices based on answers to the questions. How can I reduce tillage to improve my soil health? How can I increase my crop residue and new crop protection? What is the best crop rotation for my soil and location? Should I plant a cover or companion crop? Your answers will be unique to your needs and your direction should be selected and supported by information, experts, and experienced growers. The underlying goals remain, sustainability and profitability, which leads us to number four, accepting the truth. The truth is change is difficult. It takes what we know and makes it different. It's hard, it takes time, but to continue to do the wrong thing efficiently is not the answer. It certainly wasn't an overnight thing and when you have things drilled into you for all your childhood, this is the way you do it and this is the way you are successful. Just to move planting date by a couple of weeks on wheat, for example, took me several years, probably close to a decade, to really get comfortable with the idea.  We had a lot of failures with no-till and it took us a while to realize why the failures occurred. Good share of those were caused by inadequacy of planting equipment, being able to deal with the higher residues. We have to be able to plant through about anything in terms of residues and it took the industry a while to develop machines that would function in those levels of residue. It didn't happen overnight. Change takes us from a passive to an active role. It can be exciting and renew our love of the land, engage us, and lead to significant benefits. Sustainable practices lead to healthy soil that decreases soil erosion. This organic content promotes growth of earthworms and microbes and helps retain moisture. Those who adopt the right new tools and techniques, ones that preserve productivity and make economic sense, will survive and pass productive land to the next generation. I think the first year or two, sure. There was more than one time I wondered, boy, do I know what I'm doing? Is this the right place to be or the right way to go? After about four or five years, that question never comes to mind again. When we finally accept the truth, we realize we are part of a larger group of like-minded growers, which brings us to number five, connecting with others. There are a lot of resources out there. It was almost from the very start, there were a couple, three of us that would call each other, you know, what rate of the chemical are you using, what planting, how many seeds break, are you dropping, and the group of people who share information got larger and larger and larger as time went on, as more and more people started to adopt the practice. I've heard it said you can't be an expert unless you're 50 miles from home, and around our area there aren't too many people really doing what we are doing 15 years ago when we started. I think it's very important that we as producers share, it's certainly been important to me that there were people ahead of me that were willing to share their experiences. Well, there weren't too many books written on it, there were articles, and it was a lot speedier in field trips, you could go see results. Those meetings, looking back, it was like a little college education on the fly. Most growers are willing to share successes and failures. Number six, adopt the main principles. First, avoid excessive tillage. Reducing tillage minimizes the loss of organic matter and protects the soil surface with plant residue. Tillage can break up soil structure, speed the decomposition and loss of organic matter, increase the threat of erosion, destroy the habitat of helpful organisms, and cause compaction. The biggest thing we've done for soil health is eliminate tillage. When we first went in a no-till, I think you could have taken a shovel out in our fields and dug all afternoon and not found an earthworm. You just didn't see them. And it was about at the fourth year you started seeing a few and then on through the fifth, sixth, seventh, and we're in about the tenth, eleventh year now. When we're back checking seed placement when we're planting in the spring, the earthworms are quite frequently up, fairly high, moisture conditions are good. We'll be cutting earthworms into with the discs that place the seed. The other thing we've noticed is that it takes a really serious rainstorm to pond water on our fields now, whereas back in the tillage days it would seal over and you'd have little puddles of water behind the terraces quite frequently. Now you just don't see that very often at all. The second principle is keep the ground covered. Bear soil is susceptible to wind and water erosion and to drying and crusting. Ground cover protects the soil, provides habitats for larger organisms such as insects and earthworms, and can improve water availability. We have found out on our red clay soils that no till without residue is not a very workable situation. You just almost have to have some ground cover. Third, diversifying cropping systems. Diversity is beneficial for several reasons. Each plant contributes a unique root structure and type of residue to the soil. A diversity of soil organisms can help control pest populations, and a diversity of cultural practices can reduce weed and disease pressures. In the process of better understanding what I was doing, I have taken advantage of using diversity and intensity to establish my rotation. The biggest thing that we started doing is starting to do crop rotations and planting a double crop behind wheat. Then we had another plant of a different species using water at different times. Once we got into a rotation where we could use broadleafs and grasses at various times of the year, keep something growing there as 365 if you want. That's the ultimate goal. Principle number four is maintain living roots. Maintaining a growing crop with living roots provides additional organized matter as well as cover and food for soil organisms. So the living roots we try to sequence our growing crops as tightly as we can, and indeed if things work well, if it rains, we will have only one and two week periods between the harvest of one crop and the planting of the next. That's the planters in the field when the combine is. The principles to develop healthy sustainable soil don't change. Reduce tillage, keep ground covered, diversify cropping systems, maintain living roots. How we implement them is up to us. Implementing the ideas is number seven. Implementing the principles for healthy soils is not a minor tweak in farming practices. It's a major one. The ground cover and the soil cover has been probably the key to making no-till work for us. Several times we planted feed and just let it grow up six, seven feet tall and fall down and all the neighbors have asked, what are you going to do with that? What are you going to do with that? And then the next spring when we got ready to plant mylar or something, there was just moisture right there, so that was really noticeable. We saw thatch's start to develop and I was actually starting to get concerned about we're not going to be able to plant through this stuff. And then as the soil more or less came alive and we started to have more organisms that were living off of that thatch, now I still have trouble growing enough residue to keep things covered. It just amazes me how fast the residue goes away now and we do no-tillage whatsoever. In the beginning I didn't realize the value, but after I've witnessed the incredible support that each of the different crops in the cover crop provide each other, it's a night and day. I think once we understood what we needed to do and we made it from mind that


Hello and welcome to the session. In this session we discussed the following question which says find the angle between the vectors vector a equal to i cap minus j cap plus k cap and vector b equal to i cap plus j cap minus k cap. Let's move on to the solution. We are given vector a equal to i cap minus j cap plus k cap and vector b equal to i cap plus j cap minus k cap. Now we take let theta be the angle between vector a and vector b. So we have cos theta is equal to vector a dot vector b upon magnitude of vector a into magnitude of vector b. First let's find out vector a dot vector b. This is equal to i cap minus j cap plus k cap dot i cap plus j cap minus k cap. So this is equal to 1 minus 1 minus 1 which comes out to be equal to minus 1. So we have vector a dot vector b is equal to minus 1. Now magnitude of vector a is equal to square root of 1 square plus minus 1 square plus 1 square. So this is equal to square root of 1 plus 1 plus 1 that is equal to square root 3. So magnitude of vector a is square root 3. The next we have magnitude of vector b is equal to square root of 1 square plus 1 square plus minus 1 square. So this is equal to square root of 1 plus 1 plus 1 that is equal to square root 3. Now we put the values for a dot b magnitude of a and magnitude of vector b in this. So we get cos theta is equal to vector a that is equal to minus 1 upon magnitude of vector a into magnitude of vector b that is root 3 into root 3 and this is equal to minus 1 upon 3. That is we get theta is equal to cos inverse minus 1 upon 3.  So this completes the session. Hope you have understood the solution for this question.


Muhammad Ali was a boxer. Bam Margera who is best known as a superstar actor producer stuntman and former professional skateboarder has snagged some pretty luxurious real estate Including his former legendary mansion nicknamed Castle Bam. Castle Bam became famous in its own right as it was featured on Bam's television show Viva La Bam. Castle Bam was featured on MTV's show Cribs in 2008. In addition to the main house It has a pool barn and detached garage Bam constructed a skate park and BMX bike track on the property And he's been known to throw a few parties there In fact in 2018 Bam put out an open invitation for a house party costing patrons $40 which would be a fundraiser for his new skateboard Let me tell you this party was massive with at least a thousand people showing up ladies and gentlemen This is a house tour you do not want to miss in these videos We don't reveal any addresses so please do not show up at any private residences because it is not safe for anyone Bam Margera's had quite the eventful career show business garnering a net worth of 20 million dollars Although in his prime he was estimated to have as much as 45 million dollars What began is Margera shooting himself in front skateboarding and doing stunts eventually turned into the CKY video series Which he released independently caught the attention of Jeff Tremaine who ended up becoming the director of Jackass and launched Bam into Superstar. Bam was initially known in popular culture as a cast member of the MTV reality stunt show Jackass However, he quickly became a fan favorite and made bank with his own spinoffs Viva LaBam and Bams on Holy Union. In addition Margera first began his career as a professional skateboarder in 1997 In 1998 Bam was sponsored by Toy Machine Skateboards. He joined team element the demonstration team for element skateboards in 2001 Although as of 2016 he was no longer a part of the team at various times He's also received sponsorships from bands such as speed metal bearings, 80s footwear, electric sunglasses, Volcom, land speed wheels, destroyer trucks, Destructo trucks and Fairman skate shops. Today Bam also earns an annual salary of an estimated two million dollars just for wearing element brand attire So his total annual income is estimated at six and a half million dollars Not too shabby for a kid who began shooting himself in front of skateboarding and doing stunts With all the bank he has made from MTV with Jackass and his own spinoff shows It was only a matter of time before he dropped some serious cake on real estate and that he did The house was listed for 1.19 million dollars when it was sold to Bam in 2002 Though they agreed selling price was never made public It didn't take long before Bam turned into a castle of his own Hey what's poppin guys it's your boy Marlon Palmer and today we're bringing you another house tour here for you on Famous Entertainment I noticed 95% of you guys watching are not subscribed So please be sure to hit that subscribe button because we post new videos daily Now we've previously reported on the homes of Wayne Gresky and Drake if you'd like to check those out Please hit up our channel and do so if you like these videos ring that bell for notifications Follow me on Instagram at daddumitfly so we can chat some more and let us know whose house tour to do next in the comments below Let's get into the video Back in 2018 Bam Margera's mother April had been working on renovating the house throughout much of 2018 So that it could be rented out as an Airbnb later that year Bam had put out an open invitation for a house party Which came with a covered charge of $40 and let me tell you this party was epic throughout the day guests could buy beer pizza and it feeling really charitable some of the houses artwork now Margera had set everything up to help him Destroy the skateboarding bowl in his properties barn saying he was working with the pro skateboarder Danny Wade to create a better Drone footage from the party showed over 1,000 fans in attendance and the night got a little rowdy with a giant bonfire We're in abundance of furniture and even Christmas tree were torched I mean it wasn't really a jackass party at furniture wasn't breaking or things weren't burning the legendary castle ban was initially built in 1985 features five bedrooms three and a half bathrooms and sits on 14 acres of property that had acquired the home in 2002 And while the selling price was never made public was initially listed for 1.1 million dollars in addition to the main house It has a pool barn and detached garage that constructed escape park and BMX bike track on the property The home features a number of crazy amenities including antique jukebox gothic style of decorating and pirate themed bar in addition The home is decked out with medieval decor large velvet red curtains and unique paintings throughout while the interior gives off a medieval gothic vibe His exterior features a perfect spot for entertaining in addition His detached garage holds a Mercedes Lamborghini Hummer and other high-end vehicles But more on his backyard in a minute upon entry Yes are greeted to a unique grand entry with a grand dining hall and pleasure lounge on either side the grand dining hall features Oversized windows decked out with red velvet drapes a colossal table with elegant chandeliers soaring above and spiraling wooden staircase That leads to the second story plus balcony overlooking the rooms in addition the room boasts an abundance of unique paintings sprawled throughout the floor Some of BAM skateboards and a billiards table beside the stairway on the main floor BAM keeps quite a consistent decor as most of the Custom fixtures are crossed between Victorian and gothic vibe The pleasure lounge is decked out with an abundance of massive leather furnishings and elegant carpet and cozy fireplace with intriguing artwork soaring above Like the grand dining hall the room features oversized windows large velvet red drapes custom fixtures and a balcony which overlooks the room However, this room is steps away from BAM's very own pirate bar for those that fancy a Chardonnay BAM's bedroom is decked out with a gothic canopy collection of BAM skateboards artwork and posters dedicated to his love for punk music and even his own element pillow Whom he was sponsored by for many years despite the bizarre house tour thus far I will say he has a pretty decent size walk-in closet and nice large oversized windows steps from BAM's master bedroom is his very own home office Which had since been renovated by his mom that features custom fixtures piano keyboard and nostalgic props from the jackass stunts Probably one of the coolest spots to hang out in the interior of BAM's house is the games room This one puts traditional game rooms to shame as it features its very own arcade with all of the classics We're talking Pac-Man, Frogger, NBA Jam, Mortal Kombat, and Tetris with easy access to yet another bar It would be very easy to see why this is probably the sickest room in the house For those skinny enough to fit a narrow walkway decked out with pink insulation and water tank leads to a guest room In fact Rob himself had to stay there the room featured a cot guitar microwave and radio Basically the only things you need to survive the other part of the basement connects to what can best be described as a man cave I mean this room is decked out with night's armor guitar recording system and mixer more skateboards two quarter pipe skate ramps And yes, BAM has been known to board inside the man cave decked out within a bundles of lavish furnishings television and bear fridge This room rivals the arcade this man cave leads to the outer deck and has since been renovated to include enormous circular Deck with pool house and stairwell to the pool both the deck which overlooks the beautiful saltwater pool and poolside Are decked out with abundance of furnishings in addition the backyard features a bar outdoor barbecue area and entertainment system and an outdoor Skatepark that's right BAM's party he threw was so that he could create an even better bowl Back out also features gardens and in abundance of space almost 14 acres to be exact which is perfect for entertaining All right, so I think I'll bring this house tour to an end here We got to take a quick look at BAM Margera's home known as the famous castle BAM after seeing that fancy little Creepy snag. What did you guys think was it everything you would expect out of BAM personally? There aren't many regrets I have but not partying in castle BAM That might be one of them out of BAM's features Which ones were your fave you guys can go ahead and rate them in the comments down below Love it if you guys follow me on Instagram at that do McFly and let us know Whose house tour to do next in the comments down below. See you guys next time. Bye


What's going on guys welcome to another video? I just wanted to really make this video because I'm actually out at Nationals at this beautiful lake right here And tomorrow's second day of practice I wanted to film a video not only updating you guys but saying a few things in fact since I can't really you know film too much and You know produce a lot of content right now of fishing and so I wanted to throw out this video just for you guys and Talk a little bit so guys we're gonna get this angle of the lake in the background and everything I just like to start off this video by saying thank you guys so much for the support Everything that you guys do, you know, it's absolutely amazing and Just supporting me along my journey It's just phenomenal. I just like to say a few things as in I Would really appreciate if everyone who clicks on this video would please, you know watch it all the way through You know that would really mean a lot to me Just because I would love for you guys to hear on everything I'm gonna say because it's coming deep down And I want to talk to you guys So I'm trying my best recently to respond to a lot of comments To communicate more with you guys, you know, if I see one of you guys in public You know, I'm spending as much time as possible to talk to you guys and get to know you guys and You know, that's what I love. That's my biggest thing. I love it so much and It's just amazing To be able to sit and talk to you guys Well actually driving up here It took three days. This is a 24-hour trip. We're actually in Minnesota right now. I'm originally from Atlanta, Georgia My college is in Savannah, Georgia, and it's like a literally like a 24-hour drive Up here. I've logged a lot along the way those videos to be coming out in the next couple of days I post every Tuesday Thursday and Sunday, but driving up here guys on that 24-hour trip I met, you know, a pretty decent amount of fans and It's just crazy, you know, it's just Absolutely awesome that I can literally travel, you know around Around the world around the United States and just, you know, meet you guys and Get to see you guys and talk to you guys get to know you and there's really nothing better than That or better than, you know There's nothing in this community or in this whole fishing thing that I'm doing better than meeting people that I inspire Meeting people that I enjoy my content, meeting people that, you know, I might end up having a long-term relationship with, you know It's just amazing and driving up here those 24 hours. I actually met, you know, multiple fans I actually popped a tire which will be coming up and a recent New video coming out in the next couple of days I actually popped a tire driving up here. Of course, I just knew it was gonna happen, you know I blew the tire and actually had a fan stop on the highway, which is just Insane, you know that that's unreal That's awesome, you know, he stopped and he's wanted to say hey, and he also saw we're okay Like that's seriously that means a lot to me and like when people come up to me and people talk to me It's just it's just real, you know It's just a hundred percent real and talking to people that I've never met before That they seem like they know me so well and then me talking to you and then getting to know you is just awesome But coming up here meeting a lot of fans just went to the meeting greet for the tournament where you know Every ever all the colleges lined up actually featured my truck and boat, which was awesome big shout out the best for that for scad and Met some fans there as well, which is just it's just insane guys Like I'm literally 24 hours away at home And it just really hit me like when I when I sat there and thought about it is you know, I'm literally meeting people a Days worth of time like of just driving like all the way across the you it's just unreal. I just Can't believe it.  It's it's really unreal and There's all you guys that support me. Thank you so much That's really what I wanted to say, but I'm gonna kind of go into some details With the tournament, but seriously deep down in my heart. Thank you guys so much If you ever see me in public, please come up and talk to me. It doesn't matter what I'm doing I don't care if I seem busy. I'll take time to talk to you guys Because that's when that's what matters to me the most even if I'm in a situation, you know, just come up come talk to me It doesn't matter what I'm doing Seriously, just walk up introduce yourself.  That's that's what I love seeing It's just phenomenal It's just amazing Well for this tournament that we're gonna be fishing guys It's on Lake Bemenji in Minnesota very small lake. All right, we went out today and caught a lot of toothy fish I had a lot of toothy fish and also I got a solid one to like a four pounder But not much, you know, it wasn't it wasn't too much and talked to tons of people that really didn't even catch a bass You know, and it's just trying to find those fish. You we have two more days of practice Tomorrow, which is Tuesday the day that you guys are watching this. I'll be practicing while you guys are watching this video And then Wednesday we practice Thursday's first day of the tournament Friday's the second day after Friday they pick the top 12 to move on to Saturday and Saturday Everyone to compete the top 12 and they take the top four and they move them on to Monday on a different lake It's the top four teams. They split them up into individuals. So there's eight of you. It's a bracket round All right, there's three days of that and you'll be going head-to-head.  So, you know, it's gonna be amazing. We're gonna get out there grind these next two days It's this is one of these lakes that are so small and there's like 90 boats That's gonna be really hard to really pound out a few days of good fish without people getting in your way But rather than that, you know, I think it should be really great Rather than that's just the experience, you know, I've never fished an event up this far before Up north. So that's that's really cool. You know, I've been the rainy lake. We've just got my Scott Martin challenge with him We did that last summer awesome awesome video if you guys can go if you ever see on TV You definitely watch this really cool video. I actually got to fish a rolling Martin, but we fish rainy Lake That's about us in Canada and but I've never fished like a real tournament You know up north, which is cool. You know, I mean, this is the national championship This is my freshman year of college. And so this is my first national championship and just totally pumped about it, but um Yeah, it's gonna be it's gonna be a grinder I'm gonna be trying to film as much as possible along the way But at the same time, I'm gonna film as much as I can but then again I'm not gonna try to make it to where the film's really getting in the way of me focusing and And I know you guys can understand that because you know, this is like a national championship But I'm a film as much as possible You best bet the GoPro is gonna be running during the tournament and I'll be getting a lot of footage I might not be talking to the GoPro's a lot because of the wind and stuff and it like I know you guys can hear right now. It's probably so bad, but uh I'll definitely be filming it. I can make something out of it. It'd be great But I just want to make this video updating you guys what I'm doing and why I haven't been posting as many Many fishing videos the past couple of times It's just because I'm kind of like on the road from on a 24-hour trip to the national championship And that's kind of want to update you guys on that. Tell you guys a big Thank you because I really want to be where I'm at today without you guys, friends, family You know my fishing coach and just everyone else I really want to be where I'm at today if it wasn't I mean the base on everything that I've achieved is from you guys It's like literally it's from you guys and you guys supporting my journey and you guys helping me grow and me Getting to talk to you.  I can't express it much more I really can't but I'm gonna walk around. I'll show you a little bit of the lake I just like to say a big thank you and then we'll close out the video So first of all guys, that's Bumenji. That's Lake Bumenji pretty clear water, you know this all that This is just some crazy. All right. We're staying in this hotel right here This is just some crazy like temple thing. I don't know what it is and it's just I just thought it was cool to come film out here I mean, why not right and Crazy, I don't know what this is It was just out here trucking boats actually over there That's where I'm at. So we're gonna be putting in the morning Hotel I'm gonna be staying at and then here's Lake Bumenji. This place actually really nice You know, it's something a little different, you know, it's something totally different You know the view of the lake is just absolutely phenomenal. It's just if there's gonna be a lot of bass in here And we're gonna be able to catch them. That's the biggest thing, you know I just I just want to get on these fish and do really good in this championship But get them get on getting on them in practice always isn't the thing to do You know, like it's just all comes down during the tournament if you're gonna catch them Sorry about the wind if it's really bad, but this lake it may seem super big But I promise you it is super small It's just a big bowl literally the islands that you can see or the trees that you can see way in the distance It's literally the other side of the lake and then right here ends right here and ends right there like it is not big at all I promise you I would love to show you more but that wind is just outrageous And I don't even know how the audience gonna turn out in this video But you know making this post tomorrow because I want to update you guys have more videos coming out You know Thursday and Sunday, I'll be sure to get those done for you guys, you know Just because this tournament is coming up does not mean I'm not gonna be working I'm gonna be working on these videos getting them out to you guys for content for you guys to watch But thank you guys so much for watching you guys mean the world to me Be sure to please like this video that would mean a lot Please like this video comment below something about the channel something you want to see what type of videos you want to see and I'll expand on that with the ideas be sure to subscribe and hit the little bell as well overall guys out Beautiful Lake Bumanji, Minnesota be sure to come to the way in you know information is online Go on bassmaster.com go to college if you guys are in the area you guys are up north be sure To come to the way in All right, I'm just being honest. I don't know if they like Very bodies in there or something that's kind of freaky. I just noticed that I'm gonna kind of walk away now But thank you guys so much for watching. Thank you guys so much for the support You guys mean so much to me and I'll catch you guys in the next