Ladies, gentlemen, boys and girls and children of all ages, you're now tuned into the Prince of Investment coming to you guys and girls live from a beautiful city in state of Denver, Colorado. Don't forget to hit that like subscribe button and share button. And as always, I don't have a lot of time and I definitely know you guys and girls don't have a lot of time, so we're going to jump straight into it. So ladies and gentlemen, right here, I did this episode, I want to say to ladies and gentlemen, boys and girls and children of all ages, welcome to the Prince of Investment. I'm your host Prince Dice coming all the way live from a beautiful city and state of Denver, Colorado via Honolulu, Hawaii. Ladies and gentlemen, don't forget to hit that like subscribe button and share button. And as always, I don't have a lot of time and I definitely know you guys and girls don't have a lot of time, so we're going to jump straight into it. As you guys and girls can see Berkshire Hathaway with hail May 6th about a month ago in Omaha, not a month ago, a couple weeks ago in Omaha, Nebraska. You've seen everybody talk about it. And you guys and girls know I've been going to Berkshire for seven years now. I started back in 2017 going to Omaha, Nebraska. And I was there for a 2017 meeting, the 2018 meeting, the 2019 meeting. Then we all know what happened in 2020, 2020, kind of around me a little bit, but we all know what happened in 2020. So they didn't have a meeting in 2020. They did not have a meeting in 2021, but they had a virtual, they just did it online. I think they had the same venue, but Warren and Charlie Walker just got up and just spoke. They didn't say anything. They just got up and spoke. So 2021 and 2020 didn't have anything. 2022 was the return. I was there for that. It was a little sticky in 2022 because you know, you still had the COVID restrictions. You had to be vaccinated. You had to have a vaccination app, not the clear app to make sure you was clear to come in. The vibe was a little bit off, but it returned in 2023. So in 2023, we're back. Here we are. This is like the first time we was really back without the COVID run, without anybody getting scared about anything, without, you know, we just kind of felt like, Hey, we're finally back. Now me personally, I wasn't back all the way. I had a crazy schedule that week. First, I started out. I was in DC at the Jell-Off Boys and Girls Club awarding stocks and books to kids. So congratulations to those kids graduating the Wesley learns book program teaching kids about investing credit and insurance. And then soon after I left the Boys and Girls Club, I drove down to DC to see a good friend of mine's retired from the United States Navy. I spoke at his retirement ceremony. And when I got done with that, I immediately got onto the plane and flew to Omaha. So I got into Omaha about nine to 10 o'clock at night. By the time I landed, by the time I got my hotel, by the time I got my rental car, by the time I got to my room, grab something to eat, I think I laid it down, laid down about one o'clock in the morning, Omaha town, because you know, I had had a little layover down in Atlanta before I went to Omaha. So the first day was extremely tough day for me. Anybody who hasn't been to Berkshire, the doors open at seven, if I'm not mistaken, in the meeting, I think you start off with the movie, which starts off about eight o'clock, a private movie that they show. So it goes off on seven o'clock in the morning and it then goes to eight o'clock, right? So this is when they open up the door. So people would be out there around five, four, three, two o'clock in the morning, two o'clock in the morning, because of the seats are first come, first served. There's no assigned order. Of course, they have some reserved seats for a chairman and, you know, people who's high up in the business. But other than that, they don't have any, you know, it's just kind of open for shareholders. And they don't allow you to save seats and then look for seats, things like that as well. So the thing about it is, you know, I didn't get there that early, because it was one o'clock in the morning about the time I laid down. I got up about six or seven. Finally had to get my suit out of my suit. Now, my suit out of my suitcase, not my suit out of my suit. Get my suit out of my suitcase. Finally got everything, you know, straightened out, made myself presentable, took a shower, took a shower, had a little snack in the morning, and pressed out my suit and got on my way. So I got there a little late and I did my run arounds, right? I didn't get a chance to do any interviews this year. I didn't do not one interview, which is anybody that really follows me every year. I do interviews, I do documentaries, stuff like that, right? And I didn't get a chance to do one, two, three, four, five days. I was three days I was there. No interviews, zero, none. I didn't really have the time this year because of my schedule to line everything up. But I walked around the showroom floor. I didn't get there on Friday. I got there Saturday morning. I usually get there three days early. So everything was off me to actually get there, but everything seemed to be back in full swing.  So everything seemed to be pretty good and it was kind of back. So now we're going to jump into the actual meeting in a minute. Y'all stay tuned until your actual meeting what was said, what I heard takeaways I had there. But one of the things I noticed as well is by me jumping around from DC, driving three hours of Norfolk, then jumping off of the plane from Norfolk to Atlanta, then from Atlanta to Omaha, then traveling, then getting set up by the time I got to Omaha, Nebraska, ladies and gentlemen, it was, you know, I was extremely exhausted because that week was an exhausting week. And I didn't have anything lined up for interviews because I didn't really have a chance to get there early like I usually do. I would usually get there like on a Thursday, get settled before the rush comes, a Wednesday sometimes, and settle and be there for four or five days, almost a whole week, just hanging out in Omaha, meeting people during interviews, talking to people and things like that. Now, I will say this year, more than ever, one of the first things I noticed is Greg Abel. Greg Abel is the successor of Warren Buffett. And the thing about Greg Abel is Greg Abel is he was shown a lot this year. They started to bring him out about two years ago, but they showed him a lot this year. You know, Charlie Munger is 99, if I'm not mistaken, and Warren Buffett is 93, if I'm not mistaken. So he's getting up there in age and you're talking about Charlie Munger, he is getting, you know, definitely he's almost 100 years old, but he was there. But anyway, everybody was excited. Why? Remember those banking crisis we had? Who remember Silicon Valley Bank? We woke up one day, SVP, I think it was the 14th largest bank in America that most of us probably never heard of, unless you're in the venture capital world, blew up. This company blew up and did what, ladies and gentlemen, blew up, went all over the place, and nobody knew what would happen. Nobody knew what was going on. Then here comes First Republic. Then here comes another bank. So then the FDIC jumped out there, hey, everybody calm down. Why did this happen? What did Warren think of this? He set a very key note. This key note stuck with me because it goes to today. Today, we just heard everybody talking about the debt ceiling. The debt ceiling. Will they raise the debt ceiling? Will the debt ceiling be lower than where the debt ceiling will do this, right? He said a very famous thing in true Buffett fashion. He said fear is contagious. When people get scared, that's what have a run on banks. Run on the banks are, you know, when everybody runs to the banks and I get the money out for the most part. But what causes? What's the DNA of a run on a bank? The DNA of a run on a bank is everybody getting scared at one time. Long story short, Warren leads us in traditional fashion and saying never bet against America. And another thing is his stock that he holds, a master stock that he holds is Bank of America. He sold a lot of his companies. He showed us soldiers JP Morgan that he had for 25 years, but he kept Bank of America. The thing that made Bank of America so interesting is it is the bank that everybody ran to. When everything started to collapse, everything started to go left. Everything started to not look so good. Everybody ran to Bank of America. That stuck with me as an investor to go, hmm, Bank of America is a safe haven and it pays dividends. Let's take a look at this. If you look into the financial industry, as usual, as we get into more deeper things of what happened and what Warren said at Berkshire and actual financials of the company, I had this eerie feeling this year at Berkshire, but what would happen if Warren Buffett passed away? What happened to the Berkshire Hathaway stock? But we lose trust. I know they got the successor. They got a successor plan. They have already noted that Greg Abel is taking over, but how will shareholders really receive Greg Abel? I don't think I've seen Greg Abel speak that much. I don't think I've seen Greg Abel talk that much. I don't think I've seen Greg Abel say anything for the most part, right? Greg Abel is someone that I don't know. I don't know what investors trust. I know he came from the Berkshire Hathaway energy sector. But when he gets in, like Warren, he gets in and he talks about his mistakes that he made and things that he missed out on and his thoughts on Tesla, things like that. But it leaves people the question of Warren is allowed to make mistakes. He's 93 years old. He's the greatest investor in American history, if not the world of our time. And people are like, hey, Warren buys it. It's a good thing. If Warren sells it, maybe I should too. That's the notion in the investing world. But if Warren passes away today, tomorrow, things like that, well, will shareholders lose trust into Warren? I mean, it's a Berkshire Hathaway. You know, you're talking about it, ladies and gentlemen. I mean, in the next 10 years, it'd be pretty shocking and astonishing if we have Warren Buffett and Charlie Munger still here in the next 10 years. And even though Warren has said it a million times, I'm not running the day to day. I have Ted and Todd Combs. I think it's Todd Combs, Ted Combs, Ted and Todd Combs and all the great people behind the scenes that are running Berkshire on the day to day. They may check things with me. I'm not doing this much. Will shareholders take that? See, many Berkshire shareholders bet on Berkshire because they feel as though, hey, it's a good bet. It's Warren Buffett's company. He's at the helm, right? But we all know the market doesn't trade off of fundamentals. You can have awesome fundamentals. I've seen companies where they've had amazing fundamentals, but their stock is trading low, inefficient market.  Stock is trading high. High multiples, depending on what people feel, what people think. We all know the market is ran by emotions, not by fundamentals. And what will happen? What will people think? What will people say if Warren Buffett is no longer there? That was my biggest question this year. And I felt like Warren wanted to let everybody know he was in, everybody was going to be in good hands. But once something happens to him, you're 93 years old, I don't know if he has a terminal illness or whatever, but we all know that eventually something's going to take you out of life. Whether you're in your 30s, 40s, 50s, 60s, 70s, kids, teenagers, we all are not going to be here. We're all just living here to have an experience we don't know when that will happen. But as you already know, as you increase your age and you're 70 something years old, then that increase your probability of something happening to you even more, right? So that's always been my question, ladies and gentlemen. What will happen to Warren? What will happen to Berkshire once Warren Buffett and Charlie Munger are no longer? And you have the two new faces of Berkshire led by Greg Abel. And now Greg Abel is speaking in front of the world. Well, people trust him. Now Warren is like everybody's grandfather. He's like the old grandfather, if not great grandfather to many investors. What would be said and done when he's done on here where we really trust him?  He talked about his earnings. He talked about some of the bread, the bloodlines of his companies. He talked about the US economy, how he felt about it, how he felt things would be in 2023 and so many more things, right? And I want to get into those. But before we get into those, I want to take a break, a very big break, not a break break, but a quick break, a very quick break. Why did I say big break? I'm going to take a very quick break and after that break, we're going to come back with more of the Prince of investment right here with Prince Dykes. Now, the first thing I learned a long time ago by attending Berkshire Hathaway annual meetings was how does Warren Buffett move when he make acquisitions? They said, sometimes this kind of blew my mind when I heard this for the first time. You could buy things, you can buy things with cash and you can buy things with stock. When I saw that Warren brought things with stock, I was shocked, right? I was shocked. I was like, wow, that makes sense. You can buy things with stock instead of buying things with actual dollars. So the notion was when Warren buys things with stocks, he believes his stocks are overvalued. When he buys things with cash, he thinks his stock is undervalued. When he buys back his own stock, he thinks his stock is undervalued. When he buys things with stocks instead of buying it with dollars, he believes maybe his shares are overvalued. Now, is that true? I don't know. But that was a very interesting nugget that someone gave me while sitting in the press box many, many years ago. So here's the thing. Works right out the way. Somebody asks about dividends. Why don't you pay dividends? Warren says he doesn't believe in double taxation. The company is taxed on the earnings and he gives it to the shareholders and the shareholders, they pay another tax on their dividends. So that's like double taxation, right? So Warren's not a big component. He says, I much rather give you more value by buying stocks when I believe they're undervalued, buy our stocks when I believe they're undervalued. Now, how does Warren figure out our stocks are undervalued or whatever? We don't know. But it could be assumed that he's using a discounted cash flow model. How do we decide the value of a company? We look at the EBITDA, we look at the multiple, we compare you to company comparables and we come up with our future assumptions of what you would do. Look at your future growth. This company is growing at 5, 10, 20% rate and it has 5, 10, 20% rate of growing in the future. And you can kind of date it back to say, hey, well, this company today should be trading at this price. Is it trading at this price or not? If it's trading below that price, then it's seeing it's having value. If it's trading for all that price, it seem to be trading at a premium. You don't buy. They would gain by low and sell high. But how does our brain do it? We buy high because when a company is high, the news is good. Everybody's talking about it. All this company's just done this always blah, blah, blah. Everybody loves to buy it. Then when the news goes bad, everybody loves to sell it. So these fundamentals are very easy to be said, but it's hard to be heard. On set again, easy to be said, but hard to be heard. What I mean to say about that is that, hey, guys, look at the company and look at the financials and look at the balance and cash flow and income statement and evaluate the company and see what the company value is and look at the shares outstanding, then you should come up with a share price. And if that share price is $50, you go to the public market, you see it trading under $50. That meaning that this company is trading below its value. Right? And hey, you're getting good value. You can go out and purchase the company. Easy said, but when do we see this happen? When the companies are trading below their value or when companies are tanking, the news is not good. The news is horrible. The world is coming to an end. We have debt ceiling. We got a pandemic. We got failure of government closing. We didn't pay our bills. Credit rate and decrease.  But guess what? The financial media loves to speak about it because it is what people like to hear. If I made a video right now and put it up on YouTube and made a podcast and I said five reasons why the US economy is going to do great in 2023 versus if I made the exact same content and said five reasons why the US economy will collapse by the end of this year. Everybody is going to tune into the five reasons why the US economy will collapse because people like to be scared, especially the financial news and media. People want to hear good stuff about all the economy is going to know they like to be scared. They turn the TV up and see what's going on. It's a countdown to the debt ceiling. It's a countdown to the default. It's a countdown to coronavirus cases. It's a death calendar. It's a death calculator counter on CNN at the peak of the pandemic. Why do you show that? Because we love to be scared. We love to be feared. We love to, oh my God, I need to pay attention to what's going on. So the thing about it was here's one of the things he spoke about on a financial end that was very intriguing. He said everybody spoke about banks. He said he would love to own banks. I'm thinking at one time they own a bank, but they had to get rid of the bank in 10 years. So he said he loves banks. He loves the idea of the finances of a bank, but he spoke about Berkshire being his own bank. What does that mean? The insurance business. The insurance business does not, is not predicated upon stocks going up or down. Right? I mean the insurance business, I mean not stocks, but economy, economic corrosion. Economy is doing bad. Insurance business is pretty good. Economy is doing good. Insurance business is doing pretty good. Economy is going sideways. Insurance business is doing pretty good. The insurance business stays consistent, consistent and consistent, ladies and gentlemen. So with that being said, that's their bloodline. They don't have to worry about employees and customers and things like that. Because guess what? Every mom, no matter what the economy is doing, we're all going to have car insurance, homeowners insurance, life insurance, healthcare insurance, some type of insurance. And that's a good business to be in because every month that you pay your insurance, this money is going to warn. He can take that money. And I think he owned their own Geico and other insurance companies. They can take that money. And once they have that money, they can go out and invest that money and go buy another company and go do this with another company and go do that with another company. Right? So that's the insurance business that he spoke about. They're creating and have all this float capital. He's sitting on $135 billion, if I'm not mistaken, that was in cash. Think about that, $135 billion. What is, I don't know, if you just threw that in the savings accounts, that's millions of dollars you're going to make annually just from your savings account, money sitting to the side. Also, Berkshire Hathaway is in the top 500 companies in America. Meaning it's an index fund. What does that mean when a company is an index fund? Every time you and I go purchase the index fund, you put money to your 401k that follows money into an index or whatever and invests into the S&P 500. Some of that money is going to Berkshire Hathaway. So think about how big is the actual stock market. Every time you invest, you're sending some money straight to Berkshire Hathaway. In return, they can sit on the capital, wait, make a big mammoth investment into a new company and those type of things. So also, I wanted to speak about another bloodline. He has Bank of America, Apple. He said, I don't know what Tesla would be, but I know what Apple would be in five years. Apparently, they're pretty bullish on Apple. So Apple is a big holding. Another big holding is Oil. Also, they're on Petronium. He didn't speak a whole lot about it because it's a public and traded company. But he said that, hey, they believe in it. They think they got great management and they had great position in the Persian Gulf for oil. So I was very surprised to see that. Oil had an amazing year in the summertime.  The thing about oil all kind of reminds me of gold. Well, it is a black gold. And what it does is, the money and the economy is going down. I mean, it is just a spike. One summer, oil consumption will spike.  Maybe not this summer, but next summer, two summers from now, oil will just shoot up. During the pandemic, oil prices were in the dumps. People wasn't traveling. The demand of oil was going down as the world was on lockdown. But last year, 2022, in the summertime, oil had a crazy spike towards the end of the year, tailed off. And now it's telling off beginning of 2023, but they have a large holding. So some people, that's one of the things I've looked at. I've always been a big component of owning Berkshire Hathaway. I mean, heck, I better. I know people at Berkshire, traveled to Berkshire, Omaha so many times. You know, I got an on the stop. But the thing about I've always been concerned with the new era, the new regime, I see this coming into place. I think his name is Ajata. Ajata is coming in there being, they're coming into place. And then you're seeing Greg Abel come into place. So that's like the new era that's going to be the new era, the new face of Berkshire Hathaway. And my concern is, if Buffett passed away, you know, what would this new era do? So they say, hey, they got a strong bloodline of insurance. And they said insurance company is better than banks. And they said they would actually own a bank, but because of the regulations, they can't own a bank. So also they got a very big position in Apple and in oil. So if you didn't want to invest in the Berkshire, but you want to invest into the things that Berkshire is invested into, have your public portfolio mimic them, you're probably going to have some Occidental oil, some Bank of America and Apple. That's a way to invest around Warren Buffett and instead of investing with them. If you're like me, who's concerned with if news come out today and say Warren Buffett passed away, what would happen? Like what would that, what would that do to the market and the economy? Because we all know even though Warren and Berkshire has strong finances, we know that we know the market doesn't trade off of finances and fundamentals. The market trades off of emotions. Everybody would be emotional and say, oh, the golden era is over and done. That's the things that makes me scared and things that maybe we want to look out for. But yeah, in true fashion, Warren Buffett said, don't be worried, never bet against America, never bet against America. And to keep investing and Charlie Munger to quote him, he just said, just hold the freaking stock. And I'm saying the word freaking to, I don't want to be explicit on this broadcast, but he would just say, and hold the stock. He believed Berkshire Hathaway was a good company. He's 99 years old and never bet against America and keep going with the tailwinds of America. Even though we just went through a banking crisis, fear will always be contagious. And when people become fearful, people like to sell things, run for the board, put all that money in the cash, and that's the time for you to go out and invest. So when Warren has a bunch of cash from the sidelines, that's the indication of bad time to come. Weren't you making acquisitions? Weren't you buying? So very interesting. Well, ladies and gentlemen, my name is Prince Dykes. That's going to conclude today's episode. Thank you guys and girls for turning into the Prince of Investment. And to the next video podcast, cartoon or whatever else craze you see me doing around the globe. Y'all already know my name is Prince Dykes. Peace, be safe, I'm out and thank you.


What's up everybody, Jason here with jasperyscasebrakes.com. This is the last filler to unlock 10 spots in triple threads baseball, which will be after the dinner break But we'll give away the 10 spots after we do a 2021 mosaic quick pitch pack break number 11 random teams So first we'll do the break randomize the customer names and teams distribute the hits out Then at the end of the break we'll take all 30 customer names and randomize them the top 10 One third of you guys will get into that break a little bit later tonight so let's Roll the dice and we've got ourselves a three or three six times one two three four five and six So there you go six times Kevin down to Jonathan. So there you go six six this is for the teams now one two three four five six Arizona Diamondbacks, whoa None of the San Diego Padres All right six six So you're gonna stick to what you got guys, uh, let me quickly just alphabetize it Just so you guys your team's really quick All right Here we go the next quick pack to them. I don't know if we actually hit an autograph yet on these packs, but I guess we'll find out braily marquez chris buick and michael franco All right. All right. All right quick pitches are probably the quickest pack for those we do All right now last 10 spots being given away here guys roll it three and four another lucky number seven one two three four five six seven bow seven Kevin's in jack you're in Kevin Kevin Kevin Jonathan Stephen Kendrick Jonathan Jonathan and jack there we go Top 10 are in congratulations guys coming on a little bit the break it's up


So it's time once again to come back to the right-hand rule for the magnetic force on a current carrying wire. We figured out our equation before to get the magnitude, or we could use the cross-product. But if we find the magnitudes, we still have to find the direction using the right-hand rule. And just like we had a right-hand rule for individual charges moving in magnetic fields, there's one for current carrying wires, which is very similar. If I go back to my conceptual view, we want to remember that the current is defined as the direction opposite that the electrons are going. It's as if it was positive charges flowing in that direction. Now when we looked at our conceptual view, we described it in terms of the force on a negatively charged particle moving in the negative direction. But now we want to describe it just in terms of our current. Well, one of the biggest standard accepted rules, one of the biggest ones that's used here, sort of looks like this. Your thumb doesn't represent the velocity of the charged particles anymore. It represents the direction of the current. So whether we look at that at the hand or we look at it in terms of the wire, your thumb is going to point along the wire in the direction that the current is flowing through. Our forefingers still represent the direction of the magnetic field lines. We want to keep those nice and flat with where our thumb is. And once again, the palm of the hand is going to point in the direction of the force on that wire. So we've got our current, our magnetic field, and our force at right angles to one another. Here's just another example showing you from another perspective. Again, your fingers are pointing along the direction of the magnetic field. And your thumb is pointing along the direction of the current. One of the nice things about this particular diagram is it's reminding you that that doesn't have to be at a right angle. There can be some angle theta there in between the magnetic field and the direction of the wire, which has the current flowing out along your thumb. You just need to make sure that you've got it in a nice flat plane. And then the palm will once again show you the direction of that force vector. You're still going to need some practice. So take a look at the next video clip, which gives you several different examples of using your right hand to figure out the direction of the force on a current carrying wire.


Welcome everybody. The basic idea is no while statistical mechanics is very big in physics department, in chemistry department sits across India hardly taught. And my motivation came from once I was visiting the central college in Bangalore University and I was going through the syllabus. I was giving some valedictory lecture. Then I went to the syllabus. And they have statistical mechanics irreversible found dynamics. So I said what? But they say they don't have anybody to teach it. And then I tried to talk with physical chemistry one quantum chemist there and they said you know that they have never been taught and it is difficult for them to pick it up. So then it occurred to me and I noticed one thing in undergraduate colleges that Indian students not that many IITs and other places but across the board in the state universities and even JNU they like to read books written by Indian authors. That is the very important observation. So I said okay we don't have a single stat-mark book in neither by physics nor by chemists really in the sense of a textbook. So I already had written two books and this was a Herculean task to get this done and involve a lot of help from the students and it took a very long time. So this is the standard book that we read all read. The first edition now it is the I think second or third edition and this is the statistical mechanics by David Chandler. So but this book is somewhat different in the certain sense that I will go through though the course will be kind of a mixture and not from any one book. And it I would like to have put an elementary here but I thought that will lessen the appeal because we will do many things which are not elementary okay. And I will go on doing it for some time and I think those who are present here will enjoy it and it will take you through many things which usually you don't think about. Now let me start by saying the following thing that when you go through the take out the textbook you know when you go back you can take the Moore, Walter Moore or Castellan or Glaston or even Atkins. Atkins of late has done some amount of more modernization but if you take the undergraduate textbook you will see there is a electrochemistry, there will be binary mixtures and the phase eutectic diagram. You have liquid molecule liquids like water ethanol your polymers and then you have the liquid solid transitions huge number of things that you study in undergraduate physical chemistry almost except spectroscopy and atomic structure all the chapters essentially comes as a phenomenology. For example take the ionic motion in water you have read and about the Solvenberg model that means the water forms an ice like structure and that reduces the mobility of lithium ion. Again and again that kind of a structure or structure breaking and structure making when you do binary mixtures we say okay this is structure breaking and this structure breaking like water ethanol or water DMSO. And they have depending on the whether they are structure breaking or structure making you have a composition dependence of viscosity which have this curve going up with composition going down. I am spending so much time on this essentially to bring home the point that what we read is essentially statement of facts they are observations and they are hardly any explanations there. But that does not help you you can memorize the fact and you will forget what stays with you is you have certain amount of understanding because then you can use it later. This is one that I will come back this particular slide that because we hope to do quite a bit of that earlier part we will do non interacting systems then we do interacting systems. Ultimately we want to touch on this very important thing for a chemist particularly in modern days of nanomaterial synthesis and understanding you know you cannot give a really meaningful lecture without knowing certain amount of see I hear lecture after lecture and in my because the solution and structure chemistry. And basically they know little bit of Ostwald step rule Ostwald ripening but they do cannot explain many faculty member a prospective faculty members do not get selected simply because they cannot answer very simple questions. So you know we look for faculty we look for students who can explain things okay. Now I will do something little bit which is very important and profoundly important see when you do a quantum mechanics. We start with black body radiation and planks introduction of quantum and quantum theory. Then you go to Einstein for electric effect then we go to Niels Bohr's theory of atomic structure electrons stationary orbits. Then comes the very important the broadly wave particle duality. Then it was Peter Debye who said there is stupid to talk of silly actually talk of wave equation wave particle duality or waves without an wave equation which presumably prompted Schrodinger to do his work. Then of course Heisenberg and all these things and Dirac. So these evolution of quantum mechanics is a folklore. Most of us knew it when you are doing BSc and by MSU is certainly new. Such does not exist in the historical evolution of statistical mechanics though it is very well known and you all know quite a bit of that how did it start. So I will do a little bit of the historical evolution of statistical mechanics which will allow you to think and put the things in the perspective okay. So it is all started around 1850 there are several people though Maxwell who gave the clearest exposition they were thinking of the distribution of velocity of a gas particles. The very idea that people were thinking of distribution was quite unusual because that time it was of deterministic which you again know from quantum mechanics. Everything was kind of deterministic perspective that people were doing. Maxwell I am not going to go into very detail because I will just want to give you the history now. Maxwell came up with his famous Maxwell velocity distribution which is the Gaussian distribution. So now suddenly people like Maxwell proposed that you may not know. You might not know the velocity of an individual particle. It does not make any sense anymore because when there are so many particles moving around instead of that we should be able to talk of a velocity distribution. And this is the normalization constant. So this distribution we all know is the Gaussian distribution. There is this path velocity if it is vx and then positive and negative and this is the pv. Now that impressed Boltzmann so much that all his life rest of his life he carried that paper of Maxwell with him. So he was obsessed and he realized that this distribution is a very fundamental way can explain many things in nature starting from very corpuscular. It was called corpuscular view of matter. And so Boltzmann then went on trying to develop theories and Boltzmann suffered enormous amount of criticism. Maxwell died early. So this distribution related criticism was he did not quite suffer as much as Boltzmann suffered. To the extent he probably committed suicide and that is the main certain mystery there in 1906. Another very important thing happened around that time which all of you know is the Van der Waals equation. Why it is so significant I am now trying to tell you. And I am again I am repeating that I am giving you right now the history how statistical mechanics was developed. And very important to establish the history and the chronology of evolution. Van der Waals came up with that equation his famous equation and which is you know p plus a by v square v minus n b equal to RT. Now what was interesting and very interesting was that Maxwell and Boltzmann they already derived the equation from a molecular view a particle view the equation pv equal to RT. The universal gas law. You know if you look at that that was a very significant we cannot over emphasize the importance of that. The way they derived that because Maxwell that a particle though Maxwell is the whole kinetic theory of gases you do not see any name. Because we are all done by Maxwell maybe little bit by Boltzmann. Similarly when you do quantum mechanics all the way up to hydrogen molecule you do not hear any name. Because you are all done by Schrodinger everything was done by Schrodinger particle in a box harmonic oscillator rigid rotator hydrogen atom hydrogen molecule.  And I was just impressed that here is a guy and he did not do the way you do quantum mechanics. Very important to know that very rise and loss in the first edition did the way Schrodinger derived Schrodinger equation. Not the operator thing that you replace del square by d2 dx. No that is not the way it is. It is very very important that you know the history and the chronology because that gives you much much deeper insight. Van der Waals had those terms pressure P but Van der Waals introduced one more thing which he did not have. He had Maxwell did not have Boltzmann had ledger and I will come to that the size of the molecule. Remember this one more everything. So if I do not have if I take V going to infinity then I get PV equal to RT. So Van der Waals introduced the interaction which is A and this size which is B. Yes it is some approximate way and we all know the criticism of Van der Waals equation. But this equation was a kind of a thermodynamic equation. But it was u it used Maxwell's essentially method that the particle is going to hit the wall and it is drawn back the way we all know the derivation of Van der Waals. So interaction when atoms and molecules were beginning to come though classical mechanics and continuum people were quite a bit against and very critical of the Maxwell Boltzmann approach. Van der Waals was a thermodynamic equation. It was an equation of state which was verified in a very spectacular way by law of corresponding states. I will talk a lot about law of corresponding states. The beauty of that and the universality of law of corresponding states the whole critical phenomena originated from law of corresponding states. But that that again can wait. Now comes this Telofeginius Williard Gibbs. He realized something very very interesting. He was absolutely again obsessed with Van der Waals equation state and he set out to develop a statistical mechanical the approach. Now again a bit of history Maxwell did with ideal gas law. Boltzmann now tried to put in interaction between atoms and molecules. That there is a size and he assumed heart sphere. He did not have an ideal gas law does not need an interaction. But here there is a ballistic collision between two particles. So Boltzmann introduced this important important the collisional event that one molecule going and hitting another molecule. And then getting deflected. This scattering event or binary collision event was taken into account by Boltzmann. But Boltzmann could not go very far. What Boltzmann tried to do the evolve the distribution function of such event of binary collision. Quality distribution that one particle at one position has at position r1 as velocity v1. And another particle at position r2 as velocity v2. This joint quality distribution was a very formidable thing that Boltzmann tried to tackle.  One is that a molecular chaos. And when Boltzmann made he was heavily criticized. And remember the whole concept of entropy in a molecular definition A, C, Q, L and W that came from Boltzmann. Wherever there is a statue of Boltzmann I saw in the University of Vienna at Austria on his mast that famous equation is written from which so much flow. So much further was developed. So it is important to realize that Boltzmann tried to develop a time dependent approach to statistical mechanics. He had a molecular definition of entropy. He tried to go as far as he could. But he could not go very far. There are things are extremely complicated. On the other side of the Atlantic he was great fan of Maxwell and Maxwell was great fan of Willard Gibbs. And Willard Gibbs looked at very carefully the approach of Boltzmann. Then he realized one thing that even if I could solve what Boltzmann was trying to do. Boltzmann couldn't go beyond two particles. But we are in a liquid or in gas phase we will have many particles. They have a number. At least we need to discuss in a locally few hundred or thousand molecules interacting. So Boltzmann approach as Boltzmann tried was too ambitious it will not work. But what is the brilliant thing Willard Gibbs realize that if I have a glass of water. Then that glass of water and I put water into another glass that is standing there at equilibrium. The property with a density one number cc specific in our old unit one. All these properties are time independent. They are time independent. They are not time dependent. But Boltzmann tried with a q from Maxwell develop a time dependent. Which ultimately after a hundred years bore enormous fruit but that's much later. Willard Gibbs realized that then I should be able to develop an equilibrium approach. That means I don't have to solve the equation of motion. Boltzmann tried to solve Newton's equation couldn't do even now nobody has been able to solve the three body problem. And Gibbs realized that then I would be able to do something if I assume I create many many many many glasses of water. Millions in my mental in my mind frame. And then at a given instant all the water molecules in one in each glass are different positions. They are moving at different velocities. They are a little bit of different positions. So he realized if I now go back kind of Maxwellian way of thinking that if I can think of a distribution. An equilibrium distribution not the time dependent distribution which Boltzmann tried and couldn't do. I can do an equilibrium distribution of my millions and millions of glasses. Each of the glass in each glass the water molecules are occupied different positions. Then I should be able to then I'll be able to if I have a distribution of the locations and positions of the water molecules. I should be able to use Boltzmann distribution. Boltzmann distribution essentially e to the power minus beta e what is your Hamiltonian. So now he combined Maxwell Boltzmann and his brilliant mental construction. So we all know Boltzmann. So now he say if I have this millions of glasses and with water molecules millions of them. Each of them my at a given time my water molecules are located differently. Each of them different energy but that essentially obeys this kind of distribution. Then I'll be able to calculate the properties. So he avoided and is extremely important that we let gives avoided the construction of Boltzmann. He avoided by this brilliant which is called ensemble picture. He avoided the whole difficulty Boltzmann faced. And we let gives is considered along with Boltzmann the father of statistical mechanics.  Boltzmann did micro canonical canonical grand canonical all these things are all done by we let gives. And why we let gives did that? One thing you should really know when you are doing science that we are no different from Carpenters in certain sense. Science is a very pragmatic thing very practical thing. It is nothing to do with kind of philosophy. Science is science we are great teacher Shadhan Vasu who used to come like this with the patent disorganized and he was a wonderful teacher. Which that we had way of those days could video his thing and he was talking of free will and all these things in context of Boltz theory. And he was famous line we always to say that science is science philosophies philosophy and science is not philosophy. So we let gives really did something lot of philosophical discourse went into it but he had nothing no philosophy in mind. He just wanted to calculate. He just wanted to calculate he wanted to calculate this thing. He wanted to calculate van der Waals equation states and he wanted a formulation that starting with atoms and molecules starting with intermolecular interaction. Can I how do I go there? Not the heuristic derivation of van der Waals. And on top of that you know the van der Waals had this loop which again Maxwell corrected it called Maxwell tie line. Getting the correct pressure out of van der Waals. So these 3 guys or 4 guys are just hand in gloves they together created the whole statistical mechanics. Now so now I have said that it started Maxwell but I should emphasize again Maxwell was not the person not the only person. Some other people also had the Maxwell distribution but Maxwell gave a very clear exposition. Maxwell motivated Boltzmann and Boltzmann went to develop the solved Newton's equation for many body problem. They introduced the definition of entropy and Maxwell Boltzmann couldn't do beyond binary collision. Even that he couldn't do very well. Then Gibbs trying to develop and understand van der Waals equation and phase diagram and phase transition. Van der Waals is again the guy who did the first theory of interface surface tension. All these things were done by van der Waals which will do a little bit of that. Another very important area that you have faced in your DSN MSC is surface phenomena. But again that was not done in a very systematic way in your undergraduate or MSC. But this is a beautiful subject the surface phenomena and surface tension which is again connected with nucleation as some of you know a granular theory. Now Einstein played amazingly role. In many many statistical mechanics he played an outsider role. He created the theory of Brownian motion which we used to do the diffusion. Einstein contemporary when they are doing the great work he was senior to Einstein. Around the same time Einstein came up with what is called the theory of fluctuation. Einstein realized one thing that many probably from a Boltzmann the thing we call specific heat. The thing or conductivity, viscosity these are all what today's language we call response function. Like when you get the first thing we got the rock from the moon what is the thing we calculated. What is the thing we not calculated we measured is a specific heat. First thing that was measured was density and specific heat. Any rock that's what we do. What is the specific heat it's a response function. What is the conductivity it's a response what is the isothermal compressibility that is a response function. Einstein realized that response functions are actually natural property of the system. They are mean square fluctuations. If I have energy energy in a system interacting with surrounding media is always fluctuating moving up and down. You now take the average and then you can take the delta E energy flag different at any given time and then you square it and take an average over a long time that is your specific heat. Then take the volume and take the fluctuation of the volume that gives you the isothermal compressibility. This was done by Einstein that you know that's why he really showed the path in certain way that what how to calculate the things gives was trying to develop in a certain sense. So just like as I said in quantum mechanics all of us know very well the tree of development. In statistical mechanics however I have not seen the tree of development not even the great book of Tolman. Or any of the books that we say. So this pathway that I traced here is the way statistical mechanics was developed. And that is not the way it is told in the books but that is the way it should be told. When you try to explain statistical mechanics the beauty of it is through these things.


Hello, everyone. Welcome to this introduction to integration and anti-differentiation. Recall that up until now you have been given a function and asked to find its derivative. Now you are going to be given the derivative and asked to find the original function. This process is called anti-differentiation. Differentiation and anti-differentiation are inverse operations of each other, just as addition and subtraction are, multiplication and division are, and squaring a quantity and taking the square root of that quantity are inverse operations. Anti-differentiation is the process of finding the set of all anti-derivatives of a given function. You are going to notice throughout the problems that you are always asked to find an anti-derivative, not the anti-derivative. There's a reason for that. In general, and we read this that you see on the left side of the equal sign, as the anti-derivative of f of x dx is equal to capital F of x plus c. Let's dissect the different parts of this. F of x is what we refer to as the integrand. Think of another term you have learned in mathematics, the radicant, which is the number underneath a radical symbol, a square root symbol for instance. The number you are taking the root of is what we always called the radicant. Here the function of which you are taking the anti-derivative is called the integrand. The dx that you see there is what we refer to as the differential. It indicates the variable of integration. Capital F of x is the anti-derivative. Finally, the plus c is our constant of integration. Remember how we said before that differentiation and anti-differentiation are inverse operations of each other. Therefore, it will be true that the derivative of the anti-derivative of f of x dx simply is f of x. In accordance with the fact we know differentiation and anti-differentiation are inverse operations of each other. The derivative and the anti-derivative essentially undo each other. The power rule for integration therefore states that if n is an element of the rational numbers, remember q is the mathematical symbol for the rational numbers because q is for quotient and a rational number is a number that can be expressed as a fraction, as a quotient. So if n is an element of the rational numbers but n cannot equal negative one, hopefully it makes sense as to why, we'll talk a little bit more about that in a little bit, then the anti-derivative of x to the n dx is equal to x raised to the n plus one power divided by n plus one. So you're adding one onto the exponent and then dividing by that new exponent plus c. This is the rule that hopefully you figured out for yourself through our introductory activity. A couple things to note though. Consider the anti-derivative of x to the negative one dx which can be rewritten as the anti-derivative of one over x dx. You cannot use the power rule for integration on this because if you add one to the exponent and then divide by that new exponent, you end up dividing by zero which we all know you cannot do. That means we need to come up with another way to get the rule for the anti-derivative of this function. Thinking of the fact that derivatives and anti-derivatives are inverses of each other, can you think of a function that you take the derivative of and get one over x as the answer? Hopefully you thought and remembered that if you take the derivative of natural log of x, you get one over x. Therefore, the anti-derivative of one over x dx is the natural log. Now we do say it's the absolute value of x. There is a reason for that which we will investigate in one of the later lessons, plus c. This right here becomes the first rule you need to memorize, one of the special anti-derivative rules. The anti-derivative of one over x dx is natural log of absolute value of x plus c. Let's consider exponential functions with the number e. Remember that the derivative of e to the x is e to the x. We talked about that it's the only function which is its own derivative. Now let's think about anti-derivatives though. Can you think about what the anti-derivative then of e to the x dx would be? In other words, of what function is e to the x dx, the derivative, or what do you take the derivative of and get e to the x as the answer? Hopefully you figured this one out. The anti-derivative of e to the x dx is simply e to the x plus c. This is the second rule you need to memorize. I like to think it's a pretty easy one. e to the x is a very very special function. Again it's the only function which is its own derivative. It's also its own anti-derivative. What about exponential functions in general though? What if we want to discover a rule for the anti-derivative of e to the x dx? e would be a number. So think what function do you take the derivative of and get e to the x dx as the answer? This one's a little trickier. You have to think a little bit about this and be a little bit more creative. We find that the anti-derivative of e to the x dx is 1 over natural log of a times e to the x plus c. This is the third rule you need to memorize. Let's look at a little proof as to why this is. Remember that derivatives and anti-derivatives are inverses. So if we were to take the derivative of this answer, of the anti-derivative, we should get that integrand back again. That's one of the great things about anti-derivatives that we didn't have with derivatives. A way to actually check our answers. So let's take the derivative of this and see what we get. 1 over natural log of a, that's really a number. It's a numerical quantity so that's our coefficient that would just remain as we take our derivative. Now we need the derivative of a to the x. Think back to your derivative rules. The rule for derivative of a to the x is a to the x times the natural log of a. But look what happens. The natural log of a's cancel out leaving you with a to the x, which is our integrand. As you work through anti-derivative problems on your own, oftentimes you will have to rewrite that which is to be anti-differentiated by using some algebraic manipulation. For example, if we wanted to do the anti-derivative of 5 over square root of x dx, the 5, just like a constant when you're doing derivatives, can simply come out in the front. We're going to bring that square root of x up from the denominator and rewrite it as x to the negative one half. Then we can apply the power rule for integration. Similarly, if we wanted the anti-derivative of cube root of x times the quantity x minus 6 dx, we're going to think of the cube root of x as x to the one third and distribute it over that quantity. And we arrive at x to the four thirds minus 6x to the one third. Once again, you then apply the power rule for integration. Finally, one last example. If we wanted the anti-derivative of x to the seventh plus four over x square dx, we're going to apply the laws of exponents and rewrite this as x to the fifth plus four x to the negative second. Very similar to how you would have worked with it if you wanted to take a derivative.


psychopathy? Is it all about Dr. Lekter from Science of the Lambs and Norman Bates from Psycho? How about Patrick Bateman from American Psycho? Think again. A psychopath isn't a crazy person from a movie.  Have you ever wondered if any of your friends could actually be a psychopath? Or is Hollywood's definition of a psychopath more appealing? Contrary to what many people think, not every psychopath is a killer or a criminal. They have a personality disorder known as psychopathic personality, which falls under the antisocial personality disorder category in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. This disorder is characterized by lack of empathy, lack of remorse, and antisocial behavior. Hollywood loves to portray psychopathy as madness to ensure a box office hit, but in everyday life, that's not necessarily true. When it comes to the likelihood of having a psychopath in your life, the odds are not in your favor. According to Dr. Paul Bobbiak, one in every 100 people is likely to have psychopathic traits and the probability is even higher as you go up in the office food chain where you'll find one among every 25 managers and executives. The real reasons behind psychopathy are usually narrowed down to genetic factors. Yes, many criminals are psychopaths, but the majority of psychopaths are not involved in criminal acts at all. Here are 10 key traits of psychopaths. One, lack of empathy. A psychopath simply cannot feel what everyone else feels. They understand your feelings, but they don't feel them. Even if you're crying your heart out over the death of a loved one, they'll show compassion only to please you, not out of true emotional empathy. Two, manipulate in this. Always knowing the right strings to pull and the right buttons to push, psychopaths use deception to cheat others into thinking, believing, or acting in certain ways. They only focus on personal gains with no concern whatsoever for how others feel. Three, irresponsibility. Impulsive behavior and irresponsibility is their lifestyle. A psychopath would never admit to their mistakes. In fact, they turn the tables against whoever accuses them of anything so that the accuser would think again and even feel guilty about their complaints. Four, narcissism. Psychopaths usually view themselves as smarter, more powerful, and of more worth than everyone else. They have an extravagant, almost theatrical self-perception, thinking that the world revolves around just themselves. Five, pathological lying. Psychopaths tend to lie, lie, lie, and lie even more. Their lives are spiderwebs of lies. This ranges from moderate levels to high levels of lying. Six, superficial charm. Smooth, charming, and attractive, psychopaths aren't afraid to do or say anything they like. That absence of embarrassment attracts others as it can be misperceived as high self-confidence.  Seven, lack of remorse. Psychopaths don't feel guilty for the suffering and pain they inflict on others or for their actions in general. Eight, pronuss the boredom. Forever bored. Psychopaths have an exaggerated need for a adrenaline overdose so they're always looking for excitement and thrill. Nine, bullying. Psychopaths are usually abusive towards those that are not of much benefit to them. This can be subordinates, elderly people, children, or in most cases, animals. They like to exercise their power over other fragile beings through bullying, and they may shoot hurtful words at any time without warning. Ten, sucker for power. They have an excessive need to exercise power and control over others. In other words, they are control freaks. Everything must go the way they want it to. And that's it for the ten main traits of psychopaths.  Tell us about your experience below. If you enjoyed this video, be sure to follow our Tumblr, Twitter, and Facebook for more content, and don't forget to subscribe. Thanks for watching and have a wonderful day.


Hi everyone, I'm Richard from Delegate on Paris. In this video, I'm going to present our work on how to quantify information literature in code-based masking. This is a joint work with Sivan Kiyee, Claude Garlay, Cézanne Mélajev and Jean-Luc Danje. In this talk, we first give an introduction of code-based masking. Then we present our code-based theoretical leakage quantification. We apply it to the polynomial masking, which is based on Cézanne Mélajev's secret sharing, and show how the redundancy in masking can only increase the situational leakages. In situational analysis, a sensitive variable X is leaking in certain forms. In this case, leakage can be viewed as a combination of some function on X and a noise on N. Commonly used thinking is assuming variable noise is the additive of white Gaussian noise. So to protect the cryptographic implementation, one of the most well established contemporary masking. In particular, the masking provides provable security, and it is in the algorithmic level that it costs, increasing critically with the security order.  In Cézanne Mélajev's ancient, it's in coding as follows. The first share is constructed by XOR with the secret, the sensitive variable, and all other masks. And the shares are random masks only. As we know, the Boolean masking can be generalized into the code-based masking from a coding theoretical perspective. Let Z be K pieces of information, and let Z equal to XG plus YH, where X has K pieces of information. Why has T masks and ZN be encoded into Z with ancients? G and H are to join two matrices of linear code C and D respectively. So we note that the only condition in code-based, in generalized code-based masking is that C and D has only zero codeword in the intersection. In addition, if N equal to K plus T, there is no redundancy, like in IPM and direct sound masking. Otherwise, if N is greater than K plus T, the masking is redundant. Here we give two examples, the Boolean masking and the inner product masking. On the left, the Boolean masking is simply encoding with holding XOR. The G and H are binary matrices with holding 1 and 0. On the right, in IPM, the first share is constructed in the product operation involving AFI. As we show AFI in the first column of H, comparing with the Boolean masking, holding 1 column is changing. And we can recover the Boolean 1 by setting all AFI equal to 1. So the Boolean masking is the special case of IPM. Next we'll present a brief history of code-based masking. Notice that there's references marked in blue are the first proposals. The first observation is that the liquid screening and the polynomial masking were proposed in 2011. And the original IPM was in 2012. At last, the most general case was proposed in chess in 2020. In this paper, I will focus on this general case and show how to quantify the information leakage. The connection between above masking schemes are showing bigger three. We highlight two groups. First thing on the left, we have a red shadow, including Boolean masking, inner product masking and liquid screening and also direct sunlight. They all have no redundancy. On the right, we have a polynomial masking, which is based on Shamian's secret sharing. It can be configured with redundancy in a bleach-free context. For example, two natural questions that raise how to measure information leakage in different schemes. And secondly, how to choose the optimal parameters or optimal code for each scheme. Before we move into details, we call some definitions and the transformation. The first one is the due distance. The due code, denoted as DPEP, gave a linear code D. The due code is that each code of each codeword array is orthogonal to all codewords in D. We also have some subfiant representation and code expansion, by which we can extend a linear code from a bigger finite file to a subfiant F2. Next, as a well-known notion is called Witte numerator, which denotes a linear code to Witte polynomial. We call it D of parent N, KD. It's Witte numerator as a follow-up. The coefficient of BI is the number of codeword of finite I. In particular, BD is called the case number of D. For instance, for the linear code 844, we have a B0 equal to 1, B4 equal to 14, and the B8 is 1. In addition, we can define the adjusted case number of two linear code C and D. So B prime D is the number of codeword such that the codeword are in code D, but not in code C. Next, we show how to measure the equation in code base masking. In this work, we consider two probing models. In the bit probing model, each probe only gets one bit of information, while in the word probing model, each probe gets a little bit of information. The corresponding security order are TB and TW respectively. So in side channel analysis, the leakage function sends a beta vector into a real value, which are denoted as procedural linear function P. Then the numerical degree is defined as the maximum number of coordinates of beta, which is the coefficient of Z power I in leakage function P. And some examples are as follows for MSB and LSB in differential power analysis, which is deleted, commonly denoted as DOM. Z power I is always the only one coordinator of one. In the halfway leakage model, each bit appears only once and returns the sum. In both cases, the degree equals one. And the last example has the second order leakage or is the product of first two bits. It has a numerical degree equal to two. Then by using leakage function P, we can define the side channel leakage as L equal to PZ plus N with Gaussian noise. Then the problem is how to explode the leakage. In side channel analysis, the distinguish is to check whether the leakage on the different value of X are different. And to whether the variance is zero or not. Therefore, we can define the SNR as the ratio between the variance of information and the variance of noise as in convention. Taking hamlet leakage into consideration, we have PZ equal to hamlet of Z with power D for high order moments. Then it can be decomposed as follows as in quotient six. The first part as a term so with a numerical degree smaller than D while in the second part, always the degree is acting equal to D. So we have the following theorem for SNR in code base matching. So it involves the due distance D and the adjusted number B prime D, which is depending on both the code CMD. So it is consistent with the secret order improving model. Next from information perspective, the mutual mission between the leakage and the sensitive variable X is computed by two entropy. The total entropy HL and the conditional entropy HL given X given as follows. So, then we have the following theorem for mutual mission in code base matching. In equation 8, we have a mutual mission between L and X equals zero when the degree of P is smaller than zero, which is consistent with probing model, probing security order. And if the degree of P equals the due distance, the mutual mission is a link to the due distance and the adjusted number as in SNR. Visually, we industry to the impact of due distance and adjusted the key number as in figure four. In particular, the slope of the course in log log representation is equal to the slope and the vertical offset is a link to the B prime D. An example of four-bit cases of tuition or PM is showing figure five, the slope and the vertical offset as expected. We also propose a unified evaluation for more for GCM in which the side channel security can be characterized by the due distance and the adjust the case number. In addition, the optimal code can be given by maximizing the due distance D and minimizing the adjust the case number B prime D. Next, apply our approach to SS based polynomial masking. As pointed out in chess 2018, the polynomial masking is connected to the read the Sonoma code. The is code is defined by choosing a polynomial with all the equals smaller than T and evaluate it on public point. Then we can show the connection explicitly. The genetic matrices of G and H are as follows. In particular, each share corresponds to an evaluation in as read the Sonoma code. Next, considering an instance with solutions and the T equal to one, which is a first order secure masking. G and H are as follows for the sake of simplicity and also because of the equivalent of linear code we can set F1 equal to one. And the other two parameters are F2 and F3 are equal to F power G and F power K respectively. And the sharing is as in portion 10 where we only have one random mask U1. So by applying F2 for mutual information, we can evaluate a different code in SS based masking. Clearly, the black curves give the best code and the approximation in similar to a more accurate one is the noise increases. We give an exhaustive study list in table one different code can have various due distance and just the kissing number as shown in the last column. We give the best cases of code for 3-1 SS based masking and comparing of comparing with the state of that we show a systematic approach to find the best code in addition, we show that some parameters are the worst, the worst cases and not to recommend it for practical use. In particular, for the first time away in the streets is the impact of both called the CMD in the citron resistance of GCM. At last we evaluate the impact of redundancy in coding in code based masking. Again, we recall the sharing in 3-1 SS based masking. We have a one share for redundancy. We want to compare the information carrying in the share in the situation and into out of situation by using information. The results are shown in figure seven. On the left, we have, we show that three combinations of two shares have the same due distance and on the right, we give one instance of combining combination that has a smaller due distance. Two observations can be made. Firstly, solutions always carry carry more information than two shares and secondly, the secret is determined by the weakest, weakest combination of two shares and the internal crisis is determined by T out of N shares in SS based polynomial masking. A similar, a similar result is shown in figure eight for different codes and different combinations. Finally, we conclude our talk. So in this paper propose a coding strategic approach to quantify the side channel resistance of the code, the base masking. We use both ASOA and MI as liquid matrix and propose a unified framework for evaluation and for choosing optimal code in GCM. So our, our open source in GitHub available by using following links. We also highlight that we want to show how to find the best code by presenting detailed investigation on the trace of single no basis for code expansion from a big identified to basically, basically five F2 improve, improve on September 17. Just after so when come to our talk and please check our paper for details. Thanks for your attention. Please contact me if you have any questions.