Hi folks, this is Dr. D. I apologize for being late on this walk through. The flu kind of hit me a little bit harder and I thought it would, and I've relapsed a bit here. So bear with me, we'll get through this remix and if necessary you can take an additional day to turn in your work. This is the lab 5 remix and this is the remix student name.rmd file and this is the one that I've worked through that's got a solution on it. That's why I've got dash solution. I always like to keep the original copy for stings. I don't have to worry about that and I just make a copy of it and name it the way I want. Okay, one of the things I wanted to point out to you that may help some of you is the newer versions of RStudio and Posit Cloud, which is RStudio in the cloud, now have this visual tab and it may help you see what's going on. When you're in the source, you get the raw code over here and for example there's an image, all this can be distracting to some people, but if you click on the visual tab, you get a message like this saying you're activating the R mark down visual editing mode. But anyway, it just allows you that you can take this check mark off or leave it on if you don't want to show the message again. I'm going to take it all because I'm making more videos and just click on use visual mode and then the top part doesn't look like it's changed, but it has. As you scroll down, you can see that it's taken all the markdown coding and highlighting and makes it look more like the web page and more how it will look on your final report when you knit it to either word or PDF. You can still see the code chunks and you can still paste in them the same way that you could on the source view. And sometimes when I'm editing a lot of code, I will go back to source view for some reason just seems more familiar to me, but for many of you using the visual will make it easier to read and to see what is going on. One other thing that I would point out to you that I always do to make sure we're trying to make these things into a reproducible document. That means everything someone else would need in order to reproduce what you've done has to be in this rmd document. Objects that are over here in the environment that you created in prior sessions. If they're not, if the code that sets these things up is not in this document, then whoever you want to reproduce your work cannot reproduce your work.  Clean suite and you remove all objects in this environment. This is just from this one work space in this one work session. So I'm going to click yes and that cleans out my environment. So now I know when I create something, it'll pop up over here and I know it will not hinder me when I'm knitting to make the final document. This first code chunk works when we're knitting. You don't need to worry about it right now. The first we need to run is this one loads the tidyverse, which we use a lot. And now it's loading the infer package, which has the thing, the code chunks, the functions that I'm trying to say that we need for this assignment. And pretty doc is just something that will help make your final nitted document look a little better. So I'm going to go ahead and click on run, run those. I can see down here in my console, I got my ready prompt back and of course the RAM isn't running anymore. So I know that those ran successfully. So let's scroll down here. You can read these scroll. Get rid of that. Here we go. It highlights when you double click like that. First thing we need to do is set this C and you can read that link we've got up there that will explain, you know, why you set that and why you set a number. We're saying 76 is received. All this does, it makes it possible for us to reproduce when we run one of the random functions. We give it a flag to tell it where to start so that every time it runs, it knows where it starts so that we'll get the same answers. If you don't set a C, then you'll get a different answer every time you run the code. Here we're going to read in the SAT GPA. This is our main data file and I'm just going to click run. And you can see we get some messages here. And over there we've got the SAT GPA showing up in our environment. One thing you can do, this is a message. It doesn't say error anywhere. It doesn't say warning anywhere. It's just a message. And I will show you real briefly how to suppress those messages inside your R code symbol up there. Put a comma in space and start typing message and it will offer up message equal. We will false and then I'm going to start warning, warning equal, false. Now when I run, let me save this. Now when I run this chunk, it won't display the messages in warning. It will still display errors, which you must leave that. You don't want to suppress the errors, but it gets rid of this red stuff, so it should anyway. There you go. So now we've loaded it again and we don't have the red message. That's something you can use on any of your remixes and rises. I'm sorry, your rehearses and remixes. Put that little code in there and it will suppress the warnings and make it for a cleaner final document. First thing it says we got to do is inspect the data. So we've got this data object set underscore GPA over here. It says there's a thousand observations. That's a thousand rows of seven variables. So you can get a glimpse at it here by just clicking the down air and it will give you each of the variables here. And it says where it's a number. This first one is just the number of the row. And then the first real variable is sex as a character or a qualitative character categorical made up of male and female. Note how they spell and how they capitalize or otherwise hyphenate these names because you got to reproduce these names exactly. S-H-T verbal is the next variable and it's quantitative and it's numbers. And these are the two we're going to be using in this remix. And then what I would do would be to go back over here. Excuse me. What I like to do in order to seal them more clearly, I'm going to click or double click on the name and it will open up this data object. If it's an object in your editor and source editor and it looks more like an Excel spreadsheet. So you can see we've got the columns, these are the rows.  The example code that you're given uses the S-H-T total I think in GPA. But as you go through and edit the code chunks, you'll be using these two variable names. So let's scroll down here. Whoops, let me get back into the remix and help with it. So that's what I mean by inspect the data, identify the variables of interest and then how the data is presented. You can use this glimpse function. That'll give you a sneak peek at it. I prefer opening it up in the source editor window so it looks like an Excel file, an ordinary table, which most people are familiar with it to understand. Here's our first question and I'm going to change this when I edit this document. Is there a difference in male and female S-H-T verbal scores? Okay, so you know it's looking at the sex that is the simple dichotomy, which I know we have more flavors today than we used to. But we're using just two, male and female, these are self-reported. And that's in the sex variable. And then we're going to use this S-H-T verbal score. So those are our two variables and we're going to sort them by male and female. First thing it says, calculate the S-H-T verbal score for each gender using the group by and summarize commands from the Dipler package. Dipler is in tidy verse. It's one of the sub-packages in there. And it says you need to get code five, but we've given you that. I put a note there and I moved it from yours. This hint was in the wrong place. It says you will need to create a new data object. One of the things that I see students get confused is we're giving them the example. And that's, I've got it in green here preceded by a pound sign. And you can see there, the first step in the old code was create average underscore GPA and sex. That's comparing average GPA by sex from the S-H-T GPA, our main data source. We want to change that so that we know we've got a different variable. And again, since we cleaned out the environment, it'll make it a little bit less complicated. But this way I know the new variable, you know, what I've named the new variable. And it's just saying we want to create average verbal sex using S-H-T underscore GPA. And this is the pipe operator and then group by sex and then summarize by here. We used to have GPA, FY equal mean GPA. And now we want to change it to summarize. We're creating another column there, so to speak, S-H-T verbal. That's the name we're giving it. And we want the mean of S-H-T verb. I'm sorry, this is our existing column, but that's the S-H-T verbal variable and we want the mean of that. And then we want to just print it out so I can run this code there. And you can see this is helpful. I know I'm getting long-winded here, but by keeping the old code and putting the dollar sign in front of it, that turns will change the color, but it tells R to ignore that. By looking at the original and then looking at what I use, that can help me when I go back and I want to reuse this code or if I've got some error checking to do. So I recommend that, you know, keeping the old code, just put a pound sign in front of it, then just copy and paste below and then edit it appropriately. Here again, we've changed the two variables, S-H-T verbal there. The old was GPI at physical year. So there's our first. So this is the way I recommend you go through it. We're just going to do a simple subtraction here, taking these two values, 48.60 and 49.264, subtracting them. Now, I know I subtracted the male from the female. You can do it either way. Just be consistent throughout. Once you start with the female being, you know, on the left side and the male on the right side, you got to continue that. Granted, this gives a negative, but it's just my practice. I keep them alphabetical. F, M. And then we have these questions we're going to answer. What is a different sample mean verbal scores? And that's what we just calculated there. The minus 0.644 with the male being higher than the female. And that's what I wrote there. And then here we're making a guess. Is this different statistically similar? Now, we haven't done the calculations yet, so I don't really know. But just by looking at this, you can see that it's 0.64. And we're at 50. So that's, you know, if it were 1 out of 100, that'd be, you know, 1 over 100. This is 0.4 over that, over 49. So it's about less than 1%. So is that really a big enough difference that we call it statistically significant? My guess would be no. Okay. And here I added some code. You can do this just to divide those simple math and that gives you the about a 1% there. You can add that if you want. Next is to generate a visualization of the verbal scores. Be sure to include a title, label, or accent. Now, here again, I've got the given code chunk in the parts I'm editing. I put the pound sign in front and it turns green. I hope you can see that. When we're doing ggplot, remember it uses the plus sign instead of the pipe operator. And we can chain these things together. You'll see in some of the assignments, we'll go from tidyverse with the pipe operator into ggplot. And then we use the plus operators. And if you go back into tidyverse, you would just at the very end here. And that's what's telling our stop. There's nothing after this point. That's why it stops processing. But if I put a pipe operator there, I can go back and do some more if I wanted to. So that's how that works. And again, I've just changed out. We're using the same main database. So that's why sat GPA is the same. We're still using sex as one of our variables. But here now we're using the sat variable for the Y variable instead of GPA at Y. And then I've edited the title of it to change it from grade point averages to sat verbal scores. And then down here again, I've edited this line to go from the Y equal GPA verbal score. That's the label for the Y axis to sat verbal score. And again, we can just run that and then run it. There we go. And it gives us two box plots. And here you can see these dark lines are the medians. And they're pretty close together. There's a little bit of difference there of a male. That's the male on this side. And I forgot to label that. But if you go back and do that if you want. And this is the female over here a little bit lower. Again, that's why I don't think it's statistically significantly different. There's a difference, but there's a difference between a difference and statistically significant difference. So you have to learn that. And then we state our null and alternatives and null is usually a form of no difference. So I just say there's no difference between female and male verbal sat. The alternative is the reverse or the opposite, which is there is a difference. So we're testing this null. And we're starting with assumption that there's no difference that if he's attracted female for male or vice versa, you'd have a zero difference. So that's how we get going. And you just go through each of the steps. I think we give you the starting code. And then I would really recommend getting the habit of using the pound sign. And identifying what the variables were are and then what the data source is and then reuse the data source unless you've got a reason to change it. But I usually like to remain here again. We're creating other data object. That's what that it's called the cat to nation, but it's just I create what I like to call it create using sat GPA data. A new data object called observe difference verbal sex. And that makes sense to me.  I think we already set that in there. And then we calculate the statistic stack in here. The one we want is the difference in means. Okay. And the order since I started with female first. We want female first and then mail. Of course, once you start with mail, you could keep it all the way down. And this just this last line just prints it out. So you can see I changed it again from observe different GPA sex. That's the old one to now observe difference verbal sex. So we run this first thing we see we've got an answer here. And it just says that my response variable was sat verbal numeric explanatory sex, which is a categorical qualitative or sometimes call a factor. And then in this one, we've got that difference there again minus 0.6444. And that's what's stored over here in the observe difference verbal sex. You see it shows up in the environment. We've got one observation of one variable. If I click on that, we'll see over here, we've got our statistic. So that's the basic process. Let's just go through, be patient and identify which variables you want to change. And here's the next code chunk and the original is GPA is in the world. Now we're dealing with verbal. So I changed the SAT verbal in the world still using the basic set GPA. We're using SAT verbals of function of sex as opposed to GPA FYS of function of sex. We're doing the null is independence, leave that alone and this generate reps. We don't have to change anything there. And then down here, I'm just again, preying this out a little bit that the new data object. So I can see that and run it. It'll take a while to run and then you can see over here. And let's close that. We've got this new one, SAT verbal in null world. I can expand that so I can see the whole name. You can see it's got account those zeros. There's six of them. So it's one million observations, which means there's one million rows and we've got three variables. And we can just see these three variables here. Sex, verbal, SAT verbal, excuse me, sex. And then we've got the replicates one through one million here. That's just remembering the rows. So this is how you go. This has been a long walk through. I apologize. I will try to give you some more help, but you do this all the way through each of the sections where we give you the code. Again, I recommend putting the pound sign so that tells our, this is no longer code. This is a comment. And then you can use that as a guide and change the data objects you want so that you can keep them different from the old one. And then make whatever other changes you want to use. Mainly we're going to be changing the GPA underscore FY for SAT verbal throughout all these things. And I hope this helps.


Okay, so, yes, thanks a million to Edward and Ricardo for what is a very timely and appropriate talk to go before me, because what I want to talk to you a little bit about today has many themes that are similar to what Ricardo was mentioning there. On one hand, we have projects, interesting projects that we do within the CDAR Center that build on the state of the art in machine learning, data analytics, etc. But importantly, not all of these projects have to be about banking, have to be about finance, have to be about many of the bread and butter issues we've been doing very successfully for many years. They can be in different areas. And when we were talking to the organizers of the Predict Conference, we thought one thing that might be interesting to really focus in on this year was the issue of sustainability, the environment, and how we as data scientists, all of us here as practitioners, can try to aid and help to move the world we live in in a good direction where AI is being used for good, essentially. So that's a large aspect of what we do, particularly in terms of the individual projects that we execute in CDAR. So I'll say a little bit about some of those projects and some of the techniques we make use of at the moment. So I am a researcher in CDAR and also based in TU Dublin, which is formally known as DIT for those who didn't notice the name change earlier in the year. And as part of CDAR, what we do are these very directed industry projects. And a lot of these that I'm involved in in particular are in the agri-food space. So you're probably sitting there saying to yourself, why agri-food? Why the hell would anybody care about agri-food one way or the other in an AI venue? Well, the answer to that is quite simple in a way. It's important. Let's consider the statistics on where global population and food consumption is going in the next 40, 50 years. If the problems haven't gone away, even though we hear about Europe and Japan having very much an aging population, the global population as a whole is continuing to boom with estimates of us hitting the whole 10 billion mark by the end of the century. And that's even based on the conservative estimates. So that's definitely where we're going in terms of a jump in population. But importantly, it's not just that we have a jump in population. The problem is that the population as it expands, it's eating different types of food. So we have the consumption of meat and of dairy and all of these very protein intensive foods really taking a jump as well in terms of our predictions. And we need to be able to cope with that increasing demand. And that's what has given rise to this area of precision agriculture, but also precision food, precision food processing, which is just as important as the work that's actually happening on the farm itself. So what sort of challenges do we face in this area? Well, for a start, even though the population is increasing and the actual consumption of individual food types is increasing, we have to balance the work we want to do in feeding the population with the very fact that disease and over farming are very much challenges we need to put up with. So the question starts to come. How can we try to help farmers? How can we try to help food producers to optimize what they produce without having long term damaging effects on the environment itself? So ultimately we want to help to keep sustainability there. So that's one of the big challenges we face. But the challenges we face aren't simply out in the field itself. If we look at the food production side of things, we can try to look at what is essentially industry, what is essentially a mass factory environment, and try to aid production within those environments as well, either by looking for problems in a process or maybe assisting human workers to do work faster. Again, we need to be able to help with these things. So what can technology, what can AI start to do for us? Well, fortunately, there's many different techniques from a computer vision, from a machine learning type process that we can leverage. And here I've highlighted some of the more important ideas. Up at the top you have that idea that the world isn't just what we perceive with our own eyes. We look at the world in a variant of red, green, and blue, but that's only part of the complete electromagnetic spectrum. So a lot of practical work we do in CEDAR projects, in projects with Irish SMEs looking at food and agriculture, is trying to make use of the full electromagnetic spectrum and applying ideas from computer vision to that full electromagnetic spectrum. Because as you can see from just the image I use here for illustration, that full EM spectrum can give us an awful lot more information on what's actually going on. So we want to try to leverage it. And fortunately, we have the power of deep learning, computer vision, instant segmentation, very deep, pre-trained networks that we can leverage for all of that work. And I know people in the audience know the bread and butter of these techniques very well already, but it's nice to see them being used in novel and interesting ways. So overall, we can use these technologies to try to do very practical tasks like monitor animal health, to try to limit the amount of fertilizers that are being deployed in the fields, limit the amount of weed killer being deployed, etc. All of these are very important goals. But there are big challenges. And what I think is interesting is that many of the challenges we face in these agri-food type projects are actually challenges faced by many different, not just computer vision, but deep learning AI type problems in general, including, for example, the topics Ricardo was talking about. And the challenges in particular that I see are just pure collection of data. If we're all working with tweets and we've got massive tweets, data sets, it's pretty easy to do some interesting work. But when we're working in new and novel domains, one of the biggest challenges we have is just collecting relevant data. We have the challenge that even if we are able to collect some data, it's often not nearly enough to truly take advantage of deep learning models in the way that deep learning was intended to be used. So that's also a very significant challenge. And we have, particularly for my domain, but it's also true in other very practical real world domains, that we don't have necessarily the access to the cluster, to the back end data center to do all of the number crunching. So how do we cope with that sort of limitation? Can we develop models that are still interesting and powerful and deploy them to more limited domains? So just in the time I have left, I want to talk through a little bit of a case study on a project that we are doing at the moment and talk about maybe some of the ways in which we've tried to tackle those problems. So this is a collaboration we are doing with an Irish SME called Tanko, who are based down in Carlow. And this is, as the guys were talking about earlier, one of these projects that's semi-funded by Enterprise Ireland, also funded by the partner company as well. And I have to thank my partner on that project, the CEO of Tanko, for some input on the slides that we're using today, because it is a case study on there, our joint work with them. In a nutshell, what we're trying to do with this project is to take advantage of the state of the art in machine learning, in computer vision, and apply it through these multi-spectral imaging methods to try to do interesting things around improving the quality of grass, essentially, and how grass is used to produce silage. I know that doesn't sound particularly exciting for all of us cement dwellers, but it is pretty important in terms of making sure that farmers are getting value for money in terms of the work they're doing, putting into their yields, et cetera. So what we've tried to do with that project, still ongoing, we're still working away, is a lot about data collection. How do we gather and build data sets that are relevant? And for us, this has meant very complicated engineering tasks in terms of putting sensors together, lots of different wave bands, other sensors I don't want to go into for IP and protection issues, but some really interesting engineering, but that's ultimately coming back in a data set that we can apply with these state-of-the-art methods. But in terms of the bigger challenges, I just want to say one or two or three things about where I think people should go and have a look at interesting ideas if you want to go out and be inspired to learn something by the end of this talk. One thing to consider is while we can do a sort of a roll-your-own approach to the network design, we are of course taking advantage of very big, deep networks. And what we found that's really interesting is that even for really complex networks like Resnet and like the other pre-trained networks, even though they're not completely domain-relevant for us, we are seeing fantastic results for them. So I guess my learning there for you is be adventurous in the number of ways you try to take these pre-trained models and put them to work. You can have surprisingly good results even if in theory you think it shouldn't work. And I always think for those who have more of an older AI background like myself as well, it's like that whole thing about the naive Bayes classifier. Even though certain rules have to be obeyed in theory, often you can try naive Bayes at a problem and it gives you pretty good results. Another thing we looked at is applying transfer learning because again, we have that challenge. You've got a small data set. How are you going to try to leverage that data set? Well, make use of ideas like transfer learning. Don't build an independent model for your problem. Build a model that's based on some big pre-trained data set that's much broader and then try to specialize it into your limited domain. That's a very important learning that we should all be making, taking advantage of. And the final one that I want people to be very aware of and to actually investigate and have a look at if you're working in computer vision is we have that challenge. How do we take really big deep networks and put them to work in limited domains? And what we're doing is taking advantage of these technologies like the Movidius' Myriad chip, which is really trying to focus down and concentrate deep learning into a really small footprint. What the guys in Movidius have done is really, really fascinating, interesting stuff. They were bought out by Intel last year or so because the work was just so interesting and relevant. So, if that whole area of deep learning is something that excites you and you want to maybe see it being used in more novel or interesting domains, have a look and investigate Movidius and the Myriad chips in particular they've put together. So, that's it. I get off the stage now. All I wanted to do is really just try to give you a flavor of some of the projects we do in the agri-food space and maybe hopefully give you some thoughts on what might be some interesting technologies such as the transfer networks, deep learning and the Movidius' chips that are really exciting for a wide range of projects. Thanks again.


Hello my awesome Virgos. This is Kelly from House of Virgo. Welcome to my channel. If you're new, please do smack that subscribe button. This is a Virgo channel only for Virgos Sun, Moon, Rising, or Venus. So please keep in mind some of the messages may or may not resonate. Just take what fits, leave the rest. All right Virgos, how are you all doing? Let's get started. See what your love messages are for July. Okay, for July. And if I do an extended reading, I'll let you know throughout the reading, and I will post the link below this video if we need to go there. All right, let's take a look here. Okay, Virgo, Virgos Sun. Hello everybody in the chat. Sorry Virgos Sun, Moon, Rising, or Venus. What messages does Virgo need to know what love messages does Virgo need to know for July 2022? All right, so you've got kisses. Awesome. You keep getting the kisses card Virgo. What's up? Okay. Unconditional love, giving and receiving affection, falling in love.  Let's see what else is going on here Virgo. Virgo, coming to you in July, some love. Somebody's bringing you some affection. Okay. Okay, you've got a mask. Not showing true feelings. Hiding, pretending, gaslighting. Okay. Exciting. Somebody's wearing a mask, keeping things surface, showing love and affection, but not opening up those deep feelings, making you think that they're not truly in love with you, pretending that they could take it or leave it. Okay, somebody's maybe very insecure, or just keeping their emotions inside, not really showing the depth of their emotions yet, still being affectionate. So like the affection and the kisses are just these little sweet nothings. That's what I feel like is going on here. Okay. And you've got drag and fly being lighthearted, finding out things coming to light, adapting, changing and healing. Okay. So yeah, I feel like somebody's just going to be very lighthearted with you in July. Very sweet, loving, affectionate, but hiding their true feelings. Okay. Let me just get one more because I want to see what these messages are here. One more card for Virgo, please. One more card for Virgo. Okay, the golden mirror. Self-absorbed narcissist, one-sided relationship, love bombing. Okay. There you go.  This is somebody who's making you think or will try to make you think that they have deep affectionate feelings for you, deep love, loving feelings for you, but I don't think that's the energy. Okay. So you're definitely going to be getting a reach out from somebody. This is someone who shows that they have a crush. Okay. This is my card about, you know, someone being smitten. So there's some communication coming in. Let me see. What else is going on here? Okay. It's a very immature, light kind of energy with somebody here. Oh no, be careful. I feel like I need to tell you be careful with somebody who's giving kisses and love and affection. It's, it's very surface. What is this person's true feelings though? Because they're not showing these true feelings. They're pretending. And is somebody love bombing you? I feel like some of you are going to find out or something's going to come to light about somebody here. Let me see. Oh, okay. Seven of swords. Yeah, there's a trickster. Okay. There's somebody reaching out to you, but the trickster energy, this person's coming across as being like a thief of hearts, trying to steal your heart here, the hell out of here with that. Okay. Let me see. What the heck? Oh, okay. Four of swords in the reverse. So this person is showing up quite restless. I'm very unstable, not healed from a past relationship, not healed from something. Okay. Where it's like, this almost feels like intentional and intentional energy here to love bomb you and give you all kinds of like affection and express themselves as being and like they loving you unconditionally, but I feel like this person. Yeah, it's coming in like very one sided. Right? Okay. So three of wands here. Okay. So somebody's going to try and make plans with you. Okay, you might be at a distance to this person. They're going to try and make plans with you. They might be waiting to hear from you or they're they're keeping you on hold. Or, you know, there's an energy here of like reaching out and giving you all this love kind of energy and then waiting to hear back from you and they're very restless. Okay. It just feels like ding dong ditch energy. You know, like this person reaches out with this crush love bomb energy and then they run away and then they're restless and they're waiting to see it's like intentional waiting to see if you'll take the bait, if you'll bite. Okay. Wow. What the who is this person? What the heck is going on here? Yep. So night of wands coming in with this real lusty energy. I feel like you got to be careful in July on who this person is. You know, don't don't run with anything. Don't get your hopes up with somebody. You know, whoever this person is, it shows up. Don't don't run with it. Virgo. Just be like, okay, I see.  Don't get upset. You know, don't just ignore. Okay. This energy and that's what I just feel like because somebody's coming in here being very fake. They're fake. They're showing up very fake. Okay. Nine of swords and the seven of pentacles. Okay.  I feel like their intention is to just come in and wreak havoc in your mind and cause so some of you maybe you have this person blocked or you're in no contact or something happens where they reach out and I feel like this person's intentionally coming in to cause anxiety and stress and this person's like a nightmare. This is like, um, they're coming in like a nightmare. Okay. Um, this what this is what I feel like the intention is here to cause you I don't so here's the thing like is it being done intentionally?  Maybe I don't know.


The red acapella, Y-254, the is sakin. Yeah, I go by the name yabadabadu. Maga. The good fella, Samia say. Ekori. Ekori. Eva. Oh, yeah, yeah, yeah. Oh, oh, oh. Nataka kupa mamboflane. Kahawanguare, kahawanguare. Tuchezea dinguare. Tu silale. Nataka kupa mamboflane. Kahawanguare, kahawanguare. Tuchezea dinguare. Tu silale. Stuck in the middle of nowhere. No, no, no, no. Wondering how I'm gonna get them to you. How you doing? Baby ma Julie. Aga bi oro mi. Let me be your king. Luta mato. No worries, yeah. I go by the name yabadabadu. Ekori. Ekori. Ekori. Ekori. Ekori. Ekori. Ekori. Ekori. Nataka kupa mamboflane. Kahawanguare, kahawanguare. Tuchezea dinguare. Tu silale. Nataka kupa mamboflane. Kahawanguare, kahawanguare. Tuchezea dinguare. Tu silale. I'm a simple man, a happy man. Yeah, yeah. Who loves a simple woman. A simple woman. Who wants to love you forever. Forever baby. Niki ja niti liye. Usini pimiye. I love you right. Niki ja niti liye. Usini pimiye. I love this love you baby. I'm a simple man, a happy man. I go by the name yabadabadu. Ekori. Ekori. Ekori. Ekori. Ekori. Ekori. Ekori. Ekori. Niki ja niti liye. Nataka kupa mamboflane. Kahawanguare, kahawanguare. Tuchezea. Nataka kupa mamboflane. Tuchezea dinguare. Tu silale. I'm a simple man, a happy man. Yeah, yeah. Who loves a simple woman. I'm a simple man, a happy man. Yeah, yeah. Who loves a simple woman. Yeah, yeah. Don't care. Nataka kupa mamboflane. Niki ja niti liye. Nataka kupa mamboflane. Nataka kupa mamboflane. Kahawanguare, kahawanguare. Tuchezea dinguare. Tu silale. As promised, ono ditu na say maga play Kenyan music. But here is a good example of what Kenya has to offer. This is red acapella. We're not new to the studio. Welcome back to the studio. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. The last time you were here we were wearing Santa hats. Kristi manzea tu kasele. But you've done a lot ever since then. As in you've done a collab with Heart The Band. You've been touring all over the place. So what's been going on with you guys? It's called growth. It's called growth. So growth is when you move forward and not backwards. So whatever happened kumikavitu in place and it's simply a manifestation of our plans. So it's not coming into play. It's not coming into play. It's not coming into play. It's not coming into play. Whatever we've been doing working hard. So it's just normal. It's what we've been doing. So sizing the amount of results. But I feel like it's like you shifted to another gear. You know kiyanzu na hanzaga now and kumikanya ga klat. But it's not enough. Because you guys have just exploded. You're all over the place. Kuna some secret collabo's that I want to get into. Because I can tell that's what's going on. You even brought a friend here. A very beautiful friend. So we invite later on. But what are you not telling us? As in what have you been working on secretly? Our album. Your album. The red acapella album is finally coming? When are we expecting it? In August. So who's been featured? Who's producing? You cannot just leave us hanging like that. I don't say me. I don't say me. In August. But the album is called Idaa Taifa. Ya man. So Idaa Taifa comes from. So you know. Idaa Taifa niwa api. Now. My producer has the secret sauce. So I will look for my information. Nimsia, what kind of produce? Ah. Take it. We already know one secret. So tell us everything else. We can neither confirm nor deny. We can neither confirm nor deny. So confirm. We can neither confirm nor deny. Then confirm wood. But confirm nor deny. But the album is coming out. And the first single ita kuwai na kamaut. Apriliai album. The first single ita kuwai na kamaut. Apriliai album. Is church a part of the album? No. Just new music, something we've never had before? Ya. So you really have been working. Because at the same time. So how do you juggle all this? Because you've been touring all over the place. Because I do follow you guys on Instagram. And you've been touring all over the place. So when do you get time to record? We are more of live band performers. Only that. First of all, ita kuwai na kamaut. So we have to be here. Most of the times. So putting an album pamoja, it's not the easiest thing. I can only imagine. Ya, and then our kind of album is totally way different. Ya, because even by just listening to you. Ya, ya. Ita kuwai na kamaut na kamaut na kamaut. That's what you expect. But with something. Is it more acoustic? Or is it more like tena na tena? They're collaborating with Hard Depends. No. Our album is more is more Banga combined with Roomba but it's very urban. It's urban folk. Urban folk. It's just Roomba but very urbanized. But our own style. Because that is our style of music. So it's very Bangaish Roomba but it's very red acapella. Can I ask you something? Let me just ask you. There was this conversation about play Kenyan music. New artists may come up. Most of them are Afro pop to the core. When getting there pretending to be Afro pop. You know what I mean.  Do you think that's the problem with Kenyan music? Why it's not being played? People are not going at it as real musicians. They're just going the studio route. No, I think first of all we need to initiate who is a musician who is an artist and who is an entertainer. Please do define that for us. For those who don't know an artist is not a musician and a musician is not an artist and we also are entertainers. For example, a rapper is not a musician but a rapper is an artist and also an entertainer. A singer is not a musician but if you can sing and play an instrument you now become a musician. If you can read and write music whether you can sing or not. Now for most people you need to know where you stand in the market. Are you an entertainer? Are you an artist? Are you a musician? Because for life I don't hear people who play live complaining that play Kenyan music. That's just the thing. Yes. So the guys who play live music the real musicians don't complain because they are already fans. So already he is playing Kenyan music. Kila siku wana pika Kenyan music. Now kuna ule atakuchi za kuwa media stations. Now how the artists and entertainers but we also have musicians. Sosa kama wana say mam for example an artist for example if you can sing really well but you don't know how to play an instrument you become a recording artist. So mostly your hype when you kuwa radio na tv kumakisha kuwa. So you become a different type of artist nasimbaya. That is your route now. Now do it na royal. That's just your speciality. Exactly. So if any of you don't know how to play Kenyan nini apana. So kama ii kama ume kuwa nimi sewa tv how do you kina damon wana faini nini doa cheswe. Look tough ties of v2. Kina devido wana faini nini kwangoma nini kwangoma ui cheswe. So I will never ever complain because I am living daily through music because I want to know where I belong in the music industry. I know where my place is in the market. So please know who you are before you venture into the market. Exactly. Wale wana kumpleni wana nini wana tegemea. Hype your Instagram na radio nini kumakisha kuwa. So who say actually hadjui kama anezatoka instrument hadjui kama anezatoka angel agada fans kuwa streets na actually lepige show. Yana beli vlazima kwa through media dun yonda kuwa star. No. What kind of an artist are you? performing artists, do you just write songs, do you just play instruments? Nowhere you are so that you and you are singing kusabu mimi we have never complained since we don't get enough airplay kama kina whisk it but that is not our problem. You already getting your coins. Kusabu we know our place in the market. So kama ni live music, kama kashwini show, fans will come and will play Kenyan music. This is Kenyan music. So teachers alive. We are just talking about how it is in this room. We'll be doing that. I want to talk about something in this mansion. Its part of what you just mentioned the cloud chasing. now there's a lot of drama let's be honest in the Kenyan gospel music industry recently a lot of drama about nakuro about the cloud parts of the music industry in general. Is it essential to we need it? Speak for the recording artists fast before you speak for yourselves because clearly you don't, you don't need to do all that. But what do you talk about? I think for us personally, we are not doing this for fame It is love, it is passion and all that. And we 이�好的 kiwa Kwaisehi niwa kikiawohu na iwa niwa. Nende, udake na iwa n70 Kwaisehi niwa kikiawohu na iwa, kwaisehi niwa n90 Ntuh transition ya ya kwaisehi niwa tuna Ntuh kwaisehi niwa nigeru Ntuh kwaisehi niwa kikiawohu na iwa Ntuh kwaisehi niwa nigeru Siya ni komita na Kenечan wa dissi ni ambushi ni iistiki petiting kukita usikres firmlyce Hazata ama maika katisha flavour soo domisa incoming ngassin, maika rekuko nukin We were saying yesterday that it's coming from love. We had a conversation yesterday. We were like, Mora sora blame Shetani? Even the devil blames the devil. Why are you guys blaming the devil, man? Sometimes we don't know what's going on. We are talking about Shetani, but we don't know what's going on. I don't want to say much. So just avoid the clouds and try to be like a role model. Most of, like just educate, please. Educate. There's a pastor who told us. Ane zaku amshirati, for real. But the moment ana kanyaga kwa chachivi, anaku pewa what you need as a person to grow. You get? What you need as a person to grow and to go to heaven. That's all you need. Wachera na vi tu pastor na do. But whatever now you do, umto yana se magama na yanda chachi sandeju ya kuenda kuona staff lani. And then Keshwa Subui, Instagram. No staff. No staff. I get what you mean, I think. It's so sad, honestly. Is it just as difficult because I think secular guys and gospel guys, yes, there's that clear definition of where you need to stand, even morally, behavior-wise.  Ono na evo? One, one, one. Secular artists kwanza wana kwa gaimesha ya kwa place. You get? What's the thing with ane gini wa shirati ya know that? One thing they don't pretend. Nada. You get? That's why we never even heard of a skanulia. Yeah, it's not like that. And sometimes when there's a skanul, inakwa nga ni obvious, and it goes away in hours or a day. But now there's a man of God. Yo.  Because I need to invite your friend. This conversation we really need to sit down. Because I like where it's coming from. We call this an edutaining show. So you are edutaining. And that's what I'm talking about. The viewers, they're enjoying it. Now, what I want to do right now, there's a new song out by Red Akapella. Yes. Your favorite duo featuring Moon. Moon is a beautiful young lady. She's in studio, if you may. Yay. Kaributa Fadali. Mazee, Moona kikuja patutakua, black and white. You know.  So she's called Moon. Now I'm a cabinsan. The small stars can shine. And you look brighter. You were here the whole time. Yeah, you can see me. Yeah, I can see me. Moon. Yes. Karibu Sana. Asante, na shukuru. You're not new to the music industry, are you? No, I'm not. But I'm new here. You are new here? Yes. Karibu Sana. Asante, na shukuru. Welcome to you. Thank you. I'll tell us a bit about yourself. When did you get into the music industry? Okay. Music, nimi kwa ni kifanya, since I was a kid. And I think nili anza kwa fanya from 2013. I've been doing music, recording, tuna toa, zingna zifanya poa, zingna zina fanya poa. And so, yes. That's when it started 2013. 2013? Yes. This is what I want you to do. We're short on time. Yeah. So, Moon, please promise me that you'll come back later. I will. Definitely. We'll talk about you and you alone. Yes. For now, you're only here because muleka muangaza apa. Yes. You know what I mean? Like camera 4. I'm just getting news. Camera 4 couldn't see you. And now you're on the camera. Sol kuna ni ona? Mili kuna kuna tu? I'm okay. I'm happy with that. What do you think? What do you think? Moonina make everything. I like that. But, yes. What is that name? Mune. Mune. Mune li patiwana besti. Kitamu sudiyo li wanuna na kaji. Aliona tumuangaza. But it's obvious, man. Radiating light. So, actually, this guys have been friends. Eh? Eh? Eh? Back this was a friend. Actually, a Sudanese for that matter. So, yeah. Oh. Gay. Eh? No friends with me. Koninini, koni tu wa Mune. Munchain. No. Yes. Awesome. Mili link up adzina Reda Kapela. Reda Kapela wa me kwa ma besti. Tulimi kitambo. Eh? Na actually, kitotu wa Juni. Chocha seesong umpia. Tuli record 2017. E me kuwa tu tunasimata fanya video. Tafanya video. So, it can happen to me fanya video finally. Yumi toka. So, nkali oto wa ni tikuwa vipua. So, to appreciate. Tuna shkuru. Tuna shkuru. Nkali oto wa kuwa. Ah, yeah. I mean, Reda Kapela da. Yes. So, you are like fans of each other. Yes. Yeah. Okay, let me do something real quick before we get into Chocha. Because, hey guys, by the way, don't touch that dial. Reda Kapela and Mune are about to perform Chocha Live before after we party on YouTube. But before that, see, you're fans of each other. Yeah.  So, in how this collaboration thing really works? Go. Rudi ya tena. Rudi ya suali. Buu da, man. Nikika kawanguare, kawanguare. And you can't give this young lady a compliment. Apani kusama buu. Right. Haita maata kusabuza kwa pinjimu kichu. Sa. Tupe moja. Tupe moja. Moja. Aha. The other half of the duo, what do you have to say for yourself? Please go to me. She's moved by herself, man. Eh. Na get. Kama... Umachikuliwa? Really. Tutaku chikuwa. And Mune? Okay. Mi neza semaivi. First, nime pendam ziki ki zao from way back. Nikona like albamiya ya tiyata siji kawana jua. Nikona mangoma zao. Muzi skiliza. Chinia waji. Manoma. And minna like Stelia Amziki na pendakama artist. Na kama bro kama beshte. Yes. Guys, umu na skia. She's actually your number one fan. Yes. Una jutambona tu jam complimenta. Ya ni, in the song ya ni, it was enough. Ala. Muli kum na fikirimu. Ya ni compliment already. Ya ni kwa song. Ya ni kwa song. There are many ladies apa inje. Aja hepa Buddha. Ata sa hao he. Aja hepa Buddha. So sa, guys, you know what to do. You can find red acapella on red acapella. Kila mahali. Yes. The red acapella on Twitter. Make sure you subscribe, follow. These guys are dope. Ya, sure. We have a new YouTube channel. It's called Red Alat. Red Alat. IG at the red acapella. Twitter the red acapella. Facebook red acapella. And of course, moon. It's a moon. Moon as Kenya. Moon as Kenya. Everywhere, YouTube, Facebook, Twitter. Kila mahali. Kila mahali. Moon as Kenya. Don't forget to subscribe. Ya. Safi kabisen. I've let you look who I promise. This is a treat. This is a treat. Yes. Not a lot. Did you talk at the show up. But, there's red acapella featuring moon. Ladies and gentlemen, you know we are the red acapella alongside the moon. Ndami anyumba na jua. Yes man. Ah. Chacha time. It's chacha time on Y-2-5-4 at the E circuit. Ya ya. O I. Atatatat into... this yung Kati put pounds, ya.


You can finish this in one. You need an adjustment? I do. Great pickup line up. Ha ha ha ha! Hey girl, you need an adjustment. No, I'm not. I'm doing a pickup line.  Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Nope. Why was it turning into yuck? This is why you don't skip the entrance. Haha. Ha ha ha! Ha ha ha ha! Ha ha ha ha! Ha ha ha ha! Ha ha ha ha! I'm a lector. What does that mean? Yeah, that's me. Fall in love. I'm Twitter. I'm Twitter. I'm all juicy. It's so juicy. Like, I'm quasi. Like, see, hit the bell. What? I'm so good. You also know personal YouTube channels. Like subscription below. Personal YouTube channels. in the description below. Personal YouTube channels? I don't have one. Oh, not yet. But we're gonna make one called Elephant Titus. Featuring Lexi. Featuring. Elephant Titus. Food video, Indian street foods in England. Lives fall. Compton Indian street foods in Amadevan, India. No. Amadevan, Amadevan, India, Amadevan. You didn't say that in the first one. Amadevan. Amadevan, India. My Amadevan. My Amadevan. My Amadevan. Your Amadevan. His Amadevan. Their Amadevan. Everybody's Amadevan. We are Amadevan. We are Amadevan. Here we go. Ganga about it. In Antibas, it's a full-fledged restaurant. They serve koha in many varieties with a addition of curd, sheeps, corn, pastas, beetroot, and a lot more. All the koha fans must definitely visit this place. Here is the mall of Khakran. This place is a legendary place started by Indubain as a sata. This place has gotten popular with time due to its tasty flavours, tastes, and variety. Do visit this place if you wish to take a bus to for a long journey. Sathya, I'll stay for a while. See that restaurant even before there's a lot of people. I'll be doing that. Not a bad tour. It's a pasta. It's served with spicy chilies, based on chutney, rock-upire, fattig, and green cumin.  It looks like cinnamon twists from Taco Bell. Right? Yes. This is cow or bread. Mumbai. Wow. Take that bread, soak up those juice. This is for you in Antibas, if you are craving kohe vada pav. We can assure you that no one can come to Maharashtra because of the vada pav and they have their own crazy Bombay vada pav at their disposal. That was good. Not just the Jalebi, there's a very special one which has its own heritage value. Oh please don't get a flop. Everything about that dessert is happening. Jalebi and the very good one. Let's stop having a legacy of more than a century. How many Indians try on the hood is that? Every one? How much? Hey, hey, multiple, my God. Yes, the restaurant has been renewed, but your tendency stays forever. For your demand, if you are someone who needs to have... I'm guessing it's a variety of puny puris. It is like a mini chew ball. Yeah. So you can ask for your choice of puny puris. It is puny puri. Can you like it? The Vada pav is a snack, vada, dacquoise, and tofu. But not if you ever want to know what is the origin of the same, you'll also see pictures of the Vada pav. What were those? That was good. That was good. This is the most popular Zabeli. That looks delicious. The one which serves in the Vada pav and the one which is Zabeli. That looks so good. Also pay attention to the Mexican Vada pav, which has the lungy touch of bell peppers. Let's say Mexican. This line may not be clear, but the people that have made that dal vada believe it's producing dal vada in vada. But so we have a combination of onions, side chilies, and some cutting chives. Y'all just eat raw onions. A solution which needs to spell vada. Kabab! With some onions dressed with chives. And you have a burrito. Drizzle me in that white sauce. That's a burrito. You guys have a burrito. I straight up need that. That looks unbelievable. What was that burrito thing? You gotta figure it out and make it. It's called, I'll tell you. The way the size came out. It was gorgeous. Yes, it was just like that. That's kind of... Am I too far? Yeah. That's a burrito thing. That's kind of... Am I too far? I think so. There. Somebody write it down. I'm not on a Frankie. I'm not on a Frankie. That's just the place. That's not the thing. I'm not on a Frankie. I'm not on a Frankie. I'm not on a Frankie. Yeah, that looks so good. First time I've actually seen something that looked like a burrito. Yeah. From what I'm told. Have you been keeping it down now? A burrito. Because from what I'm told. It's interesting. No, they don't do that. No. And it's interesting because like roadie looks a lot like tortilla. It's essentially a flaky tortilla. A flaky tortilla. And many of the foods are very similar in the terms of having sauce bases and a lot of bean connections. Yeah. So it's bean connections. I was going to sing the rainbow connection like I'm at the frog, but you know what went into my head instead? What? Why? Two birds. What? Suddenly up here. Every time. I think he's just lying here. You sound like Kermit with a cold. They long to be close to me. You sound like Kermit with a cold. I think in that video, but especially that dang burrito thing. I want to bury my nostrils deep into this. Oh, but what about that sandwich that was all? Yeah. The patty bun. With the sauce. With the sauce. The head of the sauce. No, this is me flipping it onto the sides. Smooth like butter. Whoa.


You might be trying Chinese herbs or acupuncture for the first time and you don't know if it can help you Maybe you have a complex digestive illness or fibromyalgia or something else complicated going on And you've heard all these things, but you don't know what the truth is You're wondering do I just go for one treatment? Do I go for three for five like how long does it take to get better? In this video, I want to share really what are the top 10 most common things Common conditions that acupuncturists and Chinese medical doctors treat and get results for so if you have One of these and you're thinking of it. Hopefully this should be a green light to at least try it because there's a lot of Evidence that it works for it and we have a lot of experience treating these things Hey, I'm Alex Hein current doctoral student in traditional or classical Chinese medicine Author of the book master the day before we go on I've actually included a free cheat sheet down below a Beginner's guide on how to add 10 years to your life with traditional or classical Chinese medicine It's right there in the description box Alex Hein com for it slash free that'll bring you to a page and you just punch in your email and you'll get that there So go check that out So the Oregon College of Oriental Medicine a school like a sister school of mine here in Oregon Did a study on the top ten conditions that their Students see in the teaching clinic as well as what they see in their clinical practice later And these are the top ten conditions that they see typically first So the students tend to see number one musculoskeletal pain to anxiety three fatigue four headaches of various kinds five digestive conditions six depression seven women's health eight insomnia nine skin problems and Ten frequent sore throat cold cough upper respiratory infections now in terms of the Conditions that are successfully treated of the patients in private practice after these are the top ten that acupuncturists Generally nationwide tend to see and treat quite a lot The first one here again is pain The second one is women's health the third one is emotional disorders stress PTSD things like that The fourth is digestive conditions The fifth is musculoskeletal disorders in pain The sixth is allergies The seventh is insomnia The eighth is stress related pathologies The ninth is respiratory disorders and the tenth is acute injuries. So typically again, we're thinking of pain or inflammation So again, that's just kind of like the down and dirty the top ten list of what we tend to see in practice And what really nationwide we tend to see as acupuncturists or Chinese medicine doctors So obviously if you have something on that list Great go see an acupuncturist if you don't I still would You know, this is just to me trying to present to you the research so that you can have a little bit more confidence and understanding But we treat all kinds of complex pathology too And it really is up to the practitioner or the doctor and their training regarding whether or not they can help you Successfully treat that condition. So again before you go check out that list down there below It is five daily habits to help you add ten years to your life with traditional or classical Chinese medicine My own tips there below and you can check out my last two videos right here and right here


Welcome to Spotlight. I'm Liz Wade. And I'm Robin Basilen. Spotlight uses a special English method of broadcasting. It is easier for people to understand no matter where in the world they live. It is a normal Monday morning in Nairobi, Kenya. It is the beginning of a new work week. The streets are busy with traffic.  But on this particular Monday morning, there is more color than usual. At Nairobi's central bus station, a large group of men and women carry many brightly colored yellow balloons. They offer the balloons to people traveling to work. People see the balloons and smile. Soon, many more individuals are carrying yellow balloons. Some of the people holding a balloon get on the buses. Others begin walking. Slowly, the balloons spread around the city as people continue on their way to work. These yellow balloons are part of an art project called Monday Morning. Today's spotlight is on this living art project. Yasmine Arbolita is an artist from New York City. He uses art to examine cultural issues. His art projects ask many questions about society, politics, and morality. Arbolita believes that artwork is more than just something to look at. So he presents his art projects in interesting ways. In 2011, Arbolita launched a new art project. He called it Monday Morning. He knew that many people around the world do not like Mondays. Monday is the beginning of a new work week. It represents the end of the weekend, the end of people's time off of work. He told the magazine Up, Nairobi's urban perspective, that he got the idea for Monday Morning while working in India. I was sitting on the grass thinking. Then an idea came to me. Parties usually mark our happiest times in life. And what is the one element that symbolizes parties? A balloon. Combine that symbol with the usual negative feelings surrounding Monday mornings. This was the perfect way to make art with a positive influence. Arbolita wanted his art to change how people felt about Monday Morning. He decided to do the art project in seven different countries. In each country, he would make one Monday morning feel like a party. He wrote about his plan in the Huffington Post. My party would include as many people as possible. My first interest as an artist is how people physically relate with art. So I decided to give out 10,000 brightly coloured balloons on a Monday morning. I would do this in the transportation centre of a city. And I would do this in cities around the world. I would give a balloon to each person going to work. And I would ask them to hold it until he or she got to work. Arbolita has now launched the Monday Morning Art Project in three countries. India, Japan and Kenya. Before each project, Arbolita stayed in each particular country for weeks or even months. He learned what it was like to live in that country. And he tried to make each project fit the particular country. For each country, Arbolita chose a different balloon colour. He chose the colour he believed best represented the country. In India, he used orange balloons. To Arbolita, orange represented the spices Indian cooks used to add taste to food. In Japan, he used green balloons. The colour green represented Japan's success in developing green technology. Or technology that is good for the environment. And for Kenya, Arbolita chose the colour yellow. This was because he loved the golden Kenyan sun. In each country, Arbolita also organised a large group of people to help him. On the day of the art project, this group of people met at the city's transport centre. Together, they brought 10,000 balloons. They gave one or a few balloons to thousands of individuals on their way to work. Slowly, the balloons spread all around the city. As more people saw the balloons, more people's mornings were affected. Arbolita believes that the Monday morning experience gives workers a positive start to their day. He also believes it helps people think about how life and work relate to each other. He told the Japan Times. Balloons symbolise celebration. They make us remember happy times in our lives. The clash of the expected with the unexpected creates interesting connections. These connections cause people to question established ways of understanding things. This art piece opens up discussions about what we think and feel about work. There is a difference between the repeated nature of work and the playfulness of a balloon, or thousands of them moving through a city. This difference fills the art piece with the ability to shake the established understanding of a Monday morning. In Kenya, the Monday morning project did just what Arbolita hoped. On November 7, 2011, Miriam Muthoni was on her way to work in Nairobi. Suddenly, someone gave her a gift of balloons. The gift surprised her. She told the Huffington Post news organisation, I feel it has given me the energy to work. It may be a blessing. But Arbolita wanted to do more than just explore established social ideas about work. He also wanted to change how people think about and define art. He told the BBC, We are celebrating the people as they go to work. And we are explaining that art is not just a photograph or a sculpture or a painting. It is also a planned movement of balloons as they spread through a whole city. The Monday morning project had even greater meaning in Kenya. While Arbolita was planning and organizing people for the event, terrorists announced that they were going to attack the city of Nairobi. And on Monday, October 24, there were two bomb attacks in Nairobi. One of these attacks happened at a bus stop. After this, many Kenyans were afraid to ride the buses again. However, they still needed to go to work. So Arbolita kept his plans to perform the Monday morning art project. On November 7, two weeks after the bomb attacks, he filled Nairobi with balloons. This act gave people balloons, but also a new hope. To them, the balloons were a sign of peace after the terrorist bombings. Arbolita told the Huffington Post, I think fear creates negative energy. This needs to be opposed by something beautiful and colourful. Something that speaks to the heart of the people and beauty. And I think that is what art is about. The writer of this program was Courtney Scott. The producer was Mark Drenth. The voices you heard were from the United States and the United Kingdom. All quotes were adapted and voiced by Spotlight. You can find our programs on the internet at www.radioenglish.net. This program is called Monday Morning Art. We hope you can join us again for the next Spotlight program. Goodbye.


but we start with a very special first guest for our safety. I'm so excited about this nine-year NFL veteran, Patriots, Panthers, and the Indianapolis Colts, of course. You can hear him on his man-to-man podcast, which you can hear all over the place. And he is a fan-dual partner that you can see, hopefully, right here, every week this season. If I don't scare him away, please welcome Formula One enthusiast, Darius Butler. Hello. Yeah, hello. Okay. Good to see you. It's been a minute. Yeah, Darius, I literally don't recognize you without that Marlin's hat. What is going on?  A lot of people don't recognize me without a hat, so I had to switch it up, take it off for today for your show. But congratulations on your new show as well. But I'm happy to be here and fun to be here. One more sleep, still football. Can't wait. I cannot wait either. And you're busy. You got a espiango. You got a lot going on. You got, I think, Italy F1. We'll talk about that in a little bit. But we got to hit the headlines for the people out there. You guys can tweet the show. Tell us what you want to hear about. But, Darius, you were once upon a time Tom Brady's teammate up in New England. Weird offseason to say the least. I did think it was kind of crazy to read that Todd Bowles was asked if Brady was all in, which, of course, he brushed off. What are your thoughts? Do you have any doubts? I mean, no doubts. Talking about Tom Brady, like he said, he's 45 years old. No one else. I actually had a teammate in his 40s, Adam Venetieri. And nobody would question Adam about, you know, his preparation and what he had to deal with in the offseason. And Tom Brady, you know, that's literally the greatest of all time. Obviously had to take some time away. But when he got back in the build, I'm sure he picked up right where he left off. All his teammates have faith in him, trusting him, same with the coaching staff. He is a coach on the field. So no doubts about time at all going into this season. I think the Bucks are supposed to do their compete to win every game. So I know if I'm in that locker room with Tom, I have no issues with him taking that little break. I'm sure he'll be the same Tom that we saw last year, which is ridiculous at 44 leading the league in almost every quarterback metric there is. So he's a unicorn. So there's no questions, no doubts with him at all. It's impossible to know. He's the only one that knows if he's all in or not. We'll see how it plays out in the field. I do hate that. Of course he is. If even if he is all in, he's 45. He could be mentally there. And his body eventually could fall apart. It could be the offensive line like back up in New England, he could tie his shoes behind that offensive line. That might not be the case this year. Even if his level of play falls a little bit, as it should because he's strong arming father time, people could still point to that and say he's not all in. So I hate, you open yourself up to perception when you don't go to OTAs, when you're in Qatar on camels taking selfies or taking time, whatever you're doing, he's dealt with distraction though Darius so much in his career. Deflategate, family, we saw he won a, he's always sort of made it. So whatever might be going on, I have no concern, but I do think at some point the level of play has to go on and sort of go on decline naturally. Are you worried about that at all? Sean Payton yesterday said it's the Saints that are gonna win this out, then the Bucks. What are your thoughts? No, I mean, I'm not worried about that at all. You know, as a kid, literally, I watched Tom Brady growing up playing, winning Super Bowls, winning, played with him for a couple of years, left him, got cut from New England, had a nine year career, had been retired for five years and his dude is still in the MVP conversation. Like, I mean, father time is a million 37 in one right now with Tom, so I got no doubts about him. He's a, he's a, he's brilliant at eliminating distractions and taking care of what's in front of him. Being, taking that next step every day and practice, the preparation is, no doubt it's about 12 at all. Come on, Kay. You've been around the game long enough, what are you talking about? But tell me, when does it, how does it end? How does it end on his terms? I mean, I thought it ended last year, honestly, but I mean, it's going to end on his terms. I think this will be most like this last year. Obviously he's got the TV deal, you know, lined up already, who knows what's going on, you know, at home as far as I'm sure his family, you know, kind of excited maybe that he'll be retiring. So, I mean, your guess is as good as mine when it is. I think he said he wanted to play until 45 or 50, who knows, but he take care of his body. He's playing at a high level. So maybe I see this year as really being his last ride, though, on the football field. I'll be sad to see we've got to enjoy every moment. Big game against the Cowboys to kick off the 2022 season. All right, from an OG to a young cat, let's talk about Trey Lance here. He was named the starting quarterback for the Niners. Are people overblowing this? If you're in that locker room, how messy do you feel like this will get? I mean, that's tough. I, you know, nine years, been in nine different locker rooms, but I've never been in that 49ers locker room and everyone is unique.  He's going to be your future. The GM and the head coach, they're locked up long term. But if he comes out and struggles early on in the season, you know, five, six games into it, that locker room is going to start looking around because we're seeing Jimmy G practicing, you know, he'll probably be on the scout team going against the first team defense.  But as a player, you know how precious, you know, every year is out there. So it's harder to trust that process when you're a player and it's almost impossible not to look around and say, hey, you know, we know we have a guy we can win with, but Trey Lance is a reason they traded all those assets and jumped up to number three to draft him. But he hasn't played, he hasn't played a lot in this NFL level. So it's going to be a learning curve. I expect him to struggle early, but hopefully he shows improvement and get better week by week and the Niners got a stick with him. But it's a very, very weird dynamic in that locker room. Couldn't imagine being a teammate in there. And now Jimmy G, you know, he's on a one year deal, basically no trade clause, so he will be there. So now Trey, you know, he kind of got to look over his shoulder all year and all those quarterbacks last year, they struggled. You know, outside of probably Mac Jones, but Trevor Lawrence, Zach Wilson, Davis Mills had a decent year, Justin Fields struggled. You know, all those guys struggled. So I expect Trey Lance to have some sort of struggle, at least at the beginning of the year, but hopefully his talent kind of takes over. It's not fair or reasonable to expect him to not struggle. He has less experience than everybody else. He's going to have those rookie problems. And you're saying that you've never been in that locker room. Joe Staley was for 13 years and he was on local radio yesterday. And I thought it was so interesting because he, you know, he admitted like there's going to be struggles. And if they're in a locker room, you're saying we have a Super Bowl team. Why are we waiting to develop a quarterback if you have a guy that's taken us there? Like we want to win a Super Bowl. So I thought it was interesting about the players. I will say this and I like, I don't know if I'm being too optimistic about it, but it doesn't work everywhere what's going on. And it could get messy. But if there was one player that I would be like, Jimmy Garoppolo is that guy. This is not Brett Favre and Aaron Rodgers. It's not, Jimmy Garoppolo is not out there politicking saying like, I want to play, put me in. It's a perfect situation. You have a Super Bowl contender. You have two great options. One, if it doesn't work out, you have one that has the experience that the players might want. So it's almost up to the players to sort of tell themselves be patient and let it out. But Jimmy Garoppolo redid a deal to stay there fully knowing what the deal is. And he's the kind of player I think, the rare player who's like, whatever, like I understand the situation. This is the best situation for me. You might use me, you might not. And that makes it okay. And it might not be okay in 31 other locker rooms, but I think it might work in this one. Yeah, contrary to some reports that came out, I think Jimmy G is a really good teammate. I do think the locker room loves him, which can kind of be more of a problem, I guess. But Jimmy G, he's been a good soldier thus far. And he knows, you know, next quarterbacks, they're always in high demand. So he knows next year, there'll be a spot for him. But it's going to be tough. It's going to be a weird dynamic. The only thing that can make it easier is Trey Lance playing well and improving and showing improvement every week. And this team, like you said, this is a team that is built to contend for the Super Bowl. This isn't the, you know, the New York Jets or the Jacksonville Jaguars. Like you have top tier players at every position, Fred Warner, Trent Williams, Nick Bols, Jimmy Ward, Debo. Like these are top tier players. And so he's going to be in a good situation from that standpoint. You got Kyle Shanahan, who's obviously a show. He's a great play caller in the league. You got really good receivers out there. And it's a receiver that's kind of blown a lot of people away this preseason in training camp. And that's Brandon IU. I think Brandon IU could sneakily be probably a wide receiver one even over there. Debo is obviously an amazing weapon in the backfield and out at receiver, obviously George Kittle as well. But everything I've seen and heard from Brandon IU this preseason, I'll be definitely bullish on his production this year. Do you think the Niners make the playoffs? You know what, honest, I'm gonna say no. I'm gonna say no.  I think the Rams will win that division again. And you know, I got high expectations for the Cardinals as well.  I think Calamari takes a step in that off the field in tangibles leadership wise. Obviously they'll be getting Hopkins back after a week six, I believe. You brought Hollywood Brown over who did some amazing things in college with Calamari at quarterback. So I ain't got JJ Watt back healthy again. So I like the Cardinals this year as well. And once again, this is gonna be really Tray Lance's first year. And he didn't play much in college. So it's really almost gonna be like his junior, senior year on the college football field but he's gonna be playing against pros. So unfortunately, if I had to make a bet today I would say the 49ers don't make the playoffs. 49ers missed the playoffs. Brandon Iuk over a thousand yards ish. It's what you're saying, wide receiver one out there. I would say around that thousand yard mark. Maybe I would say over, I don't know what his prop is right now, but I would say he's in that 900 range. I love it. All right, let's go down to Miami we're doing all the hot topics here with Darius Butler, Patriots never loved to play there. They lose there pretty much all the time. And now they're opening the season down in Miami. They do, it's just, it's very weird thing that happens. They have to deal with a really creative new head coach. They don't know what they're really getting. And then I don't think New England's ready for that speed that Kyrie Kill's gonna bring. So to the wild card here in the situation I have always defended him. I've always had this soft spot for him. What do you need to see from him early this season to convince you that they are a playoff team or at least ready to contend in that East? You know what, early I won't react too much to what he does early in the season, but once again, just progression. Just want to see him continually get better. And I'm a lifelong, I'm a South Floridian. I'm a lifelong Dolphins fan, a Dolphan. And Tua may be our guy, right? He drafted him top five, the pick before Justin Herbert. So the pressure's always there on him. But now the team is behind him. Tyreek Hill came over and he's been singing his praises from day one. Maybe a little too far at times, but singing his praises from day one, they showed up at offensive line. Last year they were at the bottom of the league when you look at 11 personnel. That's basically when you deploy three receivers out there. And obviously we expect him to have much more that this year with bringing Cedric Wilson over from Dallas, Jay Lenoado going into a second year with Tua. And then obviously the amazing dynamic weapon that Tyreek Hill is, he's kind of a one-on-one at that receiver position. So all the pieces are there. Mike McDaniel, this is his first year as an actual play-caller and coming from San Francisco. You know, they like to lead and start things off with the run game as well. I think he came out and was quoted a couple of days ago saying they wanted to run the ball 30 times a game, which I wasn't really much a fan of hearing that, but they'll be having a lot of speed out there and Tua, everything's there for him. And then on the other side of the ball, the defense. Josh Boy, he was actually my coach when I was in New England, he was my DB coach. Now he's a DC over there. They got a lot of talent over there as well. Xavier and Howard, Javon Holland, who will be a super star at the safety position. And guys, they're really multiple, do a lot of things up-front and on the back end to confuse quarterback. So the expectations are really, really high for the Dolphins. High enough for me that I may even sprinkle something on them to win that division. I know everybody's high on the bills. Talk to me. And I am as well.  You lose Brian Debaldo, so there are, there is some question marks there. So I may sprinkle something on out at Dolphins winning that division. I don't even know what to say. But like, I'm like, I'm like, I'm like, is that like a Florida thing? Like, are you thinking about this clearly? Are we objective? Like, how, what, what? No, no, I'm gonna be honest with you. No, there is some bias here. So maybe don't tell me here, but there is some bias and I've been looking for, like once again, we've been looking for this type of offense. Tyree Hill, we've never had a weapon like Tyree Hill in Miami. Nobody saw this coming last year when the year ended that we'll have the cheetah down in Miami. So yeah, my expectations are way up here. So I'm there. I wouldn't advise you to tell me because it builds, they are that deal this year, but I love the Dolphins as well. They're super overhyped quickly. You keep talking about the speed in Tyree. What do you make of this narrative that's been out there the entire off season since that deal went down that Tua can't get the ball to Tyree. So what's the point? What do you make of that? Much to do about nothing. Tua can throw the ball. And Tyree Hill, he's not just a guy who just you got to throw in the ball six yards down the field. He could kill you with crossing routes, slants, screens, speed sweeps. Like it's just so many things that you have to plan and prepare for as a defensive player, as a defensive coordinator when 10 is on the field. And it's things like, you see certain, you see speed every week, it's NFL, but that Tyree Hill speed is something completely different. And you know, Patrick, my homes will miss it. Obviously, the chiefs will be okay. My homes, Andy, Rhee, Eric, being to me, they'll be all right, they'll be good. But to have a weapon like that for Tua, it's just gonna open up the field for Waddle, Gisecchi, Wilson, Moster and all these other guys. You're obsessed with the Dolphins, I love it. Really, really excited. I'm all chips in on the Miami Dolphins. I'm excited that you hit me with a much to do about nothing, Shakespeare out of Darius Butler this morning. I got range, baby, I got range. All right, quickly, we're gonna go through some of the games, the big matchups. Week one, the NFL season starts tomorrow. I'm so excited. Let's go to the AFC Steelers. Bengals, what do you got, Mr. Drabisky starting? Will the Steelers be able to get something done? They'll compete. They'll compete. I got the Bengals winning this one. I would never, it's tough to bet against Mike Tomlin in the Steelers team where I was gonna come out prepared. He named Mitch the starter, you can't doubt him there. Weapons on the outside. Obviously, Nigel here is the weapon in the backfield. Defense is always Blitzberg out there in PA. So they'll compete, but I got the Bengals. A lot of firepower and they got better this offseason as well. All right, revenge game, which might be overplayed, but I'm here for it. Baker, of course, going up against Miles Garrett and company. He is getting the start. So when it comes to playing a former team, who has the advantage? Is it the quarterback who's familiar with the defense or is it the coach? In this case, Mr. Stefansky. You know, the situation is situational. But I think Baker, he's gonna be fired up, but I got the Browns actually. I got the Browns in this one. Just that team. And I like, I love Jacoby Brissette.  And he's, this whole offseason, he's kind of been preparing. The Browns have been preparing to have him start at least a few games. He'll be starting at least the first 11 games. So he'll be prepared. The game plan will be tailored for him. Nick Chubb, Kareem Hunt in the backfield, invest a lot of money into that talent offensive line. Great defense as well. Baker Mayfield, I think, will still be figuring things out the early portion of the season. So I got the Browns in this one. Christian McCaffrey's healthy. I think the Panthers are going in the playoffs. I like the Panthers a lot. If he stays healthy, you know, that's a big if. Yeah, number two total defense. Like, if he stays healthy, how good does Baker even have to be? Not that great. And DJ Morrill touched, you know, a ton of rocks for him for over a thousand yards no matter who's throwing his way. So I'm excited about the Panthers. Chiefs at Cardinals. Great offensive matchup. I love this. You know, I love fantasy football. What do you got on this one? I think a lot of points would be scored. I got the Chiefs in this one. I got the Chiefs in this one. And Patrick Mahomes, he's one of those guys that's like, everyone is off season, went out of their way to kind of add some fuel to his fire. One of the most talented players that we've ever seen touch the field. Once again, brilliant play callers. They went and invested, got MVS from Green Bay, drafted Scott Moore. You just got Travis Kelsey is still there, who's a top, probably seven, eight receiving weapon period on the offensive side of the ball. Well, some moving parts on defense. Obviously Cardinals will be missing DHOP for these first few weeks. So I got the Chiefs in this one. Bills at Rams. I cannot believe this game is tomorrow. We have been waiting and waiting and waiting. What are you looking at in this game? Who do you think comes out on top? It's here. Finally made it. I can't believe this game is tomorrow either. And I also can't believe that the Super Bowl champs are underdogs in this one. I got the Rams in this one. I think the Bills of Mr. Davies White got some young guys that'll be starting out there cornerback going against the Sean McVay offense, Matt Stafford, Cooper Cup, be on the same page their second year together. Allen Robinson coming over as well. McVay does a lot of things that make you think and kind of have a little hesitation as a defensive player as a D-back. So I think the Bills will struggle with that. Josh Allen and that offense, obviously they're going to be amazing. And the Bills defense is very good as well. But young corners on the outside, I think Sean McVay, Cooper Cup. Yeah, Stafford and Cole will kind of have their way. I got the Rams in this one, straight up. I love the Bills. So much hype about them, but that secondary is their glaring hole, right? And for Davies White, one of my favorites, but he's got to be out there. Or Cooper Cup's going to have 150 yards, 200 yards in his first game, 24 hours here in LA. Quickly, Jalen Ramsey. You know D-B's, I got to give, I see the best in the game right now. He's the best. You know, he did what he does. And then now that he goes and plays on the inside as well. And he's a slot defender. He can blitz, he can tackle, he can cover obviously. I would definitely have him in that conversation for, you know, the best in the game. Before I go, I wasn't kidding that you are a Formula One enthusiast. Maybe expert even. You are so engaged in fact that you watch the qualifying runs. I don't even know what that is. Who do you like this weekend?  I'm sick. Yeah, clearly. Who do you like this weekend in Italy, I think? Yep, it's I and Grand Prix. I see you. The Tafosi will be in full force out there. Ferrari, obviously that's their home. And then Ferrari has done great things with their car, but they've had a lot of mixups on strategy and leadership, I would say, when the Grand Prix actually comes about. But it's hard to bet against Max Verstappen and Red Bull. You know, he's been the best driver on the grid this year. They have the best car on the grid this year. And their management.  You come in with a game plan and you have to just and execute on the fly and Red Bull does that better than anybody else this year at least. So, you know, Max is the easy bet here. And once again, you can always bet on something going into qualifying and then obviously at the race as well. But I got Max and Red Bull winning. They're running away with the Constructors Championship and the Drivers Championship right now. So I mean, that's that's an easy bet right now. They're like inevitable this year. I don't know what you said, but I'm here for it. You are an expert in everything football and F1. Listen to your man-to-man podcast. It is amazing. We will have you on in a little bit. Big Dolphins fan, Darius Butler. Thank you very much. So good to have you.